Pub Date : 2025-09-25DOI: 10.1016/j.seps.2025.102337
Simona Ferraro , Kaire Põder , Triin Lauri
This paper investigates how inclusive education reforms intersect with parental choice to influence school efficiency in Estonia - a system that is formally comprehensive, but increasingly selective in practice, leading to quasi-market dynamics. Applying a two-stage double-bootstrap Data Envelopment Analysis (DEA) on post-pandemic data from over 300 lower secondary schools, we assess how non-discretionary student characteristics (environmental variables), particularly special educational needs (SEN), parental income and immigration background, affect school-level efficiency. Our findings show that higher proportions of SEN students and students from low-income families are systematically associated with lower efficiency, especially in contexts where schools have no autonomy over admissions, such as neighbourhood schools. In contrast, oversubscribed or elite schools can afford to be selective, reinforcing reputational hierarchies and equity-harming quasi-market dynamics. By linking efficiency analysis with educational governance, we discuss how school market characteristics can easily jeopardise the inclusive education reform. Evidence shows that in a hybrid market, non-selective schools are worse positioned in terms of efficiency than selective schools.
{"title":"Inclusive education and parental choice: How student characteristics affect school efficiency","authors":"Simona Ferraro , Kaire Põder , Triin Lauri","doi":"10.1016/j.seps.2025.102337","DOIUrl":"10.1016/j.seps.2025.102337","url":null,"abstract":"<div><div>This paper investigates how inclusive education reforms intersect with parental choice to influence school efficiency in Estonia - a system that is formally comprehensive, but increasingly selective in practice, leading to quasi-market dynamics. Applying a two-stage double-bootstrap Data Envelopment Analysis (DEA) on post-pandemic data from over 300 lower secondary schools, we assess how non-discretionary student characteristics (environmental variables), particularly special educational needs (SEN), parental income and immigration background, affect school-level efficiency. Our findings show that higher proportions of SEN students and students from low-income families are systematically associated with lower efficiency, especially in contexts where schools have no autonomy over admissions, such as neighbourhood schools. In contrast, oversubscribed or elite schools can afford to be selective, reinforcing reputational hierarchies and equity-harming quasi-market dynamics. By linking efficiency analysis with educational governance, we discuss how school market characteristics can easily jeopardise the inclusive education reform. Evidence shows that in a hybrid market, non-selective schools are worse positioned in terms of efficiency than selective schools.</div></div>","PeriodicalId":22033,"journal":{"name":"Socio-economic Planning Sciences","volume":"103 ","pages":"Article 102337"},"PeriodicalIF":5.4,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145419008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-24DOI: 10.1016/j.seps.2025.102334
Shangyao Yan, Tsung-Hsun Hsieh, Yu-Chien Lai
The police departments in Taiwan have been facing a problem in recent years due to the shortage and aging of the police force. The government and research institutes have developed unmanned aerial vehicles (UAVs) with higher endurance, combined with advanced key technologies, to support police patrols under the concept of the “Aerial Police Vehicle”. This development aims to reduce the workload of the police and make it possible to conduct police patrols in the future by using a combination of police vehicles and UAVs. Given the characteristics of police vehicles and UAVs, this study adopts the time-space network technique, incorporates relevant operational constraints, and adopts the objective of maximizing crime coverage rates to develop the routing and scheduling model for combined UAV-police vehicle patrols. Additionally, this study proposes a heuristic algorithm that utilizes a decomposition technique of patrol resources to efficiently solve this complex problem. The performance of the proposed algorithm was evaluated using a case study created from practical data from a police department in Taiwan, demonstrating that for a large-scale problem with 9 police stations and 91 patrol points, the proposed algorithm achieved a solution with an objective value of 906 for the maximized cumulative crime coverage rate in approximately 884 s, while a commercial solver (CPLEX) failed to find a feasible solution within a time limit of 28,800 s. The recommendations based on the sensitivity and scenario analysis results can be used as a reference for decision-makers to gradually replace police vehicles with UAVs in the future.
{"title":"Enhancing public safety through integrated UAV and police patrols","authors":"Shangyao Yan, Tsung-Hsun Hsieh, Yu-Chien Lai","doi":"10.1016/j.seps.2025.102334","DOIUrl":"10.1016/j.seps.2025.102334","url":null,"abstract":"<div><div>The police departments in Taiwan have been facing a problem in recent years due to the shortage and aging of the police force. The government and research institutes have developed unmanned aerial vehicles (UAVs) with higher endurance, combined with advanced key technologies, to support police patrols under the concept of the “Aerial Police Vehicle”. This development aims to reduce the workload of the police and make it possible to conduct police patrols in the future by using a combination of police vehicles and UAVs. Given the characteristics of police vehicles and UAVs, this study adopts the time-space network technique, incorporates relevant operational constraints, and adopts the objective of maximizing crime coverage rates to develop the routing and scheduling model for combined UAV-police vehicle patrols. Additionally, this study proposes a heuristic algorithm that utilizes a decomposition technique of patrol resources to efficiently solve this complex problem. The performance of the proposed algorithm was evaluated using a case study created from practical data from a police department in Taiwan, demonstrating that for a large-scale problem with 9 police stations and 91 patrol points, the proposed algorithm achieved a solution with an objective value of 906 for the maximized cumulative crime coverage rate in approximately 884 s, while a commercial solver (CPLEX) failed to find a feasible solution within a time limit of 28,800 s. The recommendations based on the sensitivity and scenario analysis results can be used as a reference for decision-makers to gradually replace police vehicles with UAVs in the future.</div></div>","PeriodicalId":22033,"journal":{"name":"Socio-economic Planning Sciences","volume":"102 ","pages":"Article 102334"},"PeriodicalIF":5.4,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145218979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-24DOI: 10.1016/j.seps.2025.102332
Yan Huang , Hanting Yu , Jiawei Wang , Meiling Li
Excess capacity has emerged as a global challenge, limiting resource allocation efficiency and hindering sustainable industrial development. Accurate measurement of capacity utilization (CU) is therefore essential. To meet this need, we propose a new multi-period CU measurement model that integrates the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and DEA (Data Envelopment Analysis) approaches. The model first constructs positive and negative production possibility sets, integrating the best and worst production states of decision-making units (DMUs) across periods. Using duality theory and multi-objective programming theory, Pareto optimality is proven to be equivalent to DEA efficiency in these sets. This equivalence serves as a foundation for defining benchmarks and ensures their scientific validity. Building on this foundation, positive and negative CU measurement models are developed, integrating the TOPSIS concept of relative closeness to construct a composite CU indicator. To demonstrate its applicability, the model is implemented using forestry sector data from 31 Chinese provinces for the period 2011–2020 and benchmarked against traditional methods. The results show that the efficiency evaluation based on the benchmark improves ranking reliability and allows comparisons across periods. Furthermore, the new CU indicator captures both positive and negative adjustment needs of DMUs, providing a more comprehensive and objective assessment of CU. This study provides a more precise quantitative tool for capacity regulation, offering important theoretical and practical implications for promoting industrial restructuring and sustainable development.
产能过剩已经成为一个全球性的挑战,它限制了资源配置效率,阻碍了工业的可持续发展。因此,准确测量容量利用率(CU)是必要的。为了满足这一需求,我们提出了一种新的多周期CU测量模型,该模型集成了TOPSIS (Order Preference Technique for Order Preference by Similarity To Ideal Solution)和DEA (Data Envelopment Analysis)方法。该模型首先构建正生产可能性集和负生产可能性集,整合决策单元(dmu)在不同时期的最佳和最差生产状态。利用对偶理论和多目标规划理论,证明了Pareto最优等价于DEA效率。这种等效性是定义基准的基础,并确保其科学有效性。在此基础上,建立了正、负CU测量模型,并结合TOPSIS相对接近度概念构建了一个复合CU指标。为了证明该模型的适用性,我们使用了中国31个省份2011-2020年的林业部门数据,并以传统方法为基准进行了验证。结果表明,基于基准的效率评估提高了排名的可靠性,并允许跨时期的比较。此外,新的CU指标同时反映了dmu的正调整和负调整需求,为CU提供了更全面和客观的评估。本研究为产能调控提供了更为精准的量化工具,对促进产业结构调整和可持续发展具有重要的理论和实践意义。
{"title":"Multi-period capacity utilization measurement using a TOPSIS-DEA approach: A case study of the forestry industry","authors":"Yan Huang , Hanting Yu , Jiawei Wang , Meiling Li","doi":"10.1016/j.seps.2025.102332","DOIUrl":"10.1016/j.seps.2025.102332","url":null,"abstract":"<div><div>Excess capacity has emerged as a global challenge, limiting resource allocation efficiency and hindering sustainable industrial development. Accurate measurement of capacity utilization (CU) is therefore essential. To meet this need, we propose a new multi-period CU measurement model that integrates the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and DEA (Data Envelopment Analysis) approaches. The model first constructs positive and negative production possibility sets, integrating the best and worst production states of decision-making units (DMUs) across periods. Using duality theory and multi-objective programming theory, Pareto optimality is proven to be equivalent to DEA efficiency in these sets. This equivalence serves as a foundation for defining benchmarks and ensures their scientific validity. Building on this foundation, positive and negative CU measurement models are developed, integrating the TOPSIS concept of relative closeness to construct a composite CU indicator. To demonstrate its applicability, the model is implemented using forestry sector data from 31 Chinese provinces for the period 2011–2020 and benchmarked against traditional methods. The results show that the efficiency evaluation based on the benchmark improves ranking reliability and allows comparisons across periods. Furthermore, the new CU indicator captures both positive and negative adjustment needs of DMUs, providing a more comprehensive and objective assessment of CU. This study provides a more precise quantitative tool for capacity regulation, offering important theoretical and practical implications for promoting industrial restructuring and sustainable development.</div></div>","PeriodicalId":22033,"journal":{"name":"Socio-economic Planning Sciences","volume":"102 ","pages":"Article 102332"},"PeriodicalIF":5.4,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145218982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-22DOI: 10.1016/j.seps.2025.102331
Meng Tian , Yiwei Wang , Lei Han , Zhuowen Yang
Accelerating digital transformation (DT) and facilitating reasonable enterprise scale expansion (ESE) is critical for integrating the digital and traditional economies. This paper examines the scale expansion characteristics of Chinese A-share listed enterprises and constructs a “two-level, four-category” cost model to analyze the theoretical relationship between DT and ESE. The findings reveal that DT significantly promotes the asymmetrical expansion of the enterprise employee and revenue scales, with revenue scale expansion being more prominent. Heterogeneity tests show that DT has a stronger impact on large enterprises, non-high-tech enterprises, and those in developed regions, leading to increased scale differentiation. Mechanism and economic consequence analysis highlight that DT reduces external transaction costs, facilitating ESE, while enhanced market share improves production efficiency. This paper provides theoretical and empirical insights into evolving corporate growth patterns in the digital economy and suggests policy recommendations for leveraging digital transformation to promote employment growth.
{"title":"Impact mechanism and contribution measurement of digital transformation on scale expansion of Chinese enterprises","authors":"Meng Tian , Yiwei Wang , Lei Han , Zhuowen Yang","doi":"10.1016/j.seps.2025.102331","DOIUrl":"10.1016/j.seps.2025.102331","url":null,"abstract":"<div><div>Accelerating digital transformation (DT) and facilitating reasonable enterprise scale expansion (ESE) is critical for integrating the digital and traditional economies. This paper examines the scale expansion characteristics of Chinese A-share listed enterprises and constructs a “two-level, four-category” cost model to analyze the theoretical relationship between DT and ESE. The findings reveal that DT significantly promotes the asymmetrical expansion of the enterprise employee and revenue scales, with revenue scale expansion being more prominent. Heterogeneity tests show that DT has a stronger impact on large enterprises, non-high-tech enterprises, and those in developed regions, leading to increased scale differentiation. Mechanism and economic consequence analysis highlight that DT reduces external transaction costs, facilitating ESE, while enhanced market share improves production efficiency. This paper provides theoretical and empirical insights into evolving corporate growth patterns in the digital economy and suggests policy recommendations for leveraging digital transformation to promote employment growth.</div></div>","PeriodicalId":22033,"journal":{"name":"Socio-economic Planning Sciences","volume":"102 ","pages":"Article 102331"},"PeriodicalIF":5.4,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145157658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-20DOI: 10.1016/j.seps.2025.102330
Fengting Zhang , Pengcheng Xiang , Dan Wang , Jiafu Su
The planning of high-speed railway corridors in ecologically sensitive areas faces significant challenges. Stakeholder conflicts arising from multi-objective conflict often induce decision-making impasses and project delays. Effectively identifying pivotal decision makers and facilitating consensus constitutes a critical challenge. This study first applied the Lancichinetti–Fortunato method to stakeholder relationship networks, detecting overlapping communities that revealed two distinct decision-maker categories: overlapping and non-overlapping decision makers. Subsequently, the most conflicted subgroup pairs and decision-maker dyads were identified using decision maker weights and community weights. To resolve decision conflicts during the consensus-building, a two-party evolutionary game model was constructed to examine strategic interactions between overlapping and conflicting decision makers. Finally, a consensus adjustment method based on the decision makers of the largest conflict is proposed to determine the final solution choice. Sensitivity analysis of the evolutionary game revealed that public attention significantly drives strategic shifts for both overlapping decision makers and conflicting decision makers. In contrast, moral hazard losses only regulate strategy evolution speed without altering direction. Additionally, the conflict intensity between construction and ecological spaces exerts opposing regulatory effects on the two groups’ strategic choices. This study provides theoretical foundations for managing non-cooperative behavior and achieving consensus equilibrium among heterogeneous subgroups.
{"title":"Resolving stakeholder conflicts in high-speed railway route planning: An overlapping network and evolutionary game approach","authors":"Fengting Zhang , Pengcheng Xiang , Dan Wang , Jiafu Su","doi":"10.1016/j.seps.2025.102330","DOIUrl":"10.1016/j.seps.2025.102330","url":null,"abstract":"<div><div>The planning of high-speed railway corridors in ecologically sensitive areas faces significant challenges. Stakeholder conflicts arising from multi-objective conflict often induce decision-making impasses and project delays. Effectively identifying pivotal decision makers and facilitating consensus constitutes a critical challenge. This study first applied the Lancichinetti–Fortunato method to stakeholder relationship networks, detecting overlapping communities that revealed two distinct decision-maker categories: overlapping and non-overlapping decision makers. Subsequently, the most conflicted subgroup pairs and decision-maker dyads were identified using decision maker weights and community weights. To resolve decision conflicts during the consensus-building, a two-party evolutionary game model was constructed to examine strategic interactions between overlapping and conflicting decision makers. Finally, a consensus adjustment method based on the decision makers of the largest conflict is proposed to determine the final solution choice. Sensitivity analysis of the evolutionary game revealed that public attention significantly drives strategic shifts for both overlapping decision makers and conflicting decision makers. In contrast, moral hazard losses only regulate strategy evolution speed without altering direction. Additionally, the conflict intensity between construction and ecological spaces exerts opposing regulatory effects on the two groups’ strategic choices. This study provides theoretical foundations for managing non-cooperative behavior and achieving consensus equilibrium among heterogeneous subgroups.</div></div>","PeriodicalId":22033,"journal":{"name":"Socio-economic Planning Sciences","volume":"102 ","pages":"Article 102330"},"PeriodicalIF":5.4,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145117764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-17DOI: 10.1016/j.seps.2025.102329
Rómulo A. Chumacero , Leonardo Letelier S
This paper presents a newly conducted evaluation of a reform to the educational system in Chile, implemented in 2018. The reform created school districts known as Local Education Services (SLEP), marking a shift away from the decentralized spirit of the voucher system instituted in 1981. We conduct several econometric exercises to evaluate its effects on standardized test scores (SIMCE) taken by 4th-grade students. The results consistently show no significant effect. Robustness checks—including the inclusion of covariates, changes in control group composition, and tests of the parallel trends assumption—confirm the validity of these findings. We extend the analysis to 8th- and 10th-grade students and obtain similar results. Taken together, the evidence indicates that the SLEP reform has not led to measurable improvements in academic achievement.
{"title":"SLEP-less in Santiago: The effect of local educational services in Chile","authors":"Rómulo A. Chumacero , Leonardo Letelier S","doi":"10.1016/j.seps.2025.102329","DOIUrl":"10.1016/j.seps.2025.102329","url":null,"abstract":"<div><div>This paper presents a newly conducted evaluation of a reform to the educational system in Chile, implemented in 2018. The reform created school districts known as Local Education Services (SLEP), marking a shift away from the decentralized spirit of the voucher system instituted in 1981. We conduct several econometric exercises to evaluate its effects on standardized test scores (SIMCE) taken by 4th-grade students. The results consistently show no significant effect. Robustness checks—including the inclusion of covariates, changes in control group composition, and tests of the parallel trends assumption—confirm the validity of these findings. We extend the analysis to 8th- and 10th-grade students and obtain similar results. Taken together, the evidence indicates that the SLEP reform has not led to measurable improvements in academic achievement.</div></div>","PeriodicalId":22033,"journal":{"name":"Socio-economic Planning Sciences","volume":"102 ","pages":"Article 102329"},"PeriodicalIF":5.4,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145158291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-16DOI: 10.1016/j.seps.2025.102327
Qianqi Guo, Yuliang Wang
As urbanization continues to advance, Public Open Spaces (POS) have become an essential part of daily life. In the face of increasingly frequent crises such as natural disasters, pandemics, and socioeconomic upheavals, these spaces play a crucial role in maintaining the basic functions of cities and enhancing the well-being of urban residents. However, the current research on how the public perception of POS affects urban resilience rarely involves the analysis of the resistance and recovery capabilities of public in the face of disasters. Using geotagged social media big data, this paper focuses on investigating the visitation frequency, sentiment analysis, and Cultural Ecosystem Services (CES) in Western China accross the COVID-19 pandemic era and its recovery. Based on the analysis, we calculated sentiment scores and created a CES dictionary to characterize public perception. We thenemployed a PLS-SEM model to analyze the social, economic, and environmental factors influencing public sentiment toward POS. The results show that public crises lead to significant declines and fluctuations in visitation frequency and sentiment, and also alter public CES behavioral patterns. Moreover, the sentiment recovery capacity enhances the sentiment resistance capacity. High-quality urban ecological and cultural environments, healthcare infrastructure, and active social media discussions contribute to public resilience, while higher urbanization rates and population densities have the opposite effect. Additionally, during the pandemic, public interest in recreational CES was stronger than in other periods. Such public-based research provides a more comprehensive understanding of urban resilience, and offers opportunities to improve resilience policies and enhance public well-being.
{"title":"Modeling socio-spatial resilience of public engagement with urban spaces","authors":"Qianqi Guo, Yuliang Wang","doi":"10.1016/j.seps.2025.102327","DOIUrl":"10.1016/j.seps.2025.102327","url":null,"abstract":"<div><div>As urbanization continues to advance, Public Open Spaces (POS) have become an essential part of daily life. In the face of increasingly frequent crises such as natural disasters, pandemics, and socioeconomic upheavals, these spaces play a crucial role in maintaining the basic functions of cities and enhancing the well-being of urban residents. However, the current research on how the public perception of POS affects urban resilience rarely involves the analysis of the resistance and recovery capabilities of public in the face of disasters. Using geotagged social media big data, this paper focuses on investigating the visitation frequency, sentiment analysis, and Cultural Ecosystem Services (CES) in Western China accross the COVID-19 pandemic era and its recovery. Based on the analysis, we calculated sentiment scores and created a CES dictionary to characterize public perception. We thenemployed a PLS-SEM model to analyze the social, economic, and environmental factors influencing public sentiment toward POS. The results show that public crises lead to significant declines and fluctuations in visitation frequency and sentiment, and also alter public CES behavioral patterns. Moreover, the sentiment recovery capacity enhances the sentiment resistance capacity. High-quality urban ecological and cultural environments, healthcare infrastructure, and active social media discussions contribute to public resilience, while higher urbanization rates and population densities have the opposite effect. Additionally, during the pandemic, public interest in recreational CES was stronger than in other periods. Such public-based research provides a more comprehensive understanding of urban resilience, and offers opportunities to improve resilience policies and enhance public well-being.</div></div>","PeriodicalId":22033,"journal":{"name":"Socio-economic Planning Sciences","volume":"102 ","pages":"Article 102327"},"PeriodicalIF":5.4,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145117766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-16DOI: 10.1016/j.seps.2025.102328
Yi Qiu , Cong Gao , Na Song
In addition to the transformations driven by digitalization and sustainability, the digital economy has opened new paths and revitalized the advancement of green innovation. As a key driving force of the circular economy system, green innovation can effectively promote sustainable development and high-quality economic growth. This study employs a panel dataset encompassing 108 cities at and above the prefectural-level within the Yangtze River Economic Belt from 2011–2021 to investigate the spillover impacts and transmission mechanisms of the digital economy on green innovation through the Spatial Durbin Model through empirical observations. The findings reveal an uneven distribution of the digital economy and green innovation within the Yangtze River Economic Belt, with the downstream area exhibiting more significant levels than the middle and upper sections. While the digital economy enhances green innovation in local cities, it also has a trickle-down effect on neighboring cities, which remains robust through various tests. The spillover effects of the digital economy on green innovation are pronounced in downstream regions, which are cities with high concentrations of human capital and green innovation. Mechanistic testing shows that the digital economy advances local green innovation levels by facilitating the flow of R&D staff, R&D capital, and industrial structure upgrading. The positive transmission effect in neighboring areas is driven primarily by the movement of R&D staff. This study offers valuable empirical insights for guiding green transformation efforts and promoting coordinated regional development.
{"title":"Trickle-down or siphon: The spillover effects of the digital economy on green innovation from the perspective of the circular economy","authors":"Yi Qiu , Cong Gao , Na Song","doi":"10.1016/j.seps.2025.102328","DOIUrl":"10.1016/j.seps.2025.102328","url":null,"abstract":"<div><div>In addition to the transformations driven by digitalization and sustainability, the digital economy has opened new paths and revitalized the advancement of green innovation. As a key driving force of the circular economy system, green innovation can effectively promote sustainable development and high-quality economic growth. This study employs a panel dataset encompassing 108 cities at and above the prefectural-level within the Yangtze River Economic Belt from 2011–2021 to investigate the spillover impacts and transmission mechanisms of the digital economy on green innovation through the Spatial Durbin Model through empirical observations. The findings reveal an uneven distribution of the digital economy and green innovation within the Yangtze River Economic Belt, with the downstream area exhibiting more significant levels than the middle and upper sections. While the digital economy enhances green innovation in local cities, it also has a trickle-down effect on neighboring cities, which remains robust through various tests. The spillover effects of the digital economy on green innovation are pronounced in downstream regions, which are cities with high concentrations of human capital and green innovation. Mechanistic testing shows that the digital economy advances local green innovation levels by facilitating the flow of R&D staff, R&D capital, and industrial structure upgrading. The positive transmission effect in neighboring areas is driven primarily by the movement of R&D staff. This study offers valuable empirical insights for guiding green transformation efforts and promoting coordinated regional development.</div></div>","PeriodicalId":22033,"journal":{"name":"Socio-economic Planning Sciences","volume":"102 ","pages":"Article 102328"},"PeriodicalIF":5.4,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145117765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The timely supply of emergency supplies is a critical safeguard for disaster response and post-disaster recovery. With the increasing post-disaster demand for supplies, relying solely on government reserves has become insufficient to meet emergency needs, making collaboration with enterprises an essential solution. However, the specific mechanisms of government-enterprise collaboration in emergency supplies reserves require further investigation. This study employs evolutionary game theory (EGT), integrates corporate social responsibility (CSR), and incorporates reputational benefits into the analysis. A two-stage dynamic game model is constructed to systematically analyze the strategic evolution process and stabilization mechanisms between governments and enterprises during collaboration. The Collaboration Intention Formation (CIF) stage focuses on enterprise participation willingness and its determinants, while the Collaboration Deepening and Optimization (CDO) stage examines the dynamic evolution of government incentive strategies and enterprise cooperation patterns during sustained collaboration. The findings reveal that enterprise participation is directly driven by cost-benefit tradeoffs and indirectly influenced by internal and external factors. Stable and in-depth collaboration depends on the interaction of strategic choices and behavioral feedback mechanisms. Through model-based analysis and numerical simulations, this study identifies key variables influencing equilibrium stability and proposes policy recommendations to optimize emergency supply reserve systems. These results provide theoretical and practical guidance for enhancing the efficiency of government-enterprise collaboration in emergency management.
{"title":"An evolutionary multi-stage public-private cooperation framework for emergency supply reserves with corporate reputation considerations","authors":"Langyu Zhou , Jing Zhang , Jing Gong , Chaoyong Zhang , Huige Xing","doi":"10.1016/j.seps.2025.102325","DOIUrl":"10.1016/j.seps.2025.102325","url":null,"abstract":"<div><div>The timely supply of emergency supplies is a critical safeguard for disaster response and post-disaster recovery. With the increasing post-disaster demand for supplies, relying solely on government reserves has become insufficient to meet emergency needs, making collaboration with enterprises an essential solution. However, the specific mechanisms of government-enterprise collaboration in emergency supplies reserves require further investigation. This study employs evolutionary game theory (EGT), integrates corporate social responsibility (CSR), and incorporates reputational benefits into the analysis. A two-stage dynamic game model is constructed to systematically analyze the strategic evolution process and stabilization mechanisms between governments and enterprises during collaboration. The Collaboration Intention Formation (CIF) stage focuses on enterprise participation willingness and its determinants, while the Collaboration Deepening and Optimization (CDO) stage examines the dynamic evolution of government incentive strategies and enterprise cooperation patterns during sustained collaboration. The findings reveal that enterprise participation is directly driven by cost-benefit tradeoffs and indirectly influenced by internal and external factors. Stable and in-depth collaboration depends on the interaction of strategic choices and behavioral feedback mechanisms. Through model-based analysis and numerical simulations, this study identifies key variables influencing equilibrium stability and proposes policy recommendations to optimize emergency supply reserve systems. These results provide theoretical and practical guidance for enhancing the efficiency of government-enterprise collaboration in emergency management.</div></div>","PeriodicalId":22033,"journal":{"name":"Socio-economic Planning Sciences","volume":"102 ","pages":"Article 102325"},"PeriodicalIF":5.4,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145105381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-11DOI: 10.1016/j.seps.2025.102318
Tamimu Mohammed Gadafi , Decui Liang , Adjei Peter Darko
In northern Ghana, irregular rainfall poses a significant challenge for farmers. This research aims to investigate the readiness and ability of farmers in this area to invest in a smart irrigation system to tackle this problem and improve agricultural output. The research is motivated by the adverse effects of unpredictable rainfall patterns and droughts on agricultural yields in the area. To identify the key factors influencing farmers’ willingness to pay (WTP) and their maximum WTP for the smart irrigation system, the study utilizes the contingent valuation method (CVM). An integrated Bonferroni mean (BM), best-worst method (BWM) and technique for order preference by similarity to the ideal solution (TOPSIS) have been developed to evaluate these factors and rank the smart irrigation system options. A two-stage approach was proposed to account for the interrelationships among the WTP factors by integrating the Bonferroni mean (BM). Primary data was collected through a thorough survey involving 375 respondents from 125 households and 5 agricultural experts. The findings reveal that the maximum WTP for the smart irrigation system in Zabzugu District was GHS 628. Among the key factors of WTP, income level is the most significant factor and market condition is the least important factor. The effectiveness of the proposed method is demonstrated by ranking various smart irrigation system options. Weathermatic smartline was identified as the preferred choice and Galcon smart irrigation controllers as the least option. This study contributes to Ghana’s existing irrigation system literature and provides valuable insights for policymakers concerning sustainable agriculture.
{"title":"Two stages method-based on Africa smart irrigation system assessment for willingness to pay: A case of Ghana Northern Region","authors":"Tamimu Mohammed Gadafi , Decui Liang , Adjei Peter Darko","doi":"10.1016/j.seps.2025.102318","DOIUrl":"10.1016/j.seps.2025.102318","url":null,"abstract":"<div><div>In northern Ghana, irregular rainfall poses a significant challenge for farmers. This research aims to investigate the readiness and ability of farmers in this area to invest in a smart irrigation system to tackle this problem and improve agricultural output. The research is motivated by the adverse effects of unpredictable rainfall patterns and droughts on agricultural yields in the area. To identify the key factors influencing farmers’ willingness to pay (WTP) and their maximum WTP for the smart irrigation system, the study utilizes the contingent valuation method (CVM). An integrated Bonferroni mean (BM), best-worst method (BWM) and technique for order preference by similarity to the ideal solution (TOPSIS) have been developed to evaluate these factors and rank the smart irrigation system options. A two-stage approach was proposed to account for the interrelationships among the WTP factors by integrating the Bonferroni mean (BM). Primary data was collected through a thorough survey involving 375 respondents from 125 households and 5 agricultural experts. The findings reveal that the maximum WTP for the smart irrigation system in Zabzugu District was GHS 628. Among the key factors of WTP, income level is the most significant factor and market condition is the least important factor. The effectiveness of the proposed method is demonstrated by ranking various smart irrigation system options. Weathermatic smartline was identified as the preferred choice and Galcon smart irrigation controllers as the least option. This study contributes to Ghana’s existing irrigation system literature and provides valuable insights for policymakers concerning sustainable agriculture.</div></div>","PeriodicalId":22033,"journal":{"name":"Socio-economic Planning Sciences","volume":"102 ","pages":"Article 102318"},"PeriodicalIF":5.4,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145043962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}