Assessing IoT challenges in supply chain: A comparative study before and during- COVID-19 using interval valued neutrosophic analytical hierarchy process

Abstract

Although the Internet of Things (IoT) has spawned a new breed of smart factories within supply chains, the latest pandemic has ushered in unparalleled supply chain disturbances. Following the challenges identified in the literature, we interview top experts to evaluate the significance of these challenges. We apply a multi-criteria decision analysis (MCDA) tool, analytical hierarchy process (AHP) in combination with interval-valued neutrosophic numbers (IVN). The critical part of this research is that we also perform a comparative analysis by focusing on before- and during- the pandemic periods individually to better assess the impact of the latest pandemic on the IoT challenges. Our study also includes a comprehensive, systematic literature review to bring the readers up-to-date.

Introduction

The world has been going through COVID-19 pandemic, anxiously waiting for vaccination to be completed. As scientists have developed vaccines in record time, the heat is now on for the supply chains for the delivery. The urgency of the production and logistics of billions of jabs to be distributed worldwide has put the supply chain performance under the spotlight. In the wake of the age of digitalization and heavy computer usage, a new era of further-digitized and interconnected large-scale machine-to-machine (M2M) networks have been revolutionized the supply chains (SC). These M2M information exchanges, known as the Internet of Things (IoT), have connoted the fourth industrial revolution, also known as Industry 4.0 (i4.0). The pandemic has disrupted SCs going through this revolutionary transition to i4.0 even further.

There is an echo of recent literature heralding a great wave of disruption taking place. i4.0, also known as Industrial Internet of Things (IIoT) has been spawning a new breed of real-timecapable smart factories (Kiel, Arnold, & Voigt, 2017). The automatic capture of data with sensors, making them accessible to authorized entities both internally and externally, using data analytics for advanced processes securely go beyond digitalization (Ben-Daya, Hassini, & Bahroun, 2019). These capable factories, hallmarked by IoT, laden with the state-of-the art such as smart sensors and big data analytics, buttressed by law and administration are restructuring the traditional ways of manufacturing. While autonomous standalone factories with smart-capabilities are essential, the literature insists that all processes in SCs must be digitalized, integrated, and automated to realize i4.0 (Bauer et al., 2015, Hofmann and Rüsch, 2017, Tjahjono et al., 2017). Despite the rapid growth of IIoT research, IIoT’s merits on supply chains are frequently surmised, and its implications are often misidentified (Müller, Kiel, & Voigt, 2018).

Most manufacturing companies are oblivious to the extent to which their organization will be impacted by IIoT absorption. Even though the research on IIoT technologies consistently underlines their potential benefits (Moeuf et al., 2020, Prause, 2019, Raj et al., 2020, Whitmore et al., 2015), the extant literature also posits uncertainties such as, but is not limited to, the managerial (Birkel and Hartmann, 2020, Tu, 2018), environmental (Wang & Wang, 2017), or social uncertainties of IIoT (Shah, Bolton, & Menon, 2020). While using real-time, reliable, secure, and timely data processing can help create flexible and resilient supply chains, there is a diverse set of highly complex factors, risks and challenges that must be identified, analyzed, and resolved (Birkel & Hartmann, 2019). The recent COVID-19 pandemic has increased these factors even further in complexity.

Supply Chain Risk Management (SCRM) aims to assess and eliminate the risks to ensure continuity (Heckmann, Comes, & Nickel, 2015). Although the research on SCRM and IIoT is rather limited (Birkel & Hartmann, 2020), addressing the potential benefits of IIoT technologies within supply chains such as agility, flexibility and resilience has gained prominence. To build more capable supply chains, it is particularly important to understand both the issues that supply chains face during the pandemic and the implications of the pandemic on the IIoT use in supply chains. These two matters bolster the importance of managing the challenges of IIoT technologies in supply chains during a pandemic. There have been recent studies to establish a framework for classifying the potential challenges and risks associated with IIoT in supply chains. In IIoT, risks ensue the challenges. Challenges and risks – as the consequent of challenges – impact the realization of the expected gains due to IIoT adoption. To the best of our knowledge, no attempt has been made to quantify the importance of challenges associated with IIoT and supply chains. Furthermore, embedding the impact of the currently ongoing pandemic on studying these challenges could help grasp the future of IIoT in supply chains.

Our research question is: “Given the risk and challenge framework of using IIoT for supply chains, how does the pandemic affect the relative importance of the challenges of IIoT in supply chains”. In response to this question, we structure the rest of this article as follows. We offer a comprehensive and systematic literature review, and theoretical background in the next section. We describe our proposed methodology in Section 3. Section 4 is dedicated to the challenge assessment using our proposed methodology. The paper closes with conclusion and discussion section.