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The Hidden Cost of Mandatory Unpaid Overtime: How and When Mandatory Unpaid Overtime Undermines Subsequent Motivation to Work
No full textInternational audienceIn many countries workers can be required to work extra hours for which they receive little or no remuneration. How and when such mandatory unpaid overtime affects employees' subsequent motivation to work, however, remains largely under researched. This study investigates the impact of mandatory unpaid overtime on employees' motivation to work the next day, the within‐person process (how) as well as the buffering and recovery mechanisms (when). Data on mandatory unpaid overtime, psychological detachment and motivation to work the next day were collected through diaries over a 12‐day period while the participants commented on job resources on the first day. Artificial Intelligence (AI) facial recognition technology was applied to capture emotions. Multilevel analysis revealed that mandatory unpaid overtime results in negative emotions, which subsequently undermine employees' motivation to work the next day, job resources buffer the impact of overtime on negative emotions, and psychological detachment weakens the impact of negative emotions on motivation to work the next day. Theoretical and practical implications are discussed
Gendered patterns in eWOM seeking and sharing
No full textInternational audienceThis study employs social role theory to examine gender disparities in electronic word of mouth (eWOM), specifically focusing on eWOM media. Analyzing survey data from 2092 participants, it finds that women place higher importance on eWOM in pre-purchase decisions and show stronger motivation for eWOM provision than men. Platforms more frequently utilized by women than men for eWOM activities include Facebook, Pinterest, and Instagram. Conversely, men demonstrate a greater propensity to use platforms such as Google Maps, Twitter, LinkedIn, and YouTube for eWOM-related purposes. These insights can help destination management organizations and tourism businesses tailor eWOM channels and strategies by incorporating gender differences
Adaptively aggregated forecast for exponential family panel model
No full textInternational audienceAggregation strategies, playing an important role akin to that of model selection, have been extensively studied in different statistical models to improve forecasting accuracy. However, traditional aggregated forecast strategies for panel data are mainly developed under the assumption that response variables are continuously distributed (or normally distributed). Replacing this assumption by a more general family of distributions, i.e., exponential family distributions, this paper proposes a computationally efficient way to construct the cumulative risk function and to explicitly accommodate correlation structure of within-subject observations, develops two novel adaptively aggregated forecasting strategies via exponential reweighting and quadratic reweighting, and rigorously establishes the corresponding tight oracle inequalities. The proposed exponential reweighting based strategy enjoys promising Kullback-Leibler risk bound adaptation. Moreover, under the quadratic risk, a promising adaptation property can be achieved by the quadratic reweighting based strategy. The risk bound properties of the two proposed procedures in the presence of pre-screening are established under mild conditions. The calibration properties of the proposed methods are also analyzed. Simulation studies, together with an example in analyzing television viewers' binary decision sequence of watching drama episodes, verify the superiority of our methods over existing model selection and aggregation methods.</div
Vers une masculinité entrepreneuriale écologique : étude sur des entrepreneurs profondément engagés dans la transition socio-écologique
No full textInternational audiencePurpose Recent voices have called for the need to reconsider the myth of male power based on a one-dimensional view of a dominant patriarchy in entrepreneurship. In a search for alternatives to hegemonic masculinities, this paper explores a specific context - that of radical ecological and social transition - to identify how entrepreneuring in this specific social environment questions and shapes entrepreneurial masculinities. Design/methodology/approach We engage with constructivist grounded theory to analyse 17 life story interviews of French entrepreneurs, complemented by 6 focused follow-up interviews and 2 focus groups of women to give a broader and cultural understanding of entrepreneurial masculinities. Findings The paper makes four important contributions to the literature on gender and entrepreneurship. First, it enriches the spectrum of entrepreneurial masculinities with a non-hegemonic type of masculinity, namely, caring Entrepreneurial masculinity (EM). Second, it proposes an alternative model of hybrid hegemonic masculinity by showing that the “hero” posture in entrepreneurship is not necessarily that of a winner but can also serve a mission for the common good. Third, it introduces the concept of ecological EM by bridging two distinct areas of the literature related to our data. Finally, it underscores the strong influence of women in entrepreneurs’ social environment by their role in engaging change in entrepreneurial masculinities. We show how a specific social environment can partially challenge hegemonic entrepreneurial masculinities. The paper introduces ecological masculinities as an alternative framework.Objectif Des voix récentes ont appelé à reconsidérer le mythe du pouvoir masculin fondé sur une vision unidimensionnelle d'un patriarcat dominant dans l'entrepreneuriat. À la recherche d'alternatives aux masculinités hégémoniques, cet article explore un contexte spécifique, celui de la transition écologique et sociale radicale, afin d'identifier comment l'entrepreneuriat dans cet environnement social particulier remet en question et façonne les masculinités entrepreneuriales. Conception/méthodologie/approche Nous utilisons la théorie constructiviste fondée sur des données empiriques pour analyser 17 entretiens sur le parcours de vie d'entrepreneurs français, complétés par 6 entretiens de suivi ciblés et 2 groupes de discussion composés de femmes afin d'offrir une compréhension plus large et culturelle des masculinités entrepreneuriales. Résultats L'article apporte quatre contributions importantes à la littérature sur le genre et l'entrepreneuriat. Premièrement, il enrichit le spectre des masculinités entrepreneuriales d'un type de masculinité non hégémonique, à savoir la masculinité entrepreneuriale bienveillante (EM). Deuxièmement, il propose un modèle alternatif de masculinité hégémonique hybride en montrant que la posture de « héros » dans l'entrepreneuriat n'est pas nécessairement celle d'un gagnant, mais peut également servir une mission pour le bien commun. Troisièmement, il introduit le concept d'EM écologique en reliant deux domaines distincts de la littérature liés à nos données. Enfin, il souligne la forte influence des femmes dans l'environnement social des entrepreneurs par leur rôle dans le changement des masculinités entrepreneuriales. Nous montrons comment un environnement social spécifique peut remettre en question, en partie, les masculinités entrepreneuriales hégémoniques. L'article présente les masculinités écologiques comme un cadre alternatif
Research methods for the performative and communicative study of organizing and organizations
No full textInternational audienceGuest editoria
The Role of Technical and Top Management Support in the Continuance of Intention to Use Business Analytics
No full textInternational audienceThis study investigates the impact of perceived organizational support (POS) on employees' intentions to continue using business analytics (BA) tools. By integrating Organizational Support Theory (OST) and technology adoption models, the research highlights the critical roles of technical and top management support in influencing perceived compatibility and usefulness, which drive BA continuance intentions. Data were collected between August and October 2021 from employees across various industries in Ireland, Finland, and Sweden who used BA tools in their work. Using Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze data, the findings reveal significant relationships between the organizational support types and continuance intentions, with technical support being particularly crucial for long-term use. This study extends OST by emphasizing the importance of technical support and confirms the relevance of perceived compatibility and usefulness in technology continuance
Investor Sentiment, Limits to Arbitrage, and Hard-to-Value Stocks
No full textInternational audienceAn uninformed demand shock driven by investor sentiment and limits on arbitrage jointly result in the mispricing of hard-to-value stocks in standard behavioral models. However, existing work focuses on investigating the mispricing effect of either investor sentiment or limits to arbitrage possibly due to the difficulty of empirically distinguishing proxies for limits to arbitrage from hard-to-value proxies, while assuming the other is given. This paper explicitly investigates the joint and distinct roles of investor sentiment and limits to arbitrage in the mispricing effect simultaneously in a unified empirical framework. Our results show that the existence and magnitude of a mispricing depend on whether these two factors, i.e., investor sentiment and limits to arbitrage, reinforce or undermine each other. We emphasize that both investor sentiment and limits to arbitrage are two necessary conditions for a mispricing in an empirical setting
Comparing Machine Learning and Deep Learning Techniques for Text Analytics: Detecting the Severity of Hate Comments Online
No full textInternational audienceSocial media platforms have become an increasingly popular tool for individuals to share their thoughts and opinions with other people. However, sometimes people tend to misuse social media posting abusive comments against others. Abusive and harassing behaviours can have adverse effects on people's lives. This study takes a novel approach to combat harassment in online platforms by detecting the severity of abusive comments. The study compares the performance of machine learning models such as Naïve Bayes, Random Forest, and Support Vector Machine, with deep learning models such as Convolutional Neural Network (CNN) and Bi-directional Long Short-Term Memory (Bi-LSTM). The feature set for the abusive comments was made using unigrams and bigrams for the machine learning models and word embeddings for the deep learning models. The comparison of the models’ performances showed that the Random Forest with bigrams achieved the best overall performance with an accuracy of (0.94), a precision of (0.91), a recall of (0.94), and an F1 score of (0.92). The study develops an efficient model to detect severity of abusive language in online, offering important implications both to theory and practice
Predictors of safety promotion among Brazilian part 145 repair stations: regression and social network analysis
No full textInternational audienceSafety promotion is a component of any safety management system (SMS). Safety promotion in Part 145 repair stations can prevent accidents, injuries, and other adverse outcomes by proactively addressing safety concerns and continuously improving safety performance. Along with the safety promotion SMS component, there are three more components, namely safety policy, safety risk management, and safety assurance. Further, safety promotion in Part 145 repair stations can benefit from the relationship with other Part 145 repair stations based on a social network approach. This study reveals that SMS components (namely safety policy, safety risk management, and safety assurance) and the relative position of a Part 145 repair station in the social network can predict safety promotion performance. The data indicates that four predictors (i.e., all SMS components and one social network metric) are significant in this model, and the resulting regression equation predicts 78.6 % of the variance. Part 145 repair stations and aviation agencies can benefit from the findings by implementing or recommending safety promotion policies considering these predictors
Emission reduction levels of manufacturers under carbon trading policies
No full textInternational audienceConsidering the policies surrounding carbon trading, decarbonization plans have been regarded as imperative choices for the manufacturing industry. However, there has been little research into combining the concrete carbon quota allocation methods with the low-carbon supply chain. Still, the distinction between ordinary and low-carbon manufacturers has been scarcely investigated. To fill these gaps, drawing on two quota allocation methods—grandfathering and benchmarking, we model the supply chains under two production modes, which consists of an ordinary manufacturer, a low-carbon manufacturer and a hybrid manufacturer. Our primary conclusions are listed here. The carbon emission reduction level (CERL) shall fluctuate within an acceptable scope to prevent adverse consequences on total social welfare. Additionally, independent of the production mode, manufacturers' profits will peak when the gross carbon quotas meet certain values under grandfathering. Meanwhile, under benchmarking, the environmental performance and consumer surpluses are better when the benchmark quota reaches a certain value