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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.

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.

Sustainable end-of-life (Sus-EoL) practices can be achieved through manufacturing of sustainable products, and recovery and recycling after the use phase. To achieve Sus-EoL, the manufacturing organizations should handle their products after their EoL. The recovery of used products is achieved through the design of the collection location. However, the first step is to understand and identify the barriers (e.g. lack of awareness among people, lack of technology, etc.) which prevent the implementation of Sus-EoL practices. The paper aims to discuss these issues.

This paper is about the 18 barriers responsible for the poor success of Sus-EoL practices of used plastic parts. By applying the DEMATEL method and by incorporating experts’ knowledge, a prominence and causal relationship diagram was developed through which the influential strength among barriers was studied.

The α value is computed as 0.068, and the values lower than α were eliminated to obtain the digraph. Poor curbside pick is identified as the most dominant barrier in implementation of Sus-EoL practices in plastic parts with an influential score of 3.96.

The research is conducted in the Indian scenario which could be extended to global context by selecting the suitable barriers.

The results from the study can be used by the managers of organizations to enhance the possibility of Sus-EoL practices by incorporating suitable strategies which is the significant contribution of this study.

In the past, few authors discussed about the barriers of Sus-EoL practices; however, the analysis of complex interrelationship does not exist. Thus, the global and group interrelationship has been studied which is expected to pave way for future research in the direction of elimination of barriers and so on.

In the present scenario, the demand for additive manufacturing (AM) has increased. Taking into account environmental problems and sustainability, manufacturers are now also considering the environmental and sustainability criteria in their decision-making process. The sustainability concept is known as the triple-bottom line, namely, economic, social and environmental perspectives. Sustainable concept selection in the manufacturing organisation can be considered as the selection of sustainable material, product design, process, method and technology. This study aims to select an appropriate AM process by considering sustainability from various available techniques.

Appropriate sustainable performance indicators for the AM were identified based on literature as well as in discussion with experts and decision-makers. The model addresses all the major dimensions of sustainable concepts of AM such as material/product quality, machine performance, market stability, total cost and ecological values. A hybrid multi-criteria decision-making approach, i.e. stepwise weight assessment ratio analysis and complex proportional assessment methods, have been used to select the best AM technique. While selecting criteria affecting AM machines and processes, criteria based on the sustainable concept are considered.

Among the four selected AM processes, i.e. fused diffusion modelling (FDM), laminated object manufacturing (LOM), stereolithography apparatus (SLA) and selective laser sintering (SLS), the best alternative was found to be FDM.

The present study highlights some limitations in the selection of AM process and methodology used in this research. This study considers only four AM processes, i.e. FDM, LOM, SLA and SLS. Future work may include considering other AM processes and criteria that affect the sustainability of AM.

The present work will help researchers and production managers to decide the best AM alternatives to fabricate desired parts. Hence, AM can help in maximum energy utilisation, optimal consumption of resources, minimum material wastage and reduction of CO₂ emission.

The study considers some important criteria, including energy consumption, eco-friendly and wastage-free production, that help sustainable AM. This study can result in a good economic efficiency of AM industries and, therefore, positively impact customers using green products.

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 improve the productivity and quality of the wire arc additive manufacturing process by benchmarking the strategies from the selected six strategies, namely, heat treatment process, inter pass cooling process, inter pass cold rolling process, peening process, friction stir processing and oscillation process.

To overcome the lack of certainty associated with correlations and relationships in quality functional deployment, fuzzy numbers have been integrated with the quality functional deployment framework. Twenty performance measures have been identified from the literature under five groups, namely, mechanical properties, physical properties, geometrical properties, cost and material properties. Using house of quality weights are allocated to performance measures and groups, relationships are established between performance measures and strategies, and correlations are assigned between strategies. Finally, for each strategy, relative importance, score and crisp values are calculated.

Inter pass cold rolling process strategy is computed with the highest crisp value of 15.80 which is followed by peening process, heat treatment process, friction stir processing, inter pass cooling process,] and oscillation process strategy.

To the best of the authors’ knowledge, there has been no research in the literature that analyzes the strategies to improve the quality and productivity of the wire arc additive manufacturing process.

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.

Numerous leanness assessment models were developed for both manufacturing and service sectors. However, little research effort was made to provide an instrument that can be used to measure the leanness level of the product-service system (PSS). This paper aims to propose an index to assess the leanness of PSS in a UK manufacturing company.

The development of the assessment model was carried out through an iterative process. Commencing from existing literature on lean manufacturing assessment and lean service assessment, the initial model for assessing PSS leanness was developed. This initial model was refined via two consecutive phases. The first one includes semi-structured interviews with academic researchers involved in lean projects where their comments were considered. In the second phase, semi-structured interviews with several experts working in different UK manufacturing industries and involved in lean and continuous improvement projects were conducted to reach the final assessment model. After developing the model, the next step was identifying a suitable company for applying the model. The case company was selected because of its commitment to implement lean practices and its ability to participate in this study. After that, data was collected from the case company and the PSS leanness index was calculated using a multi-grade fuzzy approach. Finally, areas for further improvement were identified and the results obtained were validated.

The PSS leanness index computed for the case company indicates that the service offering process provided by the company is generally lean. Areas for further improvement were identified.

This study focussed on a single case company and is based on the experts’ opinions; this may tend to be biased. However, future studies will be performed to multiple-case studies to enhance findings and more empirical research will be conducted to catch more insights into PSS leanness.

This paper provides guidelines to manufacturing companies’ managers for measuring the PSS leanness index and planning for the future. This index gives information regarding the degree of lean adoption in the service offering process and identifying the gap between the current PSS leanness level and the desired state.

The proposed model has been developed by the opinion of academicians and industry experts. The proposed model can provide guidelines and directions for managers for PSS leanness assessment.

Lean Six Sigma (LSS) is a widely accepted business improvement methodology in healthcare, which aims to improve operations and quality and reduce cost, medical errors and waiting time by combing the principles of lean thinking with Six Sigma methodologies. To implement LSS successfully in healthcare organizations it is necessary to know the readiness level before starting the change process. Thus, the purpose of this paper is to assess the readiness level for the implementation of LSS in healthcare using a fuzzy logic approach.

The current study uses a fuzzy logic approach to develop an assessment model for readiness to implement LSS. The conceptual model for readiness is developed with 5 enablers, 16 criteria and 48 attributes identified from the literature review. The current study does the study in a medium-size hospital from India.

The fuzzy readiness for implementation of LSS index (FRLSSI) and fuzzy performance importance index (FPII) are calculated to identify the readiness level for the implementation of LSS in the case hospital. The FRLSSI is computed as average ready with (3.30, 5.06 and 6.83) and the FPII computed helps to identify 15 weaker attributes from 48 attributes.

The current study uses only one hospital for study. In the future, the model can be tested in many hospitals.

The current study would be used by the managers of a healthcare organization to identify the readiness level of their organization to implement LSS. The proposed model is based on the identification of enablers, criteria and attributes to assess the readiness level of a healthcare organization and it helps to improve the readiness level to implement LSS effectively.

The present study contributes to the knowledge of readiness for the implementation of LSS in a healthcare organization. The conceptual model is developed for assessing the readiness level of a healthcare organization and it helps to improve the readiness level for successful implementation of LSS. Weaker attributes are identified and necessary corrective actions should be taken by the management to improve the readiness. The continuation of the assessment readiness model over a period of time would help to improve the readiness level of healthcare for the implementation of LSS.

The earth’s carrying capacity cannot withstand the pace of consumption resulting from current economic models, mainly the linear economy (LE) built on a throwaway culture. In the last few decades, the concept of a circular economy (CE), aiming to design waste out of the economy and mimic ecosystems, emerged as a strong alternative to LE. Being at the heart of the economic landscape, supply chains (SCs) need to respond to the necessary shift to CE. In so doing, the planning and execution of circular supply chains (CSCs) require a broader comprehension of CE and more sophisticated and large-scale analytical decision models. This chapter surveys extant literature on available best practices and quantitative models for sustainable supply chains (SSCs) and offers a new definition of CSC. Mapping on the knowledge extracted from this classification, potential gaps and strengths in the literature are identified. Key research papers on the “closed-loop” and “open-loop” ends of CSCs are highlighted. Challenges in developing CSC performance indicators and prescriptive models are emphasized.