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on Project, Program and Portfolio Management |
| By: | Ingrid Mazzilli (LEST - Laboratoire d'Economie et de Sociologie du Travail - AMU - Aix Marseille Université - CNRS - Centre National de la Recherche Scientifique); Héloïse Berkowitz (LEST - Laboratoire d'Economie et de Sociologie du Travail - AMU - Aix Marseille Université - CNRS - Centre National de la Recherche Scientifique); Sihem Mammar El Hadj (EGEI - Éthique et Gouvernance de l’Entreprise et des Institutions - UCO - Université Catholique de l'Ouest, GRANEM - Groupe de Recherche Angevin en Economie et Management - UA - Université d'Angers - Institut Agro Rennes Angers - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement) |
| Abstract: | Localization is the process of adapting and developing international aid to suit local contexts. Thus, localization involves paying attention to the relations between organizations and local actors receiving development aid. One key question that has not, as yet, been satisfactorily answered is how to collectively organize localization to empower local actors. Through an in‐depth case study of an innovative development aid project in Senegal focusing on employment and skills ecosystems, this paper explores the impact of viewing localization as a meta‐organized process on discussions about localization going forward. Our findings unpack the dynamics and processes of sustainable localization in development aid through a place‐based and multi‐stakeholder meta‐organization. We show that this process is supported by intermediation work , carried out by a group of actors acting as transition intermediaries, who support the emergence of a shared vision during a collective project and enable sustainable collaborative transition dynamics to be engaged. Our results also highlight that the intermediation work happens in three sequences: (1) emerging localization; (2) intermediated localization; and (3) transformative intermediated localization. We contribute to the literature by highlighting that intermediation work is made possible through a set of key functions played by the meta‐organization: (1) place direction‐setting; (2) capacity mobilization; and (3) ecosystem orchestration. |
| Keywords: | place-based, Senegal, sustainable practices, meta-organization, localization, development aid |
| Date: | 2025–11–20 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05381707 |
| By: | Anna Nesvijevskaia (ISI 4C - HEG - Haute Ecole de Gestion de Genève, HEG - Haute Ecole de Gestion de Genève) |
| Abstract: | This paper explores the perpetuation of practitioners' tacit knowledge in the context of projects aimed at designing Artificial Intelligence (AI) uses in organizations. By comparing an interdisciplinary review of the state of the art on tacit knowledge with an observational field study of 7 application cases in France and Switzerland, this article sheds light on the dynamics of capturing practitioners' tacit knowledge during the design and operation of AI models and highlights three areas for consideration: (1) the emergence of new devices for translating practitioners' know-how into data models and capturing tacit knowledge through the maieutic carried out in the design phase, (2) the difficulty of taking unconscious tacit knowledge into account when judging AI in use, revealing issues of interpretability, cognitive bias and trust, and (3) the capture of knowledge, including tacit knowledge, as the primary goal of Data Science projects. But this capture may not be desired by the practitioners or even introduce an intermediation that prevents the development of further tacit knowledge derived from real-life experience in favour of that linked to the use of AI. These considerations lead to the improvement of tacit knowledge perpetuation devices, as long as their legitimacy is justified, and the risks are mitigated. |
| Abstract: | Cet article explore la pérennisation des savoirs tacites des acteurs métier dans le cadre des projets visant la conception d'usages d'Intelligence Artificielle (IA) dans les organisations. À travers la confrontation entre un état de l'art interdisciplinaire sur les savoirs tacites et un terrain d'observation de 7 cas d'application en France et en Suisse, cet article met en lumière les dynamiques de capture des savoirs tacites des acteurs métier lors de la conception et de l'exploitation des modèles IA et révèle trois pistes de réflexion : (1) l'émergence de nouveaux dispositifs de traduction des connaissances métier en modèles de données et de capture de savoirs tacites à travers la maïeutique réalisée en phase de conception, (2) la difficulté à tenir compte des savoirs tacites inconscients dans l'évaluation de l'IA à l'usage, révélant des enjeux d'interprétabilité, de biais cognitifs et de confiance, et (3) la capture des savoirs, y compris tacites, comme finalité première de projets de science de données au service de leur pérennisation. Mais cette capture peut ne pas être souhaitée par les acteurs métier, voire introduire une intermédiation empêchant le développement ultérieur de leurs savoirs tacites issus de l'expérience du réel au profit de ceux liés à l'usage de l'IA. Ces pistes mènent au perfectionnement des dispositifs de pérennisation de savoirs tacites, à condition de justifier leur légitimité et de maitriser des risques de dérives. |
| Keywords: | Information Behaviour, Trusted AI, Tacit Knowledge, Knowledge Management, Data Science Project, Artificial Intelligence, Interdisciplinarity, Skills, Human Resources, Comportement Informationnel, IA de Confiance, Ressources Humaines, Compétences, Interdisciplinarité, Intelligence Artificielle, Science de données, Gestion des connaissances, Savoirs tacites |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05413113 |
| By: | Ingvil Gaarder; Morten Grindaker; Tom G. Meling; Magne Mogstad |
| Abstract: | We test for and measure green waste: the misallocation of public subsidies for green investment projects. Our context is a major Norwegian program for green investment subsidies. We develop a model of subsidy allocation and apply it to detailed project-level data on carbon emissions and subsidy amounts for both marginal and inframarginal projects. We find that decision-makers could have achieved the same level of emission reductions at less than half the cost. To isolate the sources of this green waste, we use data on both ex-ante expected and ex-post realized emission reductions for each project. We find that decision-makers are able ex-ante to identify the projects with the highest ex-post emission reductions but unwilling to select them. |
| JEL: | D61 H23 Q48 Q54 Q58 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34649 |
| By: | Cherbonnier, Frédéric; Gollier, Christian; Pommeret, Aude |
| Abstract: | Standard evaluations of public policies involve discounting the flow of expected net benefits at a unique discount rate. Consequently, they systematically ignore the insurance benefits of policies that hedge the aggregate risk, and the social cost of projects that raise the aggregate risk. Normative asset pricing theory recommends adjusting the discount rate to the project’s risk, but few countries have attempted to implement this complex solution. We explore the equivalent "stochastic discount factor" approach based on the expected value of its state-contingent NPV, using the relevant state-contingent Ramsey discount rate. Under our "stress discounting" approach, projects are evaluated under two polar risk-free economic scenarios, one business-as-usual scenario, and one low-probability catastrophic scenario. Inspired by the recent asset pricing literature on macro catastrophes, we show that this approach adequately values assets’ risk premia under a minimal, intuitive, and operationally simple departure from the standard risk-free approach with a unique discount rate. We carry out benchmarks to check the accuracy of this approach, then apply it to value a nuclear waste disposal. |
| Keywords: | Project valuation; stochastic discount factor; rare disasters; cost-benefit analysis;; social discounting |
| JEL: | G12 H43 Q54 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:tse:wpaper:131203 |
| By: | Dang, Ruirui; Badole, Sachin B.; Towe, Charles; Heintzelman, Martin D. |
| Abstract: | This study uses data from a discrete choice experiment in the northeastern U.S. to examine resident preferences for siting wind and solar energy projects. It explores the impacts of landscape, agricultural production, cooperation, and financial compensation to stakeholders. Findings suggest that households are more favorable to renewable energy development if subsidies are provided on their electricity bills. Key factors influencing decisions include visual impact, proximity, and community engagement. Payments to landowners and communities also play a significant role in shaping local support and acceptance. Our study further reveals considerable heterogeneity in preferences. Respondents demonstrated overall support for wind or solar farm development in their local community, though preferences differed among various demographic and attitudinal groups, with the average respondent willing to be compensated $88 less in their base electric bill. |
| Keywords: | Resource/Energy Economics and Policy |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ags:aaea25:361208 |
| By: | Martin, Lisandro; Leguia Alegria, Juan Jose; Han, Ze |
| Abstract: | This paper examines whether project restructuring improves World Bank project performance. Using panel data on Implementation Status and Results ratings, it combines two-way fixed effects with the PanelMatch estimator to address concerns that restructurings are endogenously timed. Restructurings consistently raise Implementation Status and Results ratings, and these gains persist across successive reporting cycles. Timing and scope both matter: early restructurings generate durable improvements, while late interventions yield shorter-lived boosts bounded by project horizons. Level I restructurings produce larger effects than Level II adjustments. These patterns show that adaptation works best when it is timely and substantive. More broadly, restructuring should be viewed not as a reactive correction but as an ordinary mechanism of adaptive management—a structured learning process that transforms performance signals into actionable design updates, reinforcing institutional flexibility and credible mid-course correction. |
| Date: | 2026–01–09 |
| URL: | https://d.repec.org/n?u=RePEc:wbk:wbrwps:11289 |