Developing a causal framework of internet of things adoption barriers for agile manufacturing in post COVID-19

Abstract

In order to remain competitive in a post-COVID-19 scenario, manufacturing organizations should use the pandemic scenario as a lever to make IoT adoption more agile and faster by reinventing their business models. Although, IoT has vast potential in multiple sensors’ direct integration without human intervention, its adoption has observed significant barriers during COVID-19. In this context, the current research aims to identify, prioritize, categorize, and investigate inter-dependencies among the significant barriers to adopting IoT technologies in the manufacturing industry. The analysis used two-stage integrated AHP-TOPSIS (Analytical Hierarchy Process-Technique for Order Preference by Similarity to Ideal Solution) and ISM (Interpretative Structural Modeling) techniques. For AHP and ISM techniques, a group of 8 experts from academia and industry with at least 10 years of experience was surveyed to capture their perceptions. Whereas, for TOPSIS, data were collected from 433 operational-level users. The research discloses that the significant driver barriers that hamper the adoption of IoT technologies are: poor internet infrastructure, high adoption & operating costs and lack of government regulations. This study will assist practitioners, decision-makers and organizations in understanding the significant barriers to seamless IoT implementation.