• Energy Research

The growing interest in sustainability increases the challenges for decision makers in selecting the sustainable suppliers in which consider economic, environmental and social aspects. Particularly, decision makers are being increasingly motivated to improve their supply chain activities in coping efficiently with the objectives of sustainable development. Where the era of sustainability threatens the current supply chain partners to either cope with the new regulations of sustainability or leave the field for new players. Notwithstanding, most of the recent studies considered economic and green criteria in handling sustainable supplier selection and order allocation (SSS/OA) problems overlooking the social criteria which represents the third pillar of sustainability. This work aims at putting forward a hybrid Multi Criteria Decision-Making (MCDM)-Fuzzy Multi-Objective Optimization (FMOO) approach for a sustainable supplier selection and order allocation problem by considering economic, environmental and social criteria. Thus, an integrated Fuzzy AHP-Fuzzy TOPSIS is proposed to assess and rank suppliers according to three sets of criteria (i.e. conventional, green and social). A Multi-Objective Optimization Model (MOOM) is developed for choosing suppliers and allocating the optimal order quantities. To cope with the multiple uncertainties in the input data, the MOOM is reformulated into a Fuzzy Multi-Objective Optimization Model. The ε-constraint and LP-metrics approaches are used to reveal two sets of Pareto solutions based on the developed FMOO model. Finally, TOPSIS is applied to select the final Pareto solution that is closest to the ideal solution and furthest from the nadir solution. The effectiveness and the applicability of the developed hybrid MCDM-FMOO approach is demonstrated through a case study.

Abstract Determining solar power initiatives and developments for a country as large as India is difficult due to the involvement of different enablers. The decisions of these enablers will influence the formulation of strategies to encourage solar power development in India. The present research work critically analyzes Indian solar power developments to recognize and to evaluate key enablers that will encourage greater usage in India׳s current scenario. A literature review that explores the Indian solar power sector is included, with a focus on need potential, and an examination of the key enablers. This work identifies sixteen solar power enablers based on relevant literature and experts׳ inputs. To evaluate and to categorize the recognized solar power development key enablers, a fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) based methodology is utilized. The fuzzy DEMATEL approach is useful in dealing with the inherent ambiguity involved in studying interrelationships among the evaluated enablers. Research findings suggest that Initiatives taken at the state level (E7) and Power sector reforms (E12) have significant influence in adopting and encouraging India׳s solar power development. In this research, the enablers׳ causal relationships and their interactions are examined, and the findings are useful to encourage solar power development initiatives and decisions. This work will help policymakers formulate decisions to initiate and encourage solar power developments in India.

Environmental issues have been worldwide matters of concern especially in the recent decade and have made many firms implement end-of-life strategies such as remanufacturing. In prior studies, the supply side of remanufacturing supply chain has been vastly brought into focus compared to the demand side. Motivational factors that encourage consumers to purchase remanufactured products are getting firms attentions in developing effective marketing strategies to assist them being more productive in the current competitive market. However, consumer acceptance of remanufactured products has been regarded as one of the main reasons why remanufacturing has remained a majorly untapped opportunity for improving supply chain productivity.

Abstract Industries face significant pressures to enact eco-friendly practices in their supply chain due to the constraints of natural resources and growing ecological awareness among customers. Reverse logistics (RL) has been considered as a systematic approach for industries to improve their environmental impacts and to ensure sustainability in business. Industries are enthusiastic to adopt RL activities in their businesses, but they also face challenges such as insufficient knowledge and resources regarding RL implementation. Therefore, we seek to evaluate the critical success factors (CSFs) linked to the implementation of RL in manufacturing industries in India. In this work, a structural model is proposed by using Analytical Hierarchy Process (AHP) and Decision Making Trial and Evaluation Laboratory (DEMATEL) methods to evaluate the CSFs in RL adoption. The AHP methodology assists in establishing the priorities of the CSFs, while the DEMATEL approach categorizes the causal relationships among them. The findings of this work shows that the Global competitiveness main factor is highly prioritized, and thus, needs to be focused greatly in order to increase the effectiveness of RL adoption in business. The relative priority of the remaining main factors through AHP analysis is given as Regulatory factors - HR and organizational factors -Economic factors - Strategic factors. The findings also indicate that Global competitiveness; Regulatory; HR and organizational main factors are classified under cause group, while Economic and Strategic main factors belong to effect group. This model will help business analysts and supply chain managers formulate both short-term and long-term, flexible decision strategies for successfully managing and implementing RL adoption in the supply chain scenarios.

Due to increased customer knowledge and ecological pressures from markets and various stakeholders, business organizations have emphasized the importance of greening and sustainability in their supply chain through supplier selection. Therefore, a systematic and sustainability-focused evaluation system for supplier selection is needed from an organizational supply chain perspective. This work proposes a framework to evaluate sustainable supplier selection by using an integrated Analytical Hierarchy Process (AHP), ViseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), a multi-criteria optimization and compromise solution approach. Initially, 22 sustainable supplier selection criteria and three dimensions of criteria (economic, environmental, and social) have been identified through literature and experts' opinions. A real world example of an automobile company in India is discussed to demonstrate the proposed framework applicability. According to the findings, ‘Environmental costs,’ ‘Quality of product,’ ‘Price of product,’ ‘Occupational health and safety systems,’ and ‘Environmental competencies’ have been ranked as the top five sustainable supplier selection criteria. In addition, out of the five sustainable supplier's alternatives, supplier number ‘three’ got the highest rank. The work presented in this paper may help managers and business professionals not only to distinguish the important supplier selection criteria but also to evaluate the most efficient supplier for sustainability in supply chain, while remaining competitive in the market. Sensitivity analysis is also conducted to test the proposed framework robustness.

With the passage of time, the grains supply chain may go out of optimality and be disrupted, so it is necessary to redesign the supply chain to avoid incurring irreparable costs. Because of the occurring grain supply chain sub-optimization event as time passes, this paper redesigns a wheat-flour-bread supply chain network considering sustainable development under uncertainty. For this reason, both facility and transaction networks are investigated, and newly redesigned networks are presented. First, a new definition of sustainable development pillars in supply chains is proposed, and then a four-objective mixed-integer linear programming model is presented. Due to uncertainties in the economic, environmental, social, and technical parameters of the presented model, a robust optimization method is developed to deal with them. Then, an augmented weighted Tchebycheff method, followed by the Lagrangian relaxation algorithm, is applied for solving the four-objective model. Next, a real-case study is performed to appraise the efficiency of the model. Finally, a sensitivity analysis is conducted on the critical parameters of the model to analyze the behavior of different objective functions. With the model's solution, the redesign of the supply chain provides an enhancement in the economic, environmental, social, infrastructural, and final objective functions by about 18, 23, 31, 37, and 20%, respectively.

Abstract Indonesia is facing a number of independently managed challenges related to the collection, transportation, processing (composting, recycling), and landfill dependence on waste management. An intervention is needed to bring stakeholders together to solve these waste challenges. The objectives of this study are to investigate the fundamental issues and opportunities and to develop a sustainable and smart country-wide waste management system using industry 4.0 technologies. The system should provide a multi-dimensional approach, determine the maturity level of the waste management system in a technical method, and pursue the goal of designing a new strategy to minimise waste management problems. A comprehensive systematic literature review, intensive focus group discussions, and direct observation in Indonesian cities were approaches used to develop waste management business processes and their system design. Waste business processes consist of mixed-collecting, sorting, transporting, varied-treatment, and chained-disposal. The design of the proposed waste management system presents circular economy processes that can separate municipal waste, identify waste characteristics, and determine sustainable waste treatment technologies through the use of Internet of Thing (IoT) as the integrator. This study contributes to the sustainable development goals (SDG’s) such as Good health, and wellbeing (SDG 3); Clean water and sanitation (SDG 6); Decent Work and Economic Growth (SDG 8); Responsible Consumption and Production (SDG 12) and Climate Action (SDG 13). The study proposes a new design of smart and sustainable waste management which could achieve satisfactory economic, social, and environmental waste management performances.

The aim of this research is to verify the relationship between the maturity levels of environmental management and the adoption of green supply chain management (GSCM) practices by electro-electronic companies in Brazil. In this work a two-phase research was conducted, with one quantitative and the other qualitative. The quantitative phase aimed to test whether a relationship between the maturity levels of environmental management and GSCM exists, while the qualitative phase tried to detail the characteristics of this relationship. The quantitative phase was conducted through a survey with 100 Brazilian electro-electronic companies and the collected data were processed using Structural Equation Modeling. For the qualitative phase, a multiple case study was conducted with three companies located in Brazil. The results indicate that: (1) The main hypothesis was confirmed and considered statistically valid, indicating that, indeed, the maturity level of environmental management influences the adoption of GSCM practices; (2) a coevolution tends to occur between the environmental maturity and the GSCM practices; that is, the more developed is the company's environmental management, more complex GSCM practices are adopted; and (3) the GSCM internal practices tend to present a greater relative adoption than the external practices; these external practices of GSCM tend to be adopted when the company is inserted in a higher environmental stage and/or operates under a scenario of stronger normative environmental pressure. By the way, this is the first research mixing survey and case studies on GSCM in Brazil.

Abstract Generally, in Home Health Care (HHC) logistics, caregivers which are started from a pharmacy are scheduled and routed to do different care services at patients' home. At the end, they go to their laboratory to update the patients' health records. In addition to scheduling and routing of the caregivers, there are some other optimization decisions which can increase the competitive advantages of HHC organizations as a supply chain network. The location decisions of the pharmacies and laboratories and the assignment of patients to the nearest pharmacies are two of the several important logistics factors for an HHC organization. The literature shows that the green emissions and sustainability achievements for HHC logistics are still scarce. To cover more logistics and sustainability factors and make the HHC more practical, this study contributes a Green Home Health Care Supply Chain (GHHCSC) for the first time by a bi-objective location-allocation-routing model. Already applied successfully to this research area, the Simulated Annealing (SA) is also employed in this study. Another main innovation of this paper is to propose a set of new modified SA algorithms to better solve the proposed NP-hard problem. As a bi-objective optimization model, the epsilon constraint method is also utilized to check the algorithms’ results in small sizes. By using some multi-objective assessment metrics, the algorithms are compared with each other and their performance is evaluated. As such, some sensitivity analyses are performed to reveal the efficiency of the developed model. Finally, some managerial insights are deployed to achieve the sustainability for the HHC organizations.