Socio-economic Planning Sciences最新文献_第2页

Multidimensional poverty in Benin

IF 6.2 2区经济学

Socio-economic Planning Sciences Pub Date : 2025-02-19 DOI: 10.1016/j.seps.2025.102181

Esmeralda Arranhado , Lágida Barbosa , João A. Bastos

引用次数: 0

Divergent growth paths: Conflict, state capacity, and convergence clubs in Sub-Saharan Africa

IF 6.2 2区经济学

Socio-economic Planning Sciences Pub Date : 2025-02-18 DOI: 10.1016/j.seps.2025.102178

Juan J. Villar-Roldan, Aida Galiano, Juan Manuel Martín-Álvarez

{"title":"Divergent growth paths: Conflict, state capacity, and convergence clubs in Sub-Saharan Africa","authors":"Juan J. Villar-Roldan, Aida Galiano, Juan Manuel Martín-Álvarez","doi":"10.1016/j.seps.2025.102178","DOIUrl":"10.1016/j.seps.2025.102178","url":null,"abstract":"<div><div>Understanding the patterns of economic convergence in Sub-Saharan Africa (SSA) is crucial for explaining the diverse growth trajectories observed across the region. This study investigates the presence of convergence clubs in GDP among 37 SSA countries from 1992 to 2022, departing from the foundational neoclassic economic theories. Employing the Phillips and Sul club convergence methodology, the study identifies four distinct convergence clubs, rejecting the hypothesis of overall convergence towards a single equilibrium. This finding highlights the developmental challenges across SSA. A subsequent analysis using an ordered logit model explores the determinants of club membership, revealing that state capacity, conflict, and business environment significantly influence SSA countries likelihood of belonging to a higher GDP club while foreign direct investment impact appears to be conditional on these very same factors. These results highlight the critical need for development organizations such as the World Bank or the United Nations to take a more nuanced and context-specific approach to their projects in Sub Saharan African countries. Aligning development interventions with the root causes of divergence identified in this study, such as weak state capacity or conflict, can unlock the potential for transformative and equitable progress in SSA.</div></div>","PeriodicalId":22033,"journal":{"name":"Socio-economic Planning Sciences","volume":"99 ","pages":"Article 102178"},"PeriodicalIF":6.2,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143479363","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}

引用次数: 0

Does public data access improve fiscal transparency? --On a quasi-natural experiment from government data platform access

IF 6.2 2区经济学

Socio-economic Planning Sciences Pub Date : 2025-02-15 DOI: 10.1016/j.seps.2025.102184

Ning Han , Peixian Liu , Fanglei Zhong , Dezhao Zhao

引用次数: 0

Evaluation and improvement of agricultural green total factor energy efficiency: The perspective of the closest target

IF 6.2 2区经济学

Socio-economic Planning Sciences Pub Date : 2025-02-15 DOI: 10.1016/j.seps.2025.102179

Jiarong Zhang , Meijuan Li , Zijie Shen

{"title":"Evaluation and improvement of agricultural green total factor energy efficiency: The perspective of the closest target","authors":"Jiarong Zhang , Meijuan Li , Zijie Shen","doi":"10.1016/j.seps.2025.102179","DOIUrl":"10.1016/j.seps.2025.102179","url":null,"abstract":"<div><div>The effective evaluation and improvement of agricultural green total factor energy efficiency (AGTFEE) are crucial for guiding sustainable agricultural development. The directional distance function (DDF), which can evaluate efficiency values and provide efficiency improvement paths, has attracted widespread attention. However, most existing research on DDF is based on the farthest target principle, often resulting in costly efficiency improvement paths. To address this issue, this study proposes a novel cross-DDF based on a learning network under the closest target principle. The proposed model is applied to dynamically analyze AGTFEE in China from 2013 to 2022 at different levels. Compared with existing research, the proposed model offers more feasible and cost-effective quantitative paths for improving AGTFEE. Moreover, the proposed model constructs a learning network based on the interactions among decision-making units for peer evaluation, avoiding inflated efficiency values. The empirical results highlight three main findings. First, over the decade from 2013 to 2022, China's AGTFEE has exhibited a positive trend, achieving significant progress. Second, during the same period, the balance and consistency of AGTFEE development have improved. However, differences remain among regions and provinces, with the distribution pattern showing “best in the east, followed by the west, and relatively poor in the center.” Third, there are differences in the improvement paths for AGTFEE among provinces. For instance, to improve AGTFEE in Hebei Province in 2022, it is necessary to significantly reduce the amount of pesticides used in the agricultural production process.</div></div>","PeriodicalId":22033,"journal":{"name":"Socio-economic Planning Sciences","volume":"99 ","pages":"Article 102179"},"PeriodicalIF":6.2,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143509948","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}

引用次数: 0

Analysis of crime around a low-barrier, rotating homeless shelter

IF 6.2 2区经济学

Socio-economic Planning Sciences Pub Date : 2025-02-14 DOI: 10.1016/j.seps.2025.102173

Jennifer Wilking , Greg Madonia , Peter Hansen

{"title":"Analysis of crime around a low-barrier, rotating homeless shelter","authors":"Jennifer Wilking , Greg Madonia , Peter Hansen","doi":"10.1016/j.seps.2025.102173","DOIUrl":"10.1016/j.seps.2025.102173","url":null,"abstract":"<div><div>Concerns about crime often motivate local opposition to homeless services, such as shelters with low barriers to entry. To understand whether this central tenet of “not in my back yard” (NIMBY) opposition to low-barrier homeless shelters is supported empirically, researchers leveraged the natural variation associated with the operation of a seasonal, low-barrier shelter. Specifically, for three months each winter, an emergency shelter rotates to a different host location, often a church, each week. The shelter hosts 50–60 unhoused community members each night and is considered low-barrier as there are very few restrictions to entry, such as sobriety or pet ownership. To understand whether crime increased in the vicinity of the shelter host, the authors examined both arrest records and calls for service over a two-to-three-year period, for each of the 15 shelter sites. Using fixed effects Poisson and Negative Binomial regressions, we consistently find that arrests and calls for service do not significantly increase or decrease around hosts of the emergency, low-barrier homeless shelter. This finding contrasts with much of the literature on homelessness and crime, and suggests additional studies are needed that explore shelter specific factors. This study also has policy implications, as concerns about crime often motivate local opposition to the siting of homeless shelters in neighborhoods.</div></div>","PeriodicalId":22033,"journal":{"name":"Socio-economic Planning Sciences","volume":"98 ","pages":"Article 102173"},"PeriodicalIF":6.2,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143444746","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}

引用次数: 0

Quantifying political effects in the spatial allocation of public services 量化公共服务空间分配中的政治效应

IF 6.2 2区经济学

Socio-economic Planning Sciences Pub Date : 2025-02-14 DOI: 10.1016/j.seps.2025.102180

Anders Fredriksson, Maria Sylvia Macchione Saes

{"title":"Quantifying political effects in the spatial allocation of public services","authors":"Anders Fredriksson, Maria Sylvia Macchione Saes","doi":"10.1016/j.seps.2025.102180","DOIUrl":"10.1016/j.seps.2025.102180","url":null,"abstract":"<div><div>The spatial allocation of citizen-accessed public services is typically influenced by factors related to citizen demand, but also by other factors, including political considerations. We develop a method to quantify how political factors influence citizens’ spatial access to services. The method is illustrated through the study of two different public services in the state of São Paulo, Brazil; Citizen Service Centers and outpatient medical clinics. Each of the two programs, which are analyzed separately, consists of a number of units for in-person service delivery, spread across the state. We first build a regression model to analyze the allocation of each service, using citizen demand, official program criteria, and related variables as explanatory factors. The degree of explanation of the models improves once political variables are included. For each service, the geographical location of some of the implemented service units are explained by the political variables. Operations Research methods are then used to find an alternative, optimal, spatial allocation for the units discerned as political in the regression analysis. We quantify how much average citizen travel distance would have decreased, had this counterfactual allocation been implemented. Travel distance is one measure of welfare in spatial allocation problems and on average distances are thus longer in the presence of politically induced allocations. Longer distances can, in turn, have other first order welfare effects, for instance on health outcomes. Understanding political effects is thus important. Related to these considerations, we offer policy conclusions and discuss the generalizability of the study.</div></div>","PeriodicalId":22033,"journal":{"name":"Socio-economic Planning Sciences","volume":"99 ","pages":"Article 102180"},"PeriodicalIF":6.2,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143611173","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}

引用次数: 0

Predicting policy funding allocation with Machine Learning

IF 6.2 2区经济学

Socio-economic Planning Sciences Pub Date : 2025-02-13 DOI: 10.1016/j.seps.2025.102175

Nicola Caravaggio , Giuliano Resce , Cristina Vaquero-Piñeiro

{"title":"Predicting policy funding allocation with Machine Learning","authors":"Nicola Caravaggio , Giuliano Resce , Cristina Vaquero-Piñeiro","doi":"10.1016/j.seps.2025.102175","DOIUrl":"10.1016/j.seps.2025.102175","url":null,"abstract":"<div><div>Allocating funds through competitive opportunities is a core tool of place-based development policies, as it can generate economic benefits and support the revitalisation of ‘left-behind’ territories. By relying on Machine Learning (ML) techniques, this paper investigates the predictability of actors expected to benefit from EU development funding over the 2014–2020 period in Italy. We implemented eight different ML classification algorithms and Random Forest, followed by Extreme Gradient Boosting, and Support Vector Machine emerged as the most predictive. The results show that it is possible to make out-of-sample predictions and diagnose the precise factors influencing fund allocation, such as territorial attributes, economic dimensions, and production specialisation. Knowing in advance potential winners of the calls can help design tailored territorial, and even sectorial, public policies to address the obstacles to local development and green transition, and to efficiently distribute resources within the policy framework. This evidence contributes to the reflection launched by the Commission on the future of the competitiveness of the EU.</div></div>","PeriodicalId":22033,"journal":{"name":"Socio-economic Planning Sciences","volume":"98 ","pages":"Article 102175"},"PeriodicalIF":6.2,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143420186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cluster-based healthcare network design problem with referral system using a hybrid genetic algorithm 使用混合遗传算法解决带有转诊系统的基于集群的医疗保健网络设计问题

IF 6.2 2区经济学

Socio-economic Planning Sciences Pub Date : 2025-02-11 DOI: 10.1016/j.seps.2025.102174

Luqi Wang, Guoqing Yang, Jianmin Xu

{"title":"Cluster-based healthcare network design problem with referral system using a hybrid genetic algorithm","authors":"Luqi Wang, Guoqing Yang, Jianmin Xu","doi":"10.1016/j.seps.2025.102174","DOIUrl":"10.1016/j.seps.2025.102174","url":null,"abstract":"<div><div>Addressing the unbalanced distribution of demands and medical resources is a particularly important issue in many healthcare systems. To achieve the equitable and efficient utilization of medical resources across regions, various medical alliances with tiered hospitals have been proposed and promoted to implement patient referrals. However, no formal analysis has been conducted on the implementation and management of medical alliances, especially over large geographical areas. This paper proposes the cluster-based healthcare network design problem with a referral system that provides a framework for integrating healthcare districting and patient referral problems within a hierarchical healthcare network design. It partitions the healthcare network into several clusters based on administrative features and designs diverse referral strategies for heterogeneous patients. To address the proposed problem, a mixed-integer linear programming model is formulated, and a hybrid genetic algorithm framework is developed to solve it efficiently. This algorithm considers the cluster-based nature of the healthcare networks and incorporates local search strategies to guarantee convergence performance. To demonstrate the efficiency of the proposed method, a case study is conducted involving 93 hospitals in Hebei, China. The results reveal that the proposed model can be extensively used to help decision-makers make informed decisions about constructing effective healthcare networks containing multiple medical alliances to reduce costs and improve efficiency. Furthermore, it suggests that a healthcare system equipped with a multi-hub configuration, diverse referral strategies, and a more relaxed capacity setting exhibits excellent performance in terms of costs and resilience. Finally, our study demonstrates that the proposed algorithm performs well in terms of efficiency and robustness.</div></div>","PeriodicalId":22033,"journal":{"name":"Socio-economic Planning Sciences","volume":"98 ","pages":"Article 102174"},"PeriodicalIF":6.2,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395061","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}

引用次数: 0

A multi-stage machine learning model to design a sustainable-resilient-digitalized pharmaceutical supply chain

IF 6.2 2区经济学

Socio-economic Planning Sciences Pub Date : 2025-02-11 DOI: 10.1016/j.seps.2025.102165

Mostafa Jafarian , Iraj Mahdavi , Ali Tajdin , Erfan Babaee Tirkolaee

{"title":"A multi-stage machine learning model to design a sustainable-resilient-digitalized pharmaceutical supply chain","authors":"Mostafa Jafarian , Iraj Mahdavi , Ali Tajdin , Erfan Babaee Tirkolaee","doi":"10.1016/j.seps.2025.102165","DOIUrl":"10.1016/j.seps.2025.102165","url":null,"abstract":"<div><div>The significance of the Pharmaceutical Supply Chain (PSC) has been bolded during the COVID-19 pandemic when the demand for pharmaceutical products has drastically increased. The literature shows that the simultaneous consideration of resilience, sustainability, and digitalization in the PSC network design problem, especially using data-driven approaches, has been ignored by previous works. Hence, the current work aims to cover these gaps by proposing a machine learning-based model to design a PSC with resilience, digitalization, and sustainability dimensions. For this purpose, in the first stage, the potential suppliers are assessed using a Random Forest Regressor (RFR). Afterwards, a mathematical model is developed to design the PSC in which the resilience and sustainability aspects are incorporated. Then, a recently introduced method named Fuzzy Lexicographic Multi-Choice Archimedean-Chebyshev Goal Programming (FLMCACGP) is employed to achieve the optimal solution. To represent the application and efficiency of the developed model, a real-world case study in Iran is examined. It should be noted that the demand for products is estimated using the machine learning approach. Overall, the main novelty of this study is to design a sustainable-resilient-digitalized PSC network using a data-driven model. The model identify the most important indicators for the research problem wherein delivery time, quality, backup supplier, robustness, and cost are the most significant indicators. Furthermore, the proposed mathematical model selects the blockchain-based platform to establish the Information-Sharing System (ISS). The effectiveness of the developed methodology is then assessed by comparing its results with the traditional methods. Finally, managerial insights are offered based on the practical implications of the findings.</div></div>","PeriodicalId":22033,"journal":{"name":"Socio-economic Planning Sciences","volume":"98 ","pages":"Article 102165"},"PeriodicalIF":6.2,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143444747","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}

引用次数: 0

Exploring social, economic, and ecological drivers of human well-being in the Qinling Mountains, China

IF 6.2 2区经济学

Socio-economic Planning Sciences Pub Date : 2025-02-07 DOI: 10.1016/j.seps.2025.102176

Chenlu Li , Qian Wang , Wen Xiang , Huixia Wang , Zuoqiang Yuan , Fei Yu , Wenfang Xie

{"title":"Exploring social, economic, and ecological drivers of human well-being in the Qinling Mountains, China","authors":"Chenlu Li , Qian Wang , Wen Xiang , Huixia Wang , Zuoqiang Yuan , Fei Yu , Wenfang Xie","doi":"10.1016/j.seps.2025.102176","DOIUrl":"10.1016/j.seps.2025.102176","url":null,"abstract":"<div><div>Understanding the effects of different factors on human well-being (HWB) is essential for achieving sustainable development. Recent related studies have mainly focused on the effects of socioeconomic or ecological environmental factors on HWB, while less effort has been devoted to quantitatively assessing the long-term effects of multiple variables on HWB. In this study, we applied a spatial regression model to data representing 19 social, economic, and ecological environmental variables to characterize the spatial pattern of the county-level HWB in the Qinling Region. First, we quantified the HWB in 2000, 2010 and 2020, and then, we analyzed its spatial heterogeneity in the Qinling Region. Correlation analysis, multicollinearity test, and ordinary least squares (OLS) analysis were used to identify three and four key factors in 2000 and 2020, respectively. Finally, the performances of the OLS, geographically-weighted regression (GWR), and multi-scale geographically weighted regression (MGWR) methods were compared, and it was found that the MGWR achieved the best overall performance. The model results indicated that the significant factors in 2000 included the disposable income of rural households, the number of health profession technicians, and the average annual temperature; those in 2020 included the disposable income of urban households, the number of beds in medical and health institutions, and the average annual precipitation. Economic factors had the strongest coefficient of influence, and the western Qinling Region was the most vulnerable. Selecting impact factors from multiple dimensions and conducting multi-model comparisons can help improve the reliability of our results. The results of this study provide a scientific reference for improving human well-being and for achieving sustainable development in the Qinlinig Region.</div></div>","PeriodicalId":22033,"journal":{"name":"Socio-economic Planning Sciences","volume":"98 ","pages":"Article 102176"},"PeriodicalIF":6.2,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143386966","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}

引用次数: 0