C'est Matthieu qui m'a poussée à transformer ma curiosité pour le domaine de la logistique humanitaire en travaux de recherche. Merci Matthieu, merci beaucoup pour ton soutien depuis la minute 0, pour m'avoir donné ta confiance. J'ai appris énormément de ta persévérance et optimisme.

Thank you, Tina. You have been a great source of inspiration and challenge. It has been a pleasure to be part of your research team. Thank you also for all the opportunities you offered all along this way (Norway, the Triplex, Delft, …) All those experiences have been completely amazing and have shaped me as researcher and person.

Merci aussi à Mathieu Grenade, et donc la Fédération International de la Croix Rouge, pour avoir cru à ce projet et avoir joué le jeu. Spécialement pour l'accueil de toute l'équipe au Panama, qui a beaucoup contribué à construire ce projet.

Je remercie les rapporteurs et membres du jury d'avoir accepté et accompli cette tâche si critique. C'était un vrai challenge et plaisir de discuter avec vous tous. J'aimerais remercier aussi Arnaud Cabal (MSF), qui m'a ouvert les portes dans le domaine passionnant de la logistique humanitaire.

Merci à tous les collègues du Centre de Génie Industriel de l'IMT Mines Albi. Merci à vous tous pour tous les bons moments partagés.

Hossein, it was a pleasure to share this adventure with you, the best practitioner ever ;-)

Isabelle, tu étais l'âme du CGI tel que je l'ai connu. Merci pour ton amitié, pour avoir partagé ta joie de vivre, tu me manques.

Merci Nico… Gracies als amics i la familia que heu seguit aquest projecte des de la distancia. Sense vosaltres tot seria molt més dificil!

RESUM EN CATALÀ

Per una cadena de subministrament d'ajuda humanitària sostenible: caracterització, avaluació i suport a la presa de decisions Paraules clau. Cadena de subministrament humanitària, presa de decisions, planificació tàctica, gestió de crisi, sostenibilitat.

La cadena de subministrament humanitària (CSH) és un element clau per millorar la resposta davant les crisis humanitàries. Les organitzacions humanitàries (OH) han rebut pressions tant internes com externes que han conduit a una millora substancial de la gestió dels recursos (eficiència i eficàcia) durant els darrers anys.

Tot hi així, com que la diferència entre les necessitats de finançament i els recursos disponibles tendeix a créixer, i els mecenes demanen cada cop més transparència i justificació de les despeses, el coneixement i gestió del rendiment segueix essent cabdal. D'altra banda, la pressió de l'opinió publica empeny les OH a integrar els reptes de sostenibilitat, més enllà dels resultats econòmics.

A l'inici d'aquest projecte de recerca, gràcies als resultats de la investigació de camp, es van identificar les dificultats per considerar la sostenibilitat en la presa de decisions de la CSH. A part de la manca de coneixement generalitzat sobre què és la sostenibilitat i com mesurarla, alguns dels frens majors per planificar operacions humanitàries sostenibles son la manca de sistemes de suport per la presa de decisió i una cultura de sostenibilitat específica a la CSH.

La tesi aborda diferents aspectes per facilitar l'introducció de la noció de rendiment sostenible en la gestió de la CSH. En aquest sentit, s'han investigat tres pistes de recerca que han permès de desenvolupar un sistema de suport a la presa de decisió per a la planificació d'operacions de la CSH durables:

(a) Com es pot obtenir un coneixement exhaustiu d'una CSH?, La contribució proposada és una Meta-Model de la CSH, basat en la definició d'un sistema col•laboratiu, útil tant per a la investigació sobre el terreny com per al desenvolupament de sistemes de suport a la decisió.

(b) Què significa sostenibilitat en el context de la CSH? A partir de la recerca bibliogràfica contrastada amb la investigació de camp, s'estableix un marc per definir el rendiment sostenible de la CSH basat en la TBL (Tripple Bottom Line) que considera les dimensions econòmica, mediambiental i social.

(c) Com prendre decisions sostenibles en el context de la CSH? Aquesta contribució es basa en un algoritme d'investigació operativa que permet d'integrar el rendiment sostenible en la presa de decisions de manera interactiva. El procés de decisió estudiat és el de la planificació tàctica (selecció de proveïdors, mitjans de transport, magatzems) per la distribució d'ajuda humanitària en una zona geogràfica continental.

Les tres contribucions han estat aplicades a casos pràctics basats en l'activitat de la Federació Internacional de la Creu Roja (FICR).

RÉSUMÉ LONG EN FRANÇAIS

Introduction

Des Chaîne Logistiques Humanitaires pourquoi ?

La Chaîne Logistique Humanitaire (CLH) a pour but d'acheminer, au bon endroit et au bon moment, les articles de première nécessité appropriés aux personnes touchés par des crises humanitaires.

Ce qu'on appelle une crise humanitaire, est la conséquence d'un ou une suite d'évènements d'origine naturel et/ou humain qui menacent la survie d'un grand nombre de personnes.

En cas de crise, la première réponse vient toujours de la population et d'organisations locales. Ce n'est que quand les besoins dépassent la capacité du territoire que la communauté internationale se mobilise. Depuis des décennies, les Organisations Humanitaires (OH) telles que les ONGs et les agences des Nations Unies travaillent -souvent en coordination avec les autorités locales, militaires ou encore le secteur privé -pour porter assistance aux populations affectés par les crises majeures en suivant les principes d'humanité, impartialité et neutralité. Les OH sont capables de fournir de l'aide humanitaire à plusieurs crises en parallèle avec des CLH très réactives même si les ressources dont elles disposent sont souvent insuffisantes, le turnover des « humanitaires » est élevé, et les Systèmes d'Information (SI) utilisés sont plutôt rudimentaires.

Dans les dernières années on a constaté une poussée des besoins d'aide humanitaire. Les évènements (dangers) causent de plus en plus d'impacts due à l'augmentation de leur récurrence et magnitude. L'exposition de la population aux dangers augmente plus vite que descends la vulnérabilité, ce qui conduit à un incrément du risque.

La CLH, de plus en plus professionnalisée, a été identifié comme un élément clé pour garantir le succès des opérations de réponse aux crises humanitaires. Dans cette thèse on a commencé pour s'intéresser à l'évolution de la CLH pour mieux comprendre les défis à venir.

Evolution de la Chaîne Logistique Humanitaire

Si l'on considère le cycle de la gestion d'une crise (préparation, réponse, récupération, atténuation), les décideurs de la CLH ont tendance à focaliser les efforts dans la gestion de la phase de réponse. En effet, et en contraste avec la chaîne d'approvisionnement industrielle, le moteur principal de la CLH a été typiquement la réactivité et l'efficacité depuis le début (s. XX).

Cependant, plusieurs « échecs » dans la réponse à des crises humanitaires majeures on mit en cause l'approche. L'un des exemples le plus frappant est l'ouragan Mitch, en 1998, où les problématiques d'approvisionnement ont été suivies avec une couverture médiatique sans précédents. Dû à cette médiatisation, l'opinion publique et grands donateurs ont exercé une forte pression vers les OH qui a poussé à investir des ressources sur les phases de préparation, en amont des crises.

Dès lors, même si les fonds disponibles ont bien augmenté, les ressources sont toujours insuffisantes dû à l'augmentation des besoins. L'écart entre les besoins et le financement a tendance à se creuser. De plus, les donateurs exigent de plus en plus de transparence et de responsabilité dans l'utilisation des fonds. Par conséquent, la maîtrise de la performance de la CLH est un facteur clé et concerne tant l'efficacité que l'efficience des opérations.

Le terme « durabilité », ou performance durable, a été utilisé dans un large éventail de disciplines et de contextes, mais il a reçu peu d'attention dans le domaine de la réponse aux crises humanitaires. Cela n'est pas surprenant car toute CLH contribue à sauver des vies et à améliorer les conditions de vie de la population et donc ceci semble tout justifier.

Néanmoins, certaines OH se sont déjà engagées pour développer des activités plus durables, même si aujourd'hui il s'agit d'une déclaration de haut niveau. Tant la recherche sur le terrain comme la littérature scientifique soulignent que les décideurs dans le contexte de l'aide humanitaire n'ont pas les outils adéquats pour évaluer l'impact de leurs décisions en termes de durabilité.

Plus encore, l'évolution dans les attentes de l'opinion publique (et donc les donateurs) suggère que la durabilité de la CLH, en termes de performance, devra être prise en compte dans les années à venir pour assurer la compétitivité, et donc le maintien de l'activité.

La Figure 10, dans le chapitre d'introduction de ces travaux de thèse, synthétise l'évolution dans les attentes liées à la performance depuis le début de la CLH jusqu'à nos jours.

C'est donc dans ce contexte que ces travaux de recherche se positionnent, avec l'hypothèse que maitriser la performance durable dans les années à venir sera incontournable pour les décideurs de la CLH.

Défis de la Chaîne Logistique Humanitaire durable

Pour maitriser la performance durable des opérations dans la CLH, trois défis majeurs ont été identifiés d'après la littérature scientifique et les données/observations au terrain.

-Difficultés à mesurer la durabilité La performance durable est souvent définie par le biais de la TBL, pour Tripple Bottom Line en anglais, qui se compose des dimensions économiques, environnementale et sociale. La TBL est une approche systémique qui souligne la nécessité d'atteindre un minimum de performance pour les trois dimensions, mais il n'existe pas de consensus sur les compromis et les synergies entre les trois.

La définition macro-économique de la durabilité et les trois dimensions peuvent expliquer le développement durable d'un point de vue conceptuel, mais ne fournissent pas assez d'indications sur la manière dont la durabilité doit être abordée dans le contexte des opérations de la CLH.

-Planification insuffisante

Pour maîtriser la performance il faut être capable d'anticiper l'impact des décisions, ce qui relève de la planification. Cependant, le contexte des CLH est caractérisé par un manque de planification structurée [START_REF] Haavisto | Perspectives on sustainability in humanitarian supply chains[END_REF]. De plus, le réseau de logistique humanitaire est de plus en plus complexe à gérer, avec des entrepôts dits de « prepositionnement » localisés tout autour du Globe, des partenariats avec des industriels ou encore des organismes de coordination inter-organisation comme les Clusters des Nations Unies.

Ce manque de planification lié à la complexité du réseau, entraîne des défaillances dans la gestion de l'approvisionnement (i.e. gestion des stocks, mode de distribution, choix des fournisseurs), et donc des inefficacités et inefficiences telles que l'effet coup de fouet ou les retards de distribution, et constitue un obstacle à l'alignement des opérations sur des objectifs durables.

-Absence de systèmes d'aide à la décision adéquats Dans les chaînes d'approvisionnement commerciales, les processus de planification sont de plus en plus pris en charge par des systèmes d'aide à la décision (ERP, TMS, APS). Un système d'aide à la décision est généralement défini comme « un système d'information interactif basé sur ordinateur conçu pour prendre en charge des solutions aux problèmes de décision » [START_REF] Liu | Integration of decision support systems to improve decision support performance[END_REF]. Dans la gestion des opérations, les systèmes d'aide à la décision reposent souvent sur des approches de recherche opérationnelle (RO).

En matière de gestion des crises humanitaires, il est de plus en plus reconnu la nécessité d'étudier l'applicabilité de la RO. Bien que de nombreuses recherches aient été menées sur la mise au point de modèles de RO pour appuyer la prise de décision dans la CLH, très peut ont un impact réel sur le terrain (Laguna [START_REF] Salvadó | Humanitarian Value Stream Mapping: Application to the EBOLA Outbreak[END_REF].

Problématique scientifique et terrain

La littérature souligne que la durabilité est toujours négligée dans les contextes humanitaires, même si elle est essentielle pour aligner les objectifs opérationnels sur les objectifs à long terme de l'action humanitaire. Plusieurs auteurs ont appelé à davantage de recherches pour intégrer la durabilité aux prises de décision humanitaires [START_REF] Haavisto | Perspectives on sustainability in humanitarian supply chains[END_REF][START_REF] Klumpp | Humanitarian Logistics and Sustainability[END_REF][START_REF] Kunz | Sustainable humanitarian supply chain management -exploring new theory[END_REF].

Il est fondamental de bien comprendre le contexte de la CLH et de concevoir des solutions reposant sur une hypothèse forte, basée sur le terrain. Par conséquent, l'objectif de ce travail de recherche est d'aborder les questions de recherche suivantes :

Question de recherche 1 : Comment conceptualiser formellement ce qu'est un CLH ?

Le CLH est un système collaboratif dans lequel de nombreux acteurs et parties prenantes interagissent pour atteindre l'objectif ultime de « alléger la souffrance humaine ». Pour améliorer la performance globale d'un système, il est essentiel d'en avoir une connaissance suffisante. Des travaux de recherche antérieurs ont proposé des modèles pour définir ces connaissances, mais aucun de couvre totalement la CLH en tant que système collaboratif.

La difficulté donc, reste de disposer d'une conceptualisation partagée et suffisamment explicite de la CLH pour, d'une part, comprendre, puis pour améliorer le comportement du système. Cette question de recherche est intéressante à la fois pour l'académique et les praticiens de terrain, car elle devrait contribuer au partage des connaissances et à la communication entre les praticiens eux-mêmes, ainsi qu'entre les praticiens et les universitaires. Il peut également contribuer à la recherche en facilitant la conception et analyse de la recherche sur le terrain.

Question de recherche 2 : Que signifie la durabilité des opérations de la CLH et comment peut-on l'évaluer ?

Compte tenu de l'augmentation du nombre de publications scientifiques qui s'intéressent au concept de « durabilité » dans de nombreuses disciplines, on peut considérer la durabilité comme un sujet à la mode. Ceci n'empêche pas les difficultés pour définir qu'est-ce que la performance durable dans le cadre de la CLH.

Déjà, la durabilité est un concept multidimensionnel. De plus, on remarque que le niveau de granularité des mesures de la durabilité proposées dans la littérature sont généralement contraires à la transférabilité de ces mesures. C'est-à-dire, il semble que l'évaluations de la durabilité corresponds souvent à des objectifs de haut niveau (petite granularité) qui ne sont pas transférables (et donc n'appuient pas) les niveaux de décision tactiques et opérationnels (petite granularité). Ainsi, à ces niveaux de décision, chaque secteur d'activité doit trouver un moyen fiable de quantifier la durabilité.

Même si les OH ont déjà souscrit au programme de développement durable, il est encore difficile de concrétiser ce qu'est une performance durable aux différents niveaux de décision. Cette question de recherche est pertinente pour les académiques car elle vise à contribuer à combler le fossé entre les concepts généraux de durabilité et le domaine de recherche, ainsi que pour les praticiens car elle vise à permettre l'évaluation de la durabilité dans les processus décisionnels en matière de CLH.

Question de recherche 3 : Comment aider les décideurs à faire des compromis en matière de durabilité et à en explorer les conséquences de manière consciente et systématique ?

Pour améliorer la durabilité des opérations, les décideurs peuvent tirer parti de l'évaluation a priori de la durabilité dans le processus de planification. Pour planifier des opérations durables, les décideurs doivent faire des compromis sur la durabilité de manière transparente, sur la base de leur connaissance de la situation (objectifs et intérêts organisationnels, expertise, etc.) et de la prise de conscience de leurs conséquences.

Cependant, les systèmes d'aide à la décision qui traitent des compromis ne sont pas alignés sur les exigences des praticiens en termes de compétences et de temps. Les utilisateurs doivent généralement gérer des pondérations et des dépendances abstraites et complexes, ce qui peut constituer un obstacle à l'acceptabilité des systèmes d'aide à la décision sur le terrain. Le défi consiste alors à concevoir et à développer une approche de système d'aide à la décision qui contribue à réduire l'écart entre les propositions académiques et la convivialité sur le terrain.

Cette orientation de recherche est intéressante pour les universitaires car elle vise à utiliser des méthodes pour des non-experts et, partant, à améliorer systématiquement les processus de planification des CSS.

La Figure 17, dans le chapitre d'introduction aux travaux de recherche, montre une synthèse des grandes problématiques abordées dans ces travaux. L'objectif finale étant de proposer un système d'aide à la décision pour une CLH durable, trois étapes sont abordées :

-la description du système CLH, afin de structurer la connaissance, -la description des objectifs de durabilité, pour ainsi pourvoir évaluer la durabilité dans le contexte de la CLH, et -la prise de décisions qui prennent en compte la durabilité du système, et donc pour pouvoir proposer un système pour aider à la planification tactique (Master Planning) de la CLH.

Méthodologie de recherche

Pour répondre aux questions de recherche, et réduire l'écart entre la pratique et la recherche (fortement critiquée), nous avons suivi une approche de recherche inductive. Inductive, car le problème et les solutions sont tous deux fondés sur des recherches sur le terrain, dans le but de créer une hypothèse générale.

Dans ce sens, on a suivi la philosophie de la recherche-action. Nous avons donc collaboré tout au long du projet avec la branche logistique de la Fédération Internationale de la Croix Rouge (FICR), plus précisément avec le Centre Logistique Régional de l'Amérique et des Caraïbes, située au Panama.

La force des propositions repose sur la capacité d'identifier un problème pertinent pour les OH. La méthode utilisée est la collecte de données sur le terrain, avec une analyse et des retours sur les résultats vers les OH. Nous avons utilisé des données secondaires et primaires de la FICR, et d'autres ONGs et agences humanitaires.

Les données secondaires se trouvaient principalement sur Internet et sont constitués notamment de rapports annuels et communications sur les opérations. Le site reliefweb.net a été utilisé comme point de départ.

Pour les données primaires, nous avons mené une campagne de recherche sur le terrain au Panama, au Centre Logistique Régional de la FICR, et utilisé des entretiens semi-structurés, des observations et un accès aux documents.

Recherche terrain avec la FICR au Panama

Où? Centre Logistique Régional de la FICR en Amérique (Panama). Bureaux et entrepôts.

Quand? 10 jours en septembre 2015

Qui? Un chercheur sur le terrain et deux dans le « back office » Quoi? Formaliser les processus opérationnels de la CLH. L'objectif était d'identifier les défis du système et opportunités pour les décideurs.

Les résultats des recherches sur le terrain (enjeux métiers), associés à la revue de la littérature, ont permis de formuler les trois questions de recherche (enjeux scientifiques) développées dans ce manuscrit.

Pour construire des contributions scientifiques, des travaux approfondis ont permis de mettre au point des méthodes originales, ou ont adapté les méthodes existantes permettant de répondre aux questions de recherche et aux enjeux de l'organisation, la FICR.

De plus, un démonstrateur de chaque contribution a été développé et validé avec une preuve de concept basée sur des données de recherche sur le terrain.

1ère contribution : Métamodèle de la CLH

Pour faciliter la formalisation et la compréhension de la CLH, le chapitre 2 du manuscrit présente un métamodèle du système CLH. La contribution s'appuie sur les travaux de Benaben et al. (2016), qui ont proposé de définir tout système collaboratif à partir de quatre briques : le contexte, les partenaires, les objectifs et le comportement. Ces quatre briques forment le coeur du métamodèle, sur lequel des concepts correspondants a un domaine donné peuvent être structurés.

Dans ce chapitre il est décrit la couche du métamodèle correspondante au système CLH. La Figure 34 montre une synthèse de cette contribution. Cette approche repose sur l'hypothèse que le CLH est un système collaboratif qui peut être décrit par des concepts spécifiques au domaine, mais assez génériques pour être transposables d'une CLH à une autre. Nous avons construit et organisé le métamodèle à partir des concepts retrouvés dans la littérature ainsi que grâce aux recherches terrain.

Cette proposition est originale étant donné qu'aujourd'hui, il n'existe pas de conceptualisation formelle standard d'un système CLH. Elle permet donc d'organiser les informations relatives à une CLH d'une manière structurée. Les utilisations potentielles d'un tel métamodèle sont multiples, et nous mettons donc en avant :

le développement de supports pour la recherche terrain : le métamodèle est un outil qui permet de structurer l'information pour générer de la connaissance. Pendant les explorations de terrain, il peut faciliter la recollecte d'information d'une manière structurée, ainsi que la réutilisation de résultats (modèles). -le développement de systèmes d'information spécialisés de la CLH : le métamodèle permettrait à des SI d'intégrer et d'interpréter l'information et générer donc de la connaissance et notamment de l'aide a la décision. -soutenir des étapes concrètes d'amélioration continue pour les aspects logistiques : pour identifier les points faibles d'une CLH donnée, il faut maitriser l'état actuel (cartographie ASIS). Le métamodèle permettrait de faciliter cette tâche et d'assurer l'intégrité des éléments nécessaires pour analyser.

Nous avons validé et démontré l'intérêt du métamodèle de la CLH en construisant des supports pour la recherche terrain. Ces outils ont été utilisées dans le cadre du cas d'étude de la FICR et on permit un recueil exhaustif et reproductible d'information.

Limites : L'application pratique (et donc la validation) du métamodèle pour d'autres utilisations suggérées telles que la définition des spécifications d'un système d'information, ou pour faciliter la coordination et interopérabilité des OH, n'a pas été mise en oeuvre.

2ème contribution : la maison des opérations de la CLH durable

Les objectifs de cette seconde contribution sont doubles :

(1) clarifier le concept de la CLH durable,

(2) créer un cadre pour évaluer la performance des opérations.

Tout d'abord, on a défini un cadre de mesure de la performance : La Maison des opérations de la CLH durable. Ce cadre traduit les concepts de durabilité en opérations concrètes de la chaîne d'approvisionnement (achats, entreposage, transport) et souligne la nécessité de prendre en compte les trois dimensions du TBL pour améliorer la durabilité opérations. Les critères ont été définis en tenant compte de l'analyse de la littérature sur la durabilité de la chaîne d'approvisionnement et de l'impact des processus (achats, stockage et transport) sur les différentes sous-dimensions.

Ensuite, un modèle et une méthode pour évaluer la maturité de performance de la CLH durable sont proposés. Pour illustrer l'utilisation du modèle d'évaluation de la maturité, une preuve de concept a été construite avec une étude de cas de là FICR. La Figure 49 et la Figure 53 montrent la Maison des opérations de la CLH durable et le modèle pour mesurer la maturité d'un système de CLH en termes de durabilité respectivement.

Ce chapitre contribue de manière significative à la discussion naissante sur la durabilité des CLHs. Il amène des éléments de discussion et pour l'évaluation concrète de la durabilité des opérations de la CLH, qui semble encore difficile dans de nombreuses disciplines.

Le cadre de performance présenté dans le chapitre 3 constitue donc la base de l'élaboration d'un système d'aide à la décision permettant d'optimiser la planification des opérations de la CLH en ce qui concerne les impacts du TBL. Toutefois, la durabilité étant un concept multidimensionnel aux objectifs contradictoires, le défi consiste maintenant à maitriser les compromis et synergies au travers des dimensions économique, environnementale et sociale.

Limites : le cadre a été mis au point grâce aux contributions des recherches sur le terrain avec la FICR, ainsi qu'aux grilles d'évaluation de la maturité. Une validation plus large devrait être menée avec des experts de différents OH, afin de consolider un point de repère permettant de comparer les organisations.

3ème contribution : un système d'aide à la décision pour le Master Planning (comment ?)

Enfin, la dernière contribution (chapitre 4) développe une approche pour intégrer de manière concrète la prise en compte de la performance durable lors de la planification des opérations de la CLH.

À partir des recherches sur le terrain et de la littérature, le niveau de planification tactique est identifié comme un bon catalyseur pour introduire la durabilité dans le processus de prise de décision.

Par conséquent, le problème de la planification tactique (Master Planning) de la CLH durable a été abordé. Sur la base du réseau de la FICR en Amérique, un ensemble de critères de performance durable (social, économique et environnemental) ont été sélectionné et définis à fin d'être mesurables.

Ensuite, le réseau logistique dit amont (des fournisseurs jusqu'aux points d'entré aux endroits géographiques affectés par des crises) et les indicateurs sont modélisé mathématiquement avec les outils de recherche opérationnelle déterministes. Il est proposé de résoudre le système avec un algorithme d'ordonnancement lexicographique interactif qui permet de prendre en compte l'expertise des décideurs dans le processus de planification. La Figure 59 montre le diagramme logique de l'algorithme qui a été développé dans cette contribution.

Limites : le cas d'utilisation de la FICR en Amérique couvre le processus décisionnel interne et en amont, qui ne représente qu'un périmètre limité de l'ensemble de la CLH (des fournisseurs aux utilisateurs finaux). L'application pratique à un périmètre plus large et à d'autres OH reste à faire. De plus, beaucoup de données sont nécessaires pour exécuter le modèle. La capacité de collecte de ces données doit donc être étudiée en amont, de même que la sensibilité des résultats.

Perspectives

Le chapitre 5 du manuscrit présente les contributions, résultats et conclusion de ces travaux, que nous avons déjà évoqué dans ce résumé.

Pour synthétiser, les trois grandes questions qu'ont été abordées pour aller vers une CLH durable sont donc :

-la modélisation du système CLH en tant que système collaboratif, -la définition de la performance durable dans le contexte de la CLH, et -le développement d'un outil pour aider à planifier les opérations tactiques d'une CLH.

Nous présentons ici une feuille de route visant à consolider les propositions et à proposer de nouvelles orientations de recherche.

Perspectives à court terme (validation)

i.

Validation plus large avec scénario réel :

Pour démontrer la validité des propositions, toutes les contributions ont été validées via le cas d'utilisation de la FICR en Amérique. Néanmoins, chacune des contributions a été construite avec un ensemble de données limité étendu par des hypothèses. Bien que les hypothèses aient été discutées avec les praticiens ou fondées sur des observations sur le terrain et / ou la revue de la littérature, il serait pertinent de définir un scénario basé sur un ensemble complet de données réelles.

ii.

Validation en temps réel :

Pour construire un scénario réel, il serait approprié de s'engager avec la FICR sur une campagne de recherche sur le terrain dédiée à la collecte et exploitation de données en temps réel. En outre, les praticiens pourraient effectuer une étape de validation en comparant les résultats de performance avec et sans utiliser le système d'aide à la planification de la CLH.

iii.

Hypothèses du modèle contrastés avec d'autres OH :

Les hypothèses ont été construites sur les spécificités de la CLH amont de la FICR. Il s'agit d'une limitation et l'une des perspectives serait donc d'étendre la validation à un plus grand nombre d'OH, tels que le Plan Alimentaire Mondial (PAM) ou même Médecins sans Frontières (MSF), qui gèrent des réseaux de CLH similaires. La portée des autres CLH peut différer en termes de contexte (i.e. conflits armés) et, par conséquent, l'hypothèse et les contraintes du modèle de flux de réseau CLH peuvent différer.

iv.

Une évaluation plus approfondie de la sensibilité :

La sensibilité du modèle doit être examinée plus en profondeur avec un jeu de données réel. L'objectif est d'aider les utilisateurs à interpréter et à anticiper les conséquences de leurs choix au cours du processus de décision.

Perspectives à moyen terme (mise en oeuvre)

v.

Interaction homme-machine

Dans la troisième contribution, nous nous sommes concentrés sur l'algorithme et le modèle permettant d'évaluer la durabilité et de résoudre le problème décisionnel lié à la planification durable. Bien que nous ayons pris en compte le savoir-faire des utilisateurs pour hiérarchiser les objectifs de performance, l'utilisation du système reste complexe pour les non-initiés. Pour renforcer l'approche de la recherche appliquée, des travaux supplémentaires doivent être menés pour concevoir et développer des interactions ergonomiques homme-machine. Développer des interfaces utilisables (efficaces, performantes et satisfaisantes) est une question interdisciplinaire qui concerne l'ingénierie informatique et qui bénéficierait également d'une perspective des sciences sociales (conception d'interaction) [START_REF] Dix | Human-Computer Interaction[END_REF].

vi. Transfert technologique

Une fois le prototype mis en oeuvre, il est important d'envisager la diffusion du système d'aide à la décision parmi les utilisateurs potentiels (accès à la connaissance). L'intégration avec les systèmes d'information existants (par exemple, ERP) est une question connexe importante à prendre en compte. Cela peut notamment révéler des problèmes d'interopérabilité.

Perspectives à long therme (évolutions)

vii.

Évaluations du cycle de vie

Une approche standard pour évaluer les impacts d'un produit sur les différentes dimensions de la durabilité consiste à effectuer une analyse du cycle de vie (ACV). Cette évaluation a généralement été réalisée pour la dimension environnementale, mais certains auteurs envisagent également de réaliser une ACV sociale. C'est une perspective intéressante à suivre car elle peut permettre d'identifier, dans une perspective d'amélioration continue, les étapes de la CLH qui ont l'impact le plus négatif.

viii. Vers un système de planification avancée humanitaire

Le but ultime de la CLH est de générer un comportement décisionnel synergique avec toutes les parties prenantes de la réponse humanitaire en amont et en aval. Ce travail de recherche a abordé une première étape, avec le développement d'un module de planification de base, pour la CLH en amont. Cependant, la question de savoir comment les décisions prises en amont ont un impact sur la durabilité globale des CLH reste posée. Comment les décideurs peuventils acquérir une perspective holistique ?

Par conséquent, pour améliorer les opérations de la CLH, deux perspectives intéressantes se dégagent :

(1) l'intégration des différents niveaux de planification et

(2) l'intégration des parties prenantes en amont et en aval.

Pour les Chaînes Logistiques commerciales, les APS (Advanced Planning Systems) sont considérées comme la solution pour intégrer tous les processus de décision en utilisant une approche hiérarchique. Cependant, le contexte des opérations humanitaires soulève des difficultés supplémentaires : les réseaux en aval sont déployés de manière ad-hoc, les collaborations entre les parties prenantes peuvent être sporadiques et la prise de décision peut être décentralisée.

-Est-il alors possible de développer une SAP humanitaire agile et/ou flexible ? -Comment aborder la dynamique et l'incertitude du système ?

Néanmoins, de nombreuses études ont déjà été menées sur la prise de décision au niveau stratégique, avec par exemple la conception du réseau (Aurélie Charles 2010;[START_REF] Vargas Florez | A decision support system for robust humanitarian facility location[END_REF], ou au niveau opérationnel avec des problèmes de prise de décision concernant la distribution du dernier kilomètre (Burcu Balcik. et al 2008). Des questions restent à résoudre :

-Comment introduire la perspective durable dans les différents niveaux de décision et -Comment assurer l'interopérabilité des différents systèmes ?

L'utilisation du métamodèle CLH peut être un facteur facilitant le développement de l'APS humanitaire durable, si elle est utilisée comme référence commune pour définir le réseau.

ix. Agilité (détection, adaptation)

Enfin, les opérations de la CLH durable doivent faire face à un degré d'incertitude élevé. Par conséquent, le processus de prise de décision requiert des méthodes qui s'adaptent à la dynamique de l'environnement. Notre contribution se limite à la conception d'un processus (le schéma directeur) et, pour faire face à l'incertitude, nous avons proposé une approche de planification à horizon glissant. Un système agile peut détecter les écarts entre le plan et la réalité et s'adapter à la nouvelle situation. Un processus décisionnel agile peut être mis en oeuvre en ajoutant les deux dimensions : détection et adaptation.

Chapter I. INTRODUCTION

"When a humanitarian disaster hits, affected communities frequently require essential, appropriate and timely humanitarian assistance."

(Humanitarian Coalition 2015)

Humanitarian Supply Chain Context

We introduce in this section the concepts of humanitarian disasters and the response to them to obtain an overview of what a Humanitarian Supply Chain (HSC) is and what the main challenges to be solved in the future will be.

Humanitarian Disasters

Disaster terminology

For the moment, there is no consensus on the definition of a "humanitarian disaster". In the academic literature, Pearce defined it as "a non-routine event that exceeds the capacity of the affected area to respond to it in such a way as to save lives; to preserve property; and to maintain the social, ecological, economic, and political stability of the affected region" [START_REF] Holguín-Veras | On the unique features of post-disaster humanitarian logistics[END_REF][START_REF] Pearce | An integrated approach for community hazard, impact, risk and vulnerability analysis: HIRV[END_REF]. The United Nations International Strategy for Disaster Reduction (UNISDR) defines a disaster as a "serious disruption of the functioning of a community or a society (due to hazardous events interacting with conditions of vulnerability and exposure) leading to widespread human, material, economic or environmental losses and impacts" (UNISDR, 2009). This second definition stresses the fact that disasters are always the consequence of a hazard.

A hazard is defined as "something that is dangerous and likely to cause damage" (Cambridge dictionary, 2017). Therefore, the disaster's severity depends on how much impact a hazard has on a society and the environment. The UNISDR highlights that the impact of a hazard depends on population vulnerability1 and exposure 2 (UNISDR, 2017). This approach is in line with the academic literature that studies how to mitigate the risk and impact of hazards. Exposure emphasizes that the location of the hazard influences its impact. For example, the same magnitude earthquake that hits a city or that hits a desert will not have the same consequences. The impact also depends on the standards of living in the area. If the city is in a developing country the damage may be more severe. Vulnerability emphasizes that some groups are more prone to damage. Poor populations are more likely to be vulnerable than rich populations. Within affected communities, typically vulnerable groups include children, pregnant and nursing women, migrants, and displaced people

Humanitarian disaster typologies

Humanitarian disasters are often classified by the origin of the hazard: either natural, caused by physical or biological hazards; or man-made [START_REF] Van Wassenhove | Humanitarian aid logistics: supply chain management in high gear †[END_REF]. The speed of the hazard onset is also a relevant characteristic. Sudden-onsets refer to disasters that impact a community within a short period of time. A typical example of a natural sudden-onset is an earthquake. Slow-onset disasters are the humanitarian disasters that evolve progressively over time, for example droughts. The main difference is that slow-onset disasters can be mitigated by early response. Unfortunately, as stated by the United Nations Office for the Coordination of Humanitarian Affairs (UNOCHA), the response to most slow-onset disasters often ends up resembling the response to sudden-onset disasters (United Nations, 2011). Moreover, some disasters are recurrent due to the cyclical frequency of natural hazards such as hurricanes or floods. An example is the "El Niño" phenomenon, which generates both heavy rains and droughts in irregular cyclical patterns (every 2 to 7 years), and affects especially the South American Pacific coastal areas [START_REF] Vargas Florez | A decision support system for robust humanitarian facility location[END_REF].

The combination of several or prolonged hazards may lead to "complex disasters". These are characterized by extensive violence, displacement of populations, severe damage to societies and economies and even more challenging: the potential prevention of the arrival of humanitarian assistance because of political and military constraints. This complex disaster context is a risk for humanitarian responders, as illustrated by the MSF (Médécins Sans Frontières) and ICRC (International Committee of the Red Cross and Red Crescent) hospital attacks during the on-going Syrian conflict.

In Table 1, a few recent examples are classified by origin of the hazard occurrence. The lines between types of disaster are often blurred. Thus, this classification is illustrative, but non-exhaustive, and may be controversial. Syrian conflict (ongoing) South Sudan chronic political crisis

Impact

Disaster impacts may include loss of life, injury, disease, and other negative effects on human physical, mental, and social well-being, together with damage to property, destruction of assets, loss of services, social and economic disruption, and environmental degradation.

A positive trend is that the number of casualties due to natural disasters has tended to decrease since the beginning of the 20th century. Thanks to the improvement of early warning and planning systems, disasters such as floods have became less deadly, while in contrast, earthquakes have became more dangerous with the growth of cities and their vulnerability. However, statistics show a significant rise in the number of affected people (Figure 1), particularly during the last ten years. Even though the proportion of newly displaced people has decreased, the problem now for the longterm displaced population is that "many people remain in limbo for years in Internally Displaced People camps, urban slums or other areas of refuge, a situation defined as protracted displacement.

"Lacking a permanent home or sustainable livelihoods, they often have little prospect of reaching a durable solution" (UNHCR, 2017).

To sum up, the trends show an increase in both natural and man-made disaster occurrences and impacts. Therefore, there is also an increase in the short-and long-term humanitarian needs. Professionalization of humanitarian operations is more than ever a critical issue.

Humanitarian aid

The Disaster Management Cycle

Humanitarian disaster management is described as a four-phase cycle: preparedness, response, recovery and mitigation phases (Figure 4). In the short term, affected communities need external interventions to maintain and improve the quality of life of the affected population. Such assistance may range from providing specific but limited aid, such as transport, temporary shelter, and food, to establishing semi-permanent settlements in camps and other locations, before coming back to a "normal" situation. Providing such relief aid is the role of humanitarian responders during the response phase. Before a disaster happens, efforts are put on the preparedness of the areas and populations at risk. Humanitarian Organizations (HOs) have developed disaster preparedness initiatives during the past decades, which have provided quicker and more effective responses to humanitarian crises. As an example, the Inter-Agency Standing Committee (IASC) proactively anticipates the coordination of international responders with the Emergency Response Preparedness approach.

In the long term, humanitarian responders work on the recovery of the affected communities to come back to a "normal" situation and on the development of community's resilience 1 to mitigate the impacts of future disasters. Mitigation is typically addressed by the scope of development projects, which addresses systematic problems of developing countries, with a focus on economic, social and political development.

This separation between short and long-term humanitarian aid is blurred, because it is not clear when the relief is finished and the recovery begins. This thesis focuses, however, on relief assistance delivery (short-term humanitarian needs coverage), so therefore on the preparation and response phases exclusively.

Humanitarian Actors

In the aftermath of a disaster, the first responders are local or national. They can belong to many different actors such as the authorities, civil defense, communities (e.g. churches), local or 1 Resilience is defined as: "The ability of a system, community or society exposed to hazards to resist, absorb, accommodate to and recover from the effects of a hazard in a timely and efficient manner, including through the preservation and restoration of its essential basic structures and functions", United Nations Office for Disaster Risk Reduction (UNISDR), "2009 UNISDR Terminology on Disaster Risk Reduction", Geneva, May 2009 (http://www.unisdr.org/we/inform/terminology).

international Non-Governmental Organizations (NGOs), which are already in the field. When the authorities of a country/region are overwhelmed by a humanitarian crisis, the international community is mobilized. The IASC, for example, activates exceptional response mechanisms when an emergency requires a system-wide response (so-called Level 3 emergencies). For the designation of an L3 emergency, the IASC protocol establishes the analysis of five criteria: scale, complexity, urgency, capacity, and reputational risk.

The international response includes a large variety of HOs (NGOs, UN agencies, humanitarian agencies, etc.), which interact with other stakeholders: governments, militaries, media, donors (public/private), etc. Figure 5 gives an overview of the variety of organizations that are part of the humanitarian response.

Our focus is on HOs, which include Humanitarian Agencies such as the World Food Programme (WFP), the International Federation of the Red Cross (IFRC), the ICRC and local and international NGOs (i.e. MSF, Save the Children, Care). HOs are supposed to provide relief assistance while following humanitarian principles: humanity, neutrality, impartiality and independence. The UN General Assembly formally established these core principles in 1991 (humanity, impartiality and neutrality) and 2004 (independence) was inspired and reiterated by the IFRC/ICRC. Nonetheless, each HO has its own mandates in accordance with the HO's objectives. The common characteristics of HOs are [START_REF] Charles | An enterprise modelling approach for better optimisation modelling: application to the humanitarian relief chain coordination problem[END_REF]):

• They are under-resourced, with limited skills availability and high employee turnover that limits institutional memory and efficiency.

• Ineffective leverage of technology (i.e. non-robust equipment) and in particular, Information Systems that are relatively basic.

• Decision-making tends to be distributed and does not follow command/control approaches.

• HOs deal with several disasters at the same time, including both relief assistance and development projects.

Figure 5 The Humanitarian Decision-makers Taxonomy [START_REF] Gralla | Field-based decision makers' information needs in sudden onset disasters[END_REF])

Humanitarian Organization coordination

Coordination in a humanitarian disaster context can be defined as the relationship and interactions among different actors operating within the relief environment [START_REF] Balcik | Coordination in humanitarian relief chains: Practices, challenges and opportunities[END_REF]. HO coordination is an important issue, as experience has demonstrated that a lack of coordination within or between HOs leads to inefficiencies and ineffective relief operations. Coordination, still considered a weakness of the humanitarian sector, can take place at different granularity levels (local, global) and in different forms (Laguna Salvadó et al. 2015).

• Intra-Organizational Coordination concerns the internal relationships and interactions within an organization. The organizational structure is a key element (e.g. field teams with Head Quarters). This can be difficult due to the lack of "command and control" hierarchical approaches in organizations such as the IFRC, where the National Societies are autonomous.

• Inter-Organizational Coordination concerns the coordination between organizations at local and global levels. This coordination is difficult, variable, and rather low [START_REF] Charles | Collaboration Networks Involving Humanitarian Organisations -Particular Problems for a Particular Sector[END_REF].

The main difficulties and enablers at the local (Table 2) and global level ( Nonetheless, efforts have been made to improve this challenging coordination. The foundations of the current HO international coordination system were set by UN General Assembly resolution 46/182 in December 1991. Almost 15 years later, in 2005, a major reform of the humanitarian coordination approach, known as Humanitarian Reform, introduced a number of new elements to enhance predictability, accountability and partnership. The Cluster Approach, a coordination facilitator mechanism, was one of these new elements. The main objective of the system is to facilitate the exchange of information between the different HOs in the field in the aftermath of a disaster. One of the core functions of a cluster at country-level is to inform strategic decision-makers, and provide coordination of needs assessment, gap analysis and prioritization (UN OCHA, 2014).

However, some HOs feel that the Cluster Approach is contradictory to the humanitarian principles of independence, impartiality, and neutrality [START_REF] Humphries | Improving Humanitarian Coordination: Common Challenges and Lessons Learned from the Cluster Approach | The Journal of Humanitarian Assistance[END_REF]. Other arguments against it are the lack of performance, most notably in overhead and lack of agility There are other experiences of UN inter-organizational coordination approaches such as the one deployed during the West Africa Ebola Outbreak. WHO led the UN Mission for Ebola Emergency Response (UNMEER). It was set up as a temporary measure to meet immediate needs related to the unprecedented fight against Ebola. The mission deployed financial, logistical and human resources to Guinea, Liberia and Sierra Leone. However, as it was deployed "ad-hoc" in a complex situation, and some problems were encountered such as the lack of expertise of management leaders (Comes et al. 2015).

Out of all the sectors of the humanitarian response, this thesis focuses on the "logistics" activities, and in particular on certain HSC management challenges.

Humanitarian Supply Chain

To have the right resources in the right place and at the right time is crucial for a successful humanitarian intervention. In a disaster response, the main flows concerned were defined by [START_REF] Tomasini | From preparedness to partnerships: case study research on humanitarian logistics[END_REF] as the 5b's: boxes (materials), bucks (finance), bodies (manpower), brains (knowledge and skills) and bytes (info).

HSC management is defined by (Thomas & Mizushima, 2005) as "the process of planning, implementing and controlling the efficient, cost-effective flow and storage of goods and materials, as well as related information, from point of origin to point of consumption." [START_REF] Sarkis | Relief supply chain management for disasters: humanitarian aid and emergency logistics[END_REF] adds that HSC management also includes coordination and collaboration with supply chain third party service providers, and across HOs, but does not include the development aid aspect of humanitarian logistics.

Depending on the disaster, HSCs can take many forms and concern different actors. However, the material flow follows repetitive patterns. A typical HSC connects emergency item suppliers to the beneficiaries through a network of organizations, warehouses and transport flows (Figure 7) to satisfy the humanitarian needs.

Figure 7 HSC network (inspired from (Baharmand et al. 2015))

In contrast to commercial supply chains (SC), and due to the nature of disasters, HSCs deal with extremely uncertain and unexpected needs, which result in the design and deployment of ad-hoc downstream networks to reach the beneficiaries (point of demand, see Figure 7). The upstream HSC deals with all upcoming and on-going humanitarian crises and resulting aggregated demands. Finally, the main humanitarian-specific attributes are [START_REF] Widera | Understanding Humanitarian Supply Chains-Developing an Integrated Process Analysis Toolkit[END_REF]):

• Prioritization of responsive (effective) instead of efficient (cost-effective) behaviors: due to the HSC purpose of "alleviating human suffering", the main concern at the response phase has historically been to satisfy humanitarian needs "no matter what the cost". This tendency is changing due to funding shortage. • Uncertain and unpredictable demand: due to the nature of disaster, it is difficult to build longterm planning of humanitarian needs. Even though past trends allow "forecasting" of the potential needs, at least for recurrent disasters, decision-makers always face strong uncertainty. • The role of donors as buyers and beneficiaries as end users: The definition of the customers of an HSC is difficult due to this duality. The value expected by beneficiaries and donors is not the same, but is strongly related. Thus, HSC decision-makers have to satisfy both beneficiaries' and donors' expectations. • A highly volatile environment, and partly temporary and unknown HSC design: not only is demand uncertain, but also the environment and the HSC itself. Depending on the disaster context (which is unknown), the HSC network will adapt and deploy on the fly. • Focus on procurement and distribution within the logistics value chain: With the exception of kitting, no transformation is made to the emergency products.

Some HOs have made HSCs part of their "core business", such as the IFRC, the UN Humanitarian Response Depot (UNHRD), managed by WFP, or MSF. These HOs have developed specialized skills in supply chain management (SCM).

Problem Statement

In this section, the past evolutions and upcoming challenges that the HSC managers face from a practical perspective will first be discussed, and second, the gaps will be identified from an academic perspective.

Towards a Humanitarian Sustainable Supply Chain

Even though HSC has always been part of disaster response, the awareness of its key role grew significantly during the last decade. Therefore, the management of HSC operations has evolved from a reactive behavior focused on disaster response towards the current effective/efficient behavior that includes the preparation phase. Nonetheless, performance has not been systematically evaluated in the HSC field, probably because measuring the "alleviation of human suffering" is intangible [START_REF] Beamon | Performance measurement in humanitarian relief chains[END_REF]. This section explores past, present and future trends of HSC performance.

The effective and fire-fighting HSC management approach

In contrast with commercial supply chain performance approaches, effectiveness is, and has been, the main driver or value of HSC [START_REF] Widera | Understanding Humanitarian Supply Chains-Developing an Integrated Process Analysis Toolkit[END_REF]. Effectiveness is the ability to enhance the expected results [START_REF] Lauras | Méthodes de diagnostic et d'évaluation de performance pour la gestion de chaînes logistiques: application à la coopération maison-mère-filiales internationales dans un groupe pharmaceutique et cosmétique[END_REF]. It is commonly defined as achieving target outcomes.

Therefore, considering that the expected results of a relief operation are to alleviate human suffering by procuring emergency relief items, we can acknowledge that the effectiveness of an HSC is the ability to satisfy humanitarian needs in terms of emergency items (i.e. shelter, food, hygiene), on time.

However, fire-fighting behavior has also characterized disaster relief operations. Fire fighting happens when, due to time pressure, decision-makers rush from one humanitarian response to the next, and no time can be invested in solving problems.

Consequently, up until the end of the 20th century, decision-makers were mainly focused on response, and overlooked the preparedness phase. In addition, HSC management was a "back-office" support function.

At that time, the occurrence of major humanitarian disasters made evident the weaknesses of a responsive management approach. Due to the scale of the disasters, along with the unprecedented media coverage, the weakness of disaster response management became obvious, especially in terms of HSC. For instance, both Hurricane Mitch (1998) and the Indian Ocean Tsunami (2004) placed HSC under stress.

The response to Hurricane Mitch revealed the deficiencies of the IFRC HSCs in terms of effectiveness (weak responsiveness, lack of vertical coordination).

Hurricane Mitch (1998)

What? Between 22 October and 1 November 1998, a 180-mph Category 5 storm, the worst to hit the Gulf of Mexico in 200 years, swept through a number of Central American countries devastating the economies of Honduras, Nicaragua and Guatemala. Disaster outcome: 10,000 people were estimated dead while some two million were left homeless. About 400 bridges were destroyed in the region, while the course of rivers was changed and a three-foot layer of mud was deposited on flooded airport airfields.

Response weakness: IFRC's technical staff and relief delegates arrived late in the region. Emergency Response Units were deployed at the eleventh hours. It took weeks to mobilize and distribute basic supplies such as food, water and shelter to the population. Source: INSEAD Case studies (2004) Some years later, the disappointing response to the Indian Ocean Tsunami of 2004 weakened the perception of the HSC. The lack of preparedness and coordination in this response was criticized in the World Disaster Report 2004.

Indian Ocean Tsunami (2004)

What? In the early hours of the morning of Sunday 26 December 2004 a massive earthquake measuring 9.0 on the Richter scale struck the west of northern Sumatra. The quake triggered a powerful tsunami that swept the coasts of neighboring countries and caused serious damage and loss of life.

Disaster outcome: At least five million people were affected in Indonesia, Sri Lanka, Maldives, India, Thailand, Seychelles, and Myanmar. The death toll exceeded 280,000 people, and more than one million people were displaced as a result of the destruction.

Response weakness: The donors' response was unprecedented thanks to media coverage and familiarity with the affected areas (tourism). Moreover, there was also a huge mobilization of HOs. However, the low quality of operations and the excess of donated but unnecessary goods caused an HSC overload that added to operational problems inherent in the quantity and quality of local and international staff; inadequate methods, programs and tools, and little involvement in process management or coordination. Therefore, the consequences were obstructed airports, excess containers blocking ports and customs areas, saturated warehouses, expensive materials and equipment deteriorating in the sun and rain, inadequate supplies and insufficient staff to provide records of materials, poor logistics reports and, in addition to losses, the theft and sale of donations.

Source: [START_REF] Costa | Supply Chains in Humanitarian Operations: Cases and Analysis[END_REF] Accordingly, HOs started considering HSC as a key factor for improving disaster response performance.

An effective and efficient disaster response

To face internal and external pressure, and maintain a competitive position, HOs encountered the urgent need to go beyond the effective and fire-fighting approach. Thus, they started to invest time and resources on the preparedness phase, with a special focus on how to improve HSC performance.

The effectiveness approach was also challenged by humanitarian needs and funding trends. Humanitarian needs are rising year after year. Both people targeted by HOs and the appeals requested by the HOs are increasing (Figure 8). Since 2006, needs have quadrupled. In addition, funding is also rising, even though the growth is less significant. Thus, there is a continuously increasing gap between humanitarian needs and available funding. Figure 9 shows how unmet requirements have been rising for the last 10 years.

Figure 8 Inter-agency appeals: funding requested and people targeted (OCHA, 2017)

Figure 9 Requirements, funding and unmet requirements (source: Global Humanitarian Assistance report 2016)

Bearing in mind that HSC management was recognized as the most expensive part of relief operations [START_REF] Van Wassenhove | Humanitarian aid logistics: supply chain management in high gear †[END_REF], HSC managers started considering cost-efficiency in addition to effectiveness, to obtain a competitive advantage. Donors are asking for greater accountability, and have become less tolerant of inefficiencies [START_REF] Balcik | Coordination in humanitarian relief chains: Practices, challenges and opportunities[END_REF]. Thus, reducing the cost of operations, with an efficient performance perspective, allows HOs to compete in the "humanitarian donor market" and to retain and gain public and private donors who finance the operations.

Therefore, the change in performance paradigm plus the focus on the HSC resulted in a main strategic change. Major HSC organizations like IFRC or WFP shored up the design of their HSC. They deployed a network of strategically located prepositioned stocks.

This distribution strategy consists in pushing products from prepositioned contingency stocks into the country as soon as the humanitarian needs are assessed. If the response capacity of the contingency stock is exhausted, a pull model is then set up to source further goods from the suppliers. This hybrid model allows the first needs to be rapidly satisfied and gives decision-makers some buffer time to plan the upcoming procurement process.

This was a step forward in improving effectiveness (the reduction in response times) and efficiency (the reduction of acquisition costs) thanks to the management of centralized stocks and long-term relationships with suppliers [START_REF] Jahre | The organisational change of logistics in International Federation of the Red Cross and Red Crescent Societies (Case Study). HUMLOG-NET Project[END_REF][START_REF] Laguna Salvadó | A study on the sub-regionalization of Humanitarian Supply Chain: the IFRC case[END_REF]. Since then, the HSC has made significant progress in improving the efficiency of aid delivery. However, there are some limitations to this regionalization strategy.

"66% of the disaster response is related to small or middle scale emergencies, most of them recurrent"

Silent disasters campaign [START_REF] Barrena | Mesa redonda con embajadores en Panamá[END_REF] The rise in humanitarian need is significant at all scales, including small-and medium-scale disasters. However, considering that only 10% of large disasters become news headlines [START_REF] Barrena | Mesa redonda con embajadores en Panamá[END_REF], and that 66% of disaster operations are for small and medium disasters, HOs struggle to get funds because of the lack of media coverage.

These so-called silent disasters are often recurrent, affecting the same region several times. In some areas, droughts occur regularly with shorter or longer breaks in between. Other recurring disasters are hurricanes (e.g. Haiti was affected by four of them in the course of 2008) or floods (e.g. Pakistan was affected in 2010, 2011 and 2012) [START_REF] Ferris | The year of recurring disasters: A review of Natural Disasters in[END_REF]).

In the last few years, different models of shared and common service provision have emerged in the HSC context. The main objective of these approaches is to improve the cost efficiency of the regional structures. Examples are the IFRC or UNHRD logistic network, which offers specialized HSC services to the humanitarian community. These recent changes have contributed to rationalizing HSCs and meeting increasing needs, but are not sufficient [START_REF] Laguna Salvadó | A study on the sub-regionalization of Humanitarian Supply Chain: the IFRC case[END_REF]. For instance, the economic sustainability to maintain these structures is still a challenge, and there is also room for improvement in terms of effectiveness.

2. The term sustainability has been widely used in a broad range of disciplines and contexts, but in the context of disaster response it has been given little attention. This is not surprising considering that "alleviating human suffering" is seen as a priority and comes first regardless of social, environmental and other costs [START_REF] Oloruntoba | Chapter 3: A Planning and Decision-Making Framework for Sustainable Humanitarian Logistics in Disaster Response[END_REF]. In the literature it is also argued that any HSC system is (somehow) a sustainable system since it contributes to saving lives and improving the living conditions of the population. Nonetheless, the same author rejects the argument by stressing the fact that SHSCs are conditioned by pursuing direct sustainability objectives while general HSCs may indirectly serve the purposes of sustainable development [START_REF] Klumpp | Humanitarian Logistics and Sustainability[END_REF].

At the top management level, HOs have already been involved in the development of sustainable behavior, as the declaration below illustrates. However, today, it is still a high-level statement, and HSCs do not have the tools to manage a sustainable management approach.

"We happily endorse the 2030 Agenda, and our network stands ready to partner with governments, UN agencies, civil society, the corporate sector and communities themselves to turn this ambition into a reality."

-IFRC Secretary General, Elhadj AS SY New York, 25 September 2015

The trends of increased globalization in the commercial SC have assisted logistics and SCM activities, but they have also been detrimental from a sustainability perspective [START_REF] Grant | Sustainable Logistics and Supply Chain Management: Principles and Practices for Sustainable Operations and Management[END_REF]. However, the commercial sector has understood the competitive advantage of considering sustainability, as illustrated by "green" marketing, or Corporate Social Responsibility programs: when seeking to improve the environment, and social and economic performance, companies act in their own interests, in the interests of their stakeholders and in the interests of society at large [START_REF] Sisco | Supply Chain Sustainability, a practical guide for continuous improvement[END_REF]. Sustainability has been identified as one of the biggest opportunities for doing business for decades [START_REF] Hart | Beyond greening-Strategies for a Sustainable World[END_REF]. It has become an approach to both ensure long-term business viability and to obtain a "social license" to operate (integrity of a brand), and therefore, to enhance a competitive advantage [START_REF] Kunz | Sustainable humanitarian supply chain management -exploring new theory[END_REF].

The evolution of public opinion expectations (donors) suggests that sustainability will also have to be considered in the coming years for HOs seeking a competitive advantage. Sustainable Humanitarian Supply Chain (SHSC) implies innovative, socially responsible and proactive decision-making by all the stakeholders. According to [START_REF] Oloruntoba | Chapter 3: A Planning and Decision-Making Framework for Sustainable Humanitarian Logistics in Disaster Response[END_REF] sustainable decision-making must:

• Minimize negative impacts;

• Enable long-term maintenance of community wellbeing; and

• Maintain a balance between life-saving, social, ethical, environmental and economic goals.

Les tendances à la mondialisation croissante dans le commerce SC ont aidé les activités de logistique et de gestion de la chaîne logistique, mais elles ont également été préjudiciables du point de vue de la durabilité [START_REF] Grant | Sustainable Logistics and Supply Chain Management: Principles and Practices for Sustainable Operations and Management[END_REF]. Cependant, le secteur commercial a compris l'avantage concurrentiel de la durabilité, comme en témoignent les programmes de marketing «vert» ou de responsabilité sociale des entreprises: lorsqu'ils cherchent à améliorer l'environnement et les performances sociales et économiques, les entreprises agissent dans leur propre intérêt. intérêts de leurs parties prenantes et de la société en général [START_REF] Sisco | Supply Chain Sustainability, a practical guide for continuous improvement[END_REF]. La durabilité a été identifiée comme l'une des plus grandes opportunités pour faire des affaires depuis des décennies [START_REF] Hart | Beyond greening-Strategies for a Sustainable World[END_REF]. C'est devenu une approche à la fois pour assurer la viabilité à long terme de l'entreprise et pour obtenir un «permis social» (intégrité d'une marque), et donc pour renforcer un avantage concurrentiel [START_REF] Kunz | Sustainable humanitarian supply chain management -exploring new theory[END_REF].

L'évolution des attentes de l'opinion publique (donateurs) suggère que la durabilité devra également être prise en compte dans les années à venir pour les sociétés à la recherche d'un avantage concurrentiel. Sustainable Humanitarian Supply Chain (SHSC) implique une prise de décision innovante, socialement responsable et proactive par toutes les parties prenantes. Selon [START_REF] Oloruntoba | Chapter 3: A Planning and Decision-Making Framework for Sustainable Humanitarian Logistics in Disaster Response[END_REF], une prise de décision durable doit:

• minimiser les impacts négatifs;

• permettre le maintien à long terme du bien-être de la communauté; et

• Maintenir un équilibre entre les objectifs vitaux, sociaux, éthiques, environnementaux et économiques.

Towards a SHSC

We demonstrated that HSC management has evolved over the past decades from a fire-fighting approach towards a performance-oriented perspective (efficiency and effectiveness). HOs have invested in HSCs in terms of strategy, and this evolution has been accompanied by professionalization, and an increase in skills [START_REF] Jahre | The organisational change of logistics in International Federation of the Red Cross and Red Crescent Societies (Case Study). HUMLOG-NET Project[END_REF]. To sum up, until now, the main objectives of the management of an HSC have consisted in improving competitiveness by effectively managing supply flows, while minimizing costs.

Figure 10 Evolution of HSC performance expectations However, due to the awareness of donors and HOs to global sustainability challenges, the HSC needs to evolve and consider sustainability for near-future operations management. Thus, sustainability is a new paradigm for HSC managers that has been identified as a future requirement to maintain an "order winner 1 " position.

HOs are already concerned about the sustainability of disaster response, but difficulties remain for HSC decision-making to concretely introduce sustainability to their decision processes. Therefore, there is a call for more research that addresses issues of sustainability in HSC planning and decisionmaking [START_REF] Haavisto | Perspectives on sustainability in humanitarian supply chains[END_REF][START_REF] Klumpp | Humanitarian Logistics and Sustainability[END_REF].

This research work focuses on how to support HSC decision-makers to establish and enhance a concrete SHSC system. 1 The terms "order winners" and "order qualifiers" refer to the factors that may lead to competitive advantage and market success.

Research gaps

The literature states that sustainability is still overlooked in humanitarian settings, although it is essential for aligning operational objectives with longer-term objectives of humanitarian action.

Although both practitioners and academics are concerned by HSC sustainability, the state of the art reveals several risks and challenges to enhancing sustainable HSC operations. Therefore, several authors have called for more research to integrate sustainability into humanitarian decision-making [START_REF] Haavisto | Perspectives on sustainability in humanitarian supply chains[END_REF][START_REF] Klumpp | Humanitarian Logistics and Sustainability[END_REF][START_REF] Kunz | Sustainable humanitarian supply chain management -exploring new theory[END_REF].

Gap 1: Difficulties in measuring sustainability

Sustainability approaches are a young topic in the field of SCM. The academic publications have appeared since the year 2000 but they mainly have a qualitative nature. State of the art works show that even though the concern for sustainable SC is widespread, there is a gap between intentions (discourse) and implementation [START_REF] Ashby | Making connections: a review of supply chain management and sustainability literature[END_REF]. They also warn of the gap between management research and management practice.

Following the Triple Bottom Line (TBL) model, it is widely accepted to present sustainability as the balance between environmental, societal and economic dimensions. TBL is a systemic approach developed in the mid-90s by John Elkington to "capture the essence of sustainability by measuring the impact of an organization's activities including its profitability and shareholder values and its social, human and environmental capital" [START_REF] Savitz | The Triple Bottom Line: How Today's Best-Run Companies Are Achieving Economic, Social and Environmental Success --and How You Can Too[END_REF]. It stresses the need to achieve a minimum in performance for the three dimensions. However, there is no consensus regarding the trade-offs and synergies across the economic, environmental and social objectives in a humanitarian context. Moreover, there is not a standard definition for each dimension.

The macro-economic definition of sustainability and the three dimensions can explain sustainable development on a conceptual level, but do not provide much guidance on how sustainability shall be addressed in the context of HSC operations.

Gap 2: Planning shortcoming

To improve sustainable operations, decision-makers need to evaluate the impact of their decisions on TBL dimensions. The role of anticipating the impact of decisions is the job of planning. "Planning supports decision-making by identifying alternatives of future activities and selecting some good ones or even the best one" [START_REF] Stadtler | Supply chain management and advanced planning--basics, overview and challenges[END_REF].

However, the HSC context is characterized by a lack of structured planning processes [START_REF] Haavisto | Perspectives on sustainability in humanitarian supply chains[END_REF]. Overlooking planning results in a lack of coordination and inefficiencies such as the bullwhip effect or distribution delays, and it is a barrier to aligning operations with sustainable objectives.

Gap 3: Lack of adequate Decision-support Systems

On the commercial SC management side, planning processes are supported by decision-support systems such as ERP (Enterprise Resource Planning), TMS (Transportation Management System), WMS (Warehouse Management System), and more recently, APS (Advanced Planning System). Therefore, developing adequate HSC planning decision-support systems may enable decision-makers to improve performance, and eventually consider sustainability challenges (Hella [START_REF] Abidi | Humanitarian supply chain performance management: a systematic literature review[END_REF].

A decision-support system is generally defined as "an interactive computer-based information system that is designed to support solutions on decision problems" [START_REF] Liu | Integration of decision support systems to improve decision support performance[END_REF]. In Operations Management (OM), decision-support systems are often based on Operational Research (OR) approaches.

In disaster management, there is an increasing recognition of the need for study of OR applicability.

Although much research has been conducted on developing OR models to support HSC decisionmaking, just a few have a real impact in the field (Laguna Salvadó et al. 2015). [START_REF] Holguín-Veras | On the unique features of post-disaster humanitarian logistics[END_REF] highlights the need for more research on specific OR models (routing, inventory allocation, planning) in humanitarian settings: "…as a result of the unique and complex features of Humanitarian Logistics -which are significantly different from the commercial setting -there is an urgent need for analytical tools that capture such complexity and enable disaster responders to determine the best course of action."

Research Statement

Addressing the sustainability of an HSC is a young subject of discussion, which deserves the attention of the academic community to solve the increasing scientific challenges. Today, very little research work has addressed the specific gaps that HSC -decision-makers have found in concretizing an SHSC.

Difficulties in measuring sustainability, planning shortcomings and a lack of adequate decision-support systems have been identified as the main practical gaps from an Operations Management perspective. Moreover, in the HSC research domain, there is still a gap between research proposals and field implementation. To contribute to bridging these gaps, it is fundamental to have a clear understanding of the HSC setting, and to build solutions with a strong, field-based hypothesis. Therefore, the objective of this research work is to address the following research questions:

RQ1: How to formally conceptualize what an HSC is?

The HSC can be described as a collaborative system, where many actors and stakeholders interact to achieve the ultimate goal of alleviating human suffering. To improve the overall performance of this system, it is essential to have sufficient knowledge of it. Previous research work has proposed models able to define such knowledge, but only partially and in a way that does not allow reusability. The difficulty remains in having a shared and sufficiently conveyed conceptualization of the HSC system for first, understanding, and second, improving system behavior. This research question is interesting for both academics and field practitioners, as it should contribute to knowledge sharing and communication among practitioners themselves, and between practitioners and academics. It also may contribute to academia by facilitating field research design and cross-case and longitudinal study analysis.

RQ2: What does sustainability mean in HSC operations and how can it be assessed?

Sustainability is a broad multidimensional concept. Given the increase in scientific publications considering sustainability in many disciplines, it can be considered a trendy topic. Nonetheless, the level of granularity of sustainability assessments is typically contrary to measurement transferability. It appears that sustainability assessments either remain at high-level definitions, aggregations and objectives that do not support tactical and operational decision levels, or are closely linked to the interests or needs of particular sectors and decision-makers. Thus, in low decision-making levels, each sector of activity has to find a reliable way to quantify sustainability. Even if HOs have already subscribed to the sustainability agenda, it is still difficult to concretize what a sustainable performance is at the different HSC decision levels. This research question is relevant for academics as it aims to contribute to bridging the gap between the general concepts of sustainability and the HSC research domain, and also for practitioners as it aims to enable the assessment of sustainability in HSC decision-making processes.

RQ3: How to support decision-makers consciously and systematically making sustainability trade-offs and exploring consequences?

To enhance sustainable operations, decision-makers may benefit from considering the sustainability assessment "a priori", in the planning process. To plan sustainable operations, -decision-makers need to make sustainability dimension trade-offs transparently, based on their knowledge of the situation (organizational objectives and interests, expertise, etc.), and being aware of the consequences. However, decision-support systems that address trade-offs are not aligned with practitioners' requirements in terms of skills and time. Users typically have to deal with abstract and complex weightings and dependencies, so it may represent a barrier for the acceptability of decision-support systems in the field. The challenge here is then to design and develop a decision-support system approach that contributes to bridging the gap between academic proposals and field usability. This research direction is interesting for academics as it aims to make accessible the use of OR methods for non-experts, and therefore it aims to improve systematically HSC planning processes.

The IFRC application case

This thesis has been conducted in close relation with the IFRC HSC, and especially, with the American and Caribbean Regional Logistics Unit (A&C RLU). This section presents the IFRC organization, and provides an overview of the A&C RLU.

The Red Cross and Red Crescent movement

The International Red Cross and Red Crescent Movement is a global humanitarian network of 80 million people that helps those facing disaster, conflict and health and social problems. It consists of the ICRC, the IFRC and the 190 Red Cross and Red Crescent National Societies (NS).

Humanity, impartiality, neutrality, independence, voluntary service, unity and universality are the key principles to the International Red Cross and Red Crescent Movement distinct identity. These seven Fundamental Principles provide an ethical, operational and institutional framework to the work of the Red Cross and Red Crescent Movement. They are at the core of its approach to helping people in need during armed conflict, natural disasters and other emergencies.

The ICRC, the Federation and the National Societies are independent bodies. Each has its own individual status and exercises no authority over the others.

Figure 11 The Red Cross and Red Crescent International Movement

The ICRC is an impartial, neutral and independent organization whose mission is to protect the lives and dignity of victims of war and internal violence and to provide them with assistance.

The IFRC coordinates and directs international assistance following natural and man-made disasters in non-conflict situations.

The IFRC works with NSs in responding to catastrophes around the world. Their reliefs operations are combined with development work, including disaster preparedness programs, health and care activities, and the promotion of humanitarian values.

National Societies

The IFRC Humanitarian Supply Chain network strategy

The Logistics, Procurement and Supply Chain Management (LPSCM) Department of the IFRC provides humanitarian logistics services 1 . Its key mission is to support the core work of the Red Cross Red Crescent network. It also offers these services on a non-profit basis to third parties in the humanitarian sector and to governments. The worldwide activities of the IFRC LPSCM focus on three strategic objectives:

1. Support the enhancement of National Society logistics capacities 2. Increase the IFRC's logistics capacity to deliver logistics services for preparedness and operational activities 3. Provide agreed logistics services to third parties in the humanitarian sector

The mission of the IFRC HSC upstream network is composed of five Regional Logistics Units (RLU) strategically located in Panama, Kuala Lumpur, Nairobi, Beirut and Budapest, to respond to humanitarian needs.

Moreover, sub-regional logistics units (LU) based at the country level with the support of the NS are connected to each RLU. This second layer, which responds to the need to get closer to beneficiaries, is still under deployment. LU stocks are located inside NS warehouses as part of the RLU contingency stock. The operational mode is linear: the regional hub manages all warehouse procurement, and each sub-regional warehouse distributes only to internal country needs.

Figure 12 Linear sub-regional design

The sub-regional approach aims to add or reinforce a logistics capacity layer closer to the beneficiaries, while maintaining the RLU and its advantages. This enables the IFRC to:

• Improve response time, thanks to shorter geographical distance. Moreover, involving (or empowering) the country level on preparedness contributes to improving disaster response. • Enhance local capability, which may also encourage local sourcing with a positive impact on the local economy. • Re-design the HSC; this is an opportunity to improve the cost-efficiency of the system. 1 It used to be called Global Logistic Services (GLS) up until 2016 However, the linear approach (stocks coming from the suppliers to the beneficiaries through regional and sub-regional hubs) continues to require high contingency stock. As long as the RLU strategy has not been reviewed, the regional contingency stock coverage increases if we take into account the hub and sub-regional stocks, which was already overestimated.

A&C RLU activity

The American continent is a good example of recurrent disasters. Looking at the Global Humanitarian Assistance Report 2015 [START_REF] Swithern | Global Humanitarian Assitance report 2015[END_REF], none of the American countries is in the top 10 of affected countries nor in that of the international humanitarian assistance recipients (2004 to 2013).

The crises affecting America are mostly natural disasters with recurrent patterns such as El Niño [START_REF] Charvériat | Natural Disasters in Latin America and the Caribbean: An Overview of Risk (SSRN Scholarly Paper[END_REF]. These small-and medium-scale crises constitute a very high percentage of emergency interventions by HOs [START_REF] Vargas Florez | A decision support system for robust humanitarian facility location[END_REF]. Individually, each generates only a local impact, where there is no need to mobilize a massive amount of relief items.

In 2014, the A&C RLU launched 16 Disaster Response Emergency Funds (DREF) for smallmagnitude disasters and three appeals (large-scale disaster funding procedures) (Figure 13). If we extrapolate the trend of the last 15 years, it seems that the number of small-to-medium response operations will tend to rise. This pattern has a strong impact on the activity of the A&C RLU, which is sized for large-scale disaster responses. Each RLU has a contingency stock to assist 5,000 families, but the activity in a standard year can be considered low in America.

Cost recovery

The working costs of RLUs have been based since 2012 on full-cost recovery (assets and infrastructure). This mechanism charges the costs of (i) supplying goods and services and (ii) covering overheads related to the logistics services management. In a standard year, responses to crises do not generate enough rotation to cover the fixed cost of RLUs (IFRC, 2012).

The IFRC's strategy consists mainly in providing a panel of specialized services like procurement, warehousing and distribution to third parties. For the IFRC, the main customers of these services are the Partner NS and some international organizations such as Oxfam. Partner NSs are NSs from developed countries that invest part of their funds on prepositioning relief items in addition to the RLU contingency stock. But even though this provides some extra revenue, it is not sufficient to ensure the economic long-term sustainability of RLUs like those of the A&C.

Operations

The IFRC has announced that it aims to reduce response time to 48 hours [START_REF] Grenade | [END_REF]. Although with regionalization, emergency items are closer to the field than they used to be, this aim is still out of reach. By locating stocks closer to disaster-prone areas, transport time can be reduced.

Beyond risks to stock, the supply trigger procedures and coordination between actors can also cause delays. For the IFRC, an RLU cannot start any procurement activity without a formal request from the field assessment team. And this can take from several days to some weeks. An IFRC Procurement Officer (Panama, September 2015) explained a case where the request took three weeks to be validated. There was a crisis in the West Indies and the French Red Cross responded -instead of the IFRC -with their contingency stock placed at Guadeloupe island (not part of the IFRC contingency stock) because the RLU was waiting for the request validation. Practitioners consider that these recurrent delays are mainly due to cultural distances (no knowledge of the country), as Jahre has pointed out: "even if RLUs are geographically closer to the regions often struck by disasters, they are still too far from the local communities with regards to culture, knowledge and geographical distance … they are stuck in the middle".

Procurement strategy

Today, the procurement process of the IFRC is based on a competitive bidding process. In addition to the framework agreements with international suppliers that provide part of the standard contingency stock (e.g. blankets, jerry cans, kitchen sets, etc.). For regular replenishment (non-emergency), items are sourced internationally, mainly from Asia, due to the competitive cost even though there are long lead-times.

However, local sourcing stimulates local economies and reduces transportation costs. Moreover, local shipments require less documentation than international consignments that can stay blocked at customs for long periods. Despite these advantages, some items are difficult to be sourced at the country level as long as the procedures to purchase are strict to maintain standards. And at the regional level there is a lack of knowledge and visibility of the local sourcing capacity (quality and availability) because they are too far geographically and also culturally.

Research Methodology

The objective of this research project is to develop concrete solutions to support sustainable decisionmaking in HSCs with a scientific, applied research 1 approach. Enhancing sustainable operations is an interdisciplinary matter as broad as the subject of 'sustainability': engineering sciences, economic sciences and social sciences are concerned to some extent. Here, we identify and address the problem with an engineering science point of view and methodologies.

The main difficulty is still to develop decision-support systems adequate for humanitarian needs and uses. One of the biggest criticisms in the HSC literature review is the barrier between scientific proposals and field acceptance [START_REF] Holguín-Veras | On the unique features of post-disaster humanitarian logistics[END_REF]. Several authors conclude that fieldgrounded research should allow for building more adequate proposals. (Kunz et al. 2017) highlight the importance for both academics and practitioners to "jointly define research projects".

In this context, field-oriented research is a requirement for adequately developing applied research proposals to enhance an SHSC. However, it is not a trivial matter to classify a particular type of research into a single research methodology paradigm [START_REF] Laurencelle | Abrégé sur les méthodes de recherche et la recherche expérimentale[END_REF]. In the SCM literature, the most popular research methodologies are Model Building, Surveys, Case Study Research and Action Research [START_REF] Seuring | Is there a right research design for your supply chain study[END_REF].

Our proposed research methodology fits in with the philosophy of Action Research, which has been identified as valid and relevant in the context of SCM [START_REF] Müller | Action research in supply chain management-an introduction[END_REF]. Briefly, "Action Research uses a scientific approach to study the resolution of important social or organizational issues together with those who experience these issues directly" [START_REF] Coughlan | Action research for operations management[END_REF]. However, the Action Research paradigm has been criticized by some authors, mainly for the positivistic paradigm position. The principal difficulty in validating Action Research is the lack of impartiality on the part of the researcher and the view of Action Research as a "consulting process masquerading as research" [START_REF] Coughlan | Action research for operations management[END_REF]. The research process has been carried out in close relation with the IFRC to identify the problem, which explicitly shared the interest in moving towards an SHSC, and has contributed by providing information and feedback on our proposals. However, they have not led the research process and we have been free to address the problems we found relevant from both practical and academic points of view.

Given the nature of the research questions, which aim to improve the performance of an organization, Design Sciences' research methodologies are also relevant (Figure 15). Figure 15 The general methodology of design research [START_REF] Järvinen | Action Research is Similar to Design Science[END_REF] Design Sciences belongs to the Information Systems domain, which is at the confluence of people, organizations, and technology [START_REF] Holmström | Bridging Practice and Theory: A Design Science Approach[END_REF]). Design Sciences is a problem solving process through the building and evaluation of artifacts designed to meet the identified business need. The concordance between the characteristics of Action Research and Design Sciences has been highlighted by [START_REF] Järvinen | Action Research is Similar to Design Science[END_REF], who concludes that they should be considered similar research approaches. Both approaches have 5 similar steps, illustrated in Figure 15 with the design sciences approach.

In summary, to contribute to bridging the gap between practitioners and academics we followed an inductive research approach. Inductive, because the problem and the solutions are both grounded in field research, with the aim of creating a general hypothesis (Figure 16):

Figure 16 Research methodology overview

Field grounded motivations:

This is a critical step, as the relevance of the proposals rests on the capacity to identify a relevant problem for practitioners. The method used to identify a business challenge together with field practitioners is field data gathering, analysis and feedback with practitioners.

For data gathering, we used both secondary and primary data from HOs. Secondary data was mainly found on the Internet, and consists of annual reports and operations updates. For the primary data, we conducted a field research campaign and used semi-structured interviews, observations and access to HO documents.

A&C Field Research

Where? IFRC A&C RLU Office (Ciudad del Saber, Panama) & Warehouse (Panama Pacific Airport)

When? 10 days in September 2015

Who? One field researcher on site and two in the "back office"

What? The focus was on the upstream HSC business processes. The aim was to identify decision-makers' challenges.

Prior to the field research: Interviews with the Logistics Development Coordinator

On site: Observation of and semi-structured interviews with six IFRC A&C RLU team members.

Afterwards:

The observations and data analysis helped to draw a picture of the business processes, and to identify the opportunities and challenges addressed in this thesis.

Gap identification:

Once the business stakes were defined, this step consisted in identifying the scientific challenges related to the business problem. To do so, it was necessary to know the state of the art, so we could build the contributions on existing evidence. The results of both the field research, mixed with the literature review, led to finding the three research questions presented previously.

The literature review was focused on past research work, and specific keywords to identify relevant contributions.

Building scientific contributions and implementation:

This step consisted in conducting in-depth work to build original methods or to adapt existing ones (for previously addressed scientific challenges) to answer the research questions and address the business stakes. Moreover, a prototype of each contribution is developed and validated with a proof of concept based on field research data.

Evaluation & conclusions

Each proposal has been implemented with a realistic case study based on the A&C RLU. Discussion with practitioners allowed us to identify a scope relevant for this purpose and to build the case based on data from the field.

Manuscript Structure

With the objective of supporting decision-makers to enhance an SHSC, the contributions are structured following a 3W story line: What? Why? How?

The first step (what?) is to describe the system that we want to have an influence on. Therefore, the research question addressed in Chapter 2 is:

RQ1: How to formally conceptualize what an HSC is?

Chapter 2 discusses the background on HSCs, SCs and disaster management collaborative systems knowledge structuring with reference models and metamodels, and proposes a specific metamodel for HSC to support field data gathering and knowledge structure. The concepts gathered during field research, added to the HSC core literature, have allowed an original and innovative HSC metamodel to be built. Model instances built from this metamodel provide potential input for developing adequate decision-support systems, as well as for supporting the design and analysis of field-oriented research.

We illustrate the proposal with an example based on the A&C RLU.

The second step (why?) is to describe the decision-maker pursued objectives pursued by decisionmakers. The research question addressed in Chapter 3 is thus:

RQ2: What does sustainability mean in HSC operations and how can it be assessed?

In Chapter 3 we give an overview of the significance of sustainability, and how it has been addressed in the literature and in practice. Previous research has shown that the challenge for HOs is to consider a sustainability perspective in their decision-making processes. We propose a performance measurement definition. Based on field research with the A&C RLU and a literature review on humanitarian performance measurement and sustainability, we define a set of criteria, objectives and key performance indicators that translates sustainability concepts to the context of HSC. Built on the TBL philosophy, the environmental and social dimensions are added to the economic one. The aim of Chapter 3 is to define the objectives of HOs to enhance SHSC operations. The framework use is illustrated with a maturity model of the SHSC.

The third step (how?) is to make sustainable decisions. Chapter 4 addresses the challenge of introducing sustainability objectives to the HSC decision-makers process:

RQ3: How to support decision-makers consciously and systematically making sustainability trade-offs and exploring consequences?

In Chapter 4, an OR approach is proposed to define sustainable planning "a priori": to anticipate outcomes with a decision-support system. To build the decision-support system, we model the SHSC Master Planning network flow problem, and propose an algorithm which ensures the decision-maker's central role. We illustrate the proposal with a use case based on the A&C RLU. This contribution has the originality of addressing both the challenges to improving the planning processes and to including sustainable objectives in the context of HSC.

Finally, in Chapter 5 we discuss the conclusions and the perspectives of this research project.

Chapter II. HUMANITARIAN SUPPLY CHAIN METAMODELING 1. Towards an explicit conceptualization of the HSC

As discussed in the introduction, to improve the performance of the HSC, one of the challenges is to consider the complexity of the field. A shared, reusable and sufficiently conveyed view of the HSC domain may contribute to facilitating knowledge generation (field research data collection and analysis) and communication (between both practitioners and academics).

"The more we know about a given domain and the more precise we are in representing it, the bigger the chance that we have of constructing computational systems and services that are consistent with the reality of that domain." (Guizzardy, 2005).

This part of our research aims to provide an explicit conceptualization of the HSC domain to build a bridge between "real world" data and the knowledge needed for decision-making, as illustrated in Figure 18. We consider here "data" as the raw data without contextualization, "information" as an understanding of the relationships among the domain data (HSC in this concrete case), and "knowledge" as the use of information to make decisions. From a philosophical point of view, a concept is "an idea or mental image that corresponds to some distinct entity or class of entities, or to its essential features, or determines the application of a term (especially a predicate), and thus plays a part in the use of reason or language" (Oxford Dictionary). A conceptualization (as well as an abstraction) is described as "an immaterial entity that only exists in the mind of a user or a community of users of a language" [START_REF] Guizzardi | Ontological Foundations for Structural Conceptual Models[END_REF]. Ullman's triangle (1972) represents the relationships between a thing in reality, its conceptualizations and a symbolic representation of this conceptualization (Figure 19).

Figure 19 Adapted from Ullman's triangle Thus, to build an explicit conceptualization of the HSC, we need to represent the concepts of the domain with symbols that refer to the things in the field. Guizzardy ( 2005) stated that a model is the abstraction of a given portion of reality articulated according to a domain conceptualization. A model can be used either to document existing situations (descriptive mode) or to describe situations that have yet to eventuate (prescriptive mode) [START_REF] Henderson-Sellers | Object-Oriented Metamethods[END_REF]. Within the Information Systems field, conceptual modeling is defined as a formal description of some aspects of the physical or social reality for understanding and communicating (Wand et al. 1995).

According to (Kung and Solverg, 1986), the main roles of conceptual models are [START_REF]INDICATORS 2. EFFICACY OPTIMIZATION 3. SOCIAL IMPACT OPTIMIZATION 4. ECONOMY IMPACT OPTIMIZATION 5. ENVIRONMENT IMPACT OPTIMIZATION 6. EFFICACY CONSTRAINT @for(MatWT(w,t)[END_REF] supporting communication between developers and users, (2) helping analysts understand a domain, (3) providing input for the design process, and (4) documenting the original requirements for future reference. In addition, the use of conceptual models allows static phenomena (things and their properties) and dynamic phenomena (events, processes) of a domain to be represented (Wand and Weber, 2002). Formal (conceptual) models are built using more general models, also referred to as metamodels, or modeling language.

A metamodel then is the 'model of models': an explicit model of the constructs and rules needed to build specific models within a domain of interest [START_REF] Gaševic | Model Driven Architecture and Ontology Development[END_REF]. It (i) describes a domain that is representative of more than one instance in a less abstract domain, and (ii) is the core of a modeling language used to describe those instances [START_REF] Bataille | Métamodélisation et ingénierie des systèmes d'information[END_REF][START_REF] Henderson-Sellers | Bridging metamodels and ontologies in software engineering[END_REF]). If we consider that no modeling is possible without some sort of metamodel (explicit or implicit), this also becomes true for metamodeling, as it also needs its own methods and tools, which, in turn, can be described one level higher in metamodels (and so on).

Moreover, metamodels are closely related to ontologies. In the Information System literature, an ontology is usually referred to as a formal, explicit specification of a shared conceptualization for a domain of interest [START_REF] Gruber | A translation approach to portable ontology specifications[END_REF] which may be used as a unifying framework [START_REF] Uschold | Ontologies: Principles, methods and applications[END_REF]. It describes knowledge that can be used and reused to facilitate the comprehension of concepts and relations in a given domain as well as the communication between different domain actors.

When using the ontology concept for engineering purposes, two main categories are typically considered (Henderson, 2011):

• Domain ontologies, which are used to create common vocabulary for a specific application domain and are vital to ensuring that elements in the model have well-defined semantics;

• Meta-ontologies, which are equivalent to the metamodel of a modeling language and thus encapsulate the concepts needed for creating domain ontologies.

Over the past decades, there has been tremendous growth in metamodeling and ontology development (Henderson-Sellers and Bulthuis, 2012). In the literature both concepts often seem to be used indistinctly. Even if metamodels and meta-ontologies are not necessarily equivalent there is a fuzzy link between them. Metamodels can have ontological properties while treating them as a representation of the language underlying a worldview. Guizzardi conducted an in-depth study concerning the relationship between language, conceptualization metamodels and ontologies [START_REF] Guizzardi | Ontological Foundations for Structural Conceptual Models[END_REF]. We conclude that to support the explicit conceptualization of a domain of interest, here the HSC, a formal metamodel should provide a high-level framework to define model concepts and its relationships.

Research direction

In order to address the research question, the center of this contribution is to specify an HSC metamodel (or meta-ontology), which is a set of terms naming concepts (classes) and relations. The metamodel should formally represent the abstract domain-conceptualization. The main objective is to use the metamodel to support analysts (academics and practitioners) in the creation of HSC conceptual models (or sets of organized data), or instances of the metamodel. Figure 20 shows the explicit conceptualization approach.

Figure 20 A metamodel as an explicit representation of a domain (inspired from [START_REF] Guizzardi | Ontological Foundations for Structural Conceptual Models[END_REF] In the sections below, an overview of the background and recent works is provided (section 2), related to the development of metamodels (including meta-ontologies) and referent models in Disaster Management, Supply Chains and HSC domains. Second, the main contribution of this chapter is presented: the HSC metamodel. Third, the use of a metamodel is illustrated in the IFRC case. This proof of concept has been built on the data gathered during the field research of IFRC A&C RLU. Finally, some discussions and further research directions are presented.

Dom ai n -Con ceptual izat ion

Case

Background and related works

HSC has roots in both Disaster Management and SC. It integrates concepts and relationships coming from both domains (Figure 21). The HSC operates under the conditions of humanitarian disasters, therefore, (i) the objectives (life and death vs. profit and loss), (ii) the high levels of demand uncertainty, (iii) the SC formation (ad-hoc downstream design and implementation), and (iv) the changing operational conditions, make HSC part of Disaster Management, and a specific case within the SC. These specificities contribute to the fact that methods and best practices from SC are not necessarily appropriate for the HSC, and vice versa [START_REF] Charles | An enterprise modelling approach for better optimisation modelling: application to the humanitarian relief chain coordination problem[END_REF].

In this section we provide an overview of metamodels and reference models in the three aforementioned areas, to identify the opportunities and limitations of current research. Reference models (or standards) are interesting for the purposes of building a shared and explicit metamodel of the HSC because they provide well-accepted and structured frameworks for concepts related to the domain.

Even if the relationships are not explicit, they may provide validated concepts used in the domain.

Figure 21 The Humanitarian Supply Chain domains

Humanitarian Supply Chain domain

In the specific HSC literature, we can identify different reference models that contribute to a better understanding of the HSC. [START_REF] Kovács | Humanitarian logistics in disaster relief operations[END_REF] proposed one of the first models related to humanitarian logistics. It provides a highly conceptual framework that distinguishes actors, phases and logistical processes of disaster relief logistics. [START_REF] Blecken | Supply chain process modelling for humanitarian organizations[END_REF] proposed a specific reference framework for HSC, based on commercial SC reference models. It is organized in two dimensions. The hierarchical breakdown organizes SC tasks at strategic, tactical and operational levels. The structural breakdown organizes SC tasks related to assessment, procurement, warehousing and transport (Figure 22). These two dimensional frameworks help to classify the business tasks that are performed within an HSC.

Disaster Management Supply Chain

Humanitarian Supply Chain

Figure 22 Blecken reference task framework model [START_REF] Blecken | Supply chain process modelling for humanitarian organizations[END_REF] Franke et al. ( 2011) combine Blecken's reference process model with a tool for coordinating the design, run-time and monitoring of inter-organizational humanitarian logistics processes. Both Blecken's and Franke's reference models are focused on the business process conceptualization of the logistics operations while the aim of our research work is to consider a wide view of the HSC system. Nonetheless, these contributions are relevant for our problem as they can support the identification and the definition of process concepts to be included in the HSC metamodel. However, they do not formalize a metamodel as such, which limits their reusability.

Overstreet et al. ( 2011) carried out a literature review on humanitarian logistics models. None of the models discussed addresses the challenge of data gathering and structuring through a metamodel.

Many mathematical models have been developed in the context of OR dedicated to HSC [START_REF] Altay | OR/MS research in disaster operations management[END_REF][START_REF] Van Wassenhove | Humanitarian aid logistics: supply chain management in high gear †[END_REF][START_REF] Galindo | Review of recent developments in OR/MS research in disaster operations management[END_REF]. They are typically case-based, and do not provide any conceptual metamodels. However, these models are still interesting because they provide concepts and definitions of the HSC domain and relationships.

Supply Chain domain

In the commercial SC domain, many reference models have been developed; they mainly focus on the explicit conceptualization of business processes and activities in order to study their current practices and improve on them. They allow the processes to be conceptualized from several viewpoints and at various abstraction levels. There are many process modeling techniques and tools in the literature [START_REF] Alotaibi | Graphical business process modelling standards, techniques and languages: a literature review[END_REF][START_REF] Min | Supply chain modeling: past, present and future[END_REF].

The most famous SC reference model is probably the Supply Chain Operations Reference (SCOR) [START_REF] Zhou | Supply Chain Integration and the SCOR Model[END_REF]. It structures the inter-organizational SC business processes around six top-level management processes: plan, source, make, deliver, return and enable. These levels are split into sublevels.

Another reference model for representing an SC, the value stream in this case, is Value Stream Mapping (VSM). It is related to the Lean philosophy which begins by learning about the different kinds of waste that can affect the system (Womack and Jones, 1996). Waste is anything that adds cost or time without adding value (Tapping et al., 2002). VSM is a visual representation of a workflow with quantitative data at each step of the process. Its principle consists in breaking down a process value stream along different operations (at a company scale) or along different installations (at a network scale) in order to analyze each activity that contributes to overall performance (Womack and Jones, 1996). Standardized pictograms are used to illustrate each activity.

Metamodeling approaches have also started to emerge. Given the strong competitiveness, the success of enterprises is strongly related to their ability to collaborate with other enterprises [START_REF] Chan | Special Issue -Applications of reference models for supply-chain integration[END_REF][START_REF] Daniele | An ontological approach to logistics[END_REF]. This emphasizes the need to have a common understanding of the systems, both within the boundaries of the organization and with other organizations. [START_REF] Daniele | An ontological approach to logistics[END_REF] identify 5 requirements to consider in SC metamodels, which are also relevant for the HSC context:

• Activity: represents the relevant actions to achieve logistics and provide value for customers.

• Actor: denotes individuals or companies that could be a provider or demander of activities and operates these activities on related resources.

• Physical Resource: denotes the objects that are used in the activities.

• Location: denotes the geographical area used to define the place relevant for the activities.

• Time: denotes the start/end time or the time interval associated with activities.

In addition, [START_REF] Grubic | Supply chain ontology: Review, analysis and synthesis[END_REF]) made a review and analysis of metamodels dedicated to SC. They identify a set of gaps that have to be considered in future developments. The most relevant ones concerning the HSC metamodels are summarized in Table 4.

Gap

Consequences Relevance for the HSC

The granularity is only at the strategic level.

There is no work at tactical and operational levels, despite their importance.

To understand the overall HSC behavior, different decision levels must show up Lack of metamodels grounded in empirical or field research

The methodological approaches adopted are too remote from real SC, thus, the proposals are oriented to an organizational view of reality rather than with reality itself

The objective of the HSC metamodel is to conceptualize the "real HSC world", not to conceptualize how it should be.

Lack of knowledge of dyadic relationships or external SC (interoperability).

A very limited view of the scope of the SC.

To understand overall HSC behavior, relationships among stakeholders must show up Very few metamodels have formally represented and acknowledged the importance of time.

A static view of the SC metamodel prevails.

The HSC evolves in a dynamic environment

More recently, and in the context of the European research project called C2NET Given the parallels between the HSC and the SC domain, concepts and relationships from the existing SC metamodels cited in this section can instigate an HSC domain metamodel.

Disaster Management domain

In the larger domain of crisis and disaster management, along with the open data movement and the semantic web, a lot of interest has been dedicated to developing crisis and disaster management metamodels [START_REF] Aaltonen | Multi-ontology, sense-making and the emergence of the future[END_REF][START_REF] Asadi | ICT solutions supporting collaborative information acquisition, situation assessment and decision making in contemporary environmental management problems: the DIADEM approach[END_REF][START_REF] Bénabén | A metamodel and its ontology to guide crisis characterization and its collaborative management[END_REF][START_REF] Comes | Bringing Structure to the Disaster Data Typhoon : An Analysis of Decision-Makers ' Information Needs in the Response to Haiyan[END_REF][START_REF] Imran | Extracting information nuggets from disaster-related messages in social media[END_REF]. Only a few, however, attempt to represent crisis and disaster management information and knowledge structures in reusable form (metamodel). Most of the models in the literature facilitate access to crisis management expertise; however, they have several limitations (Benaben et al. 2016):

• Most of these metamodels are not formalized.

• Most of these metamodels do not provide detail of each crisis management phase.

• These metamodels focus on specific cases. The extraction of general concepts relating to specific types of crises, such as cyclones, is not generalizable.

We focus in the following section on proposals that address these challenges, and which are general enough to be interesting from an HSC domain perspective.

To overcome these limitations, (Benaben et al. 2016) presented a general crisis metamodel and associated ontology to facilitate knowledge sharing and develop advanced crisis management systems.

They structure the metamodel with a perspective of "collaboration". To explicitly conceptualize the crisis response, they consider four knowledge areas: (i) the studied system, corresponding to the subpart of the world impacted by the crisis; (ii) the crisis system, corresponding to the properties of a specific crisis; (iii) the treatment system, corresponding to a description of the abilities of actors who can be deployed in a crisis response; and (iv) the collaborative process, corresponding to a description of the crisis response. In particular, the metamodel's objective is to design the collaboration process. Thus, it identifies a particular partner, the mediator, whose role is to orchestrate the collaboration of other selected partners.

This approach can be generalized to other inter/intra-organizational collaboration situations than crisis responses. For example, it can be applied to virtual enterprise collaboration settings, where different partners share workflows. However, depending on the area of application, the concepts may not be the same. Thus, the proposed metamodel is structured with different layers as described in Figure 23: • A core metamodel relates to the general concepts of collaboration in social systems. This "kernel" is common to all collaborative situations regardless of the application domain;

• A set of layers that helps to define the concepts associated with a particular domain of application with a specific granularity level.

Their approach has been tested and validated, especially through several specific instantiations regarding crisis management applications (civil crises, but not humanitarian disasters), virtual enterprise applications and healthcare applications. Based on this principle, and considering the HSC as part of a crisis response, it is possible to define a specific layer for HSC that would be linked with the existing layer dedicated to the parent crisis management domain.

(Othman and Beydoun, 2010) developed a disaster management metamodel to help access Disaster Management knowledge, which is typically distributed across time, space and people. In contrast to (Benaben et al. 2016), they used existing disaster response models, and ten earlier crisis metamodels (Benaben et al. 2008) to identify the concepts and potential relationships. Moreover, their proposal is structured following the phases of the crisis management cycle: mitigation, preparedness, response and recovery. This approach is interesting because it adds the cyclical dimension of the disaster response; however, there is no relationship established between the different phases of metamodels, and the concepts are too specific for rescue operations.

Another original contribution to Disaster Response knowledge management is the Humanitarian eXchange Language (HXL) Situation and Response Standard [START_REF] Clark | Feasibility of Information Interoperability in the Humanitarian Domain[END_REF]. HXL is a project led by UNOCHA that aims to define data exchange for disaster responses. This is a joint project between academics and practitioners with a knowledge management approach, developed with the specific humanitarian field constraints that may be considered. Data is structured in 4 main topics:

• Geolocalization Information

• Victim Profiles

• Response Actions

• Situation and Evolution

All the reference models and metamodels discussed in this section are complementary and interesting. Concepts and relationships can be considered to be within the HSC domain. However, for building a specific metamodel for the HSC system, some of the concepts are either not relevant (outside the HSC system scope), or not specific enough. The main conclusion here is that the Collaborative System metamodel with the Crisis Management layer can be used as a metamodel for building the specific HSC metamodel.

Humanitarian Supply Chain Metamodel Proposal

As discussed in the introduction, the purpose of the HSC metamodel is to deal with the problem of structuring and sharing the implicit and explicit HSC conceptualization. In the background section it has been highlighted that previous research on Disaster Management and SC domains provide valuable metamodeling and reference model approaches, concepts and relationships that can be integrated into the HSC metamodel.

According to Benaben et al. (2016), collaborative systems can be built on a layered metamodel structure. The core is a metamodel that defines the general concepts of collaboration systems. It is common to all collaborative situations regardless of the application domain. Around the core, a set of layers allows the concepts associated with a particular domain of application to be defined.

Considering that the HSC domain is a child of Disaster Response, the proposal is structured on two complementary layers. The first one relates to generic concepts and relationships in crisis management. The second one relates to the HSC domain, and is based on the knowledge contained in the previous section.

Therefore, considering that the HSC system is a collaborative system, the HSC system metamodel is built as an external layer of a collaborative system core, in the continuity of a Crisis Management layer, which structures the concepts and relationships in Crisis Management [START_REF] Lauras | Towards a better management of complex emergencies through crisis management meta-modelling[END_REF] and [START_REF] Jiang | Meta-Modeling of Collaborative Supply Chain[END_REF]). The Crisis Management layer here becomes a "meta-metamodel", and the core, the "meta-meta-metamodel" of the HSC.

Figure 24 The HSC metamodel layer positioning

The HSC layer integrates SC and specific HSC domain reference models and previous field research (Figure 24). This section presents the HSC layer, which is connected to the Crisis Management layer proposed by (Benaben et al. 2016). First, the system description is given. Next, the metamodel formalization is presented, using UML graphical language, accompanied by precise descriptions, relationships and links to the Crisis Management metamodel.

HSC system description

This section provides an overview of the concepts and relationships to be considered in the HSC system. Most of these concepts have been already discussed in the introduction; however, here we get a structured overview of the HSC system under the four areas of the collaborative systems metamodel: context, objectives, partners and behavior.

As described in (Benaben et al. 2016) a collaborative system can be described with four sub-domains (Context, Partners, Objectives and Behavior) that contain concepts dedicated to the collaboration situation:

• Objective: objectives addressed by the partners.

• Context: components and characteristics of the considered environment, along with related opportunities, threats and risks.

• Partners: resources and the know-how of partners, including capabilities, patterns, instructions, and resources (people, material, information, etc.) and flows (links among capabilities).

• Behavior: characteristics of the collaboration. This package includes the business activities and processes, and associated events.

Objectives

According to [START_REF] Sarkis | Relief supply chain management for disasters: humanitarian aid and emergency logistics[END_REF]), the HSC system encompasses the planning and management of all activities related to material, information and financial flows in disaster relief. Importantly, it also includes coordination and collaboration with supply chain partners, third party service providers (3PL), and across HOs in a complex and dynamic environment. To be successful, the HSC has to be able to respond to multiple interventions, often on a global scale, as quickly as possible and within a short time frame [START_REF] Van Wassenhove | Humanitarian aid logistics: supply chain management in high gear †[END_REF]. The main objective of the HSC is then to satisfy the material humanitarian needs identified in the aftermath of a crisis.

The HSC operates without the market forces of demand and supply regulated through price. "Donors have become particularly influential in prompting HOs to think in terms of greater donor accountability and transparency of the whole HSC" [START_REF] Van Wassenhove | Humanitarian aid logistics: supply chain management in high gear †[END_REF]. Moreover, and as discussed in the introduction, the financial gap gives donors the role of "customers". Therefore, despite the traditional focus on the responsiveness of HSC operations, now, HOs are motivated to measure performance and invest in improving it.

Thus, HOs consider the performance of the operations as an objective. This performance is not universal, and depends on the HO's strategy.

Context

In the HSC literature it is clearly stated that the HSC evolves in a complex environment characterized by:

• The large number of stakeholders interacting in the field.

• A politically volatile climate in which the HSC must operate, which implies issues of safety.

• A high level of uncertainty in terms of demand, supply and environment.

• The possibility of unforeseeable conditions and very short time frames.

This environment adds an element of risk to the enhancement of HO objectives. SC risks refer to the possibility and effects of a mismatch between supply and demand (beneficiary's needs in an HSC context). ''Risk sources are the environmental, organizational or supply chain-related variables that cannot be predicted with certainty and that impact on the SC outcome variables. Risk consequences are the focused supply chain outcome variables like costs or quality" [START_REF] Jüttner | Supply chain risk management: outlining an agenda for future research[END_REF]. The potential mismatch of sources in the HSC is grouped here in three categories of danger:

• Organizational failure: During a crisis response, HOs can be overwhelmed and it can be difficult to apply best practices in terms of collaboration, planning or scheduling. There is evidence of a frequent lack of planning in relief supply chains, resulting in inefficiencies. For example, the overuse of expensive and unsafe air charters, failure to pre-plan stocks, congestion at ports caused by unplanned deliveries, delivery of useless or unwanted items to disaster victims and a lack of inter-organizational collaboration [START_REF] Oloruntoba | Humanitarian aid: an agile supply chain?[END_REF].

• Assessment uncertainty: Demand is often unpredictable, and may evolve during HSC operations. The difficulties in assessing the exact needs can generate misalignment (in both shortages and overstocks).

• Supply shortage: Even if HSC organizations are agile enough to manage organizational failures and needs misalignments, the peaks in demand of specific emergency items within short time periods can produce shortages at the local and international level. A clear and recent example is the shortage of homologated Personal Protection Equipment during the West Africa Ebola Outbreak in 2014-2015.

These dangers are related to disaster environment elements such as the beneficiaries (who are the origin of the demand), the administrative procedures (access) and the logistics infrastructures, all of them related to the affected geographical area.

• The socio-cultural context impacts the beneficiary's requirements. Even though beneficiaries do not express their needs as a customer can do on the commercial SC (HOs assess the needs), beneficiaries are part of a certain community, which may have cultural specificities. For example, in terms of dietary restrictions or kitchen tool standards.

• Administrative procedures such as customs clearance can produce extra delays in relief item distribution, and have to be considered while planning the operations.

• The logistics infrastructures are required for carrying out logistics activities. They are often at the origin of HSC disruption or extra delays due to congestion or collapse.

Moreover, there is the media, which plays an interesting role in the funding of HO operations. HOs need to highlight the consequences of disasters and their interventions to attract donors. It has been demonstrated that the lack of media coverage has a negative impact on funding, as illustrated by the so-called silent disasters. Only 10% of world disasters became a news headline (IFRC, 2015).

Moreover, because the media places such intense pressure on agencies to compete for visibility, organizations also have to consider communication with the international community, which mainly happens through the media (even if they are not always able to manage it effectively). For instance, Van Wassenhove ( 2006) explains that ineffective use of the media by HOs can lead to waves of unsolicited donations (with resulting bottlenecks) instead of the much-needed resources.

Partners

The HSC is comprised of different partners with different motivations. By partners, we refer here to the actors who have an active role in the HSC network. We do not consider here the beneficiaries, insofar as the demand is assessed by HOs. In the literature, donors, HOs, governments, the military and private Third Party Logistics Providers (3PLs) are considered to be the main HSC partners [START_REF] Kovács | Humanitarian logistics in disaster relief operations[END_REF]. HOs can be considered the primary actors of an HSC supply network as long as they have the role of managing public and private donations. HOs include aid agencies such as all the UN agencies (i.e. WFP, UNICEF), the IFRC/ICRC, and local and international nongovernmental organizations (NGOs) such as Oxfam or MSF.

Figure 25 Actors in the supply network of humanitarian aid [START_REF] Kovács | Humanitarian logistics in disaster relief operations[END_REF] HO relationships occur within the HO itself and with the other partners. HO internal relationships (collaborations) occur vertically between headquarters and field staff, and between various national or regional divisions, or horizontally across functional units [START_REF] Day | Humanitarian and disaster relief supply chains: a matter of life and death[END_REF]. The definition of the internal structures cannot be generalized. However, HO internal links can be represented with hierarchical "parent-child" relationships. When non-command and control management exists, there is a need to define a coordination entity that gathers the different decision-makers, such as PADRU (Pan American Disaster Response Unit) for the IFRC.

Partner-based relationships are mainly with other HOs, with 3PLs, or with military units and governments. These relationships can be defined as "customer-logistics service provider" relationships. When an HO offers a service to a government, it can be considered that the HO is the Logistics Service Provider and the government the customer, whereas when an HO orders a service from a 3PL, the HO has the customer role.

Therefore, all these partners can take the role of a Logistics Service Provider, as they contribute to the HSC network with material resources, skills, facilities or services. They can also be customers, as long as they receive services from other organizations.

As highlighted by [START_REF] Charles | Learning from previous humanitarian operations, a Business Process Reengineering approach[END_REF]) all these partners have different incentives and means of action. Depending on their presence or not in the field, the response varies drastically. It is also true that some of them, like local governments or the military, often add complexity to the situation.

Behavior

The behavior of the HSC concerns all the activities within the HSC. The HSC network supports the three main SC flows: material, informational and financial (Luk N. [START_REF] Van Wassenhove | Humanitarian aid logistics: supply chain management in high gear †[END_REF].

• Material flows which represent physical product flow (food, relief items, etc.).

• Informational flows (order transmission, tracking and coordination of physical flows) are poorly structured and managed.

• Financial flows. HSCs are funded by donors (individuals, international organizations (i.e. ECHO), governments, and the private sector). The funding process is a channel for donations from individual people or donor organizations to the beneficiaries through the HSC. Thus, contrary to commercial SCs, the financial flows are not "parallel" with the material flows.

To formalize the concepts and relationships within these flows, and make HSC behavior explicit, two modeling languages have been identified in the literature which formalize the processes: Business Process Modeling (BPM) and Value Stream Mapping (VSM).

Business Process Modeling

To improve HSC flow management, several authors have used BPM approaches, such as the HSC process reference model discussed in the background section [START_REF] Blecken | Supply chain process modelling for humanitarian organizations[END_REF]. BPM formalizes the partner's activities and relationships along the flows through process flow modeling. It also identifies the key performance indicators of each activity which contributes to the overall performance objectives. Figure 26 is an example from [START_REF] Blecken | Supply chain process modelling for humanitarian organizations[END_REF] of a field ordering process illustration using the standard BPMN (Business Process Model Notation). In this process, three partners of an HO (logistics center, regional center and headquarters) interact to purchase ordered goods.

Figure 26 A 'field ordering' process model example [START_REF] Blecken | Supply chain process modelling for humanitarian organizations[END_REF])

Value Stream Mapping

The HSC network information and material flows can be also represented from a value stream perspective. A VSM represents the physical flow from origin to destination for a given product (or product family) and the related information flows. It makes explicit the waste, such as unnecessary transportation, inventory or any activities, therefore improving the overall HSC network flows. Figure 27 shows an example of a Personal Protection Equipment value stream during the Ebola Outbreak built with data from the field (Laguna Salvadó, Laura et al. 2015).

HSC metamodel

The full HSC metamodel is structured as presented in Figure 28. At the center, the Collaboration Systems core metamodel, surrounded by the Crisis Management layer and the HSC layer.

Figure 28 HSC layered metamodel structure inspired from [START_REF] Lauras | A meta-ontology for knowledge acquisition and exploitation of collaborative social systems[END_REF] The HSC metamodel is formalized using the graphical UML (Unified Modeling Language), which links classes (the concepts) using different kinds of relationships: association, inheritance, aggregation and composition (Figure 29).

HSC layer

Crisis Management layer Core metamodel • Inheritance refers to the ability of one class (child class) to inherit the identical functionality of another class (parent class), and then add new functionality of its own.

• Aggregation is a special type of association used to model a "whole to its parts" relationship.

• The composition relationship is just another form of the aggregation relationship, but the child class's instance existence is dependent on the parent class's instance existence.

To build the HSC layer, the concepts and relationship specifics from the HSC domain have been defined as classes and linked to the Crisis Management generic layer. Only the HSC Behavior package has been connected directly to the Core (see Chapter I.3.1.4 for more details). The HSC packages are then: (i) HSC Context, (ii) HSC Partners, (iii) HSC Objectives and (iv) HSC Behavior.

HSC Context Package

Figure 30 HSC Context Package

The HSC Context package (Figure 30) defines the circumstances that form the setting where the HSC system has to evolve. Based on the HSC domain characteristics captured in the previous section, what is relevant for the concretizing of the HSC has been identified from each Crisis Management general concept. We have defined the concepts listed below to characterize the environment specificities.

The Crisis Management "Goods" concept inherits "Logistics Infrastructure":

• Logistics Infrastructure: any man-made element related to logistics activities (e.g. airport, bridges, etc.).

The Crisis Management "People" concept inherits "Humanitarian Aid Beneficiaries", which aggregates "Cultural Considerations".

• Humanitarian Aid Beneficiaries: Any group of people affected by the crisis situation and seeking humanitarian aid.

• Cultural Considerations: the cultural specificities of any group of humans that can affect HSC (e.g. food exceptions, hygiene standards).

The Crisis Management "Civilian Society" concept inherits "Media".

• Media: any characteristic related to media that can influence the HSC, for example the donors, or any stakeholder decisions.

The Crisis Management "Territory" concept inherits "Administrative Procedure".

• Administrative Procedure: any procedure related to an administrative area (customs, pharmaceutical authorizations, etc.). This will have an impact on the Stakeholders process.

Moreover, the HSC system has intrinsic risks related to context; we have identified three main risks sources:

• Demand uncertainty: as a consequence of crisis uncertainty.

• Organizational failures: any risk source related to the HSC partner processes. There can be undesired behavior as a consequence of the context (i.e. the bullwhip effect caused by logistics infrastructure disruption, as observed in the Haiti crisis, 2010; or the Nepal Earthquake, 2015).

• Supply shortage: Private Suppliers may be not able to supply some item references, as observed during the Ebola Outbreak for Personal Protection Equipment.

HSC Objectives Package

As discussed previously, the goal of the HSC is to manage the flows (physical, informational, and financial) to provide material assistance to the populations affected by a humanitarian crisis, and therefore, to alleviate human suffering. The HSC objectives are to satisfy humanitarian needs, and to maintain or enhance performance that can be expressed in different dimensions depending on each partner's strategy. Therefore, two classes inherit from the Crisis Management "Mission" class:

• Beneficiaries' needs forecast: humanitarian needs generated by the crisis situation that have to be satisfied.

• Performance dimension: Partner's objectives in terms of performance.

HSC Partner Package

The HSC partner package (Figure 32) includes all the concepts and relationships that help to describe the HSC system (actors, resources and skills) and the links between them.

• HSC Stakeholders: inherits from Actor and is the parent class for any organization that has a role in the HSC.

• Donor: can be a private or a public actor. They provide Funds, or in-kind donations of any kind of resources, and also unsolicited goods (products, services, facilities, transportation). Donations are either for a concrete crisis response or for general humanitarian responses.

• Humanitarian Organization: the parent concept of an NGO or International NGOs and Humanitarian Agencies. HOs can inherit from other HOs, to represent internal relationships.

• Military: national or international forces collaborating on HSC operations.

• Private 3PL: Providers or Third Party Logistics are any private companies specialized in logistic services and product supply.

• Public Authority: local, regional or national authority that can play a role in the HSC decisions related to location or access authorizations.

• Coordination platform: the concept relates to all stakeholder coordination initiatives (e.g. UN Logistics Cluster).

Figure 32 HSC Partner package HSC stakeholders can be both Customers and Logistics Service Providers. For example, HOs can provide HSC services for other HOs, and outsource services from private companies as the IFRC does (Laguna [START_REF] Laguna Salvadó | A study on the sub-regionalization of Humanitarian Supply Chain: the IFRC case[END_REF]).

• Customer: Any organization that orders services and/or products to another organization.

• Logistics Service Provider: Any organization that provides services and/or products and has facilities/skills/transport fleets and/or stocks.

• Skills: all the human capabilities (management and operational).

• Transport fleets: the transportation vehicle fleets owned by HOs or other actors (cars, planes, trucks, etc.).

• Facilities: all the buildings (e.g. warehouses) and materials necessary for the logistic operation.

• Products: the emergency items that can be medical, food or non-food items (shelters, hygiene kits, etc.). • Stock: Collections of products.

• Stakeholder service: Any service provided to a third stakeholder, e.g. stock management, supply.

HSC Behavior Package

The HSC Behavior Package conceptualizes the process of an HSC, related to the material, information and finance flows as they are. In contrast, the Crisis Management Behavior package was developed to define and orchestrate the Crisis Management partner process. It includes concepts such as a "mediation component" and a "mediator pool" which corresponds to a mediation information system that should define all the partners' processes.

Therefore, the HSC Behavior Package concepts are connected directly to the Collaborative Model metamodel (core). The advantage of a layered approach is that in the future, the HSC could evolve in a direction where a strong collaboration can occur (a central mediator who decides for a group of partners), and then it would be possible to link to the Crisis Management Behavior layer to use its concepts.

The HSC Behavior package (Figure 33) formalizes the operational processes that the HSC partners use to achieve the objectives in a given context. This package includes concepts related to both modeling approaches discussed in the previous section: a process oriented view (BPM), and a value stream oriented view (VSM).

Figure 33 HSC Behavior Package

The main concepts of both approaches are conceptualized in the HSC metamodel, and linked directly to the core concept "Process".

• Business Process: business oriented flow of activities

• Value Stream Process: value stream oriented flow of activities Both modeling approaches are made up of a sequence of activities that produces an outcome:

• Activity: any task performed by a partner of the HSC.

• Flow: defines the link between activities.

• KPI: Key Performance Indicator, to measure the outcome of a process Then, to define a business process it also contains:

• Gateway: defines the flow/activity sequence.

• Event: anything that takes place, for example a start or end event of a business process (i.e. order reception)

• Swimlane: defines the events and activities related partners.

And the additional value stream process concepts are:

• Inventory: the staging areas between each activity in the process.

• Timeline: the time consumed by activity/inventory

Potential uses and engineering methods

The conceptualization of HSC knowledge is required for both academics and practitioners to make the relationships among the stakeholders explicit. The HSC metamodel aims to provide a shared and common understanding of the HSC concepts and relationships, which can support data gathering, information contextualization and knowledge exploitation (Figure 34). It defines a framework for keeping, comparing and reusing information.

Figure 34 HSC metamodel contribution

The following section describes the potential uses of such a contribution, and engineering methods for implementing it are suggested.

HSC academic field research

It is clear that a real gap exists between research proposals on HSC and their application in the field. Among the authors aware of this issue, [START_REF] Galindo | Review of recent developments in OR/MS research in disaster operations management[END_REF]Pedraza-Martinez et al., 2013) have indicated that research work should be closer to practice, taking into consideration real problems and real data. The problem is that such an approach is time-consuming, as researchers find it difficult to get accurate, and above all, reliable data to support their work [START_REF] Galindo | Review of recent developments in OR/MS research in disaster operations management[END_REF]. Another issue is the capacity of researchers to structure this knowledge in order to support the development of original research and operational innovation for humanitarians. [START_REF] Tomasini | From preparedness to partnerships: case study research on humanitarian logistics[END_REF] argued that one of the main humanitarian challenges consists in learning from previous disasters by capturing, codifying and transferring knowledge of logistics operations. Researchers are no doubt aware that the main criterion of the success of scientific approaches consists in producing a complete and representative model of the studied system that helps practitioners to address problems in practice. Considered an art by many and weird science by some, modeling is not as simple as it seems. This is particularly true in the humanitarian context, as in all new research areas, where researchers have difficulty identifying appropriate decision variables and parameters to be able to develop accurate and relevant models [START_REF] Charles | An enterprise modelling approach for better optimisation modelling: application to the humanitarian relief chain coordination problem[END_REF].

Field research, in the context of HSC operations management, seeks to understand the AS-IS state of the current system's business process, and to identify limits, weaknesses and potential improvements and enablers. To do so, a macroscopic picture of the existing system can be seen as a priority. Typically, diagnosis of an SC (and any other corporate system), are made by conducting an investigation with various actors of the SC, to acquire knowledge of the organization, its culture and its modes of operation [START_REF] Lauras | Méthodes de diagnostic et d'évaluation de performance pour la gestion de chaînes logistiques: application à la coopération maison-mère-filiales internationales dans un groupe pharmaceutique et cosmétique[END_REF]. This approach can be supported by the use of interview questionnaires, and other graphical supports (i.e. maps, flow diagrams, organizational charts). Afterwards, the collected elements have to be analyzed.

To enhance the integrity and repeatability of the analysis (within different systems, or the system over time), it is interesting to build the investigation with reusable field research supports. SC investigation supports are kept confidential by consulting groups, who develop their own references. Moreover, both in the literature and the practice there is no consensus on SC field data gathering support structuration: [START_REF] Uschold | Ontologies: Principles, methods and applications[END_REF] highlighted the need for common frameworks for field research. A classic methodology for designing field investigation can be structured with four steps, inspired from (Berthier, 1998):

• Field research planning: objective, hypothesis, implementation plan, scope;

• Prepare field research supports: define a research protocol, questionnaires, graphic supports, an observation strategy;

• Implementation: introduction, data gathering, feedback;

• Analysis & research questions: AS-IS evaluation, preliminary research questions;

• Results communication: share the diagnoses.

Therefore, using the HSC metamodel to build the questionnaires and supports may facilitate the evaluation of the observed systems by building consistent and repeatable analyses.

Figure 35 HSC metamodel use within the diagnosis method

HSC continuous improvement

Beyond the scientific approaches, practitioners can also take advantage of using the HSC metamodel as a support in improving HSC processes. On the commercial SC, continuous improvement approaches have increased in order to align the SC process with market needs [START_REF] Van Wassenhove | Humanitarian aid logistics: supply chain management in high gear †[END_REF]. Continuous improvement is generally defined as "a culture of sustained improvement targeting the elimination of waste in all systems and processes of an organization" [START_REF] Bhuiyan | An overview of continuous improvement: from the past to the present[END_REF]. Therefore, it can have a positive impact on cost, customer service, capacity utilization and sustainability [START_REF] Kovács | Supply Chain Management for Humanitarians: Tools for Practice[END_REF]. Continuous improvement was popularized by Lean Manufacturing practices, which involves everyone working together to make improvements without necessarily making huge capital investments. In the context of HSC, it is not a well-developed approach: however, [START_REF] Fulzele | Identification and Modelling of Critical Success Factors of a Humanitarian Supply Chain[END_REF][START_REF] Pettit | Critical success factors in the context of humanitarian aid supply chains[END_REF] identified it as a success factor in measuring and improving performance, and [START_REF] Cozzolino | Agile and lean principles in the humanitarian supply chain[END_REF][START_REF] Taylor | A consideration of the relevance of lean supply chain concepts for humanitarian aid provision[END_REF]) also encourage the adaptation of commercial lean practices in the context of HSC.

H SC domai n Metamodel

Continuous improvement occurs through evolutionary improvement (improvements are incremental), or through radical changes (innovative ideas or new technology). The approach is cyclical, with methods such as the data-driven improvement cycle DMAIC (Define Measure Analyze Improve Control):

• Define: The purpose of this step is to identify the business problem, goal, potential resources, project scope and high-level project timeline.

• Measure: This is a data collection step, the purpose of which is to establish process performance baselines.

• Analyze: The purpose of this step is to identify, validate and select root causes for elimination.

• Improve: The purpose of this step is to identify, test and implement a solution for the problem in part or in whole.

• Control: The purpose of this step is to sustain the gains. Monitor the improvements to ensure continued and sustainable success.

In this context, the use of the HSC metamodel should facilitate the identification of the business problem and the continuous improvement project scope, as well as the measurement and analysis steps.

Figure 36 HSC metamodel use within the DMAIC method

HSC Information Systems design

People, organizations, and Information Systems software must communicate between and among themselves. However, as discussed by [START_REF] Uschold | Ontologies: Principles, methods and applications[END_REF], due to different needs and background contexts, there can be widely varying viewpoints and assumptions regarding what is essentially the same subject matter.

Define

Measure Analyze Improve

Control

H SC domai n Metamodel

One of the difficulties in transferring technology from the commercial SC to the HSC is the lack of consideration of HSC context specificities. A shared understanding of the HSC system can assist in the specification of adequate Information Systems (Rodrigues da Silva, 2015). The HSC metamodel may facilitate the process of identifying the requirements of the system and understanding the relationships among the components of the future Information System. In most descriptions of the system development lifecycle, there are eight distinct phases [START_REF] Cervone | The system development life cycle and digital library development[END_REF], as illustrated in Figure 37. Therefore, the HSC metamodel can support the problem analysis and requirement definition.

Figure 37 HSC metamodel use within Information Systems design

HSC coordination

We indicated that coordination between HOs is a difficult exercise, and sharing information is a recurrent problem. The metamodel can play the role of a shared database (instance model) to facilitate such coordination. With a common model of the HSC situation, each actor can share his abilities, capacities (in terms of resources) and any relevant information in a way that is understandable to everyone, and all actors of the crisis response can share the same picture of the situation.

Moreover, it is possible to use this structured knowledge to develop and use advanced management tools, such as Mediation Information Systems that support the orchestration of business processes between stockholders [START_REF] Lauras | Towards a better management of complex emergencies through crisis management meta-modelling[END_REF]. Furthermore, this offers the potential to improve the agility and collaboration of HSC stakeholders by proposing detection and adaptation systems based on realtime knowledge updates.

The HSC metamodel can be used as a "template" to characterize the HSC situation. Therefore, following a Mediation Information System approach, the methodology for coordinating HSC stakeholders can follow these four steps (Macé-Ramete et al.

H SC domai n Metamodel

• HSC characterization: definition of the context, the partners and the objectives of the collaboration.

• Collaboration deduction: analyzing the knowledge gathered from the previous step, in order to deduce collaborative behaviors.

• Orchestration: introduction, data gathering, feedback.

• Monitoring: research protocols, questionnaires, graphic supports, observation strategy.

Illustration: A&C RLU academic field research

Because practitioners and academics ideally would like to have a perfect understanding of the HSC operating modes, they have to collect and organize data. However, due to the complexity of disaster response, direct observation, and manual data collection and processing without a clear and transparent methodology is fastidious and inefficient.

This section presents a potential use of the HSC metamodel, based on the A&C RLU use case.

Intentionally simplified, this proof of concept aims to give readers an example of field research design supported by the HSC metamodel, and how can it support structured data gathering.

Figure 39 Metamodel used for A&C RLU diagnosis

Field research planning

The IFRC sub-regionalization strategy was still vague when the collaboration with the IFRC began in 2015. The initial goal was to support the A&C RLU to become more cost-effective by developing innovative HSC approaches. In compliance with [START_REF] Eisenhardt | Building theories from case study research[END_REF], we decided to create research propositions based on empirical evidence.

Therefore, the scope of the field research was the A&C RLU, and the objective was to identify weaknesses of the current activity model in terms of business processes, decision-making and information systems.

The strategy for collecting the A&C RLU AS-IS business process data was to do field research at the Panama hub, based on interviews with practitioners, observations and data collection:

(1) Before the field campaign: Conducting preliminary informal interviews with the Regional Logistics Development Coordinator; primary and secondary data collection.

(2) During the field campaign: Conducting on-site semi-structured interviews with all the A&C RLU practitioners; observations and primary data collection.

(3) After the field campaign: Complete the data and analysis with remote informal interviews.

Field research supports

From the HSC metamodel and the aim of making a diagnosis of a current state, the following interview protocol was devised to guide the visit of a field team to the A&C RLU. It was inspired Four generic categories of information are aligned with the HSC metamodel packages: the context, the objectives, the partners and the behavior (Figure 40). However, given the interactions between the concepts, there is an overlap between the questions and the related "packages". Objective: Identify the regional humanitarian needs profile and the A&C RLU performance approaches.

Partners: Identify the A&C RLU resources and relationships with other humanitarian actors (i.e. donors, suppliers, 3PL).

Behavior: Identify the physical, informational and financial flows, the information systems and decision-making processes.

Interview protocol

The interview protocol provides key elements that should be discussed and addressed in the opportunities we have to talk to various people in the A&C RLU. However, it is important to take advantage of the opportunity to have an open conversation and to capture as much data as possible. The elements in this document [START_REF]INDICATORS 2. EFFICACY OPTIMIZATION 3. SOCIAL IMPACT OPTIMIZATION 4. ECONOMY IMPACT OPTIMIZATION 5. ENVIRONMENT IMPACT OPTIMIZATION 6. EFFICACY CONSTRAINT @for(MatWT(w,t)[END_REF] help us map the content of the interviews and (2) ensure that we all collect the same information at the same level of detail.

Ideally, this document is set up in such a way that the same method can be applied by others as well: for example, in a second field visit as well as during online interviews outside of the field.

Introduction

Please share with us who you are, a bit of your background and what role you are currently playing in the A&C RLU activities.

PART 1: Context

The first part aims to describe both the A&C regional context and the A&C RLU objectives. The key here is to understand the regional profile; including logistics infrastructures and cultural specificities.

Can you explain to us what the specificities of the A&C region are? I would like to understand how the regional context is affecting your work."

• Disasters typically affecting the region.

• Seasonality?

• Logistics infrastructure? Logistics hubs, transportation, etc. (use of geographical maps) • Cultural specificities?

PART 2: Objectives

The second part aims to understand the humanitarian needs, the objectives the organization has, and the objectives per department. Moreover, the challenge is to find out how these objectives are evaluated.

Needs

• Type of humanitarian needs in the region?

Organization/Department:

• Type and size of the A&C RLU organization, the supply network • Size of operations • What are the A&C RLU objectives, your department's objectives?

Outcome:

• How are the objectives evaluated?

• Any KPIs or indicators that you are reporting? How often? To whom?

• What is the impact of your monitoring / reporting?

• Potentially off the record: would you suggest any strategic changes / lessons learned?

• Time frame: during what stages are decisions being made?

• Is the decision reversible? Can it be adapted or changed?

PART 3: Partners

The objective here is to provide a mapping of the links between partners, and to identify the assets and skills of each.

Cartography

• What are the skills and assets that the A&C RLU has?

• Which organizations do you interact with? (Governments, donors, etc.)

• Can I have a list of your providers?

• Any partners? (Network / Cluster, formal and informal links to other organizations)

Coordination

• Who do you coordinate with? How do you coordinate with others internally? (with respect to other departments, logs, transportation companies, suppliers, etc.) • How do you coordinate between the A&C RLU and the field ("your customers")?

PART 3: Behavior

Quantitative data

• Do you have any data on the volumes of items that have been managed (supply and delivery) during the last few years (throughput? flow per time unit? flow per item or group of items?).

Could you give us any information about where we can find such data? • What is the cycle-time of item X (reception time, waiting time, transportation time, shipment time, frequency of shipments, etc.)?

Network and Flow cartography

• Could you explain the different material flows? (use of geographical maps)

• Which are the most representative emergency kits?

• Could you map the physical flow main steps from the source to the beneficiaries or destruction? Could you draw them in a diagram? If possible, provide any information about the suppliers and the beneficiaries.

• What are the main difficulties in managing these flows?

Activity and Business Process cartography

• Which are the main activities that you or your colleagues have to manage (procurement, stock, dispatch, shipment, kitting, transportation, coordination, etc.)? (materials, information, documents, people, etc.), the main Resources (human, skills, equipment, machinery, vehicles, ITC, etc.) and the main Controls (objectives, constraints, order, etc.)?

• Could you explain the sequencing / scheduling of these activities? When should the activity start, finish? Is there any gateway between activities (things that have to be done in parallel, things that have to be synchronized, etc.).

• How can we define the performance of your business processes (activities)? Do you report any indicators (time, lack of quality, costs, etc.) of the work you are doing?

Information sharing

• How do you manage information (sharing) inside A&C RLU?

• How do you share with other organizations?

• How do you place / receive orders? [push vs. pull]

• How are you involved in the planning / inventory mgt. / etc.

Information Systems use

(Descriptions of how the work is achieved and the purpose of that work)

These questions could be covered with a conversational approach where the different aspects are articulated in a nice flowing talk.

• Describe your work day ○ What are the primary activities during a day?

○ When do you start and stop, and where do you conduct your work?

• Who do you typically interact with?

○ People that give you assignments, or people you give assignments to ○ People that report to you, people you report to

• Describe the technology you use: mobile phone / land-line, laptop (and which programs and what for), dedicated software (maps, reporting systems, news sources)

• Describe the information products produced: emails (type of emails), checklists or activity schedules, reports, status updates for meetings, meeting notes, white board illustrations

• Describe your work environment: office, meeting rooms, ad-hoc meeting settings, field environments, and vehicle-based work settings.

Data collection supports

To be more efficient and to facilitate uptake, a flowchart grid has been designed in coherence with HSC metamodel behavior concepts and relationships. This is the main support for the quantitative data collection. As shown in Figure 41, the flowchart sheet is a template that chronologically describes the activities of an HSC. These activities are classified in 4 main categories: operation, transfer, stock/wait and control. For each activity the main inputs, outputs and resources can be traced, in addition to other relevant information like cycle time or available capacity.

The rationale for using such a template is to describe the value stream map and business processes. It is important to notice that through this approach small parts of the HSC concepts are collected from each practitioner's point of view. All these elements should then be connected with the HSC metamodel relationships.

To complement the data collection step, information can be gathered (qualitative and quantitative) on physical flows that involve all processes throughout the A&C HSC. These elements can be visualized in geographical maps.

Figure 41 Example of the workflow grid to support the field interview protocol

Implementation

The fieldwork was conducted during a 10-day mission in October 2015 at the IFRC A&C RLU Panama site (office and warehouse).

The on-site research started with a meeting where the field research campaign was introduced to the team. Then, for a week all members of the RLU structure were interviewed individually at the IFRC office: Head, Service Officer, Procurement Officers, Logistics Officers and Warehouse Manager and Officers as well as the PADRU Coordinator. The warehouse facilities (which are located on a different site) were also visited for one day.

During the 10 days, there was continuous feedback with the A&C Logistics capacity development officer, to discuss missing information or misunderstandings, and to gather as much complete data as possible.

Analysis & research directions: IFRC sub-regionalization

The interviews and observations highlighted that the strategy is currently evolving. We identified the sub-regionalization challenges and the practitioners' needs.

Operation

Considered Flow :

Filed by: General Comments: Waiting for cargo shipment 0 3000 0.3

The set-up

The sub-regional logistics network design consists of a regional hub extended by a network of capacities (inventory and infrastructures) and capabilities (logistics skills) at the country level (Figure 42). The sub-regional contingency stocks are owned by the IFRC, but hosted by the Red Cross National Societies (independent entities, but members of the IFRC), who are in charge of logistics management (warehousing, customs, transportation). In the function of capability enhancement, they could also be in charge of sourcing and procurement.

Figure 42 Linear sub-regional design When starting our analysis in 2015, the network had four sub-regional prep-stocks that were already deployed and a dozen more were planned. Although the network is growing, the operation mode is centralized. The RLU, based in Panama, manages all warehouse procurement, and the Sub-Regional Logistics Units (LU) distribute only for internal country needs. As almost all the stocks are mobilized from (or through) the regional hub, and transportation options are limited, decision-making at the regional level is based on reliable monitored information and the experience of the practitioners. With the current information management system, it will be difficult to enhance responsiveness and sustainability due to the increase in the overall stock level (decentralization) and to the rigidity of operations. Figure 43 summarizes the main outcomes from the field research, according to the subregionalization strategy.

Strengths

• Local sourcing: Developing a local (country level) logistic capacity is an enabler to develop local procurement. • Response time: Pre-positioning contingency stock closer to the potential beneficiaries permits a reduction of response time.

Weaknesses

• Cost: The multiplication of contingency stocks and facilities increases the fixed and immobilization costs of the HSC network. • Vulnerability of the contingency stock: Getting closer to the potential affected areas by natural phenomenon may increase the exposure of the contingency stocks. • Operations coordination: Given that the sub-regional network increases the potential material flows in the HSC network, there is the opportunity to improve HSC coordination within the A&C RLU and NS. • Sustainable decision-making: Moreover, the operations coordination can be managed with a sustainability perspective.

Opportunities

Threads

• Current Information Systems: The coordination of the supply operations is limited by current Information Systems, which do not permit a real-time exchange of information within the sub-regional network. • Decision-making based on experience: To coordinate (i.e. plan) operations may be a challenge with experienced base approaches given the increasing complexity of the network.

Figure 43 IFRC sub-regionalization SWOT analysis

Improvement road map

From the field research analysis, three main improvement steps have been identified.

Short term: Implementing capacities and capabilities

The first step in enhancing a sustainable sub-regional system is to implement capacities and capabilities at a country level.

The first challenge is to define an RLU strategy with respect to capacity, and to determine optimal stock levels for the sub-regional network. To improve in-country logistics capability, there is a need for functioning infrastructures (warehouses, materials, vehicles, etc.) as well as people with dedicated logistics skills. Warehouse deployment is based on an agreement with the A&C RLU, the concerned

Opportunities

-Operations coordination -sustainable decisionmaking

Threads

-Current Information Systems (IS) -Decision making based on experience NS, and funding organizations (IFRC or a Partner NS). A&C RLU wants to involve NSs as "subcontractors", and this is a huge obstacle.

NSs have very different maturity levels concerning logistics. To cope with this situation, A&C RLU is in charge of developing logistics capacities through the National Societies Logistics Capacity Enhancement (NSLCE).

One main issue with this is the high turnover of local volunteers and as a consequence, the volatility of NS priorities. Moreover, NSLCE is financed by Partner NSs (such as Norway or Canada), and it is difficult to sustain enhancement in the long term, when funding runs out.

Mid term: Monitoring the capacities and capabilities

Once the capacities and capabilities are deployed, the next challenge is how to manage and ensure the real-time state of the network. This is a prerequisite for any decision or action on the network.

However, as observed during our research visit to A&C RLU in 2015, the current HSC Management Support Systems have several limitations to properly supporting this approach. Practitioners will struggle to manage the inventories and replenishments properly (no visibility, no warnings, no decision-support) and will consequently increase the fixed costs.

The support used for following inventory levels is the HumLog software application for warehouse management. The Panama warehouse manager sends a report (an Excel Spreadsheet) each month to the Logistics Officer who integrates the inventory level with another Excel Spreadsheet. Then, the Logistics Officer has to manually verify the inventory levels in accordance with defined thresholds. In the future, there will be at least eight more stock capacities (warehouses) to be followed in "real-time" and there will also be the corresponding increase in capabilities to manage. In all evidence, the management system is not ready to do that.

Long term: Planning sustainable relief operations

To make sustainable use of the sub-regional network, practitioners should be able to coordinate network resources during the same operation (Figure 44). For instance, when there is a need in the region, which warehouse will have to send what and when? Who will manage the replenishments? Today, decision-making is based only on the Procurement Officer's experience and is fully centralized.

However, when the network is deployed the possible options will be multiplied by the combination of cost (items, transport), lead-time, and event expiration date. Thus, experience will not be enough to establish the best response for executing.

Figure 44 Sub-regional coordinated response

Results communication

The results of the field research were shared and discussed with the IFRC with the aim of highlighting the priorities and identifying the research directions to be followed.

Part of the field research results were also communicated with scientific publications at the 2016 ISCRAM conference (Laguna [START_REF] Laguna Salvadó | A study on the sub-regionalization of Humanitarian Supply Chain: the IFRC case[END_REF]).

Finally, this thesis mansucript summarizes the overall impact of the field research.

Discussion

Both academics and practitioners may benefit from a clear understanding of the HSC system in order to improve performance. This chapter aims to move the conceptualization of HSC knowledge a step forward by developing a metamodeling approach. Metamodels facilitate integration among stakeholders, information systems, intelligent processing and shared reuse of knowledge among systems (Pinto and Martins, 2004). It is particularly promising in a humanitarian context that requires making the knowledge of the relationships among relief stakeholders explicit [START_REF] Humphries | Improving Humanitarian Coordination: Common Challenges and Lessons Learned from the Cluster Approach | The Journal of Humanitarian Assistance[END_REF].

The HSC metamodel has been developed to provide a framework for classifying gathered data by connecting it to HSC concepts. It has a clear, collaborative perspective, and builds on the Crisis Management metamodel proposed by (Benaben et al. 2016). The HSC metamodel is a layer that includes four packages defining the HSC collaborative system (context, partners, objectives and behavior).

The potential uses are numerous, including the design and fulfillment of academic field research, the implementation of continuous improvement approaches, the design of adequate information systems and even the development of collaborative decision-support systems. The results of current and future research work should be helpful, considering that each organization -each actor-possesses its own knowledge, with its own semantics, usually limited to its core activity. However, even though all the actors possess all the knowledge of the domain collectively, none of them will master all the knowledge or its boundaries individually.

The illustration of the IFRC field research design using the HSC metamodel as a framework for building field research supports is simple proof of the usability of the proposal. The proposed HSC metamodel is a first attempt to describe all the concepts related to the HSC as a layered metamodel, developed by a limited group of experts. It aims to bring a shared and common understanding of the HSC.

However, a significant limitation of this study is that validity and reliability in qualitative research is controversial. To go further, a reference metamodel should be validated with a large spectrum of humanitarian actors, including academics and practitioners. The different perspectives of the actors may produce some misunderstandings with the concepts included in the model, or with the identification of missing concepts unknown by the author. More work has to be done to obtain a generic HSC metamodel that can be accepted by the humanitarian community as a standard.

Moreover, the metamodel gives a static view of the HSC. By implementing it, we can obtain a "picture" of the HSC as observed in a given moment. Due to the dynamic nature of the HSC, the need for introducing a time dimension concept to the metamodel is considered.

Chapter III. SUSTAINABLE HUMANITARIAN SUPPLY CHAIN PERFORMANCE

"Definitional diversity is to be expected during the emergent phase of any potentially big idea of general usefulness."

Gladwin et al. (1995)

Introduction

Typically, HSCs refers to criteria such as efficiency and effectiveness to measure the performance of their operations. This approach allows HSCs to maintain their order-qualifier position in the humanitarian response "marketplace".

To secure an order-winning position, and in line with the global trend to address sustainability challenges, there is increasing interest in sustainable approaches in HSC management. In the HSC literature, several papers call for innovations on the sustainability of humanitarian response [START_REF] Haavisto | Perspectives on sustainability in humanitarian supply chains[END_REF][START_REF] Kunz | Sustainable humanitarian supply chain management -exploring new theory[END_REF]. [START_REF] Haavisto | Perspectives on sustainability in humanitarian supply chains[END_REF] highlighted the need to find a link between the short-term aims on operational performance and the long-term impact.

Moreover, sustainability is an abstract concept, and depending on the perspectives of people, disciplines and organizations, the concept of sustainability is addressed or understood in different manners and for different purposes. From the academic side, while sustainability is used in a wide range of scientific disciplines, it does not 'belong' to any body of knowledge [START_REF] Oloruntoba | Chapter 3: A Planning and Decision-Making Framework for Sustainable Humanitarian Logistics in Disaster Response[END_REF], and there are no clear standards and definitions. Already on 1995, academics expected that sustainability would "remain fuzzy, elusive, contestable, and/or ideologically controversial for some time to come" [START_REF] Gladwin | Shifting paradigms for sustainable development: Implications for management theory and research[END_REF].

Although performance measurement and metrics are essential to effectively manage SC operations [START_REF] Gunasekaran | Performance measures and metrics in logistics and supply chain management: a review of recent literature (1995-2004) for research and applications[END_REF], the development of performance measurement systems for HSC operations is still in its infancy.

Therefore, even if sustainability can be considered a future lever to maintain an "order winner" position for HOs, it remains an abstract objective that is difficult to quantify in HSC operations. The challenge for HSC practitioners is first to develop an understanding of what a SHSC is, so then they can adopt suitable performance measures and metrics to make the right decisions that contribute to creating the value expected by donors: sustainability. This can be achieved by a sustainable performance approach that goes beyond the effectiveness/efficiency paradigm. Moreover, using a sustainability maturity model can also contribute to improving sustainable performance [START_REF] Kurnia | Sustainable Supply Chain management capability maturity: framework development and initial evaluation[END_REF]. Unfortunately, in the literature there is no unanimously accepted performance measurement framework, nor any maturity model, for defining and measuring HSC operations sustainable performance.

To begin closing this research gap, this chapter addresses the following research question: What does sustainability mean in HSC operations and how can it be assessed?

To address the above question, we suggest a framework and assessment model to define and quantify sustainable performance in HSC operations.

In this way, this chapter contributes to turning sustainability from a set of high-level principles and blurry definitions into a concrete and measurable criterion for the HSC decision-making process.

Starting from a literature review on sustainability, sustainable SC performance and SHSC to obtain an overview of the state of the art, including methods and models, the maturity of sustainability will be assessed. The literature review was a qualitative selection of papers based on citation rate. We also considered HO reports to identify "best practices" in the sustainability field.

The remainder of the chapter is structured as follows: in Section 2, a literature review of sustainable SC, maturity models and SHSC performance approaches is presented, which outlines the origins and characteristics of the sustainability concept, and shows how this global challenge is affecting organizations with a focus on SC. Section 3 develops the first contribution of this chapter: a SHSC operations framework. In section 4, a maturity assessment model and method based on the SHSC operations framework are presented and illustrated with the IFRC application case. Finally, in Section 5 the implications of the proposal are discussed.

Background

Sustainability /səsteɪnəˈbɪlɪti/ Noun. The ability to be maintained at a certain rate or level. This section provides an exploratory overview of sustainability as it has been addressed in practice and literature to clarify the notion of SHSC and examine how to build a consistent SHSC framework.

Sustainability: a historical perspective

Sustainable development is strongly related to the concept of progress and growth. This concept dates back as far as the Greco-Roman period, which was the starting point for formulating ideas of progress. Christian theology later consolidated this understanding by introducing "a linear conception of time as a directed succession of events, that transformed the way of thinking about history and progress" (Du Pisani 2006). The idea evolved over the centuries, and during the Industrial Revolution (18 th Century), human progress became strongly linked to economic growth and material prosperity.

Industrialization, however, also brought about a growing gap between rich and poor and environmental degradation caused by the exploitation of raw materials on an unprecedented scale. Therefore, in the 20th century, the ideas about growth and development where challenged. In the late 1960's and 1970's, people became aware of the threats that industrial and commercial expansion posed to the environment and their own survival as human beings (pollution and resource depletion). Western societies became conscious that scientific and technological progress could not address the problems related to the massive consumption of resources. This period saw the beginning of environmental protection movements, with NGOs such as Greenpeace. The notion of sustainable development emerged, taking the word 'sustainability' from the ecology discourse1 .

The modern idea of sustainable development was defined on 1987 during The World Commission on Environment and Development (so called Brundtland Commission):

"Development that meets the needs of the present without compromising the ability of the future generations to meet their own needs" (Brundtland, 1983).

It was the first time sustainability was presented as the balance between the dimensions environment, society and the economy (Du Pisani 2006). Nonetheless, sustainable development, as addressed by the Brundtland Commission, has been subject to considerable criticism, as it is accused of:

(i)
being vague, "it sounds so good everyone can agree with it whatever their own interpretation" (Pearce et al., 1989), (ii) promoting 'fake greenery' [START_REF] Robinson | Squaring the circle? Some thoughts on the idea of sustainable development[END_REF]). (iii) being an oxymoron. 'Is it possible to increase world industrial output in a way that is environmentally sustainable?' [START_REF] Robinson | Squaring the circle? Some thoughts on the idea of sustainable development[END_REF]).

Although sustainability is still a fuzzy and, at times, contested concept, the definition of the Brundtland commission is still the most widely used [START_REF] Klumpp | Humanitarian Logistics and Sustainability[END_REF].

Today, there is a consensus that sustainability is the scientific and political challenge of the 21st century. Environmental sustainability is the most "mainstream" concern, due to the urgent need to address climate change. In November 2017, for the second time after the 1992 "World scientist's warning to humanity", 15,000 scientists signed a strong message of alarm on environmental trends, making a special call for a "… more environmentally sustainable alternative to business as usual" [START_REF] Ripple | World Scientists' Warning to Humanity: A Second Notice[END_REF].

The social consequences of the environmental crisis are also of great concern. Global commitments like the Millennium Development Goals (MDGs), updated by the 2030 Agenda for Sustainable Development (ASD), both promoted by the United Nations, are an attempt to define sustainable development goals with a focus on the societal aspects. The UN SDGs includes 17 goals (Figure 45) with 169 targets that relate to the three dimensions of sustainability: economic, social and environmental.

Figure 45 UN Sustainable development goals

During the 2016 World Humanitarian Summit HOs committed to contributing to the empowerment of local communities as a way to improve resilience. Sustainability challenges are already being addressed by HOs as part of their development programs, primarily during reconstruction and mitigation phases, by working on sustainable solutions that allow the impact of disasters to be reduced.

The Triple Bottom Line

Sustainability has gained recognition since the early 2000s in business. Corporate social responsibility (, good governance, and many other terms have been used to define the policies, practices, and programs to incentivize the positive impacts of companies on societal aspects [START_REF] Jamali | Corporate Governance and Corporate Social Responsibility Synergies and Interrelationships[END_REF][START_REF] Pojasek | Understanding sustainability: An organizational perspective[END_REF][START_REF] Virakul | Global challenges, sustainable development, and their implications for organizational performance[END_REF]).

In the literature, it is a widely accepted notion to present organizational sustainability as a consideration of the balance between environment, society and economy, also known as the TBL [START_REF] Carter | Sustainable supply chain management: evolution and future directions[END_REF][START_REF] Carter | A framework of sustainable supply chain management: moving toward new theory[END_REF][START_REF] Elkington | Accounting for the Tripple Bottom Line[END_REF][START_REF] Virakul | Global challenges, sustainable development, and their implications for organizational performance[END_REF]. These three pillars are also referred to as "People, Planet and Profit". The TBL model is a systemic approach developed on the mid 90's by John Elkington to "capture the essence of sustainability by measuring the impact of an organization's activities including its profitability and shareholder values and its social, human and environmental capital" [START_REF] Savitz | The Triple Bottom Line: How Today's Best-Run Companies Are Achieving Economic, Social and Environmental Success --and How You Can Too[END_REF]. It stresses the need to engage on the performance achievement of these three sustainability dimensions.

This idea comes from the recognition of the environmental, economic and social systems intersection, where sustainability is achieved [START_REF] Mebratu | Sustainability and sustainable development: historical and conceptual review[END_REF]. The TBL dimensions are defined here as:

Figure 46 TBL dimensions • Economic sustainability or "Profit": relates to cost and productivity considerations. An organization has to use its resources so that it can consistently produce an operational profit, and sustain its activities. • Social sustainability or "People": relates to proper and favorable business impact for employees, population, and the area in which the organization conducts its activities. • Environment sustainability or "Planet": relates to environmental impact. It attempts to benefit the natural setting as much as possible or at least do no damage and decrease the environmental effect.

According to [START_REF] Pojasek | Understanding sustainability: An organizational perspective[END_REF]), all activities, products and services have a footprint. This footprint creates impacts on each of the TBL dimensions. Each impact creates risks for the organization's sustainability. The organization can mitigate these risks through a sustainable management of operations that avoid creating negative impacts, as far as is possible.

Figure 47 Sustainability with an organizational perspective [START_REF] Pojasek | Understanding sustainability: An organizational perspective[END_REF] TBL is widely used as a synonym of sustainability in the business literature. However, some authors argue that the TBL elements are conflicting and that their common achievement is therefore impossible [START_REF] Milne | W(h)ither Ecology? The Triple Bottom Line, the Global Reporting Initiative, and Corporate Sustainability Reporting[END_REF]. Accordingly, the TBL approach, as it is currently used, reinforces a position where financial viability is prioritized and environmental and social considerations remain an afterthought. It is considered by some as a pathway for corporations to easily ignore or bypass key sustainability issues [START_REF] Sridhar | The three fundamental criticisms of the Triple Bottom Line approach: An empirical study to link sustainability reports in companies based in the Asia-Pacific region and TBL shortcomings[END_REF].

Here, the problem may not be the TBL philosophy itself, but to recognise and accept the limited function of measuring sustainability, which is useful for (Burritt and Schaltegger 2010):

Environment Economy Society Sustainable Management

Footprint Impacts Risks

• Providing information about an organization's impact;

• Understanding situations;

• Answering specific questions;

• And enabling comparisons.

Sustainability of the Supply Chain

80% of global trade passes through SCs. The SC is considered one of the most important levers for business to create positive (or negative) impacts in the world [START_REF] Carter | Sustainable supply chain management: evolution and future directions[END_REF]. Therefore, SC sustainability is a growing global concern. According to the UN Global Compact Initiative a sustainable SC should follow ten Principles related to the environmental and social dimensions.

The UN Global Compact Principles for SSCM Human Rights

• Principle 1: Businesses should support and respect the protection of internationally proclaimed human rights; and • Principle 2: make sure that they are not complicit in human rights abuses.

Labour

• Principle 3: Businesses should uphold the freedom of association and the effective recognition of the right to collective bargaining; • Principle 4: the elimination of all forms of forced and compulsory labour;

• Principle 5: the effective abolition of child labour; and • Principle 6: the elimination of discrimination in respect of employment and occupation.

Environment

• Principle 7: Businesses should support a precautionary approach to environmental challenges;

• Principle 8: undertake initiatives to promote greater environmental responsibility; and • Principle 9: encourage the development and diffusion of environmentally friendly technologies.

Anti-Corruption

• Principle 10: Businesses should work against corruption in all its forms, including extortion and bribery. [START_REF] Sisco | Supply Chain Sustainability, a practical guide for continuous improvement[END_REF].

Derived from: the Universal Declaration of Human Rights, the International Labour Organization's Declaration on Fundamental Principles and Rights at Work, the Rio Declaration on Environment and Development, and the United Nations Convention Against Corruption

The objective of Sustainable Supply Chain Management (SSCM) is to contribute to reducing the negative footprint [START_REF] Kleindorfer | Sustainable Operations Management[END_REF]. The most cited definition of SSCM is from [START_REF] Seuring | Core issues in sustainable supply chain management -a Delphi study[END_REF]:

"The management of materials, information and capital flows as well as cooperation among companies along the SC while integrating goals from all three dimensions of sustainable development, i.e. economic, environmental and social, which are derived from customer and stakeholder requirement" More recently, [START_REF] Ahi | A comparative literature analysis of definitions for green and sustainable supply chain management[END_REF] proposed an extended definition that integrates the previous one, but covers 7 business sustainability characteristics (economic, environmental, social, stakeholder, volunteer, resilience, and long-term focuses) and 7 SCM characteristics (flow, coordination, stakeholder, relationship, value, efficiency, and performance focuses):

"The creation of coordinated SCs through the voluntary integration of economic, environmental, and social considerations with key inter-organizational business systems designed to efficiently and effectively manage the material, information, and capital flows associated with the procurement, production, and distribution of products or services in order to meet stakeholder requirements and improve the profitability, competitiveness, and resilience of the organization over the short and long-term." Sustainable SCM (SSCM) is therefore a challenging task that basically needs to integrate economic, environmental, and social dimensions in the decision-making processes.

Sustainable SC Performance measurement

Performance /pəˈfɔː.məns/ Noun. How well a person, machine, etc. does a piece of work or an activity Performance Measurement is a way to quantify and control the outcomes obtained in any organization's process. It can be used to compare goals, standards, past results or organizations, and to anticipate the impact of decisions on planning processes. Given the far-reaching consequences of their activities, SC decision-makers are in a position to impact the economic, social and environmental dimensions of sustainability [START_REF] Carter | Sustainable supply chain management: evolution and future directions[END_REF].

The traditional objective of SC performance is to maximize financial profit, paying little or no attention to environmental and social impacts. There is evidence of growing interest in research that focuses specifically on measuring performance in sustainable SCs. Although SSCM is still a young discipline, there has been a dramatic rise in the number of publications since the beginning of the 2000's. A search of the Web of Science database shows an exponential increase in publications with the topic "sustainable SC performance".

Figure 48 Sustainable SC performance WoS publications growth

While analyzing sustainability SC disclosure initiatives, [START_REF] Okongwu | The maturity of supply chain sustainability disclosure from a continuous improvement perspective[END_REF] identified TBL performance as one of the main drivers. Also [START_REF] Baumann | Modèles d'évaluation des performances économique, environnementale et sociale dans les chaînes logistiques[END_REF][START_REF] Beske | Putting sustainability into supply chain management[END_REF][START_REF] Carter | Sustainable supply chain management: evolution and future directions[END_REF][START_REF] Seuring | Core issues in sustainable supply chain management -a Delphi study[END_REF][START_REF] Taticchi | A review of decision-support tools and performance measurement and sustainable supply chain management[END_REF] refer to the TBL when addressing SC sustainability. Therefore, TBL performance measurements for SC operations are abundant in the literature. (Chardine-Baumann and Botta-Genoulaz 2014) define the sustainable performance of a practice as the combination of its economic, social and environmental performances. A recent study identified a total of 2555 unique metrics in the SSCM literature published by the end of 2012 [START_REF] Ahi | An analysis of metrics used to measure performance in green and sustainable supply chains[END_REF]. The results highlight the great variety of approaches for measuring SC sustainability.

Academic proposals typically deal with the strategic decisional level (network design) [START_REF] Eskandarpour | Sustainable supply chain network design: An optimization-oriented review[END_REF], or with a focus on one of the SC SCOR reference operational processes [START_REF] Huan | A review and analysis of supply chain operations reference (SCOR) model[END_REF]): make, source, deliver or return. Moreover, the TBL dimensions are often addressed alone, or two by two (economic-environmental, economic-social or environmental-social).

Economic performance

The SC economic performance dimension measures the financial benefit. The economic performance is therefore strongly related to the satisfaction of customer expectations. For different industries, customers look at different measures, such as delivery service, where time is no doubt their major concern; whereas for parts manufacturing, the accuracy of the specification may be the most important consideration [START_REF]Performance Measurement in a Supply Chain[END_REF]. The economic performance is a balance between effectiveness in delivering customer value and the cost-efficiency of the SC process. SC models have typically focused on performance measures such as a combination of cost (inventory costs and operating costs) and customer responsiveness (i.e. lead time, stock-out probability, fill rate) [START_REF] Beamon | Measuring supply chain performance[END_REF].

Environmental performance

The environmental impact of increasingly globalized SCs has been widely investigated since the 1990's. It is the most highly-developed concept of the TBL. "Green business", or corporate commitment to environmental protection has been demonstrated to lead to competitive advantage [START_REF] Esty | Green to Gold: How Smart Companies Use Environmental Strategy to Innovate, Create Value, and Build Competitive Advantage[END_REF], as it is seen as an opportunity for growth and profit. Reducing resource consumption can lead to an improvement in economic performance. Environmental performance focuses on environmental protection principles that cover all phases of a product's life cycle, from the extraction of raw materials through the design, production, and distribution phases, to the use of the product by consumers and its disposal at the end of the product's life cycle [START_REF] Ahi | An analysis of metrics used to measure performance in green and sustainable supply chains[END_REF]. The World Economic Forum estimates that logistics activity accounts for 6% of the total 50,000 mega-tons of CO2 annually produced by human activity [START_REF] Grant | Sustainable Logistics and Supply Chain Management: Principles and Practices for Sustainable Operations and Management[END_REF]. Therefore, it is not surprising that the most popular metric for measuring environmental impact is the carbon footprint emitted by a company or an SC. Some other key indicators, even if defined using different words, are related to energy use, hazardous wastes generated, and material recovery [START_REF] Okongwu | The maturity of supply chain sustainability disclosure from a continuous improvement perspective[END_REF].

Social performance

Social sustainability has been less fully explored than the environmental dimension in SCs. Furthermore, the definition of social sustainability itself is still not clear. Social sustainability in SCs typically refers to issues of social justice and human rights, with studies focusing on practices such as supplier human rights actions, labor conditions, gender equality or supplier compliance with child labor laws, and the delivery of social justice through sourcing from "ethical" suppliers. Including social aspects in network design decisions allows a better evaluation of the impact of an SC on its stakeholders: employees, customers and local communities.

Standard Sustainable SC performance frameworks

The debate remains open in the Operations Management literature regarding the possibility of having standard sustainable SC performance measures. Given the lack of standardization, some authors argue that indicators need to be established on a case-by-case basis [START_REF] Bouchery | Key Performance Indicators for Sustainable Distribution Supply Chains: Set Building Methodology and Application[END_REF]. Also [START_REF] Pojasek | Understanding sustainability: An organizational perspective[END_REF] suggests that each organization should create its own definition of the term. Others argue that it is possible to have a standard set of indicators to measure the sustainable performance of a given process (i.e. source, make, deliver) [START_REF] Veleva | Indicators of sustainable production: framework and methodology[END_REF].

SSCM performance measurement has been mostly addressed -both in practice and in the literaturewith a focus on accountability reporting [START_REF] Carter | A framework of sustainable supply chain management: moving toward new theory[END_REF]. Therefore, methods such as Life Cycle Sustainability Assessment (LCSA), ISO 26000 (international standard), or the Global Reporting Initiative (GRI) suggest frameworks to report the impact of the SC on sustainability. The GRI is one of the most used references in terms of sustainability reporting. It provides guidelines on how a report should be built. The GRI defines a list of over 90 indicators in the three TBL categories. The social category is further divided into four sub-categories, which are Labor Practices and Decent Work, Human Rights, Society and Product Responsibility (Global Reporting Inititative 2015). Although the GRI is widely-used by many organizations, it has been criticized for its complexity. It adds a lot of criteria, and gathering and analyzing the data is time-and cost-consuming.

Other references, such as the ISO 14000 international standard family, or GreenSCOR are focused only on one of the environmental dimensions. For example, ISO 14031 is designed for environmental performance evaluation with indicators in three key areas: (1) environmental condition indicators, (2) operational performance indicators and (3) management performance indicators.

Sustainability maturity methods and models

Maturity /məˈtʃʊə.rə.ti/ Noun. A very advanced or developed form or state A maturity model is defined by [START_REF] Battista | The Logistic Maturity Model: Application to a Fashion Company[END_REF] as:

"A framework conceived to evaluate the maturity of an organization through the definition of a set of structured levels that describe how well behavior, practices and processes can reliably and sustainably produce required outcomes".

The origin of maturity models comes from the "Capability Maturity Model" [START_REF] Paulk | Capability maturity model, version 1.1[END_REF], which is used to assess an organization on a scale of five process maturity levels. Each level ranks the organization according to its standardization of processes in areas as diverse as software engineering, systems engineering, project management, risk management, system acquisition, information technology (IT) services and personnel management [START_REF] Correia | Maturity Models in Supply Chain Sustainability: A Systematic Literature Review[END_REF].

The use of maturity models to analysis and optimize processes has seen exponential growth in recent years, with encouraging results. Therefore, many authors have focused on the development of SC sustainability specific domain models [START_REF] Baumann | Modèles d'évaluation des performances économique, environnementale et sociale dans les chaînes logistiques[END_REF][START_REF] Golinska | The Method for Assessment of the Sustainability Maturity in Remanufacturing Companies[END_REF][START_REF] Kurnia | Sustainable Supply Chain management capability maturity: framework development and initial evaluation[END_REF][START_REF] Okongwu | The maturity of supply chain sustainability disclosure from a continuous improvement perspective[END_REF][START_REF] Reefke | Sustainable Supply Chain Management-Decision Making and Support: The SSCM Maturity Model and System[END_REF][START_REF] Srai | Understanding sustainable supply network capabilities of multinationals: A capability maturity model approach[END_REF]. [START_REF] Correia | Maturity Models in Supply Chain Sustainability: A Systematic Literature Review[END_REF] recently published a literature review on the topic, and identified the potential uses of Maturity Models as:

• A descriptive tool for the evaluation of strengths and weaknesses • A prescriptive instrument to help develop a guide (roadmap) for performance improvement • Comparative tool to evaluate the processes/organization and compare them with standards and best practices from other organizations • Enablers for internal and external benchmarking Typically, a method to assess a maturity level consists of measures and questionnaires, which allow the organization to perform self-assessment and benchmarking of their sustainability level. However, there is no standard definition of maturity levels. As an example, [START_REF] Baumann | Modèles d'évaluation des performances économique, environnementale et sociale dans les chaînes logistiques[END_REF] proposes an analytical evaluation model to characterize the global performance of an SC based on performance measurement aggregation, which is built on the TBL dimensions. The maturity of sustainable practices is defined on 4 levels proportional to the degree of implementation.

Sustainability in the HSC

Today, there is no clear global consensus on how the humanitarian system should address HSC sustainability. Previous research focuses on: (i) the theoretical conceptualization of sustainability and (ii) the analytical modeling of the HSC at different levels (i.e. network design, operations, or procurement policy).

HSC sustainability concept

Recently, [START_REF] Klumpp | Humanitarian Logistics and Sustainability[END_REF] proposed a definition for sustainable humanitarian operations built on a combination of HOs' objectives, logistics definition (from the CSCMP1 ) and the Brundtland sustainable development definition:

"Sustainable humanitarian logistics has the objective to assure every human beingespecially in situations of disasters and emergencies-a standard of living adequate for the health and well-being of himself and of his family, including food, clothing, housing and medical care and necessary social services by planning, implementing, and controlling the efficient, effective forward and reverse flow and storage of goods, services and related information throughout the whole SC in a manner that meets the needs of the present without compromising the ability of future generations to meet their own needs" This definition includes a large (but fuzzy) view of stakeholders' expectations on sustainability. With an analysis of Annual Reports from several HOs -given the lack of sustainability reports -, [START_REF] Haavisto | Perspectives on sustainability in humanitarian supply chains[END_REF] concluded that HOs mainly view sustainability in terms of the expectations of society and the beneficiaries.

Moreover, according to [START_REF] Hausladen | Considering Sustainability in the Context of Hu-manitarian Logistics[END_REF], development aid and ad-hoc disaster relief have to be considered simultaneously to achieve sustainability. They proposed a theoretical framework to integrate a TBL-oriented sustainability perspective within HSC operations planning. It is a holistic approach that combines disaster relief assistance and long-term planned continuous development for strategic, tactical and operational planning.

Also with a theoretical point of view, Kunz and Gold (2015) have developed a framework of SHSC at the rehabilitation phase. The sustainable performance is conceptualized as flowing from a strategic reconciliation between relief organizations' enablers (resources, capabilities and commitment) and beneficiaries' requirements, via an optimal SC design.

Analytical approaches

Apart from the theoretical discussions on sustainability, few proposals use analytical methods to assess SHSC performance. [START_REF] Dubey | The sustainable humanitarian supply chain design: agility, adaptability and alignment[END_REF] identify three important characteristics of SHSC networks that contribute to HSC performance: agility, adaptability and alignment, and explore possible linkages using extant literature and interpretive structural modeling with sustainability.

HSC Network design

Accordingly, dynamic sensing, responsiveness and flexibility are important dimensions of HSC agility. In order to improve the adaptability of the HSC network, focus should be placed on culture, developing mutual respect and trust among SC partners and responding to environmental needs. HSC alignment can be improved by effective communication design, through proper training and development, collaboration and by maintaining transparency.

HSC Operations

Within the SC processes, transport has been the focus of sustainable SC research and practice due to the high energy consumption, emission of gases, noise pollution and other impacts on the environmental dimension. Therefore, in the context of HSC, [START_REF] Wei | Chapter 11: A Sustainable Humanitarian Relief Network Study for the Wenchuan Earthquake[END_REF]) presented an optimization model to demonstrate the interest of measuring the impact of HSC transport on TBL performance. The model ensures sustainable economic operations with an effective use of the financial resources of donors (minimization of the economic dimension). For the environmental dimension it computes the resulting CO 2 emissions of transportation, and for the social dimension, it constrains a timely distribution and measures the response 'credibility'. The objective of the mathematical model is to minimize the total cost of procurement plus transportation.

HSC Procurement policies

Using Value Chain Analysis (VCA), [START_REF] Taylor | A consideration of the relevance of lean supply chain concepts for humanitarian aid provision[END_REF] demonstrate that the use of local manufacturing and prepositioning stocks reduces the Carbon Footprint. Considering that the HSC has similar processes to a commercial SC, [START_REF] Van Kempen | Using life cycle sustainability assessment to trade off sourcing strategies for humanitarian relief items[END_REF]) used a LCSA to discuss international versus local procurement strategies and their impact on the TBL. The study focuses on the distribution of kitchen sets to refugee camps, and although difficulties were encountered in collecting data, they conclude that based on the LCSA, local sourcing is preferable over international sourcing in social and environmental TBL dimensions.

Conclusion

The TBL is the most widely accepted approach to address sustainability. Even if it comes from the for-profit sector, in the literature many authors have already made the assumption that it is a substantial part of a sustainable humanitarian system [START_REF] Klumpp | Humanitarian Logistics and Sustainability[END_REF][START_REF] Kunz | Sustainable humanitarian supply chain management -exploring new theory[END_REF].

Unfortunately, there is no universal definition of the three TBL dimensions; neither is there an accepted standard to measure it. Even if this lack of standardization can be seen as a weakness, several authors highlight the fact that it provides the possibility to adjust this general framework to any organization.

Definition of Sustainable HSC performance

This section presents the SHSC operational performance framework to assess the impact of operations. It is based on the TBL dimensions, and decomposed into a set of sub-dimensions, with the related definitions and examples of criteria to measure it. The criteria are related to the main HSC processes: procurement, warehousing and transport.

Economic dimension

Traditional SC performance is directed towards financial and operational indicators [START_REF] Kunz | Sustainable humanitarian supply chain management -exploring new theory[END_REF]. In HSC, the added value of operations is defined by accomplishing general humanitarian ambitions like "saving lives". To do so, the main criteria to evaluate HSC performance are generally effectiveness, efficiency, and equity [START_REF] Gralla | Assessing Trade-offs among Multiple Objectives for Humanitarian Aid Delivery Using Expert Preferences[END_REF].

Effectiveness is the capability of achieving the organization's target. In a "value driven" organization, the target will be to satisfy the customer's needs. In HSC, donors ask for specific aims and target levels such as numbers of households that are provided with humanitarian relief items, shelter, or education. In HSC literature, the effectiveness objective usually corresponds to the demand satisfied. To measure it, different KPI are proposed, like population coverage, order fulfillment, stock-out minimization, etc. By looking at the specifics of the three HSC processes, the effectiveness key performance indicator for "source" will be defined as a measurement of effective replenishment, for "make", as the strategic contingency stock level maintenance, and for "deliver", as the needs coverage (real demand) on time.

Others have used the deprivation cost approach [START_REF] Holguín-Veras | On the appropriate objective function for post-disaster humanitarian logistics models[END_REF] or the amount of suffering of the victims.

Equity is considered as an important objective by HOs, however, considering it as a performance indicator is still the exception rather than the rule in the humanitarian setting. Here it is understood as a complement of effectiveness because it is an integral part of humanitarian principles. It also could be considered in the social dimension, as it has a direct link with societal wellbeing. In fact, equity has been defined as the intersection between people and profits [START_REF] Carter | Sustainable supply chain management: evolution and future directions[END_REF]. Tzur measured the equity of HSCs using the Gini Index [START_REF] Tzur | The humanitarian pickup and distribution problem[END_REF], a non-linear measurement of inequality. Others have used disparity in demand satisfaction. Non-discriminatory distribution is an objective for the "making" and "distribution" processes (contingency stock maintenance, needs coverage). For the sourcing process, field-observations at the IFRC also show that the objective is the respect of fair commercial competition.

Efficiency can be defined as the ability to avoid wasting resources to reach a target. In HSC, this dimension corresponds to the minimization of operation costs. Although making a profit is not their objective, non-profit organizations also care about financial wellbeing, since financial stability is crucial to their missions and survival. Cost key performance indicators have already been used as an objective function in many humanitarian distribution models [START_REF] Beamon | Performance measurement in humanitarian relief chains[END_REF]. Regarding the upstream HSC, Beamon and Balcik identified three dominating costs: the cost of supplies, distribution costs, and inventory holding costs. Other costs that can be considered are handling costs, kitting or consolidation costs (cost of building emergency item kits). Thus, we propose the performance criteria, objectives and key performance indicators, as presented in Table 6, to define and quantify the economic TBL performance dimension of the HSC operations.

Environmental dimension

The HSC is not a closed system. Therefore, the achievement of its objective of emergency items distribution it will inevitably imply consumption of resources (materials, energy) and discharge into the environment (wastes, pollution, noise).

Table 7 Environmental footprint of the HSC schema, inspired from [START_REF] Hervani | Performance measurement for green supply chain management[END_REF] Wa ste Pollution Noise…

Energy Materials

SC literature contends that logistics operations can particularly influence pollution (i.e. air, noise), and the conservation of resources (i.e. energy, water) [START_REF] Murphy | Green perspectives and practices: a "comparative logistics" study[END_REF]. Thus, we assume that performance in these two areas constitutes the HSC environmental dimension.

The objectives of measuring environmental pollution are mostly to reduce green house gas emissions, and to manage hazardous materials. Hazardous materials are rare in Humanitarian relief distribution, but they may be present as part of the wastes for medical relief organizations (e.g., medical disposals were an important consideration in the Ebola response). However, we consider that its management it is outside the procurement, warehousing and transport processes, and thus outside the scope of this study. Regarding greenhouse gases, the most widely used key performance indicator is direct and indirect CO2 emissions, or the carbon footprint, coming from life cycle assessment approaches (LCA) [START_REF] Baumann | Modèles d'évaluation des performances économique, environnementale et sociale dans les chaînes logistiques[END_REF]. Carbon emissions can be differentiated between two categories: stationary sources (emissions from material processing, manufacturing, and warehousing) and non-stationary sources (emissions from inbound and outbound logistics) [START_REF] Sundarakani | Modeling carbon footprints across the supply chain[END_REF]). In the GreenSCOR reference model, best practice and performance metrics are suggested by each of the SCOR processes regarding pollution reduction and resource conservation. However, there is no agreed framework for measuring the environmental footprint of the SC.

The resource conservation objective is to reduce wastes like energy, water, packaging, etc. Resources are consumed all along the SC processes. Inventory immobilization (contingency stock) generates significant energy consumption, especially in warm countries (air conditioning). Choices with regard to the mode of packaging or transportation may influence the quantity of packaging consumed

We summarize the criteria on the environmental dimension in Table 8.

Social dimension

The social dimension was the last to be developed in the TBL framework; it has been typically neglected in quantitative models (Brandenburg et al. 2014). In holistic social definitions, there are many criteria that can be found: education, equity and access to social resources, health and well-being, quality of life, and social capital.

Internal and external factors need to be differentiated here. In HSC operations, internal factors are related to labor conditions and external factors to community empowerment. Both criteria build the social sustainability performance as Table 9 shows.

Labor conditions are strongly highlighted by the 2030 Agenda for Sustainable Development, which aims at enhancing prosperity by reducing poverty and economic disparity (wages), gender equality or decent work. The labor conditions objective for the HSC seeks to preserve the health and security of employees, and ensure good conditions of work [START_REF] Baumann | Modèles d'évaluation des performances économique, environnementale et sociale dans les chaînes logistiques[END_REF]. One pillar of a humanitarian organization's strategy (HWS 2015) is to empower local communities with the aim, (among others), of improving disaster resilience [START_REF] Comes | Designing for Networked Community Resilience[END_REF]. Community empowerment can be seen as an external influence including contribution to employment and the creation of wealth. Many authors also refer to the positive impact of local sourcing as an action in favor of community empowerment [START_REF] Kovács | Trends and developments in humanitarian logistics -a gap analysis[END_REF][START_REF] Kunz | Sustainable humanitarian supply chain management -exploring new theory[END_REF] with a positive impact on regional economic development. Therefore, the current trend is favoring local sourcing wherever possible [START_REF] Haavisto | Perspectives on sustainability in humanitarian supply chains[END_REF].

Conclusion: The house of SHSC operations

Despite the published studies, including those noted above, no comprehensive inventory of metrics applied to SSCM is yet available.

The proposal set up concrete criteria, objectives and KPI sets for assessing the operations impact in the TBL approach. Figure 49 illustrates the proposed approach with the "House of SHSC Operations".

The House of SHSC Operations is based on the HSC operational processes: Procurement, Warehousing and Transportation. Each pillar is built on one of the TBL performance criteria. To enhance an overall sustainable performance, the three pillars have to be balanced, so the roof is in equilibrium. This image reflects the importance of considering all the TBL performance objectives to enhance an overall sustainable performance. [START_REF] Carter | A framework of sustainable supply chain management: moving toward new theory[END_REF] emphasize that organizations that seek to maximize the performance of all three pillars simultaneously will outperform organizations that only maximize the economic performance, or the ones that attempt to achieve high levels of social and environmental performance without explicit considerations of economic performance.

Figure 49 The House of HSC Sustainable Operations Therefore, bypassing one of the dimensions, or focusing on just one of them does not contribute to the overall sustainability performance. Figure 50 illustrates some disequilibrium scenarios where HSC dimensions are not balanced.

The first scenario (a) illustrates the current HSC approach, where economic dimension objectives drive operations. There is some awareness of the social and environmental dimensions, but they are not really considered in decision-making. The roof of the House is not stable, so not sustainable in the long term.

The second scenario (b) is the opposite case, where the focus is only on environmental and social dimensions, but forgetting the economic sustainability of the organization. The sustainability cannot be enhanced without ensuring the economical prosperity of the organization.

The third scenario (c) is a "green HSC" approach, where all efforts are put into reducing the environmental impact. As with the previous scenarios, the sustainability of the HSC is not ensured.

SHSC maturity assessment

Previously, we have defined the elements that impact the ability of an HSC to be sustainable. Once sustainable performance dimensions and sub-dimensions have been defined with the "House of HSC sustainable operations", the challenge remains to measure them. This section suggests a maturity assessment model that enables quantification of SHSC performance.

The interest of the assessment model is that it involves both benchmarking and monitoring SHSCs.

Benchmarking allows internally or externally different systems or sub-systems to be compared, for example disaster responses, or for the case of the IFRC, different RLUs. Monitoring enables the evolution of a system over time to be assessed, and therefore drive the performance.

HSC sustainability assessment method

Assessment model

A performance maturity level assessment, based on the TBL dimensions and sub-dimensions, is a way to measure the sustainability of the HSC. For this specific purpose, we suggest using a quantitative and symbolic modeling approach (Figure 52). The SHSC maturity is built on the maturity of each of the TBL dimensions, defined here by five levels:

Figure 52 HSC sustainable performance maturity levels

• L0 -Unaware: The sustainable performance dimension is not considered at all by decisionmakers. There is no information. • L1 -Beginner: Decision-makers are aware, but quantitative/qualitative results are not satisfactory.

• L2 -Medium: The performance dimension results are mitigated or insufficient.

• L3 -Good: The performance dimension is well considered and results are satisfactory.

• L4 -Expert: Decision-Makers are able to make decisions in alignment with the objectives of this dimension and considering the whole HSC (upstream and downstream). The quantitative results are excellent.

Assessment method

To define the maturity level of the SHSC, first of all, each of the maturity sub-dimensions has to be assessed. The suggestion is to use either qualitative or quantitative metrics, with an assessment grid that makes it possible to define one maturity level per sub-dimension.

Figure 53 SHSC Maturity assessment method

Secondly, once the sub-dimensions are assessed, the maturity level of each dimension of sustainability is deduced by taking the lowest sub-dimension maturity level. All the sub-dimensions are considered of equal importance because the objective is to enhance equilibrium.

Finally, a global HSC sustainability maturity level can be deduced. Based on the House of SHSC principle, which encourages equilibrium within the TBL dimensions, the method to deduce the global level is also to take the lowest dimension level. Therefore, as long as one of the dimensions is mostly ignored, the symbolic global level will remain at L0. The objective is to highlight which are the dimensions that should be improved as a priority in order to improve sustainability with a balanced approach.

A proof of concept: Assessing the sustainability of IFRC HSC

To illustrate how to use the SHSC maturity assessment model, we built a use case based on the IFRC A&C RLU operations. First, a set of the metrics and the assessment grid are defined, and secondly, the results are given and interpreted.

Assessment metrics & grid

The metrics to assess the sustainability performance can be either quantitative or qualitative. As long as the objective is to define a performance level for each of the sub-dimensions, we consider a quantitative measure if possible (a ratio can be defined). Otherwise, we have defined a qualitative assessment of the criteria, which is based on the practitioner's appreciation of the dimension (i.e. for the labor conditions). The metrics are inspired by previous discussion, and are illustrative. Depending on the HO, the criteria to define each of the sub-dimensions, as well as the measures, may be different.

Table 10 presents an example of the metrics and Table 11 shows an assessment grid that can be used for each criterion in the IFRC upstream context.

Table 10 Sustainability performance metrics per dimension

All the economical dimensions are quantifiable. For effectiveness, the ratio between the total needs over a time period, and the needs covered on time are considered. For efficiency, we consider a HSC Costs ROI (Return of Investment). A negative ROI result implies that the HSC system loses money, and a positive gives the margin that is generated. The equilibrium is around 0, considering that the objective is not to make a profit but to maintain the activity. For equity we propose using the Gini Index, as suggested by [START_REF] Tzur | The humanitarian pickup and distribution problem[END_REF]. It allows the inequalities within the distribution to be determined, where 0 indicates that there is no inequality. The environmental sub-dimensions are both qualitative. The overall objective is to reduce both the carbon footprint and the consumption of resources. Given that it is not possible to normalize these absolute values, we define different maturity levels in Table 11. The Carbon Footprint levels are based on the LCA assessment approach, which seeks to include the whole product lifecycle (from raw materials to end of life). For resource conservation (reducing consumption) the levels are similar, considering consumption of resources such as water, energy, packaging, etc. Therefore, expertise is reached when the Carbon Footprint and LCA sub-dimensions are managed upstream and downstream. The high level is also reached by using LCA and resource consumption assessments while planning operations.

Last but not least, for the social sub-dimension, we consider one quantitative and one qualitative factor. Local community empowerment (local procurement) is measured as the ratio of local investment over total investment. At the IFRC, it is not expected that 100% of local investments will be reached in the short term, due to the difficulties in finding some emergency items locally owing to strict requirements, and also because of the framework agreements the organization has with global suppliers. Labor conditions (employee management) are assessed through internal and provider audits. The high level is reached when the labor conditions are considered in the planning phase.

Illustrative results

Based on the IFRC A&C field observations and discussion with practitioners, the following illustrative data set was built, with its related sub-dimensions maturity levels. The effectiveness is computed as the proportion of orders delivered on time. The data from 2015 A&C IFRC operations do not consider an expected delivery time. For the illustration, the hypothesis is made that an acceptable delivery lead-time is one week (7 days) since orders placed will usually be urgent (Table 1).

Effectiveness

Efficiency

In a standard year, it is obvious that response to crises does not generate enough rotation to cover the fixed cost of RLUs. Based on the data of the A&C RLU activity between January and September 2015, an amount of nearly 760,000 CHF was charged to customers for a total number of 41 orders. From this total amount, 56,000 CHF corresponds to a service fee (around 7%), and the rest to the procurement costs (704,000 CHF). The income value, extrapolated over a year, results in a total income of around 1,000,000 CHF, and the procurement costs 940,000 CHF (Table 13).

The holding inventory costs correspond to the expenses generated due to the inventory's existence (i.e. waste, infrastructure, handling). This value is evaluated at between 20 and 30% of the mean inventory level value for the industry, depending on the deterioration and obsolescence risks.

Considering that the A&C IFRC infrastructure is of basic standard, and that emergency items are robust, and only hygiene kits are perishable in the long term, we diminish this value to 10% to make the estimation. Appendix A contains the A&C RLU contingency stock value on September 2015.

Considering the hypothesis that this value is close to the mean over the year, the Holding Costs of the region are around 90,000 CHF over the year (Table 13).

RATE -3%

If we compute the effectiveness indicator with this data set, considering that the HSC annual Costs are around 90,000, and that the net income (without the procurement costs) is around 75,000:

𝐻𝑆𝐶 𝐶𝑜𝑠𝑡 𝑅𝑂𝐼 = (1,000,000 -(1,030,000 + ) 1,000,000 ⁄ = -3%
Without a full data set, it is difficult to establish an exact value for the effectiveness indicator. However, the A&C RLU has clearly stated the difficulties it has in covering the costs (IFRC 2013, 2014)

Equity

In the assessment grid it is suggested that the equity should be assessed based on the Gini Index. The value of this index is between 0 and 1, and represents the level of inequality within a studied population. In this case it is the satisfaction of the customer orders of the HSC. The red line in Figure 54 represents the Lorenz curve [START_REF] Gastwirth | The Estimation of the Lorenz Curve and Gini Index[END_REF], which plots the proportion of the variable observed of the population (y axis) that is cumulated by the bottom x%. The Gini index is equal to the A area divided by the sum of the A and B areas, that is to say: Gini = A / (A + B). The bigger A is, the higher is the level of inequality.

Figure 54 Gini Index

The IFRC A&C decision-makers ensure that if there is a situation where they have to share the upstream resources within different demand points, this will be done equitably (although this situation

A B

Lorenz Curve L i n e o f E q u a l i t y

is not common upstream). Therefore, the Lorenz curve of such a situation is at 45°, and the Gini Index equal to 0, with a perfect equality.

Pollution reduction

There is no data available to compute the CO2 emissions

Resources conservation

There is no data available to assess the resources consumption

Local community development

The indicator for this sub-dimension is the proportion of procurement value from local suppliers. Let us consider the following dataset:

Labor conditions

There is a general standard for the staff rules at the IFRC, approved by the general assembly in 1976. Therefore, it is assumed that there is a systematic internal assessment of the Labor conditions. As part of the supplier selection process, it has to be guaranteed that suppliers:

• Adhere to the Fundamental Principles of the International Red Cross and Red Crescent Movement • Maintain ethical business practices always • Are not involved in any form of corruption or any fraudulent activities • Do not engage in any collusive or coercive practices The sub-dimensions maturity levels can be deduced using the assessment grid (Table 11) as follows: For the economic dimension, both effectiveness and efficiency performance are well developed, but still far from optimal. The high immobilization of stocks, and the low turnover of inventory cause the level of efficiency to be negative. Regarding effectiveness, the response time is still long, in most cases.

Equity is considered as achieved, given that it is considered as a constraint by IFRC decision-makers.

For the environmental dimension, nothing is done to assess and reduce the carbon footprint and resource consumption.

For the social dimension, local procurement is being developed, but it is still difficult to find suppliers that satisfy the requirements in most countries. This indicator could be improved with the development of sub-regional LUs. Regarding the Labor conditions, the IFRC standards are satisfactory, but no information was found on the assessment of their supplier's labor conditions.

To increase the readability of the assessment grid, these results can be presented in the form of a radar graph (Figure 55). Each TBL dimension is then assessed as the lowest one within its sub-dimensions levels (Table 15). The global maturity level of the A&C RLU is also defined by the lowest dimension level (L0), as showed in Figure 56.

A simple analysis of the results from the SHSC maturity assessment allows us to identify the subdimensions that have to be prioritized in order to achieve a more balanced sustainability performance.

This result shows that the environmental dimension is completely overlooked by decision-makers at the A&C RLU. Based on this model approach to improving the overall SHSC performance, the priority should be to work on both environmental sub-dimensions. The social dimension also remains in a lower maturity level than the economic dimension, as is predictable, given that the SHSC is still in its infancy.

Discussion

The overall aim of this thesis is to set the basis for a Humanitarian Decision-support System in sustainable operations planning. The literature review and previous research show the challenge for HOs to consider sustainability in their decision-making processes. The objectives of this chapter are twofold: [START_REF]INDICATORS 2. EFFICACY OPTIMIZATION 3. SOCIAL IMPACT OPTIMIZATION 4. ECONOMY IMPACT OPTIMIZATION 5. ENVIRONMENT IMPACT OPTIMIZATION 6. EFFICACY CONSTRAINT @for(MatWT(w,t)[END_REF] clarifying the concept of SHSC, (2) building a framework for assessing the performance of SHSC operations.

First, a performance measurement framework that translates sustainability concepts into concrete HSC operations (procurement, warehousing, transport) is defined. Based on the TBL approach, environmental and social dimensions are added to the economic dimension. The House of SHSC operations is a general framework that stresses the need to consider the three TBL dimensions to enhance sustainable operations. The criteria have been defined considering the literature review on sustainable SC and the impact that HSC processes (procurement, warehousing and transport) have on the different sub-dimensions. Secondly, a model and method to assess SHSC performance maturity is suggested. To illustrate the use of the maturity assessment model, a proof of concept has been built based on the IFRC HSC use case.

This chapter contributes significantly to the fledgling discussion of HSC sustainability. It bridges the gap between high-level sustainability theoretical discussions and the concrete assessment of HSC operations sustainability, which still seems to be difficult in many disciplines.

The contributions have been developed thanks to inputs from IFRC field research. The practical application to various humanitarian relief operations is yet to be achieved.

The SHSC performance framework presented in this chapter forms the basis for developing a Decision-support System that makes it possible to optimize the planning of HSC operations with regard to TBL impacts. However, as sustainability is a multi-dimensional concept, with conflicting objectives, the challenge now is to address these trade-offs and synergies across the economic, environmental and social dimensions. Therefore, the next chapter discusses this set of problem, and develops a Decision-support System, which integrates the HSC sustainable operations framework.

Introduction

Enhancing sustainable operations is a challenge in terms of decision-making. As discussed in the previous chapter, many conflicting dimensions have to be considered with a holistic view of the HSC system. Therefore, the decision process should take into account the complexity of sustainability objectives and trade-offs.

Along an HSC many different individual decisions are made and coordinated. In an HSC network such as the IFRC, but also the WHO or even MSF, decisions are centralized (e.g.. relief items standardization), or decentralized (e.g. regionally adapted operations design). Moreover, decisions are of different importance, from the rather simple question of scheduling shipments, to the challenging decision of whether to open or close a warehouse. To enhance a sustainable HSC, the impact of any decision has to be assessed in terms of sustainable performance.

Given that HOs have a project management approach where the response to each disaster constitutes a project, humanitarian efforts have for a long time been focused more on the execution steps (with very reactive behavior) and much less on the planning steps. As a result, the lack of preparedness and planning -developing strategies and coordinating HSC operations -has led to inefficiencies and misallocation of resources [START_REF] Jahre | The organisational change of logistics in International Federation of the Red Cross and Red Crescent Societies (Case Study). HUMLOG-NET Project[END_REF]. Today, anticipating the performance outcomes of HSCs has become very necessary and important, for three major reasons.

There is a need for decision-makers to evaluate the impact of their decisions with respect to sustainable performance objectives. In the humanitarian sector, this practice would enhance not only the improvement of HSC processes both a priori and a posteriori, but also the anticipation of the impact of future actions on performance. We note that in this sector the inclusion of the concept of sustainability in the management process is quite recent, and decision-makers do not have concrete indicators and tools for measuring sustainability performance. Moreover, the lack of structured planning processes in HSCs [START_REF] Haavisto | Perspectives on sustainability in humanitarian supply chains[END_REF], which are typically supported by decisionsupport systems, hinders the management a priori of the impact of both strategic and operational decisions. Thus, developing a decision-support systems adapted to the HSC not only may help to improve the performance of planning processes [START_REF] Abidi | Humanitarian supply chain performance management: a systematic literature review[END_REF]), but also will enable decisionmakers to take into consideration sustainability performance objectives. Structured planning processes are necessary to align decisions with the expected performance objectives.

Decision-support systems for planning are not commonly used for managing HSCs. Previous researchers have highlighted that misalignment with field specificities and lack of trust are the main reasons for the difficulties of transferring information technology from the commercial sector to humanitarian settings [START_REF] Abidi | Humanitarian supply chain performance management: a systematic literature review[END_REF]. Using a functional model specifically created for HSCs may facilitate the development of appropriate IT systems [START_REF] Blecken | Supply chain process modelling for humanitarian organizations[END_REF].

The trends are clear: scholars and practitioners are asking for more solutions that support decisionmaking, but also emphasize the importance of including humanitarian context constraints. The challenge remains to find a planning method that considers the problem of sustainable performance multi-criteria decision-making.

Therefore, this chapter aims to address the following research question: How to support Decision-Makers in consciously and systematically making sustainability trade-offs and exploring their consequences?

Humanitarian Supply Chain Planning

Improving the planning process of HSC operations is necessary to align decisions with the expected sustainable performance throughout the process. In commercial SCs, decision-support systems have been developed to supports the different planning decisions and time horizons (Figure 57).

Figure 57 Commercial SC planning matrix (Adapted from [START_REF] Stadtler | Supply chain management and advanced planning--basics, overview and challenges[END_REF] Advanced Planning Systems (APS), for example, have shown an impressive potential for integrating organizational units and planning efforts along an SC [START_REF] Forme | The role of APS systems in Supply Chain Management: a theoretical and industrial analysis[END_REF]. Unlike traditional Enterprise Resource Planning (ERP), APS systems try to find feasible, (near) optimal plans across the SC [START_REF] Stadtler | Supply chain management and advanced planning--basics, overview and challenges[END_REF]. APSs are modular, and cover the different tasks and decision levels from the SC planning matrix.

Humanitarian Supply Chain Planning Matrix

Although planning decision-support systems are widely used in commercial SC, they are not common in the HSC. The decomposition of the HSC on tasks and time horizons has been discussed in the literature, and (Blecken 2010) suggested an HSC standard referent model including processes and decision levels, which has already been discussed and used in previous chapters (Figure 58). The standard referent decision levels suggested for HSC are the same as those in commercial SCs: strategic, tactical and operational, also referred to as long, mid and short-term horizon levels [START_REF] Stadtler | Supply chain management and advanced planning--basics, overview and challenges[END_REF].

However, in practice, HSC tactical and operational planning is mainly based on the experience of decision-makers. Nonetheless, as in the commercial SC, HSC decision-makers may also benefit from the decision-support systems in the low decision levels, notably because of information granularity and the decision perimeter.

HSC Strategic planning

Decisions at this level should create the prerequisites for the development of the HSC in the future. They typically concern the design and structure of an SC and, at the HSC upstream have long-term effects, noticeable over several years. The HSC downstream design, however, is typically planned adhoc, when a crisis occurs (Baharmand and Comes 2015).

Decision-support systems at the strategic level have been explored both for the upstream HSC design and for the downstream (Balcik and Beamon 2008;[START_REF] Charles | Improving the design and management of agile supply chains: feedback and application in the context of humanitarian aid[END_REF][START_REF] Vargas Florez | A decision support system for robust humanitarian facility location[END_REF].

Strategic Tac cal

Opera onal ERP APS

This decision level is a lever to enhance economic sustainability, as it involves the design of the HSC network, and therefore allows the improvement of the network performance in terms of efficiency, effectiveness or agility [START_REF] Charles | Improving the design and management of agile supply chains: feedback and application in the context of humanitarian aid[END_REF][START_REF] Dubey | The sustainable humanitarian supply chain design: agility, adaptability and alignment[END_REF][START_REF] Jahre | The organisational change of logistics in International Federation of the Red Cross and Red Crescent Societies (Case Study). HUMLOG-NET Project[END_REF][START_REF] Laguna Salvadó | A study on the sub-regionalization of Humanitarian Supply Chain: the IFRC case[END_REF].

HSC Tactical planning

Within the scope of the strategic decisions, tactical planning, or mid-term planning, aims to define the forecast demand and to find the most suitable way of fulfilling it through an effective management of the assessment, procurement, warehousing and transport processes across an organization's supply network and over a medium-term planning horizon. This planning horizon allows for the consideration of seasonal developments, e.g. of demand.

This decision level has been overlooked both in practice and in the literature in the HSC domain (both Master Planning and Demand Planning), probably because of the segmented nature of the management of disaster responses within HOs. HSCs already have a limited ability to anticipate demand, due to the uncertainty of the occurrence of a humanitarian crisis. Moreover, HSC managers conceive each disaster response as a single SC solution instead of building a tactical planning system that aggregates the HO's network, in parallel with other on-going operations.

Master Planning allows a link to be made between the strategic decisions and the operational process, and to coordinate the different processes of procurement, warehousing and transport to ensure the fulfillment of needs (Demand Planning). Therefore, this decision level is a lever to improve SHSC performance, as it globally defines the operations that will take place according to the assessed demand. It enables the optimization of HSC flows, and therefore, of operational performance.

HSC Operational planning

The lowest planning level has to specify all activities as detailed instructions for immediate execution and control. Therefore, short-term planning models require the highest degree of detail and accuracy to define procurement, warehousing and transport tasks. Short-term planning is restricted by the decisions on structure and quantitative scope from the upper levels.

Field research at the A&C RLU shows that in the upstream HSC, the operational capacity exceeds the workload; so there is no urgency to optimize resource allocation for the operational level tasks.

In the HSC literature, operational level research works focus on transport planning, especially the downstream HSC with the last mile distribution problems (Balcik et al. 2008; Van Wassenhove and Pedraza Martinez 2012).

Conclusion

Field research at the A&C RLU (upstream) highlights the "case by case" management of the humanitarian crisis, which was identified as a main weakness to improve the overall performance of the regional operations. There is a need to improve coordination within the different warehouses, the procurement process and the distribution flows. Therefore, considering the SHSC Master Planning problem seems relevant for both practitioners and academics.

Figure 58 illustrates the positioning of this Chapter contribution within Blecken's HSC reference Model (Blecken 2010).

Master Planning Approaches

In the commercial SC, before OR tools like optimization and simulation entered the "enterpriseplanning arena", Master Planning was often done by MRP II systems 1 , or by simple calculations using spreadsheets without considering capacity limitations [START_REF] Rudberg | Centralised supply chain master planning employing advanced planning systems[END_REF].

OR-related decision-support systems that conduct Master Planning use mathematical programming to maximize performance objectives while taking constraints (e.g. capacity) into consideration as an integrated part of the planning process.

To be able to optimize the Master Planning problem, procurement, inventory and distribution must be monitored. Inputs are forecast demand data and network constraints in terms of a model that defines capacity and dependencies between different processes.

The three major difficulties in using optimization methods and approaches to define a plan are, according to Fleischmann et al. (Stadtler and Kilger 2005):

• There are often several criteria, which imply conflicting objectives and ambiguous preferences between alternatives. This is the main concern when introducing the sustainable performance that typically considers at least the three TBL conflicting dimensions. • A huge number of alternatives are a predominant feature in SC planning. In the case of continuous decision variables, e.g. order sizes, the set of alternatives is actually infinite. • Uncertainty. The forecast demand may be fuzzy. Moreover, nearly always, reality deviates from the plan, especially in the context of HSC. The uncertainty in the data is addressed using fuzzy logic approaches, which model the vagueness and imprecision by adding a probabilistic dimension to the values. Exact methods can also be used. The deviation has to be controlled and the plan needs to be revised if the discrepancy is too large. Planning on a rolling horizon basis is an implementation of this plan-control-revision interaction. The planning horizon (e.g. three months) is divided into periods (e.g. weeks). This procedure is a common way of coping with uncertainty in operational planning, both in classical planning systems and in OR approaches.

OR Master Planning approaches are an attempt to "computerize" planning. Therefore, decisionmakers have to be aware that modeling is a relaxation of reality, and remains only a decision-support system. Human knowledge will still be essential to bridge the gap between model and reality. Otherwise, OR solutions will hardly ever be adopted, especially in the context of humanitarian operations.

Nonetheless, OR methods have a "tremendous potential" in the disaster response domain, according to [START_REF] Altay | OR/MS research in disaster operations management[END_REF][START_REF] Galindo | Review of recent developments in OR/MS research in disaster operations management[END_REF]. Since 2005, there has been a noticeable increase in the publications that address HSC decision-support system problems with OR methods [START_REF] Charles | An enterprise modelling approach for better optimisation modelling: application to the humanitarian relief chain coordination problem[END_REF]. OR is a well-established discipline regarding allocation of scarce resources, because it offers the tools to support HSC operational decision-making [START_REF] Van Wassenhove | Using OR to adapt supply chain management best practices to humanitarian logistics[END_REF]. By adapting OR best practices that have proven their value in commercial SCs, relevant 1 MRP II is a successive planning concept that begins with a not necessarily feasible schedule derived from end product demand. The bill of material is used together with inventory records, lot-sizing rules, and expected lead times to calculate the time-phased material requirements. Capacity limits are not explicitly taken into account, therefore, the planned process may be infeasibleunfeasible [START_REF] Drexl | Beyond Manufacturing Resource Planning (MRP II): Advanced Models and Methods for Production Planning[END_REF].

solutions can be proposed to the complex problems faced by HOs [START_REF] Charles | An enterprise modelling approach for better optimisation modelling: application to the humanitarian relief chain coordination problem[END_REF].

A Multi-Objective Decision Problem

Due to the multi-objective nature of sustainability performance measurement, decision-makers must deal with the conflicting objectives between the economic, social and environmental dimensions of sustainability. Many OR modeling approaches can be found in the literature to solve multi-objective decision problems [START_REF] Branke | Multiobjective optimization: interactive and evolutionary approaches[END_REF][START_REF] Deb | Multi-objective optimization[END_REF].

As multiple Pareto optimal solutions usually exist, the most preferred results (or acceptable solution) can be found by using different philosophies. In no-preference methods, no decision-maker is expected to be available, but a neutral compromise solution is identified without preference information. The other classes are so-called a priori, a posteriori and interactive methods and they all involve preference information from the decision-maker in different ways. In an a posteriori method, multiple solutions are generated for decision-makers to choose from. A priori methods require that sufficient preference information is expressed before the solution process.

In the specific case of Master Planning problem, the objective is to support the decision-maker in the planning, by giving a single acceptable solution, so the a-posteriori methods are not considered.

Regarding the a-priori methods, it appears difficult to put a weight on the sustainable performance objectives. However, discussion with experts allows the hypothesis that the decision-maker can order the sustainable performance dimensions by relative importance. Well-known examples of a priori methods include the utility function method, the lexicographic method, and goal programming.

In the utility function method, the decision-maker assigns weights to prioritize objective functions. As Gralla discusses, these weights are based on assumptions about the relative importance of each objective [START_REF] Gralla | Assessing Trade-offs among Multiple Objectives for Humanitarian Aid Delivery Using Expert Preferences[END_REF]. We note that in theory, and based on previous chapter conclusions, all three dimensions need to be equally considered, but in practice they have different relative importance in any given real-life planning situation.

Goal programming can be thought of as an extension or generalization of linear programming to handle multiple, normally conflicting objective measures. Each of these measures is given a goal or target value to be achieved. Unwanted deviations from this set of target values are then minimized in an achievement function.

In the Lexicographic Optimization Method (LOM), the decision-maker ranks the objective functions according to some subjective degree of priority, and then a multi-stage optimization algorithm enables a solution to be found [START_REF] Branke | Multiobjective optimization: interactive and evolutionary approaches[END_REF][START_REF] Rentmeesters | A theory of lexicographic multi-criteria optimization[END_REF][START_REF] Sherali | Equivalent weights for lexicographic multi-objective programs: Characterizations and computations[END_REF]. Considering that the decision-maker has an active role, and can prioritize the objectives "a priori", the balance between SHSC performance objectives can be addressed following an interactive variant of the LOM. As long as the decision-maker has only to classify the objectives by priority, this approach avoids the need to specifying an abstract weight between objectives that are not homogeneous (cost vs. CO2 emissions vs. social costs…).

However, with the LO described previously, it is very likely that the process stops before less important objective functions are taken into consideration. Combining different methods could help to improve the preferred plan. In the literature, there is an extension of the LOM [START_REF] Rastegar | Relaxation of constraints in lexicographic multiobjective programming problems[END_REF][START_REF] Wray | Multi-Objective MDPs with Conditional Lexicographic Reward Preferences[END_REF], which introduces a slack component. With the slack or constraint relaxation, the Interactive LOM (ILOM) increases the range of possible feasible solutions at each stage. The decision-maker can interact with the algorithm by defining a small deviation from the optimal value of a primary variable so as to improve the secondary value functions. Interactive methods are interesting because they allow the readjustment of the a priori inputs or the introduction of additional information depending on the behavior of the model. Thus, the decision-maker can orient the solution process toward preferred solutions.

Conclusion

Until now, the main objectives of HSC managers have been to improve competitiveness by simply having an effective management of the supply flows while minimizing costs. With the continuous development of the sustainability paradigm, social and environmental performance indicators need to be added to the performance measurement dashboard of HSCs. But, the lack of structured planning processes, concrete sustainability measurement tools, and decision-support systems jeopardizes the enhancement of sustainable operations. Tactical planning has been overlooked, but it has a huge potential because it is at the crossroads between decision levels and HSC process.

In Chapter 3, we developed a conceptual performance framework to assess the maturity of SHSC operations based on the TBL model. This framework is, however, generic and does not consider the various decision levels (strategic, tactical and operational). Consequently, it does not by itself allow a concrete quantification for the Master Planning processes.

Although tactical decision-making shows a potential to improve SHSC performance, the literature has overlooked Master Planning problems in the HSC. This chapter aims to contribute to filling this gap by setting the basis for a Master Planning decision-support system, following an OR approach.

The remainder of the chapter is organized as follows. Sections 2, 3 and 4 present the SHSC Master Planning contributions: selection of Master Planning sustainable performance criteria; an ILOM proposal, and the adaptation of the network flow model for SHSC Master Planning. Section 5 presents a proof of concept, with a numerical application based on the A&C IFRC upstream use case, to demonstrate the relevance of the proposed decision-support system. Finally, conclusions and perspectives are presented in section 6.

SHSC Master Planning Objectives

To solve the sustainable Master Planning problem, the impact of material flows on sustainable performance needs to be measured. Therefore, based on the sub-dimensions identified in Chapter 3, we suggest considering only the sustainable performance criteria that can be quantified. To select the indicators, three main parameters have been assessed:

(i)

The decisions taken in the Master planning process (flow selection) have an impact on the sub-dimension criteria (ii)

The sub-dimension criteria have to be quantifiable, so it is important to have access to the related data (iii)

There is at least one indicator per TBL dimension.

Based on these constraints, each of the sub-dimensions is evaluated (Table 16). The sub-dimensions selected are effectiveness, efficiency, local empowerment and pollution reduction.

Labour conditions

Employee management Yes Difficult to quantify, need or an audit per flow Considering the equity sub-dimension, when asked, the IFRC upstream managers state that in the face of a dilemma resulting from the shortage of resources (even though this is not typically happening at the upstream level), the distribution of items may be shared equally between the demand points that need them most urgently. Therefore, in the Master Planning problem, equity is considered as a constraint, and not as an objective function.

The set of SHSC Master Planning objectives

Four sustainable performance objectives have been retained to define the SHSC: effectiveness, efficiency, local empowerment and pollution reduction. Although all four of them have to be considered, effectiveness is an essential criterion to maintain HSC activities and the value chain. Humanitarian guidelines, principles, and measures of success emphasize meeting the needs of beneficiaries as the first priority [START_REF] Gralla | Assessing Trade-offs among Multiple Objectives for Humanitarian Aid Delivery Using Expert Preferences[END_REF].

Hence, effectiveness it is an order qualifier objective, and has a larger relative importance than the other three objectives, so it is translated in the ILOM approach as the 1 st lexicographic objective (presented in the next section). The other three objectives have a conditional lexicographic order depending on situational state variables (that is, the strategic priorities, the funding/needs gap, etc.).

With the aim of simplifying the understanding of the SHSC Master Planning ILOM algorithm and the mathematical model, effectiveness is defined separately from the conditional lexicographic TBL dimensions. Therefore, in this Chapter, it is considered hereafter as a prerequisite in the SHSC. Table 1 summarizes the set of objectives retained to measure the sustainable performance of SHSC Master Planning.

SHSC Master Planning Model

The SHSC Master Planning model is a variant of the network-flow problem (Bradley et al. 1977). The common problem in the industrial sector relates to the distribution of a product from plants (origins) to consumers (destinations), with the objective being to minimize costs. In the case of an SHSC, the main differences that we address are due to the following reasons:

• The network provides more than one product,

• The optimization objectives are multiple, since sustainability is multidimensional • The problem is solved considering several time periods (time horizon).

The supply network and assumptions

The supply network is composed of three elements: supplier, warehouse and customer. The model is sufficiently abstract to represent a large variety of HSC designs and perimeters. Supplier refers to the source of relief products. Depending on the perimeter, suppliers can be private sector providers or other HOs that are specialized in the distribution of relief products. Warehouse refers to the intermediate locations where relief products are stored, but can also represent permanent locations with contingency stocks or warehouses deployed when a disaster occurs. Customer refers to the demand points of relief products, but can also be a field entry point (hub or warehouse), a distribution point or a third-party organization warehouse. The sources, destinations, and intermediate points are the nodes of the network, while the transportation links connecting the nodes (or flows) are the arcs (see Fig. 5). As in the standard problem, the suppliers' capacity, as well as the total number of products required by the customers, are assumed to be known. The products can be sent directly from source to destination, or may be routed or sourced through intermediate points (warehouses). The Master Planning is calculated for a number of periods on a pre-defined time horizon. Whereas in the industrial sector the tactical level typically considers 6 to 12 months, in the HSC this period may be shorter due to uncertainties, and depending on the HSC perimeters considered. The last-mile distribution activity may be characterized by a shorter time horizon and granularity than the upstream HSC (permanent network of prepositioned stocks). The following assumptions are developed based on both the field research presented in the methodology section and information gathered from the literature. All the network elements are supposed to be known a priori by the decision-maker.

Mathematical Model sets and parameters

This section describes all components of the flow network model: the indices and the objects built of parameters and variables.

Model indices

HSC Network model objects

Distribution Flow object

The distribution flow object gathers the data related to the physical connections between the network nodes. Each record is a physical connection between nodes, unique for each product.

Symbol Description

Input parameters

Fori

Objective functions

In this section, we will first present four sub-models before presenting the general model and the constraints of the algorithm. Each sub-model (objective function) represents one of the performance objectives. The order of the general constraints depends on the optimization sequencing.

Objective function for effectiveness

The objective function for effectiveness aims to find a feasible distribution planning that maximizes the satisfaction of demand on time. It is computed as the maximum value that can be achieved if everything is on time, minus the penalty for delays. The maximum value refers to the value of the total demand for a given period multiplied by its priority factor plus the contingency stock value of one period. The customer's penalty is proportional to the total stock-out quantity par period, the priority of demand, and the product's standard value divided by the number of periods. The warehouse's penalty is proportional to the total warehouse stock-out quantity in the time horizon divided by the number of periods.

Objective Function for efficiency (economic dimension)

The objective function for efficiency aims to minimize the costs of purchasing and distribution while satisfying the needs. In our model, the fixed cost of purchasing is not taken into consideration since the cost function is proportional to the product flow (quantity delivered).

Min ∑ ∑ 𝐹𝑖𝑛(𝑓, 𝑡) × 𝑓𝑐𝑜𝑠𝑡 (𝑓) 𝑡 𝑓

(2)

Objective Function for pollution reduction (environmental dimension)

The objective function for pollution reduction aims to minimize carbon emissions in the procurement and distribution activities. To compute the unitary emission of a shipped product, the Greenhouse Gas protocol is the most common model (Absi et al. 2013). The total amount is calculated with a linear function that depends on both the distance travelled and the carbon emission of the vehicle used (gCO/kilometer). Based on this model, the carbon emission indicator is proportional to the number of units of products allocated to each flow in the network, depending on the transportation flow.

Min ∑ ∑ 𝐹𝑖𝑛(𝑓, 𝑡) × 𝑓𝑒𝑛𝑣 (𝑓) 𝑡 𝑓

(3)

Objective function for local empowerment (social dimension)

The objective function for local empowerment aims to maximize local investments in the procurement distribution activities. In other words, this objective function maximizes purchases from local suppliers. Local suppliers are defined by the decision-maker and include those located not only in the same region, but also in neighboring countries.

Max ∑ ∑ 𝐹𝑖𝑛(𝑓, 𝑡) × 𝑓𝑖𝑡𝑐 (𝑓) 𝑡 𝑓|𝑓𝑠𝑜𝑐=𝑙𝑜𝑐𝑎𝑙 (4)

General constraints

These objective functions are subject to two categories of constraints: general and sustainability performance constraints.

Flow-balance

The flow-balance constraints apply the conservation-of-flow law which states that for all inflow records (Fin), when the time is equal to or less than the flow lead time, the inflow can only be the delivery quantities scheduled before t0 (fexp).

𝐹𝑖𝑛(𝑓, 𝑡) = 𝑓𝑒𝑥𝑝(𝑓, 𝑡), f t / t ≤ ftlt(f) (5a)

Another way of expressing them is that the inflow record (Fin) is equivalent to the outflow (Fout) from a node before the flow ∆t.

𝐹𝑖𝑛(𝑓, 𝑡) = 𝐹𝑜𝑢𝑡(𝑓, 𝑡 -𝑓𝑡𝑙𝑡(𝑓)), f t / t > ftlt(f) (5b)

Supplier-balance

The supplier-balance constraint stipulates that for each supplier-product record, the quantity of products dispatched at period t must be equal to the sum of all the inbound flows at time t for which the point of origin and product are the same as for the supplier-product couple.

𝑆𝑜𝑢𝑡(𝑠, 𝑡) = ∑ 𝐹𝑜𝑢𝑡(𝑓, 𝑡) 𝑓|𝐹𝑜𝑟𝑖(𝑓)=𝑠𝑖𝑑(𝑠) & 𝑓𝑝𝑟𝑜(𝑓)=𝑠𝑝𝑟𝑜(𝑠)
, s t (6)

Maximum capacity of suppliers

The quantity of products dispatched must not exceed the maximum capacity of the suppliers per period.

𝑆𝑜𝑢𝑡(𝑠, 𝑡) ≤ 𝑠𝑠𝑐𝑎(𝑠, 𝑡), s t (7)

Warehouse inventory-balance

For each warehouse-product couple, the sum of the inventory in the warehouse (Winv) at time t-1 and the products received at time t is equal to the sum of the inventory at time t and the products dispatched at time t. At time t1, the warehouse inventory level at time t-1 is represented by the parameter wini. w, t >1 (8b)

Satisfaction of the warehouse contingency stock level

The stock-out quantity (Wsto) refers to the difference between the desired contingency stock and the actual inventory level. It becomes an over-stock (Wove) if the requested quantity is less than the inventory level.

𝑊𝑖𝑛𝑣(𝑤, 𝑡) -𝑤𝑟𝑒𝑞(𝑤) = 𝑊𝑜𝑣𝑒(𝑤, 𝑡) -𝑊𝑠𝑡𝑜(𝑤, 𝑡), w, t

We note that at the end of the planning horizon, the forecast demand may tend to be underestimated (the demand estimation veracity and the forecast quantities decrease with the time horizon) due to the unexpected consequences and behavior of humanitarian crises. Hence, the model forces the network to finish the planned period with the required contingency stock level. This prevents the economic objective function from depleting the contingency stocks.

Winv(w, nbT) = wreq(w), w

Customer (or Demand Point) balance

For each Demand Point-product couple, the quantity of products received per period is equal to the sum of all the inbound flows (Fin).

𝐶𝑖𝑛(𝑐, 𝑡) = ∑ 𝐹𝑖𝑛(𝑓, 𝑡) 𝑓|𝑓𝑑𝑒𝑠(𝑓)=𝑐𝑖𝑑(𝑐) & 𝑓𝑝𝑟𝑜(𝑓)=𝑐𝑝𝑟𝑜(𝑐) c,t (10)

Satisfaction of the demand

The quantity of products that a demand point receives at period t, must be equal to the demand (cqua). It may be lower in case of stock-out or higher due to over-stock.

𝐶𝑖𝑛(𝑐, 1) + 𝐶𝑠𝑡𝑜(𝑐, 1) = 𝑐𝑞𝑢𝑎(𝑐, 1) + 𝐶𝑜𝑣𝑒(𝑐, 1), c, t=1

𝐶𝑖𝑛(𝑐, 𝑡) + 𝐶𝑠𝑡𝑜(𝑐, 𝑡) = 𝑐𝑞𝑢𝑎(𝑐, 𝑡) + 𝐶𝑜𝑣𝑒(𝑐, 𝑡) + 𝐶𝑠𝑡𝑜(𝑐, 𝑡 -1) -𝐶𝑜𝑣𝑒(𝑐, 𝑡 -1), c, t>1 (11b) However, given that the objective is to respond to all the demands and that the network can achieve this a priori, the model forces the satisfaction of all the demand.

Equity constraint

The equity constraint forces the distribution of products to be proportional to demand, with the same ratio for all the priority customers (level 1) and a tolerance of 10%.

∑ 𝐶𝑠𝑡𝑜(𝑐, 𝑡) 𝑡 ∑ 𝐶𝑞𝑢𝑎(𝑐, 𝑡) 𝑡 ⁄ < ( ∑ ∑ 𝐶𝑠𝑡𝑜(𝑐, 𝑡) 𝑡 𝑐 ∑ ∑ 𝐶𝑞𝑢𝑎(𝑐, 𝑡) 𝑡 𝑐 ⁄ ) × 1.1, c/cpen(c)=Level 1 (12)
5.2.6. Sustainability performance constraints

Effectiveness constraint

The effectiveness constraint is the maximum value obtained by the objective function for effectiveness (Effopt) minus a given tolerance (%).

Economy (Efficiency) constraint

The economy constraint is the minimum value obtained by the objective function for Economy (Ecoopt) plus a given tolerance (%).

𝐸𝑐𝑜𝑜𝑝𝑡 × (1 + 𝑒𝑐𝑜 𝑡𝑜𝑙 ) ≥ ∑ 𝐹𝑖𝑛(𝑓) × 𝑓𝑐𝑜𝑠𝑡 (𝑓) (14)

Environment (Pollution reduction) constraint

The environment constraint is the minimum value obtained by the objective function for Environment (Envopt) plus a given tolerance (%).

𝐸𝑛𝑣𝑜𝑝𝑡 × (1 + 𝑒𝑛𝑣 𝑡𝑜𝑙 ) ≥ ∑ 𝐹𝑖𝑛(𝑓) × 𝑓𝑒𝑛𝑣 (𝑓) (15)

Social (Local empowerment) constraint

The social constraint is the maximum value obtained by the objective function for social (Socopt) minus a given tolerance (%).

𝑆𝑜𝑐𝑜𝑝𝑡 -(𝑠𝑜𝑐𝑜𝑝𝑡 × 𝑠𝑢𝑠𝑡𝑜𝑙) ≤ ∑ ∑ 𝐹𝑖𝑛(𝑓, 𝑡) × 𝑓𝑖𝑡𝑐 (𝑓) 𝑡 𝑓|𝑓𝑠𝑜𝑐=𝑙𝑜𝑐𝑎𝑙 (16)

Master Planning for the IFRC A&C RLU use case

This section illustrates the SHSC Master Planning decision-support system in use, following the A&C RLU use case.

We developed the Master Planning dataset based on the field study data gathered at the A&C RLU, as well as on interviews with the Regional Logistic Development Officer. We also built it by imagining what the future IFRC upstream HSC would look like.

Sustainability at the IFRC

To enhance sustainable operations with the future (or under construction) sub-regional network, decision-makers should be able to coordinate the different stakeholders during an operation. For instance, if there is a need in the region, which warehouse will have to send what and when? Who will manage the replenishments? Today, decision-making is only based on the Procurement Officer's experience and is fully centralized.

When the network will be deployed the possible options will be a combination of variables that need to be considered, e.g., cost (items, transport), sourcing, or lead-time. Thus, experience will not be enough to establish the best response to execute and decision-support systems will be needed.

Figure 61 Sub-regional coordinated response

American & Caribbean IFRC sub-regional upstream network

The A&C RLU network is composed of 7 LUs and the Panama RLU. All warehouses are located close to the respective capitals and in proximity to Logistic infrastructures such as seaports and/or airports. The contingency stock level of each LU is defined by the IFRC strategy. The Panama RLU has a contingency stock level that corresponds to the needs of 5,000 families. LUs have smaller quantities, which can support between 2,000 and 5,000 families depending on the country. Figure 62 shows the geographical locations of warehouses (house), demand points (star) and regional and local suppliers (pointer).

Catalogue

Though the IFRC catalogue has many thousands of references, only a few products that correspond to basic needs (for hygiene, shelter and kitchen use, for example) are kept in the contingency stock at the LUs and RLUs depending on the specificities (climate and culture, for example) of the affected region. For the illustrative purpose of our model, we have selected only two products, one that can be sourced locally (blankets) and one that is difficult to find (tents) even at the national level in most of the countries of the A&C region.

Suppliers

Despite long lead times, most of the suppliers are based in Asian countries due to their competitive prices. At the country level, there are few local suppliers that are competitively responsive and impact positively on local empowerment. The sub-regionalization strategy helps to promote and enhance local capacity, with the aim to develop local sourcing. For our case study, we shortlisted 12 potential suppliers for blankets and 6 for tents. Only blankets are potentially sourced locally, due to the strict IFRC standard products requirements. Family tents are not commonly provided in the A&C region.

Planning horizon

The scope of the Master Planning decisions is to define, with a mid-term horizon, the emergency product flows from suppliers to the field entry points. The assessment of the demand is part of the Demand Planning, out of the scope of this Chapter. Inspired from available data, we consider that demand forecast can be done for a time horizon of 3 months and a time bucket of one week.

. Demand Points and Scenario

As discussed in the Introduction, the main service offered by the IFRC upstream is the management of procurement, warehousing and distribution processes of emergency products to feed entry points (warehouses, airports, seaports, etc.). It does not cover last-mile delivery. The demand can be then classified into different categories depending on the origin or the priority level.

For the illustration, we consider three priority levels: no priority/priority/urgent. The latter level adds a proportional penalty to the effectiveness when not delivered on time. Moreover, only urgent needs are considered by the equity constraint.

The demand of the illustration dataset is based on the socio-economic situation and the political instability of most of the countries in the area, as well as on natural phenomena (such as El Niño) that make the population especially vulnerable.

The illustration scenario is situated at the beginning of the rainy season, and therefore several countries are expecting flooding in the coming weeks/months. The consequence may be displaced people in Dominican Republic, Nicaragua, Honduras, Guatemala and Haiti and therefore, the need of tents and blankets (among other emergency items not considered here). Moreover, Colombia is facing a long-term political crisis, and the number of displaced people is increasing slightly.

Figure 64 shows the total demand of each product per week, versus the capacity. It is evident that the total supply capacity is oversized. The situation is not a grave crisis, so the choices between suppliers can be made depending on the different performance dimensions (economic, environmental, social). In an extreme crisis situation, where the total demand is close to, or exceeds the total capacity, there is no interest on using such an approach, because the effectiveness prioritization would constrain almost any other option.

. Sustainable performance objectives

The LO of the performance objectives has to be established by the decision-maker. Funding is always a problem in the A&C RLU due to the recurrent disasters affecting this area, which do not receive the attention of the media. The strategy of the IFRC is to give more priority to the development of local markets than to environmental considerations. Therefore, it is assumed in this paper that the decisionmaker prioritizes the three sustainability dimensions in the following order: (1) economic, (2) social and (3) environmental.

Numerical application

Based on this hypothesis, we built a database for the A&C RLU network flow. This database is composed of four sub-databases that can be seen in Appendix B. They are:

1) Suppliers' weekly capacity information

2) Warehouse inventory input data of LUs and the RLU,

3) Demand input data, and 4) Input data to define the potential flows.

The initial inventory corresponds to the target contingency stock level. The demand input data correspond to the estimated needs per product and per demand point for the first 7 weeks of the planning horizon. The "cpen" value represents de priority of the order (the higher this parameter, the higher the priority).

The flow database is constituted of 150 flows from suppliers to LUs and the RLU. To limit the quantity of flows, it is assumed that suppliers do not deliver directly to the field. The parameters used to define each flow are: origin, destination, mode, distance, lead-time, product environmental impact, product economy impact, product social impact, and the outstanding orders (expected receipts). Table 18 shows the parameters used to compute the cost and environmental impact. They are proportional to the transported weight and distance. For the multimodal flows, the different parameters are applied proportionally to the distance. They are inspired from [START_REF] Meiginien | Guide méthodologique Transport de marchandises -Caractéristiques de l'offre et capacité des modes de transport[END_REF], and although they do not allow the exact real impact to be measured, they give a magnitude for comparison between the different options. It has to be noted that the environmental indicator results are expressed on CHF to We ek +1

We ek +2

We ek +3

We ek +4

We ek +5

We ek +6

We ek +7

We ek +8

We ek +9

We ek +10

We ek +11

We ek +12

Quantity

Demand vs. capacity per week

Blanket needs

Family tent needs

Family tents capacity

Blanket capacity homogenize the results, and that the equivalence has been computed as 100 CHF par ton of CO2. This pricing is inspired from the 2016 World Bank report [START_REF] Zechtar | State and Trends of Carbon Pricing[END_REF].

Results and discussion

First an illustration of the decision-making process with one LO will be presented. Then, an Experimental Plan will be outlined, showing the behavior of the model when all the potential LOs are considered. Finally, the interest of using the interactive tolerance variation will be discussed.

Sustainable Master Planning decision process

We simulated the decision-making process based on the ILOM (see Figure 59). The objectives of the ILOM are:

• LO 0 : Effectiveness

• LO 1 : Economic • LO 2 : Social • LO 3 : Environmental
The first optimization step aims to maximize the Master Planning effectiveness of the SHSC. Then, following the algorithm, the optimal LO 1 (Economic) is calculated with the Effectiveness tolerance as a constraint. The interface shows the results of varying the Effectiveness constraint tolerance. In the example, the computation was done using variations that go from 0 to 20% with an incremental step of 1% (see Figure 65). We observe that demand fulfillment, which is the main performance driver, is not impacted by small tolerance variations. Small tolerances induce delays only on the warehouses inventory level. To illustrate the decision-making algorithm, we assume that the decision-maker chose to sacrifice 2%.

With 2% tolerance, the Effectiveness constraint is then fixed at 27 Million CHF and the minimal Economy Optimum at 10 million CHF.

Then, the second iteration loop computes the Social optimum (LO 2 ) with the fixed effectiveness constraint plus the variation of the Economy optimum (LO 1 ) as a constraint. The result is shown in Figure 66. Considering that a degradation of 2% of the Economy Indicator (about 10,000 CHF) allows the Social Indicator to increase by 1.2 Million CHF (about 1,205,500 CHF), we assume that the decision-maker accepts a 1% tolerance for the Economy Indicator. The Economy constraint is then fixed at 9.9 Million CHF and the Social optimum (O2) at 3.7 Million CHF. The last optimization loop computes the LO 3 optimum (Environmental) with the O2 optimum (Social) tolerance variation as a constraint. It varies from 0 to 20%, with incremental steps of 1%. The interface with the decision-maker shows the resulting graph (see Figure 67). The output graph resulting from the third iteration leaves a low choice margin for the decision-maker. Reducing the Social Indicator by 1% (37 thousand CHF) allows an improvement of 17.7 thousand CHF on the Carbon Footprint, whereas a reduction of 2% (63 thousand CHF) leads to an improvement of 18.5 thousand CHF. The assumption is therefore to accept a tolerance of 1%. The Social constraint is then fixed at 37 thousand CHF and the minimum Environment optimum (LO 3 ) at 17.7 thousand CHF. The resulting Master Planning indicators are summarized in Table 19. The decision-maker also has access to the planning of receipts, the eventual stock-outs (or overstocks) and the expected inventory levels.

Experimental Plan of LO

For a better understanding of the proposed SHSC Master Planning decision-support system, as well as the behavior of the algorithm, we built an Experimental Plan with all the possible Lexicographic Orders. Given that effectiveness is considered as a fixed LO objective and that only the three other objectives (economic, social and environmental) have to be ordered, there are six possible LO combinations of the performance indicators. Figure 68 shows how the optimal values of the three TBL objectives evolve with the tolerance variation of effectiveness. All the LO 1 objectives benefit from the relaxation of the LO 0 (effectiveness).

The improvements in the objectives amount to a decrease of 95% for the environmental impact and an increase of 20% for the social impact. The results of LO 1 , LO 2 and LO 3 depend on the tolerance defined for LO 0 . Fixing the tolerance at 2% for LO 0 (effectiveness), we observed that LO 1 and LO 2 tolerances also have an impact on the next optimization sequences.

Table 22 shows the results of the Experimental Plan of the LO, with the case data first of all set at a tolerance of 2% for LO 0 ; 0% for LO 1 and 0% for LO 2 (Table 4a) and then at 2% for LO 0 ; 1% for LO 1 and 1% for LO 2 (Table 22b) The indicators are normalized based on the optimal result that can be achieved with the LO 0 tolerance fixed at 2%. The results show that both the LO and the tolerance variation have a relevant impact on the indicators. It can be observed that with a 0% tolerance (Table 22a) the order of LO 2 and LO 3 has no impact on the indicators, while with a 1% tolerance (Table 4b) there is a significant impact of the order on the indicators. It is therefore important to fix the tolerance using an interactive method, since it may lead to an important degradation of the indicators, which may not be acceptable by the decision-maker.

Limitations

The illustrations presented above show that our proposal allows sustainable alternatives to be found for supporting humanitarian logistics. However, this illustration also indicates that decision-makers have a lot of intermediate choices to make all through the process in order to reach a good solution (ordering the TBL criteria and fixing the tolerance ratios). All these intermediate decisions can be difficult to make in an emergency context. Moreover, such a Master Planning system (as in the case of any planning system) needs a lot of data to run correctly. But in an HSC, this kind of dataset is not easy to put together and could constitute a considerable limitation to our proposal. Nevertheless, practitioners already collect such kind of data (on demand, suppliers, etc.) but may not do so in such an exhaustive manner.

Discussion

Given the growing interest in sustainable approaches for the management of humanitarian supply chains (HSCs), both academics and humanitarian organizations (HOs) are in search of effective methods for the implementation of the three sustainability dimensions (economic, social and environmental). In this chapter, we have proposed an approach that can be used for the tactical planning of sustainable operations in the HSC. Based on information gathered from the literature on sustainable HSC and performance measurement, as well as our field research, we presented three complementary contributions aimed at the development of a Master Planning decision-support system for an SHSC.

Effectiveness Economy

Social

Environmental

We started by defining a set of performance indicators used to quantify the Master Planning performance of the SHSC. A brief discussion enabled us to retain four parameters (Effectiveness, Efficiency, Local empowerment and Carbon emission) as the key performance indicators for the tactical Master Planning. To solve the multi-objective problem, we presented an ILOM approach. This sequential and interactive optimization algorithm makes it possible to take into consideration the expertise of the decision-maker by prioritizing the performance objectives. This allows a sequence of single-objective problems to be solved while progressively adding the optimums of previous solutions as constraints. Finally, we proposed a network flow model to execute the Master Planning of the SHSC while optimizing the performance objectives.

For the numerical illustration of our model, we built a case study inspired from the A&C IFRC Regional upstream network. The outcome of the case shows how the ILOM approach enables the decision-maker's expertise and knowledge of the prioritization of planning performance objectives to be integrated. In this experimental section, we emphasized the interest of using an interactive approach to define tolerances. We note that an interactive approach is mandatory since there is no trivial method for identifying a priori the impact of tolerance on performance objectives.

Several perspectives arise from this research work. The first one would consist in testing our proposal in a real context by applying it to real-life operations. Such a project is currently going on with the A&C RLU of IFRC. The objective here is firstly to go deeper into the assessment of the benefits and limits of our proposal, and secondly to ensure its usability by practitioners.

The second perspective would consist in assessing the accuracy of our ILOM outputs with respect to current practices. Our proposal is mathematically and theoretically valid but the relevance of the outputs remains to be studied and confirmed.

The third perspective would consist in extending the experimental plan to dataset combinations in order to better support decision-makers in using the SHSC Master Planning system that correspond to their own business objectives. Although we were able to develop a business case to concretely test our proposal, the parameterization remains complex for users who have to make a lot of intermediate choices in the process. Therefore, it might be valuable to help them by performing a sensitivity analysis of our model and by suggesting sets of parameters depending on the target objective (especially regarding the tolerance ratios).

The fourth perspective would consist in considering much more variability and uncertainty in our Master Planning system. Currently, our proposal is purely deterministic and the hazards are only managed through the rolling horizon of the plan. For further research, it may be interesting to use a stochastic or fuzzy approach. The last perspective is about considering an extension of the SHSC Master Planning to a global HSC management model, just as the for-profit business sectors are doing with Advanced Planning Systems.

Chapter V. CONCLUSION AND PERSPECTIVES

"Utopia lies at the horizon.

When I draw nearer by two steps, it retreats two steps.

If I proceed ten steps forward, it swiftly slips ten steps ahead.

No matter how far I go, I can never reach it.

What, then, is the purpose of utopia?

It is to cause us to advance."

-Eduardo Galeano

Academic and practical contributions

The "raison d'être" of HSCs is to diminish human suffering. However, HSCs are not isolated systems.

The increasing financial gap between needs and funding that HOs are suffering from, the global pressure to embrace sustainable development, and donor's expectations on accountability, all lead us to the conclusion that HSCs should consider a sustainable performance approach as an "order winner" enabler.

Enhancing sustainability in the HSC is a utopia. Sustainability can only be attained by a transformation of our entire society, culture, and economic system. However, this is not an overnight transformation, and thus, the short term challenge is to support organizations on their way towards sustainability. In this context, enhancing sustainability in the HSC can be seen as a "continuous improvement" process that constantly questions the impact of decisions in the short and in the long term.

There are many aspects of the HSC where this evolution can take place, from the mitigation of the impact of disasters, which may contribute to reducing humanitarian needs, to the conscious design of relief items or the strength of collaboration and synergies between actors.

These problems have been addressed here from an Operations Management perspective. From field observations and a literature review, three main gaps were identified: (1) the difficulties in measuring the impact of humanitarian operations on « sustainability », (2) a lack of planning in the context of HSC and (3) the difficulties in developing adequate decision-support systems (academic and inpractice gap).

These issues have been addressed through an inductive research approach, based on IFRC field research outcomes, and with three main focuses: What? Why? How?

What? The HSC system To facilitate the formalization and understanding of HSC systems, Chapter 2 presents an HSC dedicated metamodel. This approach lies in the idea that the HSC is a collaborative system, where different actors have to interact. The HSC system is formalized with four packages: the context, the partners, the objectives and the behavior. This proposal is original given that today, there is no standard formal conceptualization of an HSC system. Potential uses are multiple: it may facilitate field research design, as well as the development of HSC dedicated Information Systems, or support concrete continuous improvement steps for logistics aspects. We have made an HSC metamodel proof of concept, by building field research supports in alignment with the metamodel.

Limits: a proof of concept of the HSC metamodel has been done only to develop field research supports. The practical application (and therefore validation) for the other suggested uses is yet to be implemented (to define information system requirements and to facilitate coordination).

2 nd contribution: the house of SHSC operations (why?)

The second contribution seeks to define the objectives that an SHSC should consider. Following the TBL approach, we propose a set of dimensions that defines SHSC operational performance. This second contribution merges the literature on the concept of sustainability, and sustainable performance with the field of HSC operations. The framework is used to build an SHSC maturity assessment method, implemented with an A&C RLU proof of concept, which enables the measurement of sustainability.

Limits: the framework has been developed thanks to inputs from IFRC field research, as well as the maturity assessment grids. A wider validation of the sustainable criteria and maturity assessment process should be conducted with experts from different HOs, in order to consolidate a benchmark to compare organizations.

3 rd contribution: A Master Planning decision-making system (how?)

Finally, the last contribution pursues the objective of concretely incorporating a sustainable performance approach while planning SHSC operations. From field research and the literature, the tactical Master Planning process is identified as a potential enabler to introduce sustainability in the decision-making process. Therefore, the SHSC Master Planning problem has been addressed. Based on the IFRC A&C network, a set of sustainable performance criteria has been selected. Then, the multi-objective decision problem is solved with an Interactive Lexicographic Ordering Algorithm that allows decision-makers' expertise to be taken into account, linked to a deterministic HSC network flow model. The relevance of the proposal is illustrated through the A&C RLU use case.

Limits: the A&C RLU use-case covers the upstream and internal decision-making process, which is only a limited perimeter of the entire IFRC HSC (from suppliers to end-users). The practical application to a larger perimeter and various HOs is yet to be accomplished. Nonetheless, a lot of data is already needed to run the model, so the capability of gathering this data has to further investigated, as well as the sensitivity of the outputs.

Perspectives

This research has contributed to the literature on the challenge of enhancing SHSC operations. Based on the Technology Readiness Level (TRL) scale1 , the contributions are on level 3-4 maturity levels: "research to prove feasibility". We present here a research agenda to both consolidate the proposals and to propose further research directions.

• The short-term perspectives aim at consolidating a TRL 5 (technology validated in relevant environment). Therefore, we consider the need to validate the contributions with (i) a real scenario from the IFRC HSC network, (ii) a wider set of HO use cases, (iii) and a deeper study of the model sensitivity.

• The mid-term perspectives aim at consolidating a TRL 7 (system prototype demonstration in operational environment). Therefore, it appears relevant to reinforce the prototype implementation with the development of (iv) adequate interfaces in alignment with practitioners' expectations (usability), and (v) methods for a successful technology transfer to the end-users (acceptability). • The long-term perspectives aim at going beyond the scientific proposals. Within the many potential evolutions, we find it relevant to consider three main research directions. First, (vi) a deeper study of sustainability assessment all along the HSC lifecycle. Secondly, (vii) the extension over two dimensions of the SHSC planning decision-support system: the decision planning levels and tasks, and the end-to-end supply chain (from suppliers to beneficiaries). Last, but not least, (viii) the integration of an agile decision-making dimension into the decision-making process.

Short-term perspectives (validation)

x.

Wider Validation with real scenario: to demonstrate the validity of the proposals, all the contributions have been validated through the IFRC A&C RLU use case. Nonetheless, each of the contributions was built with a limited data set extended by assumptions. Although the assumptions were discussed with practitioners or built on field observations, and/or the literature review, it would be relevant to frame a complete dataset with real data.

To build a real scenario, it would be appropriate to engage with the IFRC on a field research campaign dedicated to gathering the data, and to building the real scenario. Furthermore, practitioners could perform a validation step, by contrasting the performance outcomes with and without using the SHSC Master Planning system.

xi.

Contrast model assumptions with other HOs: the assumptions were built on the specifics of the IFRC upstream HSC. This is clearly a limitation, and thus, one perspective would be to extend the validation with a wider range of HOs, such as the WFP or even MSF, who manage similar HSC networks. The scope of other HSCs may differ in terms of disaster typology (i.e. conflicting situations) and therefore, the HSC network flow model hypothesis and constraints may differ.

xii.

A deeper sensitivity evaluation: the sensitivity of the model needs to be investigated more deeply with a real dataset. The objective is to support the users in interpreting and anticipating the implications of their choices during the decision process.

Mid-term perspectives (implementation)

xiii.

Human-computer interaction: in the third contribution, we have focused on the algorithm and model to assess sustainability, and solve the sustainable Master Planning decision-making problem. Although we have considered the user dimension and user expertise on the prioritization of the performance objectives, the usability of the system remains complex for the non-initiated. To reinforce the applied research approach, further work has to be done to design and develop ergonomic human-computer interactions. Developing usable (efficient, effective and satisfying) interfaces is an interdisciplinary matter that concerns at least and computer engineering, and which would also benefit from a social sciences perspective (interaction design) [START_REF] Dix | Human-Computer Interaction[END_REF]. xiv.

Technology transfer to the field: once a prototype has been implemented, it is important to consider the dissemination of the decision-support system among the potential users (access to knowledge). An important related issue to be considered is integration with existing information systems (i.e. ERP). This may notably reveal interoperability challenges.

Long-term perspectives (evolutions)

xv.

Life Cycle Assessments: a standard approach to assessing the impacts of a product on the different dimensions of sustainability is to make a Life Cycle Assessment (LCA). This assessment has typically been conducted for the environmental dimension, but some authors also consider carrying out a social LCA. This is a challenging but interesting perspective to follow because it may make it possible to identify, in a continuous improvement perspective, the stages of the HSC that have the most negative impact.

xvi.

Towards and Humanitarian Advanced Planning System: the ultimate goal of SHSC is to generate synergic decision-making behavior with all the HSC stakeholders upstream and downstream. This research work has addressed a first step, with the development of a Master Planning module, for the upstream HSC. However, the question remains of how decisions taken upstream impact on global HSC sustainability. How can decision-makers gain a holistic perspective? Therefore, to enhance SHSC operations, two interesting perspectives arise: (1) the integration of the different planning levels (Figure 69) and (2) the integration of the upstream and downstream stakeholders (Figure 70).

In the commercial SC context, APSs are seen as the solution to integrate all the decision processes using a hierarchical approach. However, the context of humanitarian operations brings additional difficulties: downstream networks are deployed ad-hoc, the collaborations between stakeholders may be sporadic, and decision-making can be decentralized. Is it then possible to develop a flexible Humanitarian APS? How can the dynamics and uncertainty in the system be addressed? Balcik et al. 2008). The remaining issues still involve the questions of how to introduce the sustainable perspective in the different decision levels and how to ensure the interoperability of the different systems.

The use of the HSC metamodel may be an enabler to facilitate the development of Humanitarian Sustainable APS (interoperability), if used as a common reference conceptualization of the network.

xvii.

Agility (detection, adaptation): finally, HSC operations have to cope with a high degree of uncertainty. Therefore, the HSC decision-making process requires methods that adapt to the dynamics of the environment. Our contribution is limited to the design of a process (the Master Planning), and to deal with the uncertainty, we have proposed a rolling horizon planning approach. An agile decision-making process can be implemented by adding the two dimensions: detection and adaptation. An agile system can detect the deviations between plan and reality, and adapt to the new situation. @for(MatFT(f,t)|t#GT#ftlt(f):Fin(f,t)=fout(f,tftlt(f))+fexp(f,t)); @for(MatFT(f,t)|t#GT#(NT-ftlt(f)):fout(f,t)=0); ! SUPPLIERS ! supplier balance, or flow conservation; @for(MatST(s,t): Sout(s,t)=@sum(MatFt(f,t)|(fori(f)#EQ#sid(s))

LIST OF FIGURES

LIST OF TABLES

#AND# (fpro(f)#EQ#spro(s)): Fout(f,t))); ! supply capacity constraint; @for(MatST(s,t):Sout(s,t)<=ssca(s,t)); ! WAREHOUSE; ! warehouse balance, or flow conservation; ! warehouse contingency stock constraint; @for(MatWT(w,t): Winv(w,t)-wreq(w)=Wove(w,t)-Wsto(w,t)); @for(MatWT(w,t): Winv(w,NT)=wreq(w)); ! CUSTOMERS; ! Total needs value over the periode:; @for(Customer(c): ctqua(c)=@sum(Times(t):cqua(c,t))*cunc(c)); ! Total received value:; @for(Customer(c): Ctrec(c)=@sum(Times(t):Cin(c,t))*cunc(c)); ! Total stockout value over the periode:; @for(Customer(c): ctsto(c)=@sum(Times(t):csto(c,t))*cunc(c)); ! Customer balance @for(MatCT(c,t):Cin(c,t)= @sum(Flow(f)|(fdes(f)#EQ#cid(c))

#AND# (fpro(f)#EQ#cpro(c)): Fin(f,t))); @for(MatCT(c,t)|t#EQ#1:Cin(c,1)+Csto(c,1)=Cqua(c,1)+Cove(c,1)); @for(MatCT(c,t)|t#GT#1:Cin(c,t)+Csto(c,t)=Cqua(c,t)+Cove(c,t)+Csto (c,t-1)-Cove(c,t-1)); @for(Customer(c): Ctqua(c)=@sum(Times(t):Cin(c,t)*cunc(c))); ! EQUITY CONSTRAINT; @for(Customer(c)|(cpen(c)#EQ#1.

Figure 1

 1 Figure 1 People targeted by humanitarian aid in the last decade (OCHA, 2017)

Figure 2

 2 Figure 2 Atlantic hurricane trends (UCSUSA, 2016)

Figure 3

 3 Figure 3 Trend of global displacement & proportion displaced 1997-2016 (UNHCR, 2017)

Figure 4

 4 Figure 4 Disaster Management Cycle (Haddow and Bullock, 2004)

Figure 6

 6 Figure 6 UN cluster coordination approach

Figure 13

 13 Figure 13 Emergency appeals and DREFs 2001-2015 (source: IFRC PADRU, 2015)

Figure 14

 14 Figure14Logistics services provided by the IFRC[START_REF] Grenade | [END_REF]

Figure

  Figure 17 Manuscript Big Picture

Figure 18

 18 Figure 18 Chapter 2 research positioning

Figure 23

 23 Figure 23 Structuration of a collaboration metamodel (from Lauras et al. 2014)

Figure 27

 27 Figure 27 VSM example: "VSM for the Personal Protection Equipment value chain" (Laguna Salvadó, Laura et al. 2015)

Figure 29

 29 Figure 29 UML relationships between classes used on the HSC metamodel

Figure

  Figure 31 Objectives Package

Figure

  Figure 38 HSC metamodel use within the coordination method

  from previous field research work conducted by the Disaster Resilience Lab(Comes et al. 2015;[START_REF] Van De Walle | Risk Accelerators in Disasters; Insights from the Typhoon Haiyan Response on Humanitarian Information Management and Decision Support[END_REF].

Figure 40

 40 Figure 40 From the metamodel concepts & field research plan, to the field research supports

  SC performance measurement has been addressed widely in the literature. The main focus of the academic studies has been (Ahi and Searcy 2015):• Evaluating and monitoring progress, • Reporting of performance, • Identifying achievements, • Promoting improved process understanding, • Identifying critical issues, • Providing guidance for future actions, among other topics.

Figure 50

 50 Figure 50 Illustration of HSC operations sustainability conceptual "disequilibrium"

Figure

  Figure 51 A balanced SHSC performance

Figure 55 Figure

 55 Figure 55 A&C RLU SHSC sub-dimensions performance maturity level (radar graph)

Figure 60 SHSC

 60 Figure 60 SHSC Master Planning problem network elements

  ) = ∑ 𝐶𝑠𝑡𝑜(𝑐, 𝑡) × 𝑐𝑝𝑟𝑖(𝑐) × 𝑐𝑢𝑛𝑐(𝑐) 𝑡 (1c) 𝑤𝑡𝑟𝑒𝑞(𝑤) = 𝑤𝑟𝑒𝑞(𝑤) × 𝑤𝑢𝑛𝑐(𝑤)

𝐸𝑓𝑓𝑜𝑝𝑡[ 1 -

 1 (1 -𝐸𝑓𝑓𝑡𝑜𝑙)] ≤ ∑ 𝑐𝑡𝑞𝑢𝑎(𝑐) -∑ 𝐶𝑡𝑝𝑒𝑛(𝑐)

Figure 62

 62 Figure 62 Geographical locations of local suppliers, SRLU/RLU and customers

Figure

  Figure 63 Master Planning Rolling horizon

Figure 64

 64 Figure 64 Demand versus capacity per week

Figure 65

 65 Figure 65 First iteration output: Economy indicator vs. Effectiveness Tolerance variation

Figure 66

 66 Figure 66 Second iteration output: Social indicator vs. Economy Tolerance variation

Figure 67

 67 Figure 67 Third iteration output: Environment indicator vs. Social Tolerance variation

Figure 68

 68 Figure 68 Variation of the TBL indicators (LO 1 ) while varying effectiveness tolerance

RQ1:

  How to formally conceptualize what an HSC is? Why? Sustainability in the HSC RQ2: What does sustainability mean in HSC operations and how can it be assessed? How? Planning Sustainable HSC operations RQ3: How to support Decision-makers in consciously and systematically making sustainability trade-offs and exploring consequences? 1 st contribution: An HSC metamodel (what?)

Figure 69

 69 Figure 69 Perspective: Planning decision levels and tasks integration

Figure 1

 1 Figure 1 People targeted by humanitarian aid in the last decade (OCHA, 2017) ......................................

Figure 2

 2 Figure 2 Atlantic Hurricanes trends (UCSUSA 2016) ...................................................................................

Figure 3

 3 Figure 3 Trend of global displacement & proposition displaced 1997-2016 (UNHCR, 2017) ...............

Figure 4

 4 Figure 4 Disaster Management Cycle (Haddow and Bullock, 2004) ...........................................................

Figure 5

 5 Figure 5 The Humanitarian Decision-makers Taxonomy (Gralla et al. 2013) ..........................................

Figure 6

 6 Figure 6 UN clusters coordination approach ..................................................................................................

Figure 7

 7 Figure 7 HSC network (inspired from (Baharmand et al. 2015) ..................................................................

Figure 8

 8 Figure 8 Inter-agency appeals: funding requested and people targeted (OCHA, 2017) ...........................

Figure 9

 9 Figure 9 Requirements, funding and unmet requirements (source: Global Humanitarian Assistance report 2016) .................................................................................................................................................

Figure 10

 10 Figure 10 Evolution of the HSC performance expectations ........................................................................

Figure 11

 11 Figure 11 The Red Cross and Red Crescent International Mouvement .....................................................

Figure 12

 12 Figure 12 Linear sub-regional design ................................................................................................................

Figure 13

 13 Figure 13 Emergency appeal and DREF 2001-2015 (source: IFRC PADRU, 2015) ...............................

Figure 14

 14 Figure 14 Logistic services provided by the IFRC (Grenade 2015) ............................................................

Figure 15

 15 Figure 15 The general methodology of design research (Järvinen 2007) ....................................................

Figure 16

 16 Figure 16 Research methodology overview .....................................................................................................

Figure 17

 17 Figure 17 Manuscript Big Picture ......................................................................................................................

Figure 18

 18 Figure 18 Chapter 2 research positioning ........................................................................................................

Figure 19

 19 Figure 19 Adapted from Ullman's triangle ......................................................................................................

Figure 20 A

 20 Figure 20 A metamodel as an explicit representation of a domain (inspired from Guizzardi 2005) .....

Figure 21

 21 Figure 21 The Humanitarian Supply Chain domain.......................................................................................

Figure 22

 22 Figure 22 Blecken reference task framework model (Blecken 2010) ..........................................................

Figure 23

 23 Figure 23 Structuration of collaboration metamodel (Lauras et al. 2014) ..................................................

Figure 24

 24 Figure 24 The HSC metamodel layer positioning...........................................................................................

Figure 25

 25 Figure 25 Actors in the supply network of humanitarian aid from (Kovács and Spens 2007) ...............

Figure 26 A

 26 Figure 26 A 'field ordering' process model example (Blecken, 2010) .........................................................Figure 27 VSM example: "VSM for the PPE value chain" (Salvadó et al. 2015) ......................................

Figure 28

 28 Figure 28 HSC layered metamodel structure inspired on (Lauras et al. 2014) ...........................................

Figure 29 UML

 29 Figure 29 UML Relationship between classes used on the HSC metamodel ............................................

Figure 30 HSC

 30 Figure 30 HSC Context Package ....................................................................................................................... Figure 31 Objectives Package ............................................................................................................................

Figure 32 HSC

 32 Figure 32 HSC Partner's package ...................................................................................................................... Figure 33 HSC Behaviour Package ................................................................................................................... Figure 34 HSC metamodel contribution ..........................................................................................................

Figure 35

 35 Figure 35 HSC metamodel use within the diagnosis method .......................................................................

Figure 36

 36 Figure 36 HSC metamodel use within the DMAIC methode ......................................................................

Figure 37

 37 Figure 37 HSC metamodel use within Information Systems design ...........................................................

Figure 38

 38 Figure 38 HSC metamodel use within the coordination methode ..............................................................

Figure 39

 39 Figure 39 Metamodel use for A&C RLU diagnosis .......................................................................................

Figure 40

 40 Figure 40 From the metamodel concepts & field research plan, to the field research supports ............

Figure 41

 41 Figure 41 Example of the workflow grid to support the field interview protocol ....................................

Figure 42

 42 Figure 42 Linear sub-regional design ................................................................................................................

Figure 43

 43 Figure 43 IFRC sub-regionalization SWOT analyse ......................................................................................

Figure 44

 44 Figure 44 Sub-regional coordinated response .................................................................................................

Figure 45 UN

 45 Figure 45 UN Sustainable development goals ................................................................................................

Figure 46

 46 Figure 46 TBL dimensions .................................................................................................................................

Figure 47

 47 Figure 47 Sustainability with an organizational perspective (Pojasek 2012) ...............................................

Figure 48

 48 Figure 48 Sustainable SC performance WoS publications evolution ..........................................................

Figure 49

 49 Figure 49 The House of HSC Sustainable Operations ................................................................................

Figure 50

 50 Figure 50 Illustration of HSC operations sustainability conceptual "disequilibrium" ............................

Figure 51 A

 51 Figure 51 A balanced SHSC performance .....................................................................................................

Figure 52

 52 Figure 52 HSC sustainable performance maturity levels .............................................................................

Figure 53 SHSC

 53 Figure 53 SHSC Maturity assessment methode ............................................................................................

Figure 54

 54 Figure 54 Gini Index .........................................................................................................................................

Figure 55

 55 Figure 55 A&C RLU SHSC sub-dimensions performance maturity level (radar graph) .......................

Figure 56

 56 Figure 56 A&C RLU SHSC performance maturity level ............................................................................

Figure 57

 57 Figure 57 Commercial SC planning matrix (Adapted from Stadtler, 2005) .............................................

Figure 58 SHSC

 58 Figure 58 SHSC Master Planning Module in the Blecken (2010) reference task framework model....

Figure 59

 59 Figure 59 ILOM algorithm for SHSC Master Planning ..............................................................................

Figure 60 SHSC

 60 Figure 60 SHSC Master Planning problem network elements ................................................................... Figure 61 Sub-regional coordinated response ...............................................................................................

Figure 62

 62 Figure 62 Geographical locations of local suppliers, SRLU/RLU and customers .................................

Figure 63

 63 Figure 63 Master Planning Rolling horizon ...................................................................................................

Figure 64

 64 Figure 64 Demand versus capacity per week ................................................................................................

Figure 65

 65 Figure 65 First iteration output: Economy indicator vs. Effectiveness Tolerance variation .................

Figure 66

 66 Figure 66 Second iteration output: Social indicator vs. Economy Tolerance variation .........................

Figure 67

 67 Figure 67 Third iteration output: Environment indicator vs. Social Tolerance variation ......................

Figure 68

 68 Figure 68 Variation of the TBL indicators (LO 1 ) while varying effectiveness tolerance .......................

Figure 69

 69 Figure 69 Perspective: Planning decision levels and tasks integration ......................................................

Figure 70

 70 Figure 70 Perspective : Upstream and downstream integration .................................................................

  5) : Ctsto(c)/ctqua(c)<(@sum(Customer(c):Ctsto(c))/@sum(Customer(c):ctqu a(c)))+0.1); @for(Customer(c)|(cpen(c)#EQ#1.5) : Ctsto(c)/ctqua(c)>(@sum(Customer(c):Ctsto(c))/@sum(Customer(c):ctq ua(c)))-0.1); ! OBJECTIVE FUNCTIONS CONSTRAINTS; !effectiveness: !Ctpen calculation _ Penalty of the stockout par customer and product;

Table 1

 1 Examples of Humanitarian Disaster classification by hazard typology

		Natural	Man-Made (and complex
			emergencies)
	Sudden-onset	Nepal Earthquake (2015) Ecuador Earthquake (2016) Irma and Maria Hurricanes (2017)	Central African Republic, South Sudan political conflict escalation (2016) Earthquake, Tsunami and Fukushima
		Pakistan recurrent floods	nuclear disaster (2011)
			Samarco dam collapse (2015)
	Slow-onset	Sahel droughts (recurrent) Zika outbreak (2016)
		Ebola Outbreak (2013)

Table 3

 3

) were summarized by Charles et al. (2010):

Table 2

 2

Coordination barriers and enablers to implement collaboration networks involving humanitarian organizations at a local level

[START_REF] Charles | Collaboration Networks Involving Humanitarian Organisations -Particular Problems for a Particular Sector[END_REF]

Table 3

 3

Barriers and enablers to implement collaboration networks involving HOs at a global level

[START_REF] Charles | Collaboration Networks Involving Humanitarian Organisations -Particular Problems for a Particular Sector[END_REF]

  1

1.3. HSC "in the age of sustainable development" 1

	"Billions of citizens continue to live in poverty and are denied a life of dignity. There are rising inequalities within
	and among countries. There are enormous disparities of opportunity, wealth and power. Gender inequality
	remains a key challenge. Unemployment, particularly youth unemployment, is a major concern. Global health
	threats, more frequent and intense natural disasters, spiraling conflict, violent extremism, terrorism and related
	humanitarian crises and forced displacement of people threaten to reverse much of the development progress made
	in recent decades. Natural resource depletion and adverse impacts of environmental degradation, including
	desertification, drought, land degradation, freshwater scarcity and loss of biodiversity, add to and exacerbate the
	list of challenges which humanity faces."
	Transforming our world: the 2030 Agenda for Sustainable Development
	UN Assembly Resolution (2016)
	Even if world political leaders do not address the sustainable development challenges as they should,
	the commitment for sustainable development has captured public opinion, and people have become
	more sensitive to and concerned about the environmental and societal impact of their actions and
	choices. The 2030 Agenda for Sustainable Development, with 17 Sustainable Development Goals,
	emphasizes that developing a sustainable global economy is central to the debate.

Table 4

 4

SC metamodel gaps, consequences and relevance for the HSC domain (from

[START_REF] Grubic | Supply chain ontology: Review, analysis and synthesis[END_REF]

  1 ,[START_REF] Jiang | Meta-Modeling of Collaborative Supply Chain[END_REF] have developed a specific metamodel for the SC domain. Their proposal is built on Benaben's collaborative layered metamodel, with the aim of supporting Small and Medium Enterprise supply network data gathering and knowledge exploitation to optimize the logistics assets. The metamodel concepts and relationships are identified from collaborative business ontologies and reference models such as: Enterprise ontology, TOVE, SCOR, Transport ontology, etc.

  For the most important (of each of these activities), what are the main Inputs and Outputs

	• Could you explain the relationship that exists between all these activities?
	If	sufficient	time:	How	would	that	look	in	such	a	diagram?
	Hand Out Simple Diagram
	•

Table 5

 5 Humanitarian SC performance enablers[START_REF] Dubey | The sustainable humanitarian supply chain design: agility, adaptability and alignment[END_REF]

Table 6

 6 Economy sub-dimensions, definitions and criteria

	Sub-dimension	Definition	Procurement Warehousing Transport	Criteria example
						Needs coverage
	Effectiveness	The ability to satisfy demand on time	x	x	x	on time, deprivation cost
	Equity	The ability to satisfy the demand in a proportional manner (downstream)			x	Inequality measures (i.e. Gini index)
						HSC costs
	Efficiency	The ability to reduce the financial spending	x	x x	x x	(Acquisition cost + Holding cost + Kitting cost +
						Distribution
						cost)

Table 8

 8 Environment sub-dimensions, definitions and criteria

	Sub-	Definition	Procurement Warehousing Transport	Criteria example
	dimensions
	Pollution	Ability to reduce	x	x	x	Carbon Footprint
	reduction	the HSC footprint
	Resources	Ability to reduce				Resources
	conservation	resources	x	x	x	management
		consumption				capability
		(energy, water,
		packaging…)

Table 9

 9 Social sub-dimensions, definitions and criteria

	Sub-	Definition	Procurement Warehousing Transport	Criteria
	dimension					example
	Local communities empowerment	The ability to develop local wealth	x	x	x	Local procurement
			x	x	x	Employee
	Labour conditions	Ensure good conditions of work and preserve health and security of employees	x		x	management (internal) Suppliers assessment (external)

Table 11

 11

	EXCELEN T	L4	≥ 90%	≥ 5%	0%		SC flows are planned	based on LCA impact		SC flows are planned to	reduce resources	consumption	≥ 70%	SC flows are planned	based on labor	conditions
	BEGI N N ER MEDIUM GOOD	L1 L2 L3	10% ≥ Indicator <50% 50%≥Indicator <75% 75% ≥ Indicator <90%	-10% ≥ Indicator < -5% -5% ≥ Indicator < 0% 0% ≥ Indicator < 5%	50% ≥ Indicator >30% 30% ≥ Indicator <10% 10% ≥ Indicator <0%	LCA: The Carbon	The Carbon footprint is The Carbon emissions are assessed assessed occasionally systematically emissions are assessed internally + externally (upstream and	downstream)	A management system A global management	Resources use is for pollution and energy system is in place	assessed occasionally use is in place (upstream and	systematically downstream)	0% ≥Indicator <30% 30% ≥Indicator <50% 50% ≥Indicator <70%	Occasional Internal Systematic Internal Suppliers assessment assessment assessment
	UN AWARE	L0	<10%	<-10%	>50%		no info				no info		0%	no info
		Sub-dimension	Effectiveness	Efficiency	Equity		Pollution reduction			Resources	conservation	Local community	development	Labor conditions
		TBL		Economic		Environmental			Social
				SHSC performance assessment grid

Table 12

 12 Data set to assess effectiveness

	Order #	Lead time	Grand Total (CHF)	Value delivered on time (<1 week)
	1	10.00	650
	2	8.00	9107
	3	7.00	554	554.00
	4	28.00	17831
	5	22.00	15000
	6	36.00	5000
	7	5.00	50000	50000.00
	8	18.00	50000
	9	9.00	58000
	10	5.00	5000	5000.00
	11	1.00	16000	16000.00
	12	11.00	28000
	13	15.00	17000
	14	5.00	35000	35000.00
	15	5.00	136000	136000.00
	16	5.00	32000	32000.00
		TOTAL	475142	274554
		RATE	58%

Table 13

 13

	Data set to assess efficiency
		HSC Costs (year) HSC Incomes
			(year)
	Procurement costs	940,000 CHF
	Holding costs (including handling, waste and	90,000 CHF
	infrastructure)
	Service Provision Income		1,000,000 CHF
	TOTAL 1,030,000 CHF	1,000,000 CHF

Table 14

 14

			Local procurement data set
	Order #	Origin	Grand Total (CHF)	Value from local suppliers
	1	International	5000
	2	International	2000
	3	International	36000
	4	International	2500
	5	Local	300	300
	6	International	2100
	7	International	3000
	8	International	1000
	9	Local	580	580
	10	International	600
	11	Local	3000	3000
	12	Local	2500	2500
	13	International	6000
	14	International	260
	15	Local	1000	1000
		TOTAL	65840	7380
		RATE	11%

Table 15

 15 Illustrative assessment of the A&C RLU

	TBL	Sub-dimension	L0	L1	L2	L3	L4	Dimension Maturity level
		Effectiveness			x
	Economic	Efficiency			x			L2
		Equity					x
	Environmental	Pollution reduction Resource conservation	x x					L0
	Social	Local community development		x				L1
		Labour conditions				x

Table 16

 16

			SHSC Sub-dimension selection
	TBL	Sub-dimension	Criteria	(i) Master planning impact	(ii) Data accessibility
	Economic	Effectiveness Efficiency	Demand satisfaction HSC Cost Non-	Yes Yes, on variable costs	Yes (Outcome of the Master Plan) Yes Yes
		Equity	discriminatory	Yes	(Outcome of the Master
			distribution		Plan)
	Environmental	Pollution reduction Resource conservation	Carbon footprint Reduction in resource consumption	Yes* N/A	Yes, based on transport flows Difficult to quantify, need for an LCA per flow
	Social	Local community development	Local procurement	Yes	Yes (Outcome of the Master Plan)

Table 17

 17 Sustainability performance measures and indicators

				Sub-dimensions	Criteria
			Order qualifier	Effectiveness	Demand satisfaction
	TBL dimensions	winner) (order	Economy Social Environmental	Efficiency Local empowerment Pollution reduction	Variable operations cost Local sourcing rate Carbon Footprint

  Each record relates to one product and demand point throughout the time horizon.Each record relates to one constraint regarding the TBL objectives.

	fsoc(f) 5.2.3. Other Parameters Defines nearness: 1 if local, 0 any other
	fope(t,f)	The flow is operational (1) or not (0) at time t
	Symbol	Description
	fexp(t,f)	Expected products reception, defined before t0
			Input parameters
			Variables
	effopt	Optimal effectiveness constraint
	Fin(t,f)	Quantity of products received at fdes at period t
	eff_tol	Effectiveness constraint tolerance
	Fout(t,f)	Quantity of products shipped from fori at period t
	envopt	Optimal Pollution reduction constraint
	env_tol	Pollution reduction constraint tolerance
	5.2.2.2. Customer-product (demand point) object
	socopt	Optimal local empowerment constraint
	soc_tol	Local empowerment constraint tolerance
	Symbol	Description
	ecoopt	Optimal efficiency constraint	Input parameters
	cid(c) eco_tol	Customer identification Efficiency constraint tolerance
	cpro(c)	Product reference
	cunc(c)	Product standard cost
	cqua(t,c)	Units of products needed at time t
	ctqua(c)	Estimated value of the total amount of products needed by customer during the time
		horizon
	cpri(t,c)	Priority of the needs/penalty par unit
			Variables
	(f) Cin(t,c)	Origin Units of products received by the client at time t
	fdes(f) Csto(t,c)	Destination Units of stock-out products at period t
	fpro(f) Cove(t,c)	Product reference Units of over-stock products at period t
	ftlt(f) Ctpen(c)	Lead time (or flow ∆t) Total stock-out penalty value over the time horizon
	fitc(f)	Product acquisition cost
	fcost(f)	Cost (acquisition and transport) per unit
	fenv(f)	CO2 emission par unit

Table 18

 18 Model parameters

		Transport Cost	Transport emissions
	Transport type
		CHF/(T Km)	gCO2/(T Km)
	Ship long	0,001	16,05
	(from Asia)
	Ship short (within the region)	0,005	16,05
	Air	0,2	1320
	Road	0,1	81,48

Table 19

 19 Results of the Master Planning Indicators

	Indicator	Effectiveness	Economic	Social	Environmental
	Accepted	2%	1%	1%	/
	Tolerance
	Value	27 CHF Million	9.9 CHF Million	37 CHF thousand	17.7 CHF thousand
	In addition to the indicators, the model outputs are the weekly procurement and distribution flows.
	Table 20 shows a sample of the Master Planning flows allocation for the SHSC.

Table 20 SHSC

 20 Master Planning case flows allocation sample

  Table 21 summarizes the six combinations Table 21 Experimental Plan Lexicographic Orders

	Order	LO 0	LO 1	LO 2	LO 3
	A (example)	Effectiveness	Economic	Social	Environmental
	B	Effectiveness	Economic	Environmental	Social
	C	Effectiveness	Social	Economic	Environmental
	D	Effectiveness	Social	Environmental	Economic
	E	Effectiveness	Environmental	Economic	Social
	F	Effectiveness	Environmental	Social	Economic

Table 22

 22

		Experimental Plan (for a: tolerance = 0, and for b: tolerance = 1%)
	(a)	LO0	LO1	LO2	LO3
	A	98%	100%	30%	160%
	B	98%	100%	160%	30%
	C	98%	100%	125%	324%
	D	98%	100%	324%	125%
	E	98%	100%	110%	81%
	F	98%	100%	81%	110%
	Tolerance	2%	0%	0%	0%
	(b)	LO0	LO1	LO2	LO3
	A	98%	101%	44%	112%
	B	98%	101%	113%	44%
	C	98%	99%	121%	238%
	D	98%	99%	241%	121%
	E	98%	101%	108%	73%
	F	98%	101%	82%	110%
	Tolerance	2%	1%	1%	1%

Table 1

 1 Examples of Humanitarian Disaster classification by hazard typology ........................................Table 2 Coordination Barriers and enablers to implement collaboration networks involving humanitarian organizations on a local level (Charles et al. 2010) ....................................................... Table 3 Barriers and enablers to implement collaboration networks involving HOs on a global level (Charles et al. 2010) ................................................................................................................................... Table 4 SC metamodels gaps, consequences and relevance for the HSC domain .................................... Table 5 Humanitarian SC performance enablers (Dubey and Gunasekaran 2016) ................................ Table 6 Economy sub-dimensions, definitions and criteria ........................................................................ Table 7 Environmental footprint of the HSC schema, inspired from (Hervani et al. 2005) ................. Table 8 Environment sub-dimensions, definitions and criteria ................................................................. Table 9 Social sub-dimensions, definitions and criteria ............................................................................... Table 10 Sustainability performance metrics par dimension ...................................................................... Table 11 SHSC performance assessment grid ............................................................................................... Table 12 Data set to assess effectiveness ....................................................................................................... Table 13 Data set to assess efficiency ............................................................................................................. Table 14 Local procurement data set .............................................................................................................. Table 15 Illustrative assessment of the A&C RLU ...................................................................................... Table 16 SHSC Sub-dimensions selection ..................................................................................................... Table 17 Sustainability performance measures and indicators ................................................................... Table 18 Model parameters .............................................................................................................................. Table 19 Results of the Master Planning Indicators .................................................................................... Table 20 SHSC Master Planning case flows allocation sample .................................................................. Table 21 Experimental Plan Lexicographic Orders ..................................................................................... Table 22 Experimental Plan (for a: tolerance = 0, and for b: tolerance = 1%) .......................................

	7. SOCIAL COSNTRAINT
	8. ECONOMY CONSTRAINT
	9. ENVIRONMENT CONSTRAINT
	!******* 1. GENERAL CONSTRAINTS SUB MODELS **************;
	SubModel Constraints:
	! Numbero of time periods;
	NT=@SIZE(Times);
	! FlOWS CONSERVATION
	@for(MatFT(f,t)|t#LE#ftlt(f):Fin(f,t)=fexp(f,t));

Vulnerability is the characteristics determined by physical, social, economic and environmental factors or processes which increase the susceptibility of an individual, a community, assets or systems to the impacts of hazards (UNISDR,

2017).2 Exposure is the situation of people, infrastructure, housing, production capacities and other tangible human assets located in hazard-prone areas (UNISDR, 2017).

Agility is defined as (Detection + Adaptation) x Reactivity by(Bénabén

2012)

Adapted from the UN report title, 'The United Nations in the Age of Sustainable Development'

The C2NET project aims to create cloud-enabled tools which small and medium enterprises (SMEs) could afford, in order to help them to overcome the current economic crisis and to enhance their competitiveness in the global economy (C2NET Proposal, SEP

SignedEC)

In ecology, sustainability refers to the state or condition that can be maintained over an indefinite period of time.

The Council of SC Management Professionals (http://cscmp.org)

Technology Readiness Levels (TRLs) are indicators of the maturity level of particular technologies. This measurement system provides a common understanding of technology status and addresses the entire innovation chain. There are nine technology readiness levels; TRL 1 being the lowest and TRL 9 the highest (European Comission

2017).

Remerciements

Moreover, there is significant literature on SC and HSC that deals with one or several of the TBL dimensions. Indicators are abundant in the literature referring to each dimension. The difficulty remains in identifying the objectives that decision-makers need to consider in SHSC operations.

Thus, the macro-economic definition of sustainability, and the three categorical dimensions can explain sustainability on a conceptual level [START_REF] Santiteerakul | Sustainability Performance Measurement Framework for Supply Chain Management[END_REF], but do not provide much guidance on how sustainability should be measured in the context of HSC operations. Nonetheless, according to [START_REF] Haavisto | Perspectives on sustainability in humanitarian supply chains[END_REF], the sustainable performance expectations from the organization's perspective seem to have been overlooked.

Therefore, given our focus on HSC operations decision-making, we aim to address sustainable performance in the light of SC and program sustainability expectations. Nonetheless, we want to consider also the context expectations (beneficiary and societal expectations), to be coherent with the broad conceptualization of sustainability.

The ultimate objective then, is to define a performance framework that links the short-term performance expectations and the long-term impact of aid in the social and environmental dimensions, and to define a maturity model to monitor SHSC performance.

SHSC Master Planning problem

The SHSC Master Planning decision-support system has to define the material flows from suppliers to the demand points. Master Planning not only balances demand forecasts with available capacities, but also assigns demands (procurement and distribution amounts) in order to avoid bottlenecks [START_REF] Rudberg | Centralised supply chain master planning employing advanced planning systems[END_REF].

Therefore, the problem boils down to answering the following questions for a mid-term horizon:

• What (product reference) to deliver? • How much (quantity) of each item to deliver?

• When (schedule) to deliver?

• Which supplier / warehouse should provide the products?

• Where (warehouse /demand point) to deliver the items?

• How (transportation mode) to move the items?

In other words, the question is how to choose between all potential material flow combinations (within a given network and in each time horizon) those that fulfill the demand with the best acceptable performance in the three dimensions of sustainability (economic, social and environmental).

SHSC Master Planning should result in an HSC tactical plan regarding distribution, inventory, and procurement.

SHSC MASTER PLANNING

Interactive Lexicographic Optimization Method Algorithm

To plan the HSC processes from a sustainability perspective, the four indicators that were retained in previous section have to be considered in a multi-objective optimization model. As discussed previously, it is unlikely that a single solution will be found that simultaneously satisfies each optimal objective.

To choose the method, the decision-makers needs and capabilities have been considered. It is important to integrate decision-makers into the definition of an objective trade-off. However, given the difficulties in comparing the values of the objectives (i.e. carbon footprint vs. cost of operations) we made the hypothesis that decision-makers can give a priority order to the objectives.

If the decision-maker has an active role and can prioritize the objectives "a priori", the problem can be solved using the interactive variant of the ILOM. Effectiveness is an essential objective (order qualifier). The other three objectives (efficiency, local empowerment and pollution reduction) may be prioritized depending on v contextual variables: the decision level, HSC network perimeters (single or inter-organizational; upstream or downstream) or situation (disaster response, replenishment).

The proposed algorithm is illustrated by a flow chart in Figure 59. The pool on the left represents the decision-maker's tasks, while the pool on the right represents the decision-support system activities. The algorithm solves the SHSC Master Planning problem considering the four sustainable performance indicators. The execution starts when the decision-maker wants to define a Master Plan for HSC operations. But before then, (s)he has to define the HSC network model to identify potential suppliers, warehouses, forecast needs, potential transportation flows.

The algorithm is as follows (Figure 59):

(a) The first task of the decision-maker is to rank the sustainability performance objectives (economic, social and environmental) according to their relative importance or LO. This input gives the optimization order to the decision-support system (LO 1 , LO 2 , LO 3 ). LO 0 is the effectiveness, which is not prioritized but is rather considered as a prerequisite.

(b) For the decision-support system, the first activity is to solve the optimization problem with the effectiveness objective function (OF). The output of this activity (solving Sub-Model 0) is the effectiveness optimal value (O 0 ) that the model can attain with the network and forecast demand.

• Sub-model 0 Optimize: Effectiveness OF Subject to: HSC network model (c) The loop (n from 1 to 3) starts with one iteration per criterion. Following the LO approach, the Sub-model 'n' is constrained by the previous (n-1) optimal value found, but with a tolerance defined by the decision-maker. To define this tolerance, the decision-support system computes O n with a variation on the O n-1 tolerance value. For the first iteration, LO n-1 is the effectiveness, so the decisionsupport system optimizes the LO 1 Objective Function (either economic, social or environmental) with a variation on the effectiveness constraint tolerance.

• Sub-model 1 From t = 0 to t=T; Optimize: LO 1 Objective Function Subject to: HSC network model + Effectiveness Constraint(t) (d) The result is displayed to the decision-maker, who decides which is the most "acceptable" tradeoff: deteriorating the Effectiveness optimal value or improving the O 1 optimal value. The decisionmaker fixes the pair: O 1 optimal value and tolerance level t 0 .

(e) These values serve as input for the decision-support system.

The second loop (n=2) will repeat the process with LO 1 and LO 2, in order to define O 2 optimal value and tolerance level t 1 , while the third loop (n=3) repeats the process with LO 2 and LO 3 in order to define O 3 optimal value and tolerance level t 2 ,

(f) At the end of the third loop, the output is the most acceptable Master plan, based on the LO optimization and the decision-maker's expertise.

Supplier-product object

Each record relates to one product and sourcing point throughout the time horizon.

Symbol Description

Input parameters

Sid Abstract. The Humanitarian supply Chain is a key element to enhance a performing response to humanitarian crisis. Because of the internal and external pressure, Humanitarian Organizations (HO) has done efforts during last decades to improve the crisis response in terms of effectiveness and efficiency. However, the performance is challenged by the increasing gap between funding and needs. The main donors ask for more transparency and accountability. Moreover, the pressure from the international community is pushing HO to integrate Sustainability challenges on a near future. Is in this context, and field research results, that the difficulties to consider sustainability on HSC decision-making. The lack of Decision Support Systems and a sustainability culture specific to the HSC have been identified as break to improve the planning of sustainable humanitarian operations. This research work seeks to introduce the sustainability notion to the management of the HSC. The approach followed is the development of a decision support system based on performance, to plan the HSC operations.