Artikel

From adaptive to generative learning in small and medium enterprises-a network perspective

Organizational learning has been playing an important role for competitive advantages for the organization. Managing learning and change in the unique context of small and medium enterprises (SMEs) can obtain benefits from network alliance. The paper seeks to draw attention to learning approaches from adaptive learning to generative learning in a SME in the context of asymmetric learning relationship. A qualitative research is conducted on a towing company of Taiwan with 14 in-depth interviews on persons of strategic alliances. This study discusses an asymmetric learning relationship where a large enterprise dominates the central place of the network, decides the learning policies and practices and guides learning involving adaptive and generative learning. This case of the SME assumes adaptive learning to ensure the development of network capability and adopts generative learning through communication channels and resources provided by the central firm. The outcomes of generative learning are the enhancement of absorptive capacity, the transfer of knowledge, shared identities, and shared contextual understanding in the towing industry. Though acquiring generative learning development, the case of the SME gets a competitive advantage but chooses to stay small and to be a business owner. This situation meets the psychological needs of the Chinese people.

Sprache
Englisch

Erschienen in
Journal: Journal of Global Entrepreneurship Research ; ISSN: 2251-7316 ; Volume: 6 ; Year: 2016 ; Issue: 6 ; Pages: 1-12 ; Heidelberg: Springer

Klassifikation
Management

Ereignis
Geistige Schöpfung
(wer)
Li, Chao-Hua
Ereignis
Veröffentlichung
(wer)
Springer
(wo)
Heidelberg
(wann)
2016

DOI
doi:10.1186/s40497-016-0054-y
Handle
Letzte Aktualisierung
10.03.2025, 11:43 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • Li, Chao-Hua
  • Springer

Entstanden

  • 2016

Ähnliche Objekte (12)