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Mentoring : Could There Also Be Caveats in It?
No full textInternational audienceMentoring has long been viewed as an effective tool for human resource development. This paper challenges the mainstream view that mentoring is unequivocally beneficial to organizations and by extent to the wider social system. The argument is built on four caveats that emerge from the available literature: (1) evidence on the relationship of mentoring receipt with protégé job performance (as opposed to career success) is elusive; (2) the mechanism via which mentoring enhances protégé career success appears to rely mostly on power and political processes; (3) the type of learning imparted by mentoring seems mostly related to the understanding and implementation of political tactics for personal gain; and (4) the possibility that mentoring may, at times, impair protégés' ethos and lower their ethical standards. The conclusion is that caution – instead of unconditional enthusiasm – must be exercised with mentoring. The article closes with guidelines for practice and suggestions for future research, which can serve as starting points in the adoption of a more balanced view of mentoring.<br /
Regime-aware conditional neural processes with multi-criteria decision support for operational electricity price forecasting
No full textThis work integrates Bayesian regime detection with conditional neural processes for 24-hour electricity price forecasting in the German, French, and Norwegian markets. Regimes are inferred via a disentangled sticky hierarchical Dirichlet process hidden Markov model (DS-HDP-HMM). For each regime, an independent conditional neural process (CNP) learns localized mappings from input contexts to 24-dimensional hourly price trajectories; final forecasts are produced as regime-weighted mixtures of the regime-specific CNP outputs. Temporal robustness and cross-market generalization are evaluated on Germany (2021–2023) and on France and Norway (2023). We benchmark against deep neural networks (DNN), the Lasso estimated autoregressive (LEAR) model, extreme gradient boosting (XGBoost), Bayesian long short-term memory (BLSTM), and the temporal fusion transformer (TFT), and assess downstream value through battery storage optimization. Results indicate that the proposed regime-aware CNP often delivers higher profits or lower costs, while DNN can be exceptionally competitive in specific cost-minimization settings. Because point accuracy does not necessarily translate into operational optimality, we apply the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to aggregate forecasting and operational criteria. TOPSIS ranks the CNP as the leading model for 2023 and, overall, as the most balanced and consistently preferred solution across the considered markets
Le droit des données mortes-vivantes : des incohérences au service d'un idéal de cohérence ?
No full textCette contribution analyse le cadre juridique des données post-mortem au sein de l’Union européenne et met en évidence une double incohérence, à la fois législative et pratique. En l’absence d’harmonisation européenne, les États membres ont adopté des solutions hétérogènes, générant une insécurité juridique ainsi que des difficultés concrètes pour les utilisateurs, les ayants droit et les plateformes numériques à Cette situation est aggravée par la diversité des pratiques mises en place par les acteurs privés, notamment les réseaux sociaux, en matière de gestion des comptes après le décès à. S’inscrivant dans une approche dynamique du droit, l’étude montre que ces incohérences constituent une phase transitoire vers un cadre plus cohérent. Elle plaide en faveur d’un scénario fonctionnel consistant à étendre le RGPD aux données des personnes décédées, accompagné de la création d’un registre européen unique des directives post-mortem, afin de renforcer la sécurité juridique et la lisibilité du système
When green isn't enough: How AI and compliance reframe energy efficiency for sustainable investment
No full textInternational audienceAs technological advancements, artificial intelligence (AI), and climate change become increasingly intertwined, energy efficiency has emerged as a crucial issue for organizations and public authorities. This research examines how firms can align financial and environmental goals to attract diverse investor groups, focusing on AI-driven energy efficiency strategies. To do so, we use the Economies of Worth framework and explore how investors respond to energy strategies framed by financial or environmental motivations (i.e., market or green worlds), depending on the type of AI adopted and the nature of compliance. Across four experimental studies with 1,500 investors, we find that environmental motivations can reduce investor willingness to invest, mediated by perceived energy efficiency. However, AI implementation and certification mechanisms act as critical boundary conditions that can legitimize environmental strategies and enable compromise between market and green logics. Specifically, coupling environmental motivations with AI for energy efficiency and third-party certification leads to higher investor willingness to invest. This study contributes to sustainable investment research by highlighting the critical role of AI and compliance in building hybrid justifications that can facilitate alignment between environmental and financial priorities in investor decision-making.</div
Corporate social responsibility as a signal in the labor market
No full textInternational audienceWorking for a firm engaged in Corporate Social Responsibility (CSR) appeals to potential workers by boosting their self-image and sense of purpose. We propose an additional mechanism: CSR signals a firm's future treatment of workers. Our model links CSR engagement with a firm's propensity to support workers during unforeseen times of need. Under this assumption, a potential future need of the worker leads to more firms engaging in CSR and to a higher workers' willingness to accept lower wages. Our experiment manipulates potential future needs across treatments. While the aggregate analysis does not fully support our theory, exploratory analysis reveals that male workers respond as predicted, whereas female workers do not. Consistently, in a risky environment, male employers increase their CSR engagement, which raises the acceptance rate among male workers. These results do not hold for female employers and workers.</div
The Role of Heterogeneous Robots: Operating Policies of Warehousing Systems With the Lift Robot and Ground Robot Collaboration
No full textInternational audienceRecently, heterogeneous robots have been adopted in the same warehouse to enhance flexibility and improve system efficiency. Our paper is inspired by a novel heterogeneous robotic warehouse system, namely the lift robot and the ground robot collaborative (LRGR) warehousing system. In the LRGR system, lift robots store and retrieve totes on single deep storage racks. Meanwhile, ground robots transport totes between lift robots and workstations, navigating both the aisles and the space beneath the racks. The performance of an LRGR system is predominantly determined by its operational policies, especially the dwell point and junction point policies that regulate the interactions between lift and ground robots. We propose a fork-join queueing network to assess the performance of LRGR systems under various collaboration policies. An improved matrix-based approximation method is proposed to solve the model. The accuracy of the analytical models is verified by simulation. Our numerical experiments show that implementing the service completion junction point policy in combination with the service completion dwell point policy significantly boosts system efficiency and reduces energy consumption. Our model can provide new perspectives on effective collaboration policies for heterogeneous robotic systems
Platform Choice and Resource Configuration: From the Perspective of Resource Dependence
No full textInternational audienceIn the digital economy, platforms are central to value creation by connecting users and coordinating exchanges. For small and medium-sized enterprises (SMEs), deciding whether to build their own platform or join an existing one entails balancing autonomy and dependence. While Resource Dependence Theory (RDT) explains how firms manage tangible, intangible, and human resources, it overlooks the growing importance of data in platform ecosystems. To address this gap, we conducted a qualitative multiple-case study of 12 Chinese SMEs across four platform ecosystems, based on 54 semi-structured interviews and archival data. We identified four mechanisms of resource dependence, including tangible, intangible, human, and data, that shape SMEs’ platform strategies. Our results reveal that concerns over dependence, rather than resource scarcity, primarily drive platform choices, and that data dependence introduces a novel socio-technical dimension to RDT. The study extends RDT by distinguishing data from traditional intangible resources, developing a configuration model of platform choice, and revealing interaction effects among different types of dependence. Practically, it guides SMEs in evaluating platform participation risks and informs platform developers on governance mechanisms that alleviate dependence concerns, thereby enriching Information Systems research on how digital resource configurations shape strategic decisions in data-driven contexts
Blockchain traceability valuation for perishable agricultural products: Balancing economic benefit and social impact
No full textInternational audienceThe adoption of blockchain-enabled traceability systems in agricultural supply chains offers farmers a means to reduce demand uncertainty. However, downstream retailers gain full visibility into product freshness, enabling selective purchases that may inadvertently increase food waste. This study evaluates the impact of such a traceability system by analyzing agricultural supply chain transactions under two scenarios: with and without blockchain implementation. By comparing order quantities and farmer profits in both cases, we find that blockchain adoption can enhance product sales because the smart contract effect. We also find that blockchain adoption can either amplify the bullwhip effect when circulation time is short or mitigate it when circulation time is long. The interaction between the bullwhip effect and the smart contract effect impacts the farmer’s profit. The farmer achieves higher profits using the blockchain-enabled traceability system if the smart contract effect outweighs the bullwhip effect. Furthermore, adoption costs play a crucial role in determining feasibility. Beyond economic implications, blockchain-enabled traceability systems also influence social outcomes, particularly in reducing food waste. Our analysis reveals four possible outcomes based on economic benefits and social impact: (i) win-win (higher profits and reduced waste), (ii) win-lose (higher profits but increased waste), (iii) lose-win (lower profits but reduced waste), and (iv) lose-lose (lower profits and increased waste). The likelihood of each outcome is strongly dependent on product shelf life—longer shelf life increases the probability of a win-lose scenario, while shorter shelf life raises the likelihood of a lose-win outcome. Win-win and lose-lose scenarios remain the least probable
The Emerging Structure of Impact Investing: Principles, Participation and Policy
No full textInternational audienceImpact investing has evolved from a niche orientation into a sophisticated field that seeks to generate measurable social and environmental outcomes alongside financial returns. Yet despite its rapid growth, the field remains marked by epistemic instability: impact is difficult to define and to measure, a ambiguity that ultimately undermines the legitimacy and credibility of impact investing. This paper articulates a comprehensive synthesis drawing from the GIIN’s State of the Market 2025 and Data, Direction and Decisions reports, the OECD’s guidance on impact measurement, the OECD’s analysis of ESG ratings, the GIIN/HSF briefing on EU sustainable finance policymaking, and the FAIR 2024 Guide pratique: Investissement à impact. Across these sources, an interesting architecture emerges in which impact investing is best understood as a hybrid institutional field, shaped by three interdependent forces: a stakeholder-centred social approach to value creation, the pursuit of data standardisation, and the institutionalisation of sustainability through regulation. Building on this architecture, the paper first clarifies the conceptual foundations of impact investing, then examines its relational and socially embedded nature, before analysing the methodological tensions of measurement and finally the regulatory dynamics shaping the field
National Identity Salience Increases Trust in National Products via Ingroup Bias and Collective Self-Esteem
No full textNational identity salience exerts a significant impact on national product consumption. Despite its importance, it is noteworthy that no prior research has examined how national identity salience influences trust in national products or the underlying psychological mechanisms. The present research addresses this gap by demonstrating that national identity salience increases trust in national products via the serial mediation of ingroup bias and collective self-esteem. Departing from prior work that has primarily focused on cross-cultural comparisons, we tested the proposed effects across four studies conducted within a single cultural context (i.e., the U.S.), thereby contributing to the international marketing literature from a within-culture perspective. Specifically, Studies 1a and 1b establish a positive causal relationship between national identity salience and trust in national products, which, in turn, shapes purchase intention toward national products. Study 2 tests the mediating role of ingroup bias, and Study 3 examines the serial mediation effects of ingroup bias and collective self-esteem. Companies producing national products may leverage these insights by strategically priming national identity in their communication efforts to strengthen trust and enhance sales