Disruptive supply chain technology assessment for sustainability journey: A framework of probabilistic group decision making

The fourth industrial revolution, commonly recognized as Industry 4.0, has been ushered by modern and innovative intelligence and communication technologies. Concerns about disruptive technologies (DTs) are beginning to grow in developing countries, despite the fact that the trade-offs between implementation difficulties and realistic effects are still unknown. Hence, prioritization and promotion of such technologies should be considered when investing in them to ensure sustainability. The study aims to provide new critical insights into what DTs are and how to identify the significant DTs for sustainable supply chain (SSC). Understanding the DTs’ potential for achieving holistic sustainability through effective technology adoption and diffusion is critical. To achieve the goal, an integrated approach combining the Bayesian method and the Best Worst Method (BWM) is utilized in this study to evaluate DTs in emerging economies' supply chain (SC). The systematic literature review yielded a total of 10 DTs for SSC, which were then evaluated using the Bayesian-BWM to explore the most critical DTs for a well-known example of the readymade garment (RMG) industry of Bangladesh. The results show that the three most essential DTs for SSC are “Internet of things (IoT)”, “Cloud manufacturing”, and “Artificial intelligence (AI)”. The research insights will facilitate policymakers and practitioners in determining where to concentrate efforts during the technology adoption and diffusion stage in order to improve sustainable production through managing SC operations in an uncertain business environment

Behavioural factors for Industry 4.0 adoption: implications for knowledge-based supply chains

Industry 4.0 (I4.0) is a relatively new and still emerging concept. Due to its novelty, companies find it extremely difficult to adopt I4.0 and reap the full benefit of the digital transformation of the fourth industrial revolution. Even though challenges to I4.0 adoption are well explored, the extant literature has hardly investigated the numerous human-based behavioural factors that are fundamental for I4.0 adoption. Human experience, engagement, and dedication to I4.0 adoption are crucial due to the complex nature of human behaviour and can significantly affect the success of I4.0 adoption. To address the gap, this paper aims to unveil the indispensable behavioural factors for I4.0 adoption and portray a hierarchical relationship among these factors. An extensive literature review is conducted to identify behaviour critical for I4.0 adoption to operationalise this research. Then, a decision support framework based on the Delphi technique and a revised rough DEMATEL method is used to map the relationships among the behavioural factors. The results reveal that the most critical behavioural factor to I4.0 adoption is “communication,” which is followed by “I4.0 training” and “resistance to I4.0 initiatives”. This study substantiates the research on I4.0 adoption and assists in I4.0 adoption. I4.0 adoption is also essential for a country’s competitiveness; therefore, the paper will support relevant policy formulation