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on Entrepreneurship |
| By: | Drydakis, Nick (Anglia Ruskin University) |
| Abstract: | This study investigates the relationship between social vulnerability, illegal activities, and location-based business disruptions in Athens, the capital of Greece. The research utilises repeated cross-sectional data from 2008, 2014, and 2023, gathered from areas with high levels of criminal activity, reflecting the experiences of business owners and managers in these locations. The findings reveal that heightened levels of social vulnerability—including the presence of illicit drug users and homeless individuals—alongside illegal activities such as gang-related protection rackets and black-market operations, are associated with increased location-based business disruptions. These disruptions manifest in assaults on employees and customers, business burglaries, reputational damage, supply chain problems, and decreased turnover. The study also examines the impact of economic conditions in 2014 and 2023, when Greece's Gross Domestic Product was lower than in 2008, indicating an economic recession. The findings suggest that the economic downturn during these years further exacerbated location-based business disruptions. Conversely, enhanced public safety measures, such as increased police presence, law enforcement, and improved public infrastructure, were associated with a reduction in these disruptions. Furthermore, an interesting insight was that businesses with longer operating histories tend to experience fewer location-based disruptions, indicating that operating history might be perceived as a resilience factor. The study suggests that policy actions should focus on increasing police visibility, providing financial support to high-risk businesses, funding urban regeneration projects, maintaining public infrastructure, and delivering social services aimed at helping marginalised communities escape vulnerability. |
| Keywords: | social vulnerability, illegal activities, crime, criminality, business, entrepreneurship, business disruptions, economic recessions, public safety |
| JEL: | K4 K42 L26 I3 E32 |
| Date: | 2024–09 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp17321 |
| By: | Ruochen Dai (†Central University of Finance and Economics); Dilip Mookherjee (Boston University); Kaivan Munshi (Yale University and Toulouse School of Economics); Xiaobo Zhang (Peking University and IFPRI) |
| Abstract: | This research examines the determinants of entrepreneurship in China’s transition from agriculture to domestic production in the 1990’s and the subsequent transition to exporting in the 2000’s. The model that we develop and test to describe these transitions incorporates a productivity enhancing role for community (birth county) networks, which emerge in response to market imperfections at early stages of economic development. Using administrative data covering the universe of registered firms over the 1994-2012 period and the universe of exporters over the 2002-2012 period, we provide causal evidence that these networks of firms were active and were effective at increasing the revenues of their members, both in domestic production and exporting. While this substantially increased the number of domestic producers in the first stage, the incumbent domestic networks created a disincentive to enter exporting in the second stage that dominated the positive effect of the export networks. Our analysis provides a novel characterization of the development process in which community-based networks emerge at each stage to facilitate the occupational mobility of their members, and pre-existing networks slow down the growth of the networks that follow. |
| Date: | 2024–09 |
| URL: | https://d.repec.org/n?u=RePEc:cwl:cwldpp:2406 |
| By: | Fabrice Gilles; Yannick L'Horty; Ferhat Mihoubi |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:tep:teppwp:wp24-07 |
| By: | Mathieu Le Moal (UM - Université de Montpellier, UPVM - Université Paul-Valéry - Montpellier 3); Roy Thurik (Montpellier Business School, Erasmus University Rotterdam); Olivier Torrès (UM - Université de Montpellier) |
| Abstract: | Contexte : Les entrepreneurs sont souvent confrontés à des niveaux élevés de stress, d'anxiété et d'épuisement en raison de la nature exigeante de leurs activités professionnelles. Par conséquent, la récupération du stress lié au travail est une activité cruciale pour eux. Le Recovery Experience Questionnaire (REQ) est une échelle auto-rapportée de 16 items largement utilisée, couvrant quatre facteurs de récupération : le détachement psychologique du travail, la relaxation, la maîtrise et le contrôle. Cette étude porte sur la validation d'une version française du REQ. Méthodes : Un total de 1 043 entrepreneurs français provenant de divers secteurs a participé à cette étude. La cohérence interne et les corrélations ont été examinées pour évaluer les propriétés psychométriques de la version française du REQ. Une analyse factorielle confirmatoire (AFC) a été utilisée pour valider la structure à quatre facteurs du REQ, avec l'ajout de sept covariances d'erreur pour améliorer l'ajustement du modèle. Résultats : La version française du REQ a montré une bonne cohérence interne (détachement psychologique : α = 0, 88, relaxation : α = 0, 91, maîtrise : α = 0, 90, contrôle : α = 0, 91). L'AFC a confirmé la structure à quatre facteurs avec les données suivantes : RMSEA = 0, 071 (IC 95 % [0, 066, 0, 077]), CFI/TLI = 0, 955/0, 950, SRMR = 0, 050 et χ² (108) = 593, 861, p < 0, 001. Des corrélations significatives ont été trouvées entre les scores du REQ et des indicateurs de santé tels que le stress, la solitude, la santé physique, la santé mentale et la qualité du sommeil. Les résultats confirment que le REQ est une mesure valide et fiable pour évaluer les expériences de récupération chez les entrepreneurs français. Conclusion : Nous concluons que le REQ est une mesure valide et un outil utile pour la recherche sur la santé générale des entrepreneurs. De plus, la version française validée du REQ peut être appliquée à d'autres populations professionnelles, ce qui en fait un instrument polyvalent pour évaluer la santé et la récupération dans divers contextes professionnels. Pour soutenir cette affirmation, nous avons mené la même analyse de validation sur un échantillon de 1 231 employés agricoles français, démontrant à nouveau que le REQ est une mesure valide et fiable pour évaluer les expériences de récupération. |
| Keywords: | Expérience de récupération France Santé Stress Analyse factorielle Validation d'échelle Entrepreneur Psychométrie Frontiers in Psychology frontiersin.org, Expérience de récupération, France, Santé, Stress, Analyse factorielle, Validation d'échelle, Entrepreneur, Psychométrie Frontiers in Psychology frontiersin.org |
| Date: | 2024–10–02 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-04714547 |
| By: | Cheikh T. Ndour (Dakar, Senegal); Simplice A. Asongu (Johannesburg, South Africa) |
| Abstract: | This study aims to investigate the effect of fear of failure on entrepreneurship intent. It utilises survey data from the Global Entrepreneurship Monitor (2015) conducted in Senegal. Analysing a sample of 2364 individuals, the probit model was employed, revealing three key findings. Firstly, fear of failure significantly diminishes entrepreneurship intent. Secondly, individuals who are partially employed demonstrate a heightened inclination towards entrepreneurship. Thirdly, fear of failure consistently impacts entrepreneurship intent regardless of gender. A key policy implication of this research is the necessity to address discrimination in policies designed to support individuals with greater entrepreneurial aspirations. |
| Keywords: | Entrepreneurship intent, probit, occupation, gender, Senegal |
| JEL: | L26 J29 J16 C25 O55 |
| Date: | 2024–01 |
| URL: | https://d.repec.org/n?u=RePEc:exs:wpaper:24/032 |
| By: | Nigar Karimova |
| Abstract: | The research investigates how the application of a machine-learning random forest model improves the accuracy and precision of a Delphi model. The context of the research is Azerbaijani SMEs and the data for the study has been obtained from a financial institution which had gathered it from the enterprises (as there is no public data on local SMEs, it was not practical to verify the data independently). The research used accuracy, precision, recall and F-1 scores for both models to compare them and run the algorithms in Python. The findings showed that accuracy, precision, recall and F- 1 all improve considerably (from 0.69 to 0.83, from 0.65 to 0.81, from 0.56 to 0.77 and from 0.58 to 0.79, respectively). The implications are that by applying AI models in credit risk modeling, financial institutions can improve the accuracy of identifying potential defaulters which would reduce their credit risk. In addition, an unfair rejection of credit access for SMEs would also go down having a significant contribution to an economic growth in the economy. Finally, such ethical issues as transparency of algorithms and biases in historical data should be taken on board while making decisions based on AI algorithms in order to reduce mechanical dependence on algorithms that cannot be justified in practice. |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2410.05330 |