Purpose – The purpose of this paper is to examine the status of green supply chain management (GSCM) research in terms of how the field is represented along a number of dimensions including journal, year, country, university, publishing house, authors, research design, research methods, data analysis techniques, multi criteria decision-making methods, research topics/issues and major industries actively involved. Design/methodology/approach – A range of online databases from 1998 to August 2013 were searched containing the word “green supply chain” in their title and in the phrases to provide a comprehensive listing of journal articles on GSCM. Based on this a total of 177 articles were found and the information on a series of variables was gathered. Each of these articles was further reviewed and classified. The review and classification process was independently verified. All papers were allocated to the main and sub-categories based on the major focus. Findings – The major findings shows that survey research holds greater credibility and the trend in survey research is moving from exploratory to model building and testing. GSCM research related to organizational practices, environmental issues, process, performance and sustainability were found to be most widely published topics within the GSCM domain. Research limitations/implications – This paper is limited in reviewing those articles which contains the word “green supply chain” in the title and the phrases of the articles. Originality/value – The present review will provide increased understanding of the current state of research and what still needs to be investigated in the GSCM discipline.

The aim of this study is to explore the implementation of green supply chain management (GSCM) strategies and to select the best GSCM strategy using fuzzy analytical network process (ANP) methodology. The ANP helps in analyzing the interdependence and interrelations among the various determinants and dimensions of GSCM strategy selection. Fuzzy set theory is applied to avoid the vagueness and uncertainty in human preference judgement. This study uses an empirical case study of an Indian automobile organization to validate the applicability of the proposed model. The results show that the resource based strategy is in first position, having the maximum impact on each determinant. The case organization should improve the green management system with the assistance of a suitable GSCM strategy, i.e. the resource based strategy. This study may help managers to make decisions, and to analyze and standardize their environmental advantages dynamically. The robustness of the projected model is checked by conducting a sensitivity analysis. Copyright © 2018 John Wiley & Sons, Ltd and ERP Environment

Purpose The purpose of this paper is to identify and develop the relationships among the green supply chain management enablers (GSCMEs), to understand mutual influences of these GSCMEs on green supply chain management (GSCM) implementation, and to find out the driving and the dependence power of GSCMEs. Design/methodology/approach This paper has identified 35 GSCMEs on the basis of literature review and the opinions of experts from academia and industry. A nationwide questionnaire-based survey has been conducted to rank these identified GSCMEs. The outcomes of the survey and interpretive structural modeling (ISM) methodology have been applied to evolve mutual relationships among GSCMEs, which helps to reveal the direct and indirect effects of each GSCMEs. The results of the ISM are used as an input to the fuzzy Matriced’ Impacts Croisés Multiplication Appliquéeá un Classement (MICMAC) analysis, to identify the driving and the dependence power of GSCMEs. Findings Out of 35 GSCMEs 29 GSCMEs (mean⩾3.00) have been considered for analysis through a nationwide questionnaire-based survey on Indian automobile organizations. The integrated approach is developed, since the ISM model provides only binary relationship among GSCMEs, while fuzzy MICMAC analysis provides precise analysis related to driving and the dependence power of GSCMEs. Research limitations/implications The weightage for ISM model development and fuzzy MICMAC are obtained through the judgment of few industry experts. It is the only subjective judgment and any biasing by the person who is judging might influence the final result. Practical implications The study provides important guidelines for both practitioners, as well as the academicians. The practitioners need to focus on these GSCMEs more carefully during GSCM implementation. GSCM managers may strategically plan its long-term growth to meet GSCM action plan. While the academicians may be encouraged to categorize different issues, which are significant in addressing these GSCMEs. Originality/value Arrangement of GSCMEs in a hierarchy, the categorization into the driver and dependent categories, and fuzzy MICMAC are an exclusive effort in the area of GSCM implementation.

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