Sustainable Operations and Computers最新文献

The ongoing Russia-Ukraine conflict has made the global energy crisis a severe issue, particularly for emerging economies with a sharp rise in load shedding in communities, disruptions in industrial operation, and an increased cost of living. Shifting our focus from fossil fuel-based energy to sustainable and promising renewable energy sources, like geothermal energy (GE), is crucial to addressing the ongoing energy crisis. Therefore, this study aims to evaluate the significant factors influencing the adoption of GE to support the national grid of an emerging economy like Bangladesh. An integrated framework consisting of the Delphi method, fuzzy total interpretive structural modeling (TISM), and fuzzy Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) analysis was utilized in this study to evaluate the hierarchical interrelationships among the significant factors. The findings indicate that the top two influencing factors are the “scope for new investments and employment” and the “growing need for inexpensive and renewable energy sources”. The study's findings can offer significant insights to decision-makers and policymakers, which can aid in the development of long-term strategic plans to facilitate the successful adoption and integration of GE and promote sustainability and low-carbon economy in the energy sector.

With the increasing development of logistics industry, an important question arises: which logistics format should an agricultural product seller select? Or when an agricultural product seller does select a certain logistics format? To answer this question, we explore three different green agricultural product supply chain models/scenarios: a self-managed logistics format(N); a third-party enterprise logistics format(S); and a platform logistics format(E). Using the game-theoretic model, we investigate the impact of the cost coefficient on the agricultural product seller's logistics preference under the three logistics scenarios. Our theoretical analyses show that when the cost coefficient is small, the agricultural product seller prefers to cooperate with the 3PL enterprise, but as the coefficient increases, the agricultural product seller prefers to choose her self-managed logistics. Therefore, to optimize the logistics strategy of the agricultural product seller under B2C mode, it is necessary to build a reasonable logistics management mechanism and a perfect logistics distribution system to reduce the logistics service cost coefficient.

To assist enterprises in adapting to the challenges of the digital era during the product eco-design stage, based on the synergistic symbiosis theory and the eco-strategy wheel, combined with literature research and expert interviews, this study identifies 11 factors for enterprises to realize product eco-design under digital collaboration. In this study, the Decision-making Trial and Evaluation Laboratory (DEMATEL) method was used to aggregate the identified 11 factors into four factor sets: strong cause, weak cause, strong result, and weak result; and the Interpretive Structural Model (ISM) was used to create a multilevel recursive model of product eco-design for digital collaboration. The study's findings show that: digital collaborative product eco-design is a combination of intra-organizational, intra-organizational, and external organizational synergies; and digital collaboration improves the efficiency of eco-design technology acquisition. This research provides a scientific foundation for company managers to make product eco-design decisions in the context of the worldwide digitalization trend.

The plan of "transforming national high-tech zones into national innovation demonstration zones (hereinafter referred to as" NIDZ") launched in 2009 is an attempt to promote high-quality economic development in China. Based on the quasi-natural experiment of transforming national high-tech zones into NIDZ in 2009, this paper collected and sorted out the data of 51 cities where national high-tech zones were located in China from 2002 to 2018. Then we measured urban green total factor productivity by applying the SBM model and investigated the impact of transformation on urban green total factor productivity through the difference in difference (DID) method. The results show that: (1) Urban green total factor productivity has been improved by transforming into a NIDZ, and the results are relatively stable. (2) Mechanism analysis shows that the promotion of urban green total factor productivity by transformation is realized through green technology innovation and industrial agglomeration mechanism. (3)The heterogeneity analysis shows that the policy effects are better in the developed eastern regions and regions with lower levels of government efficiency, and have not been reflected in the less developed central and western regions and regions with higher levels of government efficiency.

The textile industry supply chains (SC) face numerous risks and disruptions due to the changing dynamics of high demand and limited resources. The impact of epidemics and regional conflicts further complicates global business operations, especially in emerging economies. In this context, the textile sector in these economies must prioritize Sustainable Supply Chain Management (SSCM) to achieve cost reduction, enhance productivity, and improve profitability to sustain their business. Although research has examined several SSCM viewpoints, the barriers that prevent emerging economies from adopting SSCM in the textile sector to meet the Sustainable Development Goals (SDGs) are not sufficiently highlighted in the empirical literature that has already been published. This study analyzes different barriers and investigates how they are interconnected. From the literature research, 17 main barriers were first identified in the process. The barriers were then prioritized in order of significance using a combination of fuzzy theory, Pareto analysis, and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) framework. Finally, the cause-and-effect relationships among these barriers were established. A lack of commitment from the supplier's top management, insufficient financial incentives, and the absence of supportive government standards and regulations were identified as the three topmost significant barriers to SSCM adoption. For the textile sector, governments, and policymakers in emerging economies, the study's results are helpful since they will assist them create mitigation strategies to get rid of these barriers and achieve long-term sustainability.

An increase in greenhouse gases emission from the transportation sector has led companies and the government to elevate and support the production of electric vehicles (EV). With recent developments in urbanization and e-commerce, transportation companies are replacing their conventional fleet with EVs to strengthen the efforts for sustainable and environment-friendly operations. However, deploying a fleet of EVs asks for efficient routing and recharging strategies to alleviate their limited range and mitigate the battery degradation rate. In this work, a fleet of electric vehicles is considered for transportation and logistic capabilities with limited battery capacity and scarce charging station availability. We introduce a min-max electric vehicle routing problem (MEVRP) where the maximum distance traveled by any EV is minimized while considering charging stations for recharging. We propose an efficient branch and cut framework and a three-phase hybrid heuristic algorithm that can efficiently solve a variety of instances. Extensive computational results and sensitivity analyses are performed to corroborate the efficiency of the proposed approach, both quantitatively and qualitatively. Finally a data-driven simulation implemented with the robot operating system (ROS) middleware are performed to corroborate the efficiency of the proposed approach, both quantitatively and qualitatively.