Analysis of Inhibitors to Implementing Digital Supply Chain in Saudi Arabia: An Interpretive Structural Modeling (ISM) Approach

Digitalization of supply chain management has contributed to revolutionary changes and challenges for firms and countries. Digital supply chain (DSC) has deployed the usage of innovative digital technologies such as big data and the Internet of things to build a strong competitive advantage for firms and a comparative advantage for countries. The successful implementation of DSC in Saudi Arabia requires organizational and institutional prerequisites. This chapter aims to identify and analyze the main inhibitors of DSC adoption in the Saudi context. This research consists of a two-phased approach. In the first phase, we conducted interviews with ten Saudi logistics experts and executives to explore their opinions on the most important inhibitors. The identification of different structural variables is based on existing literature and experts’ opinions. In the second phase, we opt for an interpretive structural modeling (ISM) using matrix of cross-impact multiplications applied to classification (MICMAC) analysis, to classify inhibitors according to their influence, dependence, and driving power. This contribution could help Saudi policymakers, logistics managers, and executives to recognize the classification order of inhibitors to overcome them and to outline a blueprint for effective deployment of digital supply chain in Saudi Arabia.