Pub Date : 2026-01-01Epub Date: 2026-02-13DOI: 10.1016/j.susoc.2026.02.001
Wenbin Wang, Mengyao Wang, Wenxin Yu, Meiqi Chen
Rapid technological advancements and robust economic growth have fueled an escalating demand for electronic products. As a major hub for producing and consuming electronic products, China is confronted with the swift accumulation of waste electrical and electronic equipment (WEEE). To address this challenge, this paper examines the impact of government reward and punishment mechanism (RPM) and investment cost sharing (ICS) in closed-loop supply chains (CLSC) on corporate social responsibility (CSR) and collection rate. Specifically, we construct four three-stage decision-making models for CLSC considering CSR. Through the equilibrium results, we observe that both RPM and ICS can effectively promote WEEE recycling. Besides, the level of corporate social responsibility, retailer profits and recycler profits have all improved with the increase of the government reward and punishment and the proportion of investment cost sharing. Interestingly, when the cost-sharing ratio is higher than a certain threshold, the manufacturer's profit does not decrease but rises as the intensity of rewards and punishments increases. Finally, we conduct a numerical study to validate the analytic model, confirming that the CLSC’s benefit and CSR level are greatly improved when both RPM and ICS are jointly implemented.
{"title":"Impact of reward-penalty mechanism and investment cost sharing on corporate social responsibility in a closed-loop supply chain","authors":"Wenbin Wang, Mengyao Wang, Wenxin Yu, Meiqi Chen","doi":"10.1016/j.susoc.2026.02.001","DOIUrl":"10.1016/j.susoc.2026.02.001","url":null,"abstract":"<div><div>Rapid technological advancements and robust economic growth have fueled an escalating demand for electronic products. As a major hub for producing and consuming electronic products, China is confronted with the swift accumulation of waste electrical and electronic equipment (WEEE). To address this challenge, this paper examines the impact of government reward and punishment mechanism (RPM) and investment cost sharing (ICS) in closed-loop supply chains (CLSC) on corporate social responsibility (CSR) and collection rate. Specifically, we construct four three-stage decision-making models for CLSC considering CSR. Through the equilibrium results, we observe that both RPM and ICS can effectively promote WEEE recycling. Besides, the level of corporate social responsibility, retailer profits and recycler profits have all improved with the increase of the government reward and punishment and the proportion of investment cost sharing. Interestingly, when the cost-sharing ratio is higher than a certain threshold, the manufacturer's profit does not decrease but rises as the intensity of rewards and punishments increases. Finally, we conduct a numerical study to validate the analytic model, confirming that the CLSC’s benefit and CSR level are greatly improved when both RPM and ICS are jointly implemented.</div></div>","PeriodicalId":101201,"journal":{"name":"Sustainable Operations and Computers","volume":"7 ","pages":"Pages 47-58"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147540110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01Epub Date: 2026-06-09DOI: 10.1016/j.susoc.2026.06.001
Xiong Zheng, Shangzuo Dai
This study investigates whether and how firms' ESG performance relates to supply chain resilience in China's A-share market. Resilience is operationalized as the negative of the three-year rolling standard deviation of profitability (Res=−sd3y(ROA)) and is complemented by industry × year-relative variants to purge common shocks. Using 9511 firm-year observations from 2017 to 2023 and two-way fixed effects with firm-clustered standard errors, the analysis reveals a positive association between lagged ESG and volatility-based resilience. Mechanism tests adopt a temporal mediation design, with financing constraints proxied by the Hadlock-Pierce (SA) index; for interpretability, results are reported for SArelaxed =−SA (higher = looser). Both Sobel diagnostics and firm-cluster bootstrap indicate a statistically significant indirect effect consistent with the capital-constraints-resilience pathway. The main results remain robust to alternative resilience and ESG metrics, clustering schemes, and firm-specific trends. Heterogeneity analyses further indicate stronger ESG-resilience associations among SOEs and larger firms, highlighting the roles of governance credibility and scale in translating financing advantages into operational stability. The study aligns construct measurement across ESG, constraints, and resilience, provides market-wide evidence on their linkage, and identifies settings in which ESG is most effectively translated into resilience advantages.
{"title":"Capital–constraints–resilience: Temporal mediation evidence on ESG and industry-relative supply-chain resilience","authors":"Xiong Zheng, Shangzuo Dai","doi":"10.1016/j.susoc.2026.06.001","DOIUrl":"10.1016/j.susoc.2026.06.001","url":null,"abstract":"<div><div>This study investigates whether and how firms' ESG performance relates to supply chain resilience in China's A-share market. Resilience is operationalized as the negative of the three-year rolling standard deviation of profitability (Res=−sd<sub>3y</sub>(ROA)) and is complemented by industry × year-relative variants to purge common shocks. Using 9511 firm-year observations from 2017 to 2023 and two-way fixed effects with firm-clustered standard errors, the analysis reveals a positive association between lagged ESG and volatility-based resilience. Mechanism tests adopt a temporal mediation design, with financing constraints proxied by the Hadlock-Pierce (SA) index; for interpretability, results are reported for SA<sub>relaxed</sub> =−SA (higher = looser). Both Sobel diagnostics and firm-cluster bootstrap indicate a statistically significant indirect effect consistent with the capital-constraints-resilience pathway. The main results remain robust to alternative resilience and ESG metrics, clustering schemes, and firm-specific trends. Heterogeneity analyses further indicate stronger ESG-resilience associations among SOEs and larger firms, highlighting the roles of governance credibility and scale in translating financing advantages into operational stability. The study aligns construct measurement across ESG, constraints, and resilience, provides market-wide evidence on their linkage, and identifies settings in which ESG is most effectively translated into resilience advantages.</div></div>","PeriodicalId":101201,"journal":{"name":"Sustainable Operations and Computers","volume":"7 ","pages":"Pages 169-181"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148523845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01Epub Date: 2026-02-26DOI: 10.1016/j.susoc.2026.02.003
Qi Chen , Xin Wang , Zixuan Lin , Haoyu Han
The rapid expansion of ESG (Environmental, Social, and Governance) investment faces significant challenges from greenwashing behaviors that undermine market trust and sustainable development. To examine governance mechanisms, we develop a tripartite evolutionary game model involving certification bodies (strict versus lenient certification), firms (greenwashing versus genuine Green), and ESG investors (rigorous versus label-based due diligence), while innovatively incorporating heterogeneous environmental preferences across all stakeholders. Our analysis reveals that firms’ environmental preference intensity serves as the critical determinant of market equilibrium, yielding three distinct regimes: (1) Under strong preferences, authentic environmental practices spontaneously emerge as the market norm, with governance mechanisms primarily reflecting certification bodies’ and investors’ own preferences; (2) Weak preferences generate widespread greenwashing, leading investors to rationally rely on labels while strict certification effectiveness diminishes sharply, creating adverse selection dynamics; (3) In the moderate preference range, market evolution exhibits complexity and path dependence, where achieving high-quality equilibrium critically depends on strong complementarities between strict certification and rigorous due diligence, while facing substantial suboptimal lock-in risks. This paper provides a dynamic multi-stakeholder theoretical framework for understanding diverse greenwashing market outcomes, emphasizing firms’ intrinsic motivations as central drivers and highlighting the context-dependent nature and complementarities of governance mechanisms. Our findings offer important implications for designing targeted anti-greenwashing policies, fostering coordinated multi-stakeholder governance, and preventing market failures.
{"title":"Greenwashing versus genuine green: An evolutionary game of certification, corporate strategy, and ESG investment","authors":"Qi Chen , Xin Wang , Zixuan Lin , Haoyu Han","doi":"10.1016/j.susoc.2026.02.003","DOIUrl":"10.1016/j.susoc.2026.02.003","url":null,"abstract":"<div><div>The rapid expansion of ESG (Environmental, Social, and Governance) investment faces significant challenges from greenwashing behaviors that undermine market trust and sustainable development. To examine governance mechanisms, we develop a tripartite evolutionary game model involving certification bodies (strict versus lenient certification), firms (greenwashing versus genuine Green), and ESG investors (rigorous versus label-based due diligence), while innovatively incorporating heterogeneous environmental preferences across all stakeholders. Our analysis reveals that firms’ environmental preference intensity serves as the critical determinant of market equilibrium, yielding three distinct regimes: (1) Under strong preferences, authentic environmental practices spontaneously emerge as the market norm, with governance mechanisms primarily reflecting certification bodies’ and investors’ own preferences; (2) Weak preferences generate widespread greenwashing, leading investors to rationally rely on labels while strict certification effectiveness diminishes sharply, creating adverse selection dynamics; (3) In the moderate preference range, market evolution exhibits complexity and path dependence, where achieving high-quality equilibrium critically depends on strong complementarities between strict certification and rigorous due diligence, while facing substantial suboptimal lock-in risks. This paper provides a dynamic multi-stakeholder theoretical framework for understanding diverse greenwashing market outcomes, emphasizing firms’ intrinsic motivations as central drivers and highlighting the context-dependent nature and complementarities of governance mechanisms. Our findings offer important implications for designing targeted anti-greenwashing policies, fostering coordinated multi-stakeholder governance, and preventing market failures.</div></div>","PeriodicalId":101201,"journal":{"name":"Sustainable Operations and Computers","volume":"7 ","pages":"Pages 59-75"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147540109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01Epub Date: 2025-08-08DOI: 10.1016/j.susoc.2025.07.005
Muhammad Ikram, Chaymae Boudraa
North Africa is one of the most vulnerable regions to the impacts of climate change. Achieving the UN Sustainable Development Goals (SDGs) in North Africa requires effective governance, yet the governance factors influencing SDG progress remain underexplored. Therefore, this study examines the nexus between the Worldwide Governance Indicators (WGIs) of voice and accountability, political stability and violence, government effectiveness, regulatory quality, rule of law, and control of corruption and Sustainable Development Goals (SDGs) in North Africa. Previous research has insufficiently explored the relationship between global governance progress and the 2030 agenda. To bridge this gap, we applied an integrated Grey Relational Analysis (GRA) model to compute the ranks and weights the performance of North African countries in achieving the 17 SDGs from 2016–2022. The results show that Quality Education (SDG 4), Industry, Innovation and Infrastructure (SDG 9), Reduce Inequalities (SDG10), Sustainable Cities and Communities (SDG11), Responsible Consumption and Production (SDG12) and Peace Justice and Strong Institutions (SDG16) exhibited the highest performance in the region based on Second Synthetic Grey Relational Analysis Model (SSGRA). Additionally, a conservative maximin model was used to identify which North African country has the greatest impact of WGI on SDG outcomes. The findings indicate that Morocco faced the most significant challenges, particularly in achieving SDG 6 (clean water and sanitation). These results highlight critical implications for North African governments, emphasizing the need to prioritize (clean water and sanitation) SDG 6 and implement effective national strategies. This study recommends policymakers focus on governance reforms in lagging sectors and leverage data-driven frameworks to monitor and guide sustainable development interventions.
{"title":"The role of quality governance in achieving sustainable development goals in North Africa: An integrated decision-support system","authors":"Muhammad Ikram, Chaymae Boudraa","doi":"10.1016/j.susoc.2025.07.005","DOIUrl":"10.1016/j.susoc.2025.07.005","url":null,"abstract":"<div><div>North Africa is one of the most vulnerable regions to the impacts of climate change. Achieving the UN Sustainable Development Goals (SDGs) in North Africa requires effective governance, yet the governance factors influencing SDG progress remain underexplored. Therefore, this study examines the nexus between the Worldwide Governance Indicators (WGIs) of voice and accountability, political stability and violence, government effectiveness, regulatory quality, rule of law, and control of corruption and Sustainable Development Goals (SDGs) in North Africa. Previous research has insufficiently explored the relationship between global governance progress and the 2030 agenda. To bridge this gap, we applied an integrated Grey Relational Analysis (GRA) model to compute the ranks and weights the performance of North African countries in achieving the 17 SDGs from 2016–2022. The results show that Quality Education (SDG 4), Industry, Innovation and Infrastructure (SDG 9), Reduce Inequalities (SDG10), Sustainable Cities and Communities (SDG11), Responsible Consumption and Production (SDG12) and Peace Justice and Strong Institutions (SDG16) exhibited the highest performance in the region based on Second Synthetic Grey Relational Analysis Model (SSGRA). Additionally, a conservative maximin model was used to identify which North African country has the greatest impact of WGI on SDG outcomes. The findings indicate that Morocco faced the most significant challenges, particularly in achieving SDG 6 (clean water and sanitation). These results highlight critical implications for North African governments, emphasizing the need to prioritize (clean water and sanitation) SDG 6 and implement effective national strategies. This study recommends policymakers focus on governance reforms in lagging sectors and leverage data-driven frameworks to monitor and guide sustainable development interventions.</div></div>","PeriodicalId":101201,"journal":{"name":"Sustainable Operations and Computers","volume":"6 ","pages":"Pages 198-216"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144925600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Industrial Symbiosis is recognized in the international context as a useful approach to move toward a Circular Economy. Here, the use of resources in industrial systems is improved, since waste and by-products generated by a firm are upcycled and used as input by other firms, reducing raw material extraction and waste sent to landfills. This work presents an analysis of the dynamic performance when an industrial symbiosis is implemented between two supply chains, where one represents the supplier of the other. Specifically, using the agent-based modeling simulation approach, the behavior and dynamics of the symbiotic supply chain are evaluated in different scenarios by adopting key performance indicators, such as the efficiency of symbiotic exchange, the environmental index, and the bullwhip effect. Based on our analysis, we provide useful managerial suggestions to create supportive and collaborative supply chains to support the Circular Economy.
{"title":"Enhancing circular economy through industrial symbiosis: An agent-based simulation analysis of supply chain dynamics","authors":"Rebecca Fussone , Caterina Sammatrice , Salvatore Cannella , Roberto Dominguez","doi":"10.1016/j.susoc.2025.03.002","DOIUrl":"10.1016/j.susoc.2025.03.002","url":null,"abstract":"<div><div>Industrial Symbiosis is recognized in the international context as a useful approach to move toward a Circular Economy. Here, the use of resources in industrial systems is improved, since waste and by-products generated by a firm are upcycled and used as input by other firms, reducing raw material extraction and waste sent to landfills. This work presents an analysis of the dynamic performance when an industrial symbiosis is implemented between two supply chains, where one represents the supplier of the other. Specifically, using the agent-based modeling simulation approach, the behavior and dynamics of the symbiotic supply chain are evaluated in different scenarios by adopting key performance indicators, such as the efficiency of symbiotic exchange, the environmental index, and the bullwhip effect. Based on our analysis, we provide useful managerial suggestions to create supportive and collaborative supply chains to support the Circular Economy.</div></div>","PeriodicalId":101201,"journal":{"name":"Sustainable Operations and Computers","volume":"6 ","pages":"Pages 130-139"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144131060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01Epub Date: 2024-11-06DOI: 10.1016/j.susoc.2024.11.002
Francesco Bonesso , Idiano D'Adamo , Massimo Gastaldi , Marco Giannini
Hydrogen is an energy carrier that can support the development of sustainable and flexible energy systems. However, decarbonization can occur when green sources are used for energy production and appropriate water use is manifested. This work aims to propose a socio-economic analysis of hydrogen production from an integrated wind and electrolysis plant in southern Italy. The estimated production amounts to about 1.8 million kg and the LCOH is calculated to be 3.60 €/kg in the base scenario. Analyses of the alternative scenarios allow us to observe that with a high probability the value ranges between 3.20–4.00 €/kg and that the capacity factor is the factor that most affects the economic results. Social analysis, conducted through an online survey, shows a strong knowledge gap as only 27.5 % claim to know the difference between green and grey hydrogen. There is a slight propensity to install systems near their homes, but this tends to increase due to increased knowledge on the topic. Respondents state sustainable behaviours, and this study suggests that these aspects should also be transformed into the energy choices that are implemented every day. The study suggests information to policy-makers, businesses and citizens as it outlines that green hydrogen is an operations strategy that moves toward sustainable development.
{"title":"Green hydrogen as a sustainable operations strategy: A socio-economic perspective","authors":"Francesco Bonesso , Idiano D'Adamo , Massimo Gastaldi , Marco Giannini","doi":"10.1016/j.susoc.2024.11.002","DOIUrl":"10.1016/j.susoc.2024.11.002","url":null,"abstract":"<div><div>Hydrogen is an energy carrier that can support the development of sustainable and flexible energy systems. However, decarbonization can occur when green sources are used for energy production and appropriate water use is manifested. This work aims to propose a socio-economic analysis of hydrogen production from an integrated wind and electrolysis plant in southern Italy. The estimated production amounts to about 1.8 million kg and the LCOH is calculated to be 3.60 €/kg in the base scenario. Analyses of the alternative scenarios allow us to observe that with a high probability the value ranges between 3.20–4.00 €/kg and that the capacity factor is the factor that most affects the economic results. Social analysis, conducted through an online survey, shows a strong knowledge gap as only 27.5 % claim to know the difference between green and grey hydrogen. There is a slight propensity to install systems near their homes, but this tends to increase due to increased knowledge on the topic. Respondents state sustainable behaviours, and this study suggests that these aspects should also be transformed into the energy choices that are implemented every day. The study suggests information to policy-makers, businesses and citizens as it outlines that green hydrogen is an operations strategy that moves toward sustainable development.</div></div>","PeriodicalId":101201,"journal":{"name":"Sustainable Operations and Computers","volume":"6 ","pages":"Pages 1-14"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142748297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01Epub Date: 2025-04-09DOI: 10.1016/j.susoc.2025.04.001
Jun Huang , Qiuhong Zhao
Forest fires occur abruptly and can be detrimental, posing significant threats to human safety, forest resources, and the overall environment. Timely detection and effective response are important to fight against forest fires. Aviation emergency rescue plays an increasingly important role in forest fire response due to the characteristics of fast response speed, low terrain requirements and less fire site restrictions. At present, forest fire aviation emergency has been paid more attention in the world, however, current researches provide limited support to actual situation due to the lack of systematization and pertinently. In this paper, based on remote sensing information and other multi-party data, a two-stage multi-objective stochastic optimization model of sustainable aviation emergency network for forest fire rescue is presented. The proposed model aims to minimize the maximum of effective operational distance for aerial emergency rescue efforts and the total cost, which includes ecological losses caused by forest fires. To solve the model, an algorithm incorporating the NSGA-II algorithm and SAA method is proposed. Further, a case of Hainan Province in China is studied, guiding the application of the proposed theoretical methods. The findings demonstrate considerable value in addressing forest fires and safeguarding forest resources, thereby contributing to the sustainable development of both the environment and society.
{"title":"Data driven multi-objective optimization of sustainable aviation emergency network for forest fire rescue","authors":"Jun Huang , Qiuhong Zhao","doi":"10.1016/j.susoc.2025.04.001","DOIUrl":"10.1016/j.susoc.2025.04.001","url":null,"abstract":"<div><div>Forest fires occur abruptly and can be detrimental, posing significant threats to human safety, forest resources, and the overall environment. Timely detection and effective response are important to fight against forest fires. Aviation emergency rescue plays an increasingly important role in forest fire response due to the characteristics of fast response speed, low terrain requirements and less fire site restrictions. At present, forest fire aviation emergency has been paid more attention in the world, however, current researches provide limited support to actual situation due to the lack of systematization and pertinently. In this paper, based on remote sensing information and other multi-party data, a two-stage multi-objective stochastic optimization model of sustainable aviation emergency network for forest fire rescue is presented. The proposed model aims to minimize the maximum of effective operational distance for aerial emergency rescue efforts and the total cost, which includes ecological losses caused by forest fires. To solve the model, an algorithm incorporating the NSGA-II algorithm and SAA method is proposed. Further, a case of Hainan Province in China is studied, guiding the application of the proposed theoretical methods. The findings demonstrate considerable value in addressing forest fires and safeguarding forest resources, thereby contributing to the sustainable development of both the environment and society.</div></div>","PeriodicalId":101201,"journal":{"name":"Sustainable Operations and Computers","volume":"6 ","pages":"Pages 116-129"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143898815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01Epub Date: 2025-10-11DOI: 10.1016/j.susoc.2025.10.003
Md. Hasin Arman, Ridwan Al Aziz, A. B. M. Mainul Bari, Chitra Lekha Karmaker, Sreedip Dasgupta
As industrialization and technological advancements accelerate, supply chain responsiveness has become crucial for global businesses. Industry 5.0 integrates human expertise with cutting-edge technologies such as machine learning, large-scale data analysis, and automation technologies, and creates new opportunities. However, while there has been a significant volume of research on Industry 5.0, less attention has been given to understanding and modeling the key drivers that influence the supply chain responsiveness, particularly in emerging economies. This study addresses this research gap by analyzing these drivers utilizing a mixed methodological approach. This study initially extracts sixteen primary drivers based on an extensive literature review and expert insights by utilizing a comprehensive methodology that integrates Pareto analysis, Modified Total Interpretive Structural Modeling, and Cross-Impact Matrix Multiplication Applied to Classification. Through Pareto analysis, this list is refined to the nine most influential and interconnected drivers. This analysis highlights the pivotal roles of "Big Data Analytics for supply chain cost optimization" and "Cloud Computing for dynamic supply chains" as the foremost drivers in enhancing supply chain responsiveness, especially from a sustainability standpoint. Moreover, "Application of the Internet of Things for real-time tracking," "Inventory control by using RFID," "Application of smart sensors for automation in SC," and "Artificial intelligence for smooth operation" are also identified as key drivers to supply chain improvement. When integrated, these drivers can facilitate a more resilient and adaptable supply chain, allowing businesses to leverage predictive analytics, real-time monitoring, and scalable demand-based responses. The insights obtained from this study can help managers and policymakers to pinpoint vulnerabilities within their supply chains and implement strategies to ensure sustainable and more responsive business operations.
{"title":"Improving supply chain responsiveness through the drivers of Industry 5.0: Sustainability implications for emerging economies","authors":"Md. Hasin Arman, Ridwan Al Aziz, A. B. M. Mainul Bari, Chitra Lekha Karmaker, Sreedip Dasgupta","doi":"10.1016/j.susoc.2025.10.003","DOIUrl":"10.1016/j.susoc.2025.10.003","url":null,"abstract":"<div><div>As industrialization and technological advancements accelerate, supply chain responsiveness has become crucial for global businesses. Industry 5.0 integrates human expertise with cutting-edge technologies such as machine learning, large-scale data analysis, and automation technologies, and creates new opportunities. However, while there has been a significant volume of research on Industry 5.0, less attention has been given to understanding and modeling the key drivers that influence the supply chain responsiveness, particularly in emerging economies. This study addresses this research gap by analyzing these drivers utilizing a mixed methodological approach. This study initially extracts sixteen primary drivers based on an extensive literature review and expert insights by utilizing a comprehensive methodology that integrates Pareto analysis, Modified Total Interpretive Structural Modeling, and Cross-Impact Matrix Multiplication Applied to Classification. Through Pareto analysis, this list is refined to the nine most influential and interconnected drivers. This analysis highlights the pivotal roles of \"Big Data Analytics for supply chain cost optimization\" and \"Cloud Computing for dynamic supply chains\" as the foremost drivers in enhancing supply chain responsiveness, especially from a sustainability standpoint. Moreover, \"Application of the Internet of Things for real-time tracking,\" \"Inventory control by using RFID,\" \"Application of smart sensors for automation in SC,\" and \"Artificial intelligence for smooth operation\" are also identified as key drivers to supply chain improvement. When integrated, these drivers can facilitate a more resilient and adaptable supply chain, allowing businesses to leverage predictive analytics, real-time monitoring, and scalable demand-based responses. The insights obtained from this study can help managers and policymakers to pinpoint vulnerabilities within their supply chains and implement strategies to ensure sustainable and more responsive business operations.</div></div>","PeriodicalId":101201,"journal":{"name":"Sustainable Operations and Computers","volume":"6 ","pages":"Pages 256-269"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145415228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01Epub Date: 2025-07-16DOI: 10.1016/j.susoc.2025.07.002
Dan Li
In response to the current needs of the logistics industry and the shortcomings of traditional logistics supply chain systems, this study adopts the B/S and front end/back end separation mode to construct the overall framework of the logistics supply chain system. The improved mileage saving algorithm is applied to solve the path optimization. Finally, a new type of green logistics supply chain system based on browser and server architecture and mileage saving algorithm is designed. The experimental results showed that the management module and distribution task module functional requirements of the green logistics supply chain system based on B/S and mileage saving algorithm achieved the expected results, which adapted to multiple browsers, with good universality. In addition, even in the case of a large number of users logging in simultaneously, the system proposed in the study maintained good stability, with a maximum stability of 93.68 % and a minimum running time of only 8 s. Compared with traditional logistics supply chain systems, the stability of the proposed system was improved by 12.16 %, and the running time was shortened by 21 s. In summary, the green logistics supply chain system based on browser and server architecture and mileage saving algorithm proposed in the study conforms to the logistics supply chain management in the 21st century, greatly promotes the development and efficiency of logistics supply chain management, and makes up for the shortcomings of management work.
{"title":"Green logistics supply chain system based on B/S architecture and mileage saving algorithm","authors":"Dan Li","doi":"10.1016/j.susoc.2025.07.002","DOIUrl":"10.1016/j.susoc.2025.07.002","url":null,"abstract":"<div><div>In response to the current needs of the logistics industry and the shortcomings of traditional logistics supply chain systems, this study adopts the B/S and front end/back end separation mode to construct the overall framework of the logistics supply chain system. The improved mileage saving algorithm is applied to solve the path optimization. Finally, a new type of green logistics supply chain system based on browser and server architecture and mileage saving algorithm is designed. The experimental results showed that the management module and distribution task module functional requirements of the green logistics supply chain system based on B/S and mileage saving algorithm achieved the expected results, which adapted to multiple browsers, with good universality. In addition, even in the case of a large number of users logging in simultaneously, the system proposed in the study maintained good stability, with a maximum stability of 93.68 % and a minimum running time of only 8 s. Compared with traditional logistics supply chain systems, the stability of the proposed system was improved by 12.16 %, and the running time was shortened by 21 s. In summary, the green logistics supply chain system based on browser and server architecture and mileage saving algorithm proposed in the study conforms to the logistics supply chain management in the 21st century, greatly promotes the development and efficiency of logistics supply chain management, and makes up for the shortcomings of management work.</div></div>","PeriodicalId":101201,"journal":{"name":"Sustainable Operations and Computers","volume":"6 ","pages":"Pages 189-197"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144914070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01Epub Date: 2025-10-04DOI: 10.1016/j.susoc.2025.10.002
Yanhong Ma , Hui Zhao , Haocong Ma
Green technology innovation (GTI) is the key path to promote green development and achieve China’s carbon peaking and carbon neutrality goals. Insufficient innovation motivation of enterprises and depressed market demand are still important reasons restricting GTI. The positive externalities of green products have significant impact on market demand and then the innovation motivation of enterprises. The optimized guiding policy should be proposed based on the consideration of products’ positive externalities. This paper divides green products into self-interested and altruistic. Then a tripartite evolutionary game model of government, enterprises and consumers is built. The impact of policy related parameters on evolutionary stable strategy (ESS) is analyzed, including subsidy and its distribution coefficient, carbon tax and its distribution coefficient. The results show that government can promote green behavior of enterprises and consumers through just implementing subsidy policies for self-interested products. While for altruistic products, government needs to implement subsidy and carbon tax policies simultaneously.
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