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http://hdl.handle.net/10362/163821| Título: | When do firms learn? |
| Autor: | Vendrell-Herrero, Ferran Gomes, Emanuel Darko, Christian K. Lehman, David W. |
| Palavras-chave: | F14 F60 Great convergence Great divergence Home market economic development Learning-by-exporting M16 N10 O12 Organizational learning World Bank Enterprise Survey Business, Management and Accounting(all) Economics and Econometrics SDG 8 - Decent Work and Economic Growth |
| Data: | Jan-2025 |
| Resumo: | Organizational learning begins with experience. However, it remains an open question whether firms learn from a particular type of experience: exporting. This study aims to speak into this debate by examining when learning by exporting occurs. Our core thesis is that the timing of learning by exporting depends on a firm’s home market economic development. Drawing on classic theories of organizational learning, we posit that firms in more developed home markets will enjoy greater opportunities for learning before exporting whereas firms in less developed home markets will enjoy greater opportunities for learning after exporting. The former will be observed as a divergence in productivity among firms from different home markets, whereas the latter will be observed as convergence over time. The proposed hypotheses were tested and supported using longitudinal data from the World Bank Enterprise Survey. A range of theoretical and practical contributions are discussed. |
| Descrição: | Funding Information: The authors are grateful to Esteban Lafuente, two anonymous reviewers, and attendants to the online paper development workshop for their insightful comments and suggestions during the review process. Ferran Vendrell-Herrero and Emanuel Gomes acknowledge financial support by the Spanish State Research Agency (SRA), Ministry of Science and Innovation (Reference: PID2022-136235NB-100). Funding Information: Emanuel Gomes acknowledges financial support from Fundação para a Ciência e a Tecnologia (UID/ECO/00124/2019, UIDB/00124/2020 and Social Sciences DataLab, PINFRA/22209/2016), POR Lisboa and POR Norte (Social Sciences DataLab, PINFRA/22209/2016), and David Lehman acknowledges research support from the University of Virginia. Publisher Copyright: © The Author(s) 2024. |
| Peer review: | yes |
| URI: | http://hdl.handle.net/10362/163821 |
| DOI: | https://doi.org/10.1007/s11187-024-00898-z |
| ISSN: | 0921-898X |
| Aparece nas colecções: | NSBE: Nova SBE - Artigos em revista internacional com arbitragem científica |
Ficheiros deste registo:
| Ficheiro | Descrição | Tamanho | Formato | |
|---|---|---|---|---|
| s11187-024-00898-z.pdf | 802,1 kB | Adobe PDF | Ver/Abrir |
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