Table of Content

    25 May 2024, Volume 32 Issue 5 Previous Issue   
    Re-exploration of Small and Micro Enterprises' Default Characteristics Based on Machine Learning Models with SHAP
    Xinnan Lei,Lefan Lin,Binqing Xiao,Honghai Yu
    2024, 32 (5):  1-12.  doi: 10.16381/j.cnki.issn1003-207x.2021.0027
    Abstract ( 101 )   HTML ( 26 )   PDF (794KB) ( 93 )   Save

    Machine learning methods have been applied to the small and micro enterprises’ loan approval and monitoring process, and have achieved good results in default identification. Considering the higher recognition accuracy of machine learning methods, its use of indicator information should be better than traditional models. Therefore, it hopes to dig out the important factors in the judgment of default from the perspective of machine learning in this paper.SHAP is a machine learning interpretation method based on the Shapley value of game theory, which can identify the importance of indicators in the model from the perspective of results. Based on the small and micro enterprise loan account of a bank, SHAP (SHapley Additive exPlanations) is added to machine learning models to find important default characteristics of small and micro enterprises.It is found that, in addition to traditional loan information and corporate financial indicators, non-financial indicators such as the age of the company, the number of law cases, and the “soft information” evaluated by the customer manager play significant role in identifying defaults of small and micro enterprises.From the perspective of interpretability, the application of machine learning methods is discussed in the identification of default characteristics of small and micro enterprises, and innovatively the SHAP interpretation method is introduced to study important indicators in rating. At the same time, the key indicators mined have guiding significance for the development of loan business.

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    Trade-in Strategies of Competitive Enterprises Considering Consumer Loyalty
    Fei Tang,Ying Dai,Zujun Ma
    2024, 32 (5):  13-23.  doi: 10.16381/j.cnki.issn1003-207x.2021.0066
    Abstract ( 83 )   HTML ( 8 )   PDF (857KB) ( 57 )   Save

    Trade-in programs, as an effective means of promotion strategy to retain loyal consumers and promote the sales of new products, are widely implemented in practice. Consumers who participate in the trade-in program can obtain a special discount toward the purchase of new products. The returned old products may either be within the same brand as the new product or be in a different brand. Accordingly, enterprises can offer a within-brand trade-in program to accept their own consumers only or offer a multi-brand trade-in program to attract consumers from their competitor. In addition, as consumers can gain more information regarding how well a product fits their preferences after using it, they may show some loyalty to the products they have used. The strength of consumer loyalty will affect their trade-in choices in their next purchase. In this context, it is natural to wonder what type of trade-in programs (within-brand or multi-brand) the enterprise should offer in a competitive market when considering consumer loyalty.In this paper, a game-theoretic approach is applied to examine whether competing enterprises should offer a within-brand trade-in program or a multi-brand trade-in program when facing the impacts of consumer loyalty. Based on the Hotelling model, pricing and trade-in rebate models under different trade-in strategies of the two enterprises are developed. The impacts of consumer loyalty on their optimal decisions and profits are analyzed. The results show that when the trade-in market is partially covered, no matter what trade-in strategies the two enterprises provide, it has no impact on the optimal prices of new products, the within-brand trade-in rebates, and the number of loyal consumers. Moreover, multi-brand trade-in is the pure-strategy equilibrium of the two enterprises. When both enterprises provide multi-brand trade-in and the trade-in market is fully covered, the within-brand trade-in rebate decreases while the number of loyal consumers increases with the increase of consumer loyalty. Moreover, no matter the trade-in market is partially covered or fully covered, the stronger the loyalty of replacement consumers is, the more conducive the enterprise will be to retain its own loyal consumers and attract the competitor’s brand switchers, so as to gain more profits. The results not only support some of the current trade-in practices but also have important managerial implications to guild enterprises to provide an appropriate type of trade-in program under competition.

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    Spent Power Battery Recycling Technology Selection Based on Integrated CoCoSo and Heronian Mean with Intuitionistic Linguistic Rough Number
    Haolun Wang
    2024, 32 (5):  24-37.  doi: 10.16381/j.cnki.issn1003-207x.2021.0319
    Abstract ( 27 )   HTML ( 3 )   PDF (830KB) ( 24 )   Save

    How to select the optimal spent power battery recycling technology(SPBRT) is an important group decision-making problem in the recycling management of waste power battery. Firstly, the intuitionistic linguistic rough Heronian mean (ILRHM) and intuitionistic linguistic rough geometric Heronian mean (ILRGHM) operators and their weighted forms are defined based on the intuitionistic linguistic rough numbers (ILRNs) in this paper, and the related some properties and special cases are discussed. Then, a multi-attribute intuitionistic linguistic rough group decision-making model is proposed, which includes the combination weights of attributes are determined by the decision maker’s evaluation information and the deviation maximization principle, the traditional CoCoSo method is improved by using intuitionistic linguistic rough weighted Heronian mean (ILRWHM) and intuitionistic linguistic rough weighted geometric Heronian mean (ILRWGHM), and evaluate alternatives and make the optimal decision considering the decision maker’s risk preference. This method (1) can capture the correlation between attributes, (2) can realize the balance between optimistic and pessimistic decision-making attitudes of decision makers, (3) introduces the risk preference coefficient of decision makers to make alternative ordering more flexible, and (4) can detect the influence of parameters on decision results through the change analysis of decision-making parameters and has robustness. Finally, in order to verify the effectiveness and rationality of the proposed method, SPBRT selection is taken as an example to demonstrate the advantages of this method through effect of parameters and comparative analysis with other methods.

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    Trade Credit and Industrial Policy Transmission: Theoretical Modeling Analysis and Evidence from Ten Industries Revitalization Plan
    Shen Qu,Xuesong Qian,Jin Kang
    2024, 32 (5):  38-46.  doi: 10.16381/j.cnki.issn1003-207x.2022.0214
    Abstract ( 20 )   HTML ( 2 )   PDF (1373KB) ( 13 )   Save

    The economic impact of industrial policy is an important issue of academic concern. However, constrained by research perspective, research method, and the scarcity of natural experiment, the existing research neglect the role played by trade credit in the transmission process of industrial policy, moreover, research method of these studies needs to be improved, which leads to the insufficient academic understanding of industrial policy transmission issue. In this context, it answers the following questions: How does industrial policy affect the real economy? What is the transmission mechanism? In particular, does trade credit play a role in the transmission process of industrial policy? From the perspective of industrial chain, a firms’ decision-making model introducing the impact of industrial policy is constructed, and how industrial policy affects the real economy through trade credit is analyzed. On the basis, with the help of the quasi-natural experiment of China’s Ten Industries Revitalization Plan, difference-in-difference method is used, based on the China’s listed companies data from 2007 to 2011, to find that after the introduction of the industrial policy, the firms in the experimental group take advantage of bank credit financing to provide financial support for other firms in the industrial chain through trade credit, which helped product sales and reduced inventory levels. It not only enhances our understanding of how industrial policy affects the real economy, but also helps to clarify the relationship between bank credit financing and trade credit supply with the help of the quasi-natural experiment in this paper. There is important enlightenment and reference significance for maintaining the stability of the industrial chain and promoting economic growth.

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    Equity Extreme Tail Risks,Leverage Ratio and Credit Spreads of the Corporate Bonds in China
    Linli Xie,Aifan Ling
    2024, 32 (5):  47-60.  doi: 10.16381/j.cnki.issn1003-207x.2021.0476
    Abstract ( 37 )   HTML ( 6 )   PDF (1068KB) ( 25 )   Save

    Using Merton's structural model, the theoretical relationship between extreme tail risk of equity and credit spread of corporate bonds is established. Theoretically, credit spread is an increasing function of stock extreme tail risk with leverage ratio as the intermediary variable. The empirical Chinese results show that, completely consistent with the theoretical results, the credit spread is significantly positively related with the extreme tail risk and the empirical results are robust under the considered control variables. The mechanisms are empirically analyzed and it is found that the increaseof extreme tail risk can cause the increasing of credit spread by the leverage ratio. The results are helpful to understand the causes of “credit spreads puzzle”, and provide important empirical evidence for the stochastic volatility and jump-diffusion models to fit the credit spread well in practice.CSi,t=?α+β1×ETRiskj,i,t+β2'×Firmi,t+β3'×Macrot+δi+λt+?i,t,???j=1,?2. Where is the credit spreads of corporate bonds,ETRiskj,i,t is the extreme tail risk of equityi with j-order.Firmi,t and Macrotrepresent the control variables at the corporate and macro levels. To check the impacts of extremeequity tail risk on the credit spread of corporate bonds, the following regression equation:is used 827 corporate bonds publicly issued in China's bond market from January 2009 to January 2020 are selected as bond samples,and the matching equity data of 550 companies. There are 23429 sample data in the panel. All data comes from CSMAR databaseand Wind database.It is proved the positive correlation between extreme tail risk and corporate bond credit spread both theoretically and empirically. After controlling the company and macro levels control variables, the results remain unchanged. The difference tests show that the credit spread of company with low long-term debt ratio or low credit rating are more sensitive to the extreme tail risk of equity. Extreme tail risk in corporate equity has also become more sensitive to credit spreads after the stock market crash. Mechanism analysis found that the extreme tail risk of the company's equity will affect the credit spread of corporate bonds through channels such as the company's asset volatility and leverage ratio. This is also helpful for understanding the reasons for the “credit spreads puzzle”.

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    Downside Risk in the Chinese A-Share Market: Based on the Perspective of Generalized Disappointment Aversion
    Lanbiao Liu,Liang Guo
    2024, 32 (5):  61-72.  doi: 10.16381/j.cnki.issn1003-207x.2021.0820
    Abstract ( 28 )   HTML ( 0 )   PDF (618KB) ( 38 )   Save

    In the stock marketdue to overconfidence or other subjective factors,decisions made by investors do not follow the completelyrationalhypothesis. Whether it is the 2008 financial crisis or the 2015 A-share market crash, there are traces of investor behavior such as herding effect or fire sales. At present, the research on investor preference in the A-share market mainly focuses on the theoretical model level. Few literatures are based on the theoretical model of investor preference to study the downside risks of the A-share market from an empirical perspective. At the same time, existing studies often only start from the full sample, ignoring the inconsistency of downside risks in differentstockmarketperiods.For the above reasons, based on the generalized disappointment aversion factor model proposed by Adam and Roméo(2018), the relationship between the downside risk and the expected return in Chinese stock market is studied. In the empirical test, the monthly stock data of all stocks in the A-share market from January 2002 to June 2019 are selected for a total of 210 months for research. With reference to the methods of Fama and French, 25 investment portfolios in 4 categories including scale and book-to-market value ratio, scale and momentum ranking, scale and investment ranking, and scale and profitability ranking are constructed, verifying the robustness of the downside factors after controlling for the above factors. Subsequently, in view of the differences in risk premiums at different market stages, the performance of each factor in stages is also examined, and it is found that investors with generalized disappointment aversion behavior would have an impact on the risk appetite of the market. Finally, considering that the behavior of institutional investors will also affect the formation of stock market bubbles and extreme risks, the impact of institutional investors on the downside risk premium is also examined.Through empirical research, it is found that:(1) generalized disappointment aversion and stock market downside factors can explain the expected return of assets. Chinese stock market investors have typical generalized disappointment aversion behavior, and volatility is less effective in explaining returnin Chinese stock markets. (2) With sub-testing, it is also found that the reason behind the excess return ofdownside factor is risk-taking; the excess return of downside risk has different characteristics in different periods of the stock market, indicating that investors havegreaterdegree of risk appetitewhen extreme negative returns occur in the stock marketthan other stocks market periods. During the stock market upside period, investors turn to be risk aversion. (3) Institutional investors have a higher degree of general disappointment aversion. They require a higher downside risk premium during the stock market up period, and become risk chasing during the down period of the stock market; The assets with the highest proportion of retail investors have negative downside risk premiums in all periods, and investors have shown risk chasing in all periods.

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    Research on the Application of GWO-SVR Algorithm in the Prediction of Reverse Mixed Data in Stock Market and Investment Strategy
    Yi Cai,Zhenpeng Tang,Junchuang Wu,Xiaoxu Du,Kaijie Chen
    2024, 32 (5):  73-80.  doi: 10.16381/j.cnki.issn1003-207x.2022.2710
    Abstract ( 36 )   HTML ( 4 )   PDF (4017KB) ( 22 )   Save

    The violent fluctuations of the stock market pose a threat to financial stability and have a significant impact on a country's economic development. Therefore, understanding and predicting stock market fluctuations play a crucial role in evaluating a country's economic performance. Stock returns exhibit characteristics such as non-stationarity, nonlinearity, and volatility aggregation. As a result, stock return forecasting has garnered substantial interest among scholars. However, most existing studies solely rely on historical stock price sequences for prediction, which often leads to subpar results. The weekly frequency of fund position changes holds significant value in determining future market trends. Increasing fund positions can drive stock market upswings, while individual retail investors tend to follow and mimic these position changes, thereby influencing future stock market movements. Recognizing the information gain effect of fund position changes on the stock market and the intricate relationship between these two types of data, a novel model is proposed that combines the reverse mixed data sampling model (R-MIDAS) with machine learning algorithms. The model is applied to predict the index return rate and investment strategy for 27 industries.The empirical results demonstrate several key findings. Firstly, the performance of the R-MIDAS-GWO-SVR algorithm surpasses that of other benchmark models, such as R-MIDAS-SVR, R-MIDAS-CNN, and R-MIDAS-LSTM. In particular, the R-MIDAS-GWO-SVR model outperforms the LR model in 19 industries. Secondly, the proposed model exhibits excellent performance in single-industry investment strategies, as indicated by risk-adjusted performance indicators based on the forecasted results. Lastly, when considering multi-industry portfolio investments, the R-MIDAS-GWO-SVR model consistently outperforms other models for various values of k (specifically, 5, 7, and 9). The combination of the R-MIDAS model and machine learning methods shows promising potential in predicting mixed frequency data. These findings contribute to the literature by introducing a new approach to stock return forecasting and highlighting the importance of incorporating fund position changes into prediction models. The proposed model has significant implications for investors, regulators, and policy makers in making informed decisions and formulating effective investment strategies in the stock market.

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    Research on Green Product Marketing Strategy of Enterprise Network Platform Supply Chain under Data-driven Marketing
    Yi Chen,Xiaoman Sun,Ning Zhang,Shuangli Cai,Zongyu Mu
    2024, 32 (5):  81-92.  doi: 10.16381/j.cnki.issn1003-207x.2023.1214
    Abstract ( 46 )   HTML ( 8 )   PDF (920KB) ( 55 )   Save

    The rapid development of the global economy has led to the continuous deterioration of the climate and ecological environment, and people are gradually recognizing the importance of green production and development. With the swift advancement of technology, the functionalities of online sales services and data-driven marketing advantages on Internet platforms are becoming increasingly prominent, all of which contribute to the production and sale of green products. A pressing issue arises regarding how manufacturing enterprises engaged in green research and development activities cooperate with platforms to sell products, achieving a win-win in economic, ecological, and social benefits. Therefore, manufacturers investing in green technology are contemplated to produce products and internet platforms utilizing consumer online shopping data to conduct data-driven marketing activities, and a network platform supply chain model composed of a manufacturer and a platform is constructed. The Stackelberg game model was used to study the economic and ecological benefits of cooperative marketing of green products between manufacturers and platforms in different sales models. Furthermore, the issue of manufacturers utilizing cost-sharing contracts to collaborate with network platforms in conducting data-driven marketing of green products is considered, and the accuracy of the results is validated through numerical analysis. It is found that: 1) optimizing green investment and data-driven marketing costs, as well as enhancing consumer sensitivity to green products and data-driven marketing, are conducive to elevating the profit levels of network platform supply chain members and the greenness of products; 2) under the agency selling strategy, the commission rate charged by the network platform is a primary factor affecting the selection of sales strategies by manufacturers and platforms, with a commission rate threshold existing that enables both manufacturers and platforms to obtain more profits compared to a reselling strategy; 3) under the agency selling strategy and reselling strategy, manufacturers can effectively motivate network platforms to sell green products using cost-sharing contract, and there exists a cost-sharing threshold, enabling both manufacturers and network platforms to potentially achieve Pareto-improved profits. Lower commissions charged by the network platform and larger marketing costs shared by manufacturers are conducive to realizing a win-win in economic and ecological benefits. A theoretical foundation is provided for better realizing the comprehensive development of economic and environmental benefits in the supply chain.

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    Evaluation of Coupling Coordination Effect of Economic-Society-Governance System in Minority Regions: Take Xinjiang as An Example
    Haifeng Hu,Yong Sun,Mingkai Liu,Baoyin Liu,Jie Fan
    2024, 32 (5):  93-102.  doi: 10.16381/j.cnki.issn1003-207x.2022.0311
    Abstract ( 25 )   HTML ( 0 )   PDF (894KB) ( 23 )   Save

    High-quality economic and social development in ethnic minority areas is an important part of China's high-quality development. In order to scientifically evaluate the coupling and coordination effect of economic-social-governance system in ethnic minority areas and assist the decision-making of regional economic and social high-quality development, taking Xinjiang as an example, the subdivision index panel data of each system from 2013 to 2020 are selected, and the methods such as entropy method, coupling coordination model and system dynamics are used. The development level of economic development, social development and government governance in Xinjiang is quantitatively evaluated, and the degree of coupling and coordination between systems is further measured. The results show that the level of economic development, social development and government governance in Xinjiang is gradually improved, the three show obvious coupling interaction, and the coupling coordination effect of economic-social-governance system shows an upward trend as a whole. The promotion of sustainable development in Xinjiang should be guided by the general goal of social stability and long-term stability, enhance the quality of production and living environment, enhance regional economic competitiveness on the basis of economic development, and take government governance as a means to optimize the regional development environment.

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    Stochastic Simulation Integrated Method for Multi-source Uncertain Information and Its Application
    Lu Wang,Pingtao Yi,Weiwei Li
    2024, 32 (5):  103-112.  doi: 10.16381/j.cnki.issn1003-207x.2021.0547
    Abstract ( 30 )   HTML ( 3 )   PDF (1633KB) ( 11 )   Save

    Under the increasingly complex and uncertain evaluation environment, the expression of uncertain information has been further developed and many uncertain theories and methodologies have been introduced into comprehensive evaluation problems.A comprehensive evaluation problem involves such issues that the experts with different knowledge backgrounds usually need the freedom to provide the opinions by their individual preferences and the development of social platform and search software has made it possible to obtain diversified information, such as the text evaluation information and fragment information that people leave on the website inadvertently. Besides, the absolute ranking, which means that an alternative is superior to its next adjacent one with 100% probability, is lack of explanation for comprehensive evaluation problems containing multi-source information especially uncertain information. It is a meaningful and urgent issue to propose a novel method to integrate multi-source inputs to a reasonable output.For the sake of the problems above, a multi-source uncertain information (MSUI) integration framework was built to fuse all kinds of information mentioned in this paper by simulation techniques. Then, obtain the most likely ranking with pairwise priority probabilities. Specifically, the first problem is fusing the MSUI. The MSUI is normalized into a unified scope where the random numbers considering membership degree are generated by a certain distribution. The second problem is integrating the MSUI. The MSUI is classified by the types into different clusters, based on which the MSUI integration framework is established. The third problem is obtaining a reasonable output. the priority comparison of each alternative can be done by each simulation. After adequate simulation, the ratio of the times that one alternative is prior to another one to the total simulation times tends to be stable. Then, the pairwise priority matrix (PPM) is obtained. Based on the method of regression tree, the most likely ranking with pairwise priority probabilities can be obtained from the matrix.An application example that a company evaluates the comprehensive ability of 8 employees in the marketing department shows that: (1) The development of uncertain theory, such as fuzzy sets, linguistic information, allows the experts to describe multi-attribute evaluation problems more freely but more precisely. (2) The MSUI is fully tapped by adequate simulation, which avoids the employees being sorted by just one comparison. (3) After comparing the most likely ranking and the absolute ranking, the employee o4 is not absolutely superior to employee o5, but superior to employee o5 by 70.65% probability. The most likely ranking provides more information about the comparison among the employees.The main contributions of the method proposed in this paper are summarized as follows. (1) The fusion of MSUI ensures the information characteristics and fully mines the information value. (2) This information fusion platform has strong compatibility with fragment information, which expands the range of information available for evaluation problems. (3) Some possible outputs are obtained which differ from the absolute results by most methods, which can better explain the practical phenomenon in the actual world such as the weak team winning the strong one in a game.

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    Research on the Decision of Cooperative Emission Reduction in Supply Chain under Energy Costs Hosting Contract from the Perspective of Embeddedness
    Nuo Liao,Peiyi Liang,Yong He,Xueyun Luo
    2024, 32 (5):  113-121.  doi: 10.16381/j.cnki.issn1003-207x.2021.0251
    Abstract ( 25 )   HTML ( 1 )   PDF (664KB) ( 12 )   Save

    Energy performance contracting has become the popular method to solve the carbon emission problem for manufacturers. In academia, research on the problem of supply chain cooperation and emission reduction under share savings or guarantee savings contracts has been studied, and the emission reduction issues under energy cost hosting contracts have not been considered. In view of the above considerations, the decision-making issue of cooperative emission reduction in the supply chain when energy service company (ESCO) provides embedded low-carbon services under energy costs hosting contract is explored. Two scenarios of game models are established including cooperative emission reduction in the supply chain without the participation of ESCO, and with the participation of ESCO under energy costs hosting contract. The results indicate that, only when certain condition is met, the supply chain will choose to cooperate with ESCO; when the embedding degree (the ratio of the equal present value coefficient during the contract period to the equal present value coefficient during the economic life of the project) reaches a certain value, the degree of commonality in the value of carbon emission reduction begins to converge; A high level of embedding degree could achieve better emission reduction effects, and the embedding degree has an U-shaped relationship with the expected profit of the supply chain, and is positively correlated with the expected profit of the ESCO; For manufacturers, it is better to build a medium and long-term cooperative relationship with ESCO. These conclusions provide theoretical reference for the effective application of energy cost hosting contracts in the context of supply chain.

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    Information Sharing in the Fresh Produce Supply Chain with 3PL's Fresh-keeping Effort
    Bin Dan,Songxuan Ma,Molin Liu,Yu Tian,Ting Lei
    2024, 32 (5):  122-132.  doi: 10.16381/j.cnki.issn1003-207x.2021.0778
    Abstract ( 33 )   HTML ( 3 )   PDF (871KB) ( 47 )   Save

    As the consumption level rises, the price of fresh produce is not the only concern of consumers, but the quality of fresh produce is gradually becoming a focus. In order to ensure the quality during the distribution process, fresh produce companies often choose third-party logistics (3PL) with cold chain resources to preserve freshness. 3PL’s fresh-keeping effort affects the demand for fresh produce, and plays an important role in the profitability of fresh produce companies as well as the overall performance of the fresh produce supply chain. However, the market demand uncertainty makes operational decisions on fresh-keeping effort and pricing difficult. It may result in too much or too little investment of fresh-keeping resources, leading to efficiency loss of the fresh produce supply chain. Compared with the supplier and 3PL, the retailer has an information advantage about demand forecast and may choose to share demand information to eliminate information asymmetry. Thus, there is a contradictory question of whether the retailer shares demand forecast information with the upstream members and whether upstream members transmit information to each other. To address this problem, the information sharing strategy in the fresh produce supply chain considering 3PL’s fresh-keeping effort is investigated.There are four parts as follows. First, considering the impact of the 3PL’s fresh-keeping effort on freshness, a multi-subject game model of the fresh produce supply chain is established under complete information sharing strategy, partial information sharing strategy and no information sharing strategy, and the optimal pricing and fresh-keeping effort decisions are analyzed. Second, information sharing preferences of supply chain members are analyzed and the retailer’s information sharing strategy is investigated. Third, based on the overall performance of the supply chain under different information sharing strategies, an incentive contract is designed to adjust the information sharing strategy. Finally, the impacts of the contract on the equilibrium decisions are discussed.The results indicate that only if the potential demand is relatively high, does the 3PL have the motivation to increase the fresh-keeping effort with the freshness elasticity increasing. It suggests that the development of cold chain is better off relying on a larger fresh produce market. The results also show that information sharing always benefits for the supplier while it hurts the 3PL. It is in the retailer’s best interest to share information only with the 3PL, but it cannot achieve because the 3PL will transmit the information to the supplier. As a result, when the freshness elasticity is relatively high, the retailer sharing information with both the supplier and the 3PL is the equilibrium strategy, while the freshness elasticity is relatively low, the equilibrium strategy is not to share information. The overall performance of the fresh produce supply chain is optimal when the retailer only shares information with the 3PL, so the retailer can design a transfer payment contract to circumvent the transmission of demand information between upstream members. The aim is different from the existing literature on information sharing incentives involving multiple subjects, so a new perspective on information sharing in the supply chain is provided. After that, with the high market demand information, the quality of fresh produce will be improved, and the selling price of fresh produce with high freshness elasticity will be lowered.

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    Sales Format Selection for Platform-based Supply Chain Considering Consumers' Webrooming Phenomenon in Multi-channel Retailing
    Deqing Ma,Xiaoqing Wang,Jinsong Hu
    2024, 32 (5):  133-146.  doi: 10.16381/j.cnki.issn1003-207x.2021.0806
    Abstract ( 36 )   HTML ( 1 )   PDF (1302KB) ( 31 )   Save

    Webrooming, a shopping process in which consumers use online channels to browse product information while completing purchases in offline channels, is an increasingly common type of consumer cross-channel (separation of channels for browsing and purchasing products) behavior in the multi-channel retail environment of the mobile Internet era. According to a report in the 2019 China New Retail White Paper, this webrooming phenomenon is becoming increasingly common, with the product categories in which it occurs involving mother and baby products (39%), skin care and makeup (32%), personal care (32%), alcohol (32%) and cleaning products (31%). Platform companies have also identified in practice the negative impact of this webrooming phenomenon on their sales conversion rates and economic efficiency, and have started to actively adjust their sales models to cope with the increasing retail competition and consumer webrooming behavior. For example, Amazon in the U.S., Taobao in China, and Flipkart in India have adopted a reseller model for most categories of products, while leading U.S. footwear platform Zappos and digital content platforms such as Comcast, Apple's iTunes, and Netflix sell their products through a reseller model. Whereas existing studies have explored platform sales model choice in multiple contexts, the impact of consumer cross-channel behavior, especially the most prevalent webrooming behavior today, on sales models has not been reported, and there has been little discussion of the willingness of other supply chain members to cooperate after the platform has made the optimal sales model choice. To this end, the impact of the webrooming phenomenon on the platform's optimal sales model choice is explored in the context of multichannel retailing for a platform-based supply chain consisting of a manufacturer, a platform-based retailer, and a brick-and-mortar retailer. Four differential game models are constructed: reselling model with webrooming (model S), reselling model without webrooming (model NS), reselling model with webrooming (model A) and reselling model without webrooming (model NA). The impact of the webrooming phenomenon is analyzed by comparing the level of quality improvement of manufacturers, the service level of brick-and-mortar stores, the big-data marketing of the platform retailer, and the brand goodwill and corporate profits under the four models. Using numerical examples, our previous findings are validated and the conditions are explored under which the platform-optimal sales model holds true. The results show that when the webrooming phenomenon does not exist, the platform chooses the reselling model when the commission rate is relatively low and the online retail price is relatively high, and the reselling model in other cases. When the webrooming phenomenon is present, the platform also chooses reselling when both commission rates and online retail prices are enough high, and this area widens with the degree of webrooming. An important result is that the supply chain has a globally dominant sales model only when the webrooming phenomenon is present. In addition, it is shown that the presence of the webrooming phenomenon does not affect the decisions of the manufacturer and the brick-and-mortar retailer, but it inhibits the incentive of the platform to offer online services. The presence of the webrooming phenomenon consistently hurts the platform's profitability, and it is more severe as the intensity of the webrooming phenomenon increases. As the intensity of the webrooming phenomenon increases, the brick-and-mortar retailer’s profit first increases and then decreases, with the greatest profits occurring when the intensity of the webrooming phenomenon is moderate. For the manufacturer, the impact of changes in the intensity of the webrooming phenomenon is analyzed in the context of platform commission rates and online retail prices.

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    Closed-loop Supply Chain Decision Model Based on Trade-in and Supply Chain Structural Differences
    Jiangtao Hong,Yuting Quan
    2024, 32 (5):  147-157.  doi: 10.16381/j.cnki.issn1003-207x.2021.0910
    Abstract ( 25 )   HTML ( 3 )   PDF (1026KB) ( 24 )   Save

    Companies establish closed-loop supply chain (CLSC) via trade-in mechanism, which is a way of circular economy, attracting consumers to spontaneously participate in the reverse logistics process, which can not only promote repurchase level but also realize the environmental-friendly green supply chain establishment. It focuses on the supply chain structural differences under trade-in mechanism in this study. Four structural differentiated trade-in CLSC Stackelberg game scenarios are modeled in a supply chain including a manufacturer and a retailer from two dimensions—the supply chain leader and trade-in service provider (whether to outsource the service). The market is segmented based on the customer categories and a return function is used to describe the total amount of used products collected via trade-in service, which is alse the demand realized in this channel because of the inherit character of trade-in mechanism (when a used product is returned a new product is sold at the same time). The four scenarios established and discussed in the paper according to the two dimentions above are: (i) scenarioM(I) in which the manufacturer is the leader of the supply chain and also the trade-in service provider; (ii) scenarioR(I)in which the manufacturer is the leader of the supply chain and outsources the trade-in service th the retailer; (iii) scenarioM(II)in which the retailer is the leader of the supply chain but the trade-in service is provided by the manufacturer; and (iv) scenarioR(II)in which the retailer is the leader of the supply chain and also provides the trade-in service. The Stackelberg equilibrium of each scenario is solved and discussed in this paper and a numerical study done by using mathematica is also delivered to support analytic results, show those results more visually and explore those equilibrium solutions more deeply. The results from both analytic and numerical studies show that: (1) both the manufacturer and the retailer prefer to provide trade-in service themselves when there is no transfer payment, and such divergence will be deeper when the gap between the new customers market potential and the replacement one is larger; (2) when the leader is fixed, the total supply chain profit is always higher when the manufacturer provides trade-in service; (3)the manufacturer will provide the trade-in service herself when she is the leader of the supply chain, and the retailer who does not participate in the trade-in service and related reverse channel will secure a part of the profit of reverse channel from higher forward markup; (4) the retailer tends to ask the manufacturer to outsource the service when leading the supply chain and the manufacturer can fill the retailer’s profit gap via transfer payment and reach an agreement so that she can provide the service herself and maximize the total CLSC profit. According the results and analysis in this study, a theoretical basis can be provided for enterprises and supply chains who planning to provide trade-in service, helping them to choose optimal strategies acccording to the market environment and the supply chain structure and determine their optimal prices and trade-in rebate.

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    Differential Game of Closed-Loop Supply Chain with Dynamic Stochastic Recovery Rate under Reward-penalty Mechanism of Government
    Daoping Wang,Ke Zhang,Yu Zhou
    2024, 32 (5):  158-170.  doi: 10.16381/j.cnki.issn1003-207x.2021.1138
    Abstract ( 40 )   HTML ( 1 )   PDF (941KB) ( 17 )   Save

    The dynamic equilibrium strategy of the members in a closed-loop supply chain (CLSC)dominated by retailers and recycled by manufacturers is studied under reward-penalty mechanism (RPM).The random evolution process of the recovery rate is described by using the ITO process.Based on the dynamics model of recycling, three Stackelberg stochastic differential game models of CLSC are established: the government does not impose RPM, the government imposes RPM on the manufacturer as well as the government imposes RPM on both the manufacturer and the retailer.By using stochastic differential game theory, the partial differential equations which the optimal profit function should be satisfied are given.Furthermore, the optimal profit function and equilibrium strategy value of members of CLSC are obtained and compared. In order to further study the effect of RPM on equilibrium strategy and to reveal the stochastic evolution nature of recovery of Waste Electrical and Electronic Equipment(WEEE). By numerical example, the steady-state analysis and unsteady-state analysis of closed-loop supply chain system are carried out. The results show that the RPMcan encourage manufacturers to make more recycling efforts and thus increase the recycling rate,but it can not mitigate the double marginal effects. Compared with the retailers sharing the responsibility of recycling, the RPM imposed on the manufacturer is more beneficial to the CLSC, which can bring about both economic and environmental benefits.

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    Research on Supply Disruption of Epidemic Prevention Products Considering Product Competition and Social Learning under COVID-19
    Song Shi,Ping Shi
    2024, 32 (5):  171-178.  doi: 10.16381/j.cnki.issn1003-207x.2021.1147
    Abstract ( 24 )   HTML ( 0 )   PDF (856KB) ( 11 )   Save

    In the context of major public health emergency, in view of the existence of two competing medical protection products with different protection levels in the market, a game model is constructed to study the impact of consumers' social learning on supply chain decisions based on the interruption of product supply and the prior probability of consumer shortages. In order to characterize the demand function under social learning and product supply interruption, consumers are divided into two batches in the first sales cycle. When consumers have social learning behaviors, the second batch of consumers decide whether to buy higher protection level products based on the posterior probability of out-of-stock, which is formed by the prior probability of out-of-stock and the purchase strategy of the first batch of consumers, and the probability of supply interruption. If consumers do not have social learning, the first and second batch of consumers make decision both rely on their prior probability of stock-out and the probability of supply interruption. Research results show that: Consumers will choose to buy more products with higher protection level when they have a higher priori probability of being out-of-stock, and consumer demand also affected by the intensity of consumer social learning and the price difference between the two products. For retailers, when the product price difference is large, social learning will not affect the order quantity of higher protection level product in first sales cycle, and when the product price difference is small, the product order quantity will affect by social learning. Regardless of size of inventory capacity, when product price difference is too large or too small, social learning will not increase the profit of the supply chain, when price difference is at a moderate level, social learning can improve the supply chain profit. Finally, a numerical simulation example is used to analyze and verify the research results, and it could show the research conclusions more intuitively. The research in this paper has a certain theoretical guidance and practical reference for the supply and ordering of competitive epidemic prevention products under the background of the epidemic.

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    The Joint Impact of Time-of-use Pricing and Power Output on Solar Photovoltaic Investment for Manufacturing Firm
    Lumiao Li,Peng Zhou,Zhengjun Li,Jiageng Liu
    2024, 32 (5):  179-186.  doi: 10.16381/j.cnki.issn1003-207x.2021.0486
    Abstract ( 23 )   HTML ( 5 )   PDF (787KB) ( 12 )   Save

    Distributed solar photovoltaic (PV) investment has been a promising choice for manufacturing firms to realize its energy consumption transition, while the interplay between time-of-use (TOU) electricity pricing scheme and PV power output post uncertainties to the firm’s generation value. An optimal solar PV investment capacity is determined by developing an electricity cost minimization model for a manufacturing firm and studying the synergy or complementary effect between TOU electricity pricing and power output on firm’s solar PV investment. It is found that a higher synergy will lead to a greater firm’s solar PV investment. While the PV power output exhibits a synergy with TOU electricity pricing, the synergy increases in the level of TOU electricity pricing, which will both incentive firm’s solar PV investment. In contrast, the impact of increasing or decreasing the level of TOU electricity pricing on firm’s solar PV investment is two-sided, including positive and negative effects. Our results suggest that the policy maker can take advantage of the fluctuations in TOU electricity pricing and PV power output to incentive distributed solar PV investment.

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    Research on Emergency Evacuation and Material Allocation Based on Deprivation Cost
    Ling Zhang,Pengfei Gao,Lin Zhang
    2024, 32 (5):  187-195.  doi: 10.16381/j.cnki.issn1003-207x.2021.0698
    Abstract ( 31 )   HTML ( 0 )   PDF (641KB) ( 17 )   Save

    In the early stage of large-scale disaster relief, the untimely supply and uneven distribution of emergency supplies will cause certain negative psychological emotions among the victims, which, if not eliminated in time, will most likely lead to irrational behavior of the victims and affect the development and efficiency of the relief work.To address the problem, deprivation cost is introduced into post-disaster emergency management research, comprehensively considering the negative psychological emotions of disaster victims due to material scarcity and uneven distribution. The absolute deprivation cost function is constructed to quantify the sensitivity of the victims to the demand and arrival time of supplies, and to measure the negative psychological emotions caused by the lack of supplies. The relative deprivation cost function is constructed by referring to the Gini coefficient in economics to measure the difference in the negative psychological emotions suffered by the victims in different shelters, and to measure the negative psychological emotions such as imbalance and jealousy caused by the comparison of the victims. The total deprivation cost is also used to characterize the fairness of emergency supplies allocation.Based on the effective portrayal of the negative psychological emotions of the victims, an integrated optimization model for emergency evacuation, temporary shelter location and emergency material allocation is constructed with the objective of minimizing the total cost of rescue, and a stage-by-stage decoding genetic algorithm is designed to solve the model. In the verification stage, the effectiveness of the model and algorithm is verified by constructing a case study in combination with the disaster relief scenario after super typhoon hit Guangdong Province. The results of the analysis show that the timing of post-disaster rescue operations has a significant impact on the location of temporary shelters, emergency evacuation of victims, and emergency material distribution activities. Under the scenario where the rescue time is determined, improving the fairness of emergency supplies distribution can reduce the negative psychological emotions of the victims and improve the rescue efficiency. The relevant findings can provide useful references for post-disaster emergency management.

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    Evolutionary Game Analysis of Government and Enterprises Carbon-reduction under the Driven of Carbon Trading
    Guochang Fang,Yu He,Lixin Tian
    2024, 32 (5):  196-206.  doi: 10.16381/j.cnki.issn1003-207x.2021.1401
    Abstract ( 33 )   HTML ( 3 )   PDF (872KB) ( 27 )   Save

    Carbon trading, as one of the most efficient market means in emission reduction policy, has a profound impact on enterprise carbon-reduction. Based on system dynamic theory, within the constraints of public willingness, an evolutionary game model of government and enterprise carbon-reduction is constructed under the driven of carbon trading. Taking Hubei Province as an example, through the visual analysis of government and enterprise behavior, possible game situations between government and enterprises in the development of carbon trading are discussed, and the corresponding strategies are given. The results show that there are several different game results in the development of carbon market. For the game equilibrium of (action, carbon-reduction), it is necessary to encourage enterprises to take emission reduction measures and prolong the "window period" of carbon reduction. Adopting the strategies of dynamic punishment and dynamic subsidy can eliminate the periodic behavior pattern in the game between government and enterprises. By reducing carbon emission and regulating carbon price, the strategy combination can be changed from (inaction, no reduction) to (action, carbon-reduction). The proportion of the latter combination should be increased. The initial willingness is very important in the game between government and enterprises. The higher initial willingness is more conducive to achieve (action, carbon-reduction) strategy combination. The conclusions have strong implications for enterprise carbon reduction strategies and government action in the process of carbon trading, and provide a reference for the development of carbon market.

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    Computational Experiment on the Evolution of Social Group Behavior in Major Public Health Emergencies: A Case Study of COVID-19 Epidemic
    Xingang Zhao,Ying Zhou
    2024, 32 (5):  207-217.  doi: 10.16381/j.cnki.issn1003-207x.2021.1002
    Abstract ( 25 )   HTML ( 1 )   PDF (1333KB) ( 7 )   Save

    Scientific understanding of social group behavior and its evolution in major public health emergencies is the key way to improve the government's social governance ability. Firstly, a cellular automata (CA) model for the evolution of group behavior is constructed by describing the state, behaviors and evolution rules of different groups under the COVID-19 epidemic. Secondly, the evolution of group behavior under different scenarios is simulated by using the computational experimental method. Finally, according to the simulation results, the corresponding social governance countermeasures are put forward. The results indicated that: In view of the scientific social governance of the evolution of group behavior in the transmission of COVID-19, the spread of the epidemic can be effectively controlled. The main factors affecting the evolution of group behavior include initial infection rate, infection rate, incubation period and public opinion. Among them, the initial infection rate, infection rate and public opinion have a significant impact on the evolution of group behavior, while the effect of incubation period on the evolution of group behavior is not significant. Reducing the initial infection rate and infection rate can directly reduce the number of infected people, encourage individuals to take positive behavior, and guide the evolution of group behavior to positive behavior. If the management of public opinion is improper and most individuals take zero or negative behaviors, negative group behaviors will emerge in the social system, and almost all the society will be infected, which will increase the difficulty of social governance, and vice versa.Therefore, scientifically guiding the behavior of social groups and strengthening the social governance capacity of the government are important ways to effectively control the spread of COVID-19.

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    Coordinated Optimization of Joint Replenishment and Delivery Scheduling with Heterogenous Items Based on Lipschitz Continuity
    Sirui Wang,Lin Wang,Lu Peng,Jinlong Zhang
    2024, 32 (5):  218-228.  doi: 10.16381/j.cnki.issn1003-207x.2021.1101
    Abstract ( 26 )   HTML ( 0 )   PDF (881KB) ( 11 )   Save

    In the context of global procurement, the fixed ordering costs involved in the procurement process, such as service charges, telecommunications costs, travel expenses of staff, intermediary costs for purchasing through agents, and shipping costs for international purchasing, have increased dramatically. Under such circumstances, the jointreplenishment (JR)policy is a highly effective cost-control measure, which not only decreases the fixed ordering cost but also procures a large order and achieves economies of scale. When a group of goods are supplied by the same supplier or are transported by the same freighter, JR policy can achieve the scale effect of purchasing and shipping by sharing the fixed transportation cost.Joint replenishment system, as a typical multi-item inventory system, also have some disadvantages. The heterogeneity of items is an in-negligible issue, in particular when there is a variety of items. Such heterogeneity may be caused by various reasons. For example, cold-chain transportation costs may be shared by items when fresh food and normal products are transported together; some chemical products may corrode other objects, and thus additional packaging costs can be charged in this case; joint transportation of bulky cargos and heavy cargos can lead to damage to bulky cargos.This heterogeneity often leads to additional logistics costs or unnecessary administrative difficulties. Although heterogeneous items are very important in joint replenishment system, researches about this consideration is very scarce. Moreover, the basic joint replenishment problem disregards the coordinated scheduling occurred in the delivery stage, which makes it very limited to be applied. In order to fill the above research gaps. The coordinated optimization of joint replenishment and delivery scheduling with heterogenous items (JRD-HI) is considered.The problem is formulated as a mixed integer nonlinear program. Since it has been proven strongly NP-hard, our problem at hand is very difficult to solve.Conventional methods for mathematical programming are basically inapplicable to JRD-HI.In addition, exact algorithms for this problem are very rare, and only problems of modest scale can be accurately solved. By analyzing mathematical properties of the model, a series of conclusions of optimal solutionsare obtained, including the Lipschitz continuity of the objective function, which gives rise to a new idea of solution algorithm. The new method adopts a dynamic-step-size policy to search on the continuous decision variable, while existing methods are all based on the search on integer decision variables. In an experiment of 400 randomized instances, our new algorithm shows competent performance: the optimality gap is below 0.5% averagely and the average running time is below 4 seconds. Compared to existing algorithms, the improvement on objective value can reach 11% to 26%. Furthermore, some managerial insights are found via a sensitivity analysis on the coordination effect of delivery coordination. It is found that the coordinated optimization of replenishment and delivery can achieve 8.83% cost savings in a practical instance.The reason for the cost savings mainly comes from two respects: (a) the replenishment and delivery scheduling are more coordinated; (b) the central warehouse have more cost advantage. One interesting finding we view as making important managerial implication is the boundary of coordinated delivery; It is found that coordinated delivery policy is necessary only if the inventory management level of the central warehouse is remarkably superior to that of retailers.Otherwise, coordinated optimization of replenishment and delivery cannot achieve effective cost savings. This result can be agood guide for a company's investment plan when applying the JRD model. Equipment and human resource of the central warehouse should be ensured preferentially. One should invest in warehouses first and then in retailers.

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    The Influence Mechanism of OFDI on Industrial Green Total Factor Productivity Based on the Two-Stage Super-SBM-Malmquist Exponential Module
    Chen Shen,Yaru Xin,Nisha Jia,Rui Feng
    2024, 32 (5):  229-240.  doi: 10.16381/j.cnki.issn1003-207x.2021.1620
    Abstract ( 25 )   HTML ( 0 )   PDF (925KB) ( 11 )   Save

    China's Outward Foreign Direct Investment (OFDI) plays a pivotal role in promoting the deep integration of the Chinese economy and the world economy,and forming a new pattern of domestic and international dual-cycle development. Based on the panel data of 30 regions in China from 2005 to 2017, the two-stage Super-SBM network DEA model of undesired output and the global ML productivity index are used to calculate the industrial green total factor productivity, production efficiency and pollution abatement efficiency of each province in China, and examines, the impact of China’s OFDI on the three major efficiencies theoretically and empirically.It indicates that the influence of OFDI on the three efficiencies is shown as a robust U-shaped nonlinear relationship. From the perspective of the effect mechanism, in the short term, OFDI's inhibitory effect on the three efficiencies mainly due to the scale effect, while in the long term, OFDI's promotion of the three major efficiencies is mainly due to structural and technical effects. In the eastern and western region, there is a significant U-shaped relationship between OFDI and the three major efficiencies, but the effect of OFDI has not been found in the central region. The positive effect of OFDI in the identity of the "One Belt One Road" regions shows earlier than others.

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    Dynamic Incentive Contract of On-Demand Service Platform with Different Types of Agents under Asymmetric Information
    Zhongmiao Sun,Qi Xu,Yanfen Zhang
    2024, 32 (5):  241-253.  doi: 10.16381/j.cnki.issn1003-207x.2021.0562
    Abstract ( 20 )   HTML ( 0 )   PDF (1193KB) ( 14 )   Save

    In recent years, with the rapid development of platform economy, on-demand service platforms such as instant grocery delivery, meal delivery and ride-hailing have gradually become a part of daily life. The agents of these platforms may be part-time or full-time, they have the autonomy of service effort, and it is private information, the platform cannot directly observe the degree of the agent's effort. And, with the change of market environment, the operation and market position of platform enterprises are not static, but more dynamic and continuous, and the incentive contract of the platform to the agent is not invariable, but constantly changing under the influence of many external factors. In this paper, for the dynamic incentive contract problem of on-demand platform with both part-time and full-time agents under asymmetric information, considering the participation constraints and incentive compatibility constraints of agents, taking the change of platform service goodwill as the state variable, the dynamic incentive contract models of platform employing part-time, full-time and simultaneous agents are constructed respectively by using principal-agent theory, the optimal control method is used to solve the equilibrium strategy of platform and agent under different situations, the effects of service cost, information asymmetry, platform service goodwill and other related parameters are revealed, and the optimal decisions under different principal-agent models are compared and analyzed. The results suggest that: (1) When the service cost coefficient and risk sensitivity coefficient of a certain type of agent increase, the service effort level of this type of agent in different situations will decrease, and the platform enterprise should reduce the incentive intensity to it, but the platform does not need to change the incentive intensity to another type of agent. (2) When the initial service goodwill of the platform is low, the optimal trajectory of the guarantee money and incentive contract charged by the platform to the part-time agent will first monotonically increase and then stabilize with the passage of time, while the fixed reward and the corresponding incentive contract provided by the platform to the full-time agent will monotonically decrease and then stabilize with the passage of time; However, when the initial service goodwill of the platform is high, the optimal trajectory of the variables related to part-time and full-time agents in the early stage is just opposite to that when the initial service goodwill is low. (3) When the platform changes from employing part-time or full-time agents to employing both types of agents at the same time, the service effort level of the agents will decrease, and the incentive intensity of the platform should be increased, but the guarantee money charged by the platform to the part-time agents and the fixed remuneration provided to the full-time agents should be strategically optimized and adjusted according to the service provider's sensitivity to the platform’s incentive contract. In addition, the optimal service effort of the platform under the three principal-agent modes are different. (4) Finally, the numerical simulation shows that the platform is the most advantageous in the mode of entrusting part-time agents, while the profitability is the weakest in the mode of full-time agents, but it is the second best in the mode of entrusting two types of agents at the same time. The results provide good insights for on-demand platforms in the design of incentive contracts.

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    Asymmetric Effects of Infectious Diseases-related Uncertainty on the Volatility of Commodity Futures
    Wenhua Yu,Xiangyang Ren,Kun Yang,Yu Wei
    2024, 32 (5):  254-264.  doi: 10.16381/j.cnki.issn1003-207x.2021.0747
    Abstract ( 21 )   HTML ( 0 )   PDF (1141KB) ( 11 )   Save

    The spread of COVID-19 has caused great pressures on the economic development of various countries and the stability of financial markets. In this context, the quantitative analysis for the impact of infectious diseases-related uncertainty information on the volatility of commodity futures is not only helpful to avoid investment risks, but also conducive to the stability of economic production and people’s lives. A novel nonparametric causality-in-quantiles test method is employed to analyze the asymmetric effects of infectious diseases-related uncertainty on the volatility of commodity futures, from two perspectives of different conditional distributions and good and bad volatility. Combined with the rolling time window technique, the dynamic evolution of their causal relationships before and after the COVID-19 pandemic is further discussed.The empirical results manifest that, infectious diseases-related uncertainty has significant causal effects on the volatility of commodity futures. Meanwhile, their causal relationships show obvious asymmetric features. For example, these commodity futures markets response more strongly to infectious diseases-related uncertainty during their medium volatility period. The bad volatility of oil, copper, soybeans and lean hog futures is more easily driven by infectious diseases-related uncertainty than their good volatility, while the gold futures is just the opposite. Furthermore, the dynamic causal analysis based on the rolling time window technique not only verifies the robustness of above-mentioned findings, but also shows that the outbreak of COVID-19 significantly enhances the impacts of infectious diseases-related uncertainty on the overall volatility of crude oil, copper and gold futures, as well as the asymmetries between the good and bad volatility the four commodity futures other than lean hog futures.

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    Heterogeneous Network Games with Multiple Activities
    Yifan Xiong
    2024, 32 (5):  265-274.  doi: 10.16381/j.cnki.issn1003-207x.2021.0299
    Abstract ( 18 )   HTML ( 0 )   PDF (1049KB) ( 15 )   Save

    In many economic settings, who interacts with whom matters. More and more work needs the cooperation of the population. The mutual influence between people forms complex social networks. In recent years, how social networks influence individuals’ behavior has become a hot topic in economics research. The traditional literature on social network analysis mainly considers a single social network of the population. However, people often have different partners when faced with various activities. For example, college teachers must engage both in scientific research and complete teaching tasks. The output of scientific research is closely related to their collaborators’ input, and the efforts of their colleagues in teaching have a significant impact on the quality of education. In general, collaborators in research and teaching are different, which implies teachers in a college have different social ties in these two tasks. A heterogeneous network game model with multiple activities and characterizes the existence condition of the Nash equilibrium is constructed. Two applications of the model are also provided to enhance the economic implications. The first is the pricing problem for customers who gain network externalities from their neighbors who consume the same products. Compared to previous studies, it is assumed that consumers’ network externalities on different products are heterogeneous. The second is the resource allocation problem among agents with varying cooperation relationships in multiple tasks. Each agent’s marginal output depends on how many resources she obtained. The planner could design a resource allocation scheme to induce agents to exert the maximum total effort. Specifically, the content of this article is structured as follows: A model where players have heterogeneous social network relationships on different tasks is firstly built. Referring to the study of Bramoulé et al. (2014), which connects the network game and the potential function, the maximum condition of the potential function is used to characterize the existence and uniqueness of the Nash equilibrium. This condition is closely related to the smallest eigenvalue of the technology matrix and the largest eigenvalue of the network matrix. Next, I focus on the uniqueness and the existence of the equilibrium. Under some assumptions of the maximum eigenvalue of network matrices, the equilibrium can be expressed in a closed form. Then comparative static analyses of the exogenous parameters of the game is made. Finally, two applications of the theoretical model are provided. In the pricing problem, it is revealed that the optimal monopoly price for each product is half of the customer’s marginal propensity to consume, and the equilibrium oligopoly prices are proportional to a weighted summation of all customers’ marginal consumption propensity. In the resource allocation problem, the planner and agents play a two-stage game. The planner first decides how to allocate resources for different tasks, and each agent then simultaneously selects the effort investment in each task. By backward induction, the planner should allocate resources to agents according to their inter-centrality measure in the network.

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    Impact of Marketing Capability and Production Operation Capability on Firms' Financial Performance
    Guangyu Wan,Feiyan Pu,Zichun Li,Yu Cao
    2024, 32 (5):  275-285.  doi: 10.16381/j.cnki.issn1003-207x.2021.0478
    Abstract ( 24 )   HTML ( 3 )   PDF (889KB) ( 24 )   Save

    The resource-based view and process view of the organization believe that the competitive advantage of a firm in the market depends on its unique resources and capabilities, which results in performance differences. Marketing capability and operational capability are two essential functions that create value for firms. The former means the ability to create customer demand and marketing revenue, and the latter means the ability to produce supply and meet market demand. The two are measured by calculating the input and output efficiency of the sales process and production operation, respectively. Data Envelopment Analysis (DEA) is used to measure the operational capability and the marketing capability of 1,937 listed companies in the manufacturing and retailing industries from 2013 to 2018. It uses econometric models to empirically study the relationship between the two and how they affect firm performance. The moderating effect of market demand uncertainty is also discussed. Firstly, the two capabilities significantly positively impact firm performance, but the marketing capability has a more substantial positive impact. Interestingly, the intermediary effect is verified, indicating that the marketing capability indirectly improves firm performance by driving the improvement of operational capability. Nevertheless, excessive operational capability has an inhibitory and regulatory effect on the positive relationship between marketing capability and firm performance. Finally, market demand uncertainty positively regulates the relationship between the two capabilities and firm performance. That is, the two capabilities contribute more to firm performance when the market environment displays a fluctuation. The research conclusions of this paper provide references for the resource allocation and the functional improvement of business managers in formulating market competition strategies.

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    Research on Optimal Decision of Supply Chain Customer Order Decoupling Point on Digital Advance Demand Information
    Hua Song,Xiaoye Yang,Jianyu Luo
    2024, 32 (5):  286-296.  doi: 10.16381/j.cnki.issn1003-207x.2021.0853
    Abstract ( 16 )   HTML ( 1 )   PDF (1177KB) ( 7 )   Save

    As one of the digital technologies that are gradually concerned by the industry, the digital platform Advance Demand Information system (DADI) has a positive impact on the operation optimization of the supply chain. The advance demand information collection function transforms the traditional inventory / order push-pull mode into the inventory /advance push-pull mode. By obtaining customer commitment lead time, it shortens the waiting time of customers, reduces the mismatch between supply and demand, and changes the position decision-making mode of traditional supply chain decoupling point. At the same time, the digital platform enterprises promote the rapid sharing of order demand information in the terminal market, and avoid the time lag and long tail effect of information feedback layer by layer to the upstream. Therefore, the mechanism of decision making of customer order decoupling point in supply chain optimization of DADI system is explored. Firstly, the mechanism is deduced that commitment lead time and inventory depend on each other and jointly affect the enterprise's profit. Secondly, the commitment lead time cost threshold is calculated. The threshold not only affects the supplier's choice of appointment driven or inventory driven strategy, but also affects the decoupling point position of the supply chain. Thirdly, the influence of unit inventory holding cost, delayed order cost, customer demand uncertainty and other factors on the decoupling point position is deduced. Fourth, the difference of the profit and CODP position of the supply chain is compared under the DADI system, ADI system and traditional model. Finally, sensitivity analysis of the relatively important factors is also conducted, and numerical example is carried out to demonstrate the correctness of the conclusion.

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    Cooperation Modes and Decision Optimization in Live Streaming Commerce
    Yongwei Cheng
    2024, 32 (5):  297-306.  doi: 10.16381/j.cnki.issn1003-207x.2022.2589
    Abstract ( 30 )   HTML ( 2 )   PDF (1271KB) ( 32 )   Save

    In recent years, as a distinctive emerging business form in the field of China's digital economy, the live streaming commerce has developed vigorously. Especially in the post-epidemic era, it will play an important role in solving a large number of social flexible employment and even reshaping e-commerce consumption behavior in China. Many well-known companies such as Gree Electric Appliances and Unilever have entered the live streaming market through self-operated live streaming or cooperative live streaming. However, with the diversification of participants in the live streaming, chaos emerges endlessly. Merchants, anchors, and live streaming platforms have suffered a lot of disputes and even resorted to law around price discounts, commission rates, pit fees, platform commissions, marketing and promotion expenses, etc. These phenomena essentially belong to the cooperation or contract governance issues of live streaming commerce.The motivation of this study is (1) What are the main cooperation modes or contract paradigms between merchants and anchors in live streaming? (2) How do they choose an efficient cooperation mode based on actual business scenarios? Are these cooperation modes short-term or long-term stable? (3) In their cooperation, how to determine important decision-making variables such as price discount rate, commission rate, and promotional expenses? How will these variables affect the sales and benefits of live streaming? (4) Can consumers really benefit from these cooperation? Thus, the cooperation modes and decision optimization of anchors and merchants are investigated in live streaming commerce. First, three sequential game modes are developed in which the commission rate is determined by the live streaming market and the commission rate is negotiated by both parties. Second, a new live streaming sales function is designed by introducing live streaming popularity value, price discount rate and live streaming conversion rate. Third, both parties’ optimal strategies, consumer welfare, competitive equilibrium and cooperation stability are examined under different cooperation modes.The results demonstrate that (1) When the commission rate is determined by the live streaming market, the two parties cannot reach a cooperation equilibrium under the six cooperation modes, and it is difficult to achieve long-term cooperation through profit sharing or cost sharing contracts. However, the introduction of a commission rate negotiation mechanism can improve the benefits of live streaming. (2) The current cooperation mode of “merchant decides the price discount rate, and the anchor is responsible for the conversion rate of live streaming” is actually a “prisoner's dilemma” cooperation mode with the lowest live streaming sales. "Just-needed" products or products with low profit margins that consumers are less price-sensitive are not suitable for live streaming commerce. When the market commission rate is high, it is the best cooperation mode for a strong "head" anchor to lead the live streaming. (3) The fixed fee for live streaming does not have a substantial impact on both parties’ selection of cooperation strategies, and there is always a strong “collusive” motive for anchors and merchants to make profits by falsely bidding on the market price (original price) of commodities and formulating high price discount rates. This study contributes to the governance and operation optimization of live streaming market.

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    Corporate Environmental Investment Behavior and Cooperation Evolution Considering Centralized Sanction and Reference Dependence
    Yuling Liao,Siyin Lei,Meizhe Song,Lining Zeng,Wenkang Deng,Daofu Hu
    2024, 32 (5):  307-314.  doi: 10.16381/j.cnki.issn1003-207x.2021.0816
    Abstract ( 19 )   HTML ( 1 )   PDF (665KB) ( 20 )   Save

    As important participants of society, enterprises should take responsibility of investing in the public environment production. However, the enterprises may be non-cooperative during the investment due to the public attributes of environmental resources and the externality characteristics of environmental investment, which may lead to the undercapitalization, and thus the cooperation would get to the collective action dilemma.Based on the perspective of combining centralized punishment and reference dependence, an evolutionary game model of enterprise environmental investment cooperation is constructed, and different application scenarios of cooperation invest are simulated that with/without the influence factors of reference dependence strategy interaction rules, centralized punishment mechanism, different penalties, etc. Then, by the statistical testing methods, the impact of centralized punishment and enterprise reference dependence strategy interaction on enterprise environmental investment cooperation is analyzed under different penalties.It is found that (1) With appropriate penalties, the centralized punishment mechanism can improve the level of enterprise environmental investment cooperation; (2) Under different penalties, there is a significant difference in the benefits of collective action in enterprise environmental investment cooperation. Under certain conditions, there is an optimal threshold for the penalty of enterprises, which can maximize the benefits of collective action; (3) When considering the incentive factors of punishment only, it is not enough to maintain enterprise environmental investment cooperation. More importantly, the formation of a benign strategic interaction based on reference dependence between enterprises can fully stimulate enterprises to actively participate in environmental investment cooperation actions. The above conclusions provide new ideas for improving the ecological environment.

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    Research on Pricing Strategy of Competitive E-commerce Platforms Considering Return Freight Insurance
    Jizhou Zhan,Yaqi Jin
    2024, 32 (5):  325-334.  doi: 10.16381/j.cnki.issn1003-207x.2021.1736
    Abstract ( 29 )   HTML ( 5 )   PDF (1464KB) ( 32 )   Save

    In recent years, more and more E-commerce platforms have cooperated with insurance companies to carry out return freight insurance services to solve return freight disputes, which are divided into buyer's version and retailer's version. For different types of return freight insurance, insurance companies charge different premiums, which will directly affect the pricing strategy of E-commerce platform. Based on two-sided market theory, the impact of different return freight insurance schemes on the pricing strategy of the competitive E-commerce platform is studied. The research questions are: (1) What is the impact of different return freight insurance schemes (SS, CC and SC cases) on the equilibrium pricing, market share and revenue of the E-commerce platform? (2)Which return freight insurance scheme does the E-commerce platform should adopt to obtain a higher income?The Hotelling model is utilized to describe the utilities of sellers and buyers, as well as the insurance company and platform during the transactions. The optimal premium of return freight insurance of insurance company and optimal registration fee of platform are given under different return freight insurance schemes. Comparing the operational policies and profits of each member, the results are: (1) When the two platforms have great differences, the registration costs that sellers should pay for two platforms are consistent under the case of CC, the platform with lower average return probability charge higher registration fee under the case of SS, and platform charges higher registration fee when buyer pays the premium under the case of SC. (2)When the two platforms exist complete competition and have the same return probabilities, the balanced quantity proportions of sellers or buyers in the competitive platforms are consistent under SS case and CC case, and the premium charged by insurance company is higher under SS case and CC case.

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