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The Indian micro small and medium scale enterprises (MSMEs) are potential suppliers to the original equipment manufacturers (OEM). The implementation of sustainable supply chain practices (SSCPs) enhances the chances of developing a long-term partnership with these OEMs.

A hybrid framework of analytical network process (ANP) and fuzzy logic (FL) is developed for implementing SSCPs in Indian MSMEs. This model has been validated through a case study.

The study has identified several critical success factors (CSFs) for the implementation of SSCPs in MSMEs. This study has observed that Government regulation is the most important CSF for the implementation of SSCP in Indian MSMEs followed by management support and policy framework.

The article presents a mechanism, i.e. an adaptability test that enables the OEM decision-makers to assess the suitability of an MSME for a long-term partnership.

The business enterprises are increasingly focusing on buying and supplying of products and services in a manner to reduce the adverse impacts on the environment, society, and economy. In view of the above, the concept of sustainable supply chain management (SSCM) has received attention of the industry and academia due to its importance on environmental, social and corporate responsibility through economic performance. The paper aims to discuss these issues.

The structured literature review attempts to map the various theories in the SSCM literature from the perspectives of economic performance, environmental dimensions, and social values and ethics.

As supply management is vital for enhancing organizational competitiveness, the present work attempts to investigate the theoretical perspectives in SSCM to develop an understanding of the current research activities and future potentials.

This work aims to gain a number of valid insights for the practitioners and the researchers. It also focuses on the perspectives of governance mechanisms for successful implementation SSCM practices in the business enterprises.

As the theory building initiatives with implications on the conceptualization of SSCM is limited in literature, this work has also been able to identify the trends and relevant research gaps to define the potential areas for future research.

This study aims to evaluate the sustainable supply chain performance indicators. At a macro level, the identification of the sustainable supply chain management (SSCM) performance indicators is done through exhaustive literature survey and interviews with experts. Furthermore, these indicators are evaluated through a hybrid approach, i.e. total weighted interpretive structural modelling (TWISM) followed by analytic hierarchical process (AHP).

Micro small and medium enterprises (MSMEs) in India are a major contributor to nation’s GDP. However, this sector struggles to comprehend benefits from implementation of SSCM due to a lack of appropriate performance evaluation metrics. The purpose of this paper is to contribute to the body of knowledge in SSCM by proposing and evaluating a set of SSCM performance indicators.

The paper highlights the SSCM performance indicators and concludes that business strategies, implementation planning and impact of stakeholders are the top SSCM performance indicators (SPIs). Therefore, the decision-makers must initially focus on strategic requirements which foster the implementation of SSCM, thereby ensuring profitability for all stakeholders.

Although the proposed framework was validated through a case study on Indian automobile component manufacturing MSMEs, future research would explore the extension of the framework to other industries.

The originality of this study lies in the application of the novel TWISM-AHP tool. Furthermore, the SPIs identified in the study, consider the integration of the triple bottom line from the MSME perspective. The TWISM-AHP analysis will be beneficial for SC decision-makers to enhance the SSCM performance based on the identified indicators and their criticality.

The purpose of this paper is to study various combination forms of the three basic sharing elements (i.e. orders sharing, manufacturers capacity sharing and suppliers capacity sharing) in the cluster supply chain (CSC), formulate a distributed model to protect enterprises’ decision privacy and seek to develop an effective method for solving the distributed complex model.

A distributed assembly cluster supply chain configuration (ACSCC) model is formulated. An improved augmented Lagrangian coordination (ALC) is proposed and used to solve the ACSCC model. A series of experiments are conducted to validate the improved ALC and the model.

Two major findings are obtained. First, the market order’s quantity change and the sales price of the product have a great impact on both the optimal results of the ACSCC and the cooperative strategy, especially, when the market order increases sharply, enterprises have to adopt multiple cooperative strategies to complete the order; meanwhile, the lower sales price of the product helps independent suppliers to get more orders. Second, the efficiency and computational accuracy of the improved ALC method are validated as compared to the centralized ALC and Lingo11.

This paper formulated the single-period ACSCC model under certain assumptions, yet a multi-period ACSCC model is to be developed, a more comprehensive investigation of the relationships among combination forms is to be extended further and a rigid proof of the improved ALC is necessary.

Enterprises in the industrial cluster should adopt different cooperative strategies in terms of the market order’s quantity change and the sales price of the product.

The proposed various combination forms of sharing elements and the formulated ACSCC model provide guidance to managers in the industrial cluster to choose the proper policy.

This research studies various combination forms of the three basic sharing elements in the CSC. A distributed ACSCC model has been established considering simultaneously multiple sharing elements. An improved ALC is presented and applied to the ACSCC problem.