Alireza ASGARI

Composition of the Jury

Abstract

The resilience of the agri-food supply chain (AFSC) is essential in the face of a growing global population, its inherent vulnerabilities, and the constant threat of disruptions. The use of cutting-edge technologies can counter the uncertainty caused by disruptions in the AFSC. Among these technologies, big data analytics (BDA)—which is capable of processing increasingly complex and voluminous data—has demonstrated its potential to strengthen resilience. Therefore, in this literature-based thesis, we aim to: first, explore the multifaceted concept of resilience in the AFSC to identify the capabilities and practices that constitute AFSC resilience at the organizational, supply chain, and industry levels through a systematic literature review (SLR). Next, systematically review the literature in which BDA has been used in various AFSC processes to enable resilience in order to understand the state of the art. Based on the two SLRs, third, draw on the dynamic capabilities perspective to highlight the role of the micro-foundations of the BDA in strengthening AFSC resilience capabilities through a comprehensive multiple-case study in the food distribution sector, in addition to proposing an innovative system architecture integrating descriptive, predictive, and prescriptive analyses. Finally, explore the cause-and-effect relationship and calculate the weights of socio-ecological resilience capacities to identify the most influential and significant resilience capacities, which led to the creation of a method for evaluating the micro-foundations of baseline data analysis in order to reach a consensus on the essential practices of baseline data analysis that foster resilience.