João Martins
email: jf.martins@fct.unl.pt

Luis M Camarinha-Matos

João Goes

Luis Gomes

Towards Cloud-based Engineering Systems

Keywords: Cloud-based Systems, Cloud Computing, Internet of Things

Cloud-based Engineering Systems offer new possibilities to leverage the emerging "network effect", by relying on the access to large pools of computational resources that are available in the "cloud" to overcome the limitations of environments with scarce processing and information storage capability. The impact of this approach is already observed in most engineering domains. Motivating engineering doctoral students to look into the potential of this novel research area is essential for their education. With this aim, the doctoral conference DoCEIS'15 focused on technological innovation for Cloudbased Engineering Systems, challenging the contributors to analyze in which ways their technical and scientific work could contribute to or benefit from this paradigm. The results of this initiative are briefly analyzed in this chapter.

Introduction

With the increasing demand on engineering systems applications and the rapid development of Internet technologies, cloud-based engineering systems appear as a multi-paradigm for sharing information, software and hardware, within the Internetbased environment.

Cloud-based Engineering Systems provide a truly multi-dimensional approach for modern engineering. The application scope is not only restricted to regular cloud computing, where information and services sharing are considered on both Internet and Intranet (giving clients the power to decide what information or services to use), but it goes beyond the infrastructures, towards areas such as design, manufacturing, and supervision, where users are able to configure, select and use customized information, resources and services for product / systems achievement and operation. The location of physical resources and devices being accessed are typically not known to the end user. It also provides facilities for users to develop, deploy and manage their applications 'on the cloud', which entails virtualization of resources that maintain and manage themselves. This is achieved through the synergetic multidisciplinary integration of several service components: Infrastructure-as-a-Service, Storage-as-a-Service, Database-as-a-Service, Information-as-a-Service, Process-as-a-Service, Platform-as-a-Service, Hardware-as-a-Service, and Softwareas-a-Service and Integration-as-a-Service.

As a result, a large variety of multidisciplinary research challenges appear, where the Electrical and Computer Engineering related disciplines play a relevant role. Ranging from basic hardware to advanced software solutions, through state-of-the-art manufacturing and operation systems, the impact of Cloud-based Engineering Systems is expected to be enormous in the upcoming years.

Considering that a substantial amount of technological innovation results from the research works of doctoral students, it is important to call their attention for the potential of the Cloud-based Engineering Systems and the role they can play in the innovation process. The DoCEIS'15 (6 th Advanced Doctoral Conference on Computing, Electrical and Industrial Systems) was thus organized with this mission and some of the results are summarized in this introductory chapter.

Related Concepts and Trends

The origins of the term cloud computing, or cloud to make it shorter, are difficult to identify. These terms reached some popularity after Google and Amazon began to use them around 2006 to refer to the way people can have access to computer resources over the Web, either software, computer power, or data files, in opposition to having them on their own desktops. However, as pointed out in [START_REF] Regalado | Who Coined 'Cloud Computing'?[END_REF], a first reference to cloud computing appeared as early as 1996, in a Compaq Computer Corporation internal document, where internet cloud would accommodate moving all business software to the Web.

As a matter of fact, cloud computing has become a common jargon used to describe different kinds of solutions, or even misused to describe already available (old) products. As typically happens with other jargons, cloud computing can mean different things to different people. For some, cloud computing is only an additional marketing term. Nevertheless, the attention the area has got also motivated further developments on a number of technological facets such as security mechanisms, resource sharing, virtualization of processing capabilities, distributed storage, etc., in order to make it a reliable approach to business applications.

According to NIST (National Institute of Standards and Technology) [START_REF] Mell | The NIST Definition of Cloud Computing[END_REF], cloud computing model is composed of five essential characteristics, three service models, and four deployment models. The five essential characteristics include on-demand self-service, broad network access, resource pooling, rapid elasticity, and measured service, while the three service models are Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). Three main deployment models are considered: private cloud, community cloud, and public cloud. A fourth deployment model, hybrid cloud, is characterized as a combination of two or more distinct deployment models. The essential characteristics of cloud computing typically mentioned in the literature include:

• On-demand self-service: A consumer can access to computing capabilities, such as server time and network storage, as needed automatically without requiring human interaction with the service providers.

• Ubiquitous network access: Capabilities are available over the network and accessed through standard mechanisms that promote use by heterogeneous thin or thick client platforms (e.g. mobile phones, tablets, laptops). • Location-independent resource pooling: The customer generally has no control or knowledge over the exact location of the provided resources. The service provider assigns different physical and virtual resources dynamically according to consumer demand. • Rapid elasticity: Capabilities can be rapidly and elastically provisioned to quickly scale up and released to quickly scale down.

• Measured servicing: Cloud systems automatically control and optimize resource use by leveraging a metering capability at some level of abstraction appropriate to the type of service. This measurement is the basis for billing of the used resources.

Within the engineering areas, the cloud symbol has been used for ages to represent networks. More recently, the term has been used to describe innovative application relying on Web usage. Remarkably, as an example of how widely the concept has been adopted, two major players in the EDA (electronic design automation) community, as Cadence and Synopsis, already started migration of their EDA tools in the cloud. Synopsys claimed that their VCS tool (Functional Verification for SoC Design) is the first EDA product to become available on a public cloud, as a Software as a Service (SaaS) offering. Other than having a potential strong impact on getting access to a vast network of computational resources, adoption of could computing has a direct impact in terms of version update and maintenance of the application, because they are not needed to be installed on each user's computer.

In terms of research, many projects have been launched to explore the opportunities offered by cloud computing to the development of novel engineering systems. While several of them have been addressing the development of new platforms and base components for cloud computing (e.g. ASCETIC, BETaaS, Broker@Cloud, Cactos, CELAR, Cloud4SOA, CoherentPaaS, CloudScale, CloudSpaces, CumuloNimbo, HARNESS, HEADS, MIDAS, MODAClouds, MONDO, PaaSage, Panacea, REMICS, RISCOSS, SeaClouds, SUCRE, VISION Cloud), various others are addressing the development of cloud-based engineering systems (examples in Table 1).

As an example, Fig. 1 illustrates the GloNet project [START_REF] Camarinha-Matos | Interplay of Collaborative Networks in Product Servicing[END_REF] concept which relies on cloud-computing to deliver integrated multi-stakeholder business services enhancing complex products such as solar energy plants and intelligent buildings. Through sharing resources over a cloud-based platform and using collaboration spaces on top of this platform, networks of small and medium size enterprises can collaborate to provide services in interaction with the customer and local suppliers close to the customer, possibly located in different geographical regions.

Also in engineering education, cloud computing has been contributing to change the picture, as more and more students rely for their learning activities on resources available from the cloud, as in [START_REF] Gomes | Cloud based development framework using IOPT Petri nets for embedded systems teaching[END_REF], which also support collaborative work, even carried on from different locations.

Service provision space

(along PLM)

Cloud-based pool of resources

Geo-region A Geo-region B

Physical space

Cyber space

Fig. 1 -GloNet cloud-based engineering approach to service-enhance products Towards Cloud-based Engineering Systems 7

Also a number of other related terms have emerged to represent partially overlapping perspectives or focused application contexts. Some examples are:

Cloud-Based Industrial Cyber-Physical Systems -it is expected that cyberphysical systems (CPS) will benefit from emerging cloud computing technologies, including resource-flexibility and scalability [START_REF]Industrial Cloud-Based Cyber-Physical Systems -The IMC-AESOP Approach[END_REF]. This has the potential to improve the functionality of cyber-physical systems, as well as enabling a much wider usage of CPS's data and services.

Service-oriented Architecture (SOA) -Cloud computing adopts concepts from Service-oriented Architecture, where the user may decompose a problem into services that can be integrated to provide a solution.

Grid computing -Cloud computing can be considered as a kind of grid computing, where a cluster of networked, loosely coupled computers can cooperate in order to perform large computational intensive tasks.

Internet of Things (IoT): Understood as "a dynamic global network infrastructure with self-configuring capabilities based on standard and interoperable communication protocols where physical and virtual "things" have identities, physical attributes, and virtual personalities and use intelligent interfaces, and are seamlessly integrated into the information network" [START_REF]Vision and Challenges for Realising the Internet of Things[END_REF]. In this context, a "thing" can be understood as a real/physical or digital/virtual entity that exists and moves in space and time and is capable of being identified [START_REF] Camarinha-Matos | Contributing to the Internet of Things[END_REF].

Big data / data science: The expansion of sensing capabilities, sensor networks, smart devices, and other sources, generating huge amounts of data, requires large and elastic storage capabilities, thus a clear candidate for cloud computing.

Example Contributions

Cloud-based Engineering Systems (CES) involve a set of challenges that are particularly relevant for Electrical and Computer Engineering (ECE) researchers and professionals. Most professionals (and students) focus on a specialization sub-field, rarely mastering a comprehensive view of the whole field. However, addressing each individual problem normally requires the capability to address problems from a multidisciplinary perspective. Since CES require a "strong dialogue" among the various sub-fields of electrical and computer engineering (and other areas), it represents a particularly interesting subject to bring them together.

Under this assumption, a challenge was presented to DoCEIS'15 conference participants, which are doctoral students from various countries and different subfields, as summarized in the following alternative questions:

-In which aspects your research is directly related with Cloud-based Engineering Solutions? Or, in alternative, -In which aspects your area of work could benefit from Cloud-based Engineering Systems?

As a result, all contributors made an effort to analyze the relationship between their specific research work and the CES. Among the accepted papers there is a quite balanced distribution between those that can benefit from CES adoption and those that contribute to the development of support technologies and models for CES. A summary is given in Fig. 2, which also includes the percentage of contributions in each specific sub-field. Amongst the areas that can either benefit from a CES or with a direct relationship with CES, energy management is the most represented in terms of submissions to the conference. This is certainly a result of the current challenges faced by society regarding the development of sustainable energy solutions. The materialization of smart grids strongly relies on ICT and sensing / measuring capabilities in order to shift the emphasis from the traditional "predict and supply" model to a more flexible and responsive "demand-based" model [START_REF] Fang | Managing smart grid information in the cloud: opportunities, model, and applications[END_REF]. The integration of grid and cloud will be one of the key trends in CES development, in order to optimize cloud-based services, grid services and e-infrastructures. The full realization of this idea requires highly distributed cyber-physical functionalities, but also the involvement of the customers in close (collaborative) interaction with providers, a process that should go far beyond the traditional client-supplier relationship. The concept of cloud-based engineering systems can help reaching a shared vision of long-term sustainability and facilitate more effective use of resources.

Manufacturing is another area indicated as major potential beneficiary. "Cloud Manufacturing (CM) is a customer-centric manufacturing model that exploits ondemand access to a shared collection of diversified and distributed manufacturing resources to form temporary, reconfigurable production lines which enhance efficiency, reduce product lifecycle costs, and allow for optimal resource loading in response to variable-demand customer generated tasking" [START_REF] Wu | Cloud manufacturing: Strategic vision and state-of-the-art[END_REF]. In reality, cloud manufacturing is a misleading or meaningless term; it should better be referred to as cloud-based manufacturing. Achieving truly agile manufacturing systems, able to dynamically adjust to market dynamics, requires novel approaches that take the shopfloor as a collaborative ecosystem of (progressively more) intelligent and autonomous machines / resources. On the other hand, there is a need for stronger synergies among the various engineering areas involved in product design, manufacturing system design, manufacturing system deployment, manufacturing system operation, etc., which can also benefit from the conceptual insights of cloud-based systems.

In terms of conceptual and technological contributions to the development of CES, DoCEIS'15 includes a vast number of elements, ranging from the hardware level (electronic devices, sensors, telecommunication devices and systems), to software (interfacing and computing methods and models, advanced signal processing techniques, etc.), including specific approaches for embedded systems design.

Last but not less important, other important areas indicated as major potential beneficiaries are healthcare and elderly care, and human interaction. Application examples such as, 3D hand gesture recognition, 3D human scanning solutions, health monitoring systems, high-resolution medical imaging processing and pathological speech and voice identification benefit naturally from CES since huge amounts of data have to be acquired, stored and processed in real time.

Given the scope of DoCEIS, the mentioned contributions are naturally biased by an engineering perspective. The development of advanced cloud-based engineering systems would, however, require the involvement of other disciplines.

Concluding Remarks

The increasing development of Cloud-based Engineering Systems will surely have a strong impact in many sectors of society, where some impacts are already visible. This development will be enlarged by flexible architectures, advanced compatibility mechanisms and new engineering methods. The increased Internet resources will stimulate market-oriented applications, while the integration of grids and cloud surely provide new services and e-infrastructures, opening excellent opportunities for the area of Electrical and Computer Engineering. Several current topics, ranging from the impact of emerging technologies on Cloud-based Engineering Systems to which services/enterprises/business are suitable to move to the cloud, are clearly reflected in the contributions to the DoCEIS'15 doctoral conference.

Fig. 2 -

 2 Fig. 2 -DoCEIS'15: Relationship to (and Benefits from) Cloud-based Engineering Systems.

Table 1 .

 1 A few examples of cloud-based engineering projects

	Project	Focus	URL
	ARTIST	Software modernization approach based on Model	www.artist-project.eu/
		Driven Engineering techniques to automate the
		reverse and forward engineering of legacy
		applications to and from platform independent
		models, based Cloud Computing and related
		business models.
	BigFoot	Platform-as-a-Service solution for processing and	www.bigfootproject.eu/
		interacting with large volumes of data coming
		from ICT Security, Smart Grid and other
		application areas
	ClodFlow	Enabling the remote use of computational	www.eu-cloudflow.eu/
		services distributed on the cloud, seamlessly
		integrating these within established engineering
		design workflows and standards.
	CloudSME	Scalable platform for small or larger scale	www.cloudsme.org/
		simulations, and enable the wider take-up of
		simulation technologies in manufacturing and
		engineering SMEs.
	ClouT	Leveraging cloud computing as an enabler that	http://clout-project.eu/
		bridges the Internet of Things with the Internet of
		People via the Internet of Services, in support of
		smart cities
	GloNet	Design, develop, and deploy an agile virtual	www.glonet-fines.eu/
		enterprise environment for collaborative networks
		of SMEs involved in highly customized and
		service-enhanced products through a cloud-based
		platform
	MSEE	Establishing foundations for service-oriented	www.msee-ip.eu
		virtual factories and enterprises, including service
		Clouds.
		Collaborative
		solution space
		(co-creation playground)
			Local
			supplier
		Pool of
		European Manufacturers
		Customer

Acknowledgments. This work was supported in part by the GloNet project (FP7 program) funded by the European Commission, as well as partially financed by Portuguese Agency "FCT -Fundação para a Ciência e a Tecnologia" in the framework of project PEst-OE/EEI/UI0066/2011.


Paula Graça
email: mgraca@deetc.isel.ipl.pt

Luís M Camarinha-Matos

The Need of Performance Indicators for Collaborative Business Ecosystems

Keywords: Collaborative Network, Digital Ecosystem, Business Ecosystem, Digital Business Ecosystem, Performance Indicators

During last decades there has been a trend to build collaboration platforms as enablers for groups of enterprises to jointly provide integrated services and products. As a result, the notion of business ecosystem is getting wider acceptance. However, a critical issue that is still open, despite some efforts in this area, is the identification of adequate performance indicators to measure and motivate sustainable collaboration. This work-in-progress addresses this concern, briefly presenting the state of the art of relevant contributing areas such as, collaborative networks, business ecosystems, enterprise performance indicators, social networks analysis, and supply chains. Complementarily, through an assessment of current gaps, the research challenges are identified and an approach for further development is proposed.

Introduction

The concept of Business Ecosystem was introduced by Moore in the 1990s [START_REF] Moore | Predators and prey: a new ecology of competition[END_REF], using natural ecosystems as a biological metaphor to explain a business environment. The author considers a business ecosystem "an economic community supported by a foundation of interacting organizations and individuals -the organisms of the business world. This economic community produces goods and services of value to customers, who themselves are members of the ecosystem". Furthermore, he highlights the interdependence between all the actors of the ecosystem, who "coevolve their capabilities and roles" [START_REF] Moore | The death of competition: leadership and strategy in the age of business ecosystems[END_REF].

This concept has been refined in the last two decades, namely as a result of the enabling role of ICT. One example is the emergence of the term Digital Business Ecosystem (DBE) [START_REF] Nachira | Towards a network of digital business ecosystems fostering the local development[END_REF], which puts a stronger emphasis on the technological support perspective. The DBE concept was primarily introduced as a policy strategy to address the challenge of achieving for every industry, sector and region, an effective adoption of ICT, namely enabling SMEs to become more innovative and competitive in global markets [START_REF] Nachira | A network of digital business ecosystems for Europe: roots, processes and perspectives[END_REF]. As such, it can be considered as a natural evolution of the business environment, from the e-mail and web-sites, to e-commerce and collaborative e-business. The DBE notion follows Moore's inspiration in natural ecosystems, but expressed it in terms of a "digital environment" populated by "digital species" which could be software components, applications, services, knowledge, business models, training modules, contractual frameworks, laws, etc. These "digital species", like the living species, interact, express an independent behavior, end evolve -or becomes extinct -following the laws of market selection [START_REF] Nachira | Towards a network of digital business ecosystems fostering the local development[END_REF].

On the other hand, the emergence of the discipline of Collaborative Networks [START_REF] Camarinha-Matos | Collaborative networks: A new scientific discipline[END_REF] which has a wider scope, allowed to classify business ecosystems as a sub-class of a virtual organization breeding environment (VBE), which acts as a source network of organizations, providing an adequate collaborative environment (common business processes, interoperable infrastructures, mutual trust, among others) [START_REF] Camarinha-Matos | Collaborative Networks: Reference Modeling: Reference Modeling[END_REF]. To answer to nowadays demanding market challenges, organizations must collaborate to overcome their weaknesses and strengthen their expertise, to offer better integrated services and gain competitive advantage. In order to emphasize this perspective, the term Collaborative Business Ecosystem can be adopted.

However, in spite of the potential benefits of collaboration, many networks face difficulties as it is not always obvious to each of its members what they can benefit. Unlike the case of individual enterprises management, for which there are wellknown indicators and balanced scorecards [START_REF] Kaplan | The balanced scorecard: translating strategy into action[END_REF], for enterprise networks in general, and even for business ecosystems in particular, there is still a lack of well identified and widely accepted performance indicators to measure collaborative benefits, motivating sustainability, and ensuring ecosystem's resiliency. This work is motivated by this need, and is led by the following research question:

What can be a suitable approach to assess collaboration performance and promote collaboration sustainability in collaborative business ecosystems?

For a better understanding of the proposed research contributing, this main research question is further divided into two sub-questions: What is a reasonable set of key performance indicators to measure and assess collaboration benefits in a collaborative business ecosystem? How to promote collaboration sustainability and resilience within a business ecosystem?

In order to find an answer for these questions, our research is guided by the following corresponding hypotheses: (H1) Collaboration benefits can be evaluated and made explicit if a set of indicators is established through a holistic combination of concepts on value and benefit derived from a number of research areas such as value systems, social networks analysis, supply chain performance, and theories of complexity. (H2) Sustainability and resilience of collaboration in business ecosystems can be promoted if a system of incentives, combined with transparent assessment methods, is implemented at the ecosystem level. In this context, this work corresponds to only the first stage, where the state of the art of the most relevant contributing research areas is analyzed, main gaps are identified, and promising directions to overcome these gaps are proposed.

Relationship to Cloud-based Engineering Systems

Nowadays cloud computing is changing the way the organizations manage their ICT resources and expertise. Cloud servers, cloud storage, and more generically cloud platforms offer to enterprises, more economic, scalable, and secure infrastructures for them to manage their business. This trend is contributing to boost emergent collaborative platforms operating in the cloud and offering network infrastructures and tools to logically connect individual organizations, under a common collaboration context. Such context is defined as a set of services under a coordinated choreography on contributing for some valuable objective, allowing interoperability between people or systems that can work together for some business goals [START_REF] Osório | Cooperation Enabled Systems for Collaborative Networks[END_REF]. These generic collaboration spaces support virtual organizations and virtual organizations breeding environments, being particularly promising for SME networks [START_REF] Osório | Enterprise Collaboration Network for Transport and Logistics Services[END_REF]. Complementarily, the developments on Internet of Things, facilitating access to a large number of information sources, enable the materialization of the concept of sensing enterprise and the effective implementation of better performance measurement mechanisms.

Brief Survey of the State of the Art

Our attempt to establish performance indicators for collaborative business ecosystems considers input knowledge from a number of research areas such as collaborative networks, business ecosystems, enterprise performance indicators, social networks analysis, and supply chain. An overview of these areas is presented below, briefly characterizing them and highlighting important aspects for the proposed work:

Collaborative Networks (CNs), one of the main contributing scientific disciplines on which this research work is based. A CN is defined as "a network consisting of a variety of entities (e. g. organizations and people) that are largely autonomous, geographically distributed, and heterogeneous in terms of their operating environment, culture, social capital and goals, but that collaborate to better achieve common or compatible goals, and whose interactions are supported by computer networks" [START_REF] Camarinha-Matos | Collaborative networks: A new scientific discipline[END_REF], [START_REF] Camarinha-Matos | Collaborative Networks: Reference Modeling: Reference Modeling[END_REF]. Important foundations for this area were earlier established by projects such as THINKcreative, VOmap, VOSTER, ECOLEAD, and many others. A large diversity of collaborative networks can nowadays be identified on a variety of sectors in industry and services. In order to better understand this diversity, some efforts focused on the establishment of reference models, such as ARCON [START_REF] Camarinha-Matos | Collaborative Networks: Reference Modeling: Reference Modeling[END_REF]. According to ARCON, collaborative networks are divided into two main groups, the organized collaboration and the ad-hoc collaboration. The organized collaborative networks are in turn divided into long-term strategic networks and goaloriented networks, where participants are linked together to drive a continuous specific activity, or to grab a business opportunity. Under this classification, a Business Ecosystem is seen as a sub-class of long-term strategic networks. Supply chains are considered as a particular case of goal-oriented networks. In fact, traditional supply chains tend to evolve to more collaborative structures, leading to the concept of Supply Chain Collaboration (SCC). A SCC can be defined "as a longterm partnership process where supply chain partners with common goals work closely together to achieve mutual advantages that are greater than the firms would achieve individually" [START_REF] Cao | Supply chain collaboration: conceptualisation and instrument development[END_REF].

While most works on collaborative networks have mainly addressed issues of collaboration support infrastructures and tools, organizational and governance models, very few references can be found on performance measurement in enterprise networks. The exception is perhaps the case of supply chains for which some works can be found. For instance, [START_REF] Botta-Genoulaz | Supply Chain Performance: Collaboration, Alignment, and Coordination[END_REF] identifies different levels or intensity in the collaboration, which are categorized into two types of collaborative practices. The first one considers the exchange of information as the most basic form of collaboration, distinguishing two broad groups depending on the closeness, information exchange or process integration, also called structural collaboration [START_REF] Vereecke | Performance improvement through supply chain collaboration in Europe[END_REF]. The second one considers three gradual organizational and decision-making levels (operational, tactical and strategic), i.e. the higher the degree of partners' relationships towards process integration, the stronger the interaction, sophisticated information technology, and organizational commitment among them.

Business Ecosystems. Since the introduction of the Business Ecosystem concept by Moore [START_REF] Moore | Predators and prey: a new ecology of competition[END_REF], [START_REF] Moore | The death of competition: leadership and strategy in the age of business ecosystems[END_REF], several other researchers have focused on the ICT support to this organizational structure, as illustrated by the notion of Digital Business Ecosystem [3][4]. Various authors have explored analogies between natural ecosystems and mechanisms provided by computational models such as service-orientation, multiagent systems, and swarm intelligence. Two examples can be found in [START_REF] Chang | Digital Ecosystems A Next Generation of the Collaborative Environment[END_REF], [START_REF] Boley | Digital Ecosystems: Principles and Semantics[END_REF]. These authors worked towards the establishment of the basis of a digital ecosystem, considering it as a collaborative environment, where the key elements are the "species" and the environment comprising support technologies and services. The species are "biological -humans", "economicorganizations", and "digitalcomputers, software, applications,…" linked by networks and interacting with each other to achieve benefits and objectives. Another example is given by the work of Briscoe [START_REF] Briscoe | Digital ecosystems[END_REF], [START_REF] Briscoe | Complex adaptive digital ecosystems[END_REF], which uses modeling techniques from complex adaptive systems and multi-agent systems to create a generic definition inspired by biological ecosystems, which abstractly defines the key properties, behavior, and structure of an ecosystem. The emphasis in this line of research has been, so far, more oriented to the structure, organization, behavior, and technological support of the ecosystem. Therefore, and to the best of our knowledge, the aspects of performance of such systems remain an open issue.

Performance Indicators (PI) are financial and non-financial metrics used to quantify objectives and reflect strategic performance of an organization. This kind of metrics has been largely developed for individual enterprises management but not so much to assess collaborative strategy and benefits. Nevertheless, some research lines have generated a number of elements that can be taken as a basis for the development of performance indicators tailored to collaborative networks. One of these lines has pursued the identification and characterization of collaboration benefits and value systems. Another relevant line is the social networks analysis, which has established several metrics related to graph structures. In summary:

Collaboration Benefits. A number of works have tried to model (business) benefits resulting from collaboration. One example is an estimation model for business benefits in horizontal collaborative networks for product development [START_REF] Piot | An estimation model for business benefits in horizontal collaborative networks[END_REF], which considers four phases: 1) Estimation of the opportunities that should be generated by the network; 2) Construction of the product realization graph giving a weight to each opportunity, 3) Identification of the best consortium to develop the product, and 4) Summation of the earnings. Another work [START_REF] Abreu | A benefit analysis model for collaborative networks[END_REF] suggests a set of collaboration benefits through the identification of cooperation variables and respective target goals. In this work it is argued that the perception of collaboration benefits are related to the two strategic goals perspectives -performance increase and survival capacity. Our research question is somehow in line with this perception. Although these early works have contributed to a better understanding of collaboration benefits, the proposed indicators have not been specifically tailored to collaborative business ecosystems. Furthermore, validation of these indicators in terms of their contribution to promote collaboration sustainability and resilience has not been extensively done yet.

Value Systems. Progress has been made in terms of conceptualization of value systems for collaborative networks, namely through combining views coming from the social sciences and the economy. One example is a conceptual model for value systems for collaborative networks [START_REF] Camarinha-Matos | A conceptual model of value systems in collaborative networks[END_REF], based on the identification of objects that can be evaluated, and the elements that represent the mechanisms of evaluation. More recent developments of this work [START_REF] Macedo | A Qualitative Approach to Assess the Alignment of Value Systems in Collaborative Enterprises Networks[END_REF] suggest methods to assess the alignment of value systems of different members of a network. The proposed system remains, however, quite limited when it comes to the evaluation mechanisms. Another proposal for a conceptual model, formalizes a value system for a VBE [START_REF] Romero | A conceptual model for virtual breeding environments value systems[END_REF], and a corresponding performance measurement system. This system intends to evaluate the value co-creation process through a set of indicators that quantify the VBE results, making easier to monitor its progress. The authors also propose the balanced scorecards (BSC) to monitor the performance measurement. A BSC is a classical method [START_REF] Kaplan | The balanced scorecard: translating strategy into action[END_REF] composed of a set of performance indicators strongly aligned with the vision and strategy of the enterprise, and which represents an innovation compared to other types of metrics existing at the time focused only on financial indicators, by the combination of lagging and leading indicators, resulting not only in historical indicators, but also in predictable results. These proposals, e.g. [START_REF] Romero | A conceptual model for virtual breeding environments value systems[END_REF], remain, however, at a general conceptual level, without providing concrete indicators.

Social Network Analysis. The large adherence of people to social networks has motivated a substantial amount of research, often under the umbrella of Social Network Analysis (SNA). A number of research works have also attempted to borrow methods and indicators from SNA to apply in collaborative networks. But there are also a number of arguments pointing to the limitations of SNA when adopted for the analysis of business networks, namely: i) the empirical link between organizationallevel structure and firm-level performance is not adequately demonstrated; ii) links in a social network allow a structural analysis, such as degrees of separation between nodes, "betweenness", "closeness", among others, but do not address economic or social value creation; iii) all links in a social network are of the same nature and only one link is represented between actors, not allowing, for instance, to distinguish social or economic exchanges; and iv) to analyze and interpret the network patterns requires high level of expertise. An attempt to overcome these limitations is the work of Allee [START_REF] Allee | Value Networks and the true nature of collaboration[END_REF], which introduces the concept of Value Network Analysis (VNA). A VNA is defined as "any purposeful group of people or organizations creating social and economic good through complex dynamic exchanges of tangible and intangible value" [START_REF] Allee | Value Networks and the true nature of collaboration[END_REF]. According to the author, a value network is a "human-centric, role-based, network view of any business activity". A set of metrics for managing collaborative work have been proposed in this context, representing a promising direction.

Research Approach

The analysis of the literature, as briefly shown above, shows that an adequate approach to measure and manage performance in collaborative business ecosystems is not available yet. However, several partial and, to some extent, complementary contributions can be found in a number of research fields. Bringing together all these contributions, can provide a promising direction towards identifying suitable performance indicators that not only help in performance measurement, but also contribute to the promotion of collaboration sustainability and resilience. As a result, our research approach is driven by 3 main pillars as illustrated in Fig. 1: (1) An organizational and collaborative framework, to provide an understanding of the structure, organization and behavioral aspects of the collaborative business ecosystem; [START_REF] Moore | The death of competition: leadership and strategy in the age of business ecosystems[END_REF] Performance indicators and mechanisms, to allow quantitative assessment of performance and potential benefits for the ecosystem members and the ecosystem as a whole; (3) A set of enablers, mainly provided by ICT infrastructures and new computational models that inspire and support various alternatives of organizational structures and simulation models. The initial phase of the work allowed identifying the potential contributions from each of the mentioned areas and putting them into a context. One difficulty with establishing performance indicators is that their actual value depends, to a large extent, on their acceptance by the involved community. Therefore, it is not strictly and issue of "proving" their validity in classical research terms. If a set of indicators are reasonably coherent, and based on a logical foundation, their value depends on their acceptance. As such, our approach tries to (1) guarantee the first requirements, and (2) create conditions for their acceptance.

Regarding the first aspect, at the current stage, a consolidation and formalization of concepts is being developed, together with the design of measurement mechanisms. In addition to inputs from the contributing areas mentioned above, grounded theory methods are also considered as they are likely to facilitate the capture of knowledge about the reality, behavior and interactions of the participants in a shared social context, the business ecosystem. All collected data from different formal and informal sources, allow an identification of key concepts and its categorization, leading to the establishment of collaborative performance indicators. Grounded theory emerged from the discipline of sociology, focused on society and the individual. However it has been broadening to incorporate issues with significant behavioral implications, such as ethical marketing, social marketing, green issues and experiential consumption [START_REF] Goulding | Grounded theory, ethnography and phenomenology: A comparative analysis of three qualitative strategies for marketing research[END_REF], thus appearing to be also suitable for business ecosystems. A business ecosystem can be characterized by a set of key properties taken from a generic ecosystem inspired by biological ecosystems, combining attributes of digital, business, and social ecosystems: i) the environment is the economy of society, where agents are the businesses which influence and are influenced by the environment; ii) the population and evolution match the business domain, in which the evolutionary theory of capabilities and behavior of business firms is applicable; iii) the community matches the social domain, referring to a social unit that shares common values regardless of physical location, since, instead of being located in the same geographical region, participants are connected by a digital common infrastructure supported by ICT technologies [START_REF] Briscoe | Complex adaptive digital ecosystems[END_REF].

Regarding the second aspect, we pursue the second research sub-question related to the use of the performance indicators to promote collaboration resilience and sustainability. The vision is that achieving resilience and sustainability will give a strong argument to promote wide acceptance of the proposed indicators.

At the same time, suitable validation scenarios are being analyzed. The main obstacle to the implementation of this approach is the lack of historic data or benchmarks to support effective validation. Furthermore, the main goals of using such performance indicators to promote collaboration sustainability and resilience can only be verified in the long term, a typical difficulty in most research on Collaborative Networks. Therefore, the designed validation strategy combines a mix of methods including: (partial) case studies, simulation, ethnographic methods (mainly involving business ecosystem managers), and grounded theory. Furthermore, the simulation seems to be a promising strategy, because existing specific models consistent with evolutionary theory, can be applied to business ecosystems.

Conclusions and Further Work

The analysis of the state of the art in relevant areas shows that although various relevant contributions can be found, there is still an important gap: the inexistence of adequate and effective methods for evaluation of collaboration benefits in business ecosystems. This gap points to the need of identifying suitable performance indicators and associated measurement mechanisms that can promote collaboration and cohesion of the ecosystem's members. Thus, a research strategy was designed towards developing a contribution to the survival of organizations in an aggressive and turbulent market environment. After the first stage of our work, the research framework and a preliminary solution design are achieved. The development and validation steps correspond to ongoing work.

Fig. 1 -

 1 Fig. 1 -Research strategy


Ana Inês Oliveira

Luis M Camarinha-Matos

Negotiation Environment and Protocols for Collaborative Service Design

Keywords: Collaborative Networks, Negotiation Support Environment, Business Services, Co-Design, Co-Creation, Negotiation Protocol

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Due to market unpredictability and new requirements, companies and organizations need to adapt themselves to maintain competitiveness. One option is to move from the "traditional enterprise" concept to a new business paradigm where enterprises can strategically access to each other's markets by joining competences and sharing skills and costs, resulting in a new collaboration structure of enterprises. The collaborative network concept is increasingly adopted to support organizations and companies in this change of paradigm, as it can provide agility and survival mechanisms that facilitate companies to survive to market turbulences [START_REF] Camarinha-Matos | Collaborative Business Scenarios in a Service-Enhanced Products Ecosystem[END_REF]. Nevertheless, there are some obstacles, for example: how to find or choose the right partners; lack of common or standard formats for basic profile of organizations; how to define and reach agreements for roles and responsibilities of each partner and of course how to predict associated collaboration risks.

Another important aspect that requires attention is the increasing demand from customers for highly customized products. Therefore, one tendency for manufacturers is to associate business services to the products they offer [START_REF] Camarinha-Matos | Collaborative Business Scenarios in a Service-Enhanced Products Ecosystem[END_REF]. From a collaborative perspective, these services are designed and created by multiple stakeholders to meet the individual customer's needs and/or requirements. This also brings the need to follow some service design methodology, which typically is a non-structured approach. In this context, the European research project GloNet was carried out with the aim to design, develop and deploy an environment to facilitate networks of SMEs to collaborate and achieve highly customized service-enhanced products [START_REF] Camarinha-Matos | Collaborative networks in support of service-enhanced products[END_REF]. The interaction with the customer and local suppliers is fundamental and leads to the notion of co-creation of products and business services. For the formation of such networks, one important requirement is the existence of an established negotiation process to improve the generation of agreements that facilitate collaboration and lead to the governing rules and principles of the consortium during its operation phase [START_REF] Rabelo | A Governance Reference Model for Virtual Enterprises[END_REF].

Considering this background context [START_REF] Di Maio | An open conceptual framework for operationalising collective awareness and social sensing[END_REF] that supports and fosters the creation of dynamic virtual organizations (VOs), the research question addressed by this work is:

How can an electronic negotiation support environment increase the agility in the process of successfully creating dynamic virtual organizations?

An important motivation for this work is that by contextualizing the design of a new business service in a collaborative environment, it can also use the same negotiation support environment mechanisms to reach agreements, as the ones that are used for the VO creation process [START_REF] Oliveira | Agreement negotiation support in virtual organisation creation-an illustrative case[END_REF][START_REF] Oliveira | Electronic Negotiation Support Environment in Collaborative Networks[END_REF][START_REF] Oliveira | Negotiation Support for Co-design of Business Services[END_REF].

Relationship to Cloud-based Solutions

Cloud computing provides its users with different levels of solutions in the form of services: infrastructure, platform, and software as a service. Depending on the user requirements, it provides services based on a distributed and parallel processing, improving reliability, storage capacity, and service efficiency [START_REF] Ma | Integration of Digital Campus Resources Based on Cloud Computing[END_REF] when compared to traditional solutions. In the existing market volatility, it is crucial for companies to guarantee that their applications and services are always accessible. So, through a cloud-based solution companies can, in principle, reduce their costs [START_REF] Ma | Integration of Digital Campus Resources Based on Cloud Computing[END_REF][START_REF] Ostermann | A performance analysis of EC2 cloud computing services for scientific computing[END_REF], as they don't have to keep complex private infrastructures.

While in the manufacturing and services industry the trend is to move towards a global networked economy, cloud-based solutions potentiate collaboration platforms to support the establishment and operation of the involved enterprise networks [START_REF] Camarinha-Matos | Cloud-Based Collaborative Business Services Provision[END_REF]. Considering the co-design of new business services where different and diverse stakeholders intervene in the process to achieve new business services design, the cloud-based solutions appear with relevance once they can facilitate the development of new collaborative processes [START_REF] Camarinha-Matos | Cloud-Based Collaborative Business Services Provision[END_REF]. This work is developed in such context and builds on top of a cloud-based collaboration platform [START_REF] Surajbali | A Cloud-Based Approach for Collaborative Networks Supporting Serviced-Enhanced Products[END_REF].

Context and Related Areas

To contextualize the negotiation support for service co-design and related negotiation protocol, this section gives a brief overview of the literature.

Business services and composite business services. A business service refers to an organized set of added value activities from a business perspective [START_REF] Brentani | Innovative versus incremental new business services: different keys for achieving success[END_REF], considering issues such as the delivery conditions, service level agreements, period, availability, etc. [START_REF] Camarinha-Matos | Collaborative Business Scenarios in a Service-Enhanced Products Ecosystem[END_REF]. It corresponds to the service provided to the customer, and can be implemented by manual services and/or software services whose flow can be modeled through business processes. Also, business services provided to the customer can be composed of several atomic business services [START_REF] Camarinha-Matos | Cloud-Based Collaborative Business Services Provision[END_REF]. In such situation, service providers of each business services can together form a virtual organization to deliver the composite business through a new entity that is the service integrator (that acts as the service provider of the composite business service) [START_REF] Camarinha-Matos | Collaborative Business Services Provision[END_REF].

GloNet co-Creation Network. One of the GloNet project assumptions is that if networks of SMEs are supported by an environment that facilitate collaboration, then they can achieve highly customized service-enhanced products [START_REF] Camarinha-Matos | Collaborative networks in support of service-enhanced products[END_REF]. Here the notion of co-creation networks appears as a concept that is based on collaboration between manufacturers, customers, and members of customers' community [START_REF] Camarinha-Matos | Collaborative Business Scenarios in a Service-Enhanced Products Ecosystem[END_REF]. These networks aim to co-design and co-innovate value-added services for products when new promising business ideas emerge [START_REF] Camarinha-Matos | Supporting product-servicing networks[END_REF]. Also, an analysis of the IT implementation requirements of those business applications can be performed [START_REF] Yang | Research on the cooperative decision of business application needs in IT governance[END_REF].

Service Design. This is an interdisciplinary area that emerged as a contribution to a changing context from the growing economy of the services sector and the traditional culture of design [START_REF] Sangiorgi | Building up a framework for Service Design research[END_REF]. Service design integrates relevant stakeholders in the design of services through some methodological approach [START_REF] Mager | Special issue editorial: Designing for services[END_REF]. Service design aims at designing user-oriented services making them useful, effective and different from existing ones. It potentiates co-creation between the different users of a service, and the providers [START_REF] Sandberg | Co-creating collaborative food service opportunities through work context maps[END_REF]. In the different service design activities, especially in cocreation, not all stakeholders need to be involved at the same time; they can be involved just in the specific moments or situation in which they take part [START_REF] Sanders | Co-creation and the new landscapes of design[END_REF], which applies to the co-creation and co-design case of GloNet. There are a number of methods and tools for service design that have been emerging [START_REF] Wild | Review of Service Design Methods[END_REF], some of which can be found in http://www.servicedesigntools.org/.

Negotiation Protocols. In negotiation processes it is fundamental that a protocol is defined so that an agreement can be achieved. The negotiation process includes several interactions that are based on the exchanging of some arguments and opinions on the form of dialogues [START_REF] Moschoyiannis | Verifiable protocol design for agent argumentation dialogues[END_REF]. The dialogues that take place can include some form of argumentation in favor or against certain statements [START_REF] Caminada | On the evaluation of argumentation formalisms[END_REF]. Depending on the context, the arguments used can be constructed from a knowledge base in an argumentative system [START_REF] Prakken | An abstract framework for argumentation with structured arguments[END_REF], or from a rule-based system [START_REF] Caminada | On the evaluation of argumentation formalisms[END_REF]. Typically protocols for negotiation based on argumentation can be found in agent systems where agents have a certain level of intelligence and at some point have to make their options and create some arguments [START_REF] Aknine | An extended multi-agent negotiation protocol[END_REF][START_REF] Wang | A hybrid multi-agent negotiation protocol supporting agent mobility in virtual enterprises[END_REF]. In these cases, although there are already some agent communication languages such as ACL, KQML, etc., that try to cope with some of the requirements for negotiation [START_REF] Beer | Negotiation in multi-agent systems[END_REF], there are still open issues, namely the existence of some limitations in multilateral negotiation when compared to one-to-one bilateral negotiations [START_REF] Wang | A hybrid multi-agent negotiation protocol supporting agent mobility in virtual enterprises[END_REF].

Research Contribution and Innovation

According to the different natures of collaborative networks, namely virtual organizations (VOs), the formation process of new VOs for collaboration can be diverse. Nevertheless, as illustrated in Fig. 1, typically, involved processes include some common steps, that go from the new business or collaboration opportunity (BO/CO) discovery, to the formation of the new consortium to rapidly respond to it [START_REF] Oliveira | Agreement negotiation support in virtual organisation creation-an illustrative case[END_REF]. Although the selection of the adequate partners to form the consortium is of extreme relevance, the consensus that is reached among them is of no less importance once it can serve as the basis for the operating principles of the VO. Therefore, if the process of reaching and negotiating agreements among participants can be supported by an ICT environment, then the entire process of VO formation and negotiation can become smoother [START_REF] Oliveira | Agreement negotiation support in virtual organisation creation-an illustrative case[END_REF][START_REF] Oliveira | Electronic Negotiation Support Environment in Collaborative Networks[END_REF][START_REF] Oliveira | Negotiation Support for Co-design of Business Services[END_REF]. When designing a new business service (BS), a team of interested stakeholders already exist (acting like a VO) with the aim of reaching agreements on the design requirements of the new BS. In line with the previous assumptions and with the research question mentioned in section 1, the hypothesis that supports the current research work is:

The process of creating dynamic virtual organizations can become more agile if an appropriate electronic negotiation wizard environment is established with the necessary soft modeling characteristics to structure and conduct the entire negotiation process, making it traceable, reducing the collaboration risks, and managing the participants' expectations. Moreover, the negotiation environment should be customizable according to different collaboration levels, either in terms of commitment or in terms of duration.

Therefore, a negotiation support environment is also expected to facilitate and boost the participation in business service design allowing its participants to collaborate in a co-creation environment, reducing the potential collaboration risks, and supporting different levels of collaboration. Given so, the main mechanisms for the negotiation support environment are, on one hand, to support negotiation for the classical VO formation that includes: negotiation towards the selected partners; negotiation details with partners; and negotiation with the customer; and on the other hand, to support negotiation in co-design and co-innovation.

Requirement analysis CO/BO

Planning

Partners selection VO Composition

Detailed plan

Contracting

NEGOTIATION

Service Design Methodology. To design new business services, a service design methodology has been adopted [START_REF] Oliveira | Negotiation Support for Co-design of Business Services[END_REF]. This methodology identifies and defines the needed services and their interactions with the customer, and their nature. The methodology is summarized in Table 1.

Table 1. Service Design Methodology in co-creation teams.

Service Design steps Description

Identify needed service Brainstorming exercise involving an analysis of the needs and characteristics of the customer.

Design touchpoints diagram

To identify user interaction points with the service.

Design blueprint diagram

To describe the nature and the characteristics of the service interaction to verify, implement and maintain it. It includes: temporal order, timings, and line of visibility (denoting what the customer sees and back-office).

Storyboard / storytelling

Representation of use cases, through a series of drawings or textual description put together in a narrative sequence, which illustrates a sequence of events such as a customer journey.

Service prototyping

Involving the selection, assembly and integration of the various service components (atomic services).

For the current research work, the aim is to use this service design methodology and adapt it to a philosophy of co-design where new business services can be designed in a collaborative environment involving multiple stakeholders and the customer.

Although a number of methods and tools are available for some aspects of services design [START_REF] Wild | Review of Service Design Methods[END_REF], most of them are based on simple manual methods. Therefore the proposed environment supports the collaborative process of the different stakeholders in some steps of the adopted methodology.

Service Co-design Negotiation Support System. Being the service co-design negotiation support system (CoDeN), intended to provide a collaborative environment for the design of new business services where the various involved participants can reach agreements on what needs to be decided, for the developed system it is assumed that the needed service is already identified and the relevant stakeholders (participants in the negotiation process) are previously defined. The negotiation process is guided by defined templates that follow the described service design methodology for the design of touchpoints and blueprint diagram, also addressing the identification of the business service related stakeholders mapping.

Besides the important roles of customer and involved participants (co-creation team), also, to conduct the entire negotiation process, the role of co-creation team mediator is introduced (acting like the classical VO Planner). Therefore, to properly model the core processes involved in co-design, the main actors with the correspondent roles are identified in Table 2 and the correspondent dependencies between them are illustrated in Fig. 2 using the i* modelling framework. M(NT,KNT) the set of moves allowed to participate in the negotiation of a specific topic/template (where NT represents the negotiation topic, and KNT represents the content of NT).

The defined moves consider that, in some occasions in VO formation negotiations, for each negotiation topic only a subset of participants are involved and can even be replaced by others [START_REF] Oliveira | Electronic Negotiation Support Environment in Collaborative Networks[END_REF][START_REF] Oliveira | Negotiation Support for Co-design of Business Services[END_REF]. That is why the moves ( ), ( ) are considered. In the co-creation case (in the main focus of this paper), all participants are requested to participate in the design of all templates (diagrams). So the participants' interaction with the system reduces the M(NT,KNT) to the following:

( , ) = ( , ) , ( , ), ℎ ( )
being all other moves made internally by the system. While participants can make several of the mentioned moves in the course of a negotiation dialogue, they have to do it in a pre-determined way. They may even have to wait for the other participants' moves so that actions can be made accordingly. For example, an evident restriction is that a participant cannot accept to participate on a negotiation process without the Team Mediator requesting his participation in advance. Table 3 summarizes some of the pre-and post-conditions to some moves. Fig. 3 illustrates the relation of the described moves in reference to the Team Mediator's possible states. Implementation and Validation. For the described work, a software prototype has been developed in order to check the feasibility of the proposed concepts. The prototype system was implemented in JAVA, with the VAADIN framework, and allows the generation of general information on the co-creation consortium, as well as to upload supporting documentation. For the negotiation of the templates of diagrams to guide the new service design, functionalities are also available and cope with the described negotiation protocol. The main output is a generated .pdf document that includes a summary of all the information that is generated in the course of negotiation. Fig. 4 illustrates the involved concepts and prototype usability for a general scenario. domain is being done to perform a more accurate analysis of the achieved results. Through these means, some of the concepts and preliminary results have already been positively validated.

Conclusions and Further Work

In the work presented in this paper, the aim is to have a negotiation environment to support networks of SMEs in the form of co-creation teams to achieve agreements on the design of new business services. For this purpose, a negotiation support environment has been developed and briefly summarized, highlighting the main requirements and approach. Also, the adopted negotiation protocol to specify the adequate rules was also detailed. In this case, what is intended is not to have an artificial agent system acting on behalf of organizations, but to have the human actors interacting with the system and following the adopted protocol. Therefore, one of the challenges in the definition of the protocol is to ensure that it can easily be followed and accepted by all involved stakeholders.

Fig. 1 .

 1 Fig. 1. VO formation process.

Fig. 3 .

 3 Fig. 3. Team Mediator states and related negotiation moves.

Fig. 4 .

 4 Fig. 4. CoDeN usability.Being the present work part of a PhD work, the validation process is mainly through peer validation but also through the participation on the mentioned European research project GloNet. Also, close interaction with end-users in the solar energy

Table 3 .

 3 Pre-and post-conditions for the negotiation protocol.

	m1: request(N)	pre: no condition post: accept(N), refuse(N)
	m2: accept(N)	pre: request(N) post: other moves are consequence of certain triggers
	m3: refuse(N)	pre: request(N) post: no moves may occur from the participant that refuse(N)
		pre: request(N) followed by refuse(N); or refuse(NT) on the negotiation
	m4: withdraw(N)	of a specific topic
		post: no further move
	m5: propose(NT)	pre: accept(N) post: accept(NT), refuse(NT), counterpropose(NT,KNT)
	m6: accept(NT)	pre: propose(NT) post: other moves are consequence of certain triggers
	m7: refuse(NT)	pre: propose(NT) post: no moves may occur from the participant that refuse(NT)
	m8:	pre: propose(NT)
	counterpropose(NT,KNT)	post: maybe followed by propose(NT)
	m9: withdraw(NT)	pre: propose(NT) post: maybe followed by a withdraw(N)

Acknowledgments. This work has been supported by the Collaborative Networks and Distributed Industrial Systems Research Group of Uninova and partly by the GloNet project (FP7 programme) funded by the European Commission.

Table 2. Actors and roles in co-creation teams.

Actor Role

Co-creation Team The Co-creation Team represents all the involved actors within the collaborative space aimed for co-design of services. These actors are essentially the VO Partners and the Customer.

Co-creation team mediator

The Co-creation team mediator is the VO partner responsible to conduct the entire co-design process. He acts similarly to the VO Planner in generic VOs.

VO Partners

The VO Partner is part of the co-creation team, and, gives support for the service co-design and co-innovation according to its knowledge and skills.

Customer

The Customer is also part of the co-creation team, and together with the VO Partners plays an important role in the service co-design once his satisfaction must be attained. He maybe also responsible for providing the services requirements and for giving feedback during the collaboration processes. Negotiation Protocol. The process of reaching consensus among the various participants, besides being guided through the negotiation environment, has to follow a determined protocol in order to be effective. In this specific case, a logical language was followed [START_REF] Caminada | On the evaluation of argumentation formalisms[END_REF] to define the negotiation protocol that is used to specify when a determined decision can be made by an intervenient of the process. Therefore, the negotiation protocol is used to specify when a particular move can be made in the course of the negotiation dialogue [START_REF] Moschoyiannis | Verifiable protocol design for agent argumentation dialogues[END_REF], being move here understood as the statement and/or decision that a participant can make.

Although there are different protocols for negotiation, and different defined moves for different scenarios [START_REF] Wang | A hybrid multi-agent negotiation protocol supporting agent mobility in virtual enterprises[END_REF], the benefit from the used protocol is that it is generic and can be used when addressing different negotiation contexts. Therefore, the adopted protocol relies of the following moves:


Filipa Ferrada

Luis M Camarinha-Matos

An Emotional Support System for Collaborative Networks

Keywords: Emotions, Collective Emotions, Collaborative Networks, Collaboration Health

A particular challenge in the management of collaborative networks is the effective handling of the interactions among participants, especially in what concerns the management of "soft" issues that are not currently available in the execution processes of such networks. These issues can include inter-and intra-organizational abilities, problems in keeping team cohesion, leadership, among others. Moreover, one cannot forget that organizations are composed of people, and people have intrinsically associated emotions which are present in all interactions. In this sense, when not properly handled, some participant's emotions might put in jeopardy the quality of the collaboration. On the other hand the collective emotional state of the collaborative network can also affect each participant's emotions. As a contribution to keep the emotional equilibrium of the network, this paper presents the design of an emotional support system, including the identification and categorization of the most influencing positive and negative collective emotions and also the specification and prototyping of the sub-system services.

Introduction

Over the past decades there has been a great interest in the nature and role of emotions in community and work contexts, and a growing recognition of their centrality in facilitating or not connections between people [START_REF] Stanley | Varieties and functions of human emotion[END_REF]. In this line, the understanding of the role of emotions within networks of organizations is becoming a challenge due to its organizational, dynamic and "soft" nature. Furthermore, emotions might have a central role in the quality of communications and interaction among participants, in keeping network cohesion, in decision-making, in conflicts resolution, in leadership, among others. Having these considerations into account, it becomes interesting to understand to what extent having an emotional equilibrium in the network contributes to the health of the collaboration. In this context the main research question for this work is: What could be a suitable set of models, methods and tools to promote emotional health in collaborative networks, namely allowing the diagnosis of the networks' emotional state and assisting in conflicts resolution?

The development of effective supervision functionalities to monitor and manage the emotional climate/state -or the "collective virtual emotions" -of collaborative networks with the intention of maintaining the emotional equilibrium of the community, forecasting and attempting to heal potential conflicts among participants and external communities are important elements for the success of the network [START_REF] Ferrada | Collective Emotions Supervision in the Product-Servicing Networks[END_REF]. In fact, several studies reveal that emotions are very often the cause for misunderstandings and conflicts which, in some cases might lead to the failure of collaborative networks [START_REF] Ferrada | Emotions in Collaborative Networks: A Monitoring System[END_REF]. However, very little progress has been made in this direction. A particularly challenging issue is the acquisition, via non-intrusive methods, of multi-modal emotional input for achieving awareness of the participants' as well as the collective emotional state.

As a contribution to help keeping the emotional equilibrium of the network, this paper presents an emotional support system for collaborative networks developed on top of the GloNet platform. It includes the identification and categorization of the most influencing positive and negative collective emotions and also the specification and prototyping of the sub-system services. The remainder of this paper is organized as follows: Section 2 identifies the relationship of this work to cloud-based engineering systems; Section 3 gives a brief description of the related literature, namely in what concerns emotions in organizations and group-based emotions; Section 4 presents the emotions support system, its framework and prototype; and finally Section 5 concludes.

Benefits from Cloud-based Engineering Systems

Several research projects and business initiatives show trend to develop collaboration platforms on the cloud. The consolidation of this approach is likely to facilitate an increase of collaboration among small and medium enterprises (SMEs) as, in this case, they do not need to acquire and maintain complex computational infrastructures. The work presented in this paper is developed in such context in the scope of the GloNet project: networks of SMEs involved in complex service-enhanced products [START_REF] Camarinha-Matos | Cloudbased Collaborative Business Services Provision[END_REF] are supported by a cloud-based platform. This platform not only facilitates the collaboration processes among participants but also allows the emotional support system to more easily access the information that is needed to assess and manage the emotional equilibrium within the collaborative networks.

Besides the benefits of freeing enterprises from the burden of keeping their own infrastructures, the scalability property of cloud-computing allows for greater agility, which is quite relevant in our use case on supporting the full life cycle of solar plants. Each solar plant (a complex product) and the associated business services to be provided along its life cycle are highly customized (one of a kind) and might involve the need to store increasing amount of data. On the other hand, security concerns, namely in terms of access to data and even direct access to the physical plant, are vital here. The solutions offered by cloud providers are more reliable than what could be guaranteed by proprietary development of a network of heterogeneous SMEs. On the other hand, even within a network of collaborating partners there are several levels of access to information that need to be properly defined according to the role played by each participant. The GloNet platform provides the base mechanisms for specification of those access rights [START_REF] Surajbali | A Cloud-Based Approach for Collaborative Networks Supporting Serviced-enhanced Products[END_REF] and these need to be taken into account by the emotional support system in delivering different access to members and administrator.

3 Related Literature

Emotions in Organizations

Organizations have been studied by several scientific areas as rationally designed and operated structures. Nevertheless, issues like bringing fruitful collective action, quality of interaction and relations between parties and incentives to motivate organization's participants to follow common goals were, for a while, treated as irrelevant or insignificant. Aspects of group dynamics [START_REF] Forsyth | Group dynamics[END_REF] and factors of sociality were often disregarded such as the impact of complex social processes on organization's participants. However, they surely contribute for the ability that an organization has to integrate, create and reconfigure internal and external resources according to the changing environment. These "additional factors", to a large extent, form the "social glue" that keeps together the participants of the collective action [START_REF] Luksha | Emotions in Organization: More than mere fluctuations[END_REF]. Emotions started to be recognized as an important element of cognitive processes [START_REF] Lazarus | Progress on a cognitive-motivational-relational theory of emotion[END_REF], a necessary component of individual activity motivation and have high importance in interpersonal communications. In other words, the influence of emotional factors provides significant impact for positive organizational dynamics. On the other hand, emotional factors might as well input some negative impacts in an organization [START_REF] Ashkanasy | Emotions in the workplace: research, theory, and practice[END_REF][START_REF] Brief | Organizational Behaviour: Affect in the Workplace[END_REF]. Namely, they can disrupt normal procedural flows, break working relationships, and disrupt reasoned judgment and decision-making.

Collective and Group-Based Emotions

Emotional Contagion. Emotional contagion is "a process in which a person or group influences the emotions or behavior of another person or group through the conscious or unconscious induction of emotion states and behavioral attitudes" [START_REF] Schoenewolf | Turning points in analytic therapy: The Classic cases[END_REF]. Emotions are "caught" by group members when they are exposed to the emotional expressions of other group members. Hatfield et al. [START_REF] Hatfield | Emotional contagion[END_REF] advanced that the degree to which emotional contagion occurs is mediated by attentional processes, with greater emotional contagion occurring when more attention is allocated. Zurcher [START_REF] Zurcher | The staging of emotion: A dramaturgical analysis[END_REF] argues that displays of positive emotion in group situations constitute an essential ingredient necessary for the establishment of group cohesion. Furthermore, Lawler [START_REF] Lawler | Affective attachment to nested groups: A choice-process theory[END_REF] claims that emotion is the essential social process in group formation and maintenance. This is because positive emotions strengthen feelings of control. As such, positive emotion is a necessary precursor of group cohesiveness. In the context of organizational work groups, George [START_REF] George | Personality, affect, and behavior in groups[END_REF] has also shown that positive affection is a key ingredient for group effectiveness and satisfaction. Barsade [16] found that positive emotional contagion amongst group members affects individual-level attitudes and group processes. Group members who experienced positive emotional contagion demonstrated improved cooperation, decreased conflict, and increased perceived task.

Collective Emotions. Collective emotions have been defined in a relatively general way as emotions that are shared by large numbers of individuals in a certain society [START_REF] Stephan | An integrated threat theory of prejudice[END_REF], while group-based emotions are defined as emotions that are felt by individuals as a result of their membership in a certain group or society [START_REF] Smith | Social identity and social emotions: Toward new conceptualization of prejudice[END_REF]. According to Bar-Tal [START_REF] Bar-Tal | Sociopsychological Foundations of Intractable Conflicts[END_REF], both concepts suggest that individuals may experience emotions, not necessarily in response to their personal life events, but also in reaction to collective or societal experiences in which only a part of the group members have taken part. But while the former concept suggests that group members may share the same emotions for a number of different reasons, the latter refers only to emotions that individuals experience as a result of identifying themselves with their fellow group members. A number of scholars have also pointed to the important behavioral implications of collective or group-based emotions when there are conflicts between groups and societies. Moreover, Bar-Tal [START_REF] Bar-Tal | Sociopsychological Foundations of Intractable Conflicts[END_REF] argues that the emotional element of context has great potential to influence emotional reactions and subsequent behavior. Furthermore, he proposed that, in contrast to individual emotions which are sometimes related to a dispositional system or physiological mechanism, collective or group-based emotions are solely formed as a consequence of experiences in a particular societal context. Society members experience collective emotions not only as a result of directly experiencing events that evoke particular emotion but also by identifications with the society as a collective.

Emotional Atmosphere, Emotional Culture and Emotional Climate. In the initial work of de Rivera [START_REF] De Rivera | Emotional climate: Social structure and emotional dynamics[END_REF], he suggested that it is important to differentiate emotional atmosphere from emotional culture and emotional climate: emotional atmosphere or collective mood refers to the collective behavior that a group or society may manifest when it is focused on a common event, rather than to the emotional relationships between members of the society. Such an atmosphere appears when those who identify with a group celebrate a collective success, lament a tragedy, or suffer a common threat. Emotional culture refers to the emotional relations that are socialized in a particular culture, while emotional climate is "an objective group phenomenon that can be palpably sensed -as when one enters a party or a city and feels an atmosphere of gaiety or depression, openness or fear". This basically refers to the collective emotions experienced as a result of a society's response to its sociopolitical conditions. Thus, in times of political repression, people are afraid of expressing their ideas in public; in times of ethnic tension, there is hate and/or fear toward other groups, and so on. De Rivera gives the example of Chile's Pinochet regime that was under a climate of fear and now it has changed to a climate of hope. Emotional climate is more stable than emotional atmosphere and may be a useful construct for analyzing social dynamics in contexts of political violence [START_REF] Conejero | The Impact of the Madrid Bombing on Personal Emotions, Emotional Atmosphere and Emotional Climate[END_REF].

As mentioned above, it might be considered that the emotional equilibrium of a collaborative network contributes to supporting healthy collaboration. Individual participants experience emotions not only as a result of directly experiencing events (that involve/evoke their own particular emotions) but also through collaborative interactions and by identifying themselves with the network as a whole. As a consequence, the emotional health of the collaborative network might depend of the intricate interactions between the various participants developing, in this way, a collective emotion which is influenced by each participant's dominant emotions and the network's global performance evaluation. From an intuitive point of view, it seems plausible that the more positive the collective emotion is, the healthier the collaborative network becomes.

Which Emotions

Human emotions are known and although not universally categorized and defined, some authors invested considerable research efforts on establishing theories for categorizing basic and inferred emotions, e.g. [START_REF] Averill | A constructivist view of emotion[END_REF][START_REF] Scherer | What are emotions? And how can they be measured[END_REF]. However, when it comes to the context of collaborative networks it becomes understandable that the emotions that are "felt" are not at the level of an individual but rather of a "collectivity". In this way, and under a simplified view of what should be the (collective) emotions that need to be further analyzed, the following examples can be considered:

Excitement Excitement is a positive emotion, "experienced" when the network as a whole feels excited, that might be triggered when the short-and/or long-term network objectives and partner's expectations and wishes are fully achieved. As a positive emotion, it maintains the network health calibrated ensuring, in this way, future successful interactions among network partners. Contentment Contentment, like excitement, is a positive emotion, "experienced" when the network as a whole feels content, which might be triggered when the shortand/or long-term network objectives and partner's expectations and wishes were partially achieved. As a positive emotion, it indicates a successful achievement from the majority of the network participants and causes a slight alert to the network health to be regulated. Frustration Frustration is a negative emotion, "experienced" when the network as a whole feels frustrated, that might be triggered when a partner's own actions, and/or others' actions in pursuit of the short-and/or long-term network objectives are mostly not achieved. As a negative emotion, it inhibits the achievement from the majority of network participants and down regulates the network health, increasing the chance of network "failure". Depression Depression, like frustration, is a negative emotion, "experienced" when the network as a whole feels depressed, hopeless, uninterested and unable to focus on normal activities. Depression might be triggered when a partner's own actions and/or others' actions in pursuit of the short-and/or long-term network objectives are a complete failure. As a negative emotion, it jeopardizes the network health, compromising the interactions among partners and potentially promoting conflicts.

Emotions Categorization

For both theoretical and practical reasons, some researchers define emotions according to one or more dimensions [START_REF] Russell | On the bipolarity of positive and negative affect[END_REF]. Dimensional descriptions capture essential properties of emotional states, such as arousal (active/passive) and valence (negative/positive). Emotion dimensions can be used to describe general emotional tendencies, including low-intensity emotions. In addition to these two, there are a number of other possible dimensions, such as power, control, or approach/avoidance, which add some refinement. Dimensional representations are attractive mainly because they provide a way of describing emotional states, which are more tractable than using words. A further attraction is the fact that dimensional descriptions can be translated into and out of verbal descriptions.

In the context of collaborative networks, we suggest that emotions can be defined according to three dimensions: Valence (positive/negative); Activation or arousal (active/passive); and Intensity (weak/moderate/strong).

Emotional Evidences/Information

In order to properly build an Emotional Support System, it is necessary to find (nonintrusive) mechanisms to measure/infer the emotion that the collaborative network is "feeling". Therefore, emotional evidences (or emotional information) have to be defined and their sources identified. As collaborative networks are composed of organizations and people, each one of them can bring its own emotional tendencies to the network, helping in "producing" the network collective emotion. In this way two groups of emotional evidences/information are considered: the first concerning the information that will be useful for "measuring" each member's emotional state and the second for "measuring" the collective emotion present in the collaborative network. The following tables illustrate the information envisaged, at this stage, for each group as well as were it can be collected. Due to the experimental nature of this work, this information might need to be revised later. Algorithm using all the above information

Emotional Support Sub-Systems

Having the above in mind, the Emotional Support System is divided into two subsystems: the Member's Emotional State Support and the Collective Emotional State Support as illustrated in Fig. 1.

Fig. 1 -Global view of the Emotional Support System

Member's Emotional State Support Sub-System. The Member's Emotional State support sub-system aims to support gathering all the necessary information in order to estimate the current and past emotional state of a particular member. Fig. 2 shows an adapted i* Rationale Strategic model where the involved actors as well as their dependency objectives are illustrated. Within the boundaries of the Member Emotional State Support sub-system the respective associated tasks/functionality are presented. The main functionalities of this sub-system are included in Table 3. This functionality serves to show the list of the past emotional states of an identified member.

View Member Emotional Evidences

Functionality that permits the visualization of the identified member evidences that were used to estimate the emotional state. This system is currently being evaluated and will be further validated in the context of the GloNet project, which addresses collaborative networks in support of complex service-enhanced products such as solar plants and intelligent buildings.

Conclusions and Future Work

Collective emotions are becoming an important element in the management of organizations. In the collaborative networks context its effect is also of extreme significance due to the virtual, dynamic and "soft" nature of the interactions among organization participants. Furthermore, it is also known that emotions might influence positively or negatively the network collaboration dynamics. Therefore, with the aim of maintaining the emotional equilibrium of the network, this paper presents the design of an emotional support system, including the identification and categorization of the most influencing positive and negative collective emotions and also the specification and prototyping of the sub-system services. Future work will rely on the progress of the emotional model that is used to estimate emotion according to the multi-modal non-intrusive evidences that were considered for the members and also for the network.

Fig. 4 -

 4 Fig. 4 -Developed prototype interface on the Administrators' side

Table 1 .

 1 Member´s Emotional Information

		Emotional Information	Sources
	Individual	Needs & Expectations	Survey / Questionnaire
	Part	Performance Data	Member Profile Performance
			Evaluation
		Past Emotional States	List of past Estimated
			Emotional State
	Shared Part Member Satisfaction	Survey / Questionnaire
		# of belonging Groups	Member's Groups List
		# of belonging VO's	Member's VOs List
		# of Sharing Resources	Member's Shared Resources

Table 2 .

 2 Collaborative Network's Emotional Information

		Emotional Information	Sources
	Network	Performance Data	Network Profile Performance
	Part		Evaluation
		Past Collective Emotional States	List of past Estimated Collective
			Emotional State
		List of Members' Emotional	Members' emotional Information
		Information
		Total Number of VOs	Network VOs List
		Communication Data	Social Network Analysis Tools
		Communication Flows (overall
		direction of interactions)
		Communication Intensity
		(overall frequency of
		interactions)
	Inferred	Estimated Actual Collective
	Part	Emotional State
		Name of emotion [EMOTION]
		Valence [POSITIVE,
		NEGATIVE]
		Activation [ACTIVE, PASSIVE]
		Intensity of emotion [WEAK,
		MODERATE, STRONG]

  Adapted i* Rationale Strategic Model for the Member Emotional State Support

			Member
			Emotional
			State Support
	Get Member Emotional State	Estimate Emotional State
	CN Administrator	Collect Member Individual Info	Collect Member Shared Info
	List Past Member
	Emotional States
	Fig. 2 -

Table 3 .

 3 Main Services of the Member's Emotional State support sub-system of Emotional Support

	Service Name		Service Description
	Estimate		Member	Functionality used to infer the emotional state of an
	Emotional State		identified member taking into account the current available
				emotional information.
	View	Actual	Member	This functionality serves to show the last estimated
	Emotional States		emotional state of an identified member.
	View	Past	Member
	Emotional States

Acknowledgments. This work has been supported by the Collaborative Networks and Distributed Industrial Systems (CoDIS) Research Group of Uninova and partly by the GloNet project funded by the European Commission.

Collective Emotional State Support Sub-System. The Collective Emotional State support sub-system aims to support gathering all the necessary information in order to estimate the current and past emotional state of the network as a whole.

Fig. 3 shows an adapted i* Rationale Strategic model where the involved actors as well as their dependency objectives are illustrated. Within the boundaries of the Collective Emotional State Support sub-system the respective associated tasks/functionality are presented. The main functionalities of this sub-system are included in Table 4.

View Actual Collective Emotional States

This functionality serves to show the last estimated emotional state of the network.

View Past Collective Emotional States

This functionality serves to show the list of the past collective emotional states of the collaborative network.

View Members Emotional States

This functionality serves to show the list of the current emotional states of the CN members.

View Collective Emotional Evidences

Functionality that permits the visualization of the evidences that were used to estimate the collective emotional state.

View Recommendations

Functionality that according to the collective emotion suggests recommendations to the network administrator.

Fig. 4 illustrates the interface of the implemented prototype on the Administrators' side.