Yassine Talas
email: yassine.talas@grenoble-inp.fr

Le Dain

IT contribution to collaborative NPD

Keywords: Information Technologies, New Product Development, Buyer-supplier collaboration, Multiple linear regression

Buying firms collaborate with suppliers in New Product Development (NPD) to better leverage their resources and knowledge. Prior studies' results on IT contribution to NPD project performance are mixed, and none investigated this effect for collaborative buyer-supplier NPD projects. This study adopts a contextual functional approach to explore how the effective use of IT functionalities for the three classical IT-enabled NPD activities, namely Project and Process Management (PRM), Knowledge Management (KM), and Cooperative Work (CW), impacts NPD project success in terms of project performance but also regarding the contextual factor of collaboration quality. A series of multiple linear regressions is performed to test these effects using data from a survey with 90 firms involved in collaborative NPD projects with suppliers. As results, the effective use of all IT functionalities directly improves collaboration quality, while only KM directly affects project performance. PRM and CW contribute to this performance only indirectly through collaboration quality. Hence, this study emphasizes the importance of considering a functional approach when studying the impact of IT effective use on NPD project success, and of taking into account the project context. Additionally, it incites practitioners to build a conducive collaboration climate to benefit from using IT functionalities.

Introduction

New Product Development (NPD) projects are characterized by parallel tasks and the simultaneous contribution of diversified expertise and knowledge [START_REF] Juan | A process-oriented multi-agent system development approach to support the cooperation-activities of concurrent new product development[END_REF]. In such projects, the effective use of IT (Information Technologies) enables extending the information and knowledge base of NPD teams [START_REF] Ettlie | Technology-based new product development partnerships[END_REF][START_REF] Kroh | Use and Efficacy of Information Technology in Innovation Processes: The Specific Role of Servitization[END_REF], supports the flow of relevant knowledge at the right time, and promotes the automation and monitoring of tasks [START_REF] Kawakami | Information technology tools in new product development: The impact of complementary resources[END_REF]. Regarding the NPD project performance, numerous theoretical studies underlined that the effective use of IT could result into better commercial performance, reduced time to market and lower development costs [START_REF] Menon | Antecedents and outcomes of new product development speed. An interdisciplinary conceptual framework[END_REF][START_REF] Nambisan | Information systems as a reference discipline for new product development[END_REF][START_REF] Ozer | Information Technology and New Product Development[END_REF][START_REF] Sethi | Web-based product development systems integration and new product outcomes: A conceptual framework[END_REF]. Nevertheless, the few empirical studies that investigated the impact of IT effective use on NPD project performance report mixed results. While most of this research suggest a positive impact, other scholars were not able to demonstrate this effect or even highlighted a contrary influence (e.g. [START_REF] Heim | Antecedents and consequences of new product development practices and software tools: An exploratory study[END_REF][START_REF] Kawakami | Information technology tools in new product development: The impact of complementary resources[END_REF][START_REF] Mauerhoefer | The Impact of Information Technology on New Product Development Performance[END_REF]. According to [START_REF] Barczak | Antecedents and consequences of information Technology Usage in NPD: A comparison of dutch and U.S. companies[END_REF], these mixed results on IT's contribution to NPD project performance justify their underutilization in this process despite their proliferation. Indeed, NPD project actors are not able to value the return on investment on IT nor to appreciate their benefits for project performance, which withholds them from adopting these technologies [START_REF] Markham | Product development and management association's 2012 comparative performance assessment study[END_REF].

A main reason that could explain the mixed results on the impact of IT effective use on NPD project performance is that the context of their utilization is not taken into account [START_REF] Barczak | Antecedents and consequences of information Technology Usage in NPD: A comparison of dutch and U.S. companies[END_REF][START_REF] Montoya | Can you hear me now? Communication in virtual product development teams[END_REF]. As underlined by [START_REF] Peng | Collaborative product development: The effect of project complexity on the use of information technology tools and new product development practices[END_REF], it is important to consider the peculiarities of the NPD context in order to grasp the specific contribution of IT use to project performance. Most studies that investigated this impact addressed generic or non-precise NPD contexts (e.g. [START_REF] Kawakami | Information technology tools in new product development: The impact of complementary resources[END_REF][START_REF] Marion | Do social media tools impact the development phase? An exploratory study[END_REF][START_REF] Reid | The impact of the frequency of usage of IT artifacts on predevelopment performance in the NPD process[END_REF]. One specific project configuration which has been rarely explored [START_REF] Terwiesch | Exchanging Preliminary Information in Concurrent Engineering: Alternative Coordination Strategies[END_REF] and for which no incisive results have been reached is collaborative buyer-supplier NPD projects [START_REF] Bensaou | Interorganizational cooperation: The role of information technology an empirical comparison of U.S. and Japanese Supplier Relationships[END_REF][START_REF] Vaccaro | Knowledge Management Tools, Inter-Organizational Relationships, Innovation and Firm Performance[END_REF]. Indeed, firms gain competitive advantages by collaborating with suppliers in NPD because they represent a source of innovation and knowledge [START_REF] Koufteros | The Effects of Strategic Supplier Selection on Buyer Competitive Performance in Matched Domains: Does Supplier Integration Mediate the Relationships?[END_REF][START_REF] Luzzini | From sustainability commitment to performance: The role of intra-and inter-firm collaborative capabilities in the upstream supply chain[END_REF]. However, they may face collaboration challenges with them as these alliances require specific abilities for coordination and interorganizational knowledge and resources management [START_REF] Chang | The effects of buyer-supplier's collaboration on knowledge and product innovation[END_REF][START_REF] Lau | Supplier and customer involvement on new product performance[END_REF][START_REF] Loebbecke | Managing inter-organizational knowledge sharing[END_REF]. IT tools use can support such activities and hence reduce challenges of collaborative development with suppliers [START_REF] Kroh | Use and Efficacy of Information Technology in Innovation Processes: The Specific Role of Servitization[END_REF]. Another explanation regarding the mixed findings could be that the extant literature did not investigate how the effective use of different IT functionalities contributes to NPD project performance. In fact, this IT effective use in NPD is a three-dimension construct capturing how NPD units leverage IT functionalities for Project and Process Management (PRM), for Knowledge Management (KM) and for Cooperative Work (CW) [START_REF] Pavlou | From IT leveraging competence to competitive advantage in turbulent environments: The case of new product development[END_REF]. Leveraging capabilities have differentiated impacts regarding NPD project performance [START_REF] Parente | The effect of supply chain integration, modular production, and cultural distance on new product development: A dynamic capabilities approach[END_REF].

Hence, this study investigates the impact of IT effective use on NPD project performance, considering the particular effect of the collaborative buyer-supplier context and following a functional approach that distinguishes the contributions of the three IT functionalities. To take into account the peculiarities of this collaborative context, we analyse how IT effective use indirectly influences NPD project performance through the factor of collaboration quality. Also, since this factor represents a critical success indicator in the case of NPD projects involving suppliers additional to NPD project performance [START_REF] Hoegl | Teamwork Quality and the Success of Innovative Projects: A Theoretical Concept and Empirical Evidence[END_REF][START_REF] Marion | Do social media tools impact the development phase? An exploratory study[END_REF], we explore how it is directly affected by IT effective use. Accordingly, we raise the following research question: « How does the effective use of IT functionalities (for PRM, KM and CW) contribute to the success of collaborative buyer-supplier NPD projects? ». This paper is structured as follows. Section 2 describes our theoretical foundations, while section 3 introduces the conceptual model that gathers the hypothesized impacts of IT effective use on collaborative NPD project success. Section 4 is devoted to the research methodology, a quantitative approach to analyze 90 responses collected through a survey with buyer project team members involved in collaborative NPD projects with suppliers. The results are depicted in section 5. Finally, this study is concluded by the discussion of its main theoretical and managerial implications, as well as the suggestion of its future research avenues.

Theoretical background

Collaborative buyer-supplier NPD projects

Firms are increasingly collaborating with their suppliers in NPD in order to better leverage the supplier's resources, expertise and knowledge [START_REF] Bodas Freitas | Formalized Problem-Solving Practices and the Effects of Collaboration with Suppliers on a Firm's Product Innovation Performance[END_REF][START_REF] Cao | Supply chain collaboration: Impact on collaborative advantage and firm performance[END_REF]. Indeed, collaboration with suppliers leads to an improved NPD project performance [START_REF] Mishra | In union lies strength: Collaborative competence in new product development and its performance effects[END_REF] by lowering development costs, enhancing product quality and reducing time to market [START_REF] Wasti | Collaborating with suppliers in product development: a US and Japan comparative study[END_REF]. Achieving the targeted NPD project performance, combining cost, quality and time performances [START_REF] Naveh | The effect of integrated product development on efficiency and innovation[END_REF], is a fundamental success criterion for collaborative buyer-supplier NPD projects [START_REF] Mishra | In union lies strength: Collaborative competence in new product development and its performance effects[END_REF]. Cost performance expresses the adherence to the total objective cost to develop and manufacture the new product, while time performance corresponds to the achievement of the project's targets in terms of development duration and time to market [START_REF] Rauniar | Organizational structuring and project team structuring in integrated product development project[END_REF]. Quality performance is the compliance of the technical performance and the product quality to the contractual customer expectations [START_REF] Tatikonda | Successful execution of product development projects: Balancing firmness and flexibility in the innovation process[END_REF]. Additional to NPD project performance, several authors emphasize the necessity to also consider the collaboration quality [START_REF] Bstieler | Trust formation in collaborative new product development[END_REF][START_REF] Jin | Coordinating global inter-firm product development[END_REF] in order to evaluate the success of collaborative buyer-supplier NPD projects. Indeed, since these projects involve several actors carrying out a multitude of interdependent tasks, their success holds to a high collaboration quality [START_REF] Marion | Do social media tools impact the development phase? An exploratory study[END_REF]. Such quality is perceived when the project actors openly communicate information, successfully coordinate their tasks, support each other and fully assume their responsibilities to achieve the project goals [START_REF] Hoegl | Interteam Coordination, Project Commitment, and Teamwork in Multiteam R&D Projects: A Longitudinal Study[END_REF][START_REF] Yan | Buyer-supplier collaboration quality in new product development projects[END_REF].

IT functionalities supporting NPD

Based on the resource based view, firms build a competitive advantage from IT-related resources by combining them to form an IT capability that is valuable, rare, nonimitable, and nonsubstitutable [START_REF] Pavlou | From IT leveraging competence to competitive advantage in turbulent environments: The case of new product development[END_REF]. Accordingly, Bharadwaj et al. (2002, p. 4) define IT capability as the "firm's ability to acquire, deploy, and leverage its IT resources to shape and support its business strategies and value chain activities". In an NPD context, [START_REF] Pavlou | From IT leveraging competence to competitive advantage in turbulent environments: The case of new product development[END_REF] argue that IT capability should be examined at the NPD process level by focusing on the leveraging capabilities of NPD work units. Indeed, "the impact of IT should be assessed where the first order effects are expected to be realized" (Ray et al. 2005, p. 626), which relates to the process level more than to the firm level in the context of NPD projects. Also, the leveraging of IT capability is more likely to help NPD work units differentiate themselves and build a competitive advantage in NPD [START_REF] Pavlou | From IT leveraging competence to competitive advantage in turbulent environments: The case of new product development[END_REF]. IT capability is a complex multidimensional construct, and prior research proposed several IT-related resources that combine to devise an IT capability (e.g. [START_REF] Feeny | Core IS capabilities for exploiting information technology[END_REF][START_REF] Tippins | IT competency and firm performance: is organizational learning a missing link?[END_REF]. In an NPD context, three key dimensions form IT capability and convey the leveraging competence of NPD units [START_REF] Pavlou | From IT leveraging competence to competitive advantage in turbulent environments: The case of new product development[END_REF]: Effective use of IT functionalities for Project and Process Management (PRM), for Knowledge Management (KM) and for Cooperative Work (CW):

 Project and Process Management (PRM) IT functionalities help NPD teams better synchronize and coordinate their activities [START_REF] Pavlou | From IT leveraging competence to competitive advantage in turbulent environments: The case of new product development[END_REF]. They support the project planning through its different phases [START_REF] Ahlemann | Towards a conceptual reference model for project management information systems[END_REF] and enable the project actors to respect its milestones and deadlines [START_REF] Raymond | Project management information systems: An empirical study of their impact on project managers and project success[END_REF]. These systems help the teams organize the NPD through features of tasks' sequencing [START_REF] Pavlou | From IT leveraging competence to competitive advantage in turbulent environments: The case of new product development[END_REF], project steering [START_REF] Peng | Collaborative product development: The effect of project complexity on the use of information technology tools and new product development practices[END_REF] and management of deliverables (PMI, 2017). To ensure this project steering, these PRM functionalities provide the project actors with relevant information (e.g. resources' availability) in real-time or near real-time [START_REF] Braglia | An integrated approach to implement Project Management Information Systems within the Extended Enterprise[END_REF]. In addition, they facilitate monitoring the NPD project performance and progress against its objectives [START_REF] Cooke-Davies | Project management systems: Moving project management from an operational to a strategic discipline[END_REF]. Indeed, PRM IT functionalities enable to better deploy the product development process through the modelling and execution of its different phases [START_REF] Barczak | Antecedents and consequences of information Technology Usage in NPD: A comparison of dutch and U.S. companies[END_REF].

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 Knowledge management (KM) IT functionalities cover three main features [START_REF] Pavlou | From IT leveraging competence to competitive advantage in turbulent environments: The case of new product development[END_REF]. The authors first distinguish the codification and sharing of information and knowledge [START_REF] Barczak | Antecedents and consequences of information Technology Usage in NPD: A comparison of dutch and U.S. companies[END_REF][START_REF] Sambamurthy | Shaping Agility Through Digital Options: Reconceptualizing the Role of Information Technology in Contemporary Firms[END_REF] throughout the NPD project [START_REF] García-Álvarez | Analysis of the effects of ICTs in knowledge management and innovation: The case of Zara Group[END_REF]. On the one hand, codification includes the storage of knowledge to ensure its visibility and availability [START_REF] Wang | IT support in manufacturing firms for a knowledge management dynamic capability link to performance[END_REF], its search and reuse [START_REF] Shehata | Leveraging organizational performance via knowledge management systems platforms in emerging economies[END_REF] and the management of its evolution [START_REF] Ramesh | Supporting collaborative process knowledge management in new product development teams[END_REF]. On the other hand, sharing features allow teams to exchange project knowledge and information [START_REF] Choi | The impact of information technology and transactive memory systems on knowledge sharing, application, and team performance: a field study[END_REF]. Secondly, KM functionalities support the creation of knowledge repositories [START_REF] García-Álvarez | Analysis of the effects of ICTs in knowledge management and innovation: The case of Zara Group[END_REF]. These directories allow the localization and mapping of knowledge, expertise and best practices [START_REF] Bowman | Building Knowledge Management Systems[END_REF]. The third and last feature consists of knowledge networks (e.g. discussion forums) that connect the project actors and allow them to benefit from each other's knowledge [START_REF] Apostolou | Managing Kowledge at Multiple Organizational Levels Using Faceted Ontologies[END_REF].

 Cooperative Work (CW) IT functionalities support the interactions of project actors across time and space [START_REF] Thomas | Supplier integration in new product development: Computer mediated communication, knowledge exchange and buyer performance[END_REF] which enhances their collective spirit [START_REF] Montoya | Can you hear me now? Communication in virtual product development teams[END_REF]. They enable distant collaborative work [START_REF] Banker | Understanding the impact of collaboration software on product design and development[END_REF] and facilitate face-to-face interactions [START_REF] Addas | IT capabilities and NPD performance: examining the mediating role of team knowledge processes[END_REF]. According to [START_REF] Pavlou | From IT leveraging competence to competitive advantage in turbulent environments: The case of new product development[END_REF], CW functionalities cover three subcategories namely transmission, presentation and convergence. First, transmission reflects the exchange of raw information between the project actors, who will then interpret and use it according to their own objectives [START_REF] Dennis | Media, Tasks, and Communication Processes: A Theory of Media Synchronicity[END_REF]. In an NPD context, IT for transmission allow the visualization and joint description of product structures [START_REF] Zhang | A review of Internet-based product information sharing and visualization[END_REF]. Then, presentation functionalities make it possible to generate and convert the tacit ideas and knowledge of the project actors into representations and collective models [START_REF] Pavlou | The "Third Hand": IT-Enabled Competitive Advantage in Turbulence Through Improvisational Capabilities[END_REF]). An illustration would be the use of CAD tools (computer-aided design) for common and simultaneous modelling [START_REF] Li | A proxy approach to integrate heterogeneous CAD resources for distributed collaborative design[END_REF]. In addition, these features enable combining and integrating information and knowledge [START_REF] Pavlou | From IT leveraging competence to competitive advantage in turbulent environments: The case of new product development[END_REF], for instance tools for ideas' collection and analysis to support innovation [START_REF] Lopez Flores | Open computer aided innovation to promote innovation in process engineering[END_REF]. Finally, convergence functionalities help develop a shared meaning among team members with different skills and cultures [START_REF] Wheeler | Groupware Comes to the Internet : Charting a New World[END_REF]. Unlike transmission, convergence features provide access to the individuals' opinions and ideas and thus to information already processed by the project actors and inclined to their own interpretations [START_REF] Dennis | Media, Tasks, and Communication Processes: A Theory of Media Synchronicity[END_REF].

Hypotheses' development

As explained in the introduction, this study investigates the impact of IT effective use for the main NPDrelated activities on the success of collaborative buyer-supplier NPD projects. The hypotheses underlying these impacts are depicted in our conceptual model (Figure 1) and detailed hereafter.

Collaboration success IT effective use

Direct impacts of IT effective use on quality of buyer-supplier collaboration in NPD projects

Based on the social exchange theory, [START_REF] Han | Analyzing the impact of a firm's capability on outsourcing success: A process perspective[END_REF] showed that IT capability positively influences the buyer-supplier collaboration quality in terms of communication, participation and information sharing. Other scholars demonstrated such impacts in the particular context of NPD projects. For

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instance, the survey conducted by Song and Song (2010) with NPD project leaders and IT managers highlighted that these technologies (availability to project actors, the use of advanced technology, etc.) contribute to the successful integration of R&D and marketing actors. Also, through an international study with NPD actors representing the customers of an IT editor, [START_REF] Marion | Do social media tools impact the development phase? An exploratory study[END_REF] showed that the usage frequency of some of these tools was positively associated with the intensity of collaboration, including cross-functional collaboration and collaboration with customers and suppliers. [START_REF] Reid | The impact of the frequency of usage of IT artifacts on predevelopment performance in the NPD process[END_REF] reached a similar result from a survey with NPD project actors operating in Australian companies. The IT considered in these studies were traditional tools (i.e. e-mails, shared databases, project management tools), novel tools (i.e. wiki, clouds, innovation platforms) as well as collaborative tools (e.g. corporate social network, videoconferencing, collaborative CAD) [START_REF] Reid | The impact of the frequency of usage of IT artifacts on predevelopment performance in the NPD process[END_REF].

Other studies underlined the positive influence of using specific IT functionalities on collaboration quality in NPD. For instance, the study of [START_REF] Banker | Understanding the impact of collaboration software on product design and development[END_REF] with managers and executives of companies strongly focusing on NPD showed that KM systems supporting documentary exchange and structuring had a significant positive impact on the collaboration extent between the internal NPD project teams. Also, using data from an international study on manufacturing performance conducted in nine countries and three industries, [START_REF] Peng | Collaborative product development: The effect of project complexity on the use of information technology tools and new product development practices[END_REF] proved that PRM features, communication tools (e.g. e-mail, instant messaging, videoconferencing) and specialized CW systems (e.g. CAD and collaborative simulation) could improve cross-functional collaboration as well as collaboration with customers and suppliers in NPD. Based on these prior studies that emphasize the contribution of the three IT functionalities to buyer-supplier collaboration quality in NPD, we hypothesize that:  H1: The effective use of IT for PRM has a positive impact on the quality of buyer-supplier collaboration in NPD projects.  H2: The effective use of IT for KM has a positive impact on the quality of buyer-supplier collaboration in NPD projects.  H3: The effective use of IT for CW has a positive impact on the quality of buyer-supplier collaboration in NPD projects.

Direct impacts of IT effective on performance of collaborative buyersupplier NPD projects

Innovation activities such as NPD are fostered by the effective use of IT tools supporting information flows within and oustide the firm [START_REF] Kroh | Use and Efficacy of Information Technology in Innovation Processes: The Specific Role of Servitization[END_REF]. Indeed, the information system effectiveness theory suggests that the effective use of IT resources contributes to market, process and economic performance [START_REF] Grover | Information systems effectiveness: The construct space and patters of application[END_REF]. In an NPD context, several conceptual and empirical studies proposed that IT capability positively affects NPD performance. For instance, by studying international projects of a computer manufacturer, [START_REF] Boutellier | Management of dispersed product development teams: The role of information technologies[END_REF] reported that the use of IT was "vital" to the performance of these NDP projects as they allowed the company to coordinate decentralized tasks, ensure the exchange of technical data and promote creativity. In the same vein, the positive contribution of IT to performance criteria of NPD projects has been the focus of several prior studies. [START_REF] Ozer | Information Technology and New Product Development[END_REF] explains how the use of IT in NPD for industrial firms improves the speed of development and the product quality, thereby increasing the chances of the products' commercial success [START_REF] Clark | Product development performance: Strategy, organization, and management in the world auto industry[END_REF]. Also, [START_REF] Menon | Antecedents and outcomes of new product development speed. An interdisciplinary conceptual framework[END_REF] and [START_REF] Alavi | Review : Knowledge Management and Knowledge Management Systems : Conceptual Foundations and Research Issues[END_REF] suggest that IT facilitate the rapid exchange of relevant information, which improves the speed of NPD. [START_REF] Smith | The Role of Information Technologies in Enhancing R&D-Marketing Integration: An Empirical Investigation[END_REF] argue that IT contribute to reducing development time, improving the flexibility of the NPD process, and integrating different cross-functional knowledge. Other authors highlighted the particular contributions of each IT functionality to the performance of NPD projects as detailed below.

First, PRM functionalities improve the visibility of project data, automate tasks, and enable tracking and managing the project and its resources [START_REF] Nambisan | The role of information technology in product development: an introduction. Information Technology and Product Development[END_REF]. Therefore, the effective use of these systems reduces coordination efforts and improves the quality of information for decision-making [START_REF] Mauerhoefer | The Impact of Information Technology on New Product Development Performance[END_REF]. In addition, these PRM features ensure continuity and connectivity between the different stages of the NPD process, thus contributing to the reduction of cost and development time [START_REF] Sethi | Web-based product development systems integration and new product outcomes: A conceptual framework[END_REF]. Second, KM functionalities enable capturing, coding and sharing all types of knowledge in NPD

Twenty-Eighth European Conference on Information Systems (ECIS2020), A Virtual AIS Conference. [START_REF] Hong | IT investments and product development effectiveness: Iranian SBs[END_REF]. As a result, they offer project actors the opportunity to review project information and data, which significantly improves NPD project performance [START_REF] Lynn | Knowledge management in new product teams: practices and outcomes[END_REF]. Also, they allow the integration of knowledge and information from various functions [START_REF] Durmuşoǧlu | The use of information technology tools in new product development phases: Analysis of effects on new product innovativeness, quality, and market performance[END_REF], hence positively affecting the product quality [START_REF] Sethi | Web-based product development systems integration and new product outcomes: A conceptual framework[END_REF]. In addition, [START_REF] Banker | Understanding the impact of collaboration software on product design and development[END_REF] observed that the implementation of KM tools in NPD reduces the number of design errors and late adjustments. This implementation enhances the product quality, reduces the time spent by the actors in the reengineering and cuts down the costs associated with this activity. Finally, CW functionalities support a rich communication between the project actors. This leads to the development of better quality products that meet functional requirements and customers' expectations [START_REF] Durmuşoǧlu | The use of information technology tools in new product development phases: Analysis of effects on new product innovativeness, quality, and market performance[END_REF]. Through this rich communication, these systems also increase the number of generated ideas, thus giving rise to more innovative products [START_REF] Troy | Generating new product ideas: An initial investigation of the role of market information and organizational characteristics[END_REF]. In addition, CW features support real-time distant work, which facilitates design review and simultaneous simulation [START_REF] Bacciotti | A CAD tool to support idea generation in the product planning phase[END_REF]. As a result, product design is optimized and its quality is enhanced [START_REF] Durmuşoǧlu | The use of information technology tools in new product development phases: Analysis of effects on new product innovativeness, quality, and market performance[END_REF]. This simultaneous work enabled by these IT functionalities also help resolve design problems [START_REF] Becker | The impact of virtual simulation tools on problemsolving and new product development organization[END_REF] and provide instantaneous access to information [START_REF] Sethi | Web-based product development systems integration and new product outcomes: A conceptual framework[END_REF], thus reducing cost and development time [START_REF] Thomke | The effect of "front-loading" problem solving on product development performance[END_REF]. Based on this literature, we raise the following hypotheses:  H4: The effective use of IT for PRM has a positive impact on the performance of collaborative buyersupplier NPD projects.  H5: The effective use of IT for KM has a positive impact on the performance of collaborative buyersupplier NPD projects.  H6: The effective use of IT for CW has a positive impact on the performance of collaborative buyersupplier NPD projects. [START_REF] Banker | Understanding the impact of collaboration software on product design and development[END_REF] advocated that collaborative IT positively contribute to NPD project performance (i.e. development cost and time, and product quality) when there is an efficient collaboration between the NPD project teams. Indeed, the authors showed that collaboration partially mediates the impact of collaborative IT on the performance of NPD projects. They concluded that it is important to consider as much the direct effects of using IT as its indirect effects. This study of [START_REF] Banker | Understanding the impact of collaboration software on product design and development[END_REF] is aligned with the extensive literature that associates the performance of NPD projects with the quality of collaboration [START_REF] Bodas Freitas | Formalized Problem-Solving Practices and the Effects of Collaboration with Suppliers on a Firm's Product Innovation Performance[END_REF][START_REF] Mishra | In union lies strength: Collaborative competence in new product development and its performance effects[END_REF][START_REF] Um | Collaboration and opportunism as mediators of the relationship between NPD project uncertainty and NPD project performance[END_REF]. Accordingly, we hypothesize that:  H7: The effective use of IT for PRM has a positive indirect effect on NPD project performance through the collaboration quality.  H8: The effective use of IT for KM has a positive indirect effect on NPD project performance through the collaboration quality.  H9: The effective use of IT for CW has a positive indirect effect on NPD project performance through the collaboration quality.

Indirect impacts of IT effective use on NPD project performance through collaboration quality

Research methodology

Data collection and sample

To investigate the proposed hypotheses, we performed a cross-sectional international survey with companies that have been engaged in a buyer-supplier collaboration for NPD. To determine a sample size that is sufficient for the multiple linear regression approach to be used in this study, we performed an a priori power test following the recommendations of [START_REF] Cohen | Statistical power analysis for the behavioral sciences[END_REF], with G*Power 3.1.9.2 software [START_REF] Faul | Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses[END_REF]. By considering the parameters of three predictors (Figure 1), an effect size of 0.15 (moderated value), a test power level of 85%, and a maximum allowed error of 5%, the software calculated 87 responses as the minimum adequate sample size. To form our sample, we contacted via e-

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mail the alumni of a French industrial engineering management Master's degree and the members of a professional global product development community. To assess the adequacy of these potential participants to our study, we asked them whether they have been involved in an inter-firm NPD collaboration and requested them to inform their hierarchical position in the firm. As a result, we identified 361 suitable respondents and sent them the questionnaire link. Two reminding emails were sent out over a four months' period from January 2018 to April 2018. We obtained 90 complete responses, which represents a response rate of 25%. Table 1 shows the composition of the sample.

Measurement scales

The dependent and independent variables of our study are measured with multi-item scales (Appendix A) adapted from extant literature. The variables representing effective use of PRM, KM and CW IT were inspired by the constructs of [START_REF] Pavlou | From IT leveraging competence to competitive advantage in turbulent environments: The case of new product development[END_REF] proposed for NPD contexts and not particularly developed for a buyer-supplier collaboration. Then, for buyer-supplier collaboration quality, we relied on the multi-item scale of [START_REF] Yan | Buyer-supplier collaboration quality in new product development projects[END_REF] which encompasses the different facets of buyer-supplier collaboration quality namely sufficiency of efforts, quality of communication, coordination, and mutual support. Lastly, NPD project performance was assessed with a three-item scale proposed by [START_REF] Tatikonda | Successful execution of product development projects: Balancing firmness and flexibility in the innovation process[END_REF], which considers product quality, product objective cost and development time. All items were measured using a five-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). Three additional control variables were included in the analysis. First, NPD team size was used to control for its potential influence on IT usage. Indeed, it is more difficult for large team members to get to know each other, which might affect coordination, knowledge sharing and communication [START_REF] Akgün | Knowledge networks in new product development projects: A transactive memory perspective[END_REF]. Second, we included firm size as a control variable because the adoption and the benefits gained from IT use can vary according to the size of a firm [START_REF] Caldeira | Understanding the successful adoption and use of IS/IT in SMEs: An explanation from Portuguese manufacturing industries[END_REF]. Finally, we controlled for the effect of project priority, as a high project priority encourages NPD units to work harder in order to achieve a superior performance [START_REF] Peng | Collaborative product development: The effect of project complexity on the use of information technology tools and new product development practices[END_REF].

Biases related to quantitative survey studies

To ensure that the obtained sample of responses was representative of the population, non-response bias was assessed by verifying that early and late respondents were not significantly different in terms of responses to key questions related to the constructs of the study [START_REF] Armstrong | Estimating Nonresponse Bias in Mail Surveys[END_REF]. The results of the t-test that was performed to compare early and late (i.e. fourth quartile) waves showed no statistically significant difference between the means of the two groups (p-value> 0.05), suggesting that non-response bias is not a concern in our study. Furthermore, we investigated the existence of significant differences among the respondents' groups given the heterogeneity of their functions. In this respect, we performed a t-test to compare the means of each couple of groups within our sample (R&D,

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Engineering and Others). The results indicated that, except for three items (Perf1, CQ6 and CQ8) comparing Engineering to Others group, the responses do not vary for all the remaining 48 comparisons (p-value> 0.05).

As our data are self-reported, and given that the same respondents answered the questions on IT effective use and on NPD project success, we used two tests to check for common method bias before analysing our model. First, we carried out a Harman's single-factor test by performing a principal component factor analysis on all items used in this study [START_REF] Podsakoff | Self-Reports in Organizational Research: Problems and Prospects[END_REF], which resulted into a 30.63% variance explained by the single factor. As this percentage did not account for the majority of the variance in the model, the test indicated that common method bias is unlikely to be a problem in this study. Second, we used the marker variable technique suggested by [START_REF] Lindell | Accounting for common method variance in cross-sectional research designs[END_REF]. This method examines the correlations between the study's constructs and a marker variable that is theoretically unrelated to at least one of the study's substantive variables [START_REF] Williams | Method variance and marker variables: A review and comprehensive CFA marker technique[END_REF]. Hence, we used the newness of the product's technology as a marker variable. The resulting correlations varied from 0.159 to -0.01 (average correlation value = 0.059) and none of them was significant (average pvalue = 0.478). Therefore, this test confirms the absence of common method bias issues from our study.

Constructs' validity and reliability

Before testing the model's hypotheses, we first assessed the validity and reliability of our constructs using Stata 13.0® [START_REF] Anderson | Structural Equation Modeling in Practice: A Review and Recommended Two-Step Approach[END_REF]. In this respect, a series of confirmatory factor analyses (CFAs) was performed to test the measurement scales on their unidimensionality. We divided our measures into three theoretically different subsets: the three IT effective use variables (for PRM, KM, and CW), the buyer-supplier collaboration quality construct, and the NPD project performance construct. This division into subsets is due to our small sample size, which violates the rule stating that the ratio of the sample size to the number of free parameters must not exceed 5:1 [START_REF] Akgün | Knowledge networks in new product development projects: A transactive memory perspective[END_REF][START_REF] Bentler | Practical Issues in Structural Modeling[END_REF]. For each subset, the CFA model was fitted to the data and the items that were not unidimensional or had low loadings were dropped (Appendix A) in a step-by-step purification process until a satisfactory fit was achieved [START_REF] Hair | Multivariate Data Analysis[END_REF]. The model's fit was adequate for the first two subsets: IT effective use (χ²=53.1, p-value=0.1, RMSEA=0.06, CFI=0.97, TLI=0.96) and buyer-supplier collaboration quality (χ²=0.64, p-value=0.73, RMSEA= 0, CFI=1, TLI=1.03). Unidimensionality of NPD project performance was not assessed, since one item was removed during the purification process. This resulted in a two-item CFA model for NPD project performance, which is an under-identified model with less parameters to observe than to estimate. Then, all the measures of the conceptual model were simultaneously subjected to a one-factor model CFA [START_REF] Hair | Multivariate Data Analysis[END_REF]. Due to small sample size, the analysis was performed using parcels or subsets of items (i.e. mean of several items that measure the same construct) instead of individual items as recommended by different authors (e.g. [START_REF] Akgün | Transactive memory system in new product development teams[END_REF][START_REF] Schmit | The Big Five in Personnel Selection: Factor Structure in Applicant and Nonapplicant Populations[END_REF]. In this respect, two parcels of items for each scale were computed. Each parcel consisted of a randomly divided subset of the scale's items. The one-factor CFA produced a good fit (χ²=34.46, p-value=0.10, RMSEA=0.06, CFI=0.98, TLI=0.96) providing more support to the unidimensionality of all the scales.

Bivariate correlation matrix with descriptive statistics and reliability estimates

Next, the constructs' convergent validity was verified by checking their items' loadings (which should exceed 0.5) and calculating their AVE (which should exceed 0.5) as recommended by [START_REF] Hair | Multivariate Data Analysis[END_REF].

Twenty-Eighth European Conference on Information Systems (ECIS2020), A Virtual AIS Conference.

All items strongly loaded on their constructs with p-value <0.001. Also as explained in Table 2, all AVE values exceeded 0.5 and all constructs' reliabilities (Cronbach's α and Composite Reliability) were beyond the 0.6 threshold recommended for exploratory research [START_REF] Hair | Multivariate Data Analysis[END_REF]. Finally, we assessed the discriminant validity of the constructs in our model. We checked the criteria of [START_REF] Fornell | Evaluating Structural Equation Models with Unobservable Variables and Measurement Error[END_REF] by ensuring that the square root of each construct's AVE is greater than its correlations with the other constructs (Table 2). We also tested discriminant validity based on the approach of [START_REF] Bagozzi | Assessing Construct Validity in Organizational Research[END_REF], who suggested a series of two-factor model estimations. In this respect, we performed two CFA models for each pair of constructs and compared their respective goodness of fit. In the first model, we restricted the correlation between the two constructs to unit, while in the second model we freed this restriction and calculated the goodness of fit for the original constructs.

The overall results of this test confirmed discriminant validity (Δχ² > 3.84, p-value < 0.05).

Data analysis

After refining our constructs, we analysed our conceptual model (Figure 1) using multiple linear regressions to test the direct and indirect effects on IT effective use on NPD project success. In this respect, we first evaluated the assumptions of normality, linearity and homoscedasticity of the residuals between all dependent and independent variables under IBM® SPSS® Statistics 21. We examined respectively the probability-probability (p-p) plots, plots of partial regression and plots of standardized residuals against the predicted value [START_REF] Field | Discovering Statistics Using IBM SPSS Statistics[END_REF]. These tests confirmed the required assumptions for multiple linear regression. Hence, we tested our hypothesized direct and indirect impacts of IT effective use on NPD project success by performing a series of multiple linear regressions. To estimate the indirect impact on NPD project performance through collaboration quality of effective use for each IT functionality, we performed a bootstrapping procedure under IBM® SPSS® Statistics 21 [START_REF] Hayes | Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach[END_REF], itself based on multiple linear regressions [START_REF] Preacher | SPSS and SAS procedures for estimating indirect effects in simple mediation models[END_REF]. This approach has become popular to evaluate indirect effects of mediating variables [START_REF] Hayes | Beyond Baron and Kenny: Statistical mediation analysis in the new millennium[END_REF][START_REF] Maruping | Motivating employees to explore collaboration technology in team contexts[END_REF]. If « a » is the direct effect of the independent variable on the mediator, and « b » is that of the mediator on the dependent variable, the bootstrapping aims at proving that « axb », which represents the magnitude of the indirect effect, is statistically significant [START_REF] Preacher | SPSS and SAS procedures for estimating indirect effects in simple mediation models[END_REF]. This technique relies on a random re-sampling with a discounted draw, performed from the original sample [START_REF] Efron | An introduction to the bootstrap[END_REF] in order to create a distribution resampling for the « axb » product. When the generated confidence interval does not include the null value, the indirect effect is statistically significant [START_REF] Preacher | SPSS and SAS procedures for estimating indirect effects in simple mediation models[END_REF].

Results

Direct impacts of IT effective use on success of collaborative buyersupplier NPD projects

We performed multiple linear regressions following a hierarchical procedure to test the direct effects of IT effective use on the two success criteria of collaborative buyer-supplier NPD projects, i.e. collaboration quality (Hypotheses H1, H2 and H3) and NPD project performance (Hypotheses H4, H5 and H6) as depicted in Table 3. For each of these two dependent variables, two multiple linear regression models were estimated [START_REF] Field | Discovering Statistics Using IBM SPSS Statistics[END_REF][START_REF] Hair | Multivariate Data Analysis[END_REF]. The first regression was performed only with the control variables and the dependent construct, while the second regression model also included the independent variables representing the effective use of the three IT functionalities (i.e. for PRM, KM and CW). The VIF values were below 3.0 in all models, thereby indicating that multicollinearity is not a major issue.

For the dependent variable « Collaboration Quality», the regression of this construct on the control variables was not statistically significant (Model 1). Following the introduction of the three independent variables in the second regression (Model 2), the model became statistically significant (F= 7.147, p <0.01) and explained 29.3% of variance for collaboration quality (Adjusted R² = 0.293). Moreover, the change of R² was also significant (ΔR²= 0.302, p <0.01), suggesting that the introduction of the independent variables increased the predictive power of the model. As for the control variables, « Firm

Twenty-Eighth European Conference on Information Systems (ECIS2020), A Virtual AIS Conference.

size » and « NPD team size» displayed negative significant associations with collaboration quality. Hence, the larger the sizes of the firm and the project team, the more it is difficult to reach a good collaboration quality. Finally, the regression results of the three independent variables showed that the effective use of IT for PRM (unstandardized regression coefficient B = 0.204, p <0.1), for KM (B = 0.212, p <0.1), and for CW (B = 0.209, p <0.1) have positive significant impacts on collaboration quality. These results therefore confirmed the hypotheses H1, H2 and H3 of the conceptual model. The standardized coefficients of these three effects are β= 0.225 for PRM, β = 0.224 for KM, and β = 0.230 for CW IT functionalities and are hence equivalent.

For the dependent variable « NPD project performance », both regression models (Model 3 and Model 4) were statistically significant. Also, Model 4 was characterized by a significant change in R² (ΔR²= 0.113, p<0.05) and explained 17.3% of variance for NPD project performance (Adjusted R²=0.173). Such result implies that the introduction of the independent variables improved the model's predictive power. As for the control variables, we observed that, similarly to collaboration quality (Model 2), « Firm size » and « NPD team size » displayed negative significant associations with NPD project performance. Finally, regression results for the three independent variables showed that only the effective use of IT for KM has a positive significant impact on NPD project performance (unstandardized regression coefficient B=0.325, p<0.05), therefore confirming hypothesis H5. No statistically significant effect was observed regarding the effective use of IT for PRM and for CW, hence providing no support to hypotheses H4 and H6.

Indirect impacts of IT effective use on NPD project performance through collaboration quality

We followed the recommendations of [START_REF] Hayes | Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach[END_REF] to evaluate the indirect effects of the three independent variables (effective use of IT for PRM, for KM and for CW) on NPD project performance through collaboration quality. In this respect, we simulated K = 5000 bootstrap samples to estimate three distinct models. Indeed, the indirect effect « axb » was estimated for one independent variable at a time, while controlling the direct effects of the other independent and control variables. A 90% confidence interval was set to align with the significance level for the direct effects of IT effective use for PRM, KM and CW on NPD project success (p <0.1), obtained in section 5.1. The results of these tests are presented in Table 4.

For PRM IT functionalities, the indirect effects estimated by the bootstrapping were between 0.017 and 0.306 with 90% confidence. Similarly, the estimated indirect effects for KM IT functionalities ranged between 0.016 and 0.298 with 90% confidence. Finally, the indirect effects for CW IT functionalities varied between 0.022 and 0.294 with 90% confidence. We concluded that for each of the tested indirect effects, the 90% confidence interval is strictly positive and therefore does not include the null value. Hence, the effective use of IT for PRM, KW and CW positively and significantly (p<0.1) contribute to NPD project performance through collaboration quality, which provides full support to H7, H8 and H9.

Twenty-Eighth European Conference on Information Systems (ECIS2020), A Virtual AIS Conference. Discussion and conclusions

Theoretical implications

The purpose of this study was to examine how IT effective use impacts the success of collaborative buyer-supplier NPD projects. Our study completes the literature on IT capability applied to innovation management and New Product Development [START_REF] Pavlou | The "Third Hand": IT-Enabled Competitive Advantage in Turbulence Through Improvisational Capabilities[END_REF][START_REF] Rai | Interfirm IT capability profiles and communications for cocreating relational value: evidence from the logistics industry[END_REF] by shedding light on the contributions of each of the three IT-leveraging capability dimensions, which have usually been treated as equal. Indeed, the results point that IT effective use has different effects on NPD project success depending on the considered IT functionality and the success criterion.

On the one hand, our results provide evidence that each dimension represents a complementary yet a different resource to achieve performance improvement as underlined in the resource based view. In this respect, we showed that the direct impact of IT effective use on NPD project performance is positive and significant for KM functionalities, with no significant effects for PRM and CW. These findings regarding the impact of IT effective use for KM functionalities are consistent with those of [START_REF] Vaccaro | Knowledge Management Tools, Inter-Organizational Relationships, Innovation and Firm Performance[END_REF] which, to the best of our knowledge, is the only study that focuses on the specific context of buyer-supplier collaboration in NPD. The insignificance results regarding IT effective use for PRM and CW functionalities can be accounted for the fact that such tools are usually highly sophisticated, which may cause the users' reluctance to adopt them [START_REF] Marion | Do social media tools impact the development phase? An exploratory study[END_REF][START_REF] Parida | A study of how ICT capabilities can influence dynamic capabilities[END_REF]. More broadly, insignificant effects of IT use on NPD project performance were underlined by prior research [START_REF] Durmuşoǧlu | The use of information technology tools in new product development phases: Analysis of effects on new product innovativeness, quality, and market performance[END_REF][START_REF] Marion | Do social media tools impact the development phase? An exploratory study[END_REF]. However, these studies highlighted an insignificant effect at an aggregated level of IT use without taking into account the different roles played by each IT functionality. In contrast to these prior studies, our research unveils differentiated effects of these functionalities, thereby emphasizing the importance of considering a detailed functional approach when studying the impact of IT effective use, at least on the NPD project performance criterion. On the other hand, our study confirmed that the IT effective use for PRM, KM and CW have direct, positive and equivalent impacts on buyer-supplier collaboration quality. In this sense, our results extend those of prior research in two ways. First, the majority of studies that proved a similar impact focused on intraorganizational or even non-precise collaborative contexts (e.g. [START_REF] Banker | Understanding the impact of collaboration software on product design and development[END_REF]Song and Song, 2010). Therefore, our study is consistent with their results and further extends them to the context of buyer-supplier collaboration in NPD. Second, while some scholars aggregated IT use into a single construct (e.g. [START_REF] Han | Analyzing the impact of a firm's capability on outsourcing success: A process perspective[END_REF][START_REF] Reid | The impact of the frequency of usage of IT artifacts on predevelopment performance in the NPD process[END_REF], our research offers a deeper understanding to this "black box" as we prove that the different IT functionalities contribute in a similar magnitude to improving buyer-supplier collaboration quality in NPD.

This study also completes literature on IT use in the supply chain context that questions the direct effects of IT capabilities on firm performance by contending that the effects are mediated by other capabilities [START_REF] Liu | The impact of IT capabilities on firm performance: The mediating roles of absorptive capacity and supply chain agility[END_REF][START_REF] Sambamurthy | Shaping Agility Through Digital Options: Reconceptualizing the Role of Information Technology in Contemporary Firms[END_REF]. In the context of inter-firm product innovation, it empirically demonstrates that the effective use of the three IT functionalities (for PRM, KM and CW)

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has an indirect impact on NPD project performance through buyer-supplier collaboration quality as a mediator. While our previous results have proved the direct impact of IT for KM, a major contribution of our study is to show that the impact of IT effective use for PRM and CW on NPD project performance is made possible only through an enhancement of collaboration quality. Hence, these findings offer an interesting insight for a better understanding of the mechanisms by which IT foster value in this specific context of NPD. Our result echoes the call of [START_REF] Melville | Review: Technology Information An Performance: Organizational Integrative Model of IT Business Value[END_REF] to consider intermediary processes in order to shed light on the contribution of IT effective use. By demonstrating the mediating role of collaboration quality, our study adds another piece to resolve the puzzle of IT productivity paradox [START_REF] Barczak | Antecedents and consequences of information Technology Usage in NPD: A comparison of dutch and U.S. companies[END_REF][START_REF] Montoya | Can you hear me now? Communication in virtual product development teams[END_REF][START_REF] Pavlou | From IT leveraging competence to competitive advantage in turbulent environments: The case of new product development[END_REF]. More specifically, our findings are consistent with the conclusions of [START_REF] Banker | Understanding the impact of collaboration software on product design and development[END_REF], who argues that the contribution of IT effective use to improving project performance lies within a better collaboration of NPD actors. Furthermore, the mediating role of buyer-supplier collaboration quality stresses the subjective contextspecific nature related to IT use, as suggested by different authors (e.g. [START_REF] Montoya | Can you hear me now? Communication in virtual product development teams[END_REF][START_REF] Nambisan | Information systems as a reference discipline for new product development[END_REF]. As IT use should be aligned with its context [START_REF] Premkumar | Information Processing View of Organizations: An Exploratory Examination of Fit in the Context of Interorganizational Relationships[END_REF], we could expect different mediators for each context. Consequently, one contribution of this study is to posit that for IT use in the collaborative buyer-supplier NPD context, collaboration quality is a key contextual variable to consider.

Managerial implications

This research advances managerial understanding in two ways. First, our findings highlight the need to manage the effectiveness of IT use in order to promote the success of inter-organizational collaboration with suppliers in NPD. In this respect, managers need to pay sufficient attention to the effective use of IT by NPD actors and think about ways to build this effective use in this context. This could be done by ensuring that users develop high competency of IT use regarding each IT enabled NPD activity (PRM, KM, CW) through training to enhance their practical abilities, but also by promoting and communicating on the importance of inter-organizational IT to foster the users' willingness to efficiently use these IT functionalities. This sensitization should highlight the advantages of IT to meet the needs of both buyer and supplier project teams, at least for the most strategic partnerships. Second, our study informs IT managers about the strategic potential of inter-organizational IT investments. As these systems eventually allow for savings in development costs and enhancement of product quality, IT managers could remove the top management doubts concerning the value of such IT, especially if the firm is frequently involved in collaborative buyer-supplier NPD projects.

Limitations and future research avenues

Our findings should be interpreted in the light of some limitations that future research could address. From a methodological standpoint, we first believe that other types of studies might compensate for the limits of the cross-sectional survey used in this research. Indeed, as the development of IT effective use is an ongoing phenomenon, future research could examine the same issues addressed in this study using time-series panel data. Second, regarding firm performance, IT effective use can be an endogenous explanatory variable and accordingly prior research provided guidelines to control for such bias (e.g. [START_REF] Maiga | Selection bias and endogeneity issues on the relationship between information technology and firm performance[END_REF][START_REF] Zhang | Impact of IT governance and IT capability on firm performance[END_REF]. Although no study underlined such effect at collaborative NPD level, we believe future research could explore the endogeneity of IT effective use regarding collaboration quality and NPD project performance. Indeed, firms with better buyer-supplier relationships may per se show more effective use of IT, and better project performance may induce even further effective uses of IT in the relationship. Hence, regarding such potential endogeneity effect, it would be relevant to rely on a 2SLS technique [START_REF] Benitez-Amado | How to address endogeneity in partial least squares path modelling[END_REF] to separately estimate each structural equation in our model. From a theoretical point of view, we first underline that the generalization of our findings to specific industries or firms should be made with caution. Further research could explore the significance of the conceptual framework under various industry characteristics. Second, the theoretical coverage of IT effective use for KM was altered during the purification process of the scale. Items regarding the tacit nature of knowledge were dropped. A possible perspective for future research could be the separation

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of the KM construct into two different latent variables related to explicit and tacit knowledge management. Third, our research only examined two aspects of NPD project success. There are potentially other important outcomes to consider such as innovativeness or market success. Further studies could investigate in more depth the impact of IT effective use on the multidimensional nature of NPD project success. Fourth, the direct effects of IT effective use for PRM and CW on NPD project performance were not significant, and their indirect effects through collaboration quality were significant only at p<0.1. Future empirical research might investigate additional mediators that explain the contribution of IT effective use to the performance of inter-organizational collaborative NPD projects. Fifth, our conceptual model can be enriched by introducing extra-firm control variables (e.g. market turbulence, competitive dynamism) which might explain variance in collaborative NPD project success. Finally, our study is based on data from only one informant, which may decrease the quality of the results. Future research would overcome this weakness by assessing the NPD project performance from secondary data or from another informant within the firm involved in the project.

Appendices

Appendix A. Latent variables and their associated items Twenty-Eighth European Conference on Information Systems (ECIS2020), A Virtual AIS Conference.

  Figure 1. Conceptual model

*

  and supplier) teams took full responsibility for achieving the project objectives PRM2 Control and monitoring of the project progress CQ2* Both teams fully contributed to the project workload* PRM3 Project management and provision of the necessary information for this purpose CQ3* Both teams were fully satisfied with how quick the information was made available by the other team* PRM4 Access to project documentation and real-time update of project deliverables CQ4 Both teams were fully satisfied with the accuracy of the information provided by the other team PRM5* Management of the co-development process and workflows* CQ5* The different activities carried out by the members of both teams matched well* Effective use of IT for KM (KM) KM1 Codification and storage of information and knowledge over time CQ6 The members of the two teams who worked together did their job properly and efficiently KM2 Share of information and knowledge between project actors CQ7* All activities were completed at the right time with regard to the project schedule* KM3 Search, extraction and reuse by project actors of information and knowledge CQ8 Important ideas and information were exchanged openly between the two teams KM4* Management of the documents and data evolution* CQ9* The actors of both teams adapted well to each other* KM5* Creation and support of knowledge networks* CQ10* The general atmosphere was cooperative* Item deleted following the confirmatory factor analysis (CFA) CW4 Combination and integration of information and individual knowledge for decision-making and / or joint problem solving (e.g. analysis or simulation tool, concept maps) CW5* Simultaneous real-time work and virtual design reviews*

Table 2 .

 2

Table 3 .

 3 Results of the direct impacts of IT effective use on success of collaborative NPD project

		Buyer-Supplier Collaboration Quality	NPD project performance
		Model 1	Model 2	Model 3	Model 4
	Ctrl 1: Firm Size	-0.054	-0.299**	-0.272*	-0.440**
	Ctrl 2: NPD Team Size	-0.142*	-0.182**	-0.214**	-0.214**
	Ctrl 3: Project Priority	0.008	0.08	0.05	0.101
	Effective use of IT for PRM		0.204*		0.034
	Effective use of IT for KM		0.212*		0.325**
	Effective use of IT for CW		0.209*		0.048
	F-value	1.159	7.147***	3.760**	4.111***
	R²	0.039	0.341	0.116	0.229
	Adjusted R²	0.005	0.293	0.085	0.173
	ΔR²		0.302***		0.113**
	VIF interval	[1.013-1.034]	[1.037-2.320]	[1.013-1.034]	[1.037-2.320]
	N=90, * p< 0.1, **p<0.05, ***p<0.01

Table 4 .

 4 Results of the indirect impacts of IT effective use on NPD project performance through collaboration quality 6


Pierre Soulard

Denis Dumont

Thomas Salez

Elie Raphaël

Pascal Damman
email: pascal.damman@umons.ac.be

A microscopic picture of erosion and sedimentation processes in dense granular flows

Gravity-driven flows of granular matter are involved in a wide variety of situations, ranging from industrial processes to geophysical phenomena, such as avalanches or landslides. These flows are characterized by the coexistence of solid and fluid phases, whose stability is directly related to the erosion and sedimentation occurring at the solid-fluid interface. To describe these mechanisms, we build a microscopic model involving friction, geometry, and a nonlocal cooperativity emerging from the propagation of collisions. This new picture enables us to obtain a detailed description of the exchanges between the fluid and solid phases. The model predicts a phase diagram including erosion, sedimentation, and stationary-flow regimes, in quantitative agreement with experiments and discrete-element-method simulations.

Over the last two decades, different theoretical approaches have been proposed to describe dense granular flows. The most widely used models are based on the µ(I) rheology [START_REF] Jop | A constitutive law for dense granular flows[END_REF]. This approach consists in a semi-empirical description of granular matter, through an effective friction coefficient µ, that is a function of an inertial number I directly related to the flow velocity [START_REF] Andreotti | Granular Media: Between Fluid and Solid[END_REF]. Extensions of this µ(I) rheology have been proposed by several authors to address spatial heterogeneities and non-local effects [START_REF] Pouliquen | A non-local rheology for dense granular flows[END_REF][START_REF] Kamrin | Nonlocal constitutive relation for steady granular flow[END_REF][START_REF] Bouzid | Nonlocal rheology of granular flows across yield conditions[END_REF][START_REF] Bouzid | Non-local rheology in dense granular flows[END_REF][START_REF] Kamrin | Non-locality in granular flow: Phenomenology and modeling approaches[END_REF]. For instance, the yield stress increases as the thickness of the flow region reduces, which manifests itself through a thickness-dependent stop angle in granular flows down inclined planes [START_REF] Pouliquen | Scaling laws in granular flows down rough inclined planes[END_REF]. Another example deals with heap flows, where creep appears through a spatial exponential decay of the velocity over a few grains [START_REF] Kamrin | Non-locality in granular flow: Phenomenology and modeling approaches[END_REF]. In parallel, semi-empirical models have been developed to describe the dynamics of avalanches, defined as dense granular flows atop static granular solids. This type of systems exhibits complex behaviours due to the intrinsic transfers of energy and matter between the fluid and solid phases at their interface. Specifically, the erosion of the solid phase by an avalanche feeds the fluid phase, and thus the avalanche, while the sedimentation of the fluid phase tends to stop the motion. The BCRE model was proposed to account for the coupled dynamics [START_REF] Bouchaud | A model for the dynamics of sandpile surfaces[END_REF][START_REF] Bouchaud | Hysteresis and Metastability in a Continuum Sandpile Model[END_REF][START_REF] Boutreux | Surface flows of granular materials: A modified picture for thick avalanches[END_REF][START_REF] Trinh | Erosion and deposition processes in surface granular flows[END_REF]. Two key ingredients are at the heart of this approach: i) the intuitive idea that the evolution of the interface between the two phases is determined by its local tilt angle θ (see Fig. 1); and ii) the assumed existence of a neutral angle θ * , such that for θ > θ * erosion occurs while for θ < θ * sedimentation occurs. Subsequent studies further suggested that the neutral angle is given by θ * = arctan(µ dyn ) [START_REF] Aradian | Surface flows of granular materials: a short introduction to some recent models[END_REF], where µ dyn is an effective friction coefficient that might depend on the flow rate and the fluid layer thickness [START_REF] Douady | On granular surface flow equations[END_REF].

In this Letter, we propose a new microscopic description of the erosion and sedimentation processes at play in dense granular flows driven by gravity. Our model involves a flowing layer of grains over a static, yet erodible, one and includes a nonlocal cooperativity emerging from the propagation of collisions. Its predictions are directly confronted to numerical results obtained from discreteelement-method (DEM) simulations, in two canonical configurations: an inclined plane and a heap. Despite its simplicity, the proposed model enables us to obtain a detailed description of the exchange mechanisms between the fluid and solid phases, and ultimately a complete phase diagram of erosion and sedimentation. The model quantitatively describes the observed transitions between sedimentation, stationary flow, and erosion. Moreover, it allows to rationalize an important observable from inclined-plane experiments in the literature: the stop angle of a granular flow. We consider a system made of identical spheres of diameter d, and mass m, with an interparticle sliding (resp. rolling) friction coefficient µ S (resp. µ R ) [START_REF] Estrada | Identification of rolling resistance as a shape parameter in sheared granular media[END_REF]. These two coefficients are merged into a single effective coefficient µ eff (see Supplementary Materials). It should be noted that our description is a mean-field one, involving average quantities and avoiding the actual irregularities inevitably present in a real granular medium. As schematized in Fig. 1, we consider a moving layer of thickness R (in number of grains and counted vertically), i.e. the fluid phase, above a static layer, i.e. the solid phase. The roughness of the solid-fluid interface is characterized by an angle ϕ sol with respect to the normal to the interface, quantifying the angular depth of the hole between two grains. The value of ϕ sol ranges between 23.4 • and 30 • for spherical grains in 3D [START_REF] Albert | Maximum angle of stability in wet and dry spherical granular media[END_REF]. In the following, we focus on the motion of a single moving grain at the solid-fluid interface. This grain is subjected to the weight exerted by the R grains constituting the moving layer and is not allowed to jump. In the µ(I)-rheology description, this situation is equivalent to considering flows with small in-FIG. 1. A dense fluid granular phase (yellow) moves over an underlying static solid granular phase (orange). Locally, the solid-fluid interface makes an angle θ with the horizontal plane. The instantaneous position of a particular grain, moving above a static grain n, is described through the angle ϕ between the normal to the interface and the contact interparticle-distance unit vector er. The moving grain starts at angular position -ϕ sol , with angular velocity φ+ n , and arrives at +ϕ sol , with angular velocity φn . Also shown is the effective potential energy Epot as a function of angular position ϕ, during the first step of the grain motion, within one cycle where ϕ ∈ [-ϕ sol , +ϕ sol ]. The two essential features are the barrier energy ∆EB at maximum, and the kinetic energy gained at the end of the first step ∆EK. ertial numbers. In order to move forward, the grain has to frictionally slide and/or roll over the bumpy underlying static layer. The instantaneous position of the moving grain is described through a single variable: the angle ϕ between the normal to the interface and the contact interparticle-distance unit vector e r (see Fig. 1).

As in previous studies [START_REF] Quartier | Dynamics of a grain on a sandpile model[END_REF][START_REF] Andreotti | Selection of velocity profile and flow depth in granular flows[END_REF][START_REF] Andreotti | A mean-field model for the rheology and the dynamical phase transitions in the flow of granular matter[END_REF], the motion is divided into two subsequent steps. First, the grain starts at angular position -ϕ sol with angular velocity φ+ n , and then moves above a static grain indexed by n, until it arrives at +ϕ sol with angular velocity φn . Secondly, it elastically collides the next static grain indexed by n + 1, which induces a sharp change of its velocity (orientation and norm), as well as secondary elastic collisions within the fluid and solid phases. A new and similar cycle then starts for the moving grain, with an initial angular velocity φ+ n+1 . During the first step, the trajectory of the grain is circular. The only force components which contribute to the variation of its kinetic energy are along the tangential unit vector e ϕ . These are: the transverse projection Rmg sin(ϕ + θ) e ϕ of the weight, and the effective friction force -µ eff Rmg cos(ϕ + θ) e ϕ generated by the normal projection of the weight. We implicitly assumed here that most of the frictional dissipation occurs through the contact of the considered moving grain and the underlying static layer, since all the grains of the moving layer have similar velocities.

The total force along e ϕ can be formally recast as the derivative of an effective potential, -(1/d)dE pot /dϕ, where E pot (ϕ) = Rmgd{cos(ϕ + θ) -cos(ϕ sol -θ) + µ eff [sin(ϕ + θ) + sin(ϕ sol -θ)]}, and where the origin of energies has been arbitrarily chosen at ϕ = -ϕ sol (see Fig. 1). At ϕ = arctan(µ eff ) -θ, this potential is maximal, resulting in an energy barrier, that the grain has to overcome:

∆E B = Rmgd[ 1 + µ 2 eff -cos(ϕ sol -θ)+µ eff sin(ϕ sol -θ)] .
(1) If the moving grain has enough initial kinetic energy md 2 ( φ+ n ) 2 /2 to overcome the barrier, it gains at the end of the first step the kinetic energy:

∆E K = md 2 2 ( φ- n ) 2 -( φ+ n ) 2 , (2)
= 2Rmgd [sin(θ) -µ eff cos(θ)] sin(ϕ sol ) .

(

) 3
Up to now, we have not considered the contacts between grains within each of the two layers, leading to the nonlocal cooperative effects observed for dense granular flows. In our model, these naturally come into play during the second step of motion. Indeed, after the primary elastic collision with the (n+1) th static grain (see Fig. 1), the velocity of the considered moving grain changes suddenly, and cascades of secondary elastic collisions occur within the fluid and solid phases. This process leads to a cooperative energy reallocation that forms the essence of non-locality. Specifically, the energy transferred by the moving grain to the static grain during the primary collision is assumed to be proportional to the incoming energy, and reads amd 2 ( φn ) 2 /2, with a a constant prefactor comprised between 0 and 1. After the primary collision, the energies of the moving grain and the static grain thus temporarily become (1 -a)md 2 ( φn ) 2 /2 and amd 2 ( φn ) 2 /2, before energy reallocation. Then, cascades of secondary elastic collisions are triggered in both phases. In a minimal description, we assume that they involve: i) N flu and N sol grains in the fluid and solid phases, respectively; and ii) some energy equipartition among those grains.

For the fluid phase in particular, the energy primarily lost by the moving grain is redistributed over the N flu moving grains. Over the primary and secondary collisions, the total energy loss ∆E

0 = md 2 [( φ- n ) 2 - ( φ+ n+1 ) 2
]/2 for the moving grain thus reads:

∆E 0 = amd 2 2N flu ( φ- n ) 2 . ( 4
)
As a consequence, the ratio α = ( φ+ n+1 / φn ) 2 between the kinetic energies after and before the collisions is given by α = 1 -a/N flu , and thus represents a direct signature of cooperativity in the fluid phase. Invoking the previous relations and Eq. ( 2), one finally gets the central recursive equation:

( φ+ n+1 ) 2 = α ( φ+ n ) 2 + 2∆E K md 2 . ( 5
)
Assuming a global translational invariance in the system, and thus looking for the fixed point of Eq. ( 5), one gets ( φ+

∞ ) 2 = 2α∆E K /[md 2 (1-α)].
In this homogeneous state, during each cycle, the kinetic energy gained by the moving grain when getting down the effective potential is exactly compensated by the loss due to the subsequent collisional process, such that ∆E K = ∆E 0 . The homogeneous state is stable only if the associated kinetic energy

E ∞ K = md 2 ( φ+ ∞ ) 2 /2 = α∆E K /(1 -α)
, set by Eq. ( 3), is larger than the barrier ∆E B , set by Eq. ( 1), giving a limiting condition :

α 1 -α ∆E K (θ sed , R) = ∆E B (θ sed , R) , (6)
which determines the sedimentation angle θ sed (R). If θ < θ sed , the lowest layer (at least) of the fluid phase stops, and R decreases.

A similar reasoning allows us to discuss erosion. Considering the solid phase now, the energy amd 2 ( φn ) 2 /2 gained by the static grain at the solid-fluid interface after the primary collision is then redistributed over the N sol static grains through the cascade of secondary elastic collisions. In the homogeneous state, and over one complete cycle of motion and collisions, the solid phase receives a global energy amd 2 ( φ-∞ ) 2 /2 = N flu ∆E K . Invoking the energy equipartition among the N sol grains, the static grain at the solid-fluid interface thus receives an overall net kinetic energy N flu ∆E K /N sol , set by Eq. (3). The homogeneous state is stable only if this kinetic energy remains smaller than the energy required to drive the static grain into motion, given by the energy barrier ∆E B (θ, R + 1), set by Eq. ( 1). The limiting condition:

N flu N sol ∆E K (θ ero , R) = ∆E B (θ ero , R + 1) , (7)
determines the erosion angle θ ero (R). If θ > θ ero , the highest layer (at least) of the solid phase starts to flow, and R increases. The right-hand-side term of Eq. ( 7) represents the absolute value of a cohesion energy per grain of the solid phase, at the solid-fluid interface. For the dry granular assembly considered here, only solid friction and geometry control the cohesion of the solid phase. However, other binding mechanisms may be implemented in the model, such as capillary forces for wet granular matter [START_REF] Saingier | Accretion dynamics on wet granular materials[END_REF]. In an extreme case, the static grains can even be glued, as in inclined-plane experiments [START_REF] Pouliquen | Scaling laws in granular flows down rough inclined planes[END_REF].

To solve Eqs. ( 6) and ( 7), we need to specify further N sol and N flu , and thus the shape and size of the cooperative regions in each phase. In the bulk, we assume a cooperative region of either phase to contain ξ grains and to have a fractal dimension D. Therefore, its typical length scale is given by ∼ ξ 1/D . When the thickness of a phase becomes smaller than ξ 1/D , the cooperative regions of this phase are altered by the boundaries and the bulk description should be modified. In a heap-flow configuration, the solid phase is deep enough to ensure that N sol = ξ. In contrast, for the fluid phase, the fluidair interface acts as a free-volume reservoir which is expected to truncate the neighbouring cooperative regions. At small R/ξ 1/D , the number of grains in the cooperative regions of the fluid phase thus becomes ∼ ξ 1-1/D R, while at large R/ξ 1/D it saturates to ξ. To interpolate these two limiting behaviours, we propose the following Ansatz: N flu (R) = ξ 1 -exp -R/ξ 1/D . It should be noted that the precise functional form defining N flu (R) is not crucial, as other expressions produce similar results (see Supplementary Materials). The key point here is that N flu first increases with R before saturating.

With the above expressions for N sol and N flu , the evolutions of θ sed and θ ero can be computed by solving numerically Eqs. ( 6) and [START_REF] Kamrin | Non-locality in granular flow: Phenomenology and modeling approaches[END_REF]. There are five relevant dimensionless parameters in the model: µ eff , ϕ sol , a, ξ, and D. The coefficient a was estimated to be close to 0.5 [START_REF] Quartier | Dynamics of a grain on a sandpile model[END_REF], while the effective friction coefficient is fixed to µ eff = tan(20 • ), and ϕ sol spans the range [23.4 • , 30 • ] [START_REF] Albert | Maximum angle of stability in wet and dry spherical granular media[END_REF]. Thus, ξ and D are the only free parameters. As shown in Fig. 2, θ sed and θ ero rapidly decrease as R increases over a typical length scale ∼ ξ 1/D , before saturating at two different values for thick fluid phases. In the latter limit, the sedimentation angle appears to be close to arctan(µ eff ), while the erosion angle is clearly above. These two curves define sedimentation and erosion, and collectively determine the phase diagram for a flowing layer of grains atop a static one. Below the θ sed (R) curve, the flow is unstable. Indeed, the moving grains at the solid-fluid interface do not have enough kinetic energy to overcome their effective potential barrier (see Fig. 1). Therefore, the thickness of the fluid phase decreases continuously and full sedimentation eventually occurs. Above the θ ero (R) curve, the energy transmitted from the fluid phase to the solid one through collisions is sufficient for the barrier (i.e. cohesion) energy of the static grains at the solidfluid interface to be overcome. Therefore, the thickness of the fluid phase increases continuously and full erosion eventually occurs. In between these two curves, there is neither sedimentation nor erosion, and the flow can thus be considered as stable, i.e. stationary.

To test the predictions of the model, one should ideally investigate the flow stability for experiments or numerical simulations with various (θ, R) sampling the three domains of the phase diagram. Unfortunately, for practical reasons, it is difficult to design such tests. Indeed, finitesize heap-flow experiments involve a continuous injection of grains at the top and their removal at the bottom. In this context, the fluid-phase thickness R(Q) and heap an-gle θ heap (Q) self-adjust to the incoming flux Q of grains, until a stationary state is reached -but they cannot be controlled independently. In practice, one thus only has access to a unique relation θ heap (R). Nevertheless, by building the initial heap with a sufficiently large angle, e.g. near 90 • , one can enforce the system to start far up in the erosion domain. Subsequently, erosion occurs freely until the stationary zone is reached. The system is then expected to spontaneously stabilise at the upper limit of the stationary zone, i.e. at the erosion limit, thus allowing for a practical determination of θ ero (R).

In order to probe the sedimentation limit, the inclinedplane configuration [START_REF] Pouliquen | Scaling laws in granular flows down rough inclined planes[END_REF][START_REF] Silbert | Granular flow down an inclined plane: Bagnold scaling and rheology[END_REF][START_REF] Borzsonyi | Avalanche dynamics on a rough inclined plane[END_REF][START_REF] Malloggi | Nonlocal effects in sand flows on an inclined plane[END_REF][START_REF] Kamrin | Nonlocal modeling of granular flows down inclines[END_REF] is particularly relevant. Therein, the solid phase is made of a single layer of grains glued on the incline, and is thus not erodible (i.e. the right-hand-side cohesion energy in Eq. ( 7) becomes infinite). The central observable is the stop angle θ stop , defined as the minimal tilt angle of the substrate for which a stationary flow is observed. As discussed above for the model, when the angle of the solid-fluid interface is below θ sed (R), the lowest layer of the fluid phase stops and R reduces by one unit. Based on the homogeneous picture provided by Fig. 2, and in particular the monotony of θ sed (R), the system is then expected to remain in the sedimentation domain. The sedimentation front thus propagates upwards in the granular assembly, until the whole system is stopped. From this qualitative picture, the stop angle should be identified to the sedimentation one, thus allowing for a practical determination of θ sed (R).

According to the previous considerations, we performed DEM numerical simulations for the two canonical experimental configurations: heap and inclined plane (see Fig. 3). The same microscopic parameters, i.e. the same grains and friction coefficient, were used (see Supplementary Materials for technical details). As shown in Fig. 2, the DEM numerical results for the two different configurations, together with the previously-reported experimental results for the inclined-plane configuration [START_REF] Pouliquen | Scaling laws in granular flows down rough inclined planes[END_REF], are in quantitative agreement with the model predictions for identical parameters, under the proposed identifications: θ heap θ ero and θ stop θ sed . The best-fit values of the two free parameters are D = 0.94 and ξ = 4.7, which suggest chain-like cooperative regions of a few grains and might be related to the force-chain network in static granular contact [START_REF] Geng | S Footprints in Sand: The Response of a Granular Material to Local Perturbation[END_REF][START_REF] Majmudar | Contact force measurements and stress-induced anisotropy in granular materials[END_REF].

The model having been corroborated by experiments and numerical simulations, we now turn to a detailed discussion of the phase diagram in Fig. 2. First, sedimentation and erosion appear to be different processes, characterized by distinct angles, such that θ sed (R) < θ ero (R). Therefore, stationary flows may exist for a continuum of angles ranging between these two disjoined boundaries. Interestingly, this opens a gap within the BCRE picture [START_REF] Bouchaud | Hysteresis and Metastability in a Continuum Sandpile Model[END_REF], in which a single neutral angle θ * accounted for both the sedimentation and erosion processes. Besides, this may allow one to reconsider the previous suggestion of a friction coefficient depending on the fluid-layer thickness R -that was made to rationalise the observations in the framework of a single neutral angle [START_REF] Aradian | Surface flows of granular materials: a short introduction to some recent models[END_REF][START_REF] Douady | On granular surface flow equations[END_REF]. Secondly, the validated decays of θ sed and θ ero with R are direct consequences of both the energy-equipartition and cooperativity-truncation ingredients in the model. Indeed, an increase of R implies that more grains of the fluid phase can share the energy losses due to the collisions with the static layer, which renders flow and erosion easier i.e. requiring smaller angles. Surface flow in yielded athermal granular media thus appears to be inhibited by the truncation of cooperativity -as opposed to surface flow in ideal supercooled liquids at equilibrium [START_REF] Salez | Cooperative strings and glassy interfaces[END_REF]. Thirdly, the saturations of θ sed (R) and θ ero (R) at large R are consistent with experimental observations showing that the flow properties of thick granular layers are independent of the fluid-phase thickness [START_REF] Andreotti | Granular Media: Between Fluid and Solid[END_REF][START_REF] Pouliquen | Scaling laws in granular flows down rough inclined planes[END_REF].

In conclusion, we built a novel microscopic model involving friction, geometry, and nonlocal collisional effects, in order to describe erosion and sedimentation processes in dense granular flows atop static granular layers. As previously assumed [START_REF] Bouchaud | A model for the dynamics of sandpile surfaces[END_REF][START_REF] Bouchaud | Hysteresis and Metastability in a Continuum Sandpile Model[END_REF][START_REF] Boutreux | Surface flows of granular materials: A modified picture for thick avalanches[END_REF], we have shown that ero- sion and sedimentation processes at the solid-fluid interface strongly depend on the interfacial angle. In contrast to previous work, our model suggests that each process might have its own critical angle, which depends on the fluid-layer thickness. The increase of both the erosion and sedimentation angles as the fluid-layer thickness decreases could be rationalised by considering two antagonist effects. Indeed, a decrease of R not only produces a lowering of the gravitational and thus frictional constraints for the moving grains at the solid-fluid interface, but induces as well a diminution of the size of the cooperative region in the fluid phase. This latter truncation mechanism impedes energy reallocation after collisional energetic losses, and dominates for small fluid-layer thicknesses. From our model, two classical experimental configurations -inclined plane and heap -usually analysed separately, could be described within a unified picture. A central outcome of our approach is a single phase diagram. Therein, the erosion and sedimentation limits were found to be in close agreement with numerical and past experimental measurements, of the heap and stop angles in inclined-plane and heap configurations respectively. These new results might be useful in the design of hydrodynamic models for dense granular flows, such as the BCRE scheme and depth-averaged method [START_REF] Edwards | Erosion-deposition waves in shallow granular free-surface flows[END_REF].

This work benefited from financial support by the Fonds National de la Recherche Scientifique (FNRS, PDR research project T.0109.16 "Capture biomimétique de fluide" and CDR project J.0191.17 "Mimicking elasticity with viscous fluids"), and by the Action de Recherche Concertée (UMONS, research project "Mecafood"). D. D. acknowledges funding from FNRS through the Foundation for Training in Industrial and Agricultural Research. The authors also thank Yacine Amarouchene, Fabian Brau, and Paul Rambach for fruitful discussions.

FIG. 2 .

 2 FIG.2. The θ-R phase diagram. Ensemble of results from: i) DEM simulations in two canonical configurations of granular flows, i.e. inclined plane (θstop) and heap (θ heap ) ; ii) inclined-plane results (θstop)[START_REF] Pouliquen | Scaling laws in granular flows down rough inclined planes[END_REF] ; and iii) predictions (θero, θ sed ) from the model through solutions of Eqs. (6) and (7). In the model, the fixed parameters are µ eff = tan(20 • )[START_REF] Pouliquen | Scaling laws in granular flows down rough inclined planes[END_REF], a = 0.5[START_REF] Quartier | Dynamics of a grain on a sandpile model[END_REF], and ϕ sol ∈ [23.4 • , 30 • ] (see light purple and light orange regions in the diagram) [16], and the two adjustable parameters are ξ = 4.7 and D = 0.94. The horizontal dashed line indicates θ = arctan(µ eff ), and the vertical one indicates R = 1.

FIG. 3 .

 3 FIG. 3. Snapshots of the DEM simulations for two canonical configurations of granular flows: (top) heap flow with fixed flow rate; (bottom) inclined-plane flow with fixed angle and thickness. The colour maps refer to the velocity of the grains, as indicated in the scale bar.