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The purpose of this paper is to investigate the effect of current carbon tax (CT) policy on organizations involved in a sharing network relation.

For finding the CT and economic value of the industries connected in a sharing network model a multi-objective multi-integer linear model has been formulated. The data set of the case organization is used for computation. The formulated mathematical model is computed with the aid of GAMS optimization program.

This research paper demonstrates the effectiveness of the sharing network strategy in increasing the economic value and decreasing the CT for industries involved in sharing network. The CT value INR 3,012.694 for the industries in Scenario II which incorporates the sharing network is less than the CT INR 3,580.167 for industries in Scenario I without sharing network.

The data used for the computation is based on a particular sharing network under investigation. The formulated mathematical model can be checked with similar sharing networks by varying the parameters.

This work can aid in gaining complete knowledge on the sharing network strategy which can uplift the resources and the monetary value of the non-efficient industries moving them towards sustainable and greener supply chain practices.

The presented work can impact various industries in developing countries providing them with a strategy to enhance their resources and economic value by maintaining an amicable relation.

This work uniquely was able to validate economic feasibility and CT in accordance with the carbon footprint involved in sharing network. This sharing network also incorporates the concepts of circular economy and reverse logistics for showcasing a better strategy.

The purpose of this paper is to propose a mathematical model for the design of a circular production system (CPS) for an Indian manufacturing organization participating in a symbiotic network.

A multi-objective mixed integer linear programming is used to model the network for quantifying the economic benefits. The data set collected from the case organization is used. The GAMS optimization package is used to simulate the model.

The model is able to compute the economic benefit achieved through circular operations in the case organization. The flow of different items through the network is also obtained.

The data set of the single organization in the symbiotic network is used to validate the proposed mathematical model. Further research can be done considering the all the organizations in the considered symbiotic network.

This paper will help the authors to better understand the role of sustainable supply chains in a circular economy model especially in energy and materials intensive industries.

This study has uniquely utilized a multi-objective mixed-integer linear programming approach for the analysis of variables in CPSs and the corresponding economic benefits.

The purpose of this paper is to persuade a hybrid framework, which can be used to assess the performance of various supply chains and can be further used to segregate supply chains concerning critical KPMs. The KPMs have been selected in the COVID-19 pandemic condition.

A real case of e-commerce is presented to illustrate the working of the proposed framework comprising a hybrid methodology of BWM and Fuzzy TOPSIS to measure the performance of the e-commerce supply chains by identifying the critical key performance metrics (KPMs) and measuring the performance of the considered supply chains against these.

The proposed framework is illustrated using real-time data from experts, collected through interviews and discussions. It is found that rate of return on investment (SCPM 27), flexibility of service systems to meet particular customer needs (SCPM 23) and supplier lead time against industry norm (SCPM 33) are significantly weighed in assessing performance of the selected supply chains, with weights 0.07764, 0.06863 and 0.0547, respectively. Amazon and Flipkart are seen to stand out among the other supply chains taken for the present study with closeness coefficients as 0.945 and 0.516, respectively.

The contemporary world has seen the drastic attack of COVID-19 on many firms worldwide, and hence measuring the performance of the supply chains has become necessary so as to understand the critical factors affecting performance, their relative importance and the firm's relative standings. There have been studies in the recent past where researchers worked on similar motives to generate a framework to measure performance of supply chains, but it is seen that the methodologies lack flexibility with respect to effectively handling large data, uncertainty in human emotions, consistency, etc. This is where the current study stands out in effectively measuring the performance of supply chains so as to aid many firms affected by the pandemic.

Drilling holes in composite materials is a complex and challenging process because of their intrinsic anisotropic characteristics and unevenness compared to conventional metals. Hybridization of composites enhances the strength and hardness of the material but makes it more difficult to drill a hole in it. The purpose of this study is to optimize the drilling to minimize the delamination and taperness of hybrid glass fiber reinforced plastic (GFRP)/Al₂O₃ composites.

The present study investigates the impact of drilling parameters on delamination of the drilled hole and the taperness of the hole on hybrid GFRP/Al₂O₃. Optimum drilling conditions for minimizing delamination and taperness of the hole are determined to enhance the hole quality. Feed (f), speed (N) and drill diameter (D) are the parameters taken into consideration for drilling operation. By applying Taguchi’s signal-to-noise ratio analysis, process parameters have been optimized to reduce the delamination and taperness of holes on Hybrid GFRP/Al₂O₃ composites. The effect of process parameters was analyzed using the analysis of variance method.

The investigational results confirmed that the delamination is positively affected by speed, drill diameter and feed rate. Also, the taperness of the hole is positively affected by the drill diameter. Regression-based models were developed to predict the delamination and taperness of the hole matched with the experimental results, which are attained with an order of 95% and 97%.

Minimum delamination was found at the optimum condition of drill diameter 10 mm, feed at 0.225 mm/rev and the speed at 151 rpm and minimum taperness were found at the optimum condition of drill diameter 10 mm, feed at level 0.3 mm/rev and speed at 86 rpm for hybrid laminate composite (S-glass+ GFRP/Al₂O₃) were evaluated.

Improving the medical oxygen supply chain (MOSC) is important to cope with the uneven demand and supply seen in the MOSC when India faced the second wave of COVID-19. This improvisation increases the supply chain (SC) maturity and consequently the efficiency and resiliency to tackle oxygen shortage across the country and to prevent another similar scenario from ever happening. The purpose of this study is to identify and prioritize the solutions to overcome the issues faced by the MOSC during the second wave of COVID-19 cases in India and in turn reduce the extent of casualties in the expected third wave.

This paper uses best worst method (BWM) and fuzzy technique for order performance by similarity to ideal solution to classify the sub-criteria for solutions to solve major SC issues. BWM is used to determine the weights of the sub-criteria and fuzzy technique for order performance by similarity to ideal solution for the final ranking of the solutions to be adopted.

The result of this study shows that the Internet of Things based tagging system is the best solution followed by horizontal and vertical integration of SC in making a resilient and digitized MOSC capable of handling general bottlenecks during a possible third wave.

The research provides insights that can enable the personnel involved in MOSC. Proper understanding will help the practitioners involved in the SC to effectively tailor the operations and to allocate the resources available in an effective and dynamic manner by minimizing or eliminating the pre-existing bottlenecks within the SC.

The proposed framework provides an accurate ranking and decision-making tool for the implementation of the solutions for the maturity of the MOSC.

The purpose of this paper is to develop and optimize a mathematical model based on a framework that integrates key concepts related to a circular economy (CE) and sharing economy (SE) for a leading manufacturer of laptops in India.

This study mathematically modelled the integration of sharing networks in a circular production system. This is done through an optimization package that deploys a multi-objective mixed-integer linear programming model.

This study evaluated the economic benefit and the environmental impact associated with the aforementioned integration in a production system. This study illustrated the inverse relationship between economic benefit and environmental impact and provided a set of solutions that can be used according to the case organizations goals, capacities and logistical capabilities.

This study will aid similarly structured companies in adopting this approach to integrate sustainable practices in their production system. It also enumerated Industry 4.0 (I4.0) use-cases that can be used to effectively implement this mathematical model. Further research can be conducted using multiple companies in an inter-dependent network to maximize synergy.

This study will help to better understand the role of sharing networks in the circular economy model especially in the consumer electronics industry.

This study is the first of its kind to mathematically model the integration of aspects related to SE and CE. It also validates the aforementioned model using a numerical case-study and offers decision-support to key executives within the case organization.

Industrial symbiosis (IS) is basically a synergistic association between two or more industries or businesses wherein the waste or by-product of one industry becomes the raw material or immediate material of another industry. IS is believed to bring in significant benefits to the organizations. Thus, the purpose of this paper is to evaluate the competitiveness attained through IS.

Analytic hierarchy process was adopted to analyze the various organizational competitiveness of IS implementation. The conceptual model was developed to understand the interrelationship between 14 outcomes and 5 organizational competitiveness which are identified from the literature review. The attainment of these five organizational competitiveness was evaluated by computing the global priority score of the outcomes.

The global priority score suggests that the organizational collaboration (0.19) is the important output. Further, collective learning and growth (44 percent) have been identified as the important competitiveness attained through the implementation of IS.

The relationship matrix developed can be used by the practicing managers/researchers to understand the various interactions. Thus, systematic decision making and guidance for future implementation studies will be ensured.

In the past, few authors discussed the conceptualization of IS; however, the impact of IS on the organizational performance was not extensively studied. Therefore, a conceptual model was proposed to analyze the attainment of various competitiveness through the participation of industrial symbiosis network. Further, based on the computed scores, the relationship matrix developed between outcomes and organizational competitiveness is one of the significant contributions of this work.

The purpose of this study is to present Industry 4.0 technologies for advancing the circular economy (CE) adaption in manufacturing industry’s supply chain (SC) network. To pursue the same, Industry 4.0 technological aspects were recognized as solution measures to overcome the challenges for CE implementation in SC.

A new hierarchical framework containing 13 leading CE challenges and eight promising Industry 4.0 technological aspects had been proposed, representing their mutual relationship. The proposed framework was analysed using a hybrid approach of analytic hierarchy process (AHP) and combinative distance-based assessment (CODAS) under interval-valued intuitionistic fuzzy (IVIF) environment. The IVIF-AHP was used to acquire the priority weights of the CE challenges, whereas the IVIF-CODAS was used to attain the preference order of the proposed technological aspects.

The key findings of the present work indicate that “Information disruptions among the SC members due to multiple channels” and “Manpower inability to handle the toxic materials” are the two most critical challenges hindering the adoption of CE practices in SC. Along with, the results also demonstrate that to overcome these challenges, “Smarter equipment to empower flexibility and mass customization” and “Big data driven decision-making system” are the two most significant Industry 4.0 technological solutions, adoption of which might encourage the organizations to align their operations with CE philosophies.

The sample size of the experts engaged in work was limited; however, big data studies could be conducted in future to capture more insights of the stated topic. In addition to this, to understand the implication of CE on Industry 4.0-based manufacturing, a separate study can be synthesised in future.

The proposed work facilitates a new framework consolidating various perspectives associated with CE implementation into a manufacturing industry considering the scenario of Indian rubber industry. This study enables the decision-makers to recognize the challenging factors for CE implementation into their organizations and up-taking the proposed Industry 4.0 practices as technological measures for improving the organization overall performance.

The catastrophic state of the COVID-19 pandemic outbreak has seized off all the operations along with the globe. It has not only distressed the socio-economic structure of the world but also mounted enormous pressure on the governmental bodies to save the lives of the people. Despite this, severe impacts of the same have been observed on the small and medium manufacturing enterprises (SMME) practices, resulting in the economic downturn. The purpose of this study is to facilitate the SMME’s with circular economy (CE) practices to overcome the negative impacts of the COVID-19 outbreak on their supply chain (SC) operations.

The presented work identified seven critical impacts as criteria of the novel COVID-19 pandemic on the Indian SMME and seeks to identify the relief measures in the CE paradigm by identifying 13 prominent enablers to CE as alternatives. Experts’ opinions have been engaged to detect CE enablers’ proficiency to overpower the pandemic impact through a questionnaire-based survey. The obtained data have been clustered and analyzed through a hybrid approach of entropy weight method and grey relational analysis to find an organized ranking of the enablers.

Current work spotlights the SMME’s losses due to SC disruptions and declined consumption patterns. The waste augmentation during the pandemic era has also been grouped in this study, primarily associating with the SC’s waste generation. The result of the performed analysis shows that the CE enabler “waste reduction and its transformation into a resource (E1)” have achieved the highest rank among all the considered enablers, governing a higher demand toward reusing waste for better handling the post COVID era state of affairs.

The presented study aimed to suppress the pandemic impact and generate anticipation of the CE concept, which might help the managers and policymakers identify its urgent need to achieve a stable and resilient SC system in a post COVID period. Presented work is peculiar, aiming to accelerate the CE adaption with green material usage in the industrial sector to suppress the present miserable condition and to achieve industrial and social sustainability for a better-foreseen future.

The circular economy concepts are useful for resource conservation, eliminating waste and enhancing the efficiency of production to improve the sustainability of the system. The application of CE in Indian manufacturing industry is in nascent stage. India’s manufacturing sector significantly contributes to the economic development of the nation; therefore, this study aims to identify and analyze the sustainability related challenges faced during the implementation of the circularity concept.

Comprehensive survey of literature and the use of Pareto analysis yield ten significant challenges which are further analyzed using fuzzy-Decision-Making Trial and Evaluation Laboratory approach.

Findings revealed that noncompliance of environmental laws, revenue generation, design issues owing to technological limitations and less preference to refurbished and reused product are some of the major challenges to the CE practices in the manufacturing industry.

The results will help the researchers and practitioners in strategic decision-making for the improved application of circularity in the production process.

This paper contributes to the identification and prioritization of sustainability-related challenges faced during the implementation of a novel concept by a developing economy.