Interrelationship among CE Adoption Obstacles of Supply Chain in the Textile Sector: Based on the DEMATEL-ISM Approach

Critical factors for implementing collection target responsibility in e-waste collection in China: A DEMATEL-ISM analysis

The Collection Target Responsibility (CTR) is the direction for the proper management of e-waste reuse and recycling. Despite its potential, the CTR policy is still in its infancy in China and faces significant challenges to its effective implementation. There are a few studies that have systematically identified and analyzed the factors that influence the application of CTR to e-waste collection systems in China. This study proposes a comprehensive process that considers collection targets and behaviors to develop the critical factors (CFs) involved in e-waste collection under CTR by participants including government, manufacturers and recyclers. The Decision-making Trial and Evaluation Laboratory and Interpretative Structural Modeling (DEMATEL-ISM) method was applied to analyze these CFs. The findings show that the development of policy and regulation is the root factor influencing the implementation of CTR in China, both in terms of collection targets and behaviors. Incentives and regulation of government, collection channels, and benefits of manufacturers and recyclers are important CFs that participants consider when adopting CTR and should be prioritized. This study not only contributes to the literature on e-waste collection under CTR, but also provides valuable insights for decision-makers to improve the performance of e-waste collection practices.

Building risk mitigation strategies for circularity adoption in Indian textile supply chains

Textile industries are among the most polluting and demand urgent management measures to mitigate their negative environmental impact. Thus, it is imperative to incorporate the textile industry into the circular economy and to foster sustainable practices. This study aims to establish a comprehensive, compliant decision framework to analyse risk mitigation strategies for circular supply chain (CSC) adoption in India's textile industries. The Situations Actors Processes and Learnings Actions Performances (SAP-LAP) technique analyses the problem. However, interpreting the interacting associations between the SAP-LAP model-based variables is somewhat lacking in this procedure, which might skew the decision-making process. As a result, in this study, the SAP-LAP method is accompanied by a novel ranking technique, namely, the Interpretive Ranking Process (IRP), which reduces decision-making issues in the SAP-LAP method and aids in evaluating the model by determining the ranks of variables; furthermore, the study also offers causal relationships among the various risks and risk factors and various identified risk-mitigation actions by constructing Bayesian Networks (BN) based on conditional probabilities. The study's originality represents the findings using an instinctive and interpretative choice approach to address significant concerns in risk perception and mitigation techniques for CSC adoption in the Indian textile industries. The suggested SAP-LAP and the IRP-based model would assist firms in addressing risk mitigation techniques for CSC adoption concerns by providing a hierarchy of the various risks and mitigation strategies to cope with. The simultaneously proposed BN model will help visualise the conditional dependency of risks and factors with proposed mitigating actions.

Evaluating the Intertwined Relationships of the Drivers for University Technology Transfer

Universities are the best places to gather knowledge and innovation, but the basis of technological development lies in talented R&D personnel who provide services to enterprise R&D activities, research institutions, and universities. Universities also gather many elites who cultivate talent for the country. However, universities do not have adequate technology transfer experience and do not network in industrial circles, which results in a huge gap between the concept and the practical result. This research determined the critical success factors and explored the causal relationships influencing the technology transfer from universities. We found that the main impact of the key factors was the technology market dimension. University technology transfer activities had to be classified as top priority. Technology industrial applicability was the main key evaluation factor, along with inventor attitude. In the organizational culture dimension, the attitude and ability of top management were the main evaluation factors. We attempted to draw upon our analysis results to make recommendations related to technology transfer to assist universities in successfully transferring their research results.

Testing a Recent DEMATEL-Based Proposal to Simplify the Use of ANP

The Analytic Network Process (ANP) is a well-known multi-criteria decision method that allows the relationships between its elements to be incorporated into the model. The large number of questions to be answered is one of the main drawbacks of the method, since it is time consuming for decision makers and experts who participate in the decision process. A recent DEMATEL-based ANP proposal can significantly reduce the number and the complexity of questions. This proposal was simply exposed and lacked an experimental test with real cases. The fundamental objective of this work is to answer the question: Does it work? In this work, this new proposal is applied to 45 ANP cases published in the literature. Variants to the verified proposal have also been identified. The results obtained show that the values of the priorities and the ranks obtained with this new proposal are very similar to the results obtained with the ANP, reducing the number of questions required by 42% on average. Additionally, in this work you can find the compilation of the 45 ANP weighted supermatrices to use in your investigations.