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25 December 2024, Volume 32 Issue 12 Previous Issue   
Leaders Buffering Mechanism Based on Space-Time Ratio and Case Study
Guoquan Chen, Yanling Lin, Jingyi Wang, Qingye Luo, Yue Fu
2024, 32 (12):  1-14.  doi: 10.16381/j.cnki.issn1003-207x.2023.1959
Abstract ( 118 )   HTML ( 10 )   PDF (2501KB) ( 101 )  

Currently, as the business environment faced by various organizations becomes increasingly unpredictable, members of the organization often have to bear various challenges encountered during the organization's development. When they feel overwhelmed or unable to cope, what should leaders do? Based on this, the concept of leader’s buffering behavior is put forward, which is defined as the process in which leaders can better achieve their goals by weakening the intensity of external challenges and/or improving the ability of organization members to respond to challenges in the external environment. Furthermore, we utilize the concept of space-time ratio proposed by Chen Guoquan in his “Time-Space Theory” based on general and fundamental domains to express the relationship and intensity of the interaction between organization and situation. Space-time ratio refers to the ratio of space intensity to time length. The question addressed in this paper is: in a high space-time ratio context, where space intensity is high and time length is short, how can leader buffer critical or excessive challenges in this context into moderate ones? To answer this question, a leader’s buffering mechanism based on space-time ratio is proposed. This mechanism refers to a series of strategies, measures, or methods adopted by leaders in a high space-time ratio context to reduce the intensity of external challenges and/or enhance the members’ ability to respond. These buffering measures aim to help organizational members better cope with sudden environmental changes, pressure, or conflicts, ensuring the smooth and orderly operation of the organization and providing time and space support for its members in responding to challenges. Furthermore, the leader’s buffering mechanism proposed in this paper mainly includes two paths: emotional buffering and task buffering. These two buffering paths based on the theories and methods of time and space in the field of leadership and management is systematically elaborated on. Based on the space-time ratio-based leader’s buffering mechanism proposed in this study, through the case study of ExxonMobil Huizhou ethylene project, one of the significant foreign investment projects during the China-US trade war, we specifically elaborate on the practical application of the proposed leader’s buffering mechanism. The findings are as follows: First, in Proposition 1a and Proposition 1b, we propose that leaders can establish emotional connection through learning and innovation from the perspective of time, so as to buffer employees’ emotions. The case study shows that leaders pay attention to employees’ emotional reaction when facing the project with great challenges, and establish the emotional connection between project and organization members through learning and innovation. Specifically, in the case, the leader will take employees to recall the more difficult project experiences they have overcome in the past and put forward new slogans to deal with challenges to boost morale, which will help the leader lead the members of the organization to reduce the emotional negative impact when they are at high space-time ratio context. Secondly, in Proposition 2a and Proposition 2b, we propose that leaders can buffer employees’ emotions from a space perspective by establishing emotional transmission channels between macro-level and micro-level, and paying attention to employees’ emotional needs in terms of soft power and hard power. The case study shows that leaders consciously take measures in space levels and dimensions to buffer their emotions, and multi-level and multi-dimensional emotional buffering measures make their organization members have positive emotions in the process of fighting. Thirdly, in Proposition 3a and Proposition 3b, we propose that leaders can buffer employees’ tasks from the perspective of time, by learning existing excellent experience and improving existing knowledge and work behavior through innovation. The case study found that leaders’ buffering measures for tasks started from the perspective of time, and by establishing a learning and innovation system, employees’ work efficiency was maximized in a limited time. Fourthly, in Proposition 4a and Proposition 4b, we propose that leaders can buffer employees’ tasks by establishing the task relationship between macro-level and micro-level, and by mobilizing resources of soft power and hard power. The case study found that the leaders’ buffering measures for tasks also started from a space perspective, which was embodied in the case that the leaders invested abundant resources to support the employees involved in project and established detailed standardized process arrangements among all levels. Finally, the theoretical and practical significance of this article is discussed, along with the prospects for future research.

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Information Transfer in Financial Market: Evidence based on Investor Attention Transfer in Chinese A-share Market
Chunlan Wang, Wen Shi, Fangfang Sun, Qiang Ye
2024, 32 (12):  15-24.  doi: 10.16381/j.cnki.issn1003-207x.2021.2593
Abstract ( 77 )   HTML ( 7 )   PDF (2233KB) ( 57 )  

The mechanism of how financial market information influences investor attention is crucial to understand market movement. Prior studies have shown that market information such as firm’s earnings announcement may contribute to investors’ attention transfer between firms. Relatively less about whether stock price signals can also influence investors’ attention, and how those signals would work jointly with other market information are known. In this paper, online search data are used as a measure of investor attention and the mechanism of attention transfer in China’s A-share market is explored. It is found that both earnings announcement and stock price signals of peer firms in the same industry will attract the attention of investors to the focal firm, and that stock price signals have a stronger overall explanatory role in investors’ attention transfer compared to earnings announcements. The rise or fall of a peer firm’s stock price exhibits asymmetric influence on investors’ attention. Further research shows that for focal firms with high stock price synchronicities, their investors have lower level of attention to the earnings announcements of peer firms, but higher level of attention to short-term extreme high stock returns of peer firms. Additionally, short-term extreme high price signals of peer firms significantly increase the investor attention to those industry leaders and those firms with better accounting information quality, while the earnings announcements of peer firms have a greater impact on the attention of focal firms with lower accounting information quality. From a more macro perspective, it is also found that economic policy uncertainty weakens investors’ attention transfer.

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Relationship between Stock forum's Information Diffusion and Stock Price Comovement from the Interaction Perspective
Zhanghangjian Chen, Fei Ren
2024, 32 (12):  25-36.  doi: 10.16381/j.cnki.issn1003-207x.2022.1549
Abstract ( 59 )   HTML ( 1 )   PDF (2913KB) ( 56 )  

A profound comprehension of the microcosmic mechanisms underpinning enigmatic asset pricing phenomena, such as the pronounced co-movement of stock returns, holds paramount significance for the effective management of risk in the stock market and the optimization of investment portfolios. In the context of the Internet, social media has become the most important opinion field for individual investors, which has improved the information environment for investors, and also led to an increasingly complex risk contagion pattern in the stock market. On the one hand, individual investors’ anticipated returns on stocks can be significantly influenced by the diffusion of information through social media platforms, thereby potentially contributing to the observed excess co-movement in stock returns. On the other hand, stock price fluctuations can attract online attention, especially in the aftermath of a stock market crash, often accompanied by heightened stock price co-movements.From the perspective of interaction effect, this study explores for the first time the dynamic lead-lag and interaction relationships between social media information diffusion and stock price comovement through a comprehensive methodology encompassing panel vector autoregression (PVAR) modeling, and the thermal optimal path (TOP) approach. Based on the herding effect and excessive attention theories, the intermediate processes of the relationships are investigated through the stepwise regression method. Finally, robustness checks are implemented by modifying the parameters of the TOP model, examining causality between information diffusion and stock price comovement, and changing the variable metrics.Results show that the change in information diffusion among stock bars leads that the corresponding stock price correlation before 2020, and this relationship reverses when the market has a high level of fluctuation after 2020. Secondly, there is a significant two-way effect between information diffusion and stock price comovement, and the effects have a non-linear characteristic of “negative→positive convergence”. Third, the trading behavior of individual investors is an important channel through which information diffusion affects stock price comovement. Fourth, the increase in stock price correlation can attract the attention of individual investors, leading to frequent postings and replies in the corresponding stock bars, and increasing the degree of information diffusion.Consequently, the findings hold practical significance for market participants and regulators. Investors should be cautious about the information on social media platforms and stock price fluctuations, and improve their ability to recognize effective information and respond to risks, so as to avoid making wrong trading decisions due to the diffusion of noisy information and temporary fluctuations in stock prices. For the regulators, they should strengthen the monitoring of abnormal proliferation of stock information on social media platforms and excessive linkage of stock prices, so as to improve the timeliness of risk disposal and prevent systemic financial risks.The study represents the inaugural endeavor to scrutinize the dynamic interplay between the diffusion of information through social media and the occurrence of stock price comovement. In doing so, it supplements existing research focused on elucidating the impact of information diffusion engendered by the word-of-mouth effect on stock price dynamics. The research also aligns with prior work exploring the role of investor behaviors in shaping the dynamics of stock return co-movement.

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Study on Hedging of Dry Bulk Ship Market
Cong Sui, Zhaonuo Ren, Wenlei Shi, Xin Zhao, Wenyang Wang
2024, 32 (12):  37-48.  doi: 10.16381/j.cnki.issn1003-207x.2022.1059
Abstract ( 46 )   HTML ( 0 )   PDF (2247KB) ( 19 )  

Due to the significant volatility within the shipping market, the risk management of vessels’ value has long been a focal point for both theoretical analysis and practical application. Ship risk management holds vital importance for participants in the shipping industry. Hedging vessels’ value within the shipping market is studied through the development of Forward Freight Agreement (FFA) portfolios. Specifically, it utilizes the Baltic Dry Index (BDI), time-charters (TC), and freight rates for various routes to construct 38 different FFA portfolios through different vessel ages. Using these portfolios, hedging strategies for 12 kinds of ship price spanning three types of bulk carriers and four vessel ages is investigated. The main contributions of our research are as follows Firstly, to leverage the discounted cash flow valuation principle, FFAs are employed as surrogate variables for future freight income, to facilitate the construction of portfolios that reflect the vessels’ value. Portfolio construction employs both direct summation and discounted summation methods, with the latter incorporating the discounted value of freight income. Secondly, both static and dynamic hedging techniques are employed, with dynamic hedging utilizing DCC-GARCH and BEKK-GARCH models. Thirdly, a comparative analysis is conducted between portfolios constructed using the two methods, evaluating their effectiveness in hedging vessels’ value across different vessel types and ages under static and dynamic hedging methods. The main findings of this study are as follows Firstly, in static hedging, longer-term FFA portfolios exhibit superior hedging effectiveness. Secondly, within static hedging, FFA portfolios of TC contracts for Panamax and Supramax vessels demonstrate the most efficient hedging, while C3 and C7 route-based FFA portfolios for Capesize outperform those based on BDI and TC rates. Thirdly, overall, dynamic hedging proves more effective than static hedging, with the discounted summation method outperforming direct summation in dynamic hedging strategies. An effective risk management strategy for market participants are presented such as shipowners, ship leasing companies, and ship insurance companies.

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The Way of Bridging Salary Disparity and Cooperative Tendency: Through Employee Fairness Perception and Team Competition Atmosphere
Baohuan Zhou, Xiaoli Hu, Pingfan Wang, Guangwei Deng, liang Liang
2024, 32 (12):  49-59.  doi: 10.16381/j.cnki.issn1003-207x.202.1845
Abstract ( 56 )   HTML ( 1 )   PDF (1825KB) ( 35 )  

Achieving common prosperity is a crucial goal in China's development. However, income inequality within organizations, particularly salary disparities within teams, can negatively impact employee cooperation and overall organizational performance. Driven by the pursuit of common prosperity and concerns regarding income inequality, the impact of team salary disparities on employee cooperative behavior tendency is studied. Grounded in behavioral theory and equity theory, the differential effects of explainable salary disparity (DEP) are investigated, arising from factors like skills and effort, and unexplainable salary disparity (DUP), stemming from potential biases or unfairness, on cooperation within teams. A multi-level linear model analysis is employed with data collected from 29 teams across various companies in eastern China. Team-level DEP and DUP are calculated using the Gini coefficient, while individual-level data on employee fairness perception and cooperative behavior are gathered through surveys. The findings reveal that DEP positively influences employee cooperative behavior, while DUP has a negative effect. This relationship is mediated by employee fairness perception, suggesting that employees are more inclined to cooperate when they perceive salary distribution as fair. Additionally, team competitive atmosphere moderates the relationship between salary disparities and fairness perception. In a highly competitive environment, the positive effect of DEP and the negative effect of DUP on fairness perception and subsequent cooperation are amplified. These results highlight the critical role of fair and transparent compensation systems in fostering cooperation within teams. Managers should strive to minimize DUP and ensure that any DEP is based on objective criteria. It contributes valuable insights for organizations seeking to optimize team performance by promoting fairness and cooperation among team members in this study.

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Does Overseas Investment Improve Corporate Environmental Awareness? Empirical Test Based on Heterogeneity
Quanjing Wang, Wenzhi Li, Haijie Wang
2024, 32 (12):  60-70.  doi: 10.16381/j.cnki.issn1003-207x.2021.1675
Abstract ( 70 )   HTML ( 1 )   PDF (1897KB) ( 51 )  

Although a large number of academic literatures discusses the issue of overseas investment by Chinese companies from different perspectives, so far, there is no literature that analyzes the impact of overseas investment on corporate behavior from the perspective of corporate environmental awareness. The increasing number of Chinese overseas investment enterprises provides an opportunity for us to study this issue. The analysis and discussion of the impact of overseas investment on corporate environmental protection expenditure from the perspective of institutional distance can not only further expand and enrich the relevant research on overseas investment and corporate behavior in theory, but also provide a new perspective and theoretical basis for relevant government departments to formulate relevant policies to enhance the ability of enterprises to develop green and sustainable development.The relevant data of China’s listed companies from 2010 to 2019 and the two-way panel fixed effects model and the PSM-DID measurement method are used to test the impact of overseas investment on corporate environmental awareness and its dynamics, and further whether the heterogeneity of the company and the heterogeneity of the host country change this effect is examined. The research results show that the environmental awareness of overseas investment companies is significantly higher than that of other companies. The impact of overseas investment on corporate environmental awareness is dynamic, and it only help improve corporate environmental awareness after three years of investment. In the eastern region, private enterprises, and heavy-polluting industries, overseas investment has a stronger effect on corporate environmental awareness. When the institutional distance between the host country and China is higher, overseas investment is more conducive to improving corporate environmental awareness. It is conducive to causally identifying the logical relationship between overseas investment, institutional distance and corporate environmental awareness in this article.Accordingly, the following policy recommendations are put forward: First, in the context of complex international situation, the government should guide more enterprises to go global, regulate enterprises' overseas investment behavior, and adopt the reverse spillover effect and learning effect of enterprises in host countries and the institutional constraints of host countries on enterprises' behavior, and improve their own environmental protection efforts. Second, the government should formulate corresponding preferential policies to encourage enterprises to make more strategic long-term foreign investment rather than short-term profitable foreign investment. Third, government should strive to resolve the concerns of private enterprises in making foreign investment, improve the enthusiasm of Chinese private enterprises to go global, and use the interest competition and institutional supervision in the international market to improve the enthusiasm of enterprises in environmental protection. In addition, considering the high proportion of private enterprises in the market, in order to fully mobilize the enthusiasm of private enterprises to protect the environment, while fully releasing the economic vitality of private enterprises, the leadership of the Party should be integrated into all aspects of the governance of private enterprises, and the behavior of private enterprises should be regulated through the leadership of the Party and external systems, so as to promote private enterprises to operate in a more environmentally friendly way. Fourth, while guiding enterprises in the eastern region to invest abroad, the government should focus on promoting the opening up of the central and western regions and the improvement of the legal market, improve the ability of enterprises in the central and western regions to take advantage of the dual system advantages of the host country and China. Fifth, the government should properly guide heavy polluting enterprises to make foreign investment, protect the environmental interests of biochemical enterprises through international competition, and enhance the intensity of environmental protection expenditure of enterprises. Sixth, Chinese enterprises can invest in those countries with a higher distance from China's system, take advantage of the institutional constraints of the two countries, improve the international adaptability of enterprises, and improve the intensity of enterprises' environmental protection expenditure.

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How Public Monitoring Based on the New Media Platform Can Promote Green Transformation of Enterprises: Based on the Synergistic Perspective of Development and Emission Reduction
Pingping Ma, Ming Zhang, Yan Song
2024, 32 (12):  71-87.  doi: 10.16381/j.cnki.issn1003-207x.2023.1796
Abstract ( 66 )   HTML ( 1 )   PDF (3488KB) ( 55 )  

Under the new governance system of universal participation, public monitoring relying on the new media platform (Pnm) has become a powerful means of forcing enterprises to develop in a green way, but its internal mechanism has not yet been clarified. Therefore, the data of Chinese A-share listed companies from 2011 to 2020 are selected, and the impact of pnm on enterprise green transformation (Egt) is evaluated with the help of mediation effect model and threshold regression model. The results show that Pnm can significantly promote Egt based on the dual review of corporate development and emission reduction, which is realised by both enhancing internal corporate concerns (Eic) and strengthening external government regulation (Ger), with Ger playing a greater mediating role in corporate development and emission reduction. However, under the influence of digital development (Dil), Pnm has a more complex impact trajectory on Egt, that means it has a single-threshold characteristic of increasing marginal effect on corporate development, and a double-threshold inverted U-shaped characteristic of increasing and then decreasing effect on corporate emission reduction. It is further concluded that Pnm and Ger can form an more effective synergy on Egt with more negative external reports, smaller scale, belonging to the heavy pollution industry, and higher efficiency of green technology innovation. In addition, under the influence of Pnm, enterprise development and emission reduction are mutually reinforcing. Accordingly, it is proposed that the positive moderating effect of Dil on Pnm in promoting Egt should be appropriately strengthened, and the suitability of Pnm with the Eic and the external regulatory tools of the government should be enhanced in order to maximise its potential.

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The Importance Factor of Being Central Hub in Global Value Chains Network: Quality or Price
Qizheng Gao, Jianqing Zhang, Shuting Li, Cuizehao Zhao
2024, 32 (12):  88-96.  doi: 10.16381/j.cnki.issn1003-207x.2021.2036
Abstract ( 47 )   HTML ( 2 )   PDF (3499KB) ( 35 )  

The Katz-Bonacich centrality is utilized in this paper to calculate centrality of 8 manufacturing industries across 189 economies during the period from 1990 to 2015, representing the hub position in the global value chains network. The product price is decomposed into quality and quality-adjusted price, and their impacts on the centrality are analyzed both theoretically and empirically. The findings reveal that both quality upgrading and decreases in quality-adjusted price can promote the centrality position within the global value chains network, with quality emerging as the key factor. The effect of quality and quality-adjusted price on the promotion of centrality position vary across industries, products, regions with different development levels, and time periods. Overall, the quality upgrading proves to be more effective than reducing quality-adjusted price. Mechanism analysis indicates that improving quality, compared to lowering quality-adjusted prices, results in greater export levels. The research on positioning in global value chains is extended in this paper, and the quality upgrading policies to enhance a nation’s position within the global value chains network should be prioritized.

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Research on Quality Disclosure Strategies of Reward-based Crowdfunding
Qiudan Zhang, Lei Guan, Xingjin Kan
2024, 32 (12):  97-107.  doi: 10.16381/j.cnki.issn1003-207x.2023.1920
Abstract ( 45 )   HTML ( 0 )   PDF (2697KB) ( 21 )  

As a new online financing method, crowdfunding provides a new scheme for SMEs to raise funds. One of the branches of crowdfunding, namely reward-based crowdfunding, can not only serve as a channel for entrepreneurs to raise funds, but also predict the future demand of products. According to the practices and academic research on reward-based crowdfunding, how to attract more investors, improve the success rate of crowdfunding projects and get more profits are the issues that entrepreneurs need to focus on. Among these issues, the product quality is the most important factor that will determine the result of crowdfunding projects. In practice, entrepreneurs have different ways to illustrate the product quality, such as presenting a video on the website or show more figures about the product. However, now there is no research on the quality disclosure strategies for entrepreneurs in reward-based crowdfunding while considering the pricing decisions under different crowdfunding mechanisms. To answer the question, the quality disclosure and pricing decisions of the entrepreneur under the reward-based crowdfunding are investigated based on the All-Or-Nothing (AON) mechanism and Keep-It-All (KIA) mechanism, respectively. By establishing an analytical model with one entrepreneur and two potential investors, the optimal decisions of the entrepreneur are presented. Further, numerical experiments are conducted to investigate the influence of important parameters, while the results under the two mechanisms are compared. The conclusions of this paper are as follows: When the disclosure cost is low, the entrepreneur has two options to disclose quality information or not to disclose the quality information; while when the disclosure cost is high, the entrepreneur will certainly not disclose the quality information. In addition, if the unit cost of the product is high, the entrepreneur will choose to disclose the quality information. When the cost of the product and the cost of disclosure are relatively large, the entrepreneur will not create crowdfunding projects. In terms of entrepreneur’s profits, the increase of real product quality and valuation discount coefficient will not make entrepreneur’s profits worse. When the valuation discount coefficient or the real quality of the product is low, the entrepreneur can obtain higher profits under the AON mechanism. On the contrary, for the entrepreneur of crowdfunding campaigns with high real product quality and high valuation discount coefficient, he should choose the KIA mechanism. The conclusions of this paper will provide advice for entrepreneurs to choose the better crowdfunding mechanism and help them decide whether to disclose the product quality, which can improve the success rate of crowdfunding project and increase the expected profits from crowdfunding.

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Dual Hesitant Unbalanced Linguistic Group Decision Approaches with Application to Evaluating Suppliers' Resilience Capability
Xiaowen Qi, Changyong Liang, Junling Zhang
2024, 32 (12):  108-117.  doi: 10.16381/j.cnki.issn1003-207x.2022.1196
Abstract ( 48 )   HTML ( 1 )   PDF (2786KB) ( 59 )  

To answer the advocation of “Going global” strategy by China’s central government, Chinese manufacturing companies have been increasingly and deeply participating global competition in various international markets. However, continuously emerging environmental dynamic changes and risks, such as those from unfair competition, regional politics, pandemics and etc., have been requiring to build robust supply networks for adaptation. The practical requirements thus also have been highlighting the crucial role of comprehensively evaluating resilience capability in supplier selection, which accentuates to simultaneously and comprehensively consider economic, environmental and social indicators as well as resilience ones.According to extant literatures, the focal problems of comprehensive evaluation of suppliers’ resilience capability exhibit multi-faceted complex characteristics, such as holding semi-structured or low-structured problem definitions, involving participation of multiple stakeholders in decision-making processes, incurring inaccurate assessments and decision hesitancy among decision makers. To this end, with acknowledgement of the multi-faceted complex characteristics above-mentioned, it focuses on investigating effective group decision making approaches for comprehensive evaluation of suppliers’ resilience capability by contributing to introducing in this paper: (1) an effective hybrid expression tool for eliciting decision-makers’ assessments more objectively and comprehensively; (2) fuzzy information measures for avoiding potential information distortion in comparison to widely-accepted traditional ones; (3) rational methods for objectively obtaining unknown weighting vectors; (4) processual modelling methodologies for group decision making to accommodate typical situations of suppliers’ resilience capability evaluation.To solve these problems listed above, firstly, a novel expression tool called as dual hesitant unbalanced linguistic term set (DHULTS) has been defined. Secondly, to avoid potential information distortion that is usually brought about by traditional hesitant element extension methods, a least common multiple (LCM) based extension mechanism has been introduced to develop correlation coefficient-oriented measure for DHULTS, by use of which a weighting method for obtaining unknown experts’ weights has further been established. Thirdly, grounded on the above methods, corresponding group decision making approaches have been constructed with regard to two specific situations in practices: (i) target supplier(s) for benchmarking could be derived in advance; (ii) decision making units do have different opinions on prioritization among evaluative attributes. Finally, case application and numerical studies have then been conducted to verify effectiveness and superiority of our approaches.

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M-Health Platform Recommended Strategy Analysis Considering User Search Behavior
Peilun Li, Qiuju Yin, Zhijun Yan
2024, 32 (12):  118-129.  doi: 10.16381/j.cnki.issn1003-207x.2023.1823
Abstract ( 60 )   HTML ( 4 )   PDF (2569KB) ( 66 )  

Recommender systems are common tools in e-commerce platforms. In mobile health platforms, course recommender systems assist users in finding relevant exercise courses. Existing literature suggests that recommender systems can effectively cater to user demand, leading to a significant increase in sales for recommended products. However, it remains unclear how recommender systems impact price competition among course providers when users engage in self-searching behavior. Recommendation can be perceived as a form of platform intervention, inspiring users' purchase decision to the recommended products. Additionally, users have autonomous search behaviors. When the recommended courses fail to satisfy users’ needs, they will actively seek alternatives within the same platform or other platforms. Moreover, the influence of different recommended strategies (profit-oriented or user-oriented) and recommender accuracy on platform profits needs further investigation. The design of recommender systems may not solely aim to benefit users, but also to motivate users to buy products that can help platforms to earn more commission fee. Specifically, to achieve higher profits, the recommender systems may misguide users to purchase courses that generate greater revenue for platforms.The impact of different recommendation strategies (user-oriented or profit-oriented) on the profits of a mobile health platform is examined and primarily two key questions are explored: First, how do user-oriented or profit-oriented recommendation strategies affect price competition among exercise course providers and platform profits when users have autonomous search behavior? Second, how should the platform make optimal decisions between user-oriented and profit-oriented recommendation strategies?To address these research questions, an analytical framework is developed in which two course providers offer substitute fitness courses on a mHealth platform and simultaneously set their prices. The platform charges the providers a percentage commission and recommends only one course to users. Users are not knowledgeable about the fitness courses and need to search individually. In the searching process, optimal stopping rules are adopted to characterize users’ decision-making process before purchasing. The model first considers the baseline scenario in the absence of a recommender system. It analyzes users’ purchase decisions, derives the equilibrium prices of courses, and assesses provider profits. Next, the model assumes that the recommender system exogenously alters users’ searching order. It distinguishes profit-oriented and user-oriented recommendation strategies based on the weights assigned to platform profits and user utility. Furthermore, the model explores the equilibrium prices of courses, provider and platform profits accordingly. Finally, how platforms should select the optimal recommendation strategy in different market environments is discussed.The practical significance is held for mobile health platforms with deployed recommender systems. When the system solely focuses on platform revenue while overlooking providers' strategic responses, or excessively favors either provider profits or user utility, it may potentially harm the platform's profit. Moreover, the factors are identified that determine whether the platform can benefit from the recommender system. These include the recommendation strategy, recommender accuracy, the proportion of random users, and differences in users' course preferences. It has also described how these factors influence the platform's profit.The results show that (1) When the number of users randomly purchasing exercise courses is relatively high, course providers tend to reduce course price to attract users. When users have diverse preferences for courses and their demand for courses and value assessments also vary significantly, providers have to satisfy different demands through low-price strategies. (2) The high accuracy of the recommender system is more likely to provide users with suitable exercise courses based on their preferences, which helps alleviate price competition among providers. (3) Recommender systems can alter market size but do not necessarily guarantee platform benefits. Platforms can benefit from moderately profit-oriented or user-oriented recommendation strategies. The accuracy of the recommender system contributes to increased platform revenue. (4) When choosing optimal recommendation strategy, platforms should consider commission rates, random user ratio, and the heterogeneity of user health levels within the market environment. Higher commission rates, higher random user ratios, or greater health heterogeneity exert pressure on platforms to adopt a moderately user-oriented recommendation strategy.

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Research of Hot Compression Molding Batch Scheduling for Aerospace Composite Manufacturing with Material External Time Window Constraints
Jingqi Ding, Naiming Xie, Shaoxiang Zheng
2024, 32 (12):  130-139.  doi: 10.16381/j.cnki.issn1003-207x.2023.1831
Abstract ( 45 )   HTML ( 0 )   PDF (2571KB) ( 34 )  

The scheduling problem is investigated in the autoclave operations of aerospace composite material production. The problem stems from the wide application of composites in military and civilian aircraft, which has led to a prominent contradiction between supply and demand. As a bottleneck process in composites production delays occur frequently in autoclave operations. In this study, the production planning and scheduling of autoclave operations is taken as a research perspective, aiming to provide a timely and efficient scheduling program. The current production and processing characteristics of the autoclave operations are first analyzed, describing in detail the limitations on production and processing imposed by the out-time of the prepreg and the two-dimensional spatial characteristics of the workpiece preforms. It is assumed that the out-time of all job prepregs is known. Based on the above analysis and assumptions, the problem is for mulated under consideration as a two-dimensional single-machine batch scheduling with a release time window, with the objective of minimizing the total jobs delay time of the scheduling scheme. A mixed integer programming (MILP) model is developed and effective inequalities are proposed based on the jobs release time window. For small-scale instances of the considered problem, the MILP model can be solved by commercial solvers such as Gurobi to obtain an exact solution. For solving large-scale instances, a genetic algorithm embedded with a maximum delay jobs neighborhood search strategy is developed based on the concept of maximum time-compatible jobs set. In numerical experiments, the results show that the proposed MILP model outperforms the classical integer programming model in terms of solution efficiency, and the added effective inequalities can improve the solution efficiency of the model by 15% on average. The designed genetic algorithm can solve the large-scale arithmetic and the solving quality is significantly better than the classical genetic algorithm. The results of the case study based on the M plant show that the weekly plan scheduling scheme generated by the MILP model can improve the delay situation by up to 74% over the original scheduling scheme. The total delay time of the algorithm's resultant jobs exhibits an incremental trend with the increase in the percentage of short-release time-window jobs in the jobs.

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Research on Autonomous Driving Control Mechanism and Vehicle Scheduling in Smart City Based on Global Perspective
Kunpeng Li, Xuefang Han
2024, 32 (12):  140-152.  doi: 10.16381/j.cnki.issn1003-207x.2021.2452
Abstract ( 54 )   HTML ( 1 )   PDF (3517KB) ( 66 )  

As policy guidance and automatic driving technologies mature and popularize, unmanned driving has become an important development trend of smart city traffic, which will lead to a dramatic change in the control logic of urban traffic. Currently, both manual driving and automated driving are essentially on a local decision traffic mode based on the perspective of the individual vehicle, e.g., a single vehicle planning its own route and making decisions about collision avoidance. In future smart cities, global scheduling of urban traffic resources and vehicles based on a global perspective will maximize the efficiency of the smart city, and will also become a new mode of traffic operation in a driverless environment. In this mode, the urban traffic control platform uniformly plans the driving route, decides the time of arrival at each intersection and the collision avoidance scheme. In view of this, firstly, the smart city traffic development blueprint is drawn from the aspects of global scheduling mechanism, road network environment and collision avoidance rules. The mode is then defined as a multi-level unmanned vehicle-simultaneous scheduling broken line routing problem considering the number of turns in irregular road network. To solve the problem, a mathematical model with the goal of “the shortest total running time + the least number of turns” is established. To quickly obtain a high-quality scheduling scheme, three optimization strategies are proposed to improve A* algorithm. Finally, 80 scale instances are set up to simulate the road network environment. 32 small-scale instances are used to assess the accuracy of the model and the efficiency of the algorithm, and 48 large-scale instances are used to compare the performance of the traditional A-star algorithm and the algorithm proposed in this paper. Results show that the algorithm proposed in this paper can reduce the number of turns to 1/2 of the traditional A* algorithm, and shorten the overall time of the vehicles to be scheduled by 0.49 h. Especially in large-scale problems, the reduction of the number of turns and the total time-saving effect are more significant. Compared with the traditional A* algorithm, the modified algorithm can reduce the average solution time by 0.061s. The research results can provide decision support for urban traffic management departments to plan and control future traffic and design global scheduling schemes.

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A Bilevel Heuristic for the Contactless Delivery Problem Coordinated with Trucks and Drones
Li Jiang, Changyong Liang, Xiaoning Zang
2024, 32 (12):  153-163.  doi: 10.16381/j.cnki.issn1003-207x.2022.1519
Abstract ( 52 )   HTML ( 3 )   PDF (2805KB) ( 48 )  

In this paper, a contactless delivery problem coordinated with trucks and drones (CDP-TD) is introduced, in which trucks depart from the depot, facilities in the delivery network are visited, and then drones start from the facilities to provide customers with contactless delivery services. The goal of the problem is to minimize the two-level delivery cost. The problem has application in the urban contactless delivery during the pandemic, such as COVID-19. A mixed integer programming model is proposed for the problem, and the problem is reformulated to a bilevel programming model by Benders Decomposition. Inspired by the ideas of the bilevel programming model, a bilevel heuristic is developed to solve the problem. Finally, two classes of problems are generated, including 144 instances, to test the formulation and BH algorithm. The results show that as the number of nodes increases, the performance of the CPLEX deteriorates significantly, whereas the BH has good performance for solving the CDP-TD.

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Study on Two-stage Dynamic Vehicle Scheduling Optimization Considering the Proactive Category
Guiqin Xue, Xianlong Ge
2024, 32 (12):  164-172.  doi: 10.16381/j.cnki.issn1003-207x.2021.2037
Abstract ( 54 )   HTML ( 3 )   PDF (2251KB) ( 37 )  

Terminal logistics delivery efficiency and order response speed are core objectives for logistics companies to maintain market competitiveness and customer loyalty. Faced with differentiated and dynamically emerging category demands, traditional centralized warehousing models exhibit shortcomings such as delayed customer responses and low delivery efficiency. The proactive warehouses are utilized as connection points in a two-level logistics network and a two-stage dynamic vehicle scheduling problem is investigated based on proactive category (TSDVSP-PC). The problem is described using an undirected graph, where the node set consists of depots, proactive warehouses, and customers. The arc set includes arcs between depots and static customer locations, arcs between depots and dynamic nodes without proactive categories, and arcs between proactive warehouses and dynamic customer nodes with proactive categories. During the distribution process, customers with regular demands are served directly by the depots, while customers with proactive demands are served by nearby proactive warehouses. The problem is modeled as a multi-category vehicle scheduling problem with the objective of minimizing transportation and stocking costs. A proactive warehouse selection method and an improved genetic algorithm are designed to obtain high-quality solutions within a reasonable computation time. Specifically, the method for selecting the categories and locations in proactive warehouses is based on commodity attributes and the spatiotemporal differentiation of customers. Additionally, to address the limitations of insufficient local search capabilities in traditional genetic algorithms, various neighborhood operations and 2-opt operator are incorporated, and the improved genetic algorithm is employed to solve the proposed problem. To validate the proposed model and algorithm in practical scenarios, cost and efficiency analyses are conducted for key category stocking, full-category stocking, and centralized stocking schemes. The computational results indicate that the full-category stocking scheme yields the highest stocking benefits. However, for categories with a smaller market share, the benefits of proactive stocking do not offset the associated stocking costs. Utilizing different vehicle types in the two-level network increases the system's adaptability to traffic conditions but also raises vehicle scheduling costs during the dynamic replenishment stage. Companies employing proactive stocking strategies should carefully select proactive categories and replenishment vehicle types in alignment with their business development to achieve a coordinated optimization of demand response and cost control. Finally, the study concludes that a distributed-based model considering product attributes and customer spatiotemporal characteristics can achieve a faster response to dynamic demands with lower delivery costs and higher efficiency. In practical operations, having more proactive categories is not always advantageous; the optimal number of proactive categories is determined by balancing customer response and cost control. Appropriate selection of proactive categories can effectively reduce operational costs, whereas inappropriate proactive stocking may lead to counterproductive results. Future research will consider incorporating real-time traffic information and disruption management to explore multi-category proactive management and route optimization under more complex scenarios.

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Analysis of Risk Spillover Characteristics and Mechanism among Industries: Evidence from Multilayer Network
Hong Shen, Chenyao Zhang, Xiaoxing Liu
2024, 32 (12):  173-182.  doi: 10.16381/j.cnki.issn1003-207x.2022.1546
Abstract ( 71 )   HTML ( 3 )   PDF (2446KB) ( 156 )  

The report of the 20th National Congress of the Communist Party of China pointed out that “we should strengthen and improve modern financial supervision, strengthen the financial stability guarantee system, and bring all kinds of financial activities under supervision according to law”. In the time dimension, the accelerator effect between different industries forms a risk feedback mechanism; in the spatial dimension, different industries have amplified the systematic risk through the formation of complex financial associations through the role of the market. As a result, studying the risk contagion mechanism among industries is of great significance for preventing and resolving major systemic risks and maintaining financial stability.The CSI All Share Index is taken as object, DCC-t-Copula-CoVaR model is used to measure systematic risk spillovers and absorption levels as the explained variables, a multilayer network is constructed, key structural indicators are taken as the explanatory variables, and MIDAS method is used to study the risk linkage mechanism.Consequently, suggestions are put forward to prevent systemic risks among industries:The regulatory level should consider the time-varying characteristics of the risk network and describe the dynamic evolution mechanism of systematic risk. A macro prudential risk monitoring mechanism of “too relevant to fail” based on the perspective of multi-layer networks should also be designed. To prevent and defuse systemic risks, the Party's leadership over financial should be strengthened, pushing our economy towards high-quality development.A reference model and basis for establishing a cross industry risk linkage monitoring system is provided. Through effective monitoring of inter industry risk linkage, the ability to withstand extreme risk shocks is improved, so as to increase the resilience of the macro-economy, make progress while maintaining stability, and achieve high-quality development of the industry.It is found that from the perspective of risk transmission, multilayer network theory can better describe the complex correlation among industries. It is difficult for a single industry to cause a chain reaction,but risk resonance among industries will lead to major systemic risks. Industry risk network polycentric development and diversification of contagion paths evolve under the impact of major risk events. From the aspect of influencing factors: The key role of important industries in risk contagion is similar to the "systemically important role",and the adjacent industries of important industries also deserve attention. The industries which have high relevance and close to the center in the network reflect the characteristics of both stable and fragile.

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Research on the Cooperation Model of Elevator Retrofitting Projects in Old Neighborhoods Based on PPP Model
Jingxin Gao, Xin Wang, Jinbo Song
2024, 32 (12):  183-193.  doi: 10.16381/j.cnki.issn1003-207x.2021.2509
Abstract ( 54 )   HTML ( 0 )   PDF (2711KB) ( 57 )  

The problem of elevator retrofitting has restricted the smooth implementation of old neighborhood renovation in China and intensified the contradiction between the aging population and the growing demands of the people for a better life. Therefore, designing a new model to solve the problem of elevator retrofitting in old neighborhoods has become an important and urgent practical problem. Firstly, the traditional model of elevator retrofitting in old neighborhoods is analyzed, and on this basis, the project cooperation model of elevator retrofitting is improved and designed in old neighborhoods and a profitability model of the project is constructed from the perspective of social capitalists. Secondly, the two profitability functions of such projects and their variation laws have been obtained through differential analysis. Finally, Monte Carlo simulation is used to simulate the profitability of the project under this model, and the applicable intervals of key parameters are obtained. The results show that: (1) the amount paid by the residents for using elevators is a key parameter to ensure the profitability of the project, which is a prerequisite for the effective participation of the social capital party in the project. (2) Payments from residents for the use of elevators and government subsidies have a great influence on the functional form of corporate income. This shows that, on the one hand, a reasonable amount of residents' payment should be formulated to provide the precondition and motivation for the social capital party to participate in the project; On the other hand, the government should adjust the amount of residents' payment and government subsidies through discussion, so as to influence the functional form of enterprise income to ensure that the old residential area elevator project will ultimately achieve the results of enterprise profitability, residents' willingness and government satisfaction.A valuable reference for solving the problem of installing elevators in old residential areas is provided. All stakeholders can re explore and reach favorable cooperation under the new model, which to some extent helps to eliminate the hidden dangers that the inability to install elevators brings to the reconstruction of old residential areas in China.

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Customizing or Default? Study on Cross-Market Service Providing Strategy of Platforms in Multimarket Competition
Baojiao Wang, Zhiwen Li, Yi Lu, Qiang Xiong
2024, 32 (12):  194-205.  doi: 10.16381/j.cnki.issn1003-207x.2023.2096
Abstract ( 48 )   HTML ( 0 )   PDF (2625KB) ( 57 )  

Platform cross-market operation has become more and more popular in recent years, and how platforms provide cross-market service in multimarket competition has aroused widespread social concern. Based on the Hotelling model, a multimarket competition system between two platforms serving sellers and consumers is built with different cross-market service preferences in two different markets, and the decision-making issue of platforms is examined from two available options: implementing the customizing strategy or the default strategy when providing cross-market services to consumers. The following findings are derived by the analysis. (1) Platforms price competition does not always tend to be fiercer when the same strategy is chosen by platforms than when the different strategies are chosen. Under some circumstance, it tends to be more relaxed. (2) Three situations, which are both platforms implementing the default strategy, one platform implementing the customizing strategy while the other implementing the default strategy, and both platforms implementing the customizing strategy, may be the final Nash equilibrium for platforms providing cross-market services, depending on the cross-side network externalities of platforms and the proportion of consumers who like and dislike the cross-market service. (3) Two situations, which are only one or both platforms implementing the default strategy, have the chance to bring the highest social welfare, while the situation in which both platforms implementing customizing strategy results in the lowest social welfare.

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Research on the Signaling Effects of Free Experience in Platform Digital Contents
Yuan Liu, Ying Yu, Hongmin Chen
2024, 32 (12):  206-214.  doi: 10.16381/j.cnki.issn1003-207x.2023.1863
Abstract ( 44 )   HTML ( 0 )   PDF (1988KB) ( 42 )  

In digital platforms, it is often challenging to provide users with comprehensive information about the quality of digital content products. To address this issue, many firms have adopted strategies that involve offering partial product content for free experience (FE). On video streaming platforms, users can watch certain content for free; music platforms provide extensive libraries of trial tracks; game platforms offer free trial versions of some games, and e-book platforms allow users to access free sample chapters. The FE strategy allows users to experience the product firsthand, which is beneficial in reducing information asymmetry regarding product quality.Traditional signaling game models typically involve only the signaling sender and receiver. In this paper, the platform, acting as an intermediary, is incorporated into the signaling game as an additional participant. A microeconomic theoretical model is constructed based on the signaling theory to analyze the signaling effects of firms providing FE to users on platforms. Some typical features of FE are incorporated into a signaling game model, with a particular focus on scenarios where the quality of FE fails to convey information. By comparing equilibrium solutions in cases where the platform does not participate in the game and where the platform does participate in the game, the influence of the platform is investigated as an intermediary in the signaling game.The managerial insights of this paper include two main points. Firstly, platforms should establish a screening mechanism, imposing certain advertising fees thresholds on firms. This would benefit users in distinguishing firms with varying levels of quality and mitigate the issue of information asymmetry regarding product quality. Secondly, platforms should incentivize firms to maintain consistency in the quality of their trial products and final products. When there is a significant disparity between the quality of trial products and final products in the market, users will no longer rely on the quality of free trials to assess product quality. This, in turn, diminishes the effectiveness of free trials as a means of conveying information, ultimately harming the welfare of both the platform and the firms. When users generally lack trust in the quality of trial products, it can lead to a collapse of market trust, resulting in a “lose-lose” situation.The main findings of our paper are as follows (1) When considering the informational role of FE quality, the high-quality firms can obtain higher profits if it is difficult for the low-quality firms to imitate. Conversely, if the imitation is relatively easy, high-quality firms need to increase their investment in FE to render the imitation behavior of low-quality firms unprofitable. (2) The informational effect of FE quality is more prominent in the short term. In cases of repeat purchases, whether the FE quality conveys information or not does not significantly impact the profits of the platform and the firms. (3) When the FE quality fails to convey any information, the platform should charge firms a certain threshold of advertising fees. This measure ensures that low-quality firms will find it unprofitable to imitate high-quality firms, while high-quality firms will not exit the market due to excessively high platform fees, ultimately promoting the occurrence of separating equilibria.

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Timing of Blockchain Adoption in Sharing Platform Considering Consumer Risk-aversion and Quality Distrust
Libin Guo, Xiangtian Guo, Jian Li
2024, 32 (12):  215-224.  doi: 10.16381/j.cnki.issn1003-207x.2022.1977
Abstract ( 72 )   HTML ( 2 )   PDF (2582KB) ( 37 )  

Consumers may be skeptical of the loss of shared products during transactions, generating risk aversion and quality mistrust. To cope with this situation, the blockchain technology needs to be adopted in the sharing platform to track and collect the usage information of the shared products, so as to realize the transparency and traceability of real-time loss information of shared products. In this paper, a dynamic game model of a competitive sharing platform connecting supply and demand sides is constructed by combining bilateral market theory. In this system, consumers are risk-averse, and the two sharing platforms charge platform service fees wi,pi from both supply and demand sides through supply and demand matching, information transfer and other services. Supply and demand sides choose an ideal sharing platform to complete product service transactions based on risk-averse attitudes and other horizontal differentiation factors. In the actual transaction process, users on the supply side pay costs fi for providing services on the platform i, including costs for product services and product maintenance, etc. Demand-side users have perceived uncertainty about the quality of shared products because they do not know the usage history and life cycle of shared products. Without the introduction of blockchain technology in the platform, the users on the demand side have no access to information about the quality of the shared products due to the lack of disclosure of information about the use of the shared products, so all decisions are made based on expectations. However, the implementation of blockchain in the platform makes the information transparent and traceable by tracking and recording the information on the loss of shared products. As a result, the utility obtained by all users can be updated based on unbiased estimates of randomly obtained quality information. The dynamic pricing and optimal profit of the platform under different scenarios whether blockchain technology is adopted or not are analyzed and compared. The specific timing of introducing blockchain technology to the platform is also discussed using numerical simulations.Results show that:(1) While risk averse consumers get positive information about product quality through the platform blockchain, the pricing of transaction fees for their services by the sharing platform increases with the accuracy of the disclosed product quality information.(2) While the accuracy of product quality information disclosed by the platform blockchain is low, the sharing platform with higher information quality weight can still improve its pricing to consumers based on users' trust in the platform. (3) There are opportunities to create a win-win situation for sharing platforms to disclose product quality information when blockchain technology is introduced at a lower cost and consumers have a higher perceived accuracy of product quality.

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Research on the Effect Path to Resident Cooperation Intention under Nuclear Emergency Evacuation Scenarios:A Case of Haiyang Nuclear Power Plant
Wenhui Qi, Mingliang Qi
2024, 32 (12):  225-234.  doi: 10.16381/j.cnki.issn1003-207x.2022.0901
Abstract ( 34 )   HTML ( 0 )   PDF (2085KB) ( 41 )  

Under nuclear emergency evacuation scenario, residents' intention to cooperate with government is an important factor restricting the nuclear emergency evacuation. In order to ensure the timeliness of evacuation and reduce the health and property losses of evacuated residents, the emergency evacuation plans formulated by the relevant government departments must be the coordinated by residents. Therefore, it is necessary to explore the factors influencing resident cooperation intention and their effect paths under nuclear emergency evacuation.In this paper, based on the theory of planned behavior and the theory of communication effect, a theoretical model is constructed to analyze the effects of public communication, knowledge, trust, perceived risk, perceived benefit, resident cooperation attitude, subjective norm, and perceived behavioral control on resident cooperation intention.A field survey is conducted in the area around Haiyang nuclear power plant in Shandong Province, and 322 valid questionnaires are collected. SPSS and AMOSS are used to analyze the data and a structural equation model is constructed to test the theoretical model empirically.The results show that there are three paths that can positively influence resident cooperation intention, namely: “public communication-knowledge-perceived risk-resident cooperation attitude-resident cooperation intention”, “public communication-trust-perceived benefit-resident cooperation attitude-resident cooperation intention”, and “subjective norm-resident cooperation intention”. public communication, trust, resident cooperation attitude, and subjective norm are important factorsthat trigger high resident cooperation intention.In addition, perceived behavioral control has no significant effect on resident cooperation intention. The research conclusions provide a theoretical basis for improving the nuclear accident emergency management and nuclear power public communication scheme.

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The Strategies of Social Responsibility and Carbon Information Dissemination in the Supply Chain of New Energy Vehicles
Xiaohong Chen, Ningyi Yang, Yanju Zhou
2024, 32 (12):  247-256.  doi: 10.16381/j.cnki.issn1003-207x.2023.1505
Abstract ( 67 )   HTML ( 2 )   PDF (1769KB) ( 66 )  

Under the dual carbon target, China has implemented a range of preferential policies to facilitate the optimization and upgrading of the new energy vehicle industry chain and supply chain. These measures aim to incentivize manufacturers to augment their investments in low-carbon research and development as well as production, encourage retailers to enhance their efforts in promoting and publicizing low-carbon initiatives, and urge consumers towards embracing green consumption. By leveraging their environmentally friendly characteristics, new energy vehicles are poised to garner consumer favor through the launch of a carbon publicity platform for China's automobile industry chain, thereby facilitating market share expansion and expediting the realization of low-carbon goals in the automotive sector. It focuses on the uncertainty faced by supply chain members when deciding whether to undertake social responsibility and disclose carbon information on a platform, aiming to explore strategies that maximize economic benefits for manufacturers and retailers while enhancing overall social and environmental outcomes. It is revealed that consumers' environmental preferences have a significant impact on the greenness and retail price of new energy vehicles, thereby establishing a symbiotic relationship. Although the manufacturer's profitability is positively correlated with its level of corporate social responsibility (CSR), it may be adversely affected by the free-rider behavior exhibited by retailers. Therefore, it is imperative for supply chain members to establish a shared objective of collectively constructing a low-carbon supply chain, ensuring equitable profit distribution, enhancing overall societal benefits, and achieving mutual success.

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Cost-sharing Mechanism for Closed-loop Supply Chain of New Energy Vehicles under EPR
Junfei Ding, Xujin Pu, Yuxin Cao, Jing Li
2024, 32 (12):  257-268.  doi: 10.16381/j.cnki.issn1003-207x.2023.1759
Abstract ( 58 )   HTML ( 2 )   PDF (2500KB) ( 47 )  

With the advance of manufacturing and new energy technology, new energy vehicles are trusted by consumers for their energy-saving and environmental protection characteristics. Due to policy and technological support, the global sales of new energy vehicles are gradually increasing.Although new energy vehicles have many advantages for consumers and the environment, the rapidly increasing number of new energy vehicles and their core component, power batteries, have also brought many challenges. At present, the lifespan of the first batch of new energy vehicles is approaching its end. A large number of scrapped new energy vehicles and retired power batteries not only cause waste of resources, but also pose certain environmental hazards. However, the large-scale waste disposal also contains huge business opportunities. On the one hand, although new energy vehicles have reached the end of their lifespan, some components still have high reuse value, such as motors, high-voltage wiring harnesses, and transmissions. On the other hand, retired power batteries still have a capacity of 70% to 80%, and cascading utilization can still play an important value.To promote the effective recycling of end-of-life new energy vehicles, thereby promoting the remanufacturing of key components and the echelon utilization of power batteries, the optimal cost-sharing mechanism for a closed-loop supply chain (CLSC) of new energy vehicles is explored based on extended producer responsibility (EPR). The decision-making CLSC model, composed of a battery supplier, an automobile manufacturer and a collector, is established, and then the scenarios of no cost sharing, the supplier sharing cost and the manufacturer sharing cost are investigated. Subsequently, the economic, environmental and social benefits of the CLSC are studied. The results show that, with the increase of cost-sharing proportion, the selling price of unit vehicle, the recovery rate of end-of-life vehicles, consumer surplus, the profits of the manufacturer and the CLSC, the environmental benefits and the social welfare remain unchanged if the supplier shares collection cost, under which, the cost-sharing mechanism only changes the profit distribution between the supplier and the collector; under the scenario of the battery supplier sharing collection cost, the collector’s profit decreases with the cost-sharing proportion; from the perspectives of the CLSC’s profits, consumers, the environment and social welfare, the manufacturer is ought to share collect cost rather than the supplier.

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Research on Manufacturer's Sourcing Strategies in the Face of Uncertain Supply Disruptions Risk
Junjin Wang, Songjun Xu, Jiaguo Liu
2024, 32 (12):  269-277.  doi: 10.16381/j.cnki.issn1003-207x.2023.1801
Abstract ( 215 )   HTML ( 4 )   PDF (2931KB) ( 106 )  

More and more suppliers are facing uncertain disruptions, and they do not know if and when disruptions will occur. Underestimating or overestimating the supply reliability may lead to over- or under-sourcing. A signaling game model of supply reliability is constructed for the manufacturer sourcing problem with uncertain supply disruptions risk. Manufacturer can source from a single supplier who is initially uncertain, or supplement from a reliable supplier with high cost, forming dual-sourcing. It focuses on signal quality effects, uncertainty effects and optimal sourcing strategies under different information conditions in this paper. The findings suggest that manufacturer needs to pay information rents to high-reliability supplier to prevent it from imitating low-reliability supplier under supply disruptions information asymmetry. Improving signal quality or reducing uncertainty about disruptions is not necessarily beneficial to the manufacturer, who can reduce the negative effects of information asymmetry by adjusting its sourcing strategies. In addition, when the supplier cost differences are moderate, a larger market size can hedge against the risk of switching sourcing strategies due to poor information.

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Quality Information Disclosure Strategies and Incentive Mechanism in the Supply Chain Based on the Third-party Shared Manufacturing Platform
Xumei Zhang, Bo Wang, Yi Liu, Bin Dan
2024, 32 (12):  278-287.  doi: 10.16381/j.cnki.issn1003-207x.2022.0107
Abstract ( 45 )   HTML ( 3 )   PDF (2683KB) ( 42 )  

With the development of a new generation of information technology, the third-party shared manufacturing platforms have developed rapidly and gradually become an important procurement channel for manufacturing enterprises. Productive service providers on the platform can attract manufacturers to purchase productive services by disclosing quality information reflecting their service quality. However, quality information disclosure will incur some costs. Therefore, productive service providers need to weigh the benefits and corresponding costs of quality information disclosure. In addition, productive service providers that offer alternative services on the platform compete with each other, which makes the revenue brought by quality information disclosure uncertain, and further affects the commission revenue of the platform. The quality information disclosure is conducive to increasing the platform's trading volume and commission revenue. Therefore, the platform needs to design an effective information disclosure incentive mechanism to improve the information disclosure level of service providers.Motivated by the above practice, it focuses on a supply chain composed of a third-party shared manufacturing platform, two competing productive service providers, and multiple manufacturers who purchase the productive service. By building a dynamic game model, the service providers' quality information disclosure decision is analyzed and the effects of competition intensity and the proportion of information-sensitive manufacturers on the information disclosure level are explored. On this basis, the optimal decision of the supply chain system is investigated and the feasible range of information disclosure incentive is obtained by taking the supply chain system as the comparison benchmark. Through examining the changes of information disclosure level in the feasible range, four quality disclosure incentive situations are obtained and the two-part incentive contract is designed to improve the quality information disclosure level of service providers. Finally, some numerical examples are constructed through MATLAB software to explain the results intuitively.The result indicates that competition between service providers will have a positive impact on the information disclosure level only when the proportion of information-sensitive manufacturers is large, the service price is within a range and the degree of competition is lower than a threshold value. Otherwise, intensifying competition will lower the information disclosure level. Compared with the optimal decision-making of the supply chain system, the service providers may have an excessively high level of information disclosure under certain conditions to maintain a competitive advantage. When the information disclosure level of the service provider is lower than the optimal level of the supply chain system, the two-part contract adopted by the platform can encourage competing service providers to improve the quality information disclosure level, which realizes the win-win goal of supply chain members. Under the two-part incentive contract, the platform may provide fixed compensation to the service providers, or ask the service provider for fixed compensation such as registration fee and membership fee.

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Can Green Credit Drive theGreeningof the Financial System and Enterprise Emission Reduction?Based on Evolutionary Game Analysis
Jiayu Zheng, Yi Hu
2024, 32 (12):  288-299.  doi: 10.16381/j.cnki.issn1003-207x.2022.0762
Abstract ( 56 )   HTML ( 0 )   PDF (3317KB) ( 43 )  

Green finance is an important way to achieve sustainable economic and environmental development. China has actively built green finance reform and innovation pilot areas to explore the development model of green finance. At present, China’s green financial products are dominated by green credit. Under the background of the “double carbon” goal, how to attract more financial subjects to participate in the green financial market to enrich and innovate green financial products and services is the key to China’s green financial development and also affects the realization of the “double carbon” goal. A three-party evolutionary game model of “banking financial institutions, non-banking financial institutions, and enterprises” is built to explore whether green credit can drive the “greening” of the entire financial system, thus providing more green funds for low-carbon projects to promote energy conservation and emission reduction of enterprises. The results show that: (1) The willingness of banking financial institutions to implement green credit has a signal effect on the development of green financial markets. When the initial willingness of banking financial institutions to “implement” green credit is high, it will promote enterprises to participate in energy conservation and emission reduction, and attract non-banking financial institutions to enter the green financial market; (2) When the initial willingness of each subject to participate in green financial development is low, the game can still reach the ideal equilibrium state by increasing the policy incentives of financial supervision departments and reducing the income gap between traditional projects and green projects; (3) When the initial willingness of each subject to participate in the green financial development is high, through the enhancement of the synergistic premium effect between financial institutions in the market, the enhancement of the environmental pollution punishment of financial institutions, and the compression of risk returns, all subjects will be able to converge to the ideal equilibrium state faster. Based on the above analysis, this paper puts forward corresponding policy recommendations.

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Multi-Level Structure Cooperative Game with Priority Coalitions and Its Application in Transboundary Watershed Governance
Jie Yang, Youling Dai, Libang Lai, Dengfeng Li
2024, 32 (12):  300-311.  doi: 10.16381/j.cnki.issn1003-207x.2023.1780
Abstract ( 47 )   HTML ( 0 )   PDF (2183KB) ( 50 )  

Cooperative game is a useful method to study management, and there exist multi-level structure and priority coalition in reality cooperation, which affect their final reasonable allocation. For example, in the cooperative governance of transboundary watershed, there are limited horizontal coalitions between adjacent watersheds and vertical hierarchy characteristic. In this paper, the classical definition of the core value is generalized to the cooperative game with hierarchical structure firstly. Then, a goal programming solution model of multi-level structure cooperative game with priority coalitions is established by introducing the priority factor to represent coalition priority. Moreover, the model is used to solve the cost allocation and compensation in transboundary watershed governance. In addition, it is demonstrated that: (1) There is a corresponding relationship between the optimal solution and the core of the multi-level structure cooperative game with priority coalitions. (2) The solution of multi-level structure cooperative game with coalitions is a general extension of the solution of single-level coalition structure. (3) For multi-level structure cooperative game, the solution of cooperative game with priority coalition is a general extension of structure without priority coalition. The conclusions of this paper can be drawn that the closeness of the sub-coalition in the hierarchy and the priority coalition relationship have significant effect on the cost allocation result, that is, the closer sub-coalition and the higher priority coalition lead to the greater cost saving.

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Real-time Pricing Demand Response Mechanism of Virtual Power Plant Based on Stackelberg Game
Baichen Xie, Lu Zhang, Peng Hao
2024, 32 (12):  312-322.  doi: 10.16381/j.cnki.issn1003-207x.2023.1944
Abstract ( 46 )   HTML ( 2 )   PDF (3412KB) ( 28 )  

Distributed energy plays an important role in mitigating climate change. Its large-scale application impacts the stability of the power system due to the intermittent property. Virtual power plants (VPPs), which aggregate distributed energy resources, adjustable loads, and energy storage systems, can effectively regulate load consumption and promote renewable energy consumption. We studied the demand response (DR) mechanism of real-time pricing within the VPP based on the Stackelberg game model, considering two-way electricity transactions between the VPP operator and prosumers, as well as between the VPP operator and the external main grid (MG). The study focuses on the collaborative scheduling of the MG, the VPP operator, and terminal loads. A distributed genetic algorithm is used to solve the equilibrium strategy for each stakeholder. The numerical simulation results show that: (1) The real-time pricing-based DR mechanism effectively incentivizes the VPP operator to trade with internal loads, smoothing load fluctuations and achieving significant peak-shaving and valley-filling effects. (2) From the users’perspective, both non-generating users and PV prosumers can benefit from participating in DR, while prosumers with only gas turbines have limited overall benefits. (3) The introduction of a real-time pricing DR mechanism effectively improves the benefits of VPPs and facilitates power resource scheduling. Based on these findings, the paper offers three suggestions for strengthening the future development of VPPs: First, VPPs should fully tap the controllable potential of loads, energy storage and other resources, guiding the loads to participate in peak shaving and valley filling through price signals; Second, to incentivize PV prosumers equipped with gas turbines to participate in DR, their opportunities to participate in the ancillary service market should be broadened, maximizing the income from peak balancing potential; Finally, an MG-VPP interconnection system based on artificial intelligence and big data should be developed. This system would integrate the MG’s real-time price and load forecasting information with the VPP’s functions of energy production, energy storage, and demand response.

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Complex Maritime Environment Oriented Multi-Level Supply Integrated Optimization of Wind Power Project
Sha Tao, Junying Yu, Shiwei Chen, Huihua Wang
2024, 32 (12):  323-334.  doi: 10.16381/j.cnki.issn1003-207x.2023.1982
Abstract ( 40 )   HTML ( 0 )   PDF (3376KB) ( 20 )  

With the deployment and implementation of China's 'dual carbon' and 'green development' strategies, wind power in China has entered a period of rapid development, and the vigorous development of offshore wind power projects has also become an important measure in the transformation of the energy structure.Offshore wind power project has the characteristics of distributed factory construction, all kinds of components in several factories distributed in different areas to complete the prefabricated production, transportation, and assembly in stages, and then transported by sea to the offshore construction site for on-site installation. Based on the engineering physical process of integrating the physical entities of wind turbine units from parts to whole (parts → components → assemblies → wind turbines), suppliers and manufacturers of each component level under the influence of supply-demand relationships, form a multi-level supply network. This network, in conjunction with offshore construction sites, constitutes a coherent and orderly operating whole. However, the long supply chain of offshore wind power projects and the close connections between each stage, along with the complex circulation of physical goods and information exchange within the supply network, pose significant management challenges. Moreover, as a type of major infrastructure project facing the open and complex maritime environment, the installation of wind turbines is greatly affected by uncertain factors such as sea winds, waves, tides, and undercurrents, resulting in high environmental complexity. The construction progress and assembly resource planning of offshore wind power projects are significantly influenced by real-time environmental changes and impacts, which also affect the overall supply network at the back end, thus increasing the complexity of overall supply decision-making. Therefore, the construction progress and resource demand planning for offshore wind power projects are significantly influenced by real-time environmental changes. The challenge addressed in this paper is how to accurately predict changes in maritime wind and wave conditions, and then integrate these predictions with their impacts on construction operations and progress to formulate a multi-level supply integration decision-making strategy, thereby ensuring the effective operation of the overall supply network.Firstly, this paper constructs a scenario-based multi-level supply integration optimization model for offshore wind power projects to provide support for subsequent algorithm design. This model, based on the uncertain characteristics of the real offshore environment, proposes a multi-level supply integration optimization model that addresses different environmental scenarios. The model can devise optimal multi-level supply integration plans for the entered |S| scenarios. Additionally, drawing from a case study of a wind power engineering supply network, the model considers the multi-level supply relationships corresponding to the physical process of integrating the physical entities of offshore wind power projects from parts to whole (parts → components → assemblies → wind turbines), which involves more complex elements and interrelations. For example, some parts are supplied by suppliers and transported to manufacturers to be made into components, then shipped to the dock, forming the supply chain: Supplier (parts) → Manufacturer (components) → Dock (components); some components may be supplied by suppliers and pre-assembled at the dock into assemblies, then transported to the wind farm site for final installation, forming the supply chain: Supplier (components) → Dock (assemblies) → Wind farm site (turbines). Furthermore, there are two types of turbines hoisting schemes in the construction process: one involves pre-assembling blades and hubs into rotors at the dock, then transporting them by ship for installation at the wind farm; the other involves transporting blades and hubs directly to the wind farm site for onsite assembly. Based on the above physical processes, it is necessary to integrate and collaboratively consider decisions on production, storage, and other logistics at each node along the supply chains, including decisions on matching supply with demand and choosing transportation modes. The decision variables of the model include (1) dynamic demand, production, and inventory levels of parts, components, or assemblies at various supply nodes, including suppliers, manufacturers, and docks; (2) the volumes of various components transported between supply nodes and the choices of sea or land transportation modes.Subsequently, a Markov chain-sample average approximation two-stage algorithm (MC-SAA) is designed for a solution. Initially, the first stage uses the MC model to simulate possible regional maritime environmental scenarios based on the historical environmental data of the target sea area. Then, based on the construction process requirements of the wind power project and the various offshore wind and wave scenarios simulated by the MC, a set of scenarios for construction progress and resource demand plans are further generated. In the second stage, using the SAA algorithm, multiple cycles of random scenario sampling are conducted, with each scenario set being input into the model described in section 2.2 to solve for the optimal solution. Then, the best multi-level supply integration decision-making plan is selected through comparisons of the solutions under all sampled scenarios.Finally, a real case of a wind power project in the southern maritime area of China is taken as its background, verifying the effectiveness of the model and methods through computational experiments, and exploring several managerial insights. It indicates that, overall, compared to two empirical methods, the algorithm proposed in this paper not only effectively achieves better supply decision-making outcomes but also ensures the adequate supply of wind power project components across a broader range of maritime environmental conditions, while minimizing costs associated with resource idleness, such as vessel leasing and storage, thereby demonstrating stronger scenario adaptability.The research on multi-level supply optimization for engineering projects under uncertain environments is extended and practical guidance and decision support are provided for supply decision-making in offshore wind power projects.

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