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主管:中国科学院
主办:中国优选法统筹法与经济数学研究会
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Table of Content

    25 January 2026, Volume 34 Issue 1 Previous Issue   
    The Formation and Development of China’s Management Science and Engineering Discipline
    Shanlin Yang, Chao Fu, Minglun Ren, Xinbao Liu, Yezheng Liu, Bing Jiang, Jianping Li, Changyong Liang, Zhe Liang, Liang Liang, Cuiqing Jiang, Jianling Jiao, Jun Pei, Shaobo Wei
    2026, 34 (1):  1-27.  doi: 10.16381/j.cnki.issn1003-207x.2025.2189
    Abstract ( 422 )   HTML ( 34 )   PDF (1028KB) ( 458 )   Save

    The formation and development of China’s Management Science and Engineering discipline are systematically examined from multiple perspectives, including the establishment and evolution of the disciplinary system, major research fields and methodologies, key characteristics of disciplinary development, and contributions to economic and social development. It is found that China’s Management Science and Engineering discipline possesses its own distinctive developmental context, disciplinary connotations, disciplinary structure, and independent academic contributions. As a comprehensive interdisciplinary field spanning the natural sciences, technical sciences, engineering sciences, humanities, and social sciences, its formation and development are grounded in the natural, technical, and engineering sciences and are deeply embedded in management practices across various domains of China’s economic and social development. The discipline has undergone three major stages the initial stage (1949—1977), the recovery and reconstruction stage (1978 to the mid-to-late 1990s), and the prosperity and innovation stage (from the mid-to-late 1990s to the present). It has gradually developed research characteristics that are “problem-oriented, practice-driven, and innovation-oriented through interdisciplinary integration,” and has established a relatively mature disciplinary knowledge system encompassing 20 branch fields, including general management, systems management, behavioral management, operations research and optimization, and intelligent management. The discipline has made significant contributions to the advancement of global management science theory and practice and has become an indispensable component of the overall scientific system.

    The development of the discipline exhibits four core characteristics. First, it closely aligns with major national strategies and engineering practices, extracting localized theoretical insights—such as top-level design and system decomposition, technical coordination and interface management, and comprehensive integration—from landmark projects including the “Two Bombs, One Satellite” program and the Hong Kong–Zhuhai–Macao Bridge. Second, it emphasizes theoretical and methodological innovation, generating original theoretical achievements such as the Hall for Workshop of Metasynthetic Engineering, grey system theory, and extenics theory, while promoting the transformation of traditional management paradigms toward data- and AI-driven intelligent decision-making. Third, it integrates cultural inheritance with innovation by absorbing traditional Chinese management wisdom and realizing its modern transformation, thereby proposing new theories and methods such as Oriental management, harmonious management, Tao-based management, He-He management, and the Wuli-Shili-Renli (WSR) methodology. Fourth, rooted in China’s management practices, it has developed a diversified collaborative model characterized by “joint platform construction, collaborative project research, co-cultivation of talent, and shared institutional innovation,” while deepening international cooperation across multiple dimensions to advance disciplinary development.

    The discipline has also made important contributions to economic and social development. In the field of technological innovation management, it provides systematic management frameworks for major scientific and technological initiatives such as the China Space Station. In major engineering management, it offers scientific methodologies for addressing uncertainty in complex systems. In industrial development, it facilitates industrial transformation and upgrading through resource optimization and process innovation. In social governance, it enhances the efficiency of emergency response and public service delivery.

    Looking ahead, in response to new challenges and opportunities under evolving circumstances, the discipline will focus on emerging issues such as the deep integration of artificial intelligence and management, global supply chain restructuring, and green and sustainable development. It aims to achieve new breakthroughs in fundamental theories and key technologies, including complex system management and human-machine collaborative decision-making. At the same time, it is essential to further strengthen interdisciplinary integration with artificial intelligence and other fields, cultivate interdisciplinary talent, reform the talent training system, and provide more robust theoretical support and practical pathways for high-quality development and the modernization of national governance.

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    Economic Policy Uncertainty and Chinese Stock Market Volatility: A Realized SV-MIDAS Approach
    Xinyu Wu, Zhitian Zhu, Chaoqun Ma
    2026, 34 (1):  28-40.  doi: 10.16381/j.cnki.issn1003-207x.2023.1116
    Abstract ( 118 )   HTML ( 2 )   PDF (1728KB) ( 114 )   Save

    Modelling and forecasting volatility has attracted a great deal of attention in financial econometrics literature due to the fact that volatility plays an important role in many financial applications, such as portfolio allocation, risk measurement and derivative pricing. It is well known that volatility is time-varying and highly persistent, and many models have been proposed to capture these stylized facts. The stochastic volatility (SV) model is among the most popular model. However, the standard SV model is a single factor model, which ignores important information contained in the high-frequency data and macroeconomic variables.

    An alternative approach for modelling volatility is the realized stochastic volatility (RSV) model, which extends the SV model by incorporating the realized volatility measures and produces more accurate volatility forecasts than the SV model. Despite the empirical success of the RSV model, it still fails to capture the impact of macroeconomic variables on stock market volatility. In recent years, the level of economic policy uncertainty (EPU) keeps rising due to a series of major events, such as the Sino-US trade war, the COVID-19 pandemic and the Russia-Ukraine conflict. Chinese stock market is an emerging stock market, which is affected greatly by policy. As a consequence, it can be argued that Chinese stock market is closely related to EPU. The existing literature on the impact of EPU on the stock market volatility is extensive and has not reached consistent conclusions. Moreover, the existing research is mainly based on the GARCH-MIDAS model, which lacks flexibility compared to the SV framework.

    Motivated by the above interpretation, the RSV-MIDAS model framework is proposed, which combines the insights of the SV-MIDAS model and the RSV model. The proposed framework exploits the high-frequency intraday information and allows to link macroeconomic variables (such as the EPU) directly to the long-term volatility via the flexible MIDAS structure. By incorporating the EPU into the framework, it aims to investigate the impact and predictive value of the EPU on Chinese stock market volatility. The model is flexible, but has challenges in estimation owing to the lack of a closed-form expression for the likelihood function. To address this issue, a continuous particle filters-based maximum likelihood method is proposed. Monte Carlo simulation results show that the estimation method performs well.

    The RSV-MIDAS model incorporating the EPU (hereafter the RSV-MIDAS-EPU model) is applied to the monthly Chinese EPU index and the high-frequency intraday data of the Shanghai Stock Exchange Composite Index and Shenzhen Stock Exchange Component Index. The empirical results show that the EPU has a significantly negative impact on the long-term volatility of Chinese stock market. That is, an increase in the EPU level predicts lower level of the long-run volatility of Chinese stock market. The impact of the EPU on the long-run volatility of Chinese stock market is more persistent than that of the monthly realized volatility (RV). Using various loss functions and the model confidence set (MCS) test, the out-of-sample forecasting ability of the RSV-MIDAS-EPU model and the competitor models for Chinese stock market volatility are compared. It is observed that the realized measure and EPU play an important role in forecasting Chinese stock market volatility, and the RSV-MIDAS-EPU model achieves the best forecasting performance. Further, extensive robustness analysis shows that the superior predictive ability of the RSV-MIDAS-EPU model is robust. Finally, a volatility timing strategy shows that the RSV-MIDAS-EPU model yields more significant economic value of portfolio compared to other models.

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    Stock Return Synchronicity: A Unified Framework of Information and Noise
    Zhenxi Chen, Jinghan Li, Wei Zhang
    2026, 34 (1):  41-59.  doi: 10.16381/j.cnki.issn1003-207x.2024.0795
    Abstract ( 64 )   HTML ( 0 )   PDF (935KB) ( 47 )   Save

    Clarifying the source of stock return synchronicity is pivotal in determining stock market efficiency. Existing literature on stock return synchronicity contains two strands. One believes that information determines the variation of stock return synchronicity, while the other posits that noise unrelated to information shapes stock return synchronicity. Despite such contradictive explanations, stock return synchronicity is driven by both micro-level and macro-level factors. The complexity and contradiction of stock return synchronicity incur difficulty in using stock return synchronicity as a market efficiency indicator. The source and the application of stock return synchronicity in a unified framework are addressed. Based on a heterogeneous agents model, the role of rational and irrational factors from micro and macro perspectives is theoretically formulized and empirically investigated in shaping stock return synchronicity. It is discovered that the reveal of firm-specific information and stock-level irrational behaviors alleviate stock return synchronicity. In addition, market-level fundamental information and irrational noise trading intensify stock return synchronicity while high-beta stocks possess higher stock return synchronicity. The complexity of stock return synchronicity suggests that stock return synchronicity and market efficiency are interchangeable only with additional conditions. The effectiveness of interpreting stock return synchronicity as a market efficiency indicator is discussed by investigating the role of stock analysts. It is shown that the alleviation of stock return synchronicity by stock analysts is primarily driven by the reveal of firm-specific information. However, stock analysts fuel irrational behaviors as well. A market efficiency indicator is reconstructed by reorganizing the rational and irrational components of stock return synchronicity. In general, stock analysts improve market efficiency. The guidance and suggestions are provided for applying stock return synchronicity to measure market efficiency and for enhancing the practical significance of stock return synchronicity.

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    Pre-Monetary Policy Announcement Drift of Stock Price: Formation Mechanism and Determinants
    Yong Ma, Li Chen, Wei Chen
    2026, 34 (1):  60-71.  doi: 10.16381/j.cnki.issn1003-207x.2024.0361
    Abstract ( 65 )   HTML ( 0 )   PDF (1416KB) ( 19 )   Save

    In the context of the ongoing enhancement of policy communication by the People's Bank of China, exploring how the dissemination of monetary policy-related information impacts the capital market is crucial for mitigating systemic risks arising from information shocks. The formation mechanism and determinations behind stock price drift prior to the announcement of monetary policy are examined. Theoretically, within the framework of a continuous-time rational expectations model, public information—representing the central bank's communication—and the sensitivity of stock prices to monetary policy shocks are introduced to analyze the effects of private information, public information, and stock price sensitivity on the extent of stock price drift before announcements. Empirically, A-share non-financial industry data from 2010 to 2022 are used for analysis to validate the implications of the theoretical model. The findings indicate that when the precision of private information is higher or the precision of public information is lower, information asymmetry intensifies, resulting in a larger stock price drift. Mechanism analysis reveals that information asymmetry influences investors' information acquisition behavior, thereby contributing to stock price drift. Furthermore, moderating effect analysis demonstrates that the greater the sensitivity of stock prices to monetary policy shocks, the larger the stock price drift size resulting from information asymmetry.

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    Debt Financing or Equity Financing? Service Innovation Financing Strategies of a Fresh-product Platform Cold Chain
    Ying Feng, Yangchao Feng, Suyu Chen, Yanzhi Zhang
    2026, 34 (1):  72-84.  doi: 10.16381/j.cnki.issn1003-207x.2022.0841
    Abstract ( 73 )   HTML ( 0 )   PDF (1143KB) ( 37 )   Save

    The cold chain service innovation can improve its own productivity and attract more demand with high-quality services. However, capital constraints, high financing costs and risks have been the challenges faced by cold chain service innovation.It focuses on a fresh-product platform cold chain composed of a supplier, a third-party logistics service provider (TPL) and a platform service provider (platform) in this paper. Considering the TPL financing from the platform for cold chain service innovation, the impact of his financing strategies including debt financing and equity financing on the cold chain operation is explored. Research shows the service innovation cost factor and the financing interest rate are both important factors restricting cold chain service innovation in debt financing, since their rise will inhibit the improvement of the innovation level and reduce the cold chain performance. The decline in TPL’s own funds will damage himself, and benefit the platform. In equity financing, the impact of the cost factor on the system is the same as that in debt financing. The rise in valuation or the increase in fixed assets will prompt the platform to increase capital investment, thereby encouraging the TPL to carry out service innovation which benefit both the TPL and the supplier. Comparing the two financing strategies, it is found that equity financing will lead to a higher platform commission rate and a lower product sales price, which will inhibit supplier’s motivation to participate in equity financing. If TPL’s financing purpose is to improve innovation service level, he should refer to the market size to determine his financing strategy, that is, when the market is small (larger), equity financing (debt financing) should be preferred. Numerical examples show that the profits of each member and the system in debt financing are more sensitive to the product price elasticity than in equity financing. When the price elasticity is lower (higher), all members prefer equity financing (debt financing). Furthermore, introducing the innovation failure risk, it is found there exists a threshold of the innovation failure rate in each financing strategy. TPL will only finance when the failure rate is lower than the corresponding threshold, otherwise it will give up financing due to the high financing risk. In equity financing, the trend of TPL’s anti-risk capability changing with system parameters is roughly opposite to that in debt financing.The research conclusions provide theoretical supports for how to seek financing channels, choose financing strategies, and improve the service level of cold chain when the TPL service innovation is short of funds. It also provides a reference for platform service providers to make reasonable decisions on platform commissions and set financing interest rates.

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    Consensus Model of Group Decision Making Based on Three-way Conflict Analysis Considering Conflict Perception
    Qiang Zheng, Decui Liang, Yuanyuan Fu, Zeshui Xu
    2026, 34 (1):  85-93.  doi: 10.16381/j.cnki.issn1003-207x.2023.0901
    Abstract ( 81 )   HTML ( 1 )   PDF (1305KB) ( 71 )   Save

    In complex group decision making, conflicts are an inevitable issue. Conflicts often arise due to divergence in background and knowledge among experts. While the experts may face the same conflict within a given context, their distinct backgrounds and knowledge lead to varying perceptions and cognitions regarding it. At present, there has been a growing focus on the analysis and resolution of conflicts. However, limited research has considered the influence of conflict perception on group decision making. Therefore, drawing on the idea of symbol-meaning-value (SMV) space, the perception-cognition-action (PCA) concept is integrated into conflict space to construct a three-way group consensus model. Guided by conflict perception, cognitive conflict identification, and conflict resolution strategies, this model is designed to address conflict issues and facilitate consensus reaching. For conflict perception, a method for measuring conflict perception based on the characteristics of group consensus is proposed. Based on the conflict perception among experts, conflict initiators and receivers are further identified. Regarding cognitive conflicts, the Three-Way Conflict Analysis (TCA) method is employed to address the issue of cognitive conflict identification between experts and the group. Finally, for conflict resolution strategies, direction rules are designed to eliminate cognitive conflicts and facilitate the group consensus based on perceived conflicts. Furthermore, numerical experiments and robustness tests are conducted to demonstrate the feasibility and effectiveness of the proposed model. Through the numerical experiments and robustness tests, the following results are drawn: firstly, when considering conflict perception, the proposed method can effectively reduce the overall adjustment while shortening the required time to reach the consensus. Secondly, the decision results remain stable under different situations with our proposed method. Finally, the robustness tests show the stability of our proposed model in facilitating the group consensus. Overall, it contributes to the field of group decision-making in this paper by providing a systematic approach integrating opinion dynamics and the three-way conflict analysis with conflict perception. The proposed method enhances group collaboration efficiency, facilitates consensus building, and mitigates conflict problems.

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    A Novel Linguistic Multiple Attribute Decision Making Method Based on CWPHM Operator and C-DEMATEL
    Weiming Wang, Haiyan Xu, Jianjun Zhu, Shenghai Zhou
    2026, 34 (1):  94-103.  doi: 10.16381/j.cnki.issn1003-207x.2023.0903
    Abstract ( 74 )   HTML ( 0 )   PDF (912KB) ( 50 )   Save

    Multiple attribute decision-making is a very important area of research in normative decision theory. This topic has been widely developed and discussed. Considering that an expert may has vague knowledge about the preference degree of objective things, linguistic terms are often used for a decision maker as the evaluation information in some real-world multiple attribute decision-making problems. In the face of linguistic multiple attribute decision-making problems, there may exist the correlation relationships among attributes, the causal relationships among attributes, and the overall imbalances among attributes. In such situations, a new complex linguistic multiple attribute decision-making problem occurs. The new complex linguistic multiple attribute decision-making problem can be seen everywhere in real life, and it has attracted much attention from domestic and overseas experts over the last years. However, so far the methods that can solve the new complex linguistic multiple attribute decision-making problem are rare.In order to overcome this kind of deficiency, a new cloud weighted power Heronian mean (CWPHM) operator is defined and an improved cloud decision making trial and evaluation laboratory (C-DEMATEL) model is designed, and then it puts forward a novel linguistic multiple attribute decision-making method based on CWPHM operator and C-DEMATEL. First, the basic notion of CWPHM operator is defined, and some properties of CWPHM operator that include the commutativity, idempotency, boundary, and monotonicity are discussed. Then, the traditional DEMATEL method is improved, and the attribute weight determination method based on C-DEMATEL is investigated. Finally, the CWPHM operator and the attribute weight determination method based on C-DEMATEL are fused, which can obtain the comprehensive evaluation values of alternatives. A numerical example in regard to the enterprise talent selection is provided to verify the rationality and validity of the proposed method. It is shown that not only can this method consider the fuzziness and randomness of linguistic information, but this method can also consider the correlation relationships among attributes, the causal relationships among attributes, and the overall balance among attributes.The main contributions of this paper are reflected in the following three aspects (1) The existing power Heronian mean operators are extended into cloud model decision-making environments, and then a new CWPHM operator is defined, which further expands the general applicability of the power Heronian mean operators. (2) The traditional DEMATEL method is improved to investigate a new attribute weight determination method based on C-DEMATEL, which is able to make the decision results more accurate. (3) The CWPHM operator and the C-DEMATEL model are fused to put forward a novel linguistic multiple attribute decision-making method, which can give some references for solving real-world complex linguistic multiple attribute decision-making problems.

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    A Review of Identification Methods for “Stuck Neck” Technology
    Mengsi Cai, Xin Lv
    2026, 34 (1):  104-117.  doi: 10.16381/j.cnki.issn1003-207x.2024.0809
    Abstract ( 137 )   HTML ( 3 )   PDF (1482KB) ( 95 )   Save

    Under the unprecedented great changes in the current world, technological competition is increasingly becoming the focus of major power games, thus it is urgent to break through the bottleneck of key core technologies in China. Scientifically and accurately identifying “stuck neck” problems can provide important basis for achieving breakthroughs in key core technology bottlenecks and independent controllability. Researchers have recently explored various ways of identifying “stuck neck” technologies, however, no extant research systematically summarized these efforts. To fill in this research gap, the literature on identification methods of “stuck neck” technology is reviewed, and the existing problems and future trends of “stuck neck” technology identification are summarized.

    The relevant literatures published on the academic journal in the field of “stuck neck” technology connotation, characteristics, and identification methods are reviewed. First, it begins with clarifying the connotation of “stuck neck” technology by comparing it with key core technology, disruptive technology, breakthrough technology, and “trump card” technology. Then, a framework of “stuck neck” technology characteristics is proposed, which contains five essential attributes (i.e., key core technology attributes, strategic competitiveness, technical complexity, technological gap, and national security) and a series of extended attributes. According to the main methodology used in the literatures, it summarizes the “stuck neck” technology identification methods into five categories, including Delphi-based methods, indicator evaluation methods, bibliometric-based methods, network analysis methods, and machine learning methods. Finally, it concludes with identifying the research gaps in extant research and discussing some possible future directions.

    To summarize, it is found that there is a lack of clear and unified understanding of the “stuck neck” technology and its core attributes, although the majority of scholars declare that the “stuck neck” technology belongs to the category of key core technology. In addition, the various evaluation indicators built by different researchers for identifying “stuck neck” technology show a certain degree of intersection or overlap, and no research has verified the effectiveness of these indicators in cross disciplinary “stuck neck” technology identification. It is also found that few studies have integrated data from invention patents, academic papers, research reports, news reports and other sources, and less empirical research has been conducted on identifying “stuck neck” technical points at the micro level. This review would support the early warning and precise identification of potential “stuck neck” technologies, providing reference and guidance for the deployment of national technology strategies and the original technological breakthroughs in key fields, thereby promoting high-quality economic development and safeguarding national security in China.

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    Contract Effect or Relationship Effect? Governance Mechanism and Cooperative Supply Performance of Integrated Medical and Nursing Services
    Yan Nan, Tieying Feng
    2026, 34 (1):  118-127.  doi: 10.16381/j.cnki.issn1003-207x.2023.0992
    Abstract ( 49 )   HTML ( 0 )   PDF (956KB) ( 29 )   Save

    Cooperative supply is an effective way to alleviate the contradiction between supply and demand of integrated medical and nursing services and increase the total supply of services.The governance mechanism can inhibit the opportunistic behavior caused by uncertainty and asset specificity, so as to improve the organizational cooperation performance, which is an important factor affecting the cooperative supply performance of integrated medical and nursing services. However, the relationship between the governance mechanism of cooperative network and the cooperative supply performance of integrated medical and nursing services is still vague and needs to be further verified.Problem Description In this paper, the Structure Equation Model is used to analyze the relationship between variables. The research questions in this article are: (1)How the contract governance mechanism and relationship governance mechanism affect the direct and indirect performance of integrated medical and nursing services? (2)What's the mechanism between them? First of all, the analysis framework of the cooperative network governance mechanism on the cooperative supply performance is constructed, including the relationship and influence path between contract governance mechanism, relationship governance mechanism, relationship quality and performances. Secondly, based on questionnaire survey data, structural equation model is used to carry out empirical analysis. Finally, based on the test results of the research hypothesis, the effect mechanism is analyzed. Taking into account factors such as sample representativeness and sample availability in different regions, Guangzhou and Xi 'an are selected for questionnaire and interview data collection. A total of 355 questionnaires are collected. The results show that: (1)the governance mechanism of the cooperative network can be divided into contract governance mechanism and relationship governance mechanism, and the influence of both on the cooperative supply performance is characterized by alienation. (2)Contract governance mechanism has a significant positive impact on the direct performance of cooperative supply.(3)The relationship governance mechanism has a significant positive impact on the indirect performance of cooperative supply. (4) Relationship quality plays a significant mediating role between the contract governance mechanism and the direct and indirect performance. The findings of this study are of great significance for the high-quality development of integrated medical and nursing services and the theoretical innovation of cooperative governance. In practice, institutions and related subjects can match the current situation in this study according to their own actual characteristics of contract governance mechanism, relationship governance mechanism, relationship quality and cooperative supply performance, and refer to research conclusions and inspirations to break through the dilemma of cooperative supply of integrated medical and nursing services according to local conditions.

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    A Leadership Process Research Based on Knowledge Potential
    Guoquan Chen, Qingye Luo, Jingyi Wang, Yanling Lin, Xiaoye Wang
    2026, 34 (1):  128-141.  doi: 10.16381/j.cnki.issn1003-207x.2024.0185
    Abstract ( 58 )   HTML ( 0 )   PDF (786KB) ( 43 )   Save

    How does the knowledge relationship of leader-follower influence the leadership process To answer this question, it focuses on the knowledge composition characteristic of leader-follower dyad. Based on potential science, a new construct, “knowledge potential”, is introduced,which describes the product of differences and overlaps in knowledge between a given leader and follower. It is proposed that within a leader-follower dyad, as the knowledge differences in some domains increases, and the knowledge overlaps in other domains also increases, the knowledge potentialgrows larger, which further contribute to the leadership process. It is theorized that (1) knowledge differences of a leader-follower dyad in certain domains can enhance the credibility of the leader during persuasion process, enable leader to discern the challenge encountered by follower in his or her tasks then offer pertinent feedback and guidance, foster the development of follower’ work competencies and professional demeanor; (2) knowledge overlaps of a leader-follower dyad in other domains facilitate the reduction of communication and coordination costs and foster the construction of higher-quality leader-member exchange relationships; (3) Based on the argument that “difference × overlap = potential,” the knowledge differences and overlaps of a leader-follower dyad in different domains mutually reinforce and complement each other, collaboratively influencing the leadership process; (4)Which domains does knowledge differences and knowledge overlaps come from depend on contextual factors. Lastly, the theoretical contributions of knowledge potential to leadership, team knowledge composition and potential science literature are discussed, as well as its practical implications for organizations and leaders.

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    Research on Online Cooperation Mode of Rural Logistics Based on Digital Platform
    Zhongfei Duan, Weizhen Rao, Peng Liu
    2026, 34 (1):  142-152.  doi: 10.16381/j.cnki.issn1003-207x.2023.1864
    Abstract ( 63 )   HTML ( 0 )   PDF (1862KB) ( 36 )   Save

    China vigorously promotes the digital empowerment of platforms and joint distribution of rural logistics, focusing on the difficulty of the last kilometer delivery of consumer goods to villages, the rural logistics two-echelon (county-town-village) online cooperative mode is proposed based on digital platform. Firstly, the model of two-echelon cooperative vehicle routing problem with heterogeneous fleets is constructed and optimized by adaptive large neighborhood search algorithm. Secondly, considering the marginal contribution of members, the contribution quantification model of rural logistics cooperative enterprises is designed, and the nucleolus are used to calculate optimal cost allocation value, so as to protect the interests of cooperative members. Finally, the effectiveness of the cooperation model is verified through numerical experiments, and then the impact of vehicle heterogeneity and village dispersion on the cooperation efficiency deeply is analyzed. The results show that: collaborative mode of rural logistics enterprises can reduce cost of delivery to villages, realize the complementary spatial location of rural customer orders. Simultaneously, collaborative distribution could improve the delivery efficiency of rural delivery logistics, and the maximum cost savings rate is about 54.96%. When a member adds a new type of heterogeneous fleet, cooperation can improve the flexibility of collaborative vehicle combination and further reduce the collaborative cost between the alliance and members; the higher the degree of dispersion of village distribution, the more significant the benefits of the online two-echelon cooperation.

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    Contract Design of Government Incentives for Collaborative Innovation in Scientific and Technological Innovation Platforms: A Double Information Asymmetry Perspective
    Qiang Hu, Jiqing Xie, Guangsi Zhang, Ling Liang, Jiaping Xie
    2026, 34 (1):  153-166.  doi: 10.16381/j.cnki.issn1003-207x.2024.0917
    Abstract ( 69 )   HTML ( 3 )   PDF (1680KB) ( 54 )   Save

    China regards scientific and technological (S&T) self-reliance and self-improvement as strategic support for national development, and governments at all levels are actively promoting the construction of high-capacity science and technology innovation platforms. S&T innovation platforms gather a large amount of S&T innovation resources and are important vehicles for research users to carry out S&T innovation activities. The efficient operation of S&T innovation platforms is a powerful means to realize high-level self-reliance and self-improvement in science and technology. The introduction of a market-based operation mechanism can improve the operation efficiency of S&T innovation platforms. Therefore, for governmental S&T innovation platforms, how to build a market-based operation mechanism and how the government can stimulate the collaborative innovation of S&T innovation platforms have attracted our attention.

    With the government as the principal and the platform enterprise as the agent, it is a feasible model for the government to entrust the operation of S&T innovation platform to the platform enterprise. However, in the principal-agent process, the government will face private information from the agent, including ex-ante private information about the platform’s operational capability and ex-post private information about the supporting service inputs. Given this, the principal-agent theory is applied to design two kinds of incentive contracts under the double information asymmetric: one-time payment and proportional share payment, the incentive effect of different contracts on the agent is compared, the preference of the government and the agent on the contract is discussed, and then the government’s contract selection strategy is analyzed.

    The following key findings are yielded in this paper. (i) The government needs to have certain conditions to implement the screening contract, otherwise it can only choose the pooling contract. (ii) Based on the goal of maximizing the benefits of S&T and the economy, different contracts may be the best choice for the government under the corresponding circumstances. (iii) However, from the perspective of separating different types of agents, the government should choose the proportional payment screening contract. From the perspective of incentivizing the quality of the platform’s supporting services, it should choose the one-time payment pooling contract. (iv) Agents need to make contractual choices depending on their ability types, but any ability type of agents should avoid the pooling contract of proportional share payment.

    The research work can bring some managerial insights to the government and enterprise. First, if the government chooses to implement a screening contract, it cannot design a one-time payment contract because it can only become a pooling contract. Second, the government’s proportional share payment screening contract can screen enterprises’ private information, which solves the adverse selection problem of “bad money drives out good”. Third, from the perspective of incentivizing platform enterprises to provide higher-quality supporting services, the government should choose a one-time payment contract. Fourth, platform enterprises of all capacity types should not opt for the proportional share payment pooling contract.

    The principal-agent modeling is applied under double information asymmetric to the study of operations management of S&T innovation platforms, which enriches the literature in the fields of mechanism design, collaborative innovation, and platform-based operations management. Admittedly, there are some limitations in this study, which are mainly reflected in the fact that the price of S&T innovation resource-sharing services is considered to be controlled by the government, that is, it is defined as an exogenous variable in the model, and although some useful conclusions are obtained, it fails to discuss the market pricing mechanism of S&T innovation platforms well, which will be the direction of further research in the future.

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    Can the Platform's Self-operated Channels Drive Away Third-Party Sellers Who Sell Inferior Products?
    Qi Zhang, Jingxian Chen, Liang Liang
    2026, 34 (1):  167-177.  doi: 10.16381/j.cnki.issn1003-207x.2023.0540
    Abstract ( 69 )   HTML ( 0 )   PDF (1617KB) ( 41 )   Save

    In recent years, the realm of electronic commerce in China has experienced rapid growth, leveraging the transformative force of platform economics. However, concomitantly, the implementation of complementary regulatory measures has lagged behind. Consequently, issues such as the coexistence of reputable and unscrupulous third-party sellers and the proliferation of counterfeit and substandard products have arisen. An increasing number of retail platforms have embarked on expanding their self-operated channels, characterized by stringent quality control and superior services, to mitigate the prevailing difficulties in product quality management. Nevertheless, this intensifies the competition between self-operated channels and third-party sellers, potentially compelling some third-party sellers to consider shifting their sales channels. It aims to delve into the preference of retail platforms with self-operated channels concerning third-party sellers when contemplating product quality, as well as the sales channel decisions made by these third-party sellers. It endeavors to explore the following questions: What is the strategic equilibrium game involving the transition between self-operated channels and third-party sellers? And does the establishment of self-operated channels on the platform lead to the expulsion of sellers peddling inferior products?It focuses on a retail platform that has both self-operated channels and incorporates third-party sellers. By constructing a three-stage game model, it investigates the commission decisions of the retail platform in light of product quality and the sales channel choices of third-party sellers. Firstly, the equilibrium profits of third-party sellers are compared given a specific platform commission, thereby identifying the conditions under which third-party sellers opt to switch sales channels. Secondly, assuming the choice made by third-party sellers, the commission pricing decisions of the retail platform are analyzed, by comparing the platform's profits under different commission strategies, and the optimal decision for the platform is determined to expel sellers. Lastly, the impact of the platform's decision to expel third-party sellers, as well as product quality and switching costs, on sales volume and profits for all parties involved is explored.The research findings indicate the following Firstly, when the cost of self-operation is below a certain threshold, the retail platform will establish self-operated channels. Furthermore, the platform's commission increases as the quality of sellers' products improves, and when the commission exceeds the switching cost, sellers will transition to alternative sales channels. Secondly, the retail platform is only inclined to retain both sellers or solely expel sellers peddling low-quality products; it does not favor expelling all sellers and solely relying on self-operated channels to sell products to consumers. Thirdly, for sellers with low product quality and high switching costs, even if the retail platform prefers to retain them, their sales volume on the platform will be zero.

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    Platform Adjudication or Expert Review? Study on the Online Dispute Resolution Mechanism of E-commerce Platforms
    Zhongzhong Jiang, Zhining Jiang, Na He
    2026, 34 (1):  178-189.  doi: 10.16381/j.cnki.issn1003-207x.2023.2233
    Abstract ( 64 )   HTML ( 1 )   PDF (1978KB) ( 47 )   Save

    The prosperity of e-commerce has been promoted by the rapid development of Internet technology, but a large number of online disputes between merchants and consumers have also been brought about. The “efficient, convenient and low-cost” Online Dispute Resolution (ODR) has become an important way of resolving online disputes. Among them, a platform adjudication mechanism centered on its own adjudication is adopted by some e-commerce platforms, while disputes are resolved by hiring expert juries by others. Therefore, how to scientifically choose an online dispute resolution mechanism to better resolve online disputes and enhance platform profits is an important decision-making issue faced by e-commerce platforms. Focusing on the problem, the Stackelberg game method is used by this paper to construct a game model between e-commerce platforms and merchants under two mechanisms: platform adjudication and expert review. The impact of the two review mechanisms on platform evaluation standards, product quality, profits, etc. is explored, and the relative advantages of the platform adjudication mechanism and the expert review mechanism are analyzed. The optimal choice and decision optimization of online dispute resolution mechanisms for e-commerce platforms are studied. The study shows that the selection strategy of the online dispute resolution mechanism of e-commerce platforms is mainly determined by the proportion of consumer disputes and the cost coefficient of quality for merchants. The subjective decision-making bias of the platforms can be eliminated by the expert review mechanism, and higher quality standards will be set by the platforms under the platform adjudication mechanism in order to motivate the merchants to improve the quality of their products and increase the surplus of consumers at the same time. At the same time, the penalties for merchants will be reduced by the platforms with the increase of the proportion of consumer disputes. The findings of this study may provide useful management insights for e-commerce platforms in online dispute management and industry development.

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    Perception of Benefits and Differentiated Membership Strategies of E-commerce Platforms
    Jiang Wu, Linxiu Hu, Xi Zheng
    2026, 34 (1):  190-199.  doi: 10.16381/j.cnki.issn1003-207x.2023.1255
    Abstract ( 67 )   HTML ( 0 )   PDF (1308KB) ( 37 )   Save

    In order to further tap the consumption potential, some domestic e-commerce platforms explore differentiated paid membership modes. However, there is a research gap on how to develop differentiated membership strategy.The interaction between consumer perception of membership benefits and differentiated membership strategies of e-commerce platforms is studied in this paper. First, paying members are divided into three differential types based on the member benefits provided by the e-commerce platform: unified membership, differentiated membership with order-related benefits and differentiated membership with order-independent benefits. Second, the membership volume is calculated from the consumers’ perspective. Third, the optimal membership fee and value of membership benefits are solved when the e-commerce platform implements the three membership strategies. Additionally, the impact of shopping discounts, reference effects, and preferences for additional benefits on the e-commerce platform are analyzed, and the conditions under which the three membership strategies perform effectively are identified.The results show that under the unified membership, e-commerce platforms not only increase shopping discounts but also reduce membership fees to retain consumers. Under the differentiated membership with order-related benefits, the optimal decision of the e-commerce platform depends on the amount of consumption. Under the differentiated membership with order-independent benefits, the optimal decision of the e-commerce platform depends on the reference effect and consumers' preference for additional benefits. When the reference effect coefficient of additional benefits is relatively small, the differentiation strategy based on order-independent member benefits is a better choice. When the e-commerce platform changes from unified membership to differentiated membership, it is necessary to add a membership level to make the reference effect play and change the original member benefits (shopping discounts or additional benefit value), so that differentiated membership can make the e-commerce platform obtain higher profits. These findings can provide suggestions for practitioners to change membership strategies and understand how differentiated membership strategies affect consumer decisions.

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    Study on Dynamic Pricing of Online Product Based on Sales Update Rule and Anchoring Effect
    Xuwang Liu, Yujie Zhang, Wei Qi, Xinggang Luo
    2026, 34 (1):  200-211.  doi: 10.16381/j.cnki.issn1003-207x.2023.0753
    Abstract ( 50 )   HTML ( 0 )   PDF (1121KB) ( 35 )   Save

    Customers’ two-factor anchoring behaviour gives them incredible resilience in the rapidly evolving e-commerce landscape. Businesses need to figure out how to attract them and sway their buying habits with low-priced preorders. Businesses can enjoy the extraordinary benefit of becoming “price anchored” as customers exhibit outstanding purchase intent during the eagerly awaited pre-sale discount period. Furthermore, after the end of the discount presale, the high sales volume generated during the presale period will continue to enhance consumer purchase intent through “sales anchored”. However, due to limitations imposed by the platform’s sales update restrictions, this beneficial effect will wear off eventually. In this context, under the background of discount presales, with a focus on dynamic pricing, it is crucial to explore the intricate mechanisms of the price-sales dual-factor anchoring effect on consumer behavior and the complexities arising from the constraints of sales update rules on pricing and marketing strategy formulation for online retailers. So, in this paper, the Multinominal Logit Model (MNL) in the context of discount presale is used to build an n-stage dynamic pricing model considering consumers being anchored by product price and sales, and the effects of the two-factor anchoring effect and sales update rules on the dynamic pricing, sales, and profit of online retailers are also analyzed.

    In the model construction, the price-sales dual-factor anchoring effect is incorporated into the utility function, and the consumer’s purchasing choice behavior in the dynamic pricing problem of products is simulated based on the MNL model. During the presale period, online retailers simultaneously disclose the presale price and the regular price, resulting in consumers being anchored by both price and sales factors. At this moment, the utility gained by consumers choosing to purchase the product incorporates both price anchoring and sales anchoring terms. These terms are represented by anchoring coefficients multiplied by the differences between the current product price/sales and the consumer’s price/sales anchoring points. Consumers who choose to purchase during the regular sales period are not price-anchored but are influenced only by the sales anchoring effect. In this case, if consumers choose to buy the product, the utility they gain includes the sales anchoring effect term. The term is represented by sales anchoring coefficient multiplied by the difference between the current cumulative sales and the consumer’s psychological sales anchor point. Furthermore, by transforming the profit function into a function of purchase probability, it has been proven that the profit function is concave. The optimal dynamic pricing of the product, along with the corresponding sales and profit, has been derived.

    Numerical experiments are conducted to analyze the optimal dynamic pricing, sales, and profit variations of the product throughout its entire lifecycle, considering the dual-factor anchoring effect of consumers on price and sales. It also compares the differences in optimal dynamic pricing, sales, and profit for online retailers under regular mode and Taobao mode. Furthermore, the research focuses on the sales accumulation period and explores the disparities in product pricing, sales, and profit under different sales update rules.

    It is found that, under the influence of the anchoring effect, discount presales are applicable to online retailers’ new product sales and can bring a presale “bonus”. However, due to sales update rules, this presale “bonus” will dissipate over time, and online retailers will have to take measures to increase consumer valuations in order to cope with subsequent sales downturns. The results of this paper will provide theoretical guidance for the dynamic pricing of online retailers.

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    Optimal Improvement of Retrieval Time for PBS System by Considering Parallel Movement
    Yunfeng Ma, Xijie Yang, Yugang Yu, Liang Reng
    2026, 34 (1):  212-220.  doi: 10.16381/j.cnki.issn1003-207x.2022.0495
    Abstract ( 43 )   HTML ( 0 )   PDF (1167KB) ( 25 )   Save

    Puzzle-based storage (PBS) is an emerging compact storage system where each cell is empty oroccupied by an item, and each item can be moved to its adjacent empty cells. Under the single-load movement assumption, some existing exact and heuristic algorithms have enabled the minimum number of moves for the single-item retrieval problem in a puzzle-based storage system with multiple escorts (SRPME). Nevertheless,they failed to effectively optimize the retrieval time, which is a critical indicator of system throughput.

    In this article, both movement cost and retrieval time are taken into account in the SRPME. Based on a solution obtained by the existing algorithms for solving the single-item retrieval problem in PBS system with multiple escorts, an optimal algorithm considering parallel movement is designed, that is, to reduce the moving time of the item retrieval while keeping the number of item-moves unchanged. The proposed algorithmis based on the idea of implicit enumeration, and it only judges the parallelism between the first move of each escort during each iteration.

    Extensive numerical experiments are used to evaluate the impact of parallel movement and the algorithm’s performance, where the system size of the instances ranged from 4×4 to 30×30. The results show that the parallel movement saves an overall of more than 10% in retrieval time, and the number of O-move and the actual number of escorts used are the main factors affecting parallel movement.The average optimization ratio increases as the size of the system grows, while its marginal value decreases. The proposed method has good computational performance in small to medium-size issues, which can be seen as a good choose in a large variety of future applications of the PBS systems.

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    Research on Joint Dispatching of Electric Bus Operation and Charging Considering Facility Usage Conflict
    Yang Cui, Rui Zhao, Hongli Xu, Jing Zhou
    2026, 34 (1):  221-233.  doi: 10.16381/j.cnki.issn1003-207x.2023.1411
    Abstract ( 41 )   HTML ( 0 )   PDF (1475KB) ( 22 )   Save

    With the reduction of non-renewable energy and environmental pollution issues, the electrification of vehicles is urgent, and electric buses have emerged and accounted for 59.1% of China’s total public transportation. Due to limited battery capacity and long charging time, charging scheduling has become one of the key operational management issues for electric buses. The normal operation of public transportation requires reasonable charging scheduling to ensure, which in turn determines the inbound and outbound time and dwelling time of buses, thereby affecting charging scheduling. The collaborative optimization of charging scheduling and operation scheduling can improve the overall operational efficiency of public transportation. When there is in transit charging, the collaborative optimization of the two is more important. In order to avoid charging conflicts and optimize charging plans, the bus inbound and outbound time are adjusted under the constraints of the initial bus inbound and outbound schedule and the maximum adjustable time. A joint optimization model of the electric bus operation schedule and charging plan is established to minimize charging costs while avoiding charging conflicts and ensuring continuous charging. In order to form a comparative analysis, a charging scheduling optimization model is also constructed for electric buses operating according to a fixed timetable. Finally, taking four bus routes in Shenzhen as an example, a numerical analysis is conducted. The results show that compared to charging scheduling under fixed time expression, the joint optimization of operating schedule and charging scheduling can effectively reduce the total charging cost; Meanwhile, as the energy consumption per kilometer increases, the advantages of the joint optimization model become more apparent.

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    Location-routing Problem Considering Psychological Cost in Emergency Logistics
    Lifang Peng, Nannan Zhao
    2026, 34 (1):  234-243.  doi: 10.16381/j.cnki.issn1003-207x.2023.0577
    Abstract ( 59 )   HTML ( 0 )   PDF (1460KB) ( 35 )   Save

    With the increasing risks of geological disasters, large-scale infectious diseases, and climate change, humanitarian rescue efforts have risen significantly. To reduce disaster losses, scientific emergency facility location and material distribution system optimization are crucial. Additionally, attention must be given to the psychological and mental impact on affected populations post-disaster. In emergency logistics management, unmanned aerial vehicles (UAVs) have become a focus due to their efficiency, flexibility, low energy consumption, and minimal road occupancy advantages. Integrating trucks and UAVs for joint delivery can effectively address traditional distribution challenges and “last-mile” risks. This new logistics operation model poses significant theoretical and practical challenges to vehicle routing problems, gaining more scholarly attention.The Location-Routing Problem with Drone (LRPD) is a novel optimization problem that requires solving warehouse location, UAV and vehicle path decisions, as well as addressing synchronization issues in UAV and vehicle separation and convergence operations. A demand-splitting truck-UAV collaborative location-routing model is established, including: (i) developing a location-routing model allowing demand splitting and truck-UAV joint delivery to minimize delivery time, system economic costs, and affected population's psychological costs; (ii) proposing an improved Non-Dominated Sorting Genetic Algorithm (NSGA-II) with a local search operator and verifying its performance through a set of numerical experiments.Through constructing the m-SDLRPD test set, the computational performance and speed of the ENSGA-II algorithm are tested. The experimental results demonstrate that the hybrid multi-objective evolutionary algorithm with dedicated local search operators possesses good solution quality and algorithmic performance. Comparing m-SDLRPD with the truck-only mode, it is found that UAV application significantly enhances material delivery efficiency. Sensitivity analysis of UAV parameters reveals that batch delivery is more effective in reducing travel time compared to increasing UAV payload capacity. An application example of Shanghai's material distribution illustrates the practical use of the proposed model and algorithm.

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    Studing on Enterprise CCER Project Development Models and Coordination Mechanism from the Perspective of Risk Sharing
    Peihan Li, Zhongze Wang, Xiqiang Xia, Mengyuan Lu
    2026, 34 (1):  244-255.  doi: 10.16381/j.cnki.issn1003-207x.2023.1401
    Abstract ( 48 )   HTML ( 0 )   PDF (1885KB) ( 35 )   Save

    Chinese certification emission reductions (CCER) is a fundamental element of carbon trading system and is regarded as a key path to compensate for the positive externality of renewable energy projects and promote green development of energy industry. To complete project development, certified emission reduction enterprises usually need to cooperate with carbon asset management companies. Common CCER project cooperation models include pure consultancy, revenue and risk sharing, and centralized decision-making. Under the background of the restart of CCER market, when selecting cooperation models for CCER project development, enterprises need to comprehensively consider various factors, such as revenue, risk, project clean development level, and environmental impact. Therefore, it is necessary to analyze from multiple perspectives which cooperation model certified emission reduction enterprises should choose for CCER project development. In addition, to achieve a centralized decision-making level, appropriate contracts need to be designed to coordinate the benefits of both parties, reduce project risks, and motivate certified emission reduction enterprises to carry out clean development of CCER projects.To explore the impact of different development models of CCER projects on enterprise decisions from a risk perspective, a game model is constructed based on three CCER cooperation models, consisting of a third-party carbon asset management company and certified emission reduction enterprises. The different cooperation models are compared in terms of unit product price, project development scale, profit, clean development level, and environmental impact, providing decision-making basis for the optimal project cooperation model for carbon asset management enterprises and certified emission reduction enterprises. In addition, to address the issue of marginal efficiency loss in decentralized decision-making, optimal clean development level coordination contract and optimal revenue sharing ratio coordination contract are designed to achieve supply chain coordination.Through the study, it is found that when the risk of project development failure falls within a certain threshold range, the carbon asset management company participating in the revenue and risk sharing model will share more profits. Moreover, when the risk of project development failure exceeds a certain threshold, the revenue and risk sharing model can effectively expand the project development scale and promote environmental improvement. However, when the environmental benefits of the project are significant, the revenue and risk sharing model is not always beneficial for the profit of certified emission reduction enterprises and leads to lower levels of clean development. By designing optimal clean development level coordination contracts and optimal revenue sharing ratio coordination contracts, certified emission reduction enterprises can be encouraged to develop CCER projects based on centralized transaction prices, project scales, and clean development levels, thereby achieving supply chain coordination. Therefore, when signing the revenue and risk sharing cooperation agreement, both parties should focus on negotiating and coordinating the optimal project revenue sharing ratio.In addition, the project price sensitivity coefficient is also an important factor affecting the cooperation between third-party carbon asset management companies and certified emission reduction enterprises. As the price sensitivity coefficient increases, the space for coordinated profits becomes larger. In the face of a market with limited elasticity, certified emission reduction enterprises should cautiously develop and adopt a prudent development strategy. The government should ensure that the inclusion of CCER plays a driving role in the carbon market while ensuring that offset mechanisms have a certain degree of flexibility.

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    Optimization of Post-disaster Transport Network Restoration Strategies Considering Ground-Air Coordination
    Xinya Liu, Jianjun Wu, Yunchao Qu, Hao Fu, Xin Yang, Tianlei Zhu
    2026, 34 (1):  256-267.  doi: 10.16381/j.cnki.issn1003-207x.2024.2093
    Abstract ( 53 )   HTML ( 0 )   PDF (4355KB) ( 36 )   Save

    In recent years, the increasing frequency of extreme weather events has caused significant disruptions to urban transportation networks, leading to reduced road capacity, impaired mobility, severe economic losses, and even casualties. Efficient road network restoration strategies are critical for rapidly restoring functionality and enhancing network resilience. However, traditional approaches primarily focus on ground transportation, neglecting the emerging potential of ground-air coordinated systems.The application of the ground-air coordinated mode in future urban settings is explored and a multimodal transportation network framework integrating urban surface traffic and low-altitude air mobility is developed. Considering network resilience, repair crew dispatching costs, and multimodal traffic flow distribution, a bi-level optimization model for post-disaster road network restoration is proposed. The upper-level model determines the repair sequence for damaged road segments and the allocation of low-altitude air traffic resources, while the lower-level model incorporates an extended user equilibrium traffic assignment framework that accounts for ground-air collaboration. Based on the characteristics of the model, an adaptive large neighborhood search heuristic algorithm based on node importance is developed. The proposed model and algorithm are validated using the Sioux-Falls network. Results demonstrate that the ground-air collaborative mode effectively alleviates ground traffic congestion, accelerates road network recovery, and enhances overall resilience. It provides a theoretical basis for optimizing urban road network restoration strategies in response to major emergencies.

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    Risk Assessment Model Construction of Urban Rainstorm Cascading Events Based on Risk Feature Tracing
    Zhaoge Liu, Xiangyang Li, Xiaohan Zhu
    2026, 34 (1):  268-281.  doi: 10.16381/j.cnki.issn1003-207x.2023.2025
    Abstract ( 62 )   HTML ( 3 )   PDF (12112KB) ( 88 )   Save

    Urban rainstorm disasters can easily induce large-scale, small-size, differentiated cascading events (urban rainstorm cascading events, URCE) such as damage to infrastructure and residents being trapped, etc. Disaster prevention urgently needs comprehensive and accurate assessment of the risks of different types of URCEs, but it faces the model performance constraints caused by sample data risk feature incompleteness. The comprehensive description of URCE risk features in historical cases is considered, and a risk assessment model construction method is proposed based on tracing back risk features. This method follows the basic idea of seeking “causes” from “effects”, uses case-based reasoning to trace risk features from historical cases with the connection of risk scenario descriptions, and then uses machine learning methods to learn the association between risk features and URCE risk categories, thus completing the adaptive construction of risk assessment models. The case study results of risk assessment for 6 typical URCE risks in Wuhan show that: the proposed method helps to solve the problem of incomplete features in constructing risk assessment models by tracing risk features based on cases, thus improving the accuracy of risk assessment. It also has good effects in distinguishing risks and small sample modeling. Compared with traditional comprehensive evaluation, damage curve and other methods, the proposed method has significant advantages in constructing small-grained, complex event coupled risk assessment models, which better meets the goal of accurate management of complex risks.

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    Analysis of the Joint Anti-Counterfeiting Strategy between Government and Enterprises under Major Public Health Emergencies
    Yue Wang, Ming Liu, Jie Cao
    2026, 34 (1):  282-292.  doi: 10.16381/j.cnki.issn1003-207x.2024.0918
    Abstract ( 57 )   HTML ( 0 )   PDF (1235KB) ( 41 )   Save

    During major public health emergencies, some enterprises exploit the surge in demand by engaging in counterfeiting to maximize profits. Effectively addressing this issue of combating counterfeiting, protecting consumer rights, and maintaining market order has become a critical concern. In response, products are categorized into three types based on appearance and quality: qualified products, deceptive counterfeit products, and non-deceptive counterfeit products. A game-theoretic model is then developed, with the government, compliant enterprises, and counterfeiters as key players. The model analyzes market demand, pricing strategies for each product type, and determines the optimal pricing for these products.

    Using the 2009 H1N1 flu pandemic as a case study, the analysis reveals that when deceptive counterfeit products dominate the market, compliant enterprises can reduce demand for these counterfeits by raising the prices of qualified products. Conversely, when non-deceptive counterfeit products prevail, compliant enterprises must lower the prices of qualified products to curb demand for these lower-quality products. Furthermore, government penalties and inspection efforts play a crucial role in deterring counterfeiting. It is found that only when fines and inspection intensity surpass a certain threshold can counterfeiting activities be effectively suppressed. Additionally, the formation of an anti-counterfeiting alliance between the government and compliant enterprises significantly enhances the efficiency of combating counterfeit products, especially at key stages of the product inspection process.

    The results demonstrate that joint anti-counterfeiting efforts by the government and compliant enterprises represent an effective strategy, particularly during major public health emergencies. A systematic analysis shows that imposing sufficiently high penalties and conducting thorough inspections can effectively deter the production of both deceptive and non-deceptive counterfeit products. Moreover, compliant enterprises can further reduce demand for counterfeit products by strategically adjusting the prices of qualified products, thereby contributing to the overall reduction of counterfeits in the market.

    In summary, it enriches the existing literature by illustrating that a game-theoretic model of government-enterprise collaboration in anti-counterfeiting not only explains the strategic decisions of key stakeholders but also provides valuable theoretical support and practical guidance for policy-making, especially in the context of major public health emergencies.

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    Economic Assessment of Electric Vehicle Considering the Volatility of Renewable Energy
    Ya Wang, Bowen Yi
    2026, 34 (1):  293-302.  doi: 10.16381/j.cnki.issn1003-207x.2023.1325
    Abstract ( 50 )   HTML ( 3 )   PDF (825KB) ( 42 )   Save

    The future energy system, centered around electricity, must integrate a high proportion of volatile renewable energy sources on the supply side while addressing the large-scale and unpredictable charging demands of electric vehicles on the consumer side. Centralized charging of electric vehicles during peak load hours can significantly undermine the safety, reliability, and economic dispatch of the power grid. Thus, it is crucial to coordinate and guide the charging and discharging processes of electric vehicles to mitigate their adverse impact on the grid load curve and potentially transform them into high-quality energy storage units. This is vitally important for our country to handle the fluctuations posed by a substantial reliance on renewable energy.

    A provincial power economic dispatch model is presented that covers 8,760 hours and incorporates characteristics of wind and solar fluctuations. It includes unit operational constraints, state transfer equations, power output limitations, ramping capabilities, and supply-demand balance constraints. The model bases the dispatch of generator units on external power supply and grid structural data, thereby determining the optimal hourly power output, startup, shutdown, and operational modes at the provincial level. Furthermore, the charging and discharging behavior of electric vehicles are integrated into the model to examine the synergistic effects between various operational modes of electric vehicles and the variability of renewable energy sources.

    It focuses on Guangdong, Henan, Ningxia, and Sichuan as typical provinces for optimal dispatch and simulation analysis in this study. Differences among these provinces are primarily due to variations in power demand, supply structures, and resource endowments. The data from 2018 are used as a baseline, spanning all 8,760 hours of the year, sourced from public records. It outlines four scenarios: a baseline, disordered charging, coordinated charging, and Vehicle-to-Grid (V2G).

    Results indicate that disordered charging of electric vehicles exacerbates peak and valley disparities in grid load, increasing the operational costs of the power system. Conversely, adopting collaborative vehicle-grid models such as coordinated charging and V2G can effectively smooth the net load curve, yielding additional economic benefits. Therefore, it is essential to motivate users to charge during low grid load periods using demand response systems like peak and off-peak electricity pricing.

    The main factors influencing the economic viability of electric vehicles connected to the grid include the availability of volatile renewable energy and the level of flexible resources within the power system. Different regions should develop tailored strategies based on their specific resource characteristics. In many areas of northwest and central China, the power system has limited flexible resources and a high proportion of wind and solar generation, making the economic value of grid-connected electric vehicles substantial. However, the current low number of electric vehicles in these regions suggests that if this economic value could be shared with users through an appropriate mechanism, it could significantly boost the adoption of electric vehicles.

    As the penetration of wind and solar power continues to rise, coordinated charging and V2G strategies are poised to realize greater economic value once electric vehicles are integrated into the grid. Although an increase in vehicle ownership might slightly dilute the value per vehicle, this impact remains relatively limited. In pursuing carbon neutrality, China needs to shift from merely expanding the scale of low-carbon sectors, such as electric vehicles and renewable energy generation, to establishing a cross-sectoral integration and interoperability system, thereby constructing a new energy system that harmoniously integrates vehicles and the grid.

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    Can "Double Points" Completely Replace "Subsidies"? Based on the Analysis of Output Trade-off of Fuel and New Energy Vehicles and Fuel Consumption Reduction Strategy
    Yongxi Yi, Meng Zhang, Yu Cao, Yuqiong Li
    2026, 34 (1):  303-314.  doi: 10.16381/j.cnki.issn1003-207x.2023.0051
    Abstract ( 48 )   HTML ( 0 )   PDF (2162KB) ( 38 )   Save

    China’s new-energy-vehicle purchase subsidy policy and double credit policy for vehicles have both played a positive role in the low-carbon development of the automotive industry. However, problems such as the increased financial burden of the subsidy policy have made the complete withdrawal of the policy come to the forefront. At the same time, there is a common concern in politics and academia that the withdrawal of the policy will not be conducive to the low-carbon development of the automobile industry. To this end, the dynamics of the demand for fuel and new energy vehicles and the reduction of fuel consumption and goodwill of automobiles is analyzed. It establishes a differential game model for the supply chain that mixes the production of fuel and new energy vehicles. Based on this, it analyzes the impact of three different policies: subsidies for the purchase of new energy vehicles only, double credit for automobiles only, and subsidies plus double credit on the fuel consumption reduction of cars and the production of the two types of automobiles. It is concluded that as long as a higher proportion of new energy vehicles is required in the double credit policy, the implementation of the double credit policy can promote fuel consumption reduction investment; the withdrawal of the new energy vehicle purchase subsidy will not reduce the demand for fuel vehicles, nor will it have an impact on fuel vehicle consumption reduction. Still, it will affect the market demand for new energy vehicles. However, as long as the mechanism of the dual credit policy is appropriately adjusted, such as the proportion requirement of new energy vehicles and the point value of each new energy vehicle, the demand for new energy vehicles can be promoted to make up for the impact of the complete withdrawal of subsidy policies, and the adjustment of these policies can also promote the fuel consumption reduction of fuel vehicles; After the implementation of the double credit plus subsidy policy, the withdrawal of the subsidy policy so that the manufacturer, the retailer, and the entire profits of the supply chain may go down as well as up, but the change in their earnings is not significant, as the analysis of several numerical examples shows that the difference in the profit levels of all parties in the supply chain and the overall profit level under the two policies is only in the range of 0.28% to 1.92%. The research results provide a theoretical basis for the complete withdrawal of the new-energy-vehicle purchase subsidy policy.

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    Research on the Assessment and Enhancement Methods for the Resilience of Supply and Demand Relationships in Cloud Manufacturing Services Considering Risk Sharing
    Jianpeng Mao, Jianfeng Lu, Jialin Song, Pengze Zhu
    2026, 34 (1):  315-326.  doi: 10.16381/j.cnki.issn1003-207x.2024.0848
    Abstract ( 43 )   HTML ( 0 )   PDF (2357KB) ( 48 )   Save

    The improvement of supply-demand relationship resilience is crucial to enhancing the resilience of industrial and supply chains. Therefore, the platform advantages of cloud manufacturing are utilized to study the quantitative methods for improving the resilience of supply-demand relationships. First, based on whether the supply and demand parties purchase demand forecasting services from the cloud platform, the cloud manufacturing service transaction model is divided into three modes: independent risk-bearing mode, one-party cooperation with the cloud platform mode, and tripartite cooperation mode. The optimal pricing strategies for both the supply and demand sides under these three transaction modes are then calculated using a Stackelberg game. Second, the profits and loss rates of the supply and demand sides under market disturbances are used as evaluation indicators of the resilience of the supply-demand relationship, and the entropy weight method is employed to quantify the resilience level. A method is proposed to improve the resilience of the supply-demand relationship by combining quantity flexibility contracts and cost-sharing contracts to address disturbance risks in the tripartite cooperation mode. Numerical simulations are conducted to illustrate the impact of market demand changes on the optimal pricing and profits of both parties, analyze the rationality of cost-sharing contracts under different disturbance scenarios, and compare the resilience levels across different cooperation modes. The results show that enterprises cooperating with the cloud platform have an information advantage and achieve higher profits, but cooperation only between the supplier and the cloud platform may lead to supply-demand mismatches. The tripartite cooperation model, which incorporates contracts, effectively shares disturbance risks within the cooperative alliance and enhances the resilience of the supply-demand relationship more efficiently than fixed-ratio cost-sharing methods. The enhanced resilience is robust to random market demand. A method is provided for cloud platforms to evaluate and improve the resilience of supply-demand relationships, effectively maintaining the supply-demand balance in uncertain environments and offering a new approach to enhancing the resilience of industrial and supply chains.

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    Research on Investment Decision-Making of Charging Infrastructure under the Cross-Shareholding Strategy of Supply Chain
    Yifan Wu, Lu Chen, Jing Chen
    2026, 34 (1):  327-341.  doi: 10.16381/j.cnki.issn1003-207x.2024.0077
    Abstract ( 48 )   HTML ( 1 )   PDF (1758KB) ( 22 )   Save

    With the substantial growth of new energy vehicles, the lack of charging infrastructure has become the main bottleneck restricting the development of the new energy vehicle industry. However, the investment of a single enterprise has been difficult to meet the increasing cost and complexity requirements of charging infrastructure construction, and the use of cross-shareholding strategy to seek external resource integration has been widely adopted. For example, Denso Corporation of Japan and Toyota have maintained close cooperation based on cross-shareholding. Based on the shareholding strategy and subsidy policy, game theory and operations research optimization methods are used to develop models for different scenarios. Considering the new energy vehicle supply chain, the battery supplier provide batteries to the new energy vehicle manufacturer at the wholesale price, and the new energy vehicle manufacturer sells the new energy vehicles to consumers at the selling price, and four models are constructed: (a) neither cross-shareholding nor government subsidy; (b) no cross-shareholding but with government subsidy; (c) no government subsidy but with cross-shareholding; (d) both cross-shareholding and government subsidy, to analyze the impact of cross-shareholding and government subsidies. In order to draw valuable conclusions, the model is analyzed through numerical analysis. The results show that the cross-shareholding strategy can promote the investment in the construction of charging stations, but only when the construction cost is high or the construction cost is low and the shareholding ratio of the manufacturer is low, the shareholding strategy will increase the incentive effect of government subsidies. When the government subsidy budget is high, the cross-shareholding strategy will strengthen the subsidy effect. The wholesale price and the selling price both increase in the shareholding ratio of the manufacturer, while the impact of the shareholding ratio of the supplier on the wholesale price and the selling price is non-monotonic. The supplier can always benefit from the cross-shareholding strategy, and only if the construction cost is low and the manufacturer’s shareholding is below a certain threshold, the manufacturer can benefit from the cross-shareholding strategy. The research gap of the combination of cross-shareholding strategy and charging infrastructure investment is filled, and the optimal design of government subsidies under different objectives is discussed, in order to provide reference for policymakers.

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    Optimal Investment Mode of New Energy Vehicle Charging Infrastructure under Public-private Partnership
    Dongdong Li, Wenyao Lin, Weiwei Gao, Chenxuan Shang
    2026, 34 (1):  342-352.  doi: 10.16381/j.cnki.issn1003-207x.2023.1477
    Abstract ( 58 )   HTML ( 0 )   PDF (1227KB) ( 54 )   Save

    The lack of charging infrastructure has significantly hindered the widespread promotion of new energy vehicles in China. Establishing partnerships between the public sector (government) and the private sector (enterprises) is one important approach to address this issue. In this study, a tripartite game model involving the government, enterprises, and consumers was constructed to examine the effects and differences in investment in electric vehicle charging infrastructure under three types of government- enterprise cooperation models: government-funded, feasibility gap subsidy, and user-funded. Based on this, the optimal investment model for new energy vehicle charging infrastructure is discussed. The research findings indicate that (1) government and enterprise cooperation can enhance investment in new energy vehicle charging infrastructure and promote the large-scale adoption of new energy vehicles. (2) Compared to government-funded and user-funded models, the feasibility gap subsidy model not only has a positive impact on promoting electric vehicles but also enhances social welfare, making it the optimal investment model for new energy vehicle charging infrastructure. (3) Under the feasibility gap subsidy model, the optimal subsidy ratio for the construction and operation of charging infrastructure gradually decreases as the cost coefficient increases, while the optimal charging service fee price level gradually increases. The conclusions of this study are of great significance for the widespread promotion of new energy vehicles in China and the attainment of the transportation sector’s “dual-carbon” goals.

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    "Winner Picking" or "Winner Avoiding"? Selection Mechanism for Outward Foreign Direct Investment by China's Business Group Affiliates
    Pengqi Liu, Ping Lv
    2026, 34 (1):  353-368.  doi: 10.16381/j.cnki.issn1003-207x.2024.0150
    Abstract ( 54 )   HTML ( 1 )   PDF (905KB) ( 32 )   Save

    In recent years, the scale of outward foreign direct investment by China’s business group affiliates have continued to expand, but what kind of affiliates will be picked up within the business group to carry out foreign direct investment activities has been controversial. Chinese listed companies from 2008 to 2021 are used as a sample to explore the selection mechanism for outward foreign direct investment within business groups. The winner index is employed to gauge the performance of these affiliates. The research results show that business groups tend to follow a “winner picking” selection mechanism in the process of outward foreign direct investment. This means that affiliates with higher winner index scores have a greater probability, frequency, and scale of engaging in foreign direct investment. Taking into account the internal competition within business groups, the results reveal that the “winner picking” selection mechanism has a more pronounced promotional effect on affiliates that face more intense competition. In terms of principal-agent problem, the results suggest that the promotion effect of the “winner picking” selection mechanism is weaker for affiliates with higher corporate agency costs. Heterogeneity analysis demonstrates that the “winner picking” selection mechanism is more pronounced when affiliates are state-owned, employ cross-border mergers and acquisitions as their entry mode, and possess larger asset scales. From a theoretical perspective, it helps elucidate the micro-mechanisms governing the international strategic decision-making of business groups. It also expands relevant research on the internationalization behavior of business groups, drawing from principal-agent theory and competition theory. Practically, empirical evidence is provided to assist affiliates in implementing effective foreign direct investment strategies.

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