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Configuration of sustainable supply chains for agricultural products has been a well-known research field recently which is continuing to evolve and grow. It is a complex network design problem, and despite the abundant literature in the field, there are still few models offered to integrate social impacts and environmental effects to support network design decision-making to support the configuration of the citrus supply chain. In this work, the citrus supply chain design problem is investigated by integrating the production, distribution, inventory control, recycling and locational decisions in which the triple bottom lines of sustainability, as well as circularity strategy, are addressed. Accordingly, a novel multi-objective Mixed-Integer Linear Programming (MILP) model is proposed to formulate a multi-period multi-echelon problem to design the sustainable citrus Closed-Loop Supply Chain (CLSC) network. To solve the developed model, the ε-constraint approach is employed in small-sized problems. Furthermore, Strength Pareto Evolutionary Algorithm II (SPEA-II) and Pareto Envelope-based Selection Algorithm II (PESA-II) algorithms are used in medium- and large-sized problems. Taguchi design technique is then utilized to adjust the parameters of the algorithms efficiently. Three well-known assessment metrics and convergence analysis are regarded to test the efficiency of the suggested algorithms. The numerical results demonstrate that the SPEA-II algorithm has a superior efficiency over PESA-II. Moreover, to validate the applicability of the developed methodology, a real case study in Mazandaran/Iran is investigated with the help of a set of sensitivity analyses.
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Algoritmos , Irã (Geográfico)RESUMO
The inadequate reuse and recycle of construction and demolition waste (C&DW) has been identified as a major issue, as it implies the depletion of natural aggregates, massive occupation of landfill and inefficiency of construction industry. However, a holistic view involving economic, technical and comprehensive dimensions has rarely been adopted for C&DW utilization evaluation against both qualitative and quantitative criteria. In this study, we propose a framework in a heterogeneous group decision-making environment to solve the C&DW utilization mode selection problem by integrating the Choquet integral and the elimination and choice translating reality (ELECTRE) method with two data forms, that is, interval-valued hesitant fuzzy numbers and real numbers. Firstly, an evaluation index system is constructed to assess multiple representative C&DW utilization modes in Xi'an, China. Secondly, a novel method is proposed to apply the Choquet integral for aggregation of evaluation values and fuzzy ELECTRE for outranking of C&DW utilization modes after the heterogenous evaluation data are unified into interval numbers. Thirdly, to illustrate the application of the proposed framework, this paper evaluates four typical C&DW utilization modes based on a case study in Xi'an, China, and the result shows that the most preferable mode is A3 (off-site crushing, roadbed backfilling). Finally, a comparative analysis is conducted to verify the effectiveness of this framework. This study presents useful findings to C&DW practitioners and can help avoid intuitive selection among available C&DW utilization modes.
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Indústria da Construção , China , Materiais de Construção , Tomada de Decisões , Lógica Fuzzy , Reciclagem , Instalações de Eliminação de ResíduosRESUMO
Logistics is critical in every company's supply chain (SC), and outsourcing helps businesses concentrate on their core competencies. Third-party logistics (3 PL) or logistics service providers (LSPs) assist businesses in cutting costs while improving performance, sustainability, and revenue. Logistics evaluation and LSPs choice are complicated and critical components of value delivery. This study aims to review logistics outsourcing literature to understand the trends, prospects, factors, and strategies used in logistics companies' outsourcing choices. This work examines the literature on LSPs selection published between 2010 and 2023. This paper uses VOSviewer (version 1.6.19) to visualize the relationships. Pricing, timely shipment, service quality, reliability, agility, technology, and consumer feedback are the most commonly utilized, whereas societal and environmental factors are seldom used. The study comprises journal publications, the year, selection criteria, and assessment methodologies. Numerous scholars have discovered and employed many critical selection criteria. Many investigators have also embraced multi-criteria decision-making (MCDM) methodologies, and their fuzzy form is widely used. In conclusion, recommendations for theorists and managers, limits, and future directions for research are offered.
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In recent years, the area of supply chain resilience has received heightened attention as a plethora of new risks, ranging from climate change to cybersecurity and infectious diseases, have emerged as serious threats to operational performance. The COVID-19 pandemic, in particular, has exposed the fragility of global supply chains in many sectors. Given these concerns, supply chain networks, including those designed based on the principles of lean philosophies, are increasingly being re-examined as firms grapple with the challenge of strengthening the capacity to withstand, absorb, and rebound from unexpected shocks. Addressing the urgency of this imperative, this study presents a novel framework-based on theories and concepts in the systems engineering (SE) and supply chain resilience domains to enhance the resilience implementation capabilities that are lacking in many of today's firms. By applying a Grounded Theory methodology, this study develops and validates a conceptual model that identifies six core attributes fundamental to developing resilience capabilities in complex supply chains. The study concludes by providing examples of, and insights into, the role of these attributes in building supply chain resilience.
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This paper studies how consumers' psychological factors influence their intentional purchasing behavior towards eco-labeled products and investigates why consumers choose eco-labeled products. Based on the Theory of Planned Behavior, we develop an extended model including six constructs. Among these constructs, consumers' intentional purchasing behavior, attitude towards the behavior, subjective norm, and perceived behavioral control are applied from the original theoretical framework. Health consciousness and environmental awareness are integrated additionally to reflect consumers' concerns about the natural environment and their health. Next, we conduct and analyze a survey-based empirical study with 336 samples using the Structural Equation Modeling. Our findings show that consumers' attitude towards the behavior is positively influenced by environmental awareness, but the effects of it on intentional purchasing behavior are insignificant. Also, subjective norm has a positive influence on intentional purchasing behavior, but its effects on attitude towards the behavior are not significant. Moreover, the results also show that the total effects of health consciousness on intentional purchasing behavior are significantly higher than the effects of environmental awareness. Our results can provide a reference for business managers to attract consumers through eco-labeling as well as government policymaking.