Purpose: Waste can be converted to a high-value asset if treated properly with smart solutions. The purpose of this research is to identify critical barriers hindering smart waste management (SWM) implementation in developing economies using comparative analysis and a mixed-method approach. The objective of this work is to provide exhaustive insight including the smart cities projects to discuss the deferring parameters toward IoT-enabled waste management systems.Design/methodology/approach: To accomplish the objective, the present study followed mixed-method approach consisting of two phases: In the first qualitative phase, barriers in the adoption of IoT (Internet of Things) for SWM were identified using extensive literature review and discussion with selected experts. In the second phase, the quantitative analysis using the Fuzzy DEMATEL (Decision-Making Trial and Evaluation Laboratory) method was performed on the selected barriers. The fuzzy DEMATEL methodology helps in prioritizing the most significant causal barrier by separating them into the cause-effect group. The comparative analysis was used to understand two different perceptions. To provide more detailed insight on the problems faced while implementing SWM in developing economies.Findings: The results disclose that “Lack of government strict regulatory policies,” “Lack of proper financial planning” and “Lack of benchmarking processes” are the most critical causal barriers toward IoT-enabled SWM implementation that are hindering the vision of efficient and effective waste management system. Also, “Difficulty in implementing innovative technologies” and “Absence of Dynamic Scheduling and Routing” fall under the potential causal category. The effect barriers include “Lack of awareness among the community,” “Lack of source segregation and recycling commitment” and “Lack of service provider” as concluded in results considering the comparative analysis. The results can aid the policy-makers and stakeholders to identify the significant barriers toward a sustainable circular economy and mitigate them when implementing IoT-enable waste practices. Also, it assists to proactively build programs, policies, campaigns and other measures to attain a zero-waste economy.Research limitations/implications: The research is focused on the context of India but it provides new details which can be helpful for other developing economies to relate. The research addresses the call for studies from public-sector and citizen’s perspectives to understand the acknowledgment of SWM systems and critical success factors using qualitative and exploratory method analysis.Practical implications: The practical implications of the study include strict regulatory policies and guidelines for SWM acceptance, proper financial administration and benchmarking waste-recycling practices (prominent causal barriers). The practical implication of the results includes assistance in smart city projects in handling barriers proactively. The “Lack of Benchmarking processes” provides a critical application to standardized recycling practices in developing economies to improve the quality of the recyclable material/product. The comparative analysis also provides in-depth reflection toward the causal barriers from both the perspective which can help the government and stakeholders to work in a unified manner and establish an efficient waste management system. The results also conclude the need for targeted training programs and workshops for field implementation of innovative technologies to overcome the causal barrier. Moreover, policy-makers should focus to improve source segregation and recycling practices and ensure dedicated communication campaigns like Swachh Bharat Abhiyan to change the behavioral functioning of the community regarding waste. Lastly, developing economies struggle with the adequacy of resources to establish SWM systems, hence the authors conclude that proper financial planning is required at the ground level for smart city projects to overcome the spillover effects.Social implications: The social implications of the study include a reduction in pollution and efficient handling of waste resulting in a healthier and cleaner environment using IoT technology. Also, the results assist decision-makers in developing economies like India to establish smart city projects initiatives effectively to improve the quality of life. It proposes to establish standardized recycling processes for the better quality of recyclables and help in attaining a sustainable circular economy.Originality/value: The research is novel as it provides comprehensive and comparative information regarding the barriers deferring SWM including the field barriers. To our consideration, the present study serves the first to address the comparative analysis of barriers in IoT-enabled waste systems and establish the relationship from both the perspective in middle-lower income economies. The study also suggests that the effect barriers can be overcome automatically by mitigating the causal barriers in the long run.

Purpose: Industry 4.0 and circular economy are the two major areas in the current manufacturing industry. However, the adoption and implementation of Industry 4.0 and circular economy worldwide are still in the nascent stage of development. To address this gap, the purpose of this article is to conduct a systematic literature review on integrating Industry 4.0 and circular economy. Further, identify the research gaps and provide the future scope of work in this area.Design/methodology/approach: Content-based analysis was adopted for reviewing the research articles and proposed a transition framework that comprises of four categories, namely, (1) Transition from Industry 3.0 to Industry 4.0 and integration with circular economy; (2) Adoption of combined factors and different issues; (3) Implementation possibilities such as front-end technologies, integration capabilities and redesigning strategies; (4) Current challenges. The proposed study reviewed a total of 204 articles published from 2000 to 2020 based on these categories.Findings: The article presents a systematic literature review of the last two decades that integrates Industry 4.0 and circular economy concepts. Findings revealed that very few studies considered the adoption and implementation issues of Industry 4.0 and circular economy. Moreover, it was found that Industry 4.0 technologies including digitalization, real-time monitoring and decision-making capabilities played a significant role in circular economy implementation. The major elements are discussed through the analysis of the transition and integration framework. The study further revealed that a limited number of developing countries like India have taken preliminary initiatives toward Industry 4.0 and circular economy implementation.Research limitations/implications: The study proposes a transition and integration framework that identifies adoption and implementation issues and challenges. This framework will help researchers and practitioners in implementation of Industry 4.0 and circular economy.Originality/value: Reviews of articles indicated that there are very few studies on integrating Industry 4.0 and circular economy. Moreover, there are very few articles addressing adoption and implementation issues such as legal, ethical, operational and demographic issues, which may be used to monitor the organization's performance and productivity.

The world is facing economic, as well as social, crisis due to the COVID-19 pandemic. Implementing sustainable practices is one of the possible ways to address these issues. Adopting circular oriented techniques throughout the supply chain not only guarantees economic profitability, but also provides an edge to the organization in the market of fierce global competition. The concept of implementing circularity in the supply chain is novel and dynamic in nature, and it involves certain risk. In this study, a Bayesian Network methodology is adopted to analyze how the risk propagation takes place in a circular supply chain network of an automobile organization. The circular supply chain network consists of a group of manufacturers, retailers and recyclers, located in the Delhi–NCR region. Economic, environmental, social, technological, waste management, agile vulnerability, and risk of cannibalization are the major risk categories that were identified through an extensive literature review. Further, the impact of risk on the performance of the circular supply chain is analyzed by considering performance parameters such as lost sales, impact on supply chain revenue, and inventory holding cost. Risk exposure index is incorporated into the study to analyze the vulnerability of each node. The findings of the study reveal that the reverse side of the circular supply chain can be a source of risk propagation during the implementation of the circularity concept. This work is carried out under a single industry domain. In the future, risk propagation analysis can be examined in the supply chain of other sectors. The findings of the study can assist the supply chain managers and the risk experts to focus on the areas that are more vulnerable to risk.

Purpose: The study presents various barriers to adopt big data analytics (BDA) for sustainable manufacturing operations (SMOs) post-coronavirus disease (COVID-19) pandemics. In this study, 17 barriers are identified through extensive literature review and experts’ opinions for investing in BDA implementation. A questionnaire-based survey is conducted to collect responses from experts. The identified barriers are grouped into three categories with the help of factor analysis. These are organizational barriers, data management barriers and human barriers. For the quantification of barriers, the graph theory matrix approach (GTMA) is applied.Design/methodology/approach: The study presents various barriers to adopt BDA for the SMOs post-COVID-19 pandemic. In this study, 17 barriers are identified through extensive literature review and experts’ opinions for investing in BDA implementation. A questionnaire-based survey is conducted to collect responses from experts. The identified barriers are grouped into three categories with the help of factor analysis. These are organizational barriers, data management barriers and human barriers. For the quantification of barriers, the GTMA is applied.Findings: The study identifies barriers to investment in BDA implementation. It categorizes the barriers based on factor analysis and computes the intensity for each category of a barrier for BDA investment for SMOs. It is observed that the organizational barriers have the highest intensity whereas the human barriers have the smallest intensity.Practical implications: This study may help organizations to take strategic decisions for investing in BDA applications for achieving one of the sustainable development goals. Organizations should prioritize their efforts first to counter the barriers under the category of organizational barriers followed by barriers in data management and human barriers.Originality/value: The novelty of this paper is that barriers to BDA investment for SMOs in the context of Indian manufacturing organizations have been analyzed. The findings of the study will assist the professionals and practitioners in formulating policies based on the actual nature and intensity of the barriers.