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    28 July 2026, Volume 35 Issue 4 Previous Issue   
    Vehicle Assignment and Route Optimization for Major Project Spoil Transportation Based on Improved Ant Colony and Genetic Algorithms
    Li Yulong, Su Han, Du Junhan, Li Shuxin, Mao Quan
    2026, 35 (4):  892-903.  doi: 10.3969/j.issn.2097-4558.2026.04.001
    Abstract ( )   PDF (5296KB) ( )   PDF(mobile) (1851KB) ( 5 )  
    Major linear infrastructure projects crossing complex and dangerous environments often require the construction of large-scale tunnels. The disposal of tunnel spoil in such regions must comprehensively consider multiple factors, including spoil disposal site selection, transport vehicle selection and assignment, route optimization, and environmental constraints. To balance environmental constraints, scientifically assign transport vehicles, optimize transport routes, and improve transportation cost-effectiveness, this paper develops a mathematical model covering the full process from spoil disposal site selection to spoil transportation, and used an improved genetic algorithm and ant colony algorithm (ACO) to solve the model. Through simulation analysis of spoil transportation of a major project in Xizang, it verified optimization performance of the improved algorithm and model. The results show that the new-energy medium-sized vehicles are well suited to spoil transportation in Xizang, and that the shortest transportation route should be prioritized under given constraints. The case study provides a new vehicle assignment and route optimization scheme for spoil transportation decision-making, and offers references for optimizing spoil transportation management strategies for major projects under environmental constraints.
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    Multi-Stakeholder Decision-Making Behavior Analysis of Permanent-Temporary Integration in Megaprojects
    Song Ruizhen, Gao Xin, Jia Fuyuan, Nan Haonan
    2026, 35 (4):  904-916.  doi: 10.3969/j.issn.2097-4558.2026.04.002
    Abstract ( )   PDF (2500KB) ( )  
    Permanent-temporary integration (PTI) in megaprojects refers to the design concept of integrating permanent facilities for the operation phase with temporary facilities for the construction phase. This approach not only avoids resource waste caused by dismantling temporary facilities but also promotes infrastructure construction that benefits the public. However, coordinating the interests of participating stakeholders remains challenging, highlighting the need for management mechanisms that encourage multi-stakeholder collaboration. Drawing on evolutionary game theory, this paper develops a multi-stakeholder decision-making game model involving local governments, project owners, and contractors. The model analyzes the evolutionary process of stakeholders’ decision-making behaviors regarding permanent-temporary integration, along with key influencing factors. The results indicate that stable cooperation can form among local governments, owners, and contractors, with local governments’ strategic choices being critical to achieving equilibrium. Livelihood-oriented PTI projects are better suited to a “cooperative” investment model, while strategic projects are more appropriate for a “dominant” investment model. Furthermore, unreasonable allocation of investment proportions may lead to conflicts between local governments and project owners, while real-time supervision of contractors’ construction quality proves to be an effective measure for promoting stakeholder participation.
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    Explainable Train Operation Status Prediction and Self-Updating Method for Complex Environments
    Chen Haoran, Wang Xi, Wang Hongwei, Yang Xin, Fei Zhenhao, Wang Jianying
    2026, 35 (4):  917-927.  doi: 10.3969/j.issn.2097-4558.2026.04.003
    Abstract ( )   PDF (3757KB) ( )  
    As a strategic railway line operating in high-altitude and complex environment, the Sichuan-Xizang Railway faces challenges such as harsh climate conditions, mixed passenger-freight operations, and frequent abnormal events. Existing train operation prediction methods rely heavily on static historical data and lack real-time adaptive capabilities, resulting in accumulated prediction errors. To address these issues, this paper proposes an explainable prediction model that integrates probabilistic distribution prediction with online self-updating capabilities. The model constructs structured multidimensional feature matrices from multi-source heterogeneous data and utilizes gradient boosting trees to generate both numerical forecasting and probabilistic predictions. A four-layer validation framework is designed based on SHAP(SHapley Additive exPlanations) feature contribution analysis to establish validation mechanisms for data effectiveness, causal interpretability, model stability, and prediction consistency. New data with clear causal relationships are selected to trigger incremental updates. Through incremental decision tree-tree expansion using a data buffer pool, model parameters are precisely optimized. The experimental results show that the proposed method achieves superior numerical prediction performance while maintaining comparable probabilistic prediction capability relative to advanced baseline models. Regarding self-updating performance, the root mean square error (RMSE) decreases by 27.9% compared with static models, and the error fluctuation rate remains below 3.2% even with 10% noise injection. This paper not only improves prediction accuracy through continuous self-updating, but also effectively prevents invalid data from degrading the model performance, thereby providing reliable and interpretable support for train operation scheduling in complex environments.
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    Management Resilience Evaluation of Major Construction Project  in Complex and Uncertain Environments
    Wang Duo, Yang Kai, Yang Lixing, Fu Shuaishuai, Zheng Yan, Wang Weiqiao
    2026, 35 (4):  928-938.  doi: 10.3969/j.issn.2097-4558.2026.04.004
    Abstract ( )   PDF (10470KB) ( )  
    To identify weaknesses in major construction projects system in complex and uncertain environments, it is essential to evaluate its management resilience. First, this paper constructs a resilience evaluation index system for major construction projects covering six dimensions: quality management, material management, progress management, safety management, personnel management, and contract management. A combination of analytic hierarchy process (AHP) and entropy weight method (EWM) based on game theory is employed to determine indicator weights, thereby improving the scientific validity of weight allocation. Next, a management resilience evaluation method based on two-dimensional cloud model is proposed from the perspectives of defense capability and recovery capability. MATLAB is then used to achieve the conversion between qualitative and quantitative evaluations, and closeness calculations are conducted to determine management resilience of the major construction engineering. Finally, a railway construction project in a complex and hazardous area is selected for empirical analysis. The results indicate that the project’s resilience level is moderate, suggesting a relatively high level of management resilience. The findings provide decision-making support for managers seeking to improve resilience strategies for major projects in complex and uncertain environments.
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    Dynamic Collaborative Decision-Making for Emergency Rescue in Major Railway Projects in China
    Lei Yuanyuan, Zhang Jingxiao, Dong Guanxi
    2026, 35 (4):  939-950.  doi: 10.3969/j.issn.2097-4558.2026.04.005
    Abstract ( )   PDF (5385KB) ( )  
    Emergency rescue operations for major railway projects in China involves decision-making among multiple stakeholders. To address the challenges of multi-agent decision-making under information uncertainty, this paper incorporates expert decision-making into a framework involving government agencies, enterprises, and non-governmental rescue organizations. By integrating multidimensional factors such as geography, climate, and engineering complexity, a dynamic response collaborative decision-making model is established from a temporal perspective for major railway projects in complex and hazardous environments. It examines the strategic choices and interaction mechanisms among stakeholders during emergency rescue operations. The results show that reputation fluctuations significantly affect stakeholder strategies. Governments consistently adopt immediate rescue strategies to fulfill responsibilities for public safety and social stability. As government decisions evolve toward immediate rescue, enterprises, experts, and non-governmental rescue organizations display stronger rescue willingness and coordination tendencies, eventually evolving into a collaborative response equilibrium. Finally, it proposes policy recommendations for improving emergency rescue systems by strengthening expert guidance and introducing reputation evaluation mechanisms.
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    Major Engineering Material Distribution Route Planning Based on End-to-End Predict-Then-Optimize Approach
    Kang Liujiang, Zhou Lunwei, Mao Xueli, Cao Shurui, Sun Huijun
    2026, 35 (4):  951-960.  doi: 10.3969/j.issn.2097-4558.2026.04.006
    Abstract ( )   PDF (11212KB) ( )  
    This paper studies the optimization problem of distribution route for major engineering material based on the end-to-end predict-then-optimize (EPO) approach. First, a route optimization model for engineering material distribution is developed with the objective of minimizing total travel time. Then, considering that travel times on construction routes are highly affected by factors such as weather and geological conditions, a travel-time prediction model based on bidirectional long short-term memory (BiLSTM) neural network is proposed, along with a multi-source temporal data fusion mechanism. Subsequently, a differentiable training framework based on an upper bound of decision loss is developed to address gradient backpropagation stability by relaxing the non-convex loss function. Finally, a real-world case study from a railway construction area is used to validate the proposed the EPO-BiLSTM model. The results demonstrate that the EPO-BiLSTM model significantly outperforms benchmark models in terms of travel time reduction, routing planning stability, and robustness.
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    Disaster Risk Propagation Analysis and Assessment Along Railway Projects in Southwestern China Based on Heterogeneous Information Networks
    Xu Yuanxi, Li Keping, Liang Yan
    2026, 35 (4):  961-971.  doi: 10.3969/j.issn.2097-4558.2026.04.007
    Abstract ( )   PDF (7359KB) ( )  
    Railway construction in Southwestern China faces extremely complex and hazardous natural environments. Analyzing potential relationships among disaster risks is crucial for engineering design and safety assurance. To address multi-source heterogeneous unstructured disaster risk data from actual projects in Southwestern China, this paper constructs a heterogeneous information network to explore various latent relationships and disaster risk chains among geological, geographical, and environmental risks along railway projects. The proposed model treats disaster risks in high-risk railway sections as nodes and the latent relationships among risks as edges. Quantitative analysis of network topology indicators reveals potential associations among disaster risks, while network identification methods are employed to identify disaster risk chains. The results indicate that disaster risks along railway projects in Southwest China exhibit clustering characteristics, with some risks strongly correlated, implying a higher probability of cascading disasters in vulnerable regions. This paper provides scientific support disaster risk assessment in railway engineering construction.
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    Multi-Stage Timing,Frequency,and Periodic Pricing Strategies Based on Consumer Anticipated Regret
    Guo Chunxiang, Tan Yue, Yu Shiqiang
    2026, 35 (4):  972-983.  doi: 10.3969/j.issn.2097-4558.2026.04.008
    Abstract ( )   PDF (2543KB) ( )  
    In recent years, time-limited promotional models such as the “Double Eleven” shopping festival have created mutual benefits for both consumers and merchants, while also exposing issues such as arbitrary promotion scheduling time setting and inaccurate pricing. To address these problems, this paper integrates consumer strategic behavior with multi-stage decision-making based on the theory of consumer anticipated regret, and constructs a multi-stage promotional decision model involving timing, frequency, and pricing strategies. By using actual customer flow data in shopping malls, the model optimizes merchants’ multi-stage strategies during sales periods. The results show that, by considering consumer strategic behavior, merchants can formulate appropriate time-limited promotional strategies to achieve market segmentation and increase profit. During the sales period, there exist optimal combinations of pricing, promotion frequency, and promotion timing for the merchants. The promotion frequencies should not be lower than the optimal value, and each promotion should not be excessively long. Further sensitivity analysis shows that an increase in consumer attrition coefficient has a negative impact on the merchant profits, in which case merchants should appropriately increase promotion frequency to avoid greater loss of profit. An increased proportion of strategic consumers help merchants segment markets and improve profits, though it has limited impact on the optimal promotion frequency. In addition, as consumers’ regret sensitivity increases, the utility they derive from purchasing products during low-price periods decreases, while merchants’ profits increases, and the optimal promotion frequency correspondingly decreases.
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    Supply Chain Investment in RFID Technology and Coordination Mechanism Design Considering Inventory Shrinkage
    Yang Huixiao, Jiang Chenqi, Yi Zelong
    2026, 35 (4):  984-997.  doi: 10.3969/j.issn.2097-4558.2026.04.009
    Abstract ( )   PDF (3886KB) ( )   PDF(mobile) (390KB) ( 1 )  
    This paper considers a supply chain composed of a single manufacturer and a single retailer. Before investing in radio frequency identification (RFID) technology, the retailer faces inventory shrinkage issues, and the two parties transact under a wholesale price contract. After investing in RFID technology, the retailer shares part of the sales revenue with the manufacturer. It is found that introducing only a revenue-sharing mechanism increases the manufacturer’s profit but reduces the retailer’s profit. Therefore, three coordination mechanisms are further explored: revenue sharing with negotiated wholesale prices, revenue sharing with negotiated wholesale prices and order quantities, and negotiated wholesale prices with revenue-sharing ratios. The objective is to identify conditions under which revenue-sharing mechanisms can simultaneously improve profits for both parties, analyze preferences for different coordination mechanisms, and determine when both parties benefit from RFID investment. This paper also compares investment incentives under different mechanisms. It obtains several new conclusions, offering insights into motivating supply chain members to adopt item-level RFID technology and enriching supply chain coordination theory.
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    Resilient Supply Chain System Design Considering& Capacity Reservation and New Technology Research and Development
    Li Musen, Xiao Qian, Yu Jiayi, Yang Yanran
    2026, 35 (4):  998-1014.  doi: 10.3969/j.issn.2097-4558.2026.04.010
    Abstract ( )   PDF (9356KB) ( )   PDF(mobile) (401KB) ( 0 )  
    Supply chain resilience is of great significance to national security and economic development. However, major disruptions faced by supply chains in recent years have demonstrated that relying solely on inventory stockpiling is insufficient to effectively ensure supply chain resilience. To address this issue, this paper considers three types of resources: inventory storage, capacity reservation, and new technology research and development (R&D), and constructs a government decision-making model based on inventory management theory. 
    The model analyzes the impact of integrating capacity reservation or new technology R&D on supply chain resilience beyond inventory reserves, and further explores whether governments should simultaneously adopt all three resources and in what sequence they should deploy them to maximize resilience improvement. The findings indicate that when reservation costs and R&D costs are relatively low, governments can economically improve supply chain resilience through capacity reservation and new technology R&D. However, the three resources are not always required simultaneously in resilient supply chains, and their optimal reserve level are closely related to the cost structure of each resource. As the fixed costs of new technology R&D increase, governments tend to substitute inventory reserves and capacity reservation for R&D resources. In addition, government budget constraints influence the utilization levels of the three resources, and as budget investment increases, governments do not proportionally increase investment in all three resources.
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    Information Boundary Spanning:A Study on User’s Boundary Spanning Connection Behavior in the Idea Generation Stage
    Zhou Mi, Song Mengmeng, Wu SHUHUI, Li Lan
    2026, 35 (4):  1015-1028.  doi: 10.3969/j.issn.2097-4558.2026.04.011
    Abstract ( )   PDF (1929KB) ( )  
    In the context of open innovation, companies can obtain user-generated ideas through online communities to foster innovation development. However, differences in information topics and directions create information boundaries that limit cross-domain information flow and application, thereby hindering the generation of high-quality user ideas. Using users of Zhihu as the research object, this paper aims to identify patterns of user boundary spanning connection behaviors and constructs a mechanism model to explain the influence of these behaviors on idea contribution quality. It conducts empirical tests to test the model using ordinary least squares regression and zero-inflated negative binomial regression models. The findings show that boundary spanning connection behavior encompasses both cross-domain connections and same-domain connections. Cross-domain connection behavior enhances both the novelty and usefulness of user contributions, while same-domain connection behavior primarily fosters usefulness of idea contributions. Structural holes weaken the positive effect of cross-domain connections on the novelty of idea contributions, while strengthening the positive relationship between same-domain connections on the usefulness of idea contributions. In addition, users with high social activity preferences are more inclined to engage in cross-domain connections, while those with high professional contribution preferences focus more on same-domain connections. This paper provides new insights into the mechanisms underlying the quality of user idea contributions and offers practical implications for personal information management and corporate innovation development.
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    Information Value of Big Data Credit Reporting in Platform Credit Decisions: From the Perspective of Consumption Behavior Information on Internet Platforms
    Song Ke, Yu Siyan, Yang Yaxin
    2026, 35 (4):  1029-1046.  doi: 10.3969/j.issn.2097-4558.2026.04.012
    Abstract ( )   PDF (1528KB) ( )  
    To clarify the role of big data credit reporting in online consumer credit decisions, this paper analyzes approximately 500,000 active user records randomly sampled from a domestic tourism-related internet consumer credit platform. The findings reveal that big data credit reporting provides significant informational value in credit-granting decisions. Applicants’ consumption capacity, consumption habits, and user engagement are incorporated into credit reporting. Consumers with higher cumulative spending, more frequent use of consumption vouchers, and longer platform engagement enjoy a relative advantage in the credit-granting process. Traditional credit information and consumption behavior information differ and exhibit a substitution relationship in credit decisions, with platform usage duration and credit card payment ratios serve as substitutes for traditional credit information. Heterogeneity analysis shows no regional discrimination in platform credit-granting decisions. The platform places greater emphasis on the traditional credit profile and platform dependency of younger consumers, while prioritizing consumption capacity in assessing older consumers. This suggests that internet consumer credit exhibits inclusive characteristics. Under the impact of the COVID-19 pandemic, fintech platforms strengthened risk management, reducing the weight of platform dependence in credit decisions and displaying a certain degree of procyclicality.
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    How Dual Institutional Logics Complement Each Other:Matching Relationships Between Control and Collaboration Strategies in Local Government Environmental Governance
    Sun Yan, Zhang Bei, Song Jinbo
    2026, 35 (4):  1047-1059.  doi: 10.3969/j.issn.2097-4558.2026.04.013
    Abstract ( )   PDF (1578KB) ( )  
    To reveal how local governments can effectively use control and collaboration to improve environmental governance performance in the context of multi-stakeholder co-governance, this paper develops an analytical framework “wicked environmental problems–control strategies–collaboration strategies” from the perspective of dual institutional logics. Using typical environmental governance cases disclosed during the second round of the Central Environmental Protection Inspectorate (CEPI) as data sources, it employs large-sample crisp-set qualitative comparative analysis (csQCA) analysis. The findings indicate that under the influence of dual institutional logics, local governments need to adopt hybrid strategies combining control and collaboration to achieve effective environmental governance performance. Based on heterogeneity external contexts, this paper identifies four matching patterns of hybrid strategies. Among them, the matching between political mobilization and inter-departmental collaboration shows no contextual heterogeneity, whereas the matching between administrative control and cross-actor collaboration does exhibit contextual heterogeneity. As environmental problems become more complex, local governments should enhance their response to collaboration logic and increasingly assume the role of collaborators. This paper fills the gap in the literature regarding how local governments effectively manage dual institutional logics, and provides policy recommendations for appropriately combining control and collaboration strategies to achieve collaborative governance.
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    Influence of Early Entry and Product Complexity on Digital Product Performance
    Liu Yongdong, Ren Shengce, Hua Zhibing
    2026, 35 (4):  1060-1074.  doi: 10.3969/j.issn.2097-4558.2026.04.014
    Abstract ( )   PDF (1550KB) ( )  
    Rapid advances in digital technology have made it increasingly challenging for companies to profit from digital innovation. Early entry and product complexity mechanisms have become important informal appropriability mechanisms for protecting digital innovation and achieving profitability. However, their specific roles in digital innovation remain unclear. Based on innovation appropriability theory and using App Store platform data from April 2019 to April 2024, this paper analyzes the effects of early entry and product complexity on digital product performance, and further examines the interaction between these two mechanisms. The findings show that early entry mechanism has a positive effect on digital product performance, and product complexity also has a positive effect. External digital technology dynamism strengthens the positive effect of early entry while weakening the positive effect of the product complexity. In addition, early entry and product complexity exhibit a substitution relationship. These findings enrich innovation appropriability theory in the context of digital platforms and provide theoretical guidance and optimization directions for companies implementing informal appropriability mechanisms.
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    Impact of Digital Orientation on Radical Technological Innovation from a Systems Perspective
    Yu Li, Wu Weiwei
    2026, 35 (4):  1075-1086.  doi: 10.3969/j.issn.2097-4558.2026.04.015
    Abstract ( )   PDF (6017KB) ( )  
    Digital technologies such as big data and cloud computing have had an important impact on firms’ radical technological innovation in the digital economy era. Drawing on attention-based view theory, this paper aims to explore the dynamic impact of digital orientation on radical innovation. It then constructs a system dynamics model to analyze the temporal effects of digital orientation on radical technological innovation using Vensim PLE software. The results show that digital orientation has a positive effect on radical technological innovation through top management team innovation attention. This effect continuously increases over time before gradually stabilizing, while also revealing a threshold effect in the relationship between digital orientation and radical technological innovation. The findings contribute to a systematic understanding of the internal mechanisms through which digital orientation affects radical technological innovation, breaking through limitations of prior static perspectives. Moreover, the findings provide useful supplements to the theoretical research on digital technology-empowered innovation, and offer theoretical and practical guidance for firms pursuing digital transformation and innovative development.
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    Impact of Customer Environmental Regulation on Renewable Energy Supplier Investment from a Supply Chain Spillover Perspective
    Hu Haiqing, Zhang Qian, Chen Di
    2026, 35 (4):  1087-1099.  doi: 10.3969/j.issn.2097-4558.2026.04.016
    Abstract ( )   PDF (1849KB) ( )  
    The supply chain networks formed through supplier-customer linkages promote environmental regulatory requirements and pressures in customer regions to spill over along supply chains, prompting suppliers to meet customers’ environmental demands and thereby influencing investment decisions by renewable energy suppliers. This paper, using Chinese A-share listed renewable energy firms from 2013 to 2023 as samples, constructs a customer network centered on renewable energy suppliers based on disclosed information regarding their top five customers to study the impact and underlying mechanism of environmental regulation intensity in customer regions renewable energy suppliers’ investment, while also examining the moderating roles of supplier-customer relationships and board network positions. The results show that stronger environmental regulation in customer regions encourages renewable energy suppliers to expand their investment scale. Moderating effect analysis shows that, from the perspective of relational governance, customer concentration and supplier industry competition affect supplier investment scale. From the perspective of structural embedding, higher board network centrality strengthens the impact of customer-region environmental regulation on supplier investment, whereas richer structural holes weaken this effect. Further analysis reveals that customer-region environmental regulation promotes supplier investment by affecting revenue and costs and adjusting supply-demand relationships. The findings provide reference for optimizing environmental regulation policies, promoting renewable energy investment, and improving supply chain governance.
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    “Mine” or “Ours”:The Influence Mechanism of Psychological Ownership on Pro-Environmental Behavior
    Liu Manzhi, Ma Ruonan, Lü Xueqing, Zhang Linlin, Bai Xiaoyu, Luo Jie
    2026, 35 (4):  1100-1113.  doi: 10.3969/j.issn.2097-4558.2026.04.017
    Abstract ( )   PDF (2310KB) ( )   PDF(mobile) (5639KB) ( 0 )  
    Encouraging residents to actively engage in pro-environmental behavior is an important practical pathway for advancing the construction of a “Beautiful China.” However, how to more effectively motivate such behavior remains a key issue requiring clarification. Should policymakers stimulate individuals’ sense of environmental ownership, or strengthen collective belonging awareness? The underlying mechanisms and boundary conditions through which these approaches influence pro-environmental behavior require further exploration. Based on theories of psychological ownership, social loafing, and psychological reactance, this paper examines the effects of psychological ownership (individual-oriented vs. collective-oriented) on pro-environmental behavior, while revealing the mediating role of perceived responsibility and the moderating role of normative appeals. Across four experiments, the results show that psychological ownership is an effective driver of pro-environmental behavior. Activating individual-oriented (vs. collective-oriented) psychological ownership produces stronger pro-environmental behavior (Experiments 1A and 1B). Perceived responsibility mediates the relationship between psychological ownership and pro-environmental behavior (Experiment 2). Normative appeals moderate this relationship: under descriptive norm conditions, individual-oriented psychological ownership exerts a stronger positive effect, whereas under injunctive norm conditions, collective-oriented psychological ownership has a stronger promoting effect (Experiment 3). The findings enrich research on psychological ownership and pro-environmental behavior, while providing practical implications for governments and enterprises in designing green nudging strategies.
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    Stable Investment Effect of Smart City Construction
    Wang Zhenjie, Yang Yi
    2026, 35 (4):  1114-1130.  doi: 10.3969/j.issn.2097-4558.2026.04.018
    Abstract ( )   PDF (2281KB) ( )  
    This paper, based on data from A-share listed companies from 2009 to 2022 and using an overlapping difference-in-differences (DID) model, examines the impact of smart city pilot policies as a new infrastructure initiative on corporate real investment. The results indicate that smart city pilot policies significantly increase the share of corporate real investment, and this conclusion remains robust after extensive robustness tests. Mechanism analysis shows that government fiscal subsidies and tax incentives are the main transmission channels through which policies promote real investment expansion. Further analysis shows that the positive effects are concentrated among private enterprises, growth-stage enterprises, enterprises with lower capital misallocation, and enterprises located in regions with lower market expectations. Moreover, the policy effect increases with deeper smart city development. These findings demonstrate that smart city infrastructure policies have a precise guiding effect on promoting the development of the real economy.
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    Driving Factors of SME Risk Spillover Effects on Shadow Banking: A Multilayer Temporal Network Perspective Across Frequency Domains
    Liu Chao, Li Juchao, Zhang Tingting, Li Guocheng
    2026, 35 (4):  1131-1144.  doi: 10.3969/j.issn.2097-4558.2026.04.019
    Abstract ( )   PDF (1980KB) ( )   PDF(mobile) (12677KB) ( 0 )  
    Accurately identifying the driving factors of the spillover effects of small and medium-sized enterprises (SMEs) on shadow banking is of great significance for maintaining the safety and stability of China’s financial system. Based on daily closing price data of China’s A-share listed SMEs and shadow banking institutions from January 2, 2018 to September 30, 2024, the ARMA-TGARCH-time-varying Copula-CoVaR model is employed to examine the risk spillover effects of “specialized and sophisticated” SMEs versus traditional SMEs. A multilayer temporal network model is used to explore eigenvector centrality characteristics of multilayer volatility spillover networks across short-, medium-, and long-term frequency domains. Furthermore, the driving factors of SMEs risk spillover from three dimensions: network centrality, macroeconomics, and microeconomics levels is systematically explored. A double/debiased machine learning model is then used to test the relationships between these factors and risk spillovers. The findings show that specialized and sophisticated SMEs exhibit stronger risk spillover effects on shadow banking than traditional SMEs. However, traditional SMEs display stronger volatility spillover effects among themselves across time and frequency domains. Network centrality, economic policy uncertainty, corporate liquidity, and shadow banking financing scale significantly increase risk spillover for both SME types. In addition, investor sentiment significantly increases spillovers only for specialized and sophisticated SMEs, while inflation significantly strengthens spillovers only for traditional SMEs.
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