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Generative Mechanisms for Scientific Knowledge Transfer in the Food Industry

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  • Karla Zimpel-Leal

    (CIRCLE, Faculty of Social Sciences, The University of Sheffield, Sheffield S10 2TN, UK)

  • Fiona Lettice

    (Norwich Business School, University of East Anglia, Norwich NR4 7TJ, UK)

Abstract

This paper investigates the generative mechanisms for scientific knowledge transfer in the food industry, addressing the sustainability of knowledge transfer projects related to health, safety and regulation. Different levels of analysis examine structure, agency and interactions within a multilevel framework. The main research questions are: (1) what are the key generative mechanisms within science–industry knowledge transfer? and (2) what are the implications of these mechanisms to policy? This research applies explaining-outcome process-tracing by investigating different knowledge transfer projects, utilising empirical data from 52 in-depth interviews with food scientists and food SMEs, 17 supporting documents and 16 observations. Systematic combining is used to develop a narrative from empirical data, where the evidence leads to the formation of the most plausible explanation. This is followed by the abstraction of mechanisms which are then matched to a suitable theoretical framework. The results from the study show a range of predominant mechanisms that drove scientific knowledge transfer including nonpecuniary incentives, reputation, opportunity, instrumental rationality, self-interest, strategic calculation, aggregation, learning and adaptive self-regulation. The overall conclusion is that the construction of relationships based around social norms, autonomy and relatedness are more dominant than those focused on financial incentives or transaction cost theories.

Suggested Citation

  • Karla Zimpel-Leal & Fiona Lettice, 2021. "Generative Mechanisms for Scientific Knowledge Transfer in the Food Industry," Sustainability, MDPI, vol. 13(2), pages 1-23, January.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:2:p:955-:d:482707
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    1. Han-Wen Tuan & Kuo-Chen Hung & Gino K. Yang, 2021. "Inventory Model with Fixed Shelf Life under Generalized Non-Increasing Demand," Mathematics, MDPI, vol. 9(21), pages 1-15, October.

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