Socio-economic Planning Sciences最新文献

{"title":"Analysis of crime around a low-barrier, rotating homeless shelter","authors":"Jennifer Wilking ,&nbsp;Greg Madonia ,&nbsp;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}

{"title":"Quantifying political effects in the spatial allocation of public services","authors":"Anders Fredriksson,&nbsp;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}

{"title":"Predicting policy funding allocation with Machine Learning","authors":"Nicola Caravaggio ,&nbsp;Giuliano Resce ,&nbsp;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}

{"title":"Cluster-based healthcare network design problem with referral system using a hybrid genetic algorithm","authors":"Luqi Wang,&nbsp;Guoqing Yang,&nbsp;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}

{"title":"A multi-stage machine learning model to design a sustainable-resilient-digitalized pharmaceutical supply chain","authors":"Mostafa Jafarian ,&nbsp;Iraj Mahdavi ,&nbsp;Ali Tajdin ,&nbsp;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}

{"title":"Exploring social, economic, and ecological drivers of human well-being in the Qinling Mountains, China","authors":"Chenlu Li ,&nbsp;Qian Wang ,&nbsp;Wen Xiang ,&nbsp;Huixia Wang ,&nbsp;Zuoqiang Yuan ,&nbsp;Fei Yu ,&nbsp;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}

{"title":"Demand information disclosure in fresh produce supply chain considering competition between geographical indication and local suppliers","authors":"Zhenjiang Chen ,&nbsp;Bin Dan ,&nbsp;Ting Lei ,&nbsp;Songxuan Ma","doi":"10.1016/j.seps.2025.102177","DOIUrl":"10.1016/j.seps.2025.102177","url":null,"abstract":"<div><div>When geographical indication fresh produce (GIFP) enters a distant market, demand uncertainty complicates the operational decisions for both the GIFP supplier (GS) and the local fresh produce supplier (LS), whereas the retailer disclosing demand information helps suppliers make optimal decisions. This study aims to explore the impacts of information disclosure on the retailer, GS, and LS and study the information disclosure strategy in the fresh produce supply chain (FPSC). We construct a multistage game model to investigate the retailer's optimal information disclosure decisions and demonstrate the validity of the results through a case study. Furthermore, we develop information contracts to prompt information collaboration in the FPSC. The results show that both the GS and the LS are willing to receive information, whereas the retailer chooses to disclose it voluntarily only when the freshness elasticity is not too low. Moreover, with the improvement in freshness elasticity, the retailer should first disclose to the GS and then to both the GS and LS and finally shift back to the GS. The influences of information disclosure on the performance of the supply chain are relevant to both the freshness elasticity and the quality advantage of the GIFP. Additionally, we identify three scenarios where supply chain performance can be improved by adjusting the retailer's disclosure strategy and propose corresponding contracts on the basis of information fees. This study provides actionable strategies for FPSC stakeholders.</div></div>","PeriodicalId":22033,"journal":{"name":"Socio-economic Planning Sciences","volume":"98 ","pages":"Article 102177"},"PeriodicalIF":6.2,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143420187","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}

{"title":"The local effects and neighborhood effects of high-speed railway on urban entrepreneurial vitality: Evidence from China","authors":"Wei Jiang ,&nbsp;Nana Jiang ,&nbsp;Ke-Liang Wang","doi":"10.1016/j.seps.2025.102172","DOIUrl":"10.1016/j.seps.2025.102172","url":null,"abstract":"<div><div>Using the spatial difference-in-differences (SDID) model, This paper quantitatively investigates the local effects and neighborhood effects of High-speed railway (HSR) on urban entrepreneurial vitality based on the balanced panel data of China's 277 prefecture-level cities between 2003 and 2019 with HSR opening as a quasi-natural experiment. The findings indicate that: (1) HSR not only enhances entrepreneurial activity in local cities but also boosts entrepreneurial activity in neighboring cities. This conclusion is supported by a series of robustness tests. (2) The neighborhood effects of HSR on urban entrepreneurial activity have a boundary of 600 km, meaning that the spatial spillover effect of HSR dissipates at a distance of 600 km. (3) The local effects and neighborhood effects of HSR on entrepreneurial vitality are more pronounced in core cities, cities with higher levels of innovation, cities with superior traditional transportation infrastructure conditions, and cities with a wider variety of cultural backgrounds. (4) HSR can effectively promote urban entrepreneurial vitality by accelerating talent mobility and alleviating financial constraints. The above conclusions can be extremely beneficial in assisting China and other emerging countries develop concrete proposals for HSR construction that will boost urban entrepreneurial vitality.</div></div>","PeriodicalId":22033,"journal":{"name":"Socio-economic Planning Sciences","volume":"98 ","pages":"Article 102172"},"PeriodicalIF":6.2,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143378636","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}

{"title":"Optimizing training efficiency amid postgraduate enrollment expansion: A new parallel network DEA allocation model","authors":"Jiqiang Zhao ,&nbsp;Lijun Cheng ,&nbsp;Xianhua Wu ,&nbsp;Lei Zhao","doi":"10.1016/j.seps.2025.102167","DOIUrl":"10.1016/j.seps.2025.102167","url":null,"abstract":"<div><div>Against the backdrop of the continuous expansion of postgraduate enrollment in China, ensuring the quality of postgraduate education has become a long-term focus of concern for the entire society. Currently, the allocation model of postgraduate enrollment quotas among Chinese universities and within universities has not formed an effective competitive mechanism, making it difficult to reflect quality orientation and improve training efficiency. Therefore, a new parallel network data envelopment analysis (DEA) enrollment quotas allocation model based on shared investment is proposed to achieve efficiency and fairness. An empirical analysis is conducted using the allocation of enrollment quotas for professional degree postgraduates at a university in Shanghai as an example. The study shows that (1) the existing allocation schemes only follow a single high average principle, which neglects allocation efficiency. Through optimization, the allocation efficiency has been improved from 0.76 to 1. (2) When the subjective stage weight coefficient <span><math><mrow><msub><mi>γ</mi><mn>1</mn></msub></mrow></math></span> = 0.9, the Gini coefficient of the allocation scheme is the lowest, which is the optimal allocation scheme under the condition of efficiency priority. (3) When the coefficient of the subjective efficiency stage and the input-oriented weight coefficient within the subjective efficiency stage change by 11 % and 40 %, respectively, there is no significant difference between the test and control groups in the allocation results (P &gt; 0.05), and the Pearson correlation coefficient (R²) is 0.96. Therefore, this allocation model demonstrates good stability and can be applied to the allocation of enrollment quotas among different universities and other types of postgraduates.</div></div>","PeriodicalId":22033,"journal":{"name":"Socio-economic Planning Sciences","volume":"98 ","pages":"Article 102167"},"PeriodicalIF":6.2,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143377315","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}

{"title":"A hybrid decision support system for transport policy selection: A case study on Russia's Northern Sea route in Artic region","authors":"Galip Cihan Yalçın ,&nbsp;Elif Gürdal Limon ,&nbsp;Karahan Kara ,&nbsp;Onur Limon ,&nbsp;Pınar Gürol ,&nbsp;Muhammet Deveci ,&nbsp;Özgür Demirayak ,&nbsp;Hana Tomášková","doi":"10.1016/j.seps.2025.102171","DOIUrl":"10.1016/j.seps.2025.102171","url":null,"abstract":"<div><div>The selection of transport policies by countries is critical both for international relations and for the implementation of effective and sustainable transport practices. Countries consider numerous parameters when deciding on transport policies. This study aims to develop a Decision Support System (DSS) to assist countries in selecting transport policies and to demonstrate its applicability. The primary motivation of the research is to identify transport policies for Russia's Arctic region and to determine the best alternative policy based on expert evaluations. For this purpose, the IF-SIWEC-ARLON (<em>Intuitionistic Fuzzy Sets - Simple Weight Calculation - Alternative Ranking Using Two-Step Logarithmic Normalization</em>) hybrid method was developed as a DSS in this study. To implement this hybrid method, a decision model incorporating experts, criteria, and transport policies was first established. The contribution levels of experts to the decision-making process were calculated using IF sets. Next, the criteria weights were determined using the IF-SIWEC approach. Finally, the ranking of transport policies was carried out using the IF-ARLON method. An algorithm representing the application of this hybrid method was developed and applied to a case study focusing on Russia's transport policy selection process of Northern Sea Route (NSR) in the Arctic region. The results supported the successful application of the IF-SIWEC-ARLON hybrid method. Its robustness was tested through sensitivity analysis scenarios, while the consistency of the findings was verified via comparative analyses. The study concluded that the best transport policy for Russia's Arctic region is \"Improved regulatory control with strategic international partnerships\", with the most influential criterion in the decision process identified as \"<em>State interests, security, and sovereignty</em>.\".</div></div>","PeriodicalId":22033,"journal":{"name":"Socio-economic Planning Sciences","volume":"98 ","pages":"Article 102171"},"PeriodicalIF":6.2,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143377316","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}