Artificial intelligence as an enabler of agri-food supply chain resilience

Supply chain organisations have endured increasing levels of pressure in recent years due to unprecedented levels of uncertainty. These issues are exacerbated for agri-food supply chain (AFSC) organisations, as they are faced with meeting demanding food production targets (United Nations, 2022), while combating issues such as limited farmland, reduction of natural resources, and climate change (Spanaki et al., 2021). While disruptions are costly for all supply chain organisations due to the perishable nature of agri-food products, disruptions pose a significant concern for AFSC organisations as disruptive events cause products to edge closer to expiry, adding to unintentional food loss and cost of production. Hence, developing the capability to minimise the impact of disruptive events is crucial for AFSC organisations. Therefore, this doctoral research aims to examine the potential of AI as an enabler of AFSC resilience. Five research questions were outlined to achieve this overarching research objective, which was achieved through four studies. Study 1A conducts a systematic literature review focussing on understanding the applications, challenges, and benefits of AI in supply chain research. AI and supply chain research is largely fragmented into streams based on different types of AI technologies across several supply chain contexts and through varying disciplinary perspectives. Study 1A is the first review to synthesise this fragmented body of knowledge, giving direction to both researchers and practitioners. Study 1B is a practitioner-focused paper that combines the outputs of Study 1A, in addition to data collected from 147 AFSC respondents, to provide an insight into the view of AFSC practitioners on AI applications. Study 1B extends the findings of Study 1A, giving this research a strong understanding from both literature and industry on AI's applications, challenges, and benefits in the AFSC industry. Collectively, this provides a foundation to guide the remainder of the studies conducted in this doctoral research. In Study 2, this research provides empirical evidence on AI and SCR. Drawing on organisational information processing theory, this research provides a novel perspective to understanding how AFSCs can deploy AI-based information processing, utilising organisational mindfulness (OMIN) and organisational flexibility (OLFEX) to build resilient supply chains. Furthermore, Study 3 extends the research model proposed in Study 2 by drawing on dynamic capability theory to empirically test AI assimilation as an enabler of SCR under the moderating effect of environmental dynamism. pg. 9 Collectively, these studies make specific and distinguishing contributions to AI and supply chain research and practice. Study 1A contributes to the accumulative building of knowledge by extending theoretical discourse about the specificities of AI for prescriptive analytics to enable SCR. Study 2 is among the first empirical studies to draw on organisational information processing theory to examine AI-based information processing for developing AFSC resilience as well as the mediation effects of OFLEX and OMIN on this relationship; therefore, addressing the lack of theoretical development and understanding how AI-enabled information processing affects SCR (Belhadi et al., 2021), particularly in the context of AFSCs. Moreover, Study 3 is among the first to draw on dynamic capability theory to examine the impact of AI assimilation on SCR as well as the mediation effects of OMIN and OLFEX on this relationship. This is a considerable contribution to AI literature, as it provides a theoretical basis and empirical evidence of the importance of organisational competencies for leveraging AI technologies to improve SCR. In terms of practical implications, this research helps decision-makers gain a better understanding of AI and its applications, specifically, how AI can be leveraged to develop SCR. Study 1A proposed a strategic AI resilience framework to support supply chain decision- makers and enhance the use and value of prescriptive analytics as an enabler to developing a resilient supply chain. Studies 2 and 3 demonstrate the important role of OMIN and OFLEX for AFSC managers seeking to use AI technologies to develop SCR. This implies that the employment of AI technologies to promote SCR requires managers to adopt the principles and practices of OMIN and OFLEX. Besides illustrating the importance of developing resilience for performing successfully in the turbulent environment that AFSCs operate in, this research also demonstrates that developing resilience can enhance AFSC performance and be a source of competitive advantage, giving further reasoning to AFSC managers to develop SCR.

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University of Galway

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Attribution-NonCommercial-NoDerivatives 4.0 International

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University of Galway Theses (PhD Theses)