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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.

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.

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.

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.

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.