The developments of the fourth industrial revolution have caused changes in all areas of society, including production. The changes in production caused by the fourth industrial revolution have also resulted in fundamental changes in the supply chain and have converted it to supply chain 4.0. Organisations must be receptive to supply chain 4.0 to maintain their competitive advantage. Therefore, this study aimed to investigate the relationships among supply chain 4.0 technologies so that, by learning and understanding these connections, industries can pave the way for the implementation of these technologies in their supply chains and use them in problem-solving. The literature review was used to identify the supply chain 4.0 technologies, and the Delphi technique was applied to extract them, including the Internet of Things (IoT), cyber-physical systems, cloud computing, big data, blockchain, artificial intelligence, Radio-frequency Identification (RFID), augmented reality, virtual reality, and simulation. The relationships of supply chain 4.0 technologies were examined using the DEMATEL technique and based on interpretive structural modelling (ISM), their deployment map was drawn. The type of technologies was determined using the MICMAC method. The MICMAC analysis found that the artificial intelligence technology is independent and, based on the findings through the DEMATEL technique, this technology is related to simulation, which belongs to the first level of the interpretive structural modelling technique, and IoT, cloud computing, big data, and blockchain technologies, which are at the second level. Based on the ISM method, RFID, virtual reality, augmented reality and simulation technologies are located at the first level; IoT, cyber-physical systems, cloud computing, big data and blockchain technologies are situated in the second level; and artificial intelligence technology belongs to the third level. According to the related literature, few studies have been conducted on the issues of supply chain 4.0 and the technologies that affect it.

The circular supply chain (CSC) plays a pivotal role in delivering sustainable products to end users, profoundly affecting organizational performance and societal welfare. In this ecosystem, effective Product Return Management (PRM) is crucial, as consumers play a pivotal role in returning used products for reuse or recycling. Despite its significance in waste reduction and attaining environmental and economic goals, scant research has explored product return barriers within CSC. This study bridges this gap by investigating and prioritising these barriers to enhance the circular economy. Employing a systematic literature review (SLR), we extracted and screened 13 product return barriers in CSC using the Grey Delphi method. Subsequently, we introduced an enhanced version of the Group Grey-Best–Worst Method (GG-BWM), a novel approach that harmonises expert judgments by addressing uncertainties through Grey Theory and incorporating both individual-level and group-level inconsistency ratios. The findings highlight lack of motivation, lack of consumer awareness, and lack of proper infrastructure as the most critical barriers. Furthermore, sensitivity analysis conducted across 11 scenarios emphasises the significance of our results. This study contributes to the group multiple criteria decision making (MCDM) methods and CSC literature, while offering actionable insights practitioners seeking to improve the effectiveness of their CSC strategies.