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

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 Q1 ECONOMICS

Socio-economic Planning Sciences

Pub Date : 2025-02-11 DOI: 10.1016/j.seps.2025.102174

Luqi Wang, Guoqing Yang, Jianmin Xu

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.

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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 Q1 ECONOMICS

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

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.

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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 Q1 ECONOMICS

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

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.

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引用次数: 0

Demand information disclosure in fresh produce supply chain considering competition between geographical indication and local suppliers

IF 6.2 2区经济学 Q1 ECONOMICS

Socio-economic Planning Sciences

Pub Date : 2025-02-07 DOI: 10.1016/j.seps.2025.102177

Zhenjiang Chen , Bin Dan , Ting Lei , Songxuan Ma

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.

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引用次数: 0

The local effects and neighborhood effects of high-speed railway on urban entrepreneurial vitality: Evidence from China

IF 6.2 2区经济学 Q1 ECONOMICS

Socio-economic Planning Sciences

Pub Date : 2025-02-06 DOI: 10.1016/j.seps.2025.102172

Wei Jiang , Nana Jiang , Ke-Liang Wang

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.

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引用次数: 0

Optimizing training efficiency amid postgraduate enrollment expansion: A new parallel network DEA allocation model

IF 6.2 2区经济学 Q1 ECONOMICS

Socio-economic Planning Sciences

Pub Date : 2025-02-03 DOI: 10.1016/j.seps.2025.102167

Jiqiang Zhao , Lijun Cheng , Xianhua Wu , Lei Zhao

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

γ_{1}

= 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 > 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.

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引用次数: 0

A hybrid decision support system for transport policy selection: A case study on Russia's Northern Sea route in Artic region

IF 6.2 2区经济学 Q1 ECONOMICS

Socio-economic Planning Sciences

Pub Date : 2025-02-03 DOI: 10.1016/j.seps.2025.102171

Galip Cihan Yalçın , Elif Gürdal Limon , Karahan Kara , Onur Limon , Pınar Gürol , Muhammet Deveci , Özgür Demirayak , Hana Tomášková

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 (Intuitionistic Fuzzy Sets - Simple Weight Calculation - Alternative Ranking Using Two-Step Logarithmic Normalization) 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 "State interests, security, and sovereignty.".

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引用次数: 0

San Francisco Bay area community cohesion and resilience: Two case studies

IF 6.2 2区经济学 Q1 ECONOMICS

Socio-economic Planning Sciences

Pub Date : 2025-02-02 DOI: 10.1016/j.seps.2025.102157

Alexander Gilgur, Jose Emmanuel Ramirez-Marquez

In this submission, the authors develop an innovative approach to measuring community resilience by mathematical analysis of its members’ social-media microblogs. The approach involves applying machine-learning and graph-analytic techniques to infer social cohesion, which is later used as the state variable by which resilience is measured. We analyze community cohesion and its dynamics during two natural disasters that hit San Francisco Bay Area with an interval of only two years - the wildfires of 2020 and the torrential rainstorms during the water year of 2022/23.

The backdrop of the wildfires was characterized by the first year of the COVID pandemic, with all the uncertainty, deficit of personal protective equipment (PPE), loss of jobs, social-justice protests, and Presidential elections. For the rainstorms, the backdrop consisted of the Omicron variant of COVID, structural damage due to heavy rains and winds, and midterm elections. Bay Area economy too was in a different state during the wildfires than it was during the rainstorms. In this submission, we measure the community resilience based on the dynamics of Bay Area recovering from these events. We propose novel metrics for community cohesion and investigate the mechanisms by which emotions, local economy, weather, and air quality affects community cohesion. We also explore whether community resilience is influenced by these mechanisms.

Specifically, we analyze the mediating role played by emotions in the community cohesion and resilience processes.

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引用次数: 0

Dynamic decision-making of the e-commerce supply chain considering greenwashing and sales format

IF 6.2 2区经济学 Q1 ECONOMICS

Socio-economic Planning Sciences

Pub Date : 2025-02-01 DOI: 10.1016/j.seps.2025.102170

Liying Yu , Hui Xu , Ziyuan Zhang

With the rapid growth of e-commerce, reselling and agency selling have emerged as two prominent sales formats within the e-commerce supply chain (ECSC), alongside which the phenomenon of greenwashing has also become prevalent. How to choose the optimal combination of greenwashing and sales format to achieve long-term sustainable development of the ECSC has become a pressing issue. Considering greenwashing and sales formats, this paper constructs differential game models of the manufacturer and the e-commerce platform under four scenarios. Then the feedback dynamic equilibrium strategies are obtained, the impacts of greenwashing and sales formats on ECSC decision are analyzed and the optimal combination of greenwashing and sales format is thoroughly discussed. Results show that when the exposure probability of greenwashing is low, the manufacturer tends to adopt greenwashing behavior, but this move will harm the interest of the e-commerce platform. There exists a weakening effect of greenwashing, and this effect is more extensive in agency selling format. Commission rate determines the sales format selection. When the commission rate is in a specific interval, both the manufacturer and the e-commerce platform will prefer agency selling format, otherwise, they may not reach an agreement on sales format. For the e-commerce platform, the point where profit peak is called the optimal commission rate, which will increase as the exposure probability of greenwashing goes up. Last, consumer trust has a significant impact on both greenwashing and sales format selection. The increase in consumer trust can enhance manufacturer's greenwashing profit and create more opportunities for greenwashing. As consumer trust increases, the commission rate threshold range for both the manufacturer and the e-commerce platform to agree on agency selling format will move towards the left.

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引用次数: 0

Performance evaluation of Chinese and foreign property insurance companies considering negative data: Based on the dynamic two-stage IBP-SBM model

IF 6.2 2区经济学 Q1 ECONOMICS

Socio-economic Planning Sciences

Pub Date : 2025-01-28 DOI: 10.1016/j.seps.2025.102169

Peide Liu , Huizhi Sun , Hongxue Xu

In the insurance industry, performance evaluation is a crucial instrument for resource management, allocation, and industry development. Negative data, however, have received little attention in the present evaluation system and are considered an undesirable consequence of research evaluation. To fill this gap, this paper establishes an evaluation indicator system that includes negative data and proposes the dynamic two-stage improved base point slacks-based measure (IBP-SBM) model for handling negative data. The model fully considers the internal structure of the production process and the measurement of intermediate products, and obtains the system efficiency and stage efficiency in two steps. In order to verify the applicability of the model, we evaluate the performance of 48 Chinese and foreign property insurance companies over the period from 2018 to 2020 through the proposed model. The empirical results indicate that variations in the investment stage are primarily responsible for shifts in the overall efficiency of the property insurance industry. With this method, decision-making is aided by a wealth of information.

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引用次数: 0