Sectoral resilience through learning in networks and GVCs: A historical perspective on the food-processing and clothing industries in Poland

Deniz E. Yoruk, Esin Yoruk, Paulo N. Figueiredo and Andrew Johnston

Technological Forecasting and Social Change, 2023, vol. 192, issue C

Abstract: This paper investigates how inter-organizational learning in networks and global value chains (GVCs) has contributed to resilience in Poland's food processing and clothing industries. The Polish economy has been widely accepted as resilient since Poland's transition from a planned to a market economy. Through drawing on the regional resilience literature, this paper develops a network-oriented framework of sectoral resilience that integrates network evolution, inter-organizational learning in networks, and the role of history. It uses unique primary data from the period of Poland's abovementioned transition (1989–2001), which is complemented with secondary data on the networking activities of Polish firms in the two abovementioned sectors between 2004 and 2018. In turn, the firms' interactive learning is found to function as an important contributor to their path-dependent network trajectories and resilience. Moreover, knowledge networks and GVCs present different dynamics in terms of their effects on learning and result in uneven sectoral resilience. Learning from knowledge spillovers and by interacting with the co-existence of adaptation- and adaptability-related network characteristics has guided both the studied sectors towards developing short-term adaptive capacity for path-extension and sustainability. Learning from advanced science and technology (S&T) and education regarding exclusive adaptability-related network characteristics has driven Poland's food-processing industry's path-evolving long-term capability to be fully resilient.

Keywords: Networks; Global value chains; Inter-organizational learning; Resilience; Adaptability; Adaptation; Low and medium technology sectors (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:192:y:2023:i:c:s0040162523002202

DOI: 10.1016/j.techfore.2023.122535

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