HAL - Audencia Group
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HOW DOES LATE-CAREER ENTREPRENEURSHIP RELATE TO INNOVATION?
No full textInternational audienceIn this paper, we present an explorative study that develops our understanding of the relationship between late-career entrepreneurship and innovation-driven business activity. Based on observations of 2,903 solo founders of new ventures in Germany in 2008-2017, we offer first and robust evidence that late-career entrepreneurs (~50 years and above) are more likely than younger founders to introduce product/service innovations that are 'new to the market'. Our explorations specifically reveal that older founders who draw on personal financial resources and combine their innovation orientation with prior managerial experience are most likely to generate the types of innovations that bring new products or services to the market. We conclude by discussing how our study's insights contribute to the research agenda on innovations in late-career entrepreneurship
Understanding the use of digital technologies in entrepreneurial start-up settings and growth-oriented firms
No full textInternational audienc
Perceived prevalence of misinformation fuels worries about COVID-19: a cross-country, multi-method investigation
No full textInternational audienceData suggests that the majority of citizens in various countries came across 'fake news' during the COVID-19 pandemic. We test the relationship between perceived prevalence of misinformation and people's worries about COVID-19. In Study 1, analyses of a survey across 17 countries indicate a positive association: perceptions of high prevalence of misinformation are correlated with high worries about COVID-19. However, the relationship is weaker in countries with higher levels of case-fatality ratios, and independent from the actual amount of misinformation per country. Study 2 replicates the relationship using experimental data. Furthermore, Study 2 demonstrates the underlying mechanism, that is, perceived prevalence of misinformation fosters the belief that COVID-19 is spiralling out of control, which in turn, increases worries. Our findings suggest that perceived prevalence of misinformation can have significant psychological effects, even though audience members reject the information as being false
The use of choline chloride for salt reduction and texture enhancement in bread
No full textInternational audienceCereal products, and in particular bread, are the main source of salt in human diets. However, salt is a critical ingredient in breadmaking, and its reduction can have a negative impact on bread quality. In order to respond to the World Health Organization (WHO)’s recommendation to reduce dietary salt intake, this research aims to develop a bread recipe "reduced" in salt (sodium chloride or SC) by -50 % and partly substituted by choline chloride (CC). The effect of CC on the properties of bread was studied during baking, cooling and storage of bread. It was observed that partially substituting SC with CC led to an improvement in bread texture. Indeed, CC bread was technologically similar to the control bread. In aqueous solution, CC behaves like an ionic liquid and causes a reorganization of the internal structure of the starch grain. As a result, the staling study highlighted the positive effect of CC on bread texture and on the starch retrogradation. CC limited amylopectin recrystallization by reducing water availability in the medium, consequently slowing down the staling of the bread
Negative signals on Peer-to-Peer platforms: The impact of cancellations on host performance across different property types
No full textInternational audienceScholars investigated the factors enhancing Airbnb hosts’ performance; however, less research focused onnegative signals, such as host cancellation messages. Cancellations are a negative signal that conspicuously revealsthe number of times a host has canceled a pre-existing reservation. Drawing upon signaling theory and productinvolvement, we argue that cancellation signals have a negative impact on host occupancy, but this impact ismoderated by the level of involvement associated with the accommodation type (i.e., private room, shared room,entire apartment). The study used a dataset of 31,778 reviews of 6384 Airbnb listings. The results show thataccommodation type moderates the relationship, that is, the impact of cancellations is stronger for higherinvolvement accommodations (entire apartment) versus low involvement ones (shared rooms). This study advances the literature on negative signals and helps P2P managers understand the impact of cancellations on theirrevenues
L’hétérogénéité des investisseurs institutionnels et la détention d’actifs liquides : Effet modérateur du contrôle familial
No full textInternational audienceCette étude se propose d’étudier l’effet de la présence des investisseurs institutionnels (II) sur le niveau de détention d’actifs liquides dans un contexte d’actionnariat familial. Les résultats empiriques révèlent que les II ayant un horizon d’investissement à long terme et une importante participation au capital sont plus à mêmes de contrôler et limiter l’accumulation d’actifs liquides. Cependant, un comportement d’investissement passif de la part de ces II conduit les dirigeants à privilégier leurs intérêts privés et d’extraire ainsi des rentes à partir de l’accumulation des liquidités. Les résultats montrent également que le contrôle familial peut modérer l’activisme institutionnel et amplifier en contrepartie la passivité de ces investisseurs. En effet, les entreprises familiales peuvent privilégier une coalition de contrôle avec les II passifs pour faciliter l'expropriation des intérêts des actionnaires minoritaires et affaiblir le pouvoir des II actifs
How can big data and predictive analytics impact the performance and competitive advantage of the food waste and recycling industry?
No full textInternational audienceBig data and predictive analytics (BDPA) techniques have been deployed in several areas of research to enhance individuals’ quality of living and business performance. The emergence of big data has made recycling and waste management easier and more efficient. The growth in worldwide food waste has led to vital economic, social, and environmental effects, and has gained the interest of researchers. Although previous studies have explored the influence of big data on industrial performance, this issue has not been explored in the context of recycling and waste management in the food industry. In addition, no studies have explored the influence of BDPA on the performance and competitive advantage of the food waste and the recycling industry. Specifically, the impact of big data on environmental and economic performance has received little attention. This research develops a new model based on the resource-based view, technology-organization-environment, and human organization technology theories to address the gap in this research area. Partial least squares structural equation modeling is used to analyze the data. The findings reveal that both the human factor, represented by employee knowledge, and environmental factor, represented by competitive pressure, are essential drivers for evaluating the BDPA adoption by waste and recycling organizations. In addition, the impact of BDPA adoption on competitive advantage, environmental performance, and economic performance are significant. The results indicate that BDPA capability enhances an organization’s competitive advantage by enhancing its environmental and economic performance. This study presents decision-makers with important insights into the imperative factors that influence the competitive advantage of food waste and recycling organizations within the market
Design for multi-material 4D printing: Development of an algorithm for interlocking blocks assembly generation
No full textInternational audience4D printing involves smart materials (SMs) that can respond to stimulation energy by changing their shape/property. Current advances in digital materials require addressing heterogeneous (multi-material deposition) 4D printing to attain targeted shapechanges. However, innovative structures embedding inert and SMs simultaneously are yet difficult to build. To overcome this challenge, we propose a genuine computational design approach addressed to heterogeneous additive manufacturing (AM). The main idea is to resort to an efficient algorithm capable of converting a computed digital multi-material distribution in a voxel-based 3D/4D structure to interlocking blocks intended to be printed separately with different AM techniques and then assembled
Making sense of renouncing: A typology of types, motives, and approaches to renouncing at work
No full textInternational audienceIn this paper, we provide an exploratory account of the experience of renouncing at work-giving up a work-related aspiration. Despite the importance of the phenomenon, the conceptualization of renouncing has been overlooked by the literature. Taking a narrative sensemaking approach to renouncing, we document variance in individual experiences to renouncing, that is, how they subjectively understand what, why, and how they renounce at work. Through a qualitative approach, we investigate the case of 30 academics working in three French business schools characterized by an increasingly influential managerialist "publish or perish" regime, a context conducive to renouncing. Based on our findings identifying various experiences of renouncing, we inductively build a matrix and a model connecting six experiences of renouncing based on the type of renouncing (renouncing in order to succeed vs. renouncing success itself) and how people approach renouncing (suffered, accepted, or chosen renouncing)
Explainable AI for Operational Research: A Defining Framework, Methods, Applications, and a Research Agenda
No full textInternational audienceThe ability to understand and explain the outcomes of data analysis methods, with regard to aiding decision-making, has become a critical requirement for many applications. For example, in operational research domains, data analytics have long been promoted as a way to enhance decision-making. This study proposes a comprehensive, normative framework to define explainable artificial intelligence (XAI) for operational research (XAIOR) as a reconciliation of three subdimensions that constitute its requirements: performance, attributable, and responsible analytics. In turn, this article offers in-depth overviews of how XAIOR can be deployed through various methods with respect to distinct domains and applications. Finally, an agenda for future XAIOR research is defined