Increase Supply Chain Performance by Addressing Knowledge Governance, Resilience Capabilities, and Risks: Empirical Evidence from the Agri-Food Industry
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Agri-food supply chain (AFSC) are becoming more complex due to the prevalent of lean strategy, a higher rate of innovation, and customer preference towards high quality and fresh agri-food products. AFSC can operate smoothly and efficiently in stable business environments but are highly vulnerable to various risks and uncertainties. Knowledge is a vital resource for firms to survive and to achieve sustainability and profitability in the dynamic and volatile business environment. However, according to author’s knowledge, little research has been conducted to explore the interactions among knowledge governance mechanisms (KGMs), AFSC resilience capabilities, AFSC risks, and AFSC performance. KGMs are defined as the different mechanisms for sharing, integrating, interpreting and applying know-what, know-how, and know-why embedded in individuals, groups and other source of knowledge. This study aims to investigate the direct impact of KGMs on AFSC performance and the indirect impact through resilience capabilities and risks by using a multi-method qualitative approach. The research aim can be achieved through investigating different KGMs that can be used for managing knowledge, investigating different resilience capabilities that can be used for building AFSC resilience, investigating different risks that exist in the AFSCs, as well as investigating different key performance indicators (KPIs) that can be used for measuring AFSC performance. The empirical study has been conducted in three phases. Phase one of the empirical study, semi-structured interviews were conducted with experienced AFSC practitioners from Argentina, France, Italy, and Spain, followed by thematic analysis to analyse data. As a result, themes related to KGMs, AFSC resilience capabilities, AFSC risks, and AFSC KPIs were identified. Then, TISM (Total Interpretive Structural Modelling) was used to build relationships among the constructs (e.g., KGMs, AFSC resilience capabilities, AFSC risks, and AFSC KPIs). Thus, the relations among the four constructs were defined. Phase two of the empirical study, structured interviews were conducted with experienced AFSC practitioners to collect data. Then, prioritising of resilience capability factors and risk factors was conducted through a combination of TISM and fuzzy MICMAC (Impact Matrix Cross-reference Multiplication Applied to Classification) analysis. TISM was used to build interrelationships among different AFSC resilience capability factors and among different AFSC risk factors, respectively, through allocating different factors into different layers. Fuzzy MICMAC analysis was employed to categorise different AFSC resilience capability factors and different AFSC risk factors into different categories, respectively. The research results indicate that extreme weather conditions and political and economic instability have the highest driving power and are located at the lowest level in the TISM hierarchy. These risks have an increased tendency to disturb the whole flow of AFSC and so should be managed effectively. Furthermore, the research results also indicate that leadership should be given critical focus for building AFSC resilience, as it locates in the lowest level in the TISM hierarchy. In the research evaluation phase, structured interviews were conducted in Chile to evaluate the research results obtained through empirical research phase one and two. All statements rated relatively positive, indicating that respondents highly agree with the elements and relationships identified in the empirical findings. This study has a number of theoretical contributions. Firstly, it provides empirical evidence in identifying elements for building KGMs, AFSC resilience capabilities, AFSC risks, and AFSC KPIs. Secondly, it provides empirical evidence that KGMs have positive effects in enhancing AFSC performance and in improving AFSC resilience capabilities. Thirdly, it prioritises AFSC resilience capability factors and risk factors through building interrelationships among them using TISM and categorising them using fuzzy MICMAC analysis. This study provides practical guidance for helping AFSC practitioners to strengthen knowledge sharing/transfer, build AFSC resilience capabilities, reduce AFSC risks, and improve AFSC performance.
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