Percorrer por autor "Silva, Bruno C."
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- Entrepreneurship and the gig economy: a bibliometric analysisPublication . Silva, Bruno C.; Moreira, AntonioThere is an increasing number of academic publications on studying the impact of the gig economy and digital platforms. Some of them involve entrepreneurship and business models. However, there is a lack of a global picture depicting the scientific structure of knowledge regarding the gig economy and entrepreneurship. This paper presents a conceptual, intellectual, and social bibliometric overview, using Bibliometrix and Biblioshiny (R-packages). To this end, total of 345 published articles were analyzed, covering 245 sources, 44 countries and 751 authors. There are several important findings: five main clusters emerged from the study (Self-employment and social economy; Sharing economy and sustainable development; Entrepreneurship and innovation; Gig economy and platform economy; and Digitalization); the main themes that emerge deal with sharing, gig, and platform economy, digitalization, teleworking, career participation and platforms; finally, gig workers are key for developing strategies, policies, and actions to achieve a social welfare through entrepreneurship in the platform ecosystem. It is also important to highlight the role of communities and social capital in the development of sustainable collaborative initiatives through digital entrepreneurship.
- The role of passion and self-efficacy in entrepreneurial activities in the gig economy: an unsupervised machine learning analysis with topic modelingPublication . Silva, Bruno C.; Moreira, AntonioThis research examines passion and self-efficacy through experience and knowledge, as motivational factors that support entrepreneurs within the gig economy (GE). It sheds light on entrepreneurs’ sources of passion in the GE literature. The sample is composed of all the 1164 entrepreneurship activities offered worldwide through Airbnb, Tour by Locals, and Withlocals on 5 May 2022. The study is supported by unsupervised machine learning models and seeks to find latent topics emerging from the analysis of the entrepreneurs’ descriptions and exposes the main correlated clustered dimensions. There are six main motivators behind GE platforms as a first step toward entrepreneurship: Experience, Passion for share, Knowledge, Classic traditions, Empowered community and local activities, and Well-being. It also confirms the correlation between passion and self-efficacy through experience, pointing them as main factors behind entrepreneurship in the GE. Five of the six sources of passion previously pointed by theory were found: Passion for growth, for people, for product/service, for innovation and for social mission. This study discloses self-efficacy and the sources of passion and points directions to practitioners involved in entrepreneurial activities in the GE ecosystem. This work used machine learning models to access quantitatively a paradigm that is inductive by nature. The results point to well-being as a significant factor to be addressed in future research regarding entrepreneurship. This research only studies individuals involved in the GE; as such, further studies should cohort new populations from different fields.