M@n@gement

Rethinking Responsibility in Organization and Management Research

Pierre-Jean Barlatier — 2026-03-16

Ethical Considerations in Algorithm Construction: Evidence from Two Human-Resources Algorithms

Clotilde Coron — 2025-11-05

Organizations increasingly rely on algorithms for decision-making, which raises significant ethical issues. In this paper, we provide a detailed case study of the development and deployment of two human resources (HR) algorithms in a major French digital company. Our findings show that these ethical issues reflect the ethical considerations of the various stakeholders involved in the process, including data scientists, HR practitioners, and legal experts. We discuss how these considerations intervene during the decision-making process in algorithm design and usage, offering insights for both academics and practitioners into how ethical issues are approached by different actors.

Proximity-Based Antecedents of Agricultural Producers’ Motivations and Commitment to Adopt Local Distribution Channels: The Case of Normandy in France

Marie-Laure Baron — 2025-11-24

The integration of local distribution channels (LDCs) by agricultural producers plays a crucial role in regional sustainability and economic development. However, the determinants of producers’ motivations and commitment remain underexplored. This study addresses this gap by applying proximity theory to assess the antecedents influencing Norman producers’ engagement in LDCs. Through an empirical study in Normandy (France), we examine perceived cognitive, social, institutional, organizational, and geographical proximities to determine their relative impacts on producers’ commitment and motivations. Our findings reveal that these are significantly driven by cognitive, social, and institutional proximities, whereas geographical and organizational proximities, although relevant, are less important. Producers engage in LDCs primarily to exchange knowledge, collectively improve their offerings, and contribute to local development rather than being driven by purely economic incentives. This research provides a holistic, quantitative framework for understanding producers’ motivations and commitment, challenging conventional assumptions centered on geographic and organizational proximities. Offering both theoretical and managerial contributions, the proposed predictive model applies to various regional contexts. Meanwhile, decision-makers in Normandy can draw on these insights to develop policies that strengthen producer engagement in LDCs and promote more sustainable food systems.

Interplay of Human and Structural Capital Signals for New Technology Ventures in Early-Stage Venture Capital Funding

Arnauld Bessagnet — 2026-02-27

By drawing on the socio-cognitive perspective of signalling theory, this study examines how the interplay of human and structural capital signals may be associated with early-stage venture capital (VC) funding for new technology ventures. Using a dataset of 453 French new technology ventures operating in the digital industry, the findings reveal that strong signals such as patents or trademarks enhance firm legitimacy, while weaker signals such as education level or degrees from elite institutions reinforce team credibility. Both types of signals are positively correlated with early-stage VC funding. However, the results indicate that combining signals of the same dimension and strength yields diminishing returns because additional within-dimension signals are informationally redundant, add little new information about legitimacy or credibility, and lower the likelihood of funding. In noisy, information-saturated contexts, overlapping signals create redundancy and investor cognitive overload rather than facilitating decision-making. This study advances signalling theory by framing signal interactions as a strategic portfolio choice, and outlines implications for entrepreneurial research, investor decision-making, and future work on signalling strategies.

Unravelling the Rationales behind Business Model Innovation for Sustainable Value

Gaëlle Cotterlaz-Rannard — 2026-02-27

Despite recent research clarifying some of its core constructs, business model innovation (BMI) literature still lacks conceptual consistency, particularly regarding the architecture that articulates the mechanisms of value creation, delivery, and capture at the individual, organizational, value network, and societal levels of analysis. In response to recent research calling for the identification of BMI rationales, we draw on a systematic literature review to unravel how the rationales underlying the strategic choice to adopt BMIs shape and align the multilevel mechanisms that result in distinct coherent BMI architectures. Our contributions are twofold: first, we provide scholars with further conceptual consistency for BMI as well as new research avenues by identifying three main BMI architectures: (1) rational sympathy-based, (2) rational commitment-based, and (3) rational egoism-based. Second, this research provides a diagnostic and guiding tool to help managers select and align mechanisms within a cohesive BMI architecture to generate more sustainable value at various levels.

How to Make Open Innovation Work Better? Leverage Your Competitors

Henry Chesbrough — 2026-02-16

Corporate open innovation initiatives involving start-ups often fail to deliver the expected results. Such failure is due in part to the behavior of individuals within corporate business units. Specifically, we examine the notion of ‘not invented here syndrome’ (NIHS), a behavioral bias that leads employees to reject external innovations, thus hindering collaboration with promising start-ups. This paper explores how corporations can overcome individuals’ NIHS, thus collaborate more effectively with external start-ups. Our research, which is based on an in-depth case study of Telefónica, confirms that NIHS can be the result of a lack of information on start-up promises, use cases, and viability. We identify a three-step organizational routine that can help mitigate NIHS in the process of evaluating external start-ups: (1) referring external start-ups to competitors, (2) monitoring competitors’ collaboration with start-ups, and (3) diffusing this additional information with the aim of shifting individuals’ decision-making by reducing their reliance on behavioral biases against external start-ups. Our findings extend the behavioral theory of the firm by demonstrating that the organizational routines implemented to offset individual biases can involve external actors rather than being limited to internal processes. We also contribute to open innovation by revealing that bringing the knowledge possessed by outside start-ups into the organization is insufficient in isolation to ensure adoption; external perspectives on those start-ups provide a second opinion to the organization that may offset internal NIHS biases.