Strategic sourcing model for green supply chain management: an insight into automobile manufacturing units in India

Abstract

PurposeSupplier selection (SS) is one of the prime competencies in a sourcing decision. Taking into account the key role played by suppliers in facilitating the implementation of green supply chain management (GSCM), it is somewhat surprising that very little research attention has been imparted to the development of a strategic sourcing model for GSCM. This research aims to develop a strategic sourcing framework in which supplier organizations are prioritized and ranked based on their GSCM performance. Accordingly, the benchmark organization is identified and its strategy is explored for GSCM performance improvement.Design/methodology/approachThe research develops an innovative GSCM performance evaluation framework using six parameters, namely, investment in corporate social responsibility, investment in research and development, utilization of renewable energy, total energy consumption, total carbon-di-oxide emissions and total waste generation. An integrated multicriteria decision-making (MCDM) approach is proposed in which the entropy method calculates criteria weights. The Complex Proportional Assessment (COPRAS) and the Grey relational analysis (GRA) methods are used to rank supplier organizations based on their performance scores. A real-world case of green supplier selection (GSS) is considered in which five leading India-based automobile manufacturing organizations (Supplier 1, Supplier 2, Supplier 3, Supplier 4 and Supplier 5) are selected. Surveys with industry experts at the strategic, tactical, and operational levels are carried out to collect relevant data.FindingsThe results reveal that total carbon dioxide emission is the most influential parameter, as it gains the highest weight. On the contrary, investment in research and development, and total waste generation have no significant impact on GSCM performance. Results show that Supplier 5 secures the top rank. Hence, it is the benchmark organization.Research limitations/implicationsThe proposed methodology offers an easy and comprehensive approach to sourcing decisions in the field of GSCM. The entropy weight-based COPRAS and GRA methods offer an error-free channel of decision-making and can be proficiently used to outrank various industrial sectors based on their GSCM performances. This research is specific to the automobile manufacturing supply chain. Therefore, research outcomes may vary across supply chains with distinct characteristics.Practical implicationsThe basic propositions of this research are based on a real-world case. Hence, the research findings are practically feasible. The less significant parameters identified in this study would enable managers to impart more attention to vulnerable areas for improvement. This research may help policymakers identify the influential parameters for effective GSCM implementation. As this research considers all aspects of sustainability, the strategies of the benchmark supplier have a direct impact on organizations' overall sustainability. The study would enable practitioners to make various strategies for GSCM performance improvement and to develop a cleaner production system.Originality/valueThe originality of this research lies in the consideration of both economic, social, environmental and operational aspects of sustainability for assessing the GSCM performance of supplier organizations. Quantitative criteria are considered so that vagueness can be removed from the decision. The use of an integrated grey-based approach for developing a strategic sourcing model is another unique feature of this study.

Green Supplier Selection in the Automobile Industry: A Comprehensive Framework for Multi-Criteria Decision Analysis

“…As discussed earlier, this research intends to incorporate Environmental, economic, and operational criteria into the GSS process, which are enlisted in Table 3. Use of eco-friendly packaging material P12 Environmental Weber et al [47] Top management commitment for GSCM implementation P13 Environmental Sahoo et al [10] Design for proper utilization of resources P14 Operational Ghosh et al [11] Thereafter, a structured questionnaire [28] is prepared to capture a speci c set of queries regarding the GSS problem. It comprises of three parts namely, the general part, the technical part, and the miscellaneous part.…”

“…Under this category, more than one stand-alone method is integrated in order to achieve more precise and valid outcomes. Some of the widely used methods are AHP-grey relational analysis (GRA) [67], entropy-TOPSIS [7], AHP-Entropy-TOPSIS [56], AHP-VIKOR [34], AHP-ELECTRE [36], AHP-WASPAS-multi-attributive border approximation area comparison (MACBAC) [2], ANP-grey-decision making trial and evaluation laboratory (DEMATEL) [68], entropy-COPRAS-GRA [11], entropy-TOPSIS-COPRAS-GRA [8], BWM-WASPAS-COPRAS [69], and so on. Unfortunately, the main disadvantage of such methods is failing to cope with various kinds of uncertainties, especially human bias that is common in practice.…”

“…However, prior research proved that both nancial and environmental performance can be improved signi cantly by implementing various GSCM practices, such as green purchasing, green design, green manufacturing, green transportation, green marketing, and so on [9,10,62]. An organization's GSCM performance depends on not only its internal green initiatives but also its suppliers' green practices [11]. As organizations tend to outsource a variety of jobs, GSS, as an integral part of GSCM, has a critical role in guiding organizations to maintain their strategic stance in market [12].…”

An integrated mathematical model based on grey optimal ranking for supplier selection considering pandemic situation

“…In the first stage of their work, they identified the criteria that influence supplier selection in the polyethylene industry, and, in the second stage, suppliers are selected in a green supply chain using multi-criteria decision-making. A similar study was also conducted by Ghosh et al [ 18 ], where they developed a GRA based strategic sourcing framework in which supplier organizations are prioritized and ranked based on their green supply chain performance. Through a case study in a food manufacturing company, Leong et al [ 31 ] identified seven criteria for a resilient supplier selection framework and determined the importance of these criteria by GRA.…”

Managing multi-sided platforms in an emerging country: challenges, critical success factors and contrasts with traditional companies

“…For instance, Chakraborty et al (2018) aimed to explore the potential and capability of different nontraditional machining (NTM) processes and employed GRA to present a multi-objective optimization technique considering three NTM processes. Yurtyapan and Aydemir (2022) studied the issue of ERP software selection and collected data from four experts, whereas Ghosh et al (2022) between industrial characteristics and innovation capabilities and used GRA to draw a ranking considering five high-tech industries.…”