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Incorporating sustainable decisions with the retailer’s operational management has attracted enormous significance due to government regulations and customer demand for environmental consciousness. However, incorporating sustainable operations may interfere with the operational performance of the firm and, hence, retail companies need to examine the influence of these operations on overall supply chain efficiency. The present study develops a performance measurement model based on a two-stage network data envelopment analysis (DEA) technique for measuring the joint impact of sustainable operations and operational activities on the business performance of a retail company. A case study of an Indian electronic retail chain is presented to reveal the potentiality and suitability of the proposed models. The novelty of the paper lies in establishing DEA models for an Indian retail chain company and for providing an analytical understanding of the conditions under which the strategic decisions at the operational level successfully support the integration of sustainable operations into the SC management. The results show that the additional sustainable constraints lead to improved operational efficiency of some firms of the retail chain and result in improved business efficiency, while for other firms the integration of sustainable objectives decrease business efficiency. The significance of the study lies in providing efficient target conditions for inefficient retail stores to improve their performance. The findings of the study provide meaningful insights to Indian retailers venturing into sustainable retailing operations for enhancing the operational and business efficiency of the supply chain.

With growing competition in the market and dire need for sustainability, it has become imperative for companies to build long-term relationship with their supply chain partners through sustainable collaboration. Among these, the supplier–manufacturer relationship is crucial for improved organizational, business and sustainable performance. Sustainable collaboration with suppliers involves crucial decision-making processes such as continuous supplier monitoring and supplier development. Hence, a critical challenge that a company faces is to identify the key performance indicators (KPIs) for assessing the performance of a supplier for sustainable collaboration. In this regard, this study focuses on identification of KPIs for an Indian home appliance company through exhaustive discussions involving multiple decision-makers. Further, a grey-based decision-making trial and evaluation laboratory (DEMATEL) model is proposed in the study for analysing the importance levels among the fifteen KPIs based on multiple stakeholder perspectives. The results of the grey structural model indicate seven KPIs as influencing KPIs and eight KPIs as influenced KPIs. The KPI ‘Information disclosure’ has been identified as the most influential KPI for the evaluation of suppliers for sustainable collaboration. The implications drawn from the result analysis model can provide meaningful insights to managers for identifying strategies towards strengthening the supplier–manufacturer relationship and achieving organizational and market competence.

Increasing sustainability demands of stakeholders and government regulators are driving Food Manufacturing Companies (FMCs) towards embedding sustainability practices across the entire food value chain. This is most relevant in emerging economies such as India, as the sustainable growth of the food supply chain (SC) is predominantly dependent upon its multiple tiers of suppliers. Regrettably, the most impactful tier of suppliers, which are the grass-root suppliers, lie outside the reach of the sustainable efforts of the FMC. Significantly, the incorporation of the sustainability initiatives needs consistent and coordinated efforts of all the tiers of suppliers and stakeholders, especially in the current situation where a global pandemic badly hits farmers. This can be achieved by adopting Collaborative Sustainable Practices (CSPs) for channelization of joint efforts of FMC and stakeholders towards sustainability of grass-root suppliers using supply chain practice view. However, minimal documentation exists regarding the same, and the present study intends to fill this gap. Based on a case study of an Indian flour milling company, the focus of the research work is (1) identifying CSPs that FMC can adopt, (2) ascertaining the role of interim suppliers for ensuring sustainability up to the last tier of suppliers, and (3) developing a structural model utilizing combined efficiencies of Total Interpretive Structural Modeling technique and Fuzzy-MICMAC analysis, which the FMC can adopt for effectively implementing both the traditional practices as well as the CSPs. Through the result findings, decision-makers can visualize the impact and strength of each CSP and its interactions with other CSPs. It can enable them to cascade effective managerial responses into the respective tiers of SC for successful implementation of the CSPs and transmission of sustainability benefits to include the grass root suppliers. The study provides significant theoretical implications contributing to the existing literature on sustainability in a multi-tier food SC. Further, inputs to policy formulators for enhancing sustainability of farmers are outlined.

Sustainability consciousness among food manufacturers or transformers is one of the principal drivers for a sustainable food supply chain (SC) and it creates a possibility to enforce sustainability across all tiers of suppliers. This paper focuses on addressing sustainable supplier selection and optimal order allocation problem in agri-food SC. For this, an integrated bi-objective optimization model is developed in the study for configuring the SC network. It facilitates the selection of sustainable suppliers, allocates optimum order quantities among the selected suppliers, and determines flow of units across all the echelons of the SC network. The central focus is on enhancing the sustainable impact of the SC while keeping the SC costs at the minimum. The model developed in the study contains a three-phase comprehensive approach. The primary phase utilizes Best–Worst Method for evaluating and selecting sustainable suppliers based on economic, environmental, and sustainability criteria; the secondary phase involves formulation of a mixed-integer programming model for configuring the SC network and addressing the supplier selection and order allocation problem while aiming to achieve a compromised solution between the fuzzy objectives of minimization of cost and maximization of the sustainable value of purchase. In the final phase, fuzzy programming is effectively utilized for obtaining a compromised solution to the fuzzy bi-objective model utilizing real data of a case study from flour milling industry in India.

Reduction of excessive carbon emissions (CEs) is an acute challenge faced by manufacturing companies in operation of their Reverse Logistics (RL) networks, specifically in the developing nations. Hence, companies are realizing the importance of examining the carbon footprint across the network and attaining significant reduction through refurbishing, repair and recycling of their end of use and end of life products. This research contributes to the area of modeling reverse logistic network design problems, by developing a bi-objective optimization model under carbon tax scheme, for integrating strategic decision making at the design phase of the RL network. The carbon emissions due to each of the operational activities are considered and their corresponding costs along with investment in technology are also embedded in the model. The objectives of the model are: (1) profit maximization (2) carbon emissions minimization. The RL network design is configured as a mixed-integer programming problem model and fuzzy programming is utilized as solution methodology for obtaining a trade-off solution. A case of an Indian electrical and electronics remanufacturer is considered. The results furnishes valuable managerial and policy insights; (i) impacts of carbon tax on the strategic level of RL from an emerging economy perspective, (ii) optimal carbon price for maximum carbon emissions reductions per dollar increase in the total cost.

Reverse Logistics (RL) has become an important factor for manufacturing industries to gain competitive edge, address environmental concerns and enhance supply chain sustainability. Due to lack of expertise, financial support and resources, manufacturers prefer outsourcing all activities related to the return flow of products to Third Party Reverse Logistics Providers (3PRLPs). However, in the current scenario, with regard to being truly sustainable, manufacturers are considering possibilities of collaboration with the 3PRLPs in order to reap benefits of better customer satisfaction, reduced environmental impact and generation of additional revenue. Thus, it becomes essential to analyze plausible Critical Success Factors (CSFs) which can aid in realizing sustainable collaboration with 3PRLPs. With this perspective, the present study seeks to recognize and examine CSFs related to the implementation of RL under sustainable collaboration with 3PRLPs. Further it attempts to develop an analytical structural model to study the contextual relationship among the identified CSFs and determine the most influential CSFs with the aid of fuzzy Interpretive Structural Modeling (ISM). The results obtained from fuzzy-ISM are further used as an input to fuzzy Matrix Impact of Cross-Multiplication Applied to Classification (MICMAC) analysis to classify the listed factors into four groups on the basis of their driving and dependence power. The uncertainty in the decision making environment is handled effectively using fuzzy set theory. The analytical model developed in the study yields a practical tool for the supply chain managers to centre focus primarily on the CSFs which exert the maximum dominance, to ensure effective implementation of RL under sustainable collaboration.

Growing environmental issues, social concerns, enforced regulations and intense competition have motivated electronic companies to inculcate Reverse Logistics (RL) practices in action for sustainable Reverse Supply Chain (RSC). Due to lack of expertise and the heavy costs associated with the setting up of reverse logistics system, RL practices are widely embraced by most companies through Third Party Reverse Logistics Providers (3PRLPs). Due to the dependency of companies on 3PRLPs, the evaluation and selection of 3PRLP is a matter of strategic concern and requires critical decision-making. The main challenge in this regard that the companies face is to identify the appropriate criteria for assessing the performance of 3PRLP under a sustainable environment. In this sense, the main intent of the current study is to provide a systematic framework for an electronics company to (i) identify the most relevant 3PRLP performance evaluation criteria under three sustainability dimensions namely, economic, environmental and social, (ii) extract the most influential list of sustainable criteria and (iii) determine the weights of importance of the influential criteria. In order to attain this objective, a decision-making model is proposed in which firstly, the economic, environmental and social criteria are derived from an extensive literature survey. Secondly, Delphi technique is used to shortlist the most influential criteria. Thirdly, the Best Worst Method (BWM) is used to determine the importance of the shortlisted criteria. The result analysis shows that environmental sustainability is the primary focus of the companies for the implementation of RL, contrary to the assumption that economic performance is always the major motivation. ‘Quality’, ‘RL Practices’ and ‘Health and Safety’ are accorded the highest ranking under economic, environmental and social dimensions, respectively. The proposed model can assist electronic companies in determining the most important criteria for sustainable 3PRLP selection for outsourcing RL activities.

Retail sector around the world is going through a transition due to digitalization. Customers now demand convenience of online channel with instant fulfilment of offline channel. As a result, the concept of omni-channel retailing has come into existence. In omni-channel retailing, both the channels of a firm are fully or partially integrated. There are many strategies that may be developed by retailers for efficient functioning of the omni-channel retail chain. The choice of such a strategy depends upon the comparative benefits that can be derived from them. One such strategy gaining immense attention of retailers is the Buy Online Pickup in Store (BOPS) strategy. In order to understand this BOPS, we conducted a detail case study of an Indian multi-channel retail chain who is considering the option of launching BOPS option in few of its retail stores. The focus is to evaluate and select a fixed number of operational retail stores to also act as pick-up points for online deliveries. K-means clustering is utilized for formation of retail zones as per the number of retail stores to be selected. The retail stores in each zone are evaluated on the basis of a number of criteria such as demand, inventory carrying capacity, cost, and population characteristics using Analytical Hierarchy Process (AHP) and Complex Proportional Assessment-Grey (COPRAS-G). Based on these evaluations the best suitable retail store is selected for expansion from each zone. The result implications drawn in the study can provide an understanding of the future strategies that can be developed by the decision makers of the firm for launching the BOPS option. The study can also be beneficial to other Indian retail firms who can derive meaningful insights from the findings.

Product recovery, accompanied by cradle to cradle policies from the contemporary supply chain, becomes an essential element in meeting environmental compliance and waste management policies. Incorporation of reverse logistics into the traditional supply chains becomes a complementary factor for efficient product recovery. To begin with product recovery, consumers are encouraged to return their end-of-use/end-of-life products, and the steps of collecting and planning the movement of returned products are crucial decisions. The efficient planning of a cost effective recovery process in reverse logistics requires dealing with the uncertainty underlying in the quantity and quality of the returned products. In this paper, we propose establishing an initial collection point within a permissible radius of the customer zones to overcome some of the issues of uncertainty. The uncertainty in the quantity and quality of the returned products are modelled using fuzzy triangular numbers. To capture the real world conditions of the proposed problem, our model aims at maximizing the profit incurred in the recovery process in an uncertain environment. The model was solved with the help of fuzzy mathematical programming. The model is validated by a company case belonging to the manufacturing of electronic products. To increase the applicability of the product recovery process in the industry, we propose a recovery process for the planning horizon consisting of multi periods and multi products. The outcomes of the proposed model indicate that for the successful realisation of such network, customers need to be legally enforced to return their end of used products in the channels established for value recovery.

In the current scenario, sustainability is asserting a profound effect on the global Food Supply Chain (FSC). It is driven primarily by growing consciousness of consumers who want healthy food and at the same time, they demand that food production should not harm the environment. However, sustainability cannot be improved in isolation. It has to be a collaborative effort of all the players involved in the supply chain. This study is aimed at exploring the possibilities for agri-food sector of India to sustainably remunerate as good as its potential. From the perspective of a company engaged in production of an agri-food product, it is a challenging area of research to investigate into the decision-making methodologies which suit the requirements of the stakeholders as well as generate a positive sustainable impact on the FSC. In this study, a detailed analysis is done considering the present sustainable practices followed and scope for future strategies which can be adopted by its Production Plant (PP). This is achieved with the aid of Interpretive Structural Modeling (ISM) technique, a multi-criteria decision methodology and fuzzy-MICMAC analysis. A structured framework is obtained which shows the strength of the impact of each practice on the other. Using the result findings, it has been concluded that the PP must prioritize their efforts in taking measures for water reservation, pollution reduction, creating awareness among farmers and traders, and adopting sustainable employment practices. This research work can, hence, steer the focus of the company in the direction of appropriately prioritizing their sustainability practices for achieving a sustainable supply chain.

The concept of green manufacturing has gained cognizance among manufacturers due to regulations imposed by the government and rising environmental consciousness of customers. Acknowledging the fact that green manufacturing can yield long-term economic and environmental gains with significant efforts channelized toward green marketing, firms are reinventing their marketing strategies. Although many researchers have discussed the importance as well as theory building of green marketing, none have analyzed the strategies under multi-criteria environment and with multi-stakeholder perspective, which is the novelty of this study. Here, a real-life case of a manufacturing firm has been considered, who wants to select an appropriate green marketing strategy for promoting its newly introduced green product, from four available strategies, namely (i) Lean Green, (ii) Defensive Green, (iii) Shaded Green, and (iv) Extreme Green. The firm’s objective is to select the most appropriate strategy which is ideal for targeting green consumers. Integrated methodology of Fuzzy Analytical Hierarchy Process (Fuzzy AHP) and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) is implemented for strategy selection, based on criteria such as green market size, price parity, and top management’s commitment. It confirms accurate selection even with difference of opinion among stakeholders.

Amidst stiff competition, Small and Medium scale Enterprises (SMEs) need to continuously improve their supply chain sustainable performance. Due to customer pressure and government interventions, the focus has also shifted to enhancing the social and environmental performance of the SC. However, the challenge faced by SMEs is to identify the necessary socio-ecological key factors (KF)s required for a better sustainable performance and how to constantly assess the KFs for improving the SC performance. Hence, the research objective of the study is development of a decision model for assessing the social and environmental key factors or Indian SMEs and analyzing their interrelationships. To attain the research objective, the KFs for social and environmental performance are first identified through an extensive literature survey. Further, the KFs are evaluated using fuzzy-DEMATEL technique. The fuzzy-DEMATEL method is used to draw a directed graph for visibly capturing the causal relationships between the multiple KFs. The structural graph helps to portray a contextual relationship among 12 identified KFs including green market trends, business risk protection, and green collaborations. The result reveals that product responsibility and stakeholders’ involvement are both significant factors affecting other factors and play key roles in overall sustainable enhancement of SC for SMEs. The research is based on data collected from an electronics firm, analyzed to extract cause factors, which foster sustainability satisfaction from the SME’s perspective. The results of the study provide a benchmark for decision-makers to estimate the uncertain environment for developing a socio-ecological responsive and performance-driven SC.

The decision for facility location selection is an important one in the context of management of Supply Chain (SC). Facility location decision affects the overall SC performance, since there is an influence on the cost, delivery speed, service levels and effectiveness of SC. Hence it is essential to evaluate the impact of selection of each facility location. In addition to the traditional criteria such as market, labor, transportation, community and climate, Quality of Life (QOL) has also become an important factor for sustainable facility location selection decision. Since QOL includes aspects of social, economic, environmental, and psychological well-being therefore quantification of QOL for facility location evaluation is a challenging task. Due to subjectivity of the decision makers, vagueness sets in the decision making process and hence fuzzy decision making approach is required for handling the vagueness in assessment of QOL factor. Thus the present study considers an effective integrated approach using Fuzzy Analytical Hierarchy Process (FAHP) and Fuzzy Technique for Order Performance by Similarity to Ideal Solution (FTOPSIS) for evaluation of facility locations, considering the criteria of QOL. FAHP is used for calculating the weight of each QOL criterion and FTOPSIS methodology is used for computing the rank of the facility location options under the fuzzy environment. The application of this integrated approach is applied to case of an Indian manufacturing company.

Due to rising concerns for environmental sustainability, the Indian electronic industry faces immense pressure to incorporate effective sustainable practices into the supply chain (SC) planning. Consequently, manufacturing enterprises (ME) are exploring the option of re-examining their SC strategies and taking a formalized approach towards a sustainable partnership with logistics providers. To begin with, it is imperative to associate with sustainable forward and reverse logistics providers to manage effectively the upward and downstream flows simultaneously. In this context, this paper proposes an integrated SC network for the evaluation and selection of forward distribution partners (FDP) and third party reverse logistic providers (3PRLP) from a sustainable perspective of an Indian electronic ME. The sustainable evaluation of the logistic partners is performed using fuzzy analytic hierarchy process and the technique for order performance by similarity to ideal solution. The integrated logistics network is modeled as a bi-objective mixed-integer programming problem with the objective of maximizing the profit of the manufacturer and maximizing the sustainable score of the selected forward and reverse logistics providers. The novelty of the study is its ranking of the FDPs and 3PRLPs on the economic, environmental, and social dimensions of sustainability and the simultaneous integration of logistics outsourcing decisions for the forward and reverse flow of products. Goal programming approach is utilized to capture the trade-off between the conflicting objectives and to attain a satisfying solution to the bi-objective problem. The results indicate that integrating the strategic decisions of selection of logistics partners with the operational flow planning decisions can immensely improve the sustainable performance value of the SC network and secure reasonable profits. The managerial implications drawn from the result analysis provide a sustainable framework to the ME for enhancing its corporate image.

Immense concern for sustainability and increasing stakeholders’ involvement has sparked tremendous interest towards designing optimal supply chain networks with significant economic, environmental, and social influence. Central to the idea, this study aims to design a closed loop supply chain (CLSC) network for an Indian laptop manufacturer. The network configuration, which involves a manufacturer, suppliers, third party logistics providers (forward and reverse), retailers, customers and a non-government organisation (NGO), is modelled as a mixed integer linear programming problem with fuzzy goals of minimising environmental impact and maximising net profit and social impact, subject to fuzzy demand and capacity constraints. Profit is generated from the sale of primary and secondary laptops, earned tax credits, and revenue sharing with reverse logistics providers. The environmental implications are investigated by measuring the carbon emitted due to activities of manufacturing, assembling, dismantling, fabrication, and transportation. The social dimension is quantified in terms of the number of jobs created, training hours, community service hours, and donations to NGO. The novelty of the model rests on its quantification of the three triple bottom line (TBL) indicators and on its use of AHP–TOPSIS for modelling the multi-criteria perspectives of the stakeholders. Numerical weights for the triple lines of sustainability are utilized. Further, a fuzzy multi-objective programming approach that integrates fuzzy set theory with goal programming techniques is utilised to yield properly efficient solutions to the multi-objective problem and to provide a trade-off set for conflicting objectives. The significance of the CLSC model is empirically established as a decision support tool for improving the TBL performance of a particular Indian laptop manufacturer. Practical and theoretical implications are derived from the result analysis, and a generalised quantitative closed-loop model can be effectively adapted by other electronic manufacturers to increase their competitiveness, profitability, and to improve their TBL.

Increasing pressure from government and stakeholders has led manufacturing companies to initiate sustainable practices into their supply chains (SCs). Integrating practices like sustainable supplier selection, performance-based order allocation and carbon efficient distribution planning can immensely improve companies' sustainable image and hence provide a competitive edge. The current study focuses on the development of an integrated two-stage multi-attribute optimisation model to discuss these issues. In first stage, Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique based on grey numbers along with grey relational analysis (GRA) is utilised to evaluate suppliers' performance based on influential attributes. In the second stage, a multi-objective optimisation model was developed to optimise system's total cost, carbon emission and total value of purchasing (TVP) while contemplating delivery time windows. Weighted goal programming approach is utilised further for obtaining trade-off among multiple objectives. To validate the effectiveness of proposed methodology, a case study of an electronics company is considered.

Reverse logistics (RL) is a value proposition that goes beyond just cost reduction and customer satisfaction. It can be used as an efficient tool by manufacturers for overhauling their supply chain...

The Indian electronics industry is facing immense pressure to include sustainability practices in order to meet customer expectations, comply with legislation and create an edge over competitors. This growing need for inclusion of sustainability is driving original equipment manufacturers (OEMs) to collaborate with third-party reverse logistics providers (3PRLPs) to sustainably manage returns. Collaboration with 3PRLP will put OEMs in a stronger position regarding compliance with government legislation, improving upon their corporate image and customer satisfaction. It is a win-win situation for the OEM. On the other hand, from the 3PRLP's point of view, it is important to know the capabilities of the OEMs before entering into a collaborative endeavour. Hence, it is firstly necessary to identify the most appropriate attributes of the manufacturer which are essential for a sustainable collaboration. In this context, the study proposes a novel framework for investigating the performance attributes of the OEMs from the economic, environmental and social aspects of sustainability. Since the evaluation of each attribute for each dimension of sustainability differs in terms of the nature of the information needed and the time and resources required, it is necessary to conduct a pre-evaluation of the attributes using the Complex Proportional Assessment (COPRAS) method. Furthermore, the shortlisted attributes for each sustainability dimension are evaluated and prioritized using the best worst method (BWM). The novelty of the attribute selection process lies in simultaneously considering the degree of importance of the attribute as well as the degree of difficulty of the collection of data required for the assessment of the OEM. The result of this study helps decision-makers and practitioners to comprehend the most influential attributes of OEMs which are crucial for collaboration, thus enhancing the overall sustainability impact of the supply chain. The managerial implications drawn from the resulting analysis provide the 3PRLP with a sustainable evaluation framework which can be ideally used for the selection of collaborative partners. The above model is validated using the case of an Indian 3PRLP company that handles electronic products.

Increasing consumer consciousness along with urbanization, trade globalization, and agro-industrialization in the last few years has led to an exponential growth of sustainability in food supply chains (FSCs). In order to withstand competition, manufacturing enterprises are implementing proactive strategies to accelerate their sustainability performance. However, there are many barriers in the effective execution of sustainable FSC in India. Understanding the impact of these barriers will help the manufacturers in effectively utilizing their resources and attaining an environmental and social FSC. The main focus of the paper is to identify the dominant barriers, which create hindrance in the adoption of the sustainability in the Indian food industry. Further, the relationship between the barriers is defined, and the most dominant barriers are classified from the suggested barrier list using interpretive structural modeling (ISM). The outcome of ISM has been taken as an input for MICMAC analysis, which classifies the barriers based on their driving and dependence power. The proposed integrated structural model will be helpful in comprehending the mutual relationships and dependencies among the barriers in the diffusion and implementation of sustainability in FSC. The suggested framework can be used as a tool by decision-makers to systematically overcome the barriers and develop strategies toward incorporation of sustainability in Indian food industry.

Background: Designing and implementation of reverse logistics (RL) network which meets the sustainability targets have been a matter of emerging concern for the electronics companies in India. Objectives: The present study developed a two-phase model for configuration of sustainable RL network design for an Indian manufacturing company to manage its end-of-life and endof-use electronic products. The notable feature of the model was the evaluation of facilities under financial, environmental and social considerations and integration of the facility selection decisions with the network design. Method: In the first phase, an integrated Analytical Hierarchical Process Complex Proportional Assessment methodology was used for the evaluation of the alternative locations in terms of their degree of utility, which in turn was based on the three dimensions of sustainability. In the second phase, the RL network was configured as a bi-objective programming problem, and fuzzy optimisation approach was utilised for obtaining a properly efficient solution to the problem. Results: The compromised solution attained by the proposed fuzzy model demonstrated that the cost differential for choosing recovery facilities with better environmental and social performance was not significant; therefore, Indian manufacturers must not compromise on the sustainability aspects for facility location decisions. Conclusion: The results reaffirmed that the bi-objective fuzzy decision-making model can serve as a decision tool for the Indian manufacturers in designing a sustainable RL network. The multi-objective optimisation model captured a reasonable trade-off between the fuzzy goals of minimising the cost of the RL network and maximising the sustainable performance of the facilities chosen.

Establishment of a closed loop supply chain (CLSC) network has attracted immense significance due to government policies and societal demand for environmental consciousness. However, to enhance the financial and ecological impact of the network, the forward and reverse supply chain networks must integrate well so that decisions taken in both areas complement each other. In this study, we propose an eco-efficient CLSC design for extending the existing supply chain of an Indian firm that assembles inkjet printers. The network design is configured as a multi-objective model in a multi-period setting and is mathematically formulated into a mixed integer programming problem with fuzzy objectives. Fuzziness provides flexibility to the decision makers because they must accommodate the conflicting nature of the objectives. The fuzzy multi-objective model incorporates the firm's economic and environmental concerns into the decision making process by selecting environmentally responsible suppliers to procure components based on sustainable criteria, choosing appropriate recovery options for end-of-use (EOU) inkjet printers, and planning an efficient transportation network design for reducing the carbon emission of the distribution and collection activities. The uniqueness of the proposed fuzzy CLSC optimization model lies in providing an integrated decision making framework that can aid the manufacturer in making crucial strategic, tactical, and operational decisions of optimal selection of suppliers, component order allocation, recovery flow allocation, and vehicle routing planning. The novelty of the model also lies in simultaneously minimising the overall cost of the activities undertaken, maximizing the performance of the component suppliers and minimising the carbon emissions of the associated transportation activities. A weighted fuzzy mathematical programming approach is utilised for generating a fuzzy, properly efficient solution as the desired compromised solution for the CLSC network problem configuration. The relevance of the model is justified using a real data set derived from a case study of the firm based in the northern capital region (NCR) of India. The findings indicate that the proposed integrated CLSC network model enables the firm in gaining sustainably from the numerous electronic product reuse opportunities in the Indian market. Further, while costly to begin with, choosing suppliers with higher sustainable performance and vehicles with lesser emission rate could substantially enhance firm's sustainable image and result in higher profits in the future.

Due to intensification of market competence and customers increasing socio-environmental concerns, sustainability has become a focal point for most organizations. Thus incorporation of customer sustainable expectations into the conventional supplier selection process has become necessary for manufacturers to sustain in the competitive market. To cope with this issue, it is necessary to model the customers’ opinions and expectations into the strategic supplier selection and order allocation decision making, an area not delved upon much in the literature. Therefore, the aim of the study is to develop an analytical model for manufacturing firm for selection of suppliers based on customers’ expectations which are reflected as retailers’ expectation level and also for bringing in financial and socio-environmental stability to the whole SC. The research methodology adopted involves 1) use of fuzzy-TOPSIS technique using Z numbers for evaluation of suppliers based on traditional as well as social environmental attributes which reflect customer's social and green expectations, 2) development of a novel bi-objective mathematical model for selecting suppliers meeting the expectation levels, allocating orders proportionate to the performance scores of the suppliers, rewarding or penalizing the suppliers as per their sustainable performance, 3) Transformation of the bi-objective model into a weighted goal programming model for attaining a trade-off solution between the objectives of minimization of cost and maximization of sustainable value of purchase. To exemplify the efficacy of the model, case of electronics sector is presented. The findings of the result suggest that penalty and reward value incorporated in the cost objective system is effective in enhancing the sustainable performance of the suppliers and can prove to be an effective strategy for DMs. The study recommends that the proposed mathematical model can considerably aid the manufacturer in integrating supplier selection and order allocation decisions while optimizing the performance of the customer oriented supply chain. Keywords: Customer sustainable expectations, FTOPSIS, Z-numbers, Supplier selection, Goal programming

Retail plays an important role in creating a link between upstream stages of a supply chain and the end customers. Supply chains can create higher customer value and competitive advantage if retailers are capable of extending their capabilities and performance. It is imperative for retail businesses to monitor their performance based on appropriate performance measures and devise strategies for continuous improvements. This study presents the methodology for selection of performance assessment measures integrating fuzzy Delphi and data envelopment analysis (DEA) selective measure methods; and then compute the relative efficiency of multiple stores of an Indian Electronics retail chain following the DEA method. The overall performance of a retail chain rest on the individual store's performance and hence it is all the more important for the inefficient stores to benchmark the performance of the efficient stores. Subsequent to efficiency measurement, super efficiency scores are computed to rank the efficient stores and input/output slack are determined for inefficient stores to help practitioners in planning strategies for benchmarking and performance enhancement.

Increased competition, higher profits, and drive toward sustainability are motivating third party revere logistics providers (3PRLs) to seek strategic alliances with original equipment manufacturers (OEMs) for recovering maximum value from product returns. With emphasis on combining technological capabilities, enhancing performance levels, developing a fast redistribution system, and addressing common sustainable concerns, a successful partnership can be achieved between the 3PRLs and OEMs. An alliance between the OEM and 3PRL is such that either the OEM outsources all its reverse logistics (RL) activities to the provider or both parties collaborate for jointly planning and executing the RL operations through mutually shared infrastructure and facilities while sharing profits. However, from 3PRL provider’s perspective, a long-term view is needed to anticipate the economic viability of a collaborative system before entering into a logistics relationship with the manufacturers. As our contribution to the existing literature, we propose a fuzzy integer nonlinear programming model which can be used as a decision tool by 3PRLs for making this key decision of enhancing sustainability of the product recovery design. The proposed model is designed with the main objective of maximizing the profit generated by the multi-echelon RL network while analyzing the nature of the alliance to be formed between the OEMs and 3PRLs for each product to be recovered. The model also determines which clients (manufacturers) and how many clients to be acquired for maximum profitability. The core focus of the research is to exploit the maximum recoverable potential of the product returns and achieve a socially and environmentally sound and yet profitable RL system. The proposed model is validated by considering case study of a 3PRL offering product recovery services such as collection, repair, refurbishing, dismantling, and redistribution to manufacturers of electronic equipments.

Adoption of reverse logistics practices in existing supply chains has emerged as an important incentive for manufacturers to gain financial and competitive advantage. Growing environmental and social concerns are driving firms to incorporate sustainable strategies into designing of their reverse supply chain (RSC) network. A sustainable RSC can be attained by following the triple bottom line (TBL) philosophy i.e. economical, social and environmental development. In this paper, we develop a sustainable reverse logistics model for laptop manufacturers for handling of end-of-life (EOL) and end-of-use (EOU) product returns. In the first stage of the model, a hybrid method using Analytical Hierarchy Process (AHP) and the Fuzzy Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) based on the criteria of TBL is applied to calculate weights for the three dimensions of sustainability. In the second stage, a three objective mixed integer linear programming model is developed in fuzzy environment which minimises the total cost, the environmental impact (in terms of CO 2 e emissions) and maximises the social impact of the network utilising the weights of the objectives from the first stage. The social sustainability is tacked in the model by the management of social resources including training for the workers, fixed jobs as well as inclusion of variable jobs based on the quantity of returns. The model is validated through a case study and its societal, economical and environmental impact is discussed.

Efficient integration of forward and reverse logistics network is significant for optimising the economic and ecological value of a closed-loop supply chain network (CLSCN). There is also a high measure of uncertainty involved in such networks and must be handled appropriately in the decision-making process. In this study, we propose a fuzzy optimisation model for improving a CLSCN for handling end-of-life (EOL) and end-of-use (EOU) products. Manufacturer uses fabricated components obtained from the recovery processes and procures new components from external suppliers to assemble new products. Suppliers are evaluated using ANP and are assigned weights. Environmental concerns are also addressed by the model by ensuring that the carbon emission due to transportation does not exceed the permissible carbon cap. To achieve this, hybrid distribution-cum-collection centres (HDC) are grouped into optimal clusters. Products are carried along optimal routes within these clusters using travelling salesman problem (TSP). A fuzzy multi-objective mixed integer linear programming model is proposed which aims at minimising cost of the network and maximising weights of suppliers. A case study of printers is considered to validate the model.

Increase in environmental concerns and consumer awareness together with imposition of government regulations are forcing electronic industries to set up their own reverse logistics network. An evaluation of the impact of their reverse logistics activities is also imperative for the design of an effective and efficient reverse supply chain. This paper presents a bi objective mixed integer linear programming model for a reverse logistics network design that considers value added recovery of return of end of life (EOL) products and also focuses on controlling the transportation activities involved in the reverse logistics system, a major contributor to the increase in carbon emission. The objectives are to maximise the product’s value recovery by determining the optimum flow of products and components across facilities in the network and minimise the carbon emission by determining the optimum routes to be taken by vehicles and by appropriate selection of vehicles. The reverse logistics model developed is goal programming model and it takes into account two objectives with almost equal weightage. The model captures the trade-offs between total profit and emission of CO2. The model is justified by a case study in the context of the reverse logistics network design of an Indian company manufacturing air conditioners and refrigerators.