Table of Content

25 September 2025, Volume 33 Issue 9 Previous Issue   

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Informed Trading in Stock Market and Credit Spreads in Bond Market Yanyi Ye, Xiaoguang Yang 2025, 33 (9):  1-10.  doi: 10.16381/j.cnki.issn1003-207x.2022.2798 Abstract ( 38 )   HTML ( 0 )   PDF (564KB) ( 22 )   Save Informed trading in the stock market reflects the extent of information leakage of corresponding enterprises. For Chinese interbank bond market， which is dominated by institutional investors， an interesting question is whether and how informed trading in the stock market affects the pricing of corporate bonds. In this paper， it aims to examine the impact of informed trading in the stock market on corporate bond yield spreads and its transmission mechanism. Informed trading refers to the informed traders taking their information advantages to make trades and earn higher returns. It is proposed that uninformed traders holding bonds with more informed trading， require the higher risk compensation because uninformed trades face the risks of losing to informed trades. Liquidity is related to how informed trading gets incorporated into corporate bond prices. With the decrease of liquidity， it is more difficult for uninformed traders who stick to the market to obtain information through order flow， which damages the interests of these uninformed traders， so they require higher risk compensation. With the regression analysis and moderation and mediation effects test methods， these hypotheses are empirically tested based on two datasets of secondary market transactions of stocks and corporate bonds issued by Chinese listed firms from May 1， 2014， to December 31， 2020. In the regression analysis， it is found that the credit spreads increase as the informed trading in the stock market increases. It is found informed trading in the stock market affects corporate bond spread through a bond illiquidity channel. It is also found that the effect of informed trading in the stock market on credit spreads is exacerbated by higher bond illiquidity. Further evidence shows that the informed trading in the stock market effect is stronger for non-SOE firms， firms with higher information asymmetry， and firms with higher leverage. Moreover， our results remain robust to alternative measures of credit spread， informed trading； to the alternative samples；and to potential endogeneity bias. Three major contributions are made. Firstly， the significant impact of informed trading on the pricing of Chinese interbank credit bonds is confirmed， which reveals the interlinkages between markets through information transmission. Secondly， the channel role of illiquidity in the pricing of informed trading is illustrated and it helps to understand the underlying mechanism of the pricing impact of informed trading. Finally， the findings of this paper are helpful for both investors and regulatory authorities in their decision-making. Figures and Tables | References | Related Articles | Metrics

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Research on the Effect of Platform Horizontal Merger Considering Congestion Effect and Merger Type Qian Chen 2025, 33 (9):  11-21.  doi: 10.16381/j.cnki.issn1003-207x.2022.2598 Abstract ( 33 )   HTML ( 0 )   PDF (905KB) ( 7 )   Save In recent years， with the rapid development of the platform economy， the wave of mergers in the field of platforms has been widely concerned. Platforms such as those in ride hailing market and group buying market have been merged horizontally to make market structure more concentrated. There are two merge types in real cases. One is to keep the original two brands operating separately and the other is to retain one brand. Motivated by the observation， how the changes of merge type affect the economic effects of platform horizontal merger is investigated.In the two-sided markets， sellers are strongly affected by congestion effect besides positive indirect network effect. Fierce competition or conflicts among sellers within the same platform leads to reducing the willingness of sellers to access the platform， which is referred to as congestion effect. According to previous literature， most of the theoretical studies on the economic effects of platform horizontal merger focus on the impact of indirect network effect while how congestion effect affect these economic effects including price effects， profit effects and welfare effects is not clear. Introducing congestion effect among sellers， a Salop circular market model is developed for merger analysis. The effect of congestion effect on economic effects of platform horizontal merger under different merger types is analyzed. The following results are obtained.First， when only one brand is retained after merger， if congestion effect is strong and indirect network effect is weak， the pressure to reduce price is small and profit of platforms involved in the merger will be improved. When two brands are retained after merger， prices on the seller side will always increase and profit of platforms in the market will always be improved. If indirect network effect is strong， the pressure to reduce price on the buyer side is greater. Furthermore， the endogenous choice of merger type is determined by congestion effect and indirect network effect. In general， if congestion effect is strong， platforms tend to retain one brand. If indirect network effect is strong， platforms tend to retain two brands.Second， welfare analysis shows that indirect network effect improves welfare after merger while congestion effect tends to reduce welfare. From the perspective of sellers， welfare will always be reduced when two brands are retained after merger and horizontal merger of platforms may have a positive impact on welfare if indirect network effect is strong and congestion effect is weak when one brand is retained. From the perspective of buyers， if the indirect network effect is strong， buyers will be better after merger under both merger types. From the perspective of social efficiency， horizontal merger of platforms may have a positive impact on total social welfare if indirect network effect is strong and congestion effect is weak under both merger types. In addition， if the indirect network effect is strong enough， either the congestion effect is strong， or the congestion effect is small， but the indirect network effect is not particularly strong， the "see-saw" effect of improving welfare of buyers and reducing welfare of sellers will appear under both two merger types.Third， after extending the merger analysis to the network integration of platform horizontal merger， relevant result shows that network integration strengthens the impact of congestion effect and indirect network effect， and the greater the degree of network integration is， the more inclined the platform is to reduce prices after merger on both sides. Figures and Tables | References | Related Articles | Metrics

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Information Acquisition in Secondary Market and Convertible Bond Financing Liu Gan, Yingli Cai, Mingyu Xu, Yingxian Tan 2025, 33 (9):  22-32.  doi: 10.16381/j.cnki.issn1003-207x.2023.0387 Abstract ( 26 )   HTML ( 0 )   PDF (1078KB) ( 2 )   Save In 2017， the China Securities Regulatory Commission provided a richer path for companies to flexibly use different bond financing tools to seek innovative development. It revised its refinancing policy to encourage listed companies to use convertible bonds， a composite bond financing tool， to improve their capital structure. In recent years， the convertible bond market has been constantly developing and the market size continues to grow， which improve and enrich the research in the field of convertible bond financing to create the prerequisites. Although the convertible bond market is in a state of continuous development and is an enrichment of corporate financing tools with policy support， there are also unfavorable factors such as insufficient liquidity and imperfect price discovery function in the secondary bond market. At present， the research on convertible bonds mostly focuses on how bond financing affects firms' business decisions under the friction of the secondary bond market. However， there is little literature to explore quantitative research on how the contractual terms of convertible bonds affect the liquidity and trading volume of the secondary bond market. Against the background， the information asymmetry of investors is modelled with respect to the recovery rate of firms in bankruptcy， taking into account factors such as insufficient liquidity in the secondary market. There are both high-quality companies and low-quality companies on the market， and the recovery rates of these companies in bankruptcy are different. At the same time， when selling bonds in the secondary market， convertible bondholders will need to engage in costly information-gathering and then construct the information-gathering strategy of convertible bondholders. Then， an equilibrium model is constructed and analytical expressions of the equilibrium pricing of corporate securities， the optimal bankruptcy time， the optimal conversion time， and the corporate financing strategy under the information asymmetry of the secondary bond market and the information acquisition of convertible bond holders are obtained. It is found that the higher conversion rate of convertibles increases the trading volume of lower quality bonds in the secondary market， while reducing liquidity. As the cost of information acquisition increases， the optimal leverage of the company will show a U-shape. The research of this paper enriches the theory for the financing of convertible bonds and provides a useful reference for the corporate governance. Figures and Tables | References | Related Articles | Metrics

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Tail Risk Contagion Research on Cryptocurrencies and Global Stock Markets Xiaoli Gong, Kaiwen Jia, Xiong Xiong 2025, 33 (9):  33-45.  doi: 10.16381/j.cnki.issn1003-207x.2023.0889 Abstract ( 30 )   HTML ( 0 )   PDF (3723KB) ( 13 )   Save Cryptocurrency market is an independent emerging financial market whose intrinsic value is difficult to accurately estimate. Cryptocurrency prices are largely influenced by investor sentiment and will fluctuate wildly when major emergencies occur. In the context of financial market integration and investor homogeneity， the risk contagion effect between the cryptocurrency market and traditional financial markets is significant. The cross-contagion characteristics of tail risks between cryptocurrencies and the global stock market under different market conditions and time periods are different. Besides， it needs to be studied from both the time domain and frequency domain perspectives.By combining the quantile vector autoregression （QVAR） model with the frequency domain perspective， the quantile time-frequency risk spillover model can be used to study this issue. First， the EGARCH model using leptokurtosis and thick tail distribution is used to fit the fluctuations of cryptocurrency and global stock markets. On this basis， wavelet coherence is used to examine the relationship between cryptocurrency and the stock market of major economies in different time and frequency domains. Finally， the tail risk spillover network between cryptocurrencies and global stock markets is constructed. By analyzing the changes in tail risk spillover effects based on different quantiles in the time-frequency domain， the tail risk contagion characteristics of cryptocurrencies and global stock markets are studied. All sample data comes from the Investing.com.It is found that the spillover index based on the quantile measure can better capture the tail risk spillover effects of cryptocurrencies and global stock markets under different impact sizes， while the traditional spillover index based on the conditional mean measure will underestimate the true tail risk spillover level. Under extreme conditions， the tail risk spillover effect between cryptocurrencies and global stock markets is significantly stronger than in normal conditions， and is obviously asymmetric. From the frequency domain perspective， the tail risk spillover between cryptocurrencies and global stock markets shows significant cyclical characteristics. In addition， cryptocurrencies are net risk bearers under normal conditions， but they have obvious net risk spillover effects when the market is subject to positive shocks.Different from the previous research， the innovative contributions of this article are mainly reflected in the following aspects： （1） After characterizing the leptokurtosis and thick tail characteristics of the return distribution of cryptocurrencies and global stock markets， wavelet analysis method is used to examine the dynamic changes in the fluctuation linkage between cryptocurrencies and the stock markets of major economies in the time domain and frequency domain； （2） Based on the dual dimensions of time domain and frequency domain， tail risk spillover networks between cryptocurrency and global stock markets are built， and the characteristics of tail risk spillover effects in different time domains and frequency domains are deeply analyzed； （3） The tail risk spillover index under the conditional mean is expanded through the quantile vector autoregressive model， and the tail risk spillover effects of cryptocurrencies and global stock markets under different shock scales are examined， revealing the asymmetry of the tail risk spillover effects between cryptocurrencies and global stock markets in extreme rising and falling states. By examining the cross-contagion characteristics of tail risks between cryptocurrencies and global stock markets under different market conditions and time periods， it will help regulatory authorities formulate， implement and improve cryptocurrency regulatory policies. Figures and Tables | References | Related Articles | Metrics

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Study on Optimal Portfolio Strategy from the Perspective of Multilayer Temporal Network Chao Liu, Lantao Xu 2025, 33 (9):  46-56.  doi: 10.16381/j.cnki.issn1003-207x.2023.0851 Abstract ( 25 )   HTML ( 0 )   PDF (1617KB) ( 3 )   Save Stocks of varying quality have put forward new requirements for investors’ investment research capabilities， especially for Chinese investors who are mainly natural persons （retail investors）. Since retail investors have weak risk tolerance and high degree of loss aversion， facing the increasing asset scale， how to obtain higher returns with the lowest possible risk is undoubtedly the issue that investors are most concerned about. The stock market is studied from the linear and nonlinear correlation and dynamic evolution characteristics between stock assets. First， it describes the stock market with multilayer temporal network， and designs network risk measurement indicators based on the eigenvectors centrality measure. Then Combining it with optimization theory， the Global Minimum Network-Risk portfolio model is proposed to simulate dynamic investment process based on the data of HS300 constituent stocks from 2010 to 2022， and then the portfolio model with a variety of evaluation indicators is evaluated.Experimental results are as follows （i）The multilayer temporal network can comprehensively ascertain the correlation structure and evolution characteristics of stock assets， accurately describe the structure of complex financial systems， and identify high-quality investment assets； （ii）The peripheral portfolio model can obtain better investment performance and cumulative return rate， and the return is not offset by systematic risk factor exposure； （iii）The peripheral Global Minimum Network-Risk portfolio model has the best investment performance during the out-of-sample period， and it still maintains strong robustness in stock market fluctuations， which is suitable for investors with low risk tolerance. Theoretical and practical references are provided for investors with different risk preferences especially for retail investors with low risk tolerance， the traditional mean-variance portfolio theory is expanded and improved based on multilayer temporal network， and further research in this field is enriched. Figures and Tables | References | Related Articles | Metrics

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High-dimensional Active PU Learning with Its Application to Credit Scoring Yongqin Qiu, Kuangnan Fang, Qingzhao Zhang, Lean Yu 2025, 33 (9):  57-66.  doi: 10.16381/j.cnki.issn1003-207x.2023.0483 Abstract ( 24 )   HTML ( 0 )   PDF (894KB) ( 4 )   Save In classification problems， there is a situation that only positive and unlabeled samples are available， i.e.， PU （positive and unlabeled） data. Most existing studies require class prior and sufficient sample size to achieve good results， and the model estimation results are often poor when the data is high-dimensional and small sample. For this purpose， a high-dimensional active PU learning model is propased. By adjusting the classical A-optimality criterion， it not only can effectively select new samples in high-dimensional cases and improve the model estimation， but also significantly reduces the time cost of sample selection. In addition， in the process of selecting and labeling samples， the proposed method can estimate the parameters of the class prior without initial value for parameter， reducing the bias caused by prior information errors. Through simulation experiments， it is found that the proposed method in this paper outperforms the comparative methods in variable selection， coefficient estimation and classification prediction. Furthermore， compared to the classical A-optimality criterion， the method achieves a substantial reduction in selection time. Finally， the model proposed in this paper is applied to the consumer finance loan credit score data. The results indicate that compared to randomly selecting samples for labeling， actively selecting samples can better enhance predictive performance， especially when the number of labels is limited， the improvement is more pronounced. Additionally， the approach is also more robust in the selection of important variables. The model developed in this paper can provide a powerful tool for credit risk analysis for newly launched credit products. Figures and Tables | References | Related Articles | Metrics

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Research on Manufacturer Production Strategies Considering Credit Discount Zhibing Lin, Yuwen Li, Mofan Chen 2025, 33 (9):  67-76.  doi: 10.16381/j.cnki.issn1003-207x.2022.2535 Abstract ( 33 )   HTML ( 0 )   PDF (622KB) ( 6 )   Save In this paper， a three-layer supply chain consisting of a manufacturer， a retailer and a payment platform has been considered. The Stackelberg game models under three production strategies （traditional production strategy， green production strategy and mixed production strategy） are established to analyze the impact of credit discount on the selection of manufacturer production strategies and promotion of green product. The results show that： （1） green consumer credit is not always beneficial to channel members， but the credit discount of the payment platform helps to mitigate the price disadvantage of green products. （2） When the interest-free period is short， the green production strategy is more beneficial to the promotion of green products， otherwise， the mixed production strategy has better promotion effects. （3） Credit discount helps the manufacturer to refuse the traditional production strategy. Specifically， when consumers are more sensitive to interest-free period and credit rates are low， the manufacturer prefers green production strategy， otherwise， the manufacturer prefers mixed production strategy. Finally， the model is extended to the case of the retailer's vertically integrated payment platform. The results show that， the vertically integrated of payment platform is beneficial to channel members， and after integration， both channel members prefer mixed production strategy. Figures and Tables | References | Related Articles | Metrics

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Adoption Decision on Ship-from-store Strategy for Dual-channel Retailers in the Context of Public Health Emergencies Ping Xie, Di Xu 2025, 33 (9):  77-88.  doi: 10.16381/j.cnki.issn1003-207x.2022.1854 Abstract ( 36 )   HTML ( 0 )   PDF (1360KB) ( 6 )   Save Influenced by public health emergencies， ship-from-store （SFS） has emerged as a pivotal strategy for the digital transformation of the retail industry. However， given the potential cannibalization and complementarity effects between sales channels， as well as the additional operational costs associated with SFS， the question of whether dual-channel retailers should adopt this strategy remains unresolved. Furthermore， as the status of epidemic prevention and control evolves， it is essential to examine how dual-channel retailers should adjust their SFS adoption decisions in response. To address these issues， game-theoretic models are developed to analyze the adoption of SFS by dual-channel retailers under different pandemic control scenarios. First， the scenario involving mandatory lockdown policies is examined. By solving and comparing equilibrium outcomes before and after SFS adoption， the conditions under which retailers should implement this strategy are identified. Second， the post-lockdown scenario is analyzed， deriving the retailer’s optimal decision once such restrictions are lifted. Finally， through a comparative analysis of equilibrium outcomes across both scenarios （i.e.， with and without lockdown policies）， the interplay between pandemic control status and SFS adoption is revealed. The main findings are as follows. First， under lockdown policies， SFS is viable only for retailers with low operating costs and high product valuations. Second， once lockdown policies are lifted， SFS benefits not only retailers with low operating costs and high valuations but also those with high operating costs and low valuations. Third， retailers should dynamically adjust their SFS adoption decisions in accordance with changes in pandemic control status， with different types of retailers following distinct transition paths. Finally， although lockdown policies consistently harm dual-channel retailers， those with low costs and high valuations can leverage SFS to mitigate or even fully counteract these negative effects. Figures and Tables | References | Related Articles | Metrics

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Determination of Optimal Endogenous Direction and Improvement Path in Directional Distance Function Lei Chen, Xu Guo, Yingming Wang 2025, 33 (9):  89-96.  doi: 10.16381/j.cnki.issn1003-207x.2022.1912 Abstract ( 29 )   HTML ( 0 )   PDF (1082KB) ( 5 )   Save Although the flexible direction determination is the most characteristic advantage of the direction distance function （DDF）， the different results caused by different directions have also become the technological difficulty， which is controversial. In view of this problem， the basic principles and limitations of the existing direction determination methods in DDF are analyzed， and shadow price is introduced to clarify a new endogenous direction setting mechanism. Secondly， the improvement space of each input/output element of the decision-making unit to the maximum extent is taken as the goal to construct the optimal shadow price determination model. Sequentially， a new method for determining the optimal endogenous direction and improvement path， N-DDF method， is constructed based on the shadow price. The new method can not only get rid of the dependence on exogenous data and determine direction completely by the endogenous method， but also overcome the limitation of traditional endogenous methods that lacking economic connotation. Through theoretical expansion， it can be found that the N-DDF method is not only applicable to the hypothesis of variable returns to scale， but also applicable to others different decision scenarios， such as the hypothesis of constant returns to scale and considering undesirable outputs. Finally， an example analysis is given to illustrate the effectiveness of the N-DDF method. Figures and Tables | References | Related Articles | Metrics

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An Affinely Adjustable Robust Optimization Model for Prouction-Inventory Planning Problem with Demand and Lead Time Uncertainties Mingli Yuan, Ruozhen Qiu, Yue Sun 2025, 33 (9):  97-108.  doi: 10.16381/j.cnki.issn1003-207x.2022.1692 Abstract ( 91 )   HTML ( 0 )   PDF (1837KB) ( 6 )   Save The rapid changes of supply chain environment make it difficult for firms to predict future demands or obtain a full knowledge of raw material supplies， resulting in low efficiency of production and operation. How to cope with market demand and raw material supply uncertainties and ensure ideal operational performance has become an urgent issue for firms.A production-inventory planning problem is explored for a three-stage supply chain consisting of a raw material supplier， a manufacturer， a third-party logistics company， and customers. The raw materials used to produce products are supplied and distributed by the supplier to the manufacturer. The output of each product is influenced by the inventory levels of raw materials， the production capacity and the market demands. The total production time is subject to maintenance， holidays and other factors. The end products are supplied by the manufacturer to the customers. In particular， any unsold products will be stored by the third-party logistics company. Considering demand and raw material lead time uncertainties， a multi-product multi-period production-inventory planning robust optimization model is developed by minimizing the total production-inventory cost with production capacity， quantities of raw materials， product inventories and logistics as constraints， and order quantities of raw materials， production time， number of orders signed by the manufacturers and the third-party logistics companies and lost sales as decision variables. Furthermore， an affinely adjustable robust optimization model is developed based on the realized demands. With the definitions of the uncertain sets to which the uncertain demands and the lead times belong， the proposed robust optimization models are transformed into tractable linear programming models by dual approach. Finally， numerical studies are conducted to verify the proposed models， especially to illustrate the effectiveness and advantages of the affinely adjustable robust optimization model in coping with demand and lead time uncertainties.The main findings reveal that the affinely adjustable robust optimization model outperforms the traditional static robust optimization model in terms of the total costs and operational decisions. The total production-planning costs under the two robust optimization methods increase with the increase of the demand and lead time uncertainties， indicating that decision-makers should strengthen the management of uncertainties in practice and reduce the uncertainty levels to reduce costs. Figures and Tables | References | Related Articles | Metrics

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Traffic Security Network Design and Resource Coordination Based on Network Interdiction Yin Xiang, Chenmei Teng, Xue Wang, Wenjing Zhang 2025, 33 (9):  109-120.  doi: 10.16381/j.cnki.issn1003-207x.2023.0357 Abstract ( 23 )   HTML ( 0 )   PDF (2103KB) ( 3 )   Save In recent years， with its rising international status， China has hosted an increasing number of major events （2008 Beijing Olympics， 2022 Beijing East Olympics， 2023 Hangzhou Asian Games） and conferences （2010 Shanghai World Expo， 2016 Hangzhou G20 Summit）. However， this also provides opportunities for various types of intruder （e.g. terrorist） who deliberately infiltrate the event sites and attempt to launch riots. In this context， during major events， how security agencies can reduce the intrusion probability of intruders through the design of traffic security network has become a significant research problem.Research on network interdiction problems provides theoretical and technical support for optimize the above problems.The network interdiction problem， usually based on leader-follower games， concerns how to monitor or halt adversary behaviors in a network.Although there have been an increasing number of studies on network interdiction problems in recent years， most of them provide solutions based on assumptions that fail to address real-life problems. Such assumptions include （1） only arcs can be interdicted， （2） interdiction is a binary decision， （3） the interdict effect is exogenous， and （4） resource sharing is not allowed.In this context， a novel network interdiction problem is presented， for which the nodal interdiction pattern is considered， the interdict variable is defined as an integer variable （representing the amount of interdict resources）， resource sharing between nodes is allowed， it is assumed that the interdict effect is no longer an exogenously given parameter but determined by the amount of resources on the node， and further the expansion of the situation such as multi-source and multi-sink nodes is considered， the defender （e.g. security agencies） dispatches both existing and new resources， and the intruder has some incomplete information. These problems are addressed as some novel defender–attacker bilevel models. The upper-level program belongs to the defender， who optimizes the resource-sharing strategy and improves the interdict effect of some critical nodes， whereas the lower-level program refers to the attacker who responds to find a maximal reliable path between a given pair of source and sink nodes. To solve the models， a hybrid method integrating ε-constraint and Benders decomposition is designed.Finally， numerical studies are carried out with the background of China-Eurasia Expo， and the results verify the effectiveness of the model and the algorithm. Figures and Tables | References | Related Articles | Metrics

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Research on the Evaluation of Multi-channel Online Advertising Combination Effects Based on Channel Click Path Li Li, Bingkun Cao, Zhenyi Yang 2025, 33 (9):  121-134.  doi: 10.16381/j.cnki.issn1003-207x.2022.0304 Abstract ( 26 )   HTML ( 0 )   PDF (937KB) ( 2 )   Save The rapid development of the Internet， mobile and social media has brought many new online advertising and marketing channels to e-commerce enterprises. Under the background of integrated marketing and multi-channel online advertising， users may not only contact the online advertising channels once before purchase， and the channels contacted successively will affect consumers jointly but not independently. Therefore， in the effectiveness study of multi-channel online advertising， it is also necessary to consider the multi-channel combination effect of online advertising.The click-stream data of this study comes from the third party insurance agency website in Nanjing. After extracting， cleaning and transforming， the basic variables of this study are obtained.To explore the combinatorial effect of multi-channel online advertising， according to the choice set theory， related research hypotheses based on the classified combination effects of online advertising channels are proposed， and then the COX model is constructed. Based on the channel click path data of individual users in e-commerce enterprises， the relevant variables are extracted， and the COX model is verified by empirical analysis. Then the channel combination effect of the same channel， cross-channel and channel classification is analyzed.The results show that the combination of advertising channels from firm-initiated channels to brand search of customer-initiated channels will have a positive combination effect on purchases， while the combination of advertising channels from customer-initiated channels to firm-initiated channels will have a negative impact on purchases. In addition， the order of channels that move from general-purpose search to brand-type search has a positive combination effect on purchases. The data are grouped by gender to explore the differences in advertising effects of users of different genders. The results can help enterprises establish their marketing mix of advertising channels and mitigate the cost of ineffective advertising channel mix. Figures and Tables | References | Related Articles | Metrics

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Under Cascade Utilization of Power Battery the Lease Strategy Selection of Energy Storage Power Station in Wind Power Enterprises: Capacity Charging or Two-part Charging? Mingzhen Song, Teng Ma, Lingcheng Kong, Jiaping Xie 2025, 33 (9):  135-147.  doi: 10.16381/j.cnki.issn1003-207x.2022.2752 Abstract ( 27 )   HTML ( 0 )   PDF (1058KB) ( 2 )   Save In achieving China’s “dual carbon goals”， it is urgent to promote the transformation of the energy structure towards a distributed energy system dominated by renewable energy. However， its intermittent existence has led to the consumption problem of renewable energy electricity （referred to as “green electricity”）. With the rapid increase in the proportion of renewable energy， its consumption problem has become increasingly prominent. The configuration of energy storage stations in green electricity projects and the implementation of time-of-use electricity pricing policies are vital measures to solve the consumption problem of green electricity. However， the high cost of energy storage batteries has had a negative impact on the configuration of energy torage stations in green electricity projects. It can effectively alleviate the cost dilemma of energy storage by promoting the tiered utilization of power batteries （referred to as “old batteries”） in the energy storage field and implementing a two-part charging model for energy storage leasing.Therefore， wind power generation is used as an example， introducing the cascading utilization of power batteries and a two-part charging model. Regarding the use of new or old batteries and the choice of capacity rental or two-part charging， it designs four strategies： nR strategy （using new batteries， choosing capacity charging）， nT strategy （using new batteries， choosing two-part charging）， sR strategy （using old batteries， choosing capacity charging）， and sT strategy （using old batteries， choosing two-part charging）. At the same time， under the dual uncertainty of the intermittent wind resources and random fluctuations in peak electricity demand， considering the government’s constraints on the configuration of energy storage stations in wind electricity projects， it constructs leasing decision models of energy storage power stations for four strategies. In the construction of the decision model， it uses the intermittency factor u_i=[\mathrm{1},{\mathit{\rho }}_i;\mathrm{0,1}-{\mathit{\rho }}_i] to characterize the intermittency of wind power indicating that the probability of wind power projects generating electricity at rated power k is {\mathit{\rho }}_i in phase i， and the probability of not generating electricity is \mathrm{1}-{\rho }_i. It introduces a capacity retention rate \mathit{\tau } to measure the available capacity of power batteries. It sets the constraint ratio of government energy storage configuration as \mathit{\sigma }， so the capacity of energy storage stations that wind power projects should lease is \mathrm{m}\mathrm{a}\mathrm{x}\left(\mathit{\sigma }k,k_s\right)， where k_s is the leasing capacity of energy storage stations under profit maximization.The specific research steps are as follows　Firstly， using the decision model， the optimal leasing capacity decision is determined for four strategies of energy storage power stations. Secondly， it analyzes the impact of key parameters such as wind power intermittency， generation cost， electricity price， and capacity retention rate on the optimal leasing capacity. it also sort out the relevant properties and management insights. Finally， the advantages and disadvantages of the four strategies are compared from the perspectives of energy storage leasing capacity and maximizing profits for wind power enterprises. Figures and Tables | References | Related Articles | Metrics

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Research on Dynamic Licensing Pricing Strategy of Dual-use Defense Patent Considering the Social Efficiency Fei Yan, Hongzhuan Chen 2025, 33 (9):  148-160.  doi: 10.16381/j.cnki.issn1003-207x.2022.2366 Abstract ( 33 )   HTML ( 0 )   PDF (1399KB) ( 4 )   Save Considering the impact of the improvement of the social efficiency brought by transferring the dual-use defense patents to the civilian market， the dynamic licensing pricing strategy of the dual-use defense patent is studied. The dynamic no licensing model， dynamic fixed-fees licensing model and dynamic royalty licensing model considering the social efficiency are constructed. Based on this， the optimal dual-use defense patent licensing strategy of military manufacturer is studied， and the impact of discount rate and military and civilian product brand difference is analyzed. The results show that： 1） For the military manufacturer， in the short term， it is easier to obtain higher profits without licensing， but in the long run， the choice of the licensing strategy is more beneficial to the military manufacturer； 2） Compared with the dynamic fixed fee licensing model， the dynamic royalty licensing can encourage the military manufacturer to improve the social efficiency， moreover， the improved social efficiency under the dynamic royalty licensing improves the consumer utility and helps to expand the market sales， which helps the military manufacturer to get more licensing revenue and sales revenue. 3） Under the steady-state equilibrium， the no licensing strategy is more beneficial to the military manufacturer when the discount rate is lower， however， the licensing strategy will be more beneficial to the military manufacturer when the discount rate is higher. 4） When the brand power of the civilian manufacturer is weak， the royalty licensing model is optimal； others， the fixed fee licensing model is optimal. Figures and Tables | References | Related Articles | Metrics

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The Resilience and Sudden Change Mechanism of Group Opinion in Online Community Zilin Zeng, Bin Hu, Zhichao Wang, Xiaomeng Ma 2025, 33 (9):  161-176.  doi: 10.16381/j.cnki.issn1003-207x.2023.0247 Abstract ( 29 )   HTML ( 0 )   PDF (2457KB) ( 4 )   Save The sudden change phenomenon in group opinion in online communities is becoming increasingly prominent and needs to be described and predicted by reasonable methods. Combining catastrophe theory with resilience modeling， resilience index prediction methods are proposed for sudden changes in group opinion of online communities. Taking Xiaomi community as an example， the catastrophe model is fitted and the resilience calculation is performed. Then the method is verified and confirmed from several perspectives， and the stability of the resilience threshold under different community sizes is tested through comparative experiments. The influence of key variables on group opinion and the relationship between resilience index and fluctuation of product reputation are discussed for the actual case of Xiaomi community. The contribution of this paper is the establishment of the resilience index prediction method for the sudden changes in group opinion in online communities. The actual case study shows that this work can quickly grasp the level of group opinion in online communities and predict the fluctuation of it， providing support for community management decisions. Figures and Tables | References | Related Articles | Metrics

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Multi-Attribute Large Group Decision Making Method Based on T2PLD Operator in Social Trust Network Faming Zhang, Jiangtao Han, Linqian Zhang, Shuqi Zhu 2025, 33 (9):  177-188.  doi: 10.16381/j.cnki.issn1003-207x.2023.0437 Abstract ( 22 )   HTML ( 0 )   PDF (1353KB) ( 5 )   Save With the increasing complexity of decision-making problems and the increasing scale of decision-making groups， how to aggregate large group decision-making information to obtain satisfactory decision-making results is a key step and an important part of multi-attribute large group decision-making problems. However， in the previous research on multi-attribute large group decision-making methods， most of them usually assume that decision makers are independent of each other， and rarely consider the social network relationship among decision makers. At the same time， most of the existing multi-attribute large group decision-making methods based on social trust network have not considered the realistic situation that decision makers belong to multiple groups or decision makers are isolated nodes. In order to solve these problems， in this paper， a new multi-attribute large group decision making method based three-dimensional probabilistic linguistic density operator is proposed. First， for the situation that decision makers belong to multiple groups or have isolated nodes in decision making， the improved method of social network analysis is used to make a proper cluster for large group decision makers based on the social trust network relationship among decision makers. Then， the weight of decision makers can be obtained by measuring the similarity of preference information of decision makers in the sub-groups， and the comprehensive density weight of sub-groups can be obtained by the linear combination of the vectors of centrality， trust and the number of decision makers in the sub-groups. Finally， the three-dimensional probabilistic linguistic density operator is defined， which is used to aggregate large group probabilistic linguistic evaluation information.Through an emergency management decision-making case， the proposed method is effectively applied. The case shows that the decision-making method is reasonable and reliable as it not only can deal with the social trust network relationship among large group decision makers， but also can effectively aggregate the probabilistic linguistic information of large group decision making. On this basis， in order to illustrate the advantages of this method， the group decision-making methods in previous studies are introduced to conduct the method comparisons. The results show that the decision-making method based on three-dimensional probabilistic linguistic density operator enhances the flexibility and stability of large group decision-making expert clustering， and improves the consensus level of large group decision-making. Figures and Tables | References | Related Articles | Metrics

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Grey Incidence Decision-making Method with Mixed Information Based on 2-additive Choquet Integral and Its Application Yu Feng, Yaoguo Dang, Junjie Wang, Zhangcheng Yang 2025, 33 (9):  189-200.  doi: 10.16381/j.cnki.issn1003-207x.2022.2502 Abstract ( 22 )   HTML ( 0 )   PDF (752KB) ( 5 )   Save With the rapid development of modern technology and information， there are many complex multi-attribute decision-making problems with overlapping grey areas and ambiguities， and the decision attributes often have mutual interaction effects. To address the mixed multi-attribute decision-making problem with interaction effects between attributes， and a mixture of precise numbers， interval grey numbers， intuitionistic fuzzy numbers， hesitant fuzzy numbers， and linguistic variables， a mixed information grey relational decision-making method based on 2-additive Choquet integral is proposed.The specific research process as follows　（1） First， the mixed information decision matrix \tilde{R}={\left({\tilde{r}}_{ij}\right)}_{m\times n} is defined， and the mixed information grey relational coefficient {\eta }_{ij} is constructed. （2） Then， the 2-additive Choquet integral operator is introduced to nonlinearly aggregate the grey relational coefficients of different attributes and construct the mixed information grey relational degree based on 2-additive Choquet integral， which can be expressed as {\eta }_i={\displaystyle \sum _{j=\mathrm{1}}^n}{I}_j{\eta }_{ij}-\frac{\mathrm{1}}{\mathrm{2}}\sum _{\left\{c_j,c_k\right\}\subseteq C}{I}_{jk}\left|{\eta }_{ij}-{\eta }_{ik}\right|. I_{jk} indicates the interaction index between attribute j and attribute k. （3） To objectively determine the interaction indices between attributes， a mixed information grey relational multi-objective nonlinear optimization model is established， and the whale intelligence algorithm is used to solve the parameters. （4） Subsequently， a novel grey relational decision-making method with mixed information based on 2-additive Choquet integral is constructed， and specific algorithm steps are given. Figures and Tables | References | Related Articles | Metrics

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Personalized Individual Semantic with Continuous Learning and Behavior Modeling to Support Consensus Reaching in Multi-granular Linguistic Environment Congcong Li, Haiming Liang, Yucheng Dong 2025, 33 (9):  201-212.  doi: 10.16381/j.cnki.issn1003-207x.2023.0230 Abstract ( 24 )   HTML ( 0 )   PDF (1533KB) ( 8 )   Save Along with the rapid development of Internet technology and the rise of new social media， the pattern of group decision making has been changed profoundly， and it often occurs in a linguistic context. The multi-granular linguistic representations and semantics complexity have been the focuses in computing with words and linguistic decision-making. The personalized individual semantics （PISs） model with continuous learning and behavior modeling is proposed to support group consensus decision-making under multi-granular linguistic environment. Firstly， it is considered that the PISs of decision makers will be affected by the decision-making environment and decision-makers' preferences， so it will be changing dynamically during the consensus reaching process. Thus， a PISs model of behavior modeling and continuous learning based on prospect theory has been proposed. Then， the consensus measurement and feedback recommendation based on PISs under multi-granular linguistic context are developed to support the consensus process. Finally， numerical and simulation analysis are presented to illustrate the use of the proposed model， and to show the influences of the decision-making behaviors （e.g.， dynamic PISs， loss aversion） on the evolution of group consensus. The research results in this paper show that the PISs and consensus decision-making model can be improved by integrating continuous learning and behavior modeling. Figures and Tables | References | Related Articles | Metrics

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The Research Progress and Prospects of Sustainable Supply Chain Management under the New Development Pattern Junjun Liu, Xiqiang Xia, Qinghua Zhu 2025, 33 (9):  213-226.  doi: 10.16381/j.cnki.issn1003-207x.2024.1638 Abstract ( 29 )   HTML ( 0 )   PDF (1194KB) ( 9 )   Save In recent years， the compounded and sustained impacts of major global events—including the COVID-19 pandemic， escalating geopolitical conflicts， and a new wave of technological advancements—have redefined global development trends. This evolving landscape is marked by increased macro-environmental uncertainties， a growing consensus on green development， and the accelerated pace of technological change. In response， the sustainable supply chain management （SSCM） of enterprises faces heightened challenges and pressures. Improving SSCM practices to navigate these complex challenges has become a focal area for both industry and academia. Amid efforts to enhance SSCM， numerous “pioneer” companies have emerged with successful practical initiatives and advanced management practices. These examples highlight the resilience and adaptability needed as businesses face supply chain disruptions and trade tensions. Today， stakeholders—including governments and consumers—demand greater environmental and social responsibility from supply chains， prompting companies to rethink and adjust their strategies and operations. Consequently， SSCM research has become increasingly important， shaping responses to the new global development patterns （Lee，. To address this need， a systematic review of recent advancements is provided in SSCM research. Employing the classic SSCM analytical framework of “drivers or pressures-practices-performance，”both quantitative and qualitative analyses of SSCM research published in major supply chain journals from 2020 to 2024 are conducted. Through this review， four major research topics are identified， including macro factors-climate change and carbon emissions， sustainable supply chain management under the impact of the new coronavirus pandemic， application of Industry 4.0 technologies and sustainable supply chain management， and sustainable governance of multilevel supply chains and supply chain networks-and the progress of their respective research is summarized. On this basis， the outlook of future research is presented from three aspects. The first is sustainable supply chain management in a dynamic environment， including three sub-research directions： sustainable supply chain management under the risk of chain breakage， sustainable supply chain management under the development of Industry 5.0 technology， and ESG responsibility of supply chains under new regulations. The second is sustainable supply chain management tools for triple-bottom-line objectives， which also includes three sub-research directions： green （low-carbon） financial tools empowering supply chain synergistic value， sustainable supply chain governance with multi-organizational participation under the perspective of value symbiosis， and industry standards for fine-tuned sustainable supply chain management. In addition， the theoretical needs and development of sustainable supply chain management are also discussed， including the expansion of theoretical frameworks in complex （dynamic） environments， interdisciplinary integration to enrich theories or explanatory mechanisms and theoretical discovery driven by new ideas or management practices. By carrying out literature review and summarizing the research progress， the understanding of the core topics of the current research on sustainable supply chain management under the new development pattern is facilitated， and a clear framework and direction for the subsequent research is also provided. Meanwhile， by summarizing the potential research directions， it provides a reference for scholars to further explore the sustainable development of supply chain. Figures and Tables | References | Related Articles | Metrics

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Analysis and Countermeasures of Three-stage Evolution Path on“Big Data Affinity”of Internet Platforms Mingkun Li, Zhengyan Cui, Tian Liang 2025, 33 (9):  227-235.  doi: 10.16381/j.cnki.issn1003-207x.2023.0071 Abstract ( 29 )   HTML ( 0 )   PDF (815KB) ( 5 )   Save Internet platforms have formed an evolutionary path of “Big Data Affinity” and relying on it to seek success. The path implies a three-stage method which includes cash-burning for clout， cultivating habits and access to revenue. It brings a key concern on how to break the path dependence and promoting anti-monopoly governance. In this paper， the Salop circular model is introduced to deduce the market competition of platforms in the three-stage evolutionary path. And the impact of price sensitivity factors and user transfer costs on the market share and profits of platforms is analyzed. 1） The results show that it helps platforms to gain a big market share by spending plenty of money， in particular， when the price sensitivity of customers is high. 2） The profit of the platform might decline significantly， while the competition for users puts all platforms in the market under pressure. 3） The more the number of platforms in the market， the more their market share and profits are affected by the cost of transferring users， and the less conducive they are to take the monopoly advantage and implement “Big Data Affinity”. Accordingly， it is proposed that a price monitoring platform should be set up and customers are provided with more market information and options of transferring. More investment and support should be put to latecomer platforms in order to break the path dependency. Figures and Tables | References | Related Articles | Metrics

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Research on Risk Control of Quality Chain of Quality Agricultural Products Based on GERT Guangsi Li, Shaobo Zhang 2025, 33 (9):  236-247.  doi: 10.16381/j.cnki.issn1003-207x.2023.1128 Abstract ( 25 )   HTML ( 0 )   PDF (1848KB) ( 6 )   Save In order to accelerate the development of quality control system of high-quality agricultural products and improve the supply capacity of high-quality agricultural products， based on the GERT theory， the three levels of quality chain links， processes and quality （control） activities are nested in the same network analysis framework， the network characterization of quality risk transfer of high-quality agricultural products is analyzed， and the parameters of the network are updated by means of Bayesian updating from the “human-machine-data-fa-environment” multiple aspects to study the risk control path. “By updating the network parameters in a Bayesian way， the risk control path is studied from multiple aspects， and then the risk transfer and risk control model of agricultural product quality chain is constructed with the optimization goal of minimizing the quality risk and risk control cost. On this basis， the vertically integrated apple production enterprise is taken as an example to clarify the quality risk proliferation transfer mechanism， and the optimal cost-risk control strategy for high-quality agricultural products is proposed in combination with the risk control cost. It is shown that， due to the different processes and quality activities in each link， the amount of quality risk proliferation is not the same， but the source management is still crucial to reduce the transmission of quality risk and prevent the proliferation of risk； “human-machine-material-method-environment” multi-faceted risk control is effective in reducing the risk of hidden danger， but it will bring about high costs， and the enterprise can choose the first one according to its own endowment situation， and then choose the first one according to its own endowment situation. Enterprises can choose “high” cost-effective risk control strategies according to their own endowment， and then gradually change to all-round risk control； when enterprises make decisions on risk control， they should assess their own endowment， and apply measures according to their circumstances. Figures and Tables | References | Related Articles | Metrics

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Service-performance-based Contract Designs for Equipment Suppliers and Their Signaling Mechanisms Xuwei Qin, Yimei Zhu, Zhongzhong Jiang, Xiaoran Liu 2025, 33 (9):  248-257.  doi: 10.16381/j.cnki.issn1003-207x.2022.1228 Abstract ( 28 )   HTML ( 0 )   PDF (1016KB) ( 5 )   Save Industrial internet technology transforms theequipment service environment where performance-based service becomes an emerging business model and the suppliers have an information advantage on the equipment， which leads to asymmetric information in performance-based contracting （PBC） between the supplier and the customer. The supplier possesses two types of equipment， i.e. the high and the low reliability. Considering two scenarios where the supplier's repair capacity can be verified or not， the PBC design problem is modeled in the framework of the signaling game and the signaling-with-renegotiation to obtain the optimal contract and the supplier’s equilibrium capacity. In addition， how the interaction mechanism between the PBC and the verifiability of repair capacity signals the equipment type is further investigated. Equilibrium and simulation outcomes confirm the following conclusions： When the supplier’s repair capacity is verified， the supplier signals high-reliability information to the customer by multiple and flexible PBCs with higher fixed payments and higher penalty rates as well as a lower repair capacity， and meanwhile the equilibrium repair capacity and the supplier’s service profit both achieve the first-best level； when the repair capacity is unverifiable， by contrast， the supplier adopts a unique PBC with a high fixed payment and ultra-high penalty rate to signal information about types， resulting in overinvestment in repair capacity and supply chain inefficiency， and limiting the flexibility of the PBC. These findings reveal the advantage of the verifiability of the repair capacity and suggest that suppliers should utilize industrial internet technology to timely disclose service effort information to customers and then eliminate inefficiency caused by information asymmetry. Figures and Tables | References | Related Articles | Metrics

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The Competitive Price-matching Policy of an Inferior Retailer in Asymmetric Competition Tianfang Zan, Jinpeng Xu, Yi Li, Xiaolan You, Gengzhong Feng 2025, 33 (9):  258-268.  doi: 10.16381/j.cnki.issn1003-207x.2022.1847 Abstract ( 33 )   HTML ( 0 )   PDF (1401KB) ( 4 )   Save With the development of the e-commerce， it is common for consumers to compare prices on multiple channels. In order to eliminate consumers' doubts about high prices and attract more consumers， competitive price-matching policy， which can influence consumers' purchasing decisions， is favored by some inferior retailers in asymmetric competition （i.e.， Dangdang， Suning and Gome etc.）. When one retailer offers competitive price-matching policy， consumers can apply to the retailer for price difference compensation if they find a lower retail price within a certain period of time and within a certain area after purchasing the product. The existing literature has a theoretical gap in how an inferior retailer should adopt competitive price-matching policy in asymmetric competition with a superior retailer， which motivates us to ask the following research question： First， under what market conditions can the inferior retailer obtain greater profits by adopting competitive price-matching policy？ Does the superior retailer benefit from the inferior retailer's competitive price-matching policy？ Second， how do the structure of consumers， the market stimulus effect of the policy， and the cost of price-matching affect the conditions under which the inferior retailer adopts competitive price-matching policy？ Third， how will the equilibrium price and profit of the inferior and superior retailers， and consumer welfare change after the inferior retailer adopts the policy？ To address these questions， it is considered that the market is consisting of two types of consumers， i.e.， switchers and loyals， and a game-theoretical model is developed based on Hotelling model to study the price competition between an inferior retailer and a superior retailer. The scenarios of non-adoption and adoption of competitive price-matching policy by the inferior retailer （i.e.， scenario N and scenario M） is analyzed.The research results show that the competitive price-matching policy has a competition-dampening effect， which will increase the price of the inferior retailer and the average market price. The possibility of the two retailers colluding to reach the same price increases with the proportion of consumers who request refunds. Whether the inferior retailer can benefit from the policy depends on the structure of consumers， the policy's market stimulus effect and the price-matching cost， and the superior retailer may either benefit or suffer from the policy. In addition， the policy does not always hurt consumer welfare. From the perspective of consumer structure， the mechanism and conditions of an inferior retailer adopting competitive price-matching policy to improve the competition situation are discussed. In other words， the main contribution of this study is to explain why inferior retailers are more aggressive in adopting competitive price-matching policy， and analyze how consumer structure， the policy's market stimulus effect， and price-matching cost jointly affect the equilibrium prices， and the conditions under which the two retailers and consumers can benefit from the policy. The results provide guidance for inferior retailers on whether or not adopting competitive price-matching policy and how to decide on the retail price under the policy. Specifically， inferior retailers should decide whether to adopt competitive price-matching policy based on market structure and cost. After adopting the policy， they should strengthen publicity to expand the market promotion effect of the policy， and establish a refund application review system to reduce refund costs. In addition， consumers should not put too much faith in competitive price-matching policy. Figures and Tables | References | Related Articles | Metrics

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Platform Pricing Strategies and Mode Selection of Retailers Facing Potential Competitors’ Heterogeneous Product Introduction Zonghuo Li, Shanliang Li, Liwen Liu 2025, 33 (9):  269-279.  doi: 10.16381/j.cnki.issn1003-207x.2022.2030 Abstract ( 40 )   HTML ( 0 )   PDF (1326KB) ( 7 )   Save With the rapid development of the platform economy， more and more retailers rely on online platforms to sell products. In turn， online platforms allow retailers to enter the market by charginga commission fee. In the process of cooperation between retailers and the online platform， potential competitive retailers invade the platform retail system with products of different quality. This has led to fierce channel and product competition.A platform retail system where an incumbent retailer and an online platform reach a contract is studied based on a commission fee. A potential competitive retailer enters the system through direct sales mode， wholesale mode， and hybrid mode with heterogeneous products. The game theory is adopted to analyze the impact of quality differences and introduction modes on the operational decision of the platform retail system. The optimal pricing strategy and mode selection of the game players are extracted. The result shows that product introduction does not necessarily reduce the profit of the incumbent retailer and platform. Rather， the incumbent retailer derives a higher profit when the product quality and commission fee are low； and the platform derives more profit when the product quality is low and the commission fee is large. The result also indicates that the incumbent retailer should resist a low-quality product introduction through wholesale mode when the commission fee is large； while it should resist a high-quality product introduction through hybrid mode. The platform should adopt a hybrid mode to resist a high-quality product introduction under a high commission fee. Interestingly， even if the commission fee is low， the platform will still choose the direct sales mode to resist a low-quality product introduction.The results of this paper can provide theoretical suggestions for the pricing strategy of the platform retail system. Meanwhile， it provides decision-making reference for cooperation mode selection and benefit distribution between online platforms （such as Amazon.com and JD.com） and upstream retailers. Figures and Tables | References | Related Articles | Metrics

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Optimal Blockchain Platform Construction and Joining Strategy of Supply Chain under Product Quality Differentiation Xiaohong Chen, Weidong Zhang, Fuqiang Wang 2025, 33 (9):  280-290.  doi: 10.16381/j.cnki.issn1003-207x.2022.1748 Abstract ( 34 )   HTML ( 0 )   PDF (847KB) ( 9 )   Save Recently， blockchain technology has been increasingly applied in supply chain operation management. However， the successful implementation of blockchain needs the participation of upstream and downstream enterprises of the supply chain. Therefore， it is a critical issue to identify the conditions for upstream and downstream enterprises of the supply chain to adopt blockchain technology in a competitive environment.In this paper， a supply chain that composed of two upstream suppliers with differences in product quality and one downstream retailer is considered. The retailer can choose to build the blockchain platform according to the market situation， and the suppliers can choose to join the blockchain platform. The models for maximizing profits of the suppliers and the retailer are constructed with regard to the retailer does not build a blockchain platform （the suppliers cannot join the blockchain platform） and the retailer builds a blockchain platform （the suppliers choose to join the blockchain platform or do not join the blockchain platform）. Then， by solving the models， the optimal decisions of the retailer and the suppliers are obtained in different scenarios. Further， the profits of the retailer and the suppliers are compared to analyze the optimal strategies of the retailer and the suppliers. On this basis， equilibrium results are gotten for the retailer and the suppliers.Several important results are shown through the theoretical analysis. First， whether upstream suppliers join the blockchain platform depends mainly on the cost of blockchain， the increase of market potential after adopting blockchain technology and the differentiation level of product quality of upstream suppliers. Second， when the low-quality supplier decides to join the blockchain platform， the optimal strategy for high quality supplier is to always join the blockchain platform. In the end， upstream suppliers joining the blockchain platform is not always beneficial for retailer and overall supply chain profit. Particularly， only when the production competition intensity is small or the upstream suppliers’ product quality differentiation is significant， it would be better for retailer to construct the blockchain platform. Overall， the research can provide theoretical support for the decision of the retailer to build the blockchain platform in reality， and can also provide theoretical and ideological reference for different types of suppliers to join the blockchain platform. Figures and Tables | References | Related Articles | Metrics

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Technical Input and Cooperation of Energy Enterprises under Renewable Portfolio Standard Jian Cao, Jinyi Chen, Qin Shao 2025, 33 (9):  291-300.  doi: 10.16381/j.cnki.issn1003-207x.2022.2450 Abstract ( 30 )   HTML ( 0 )   PDF (960KB) ( 5 )   Save The era of parity Internet access with the full implementation of Renewable Portfolio Standard （RPS） is arriving in China， while the price of domestic Tradable Green Certificate （TGC） is high and the TGC market is sluggish. Since the price of TGC is tightly related to the cost of power generation， renewable energy technology input becomes particularly essential. To explore the technology input and cooperation of energy enterprises under the full implementation of the quota system， three models are constructed. A Cournot model is used to analyze the production decisions of energy enterprises under RPS； A two-stage dynamic model is constructed to reflect the technology input of renewable energy enterprises； A three-stage dynamic model is aimed at studying the R&D cooperation among energy enterprises. Furthermore， a corresponding empirical study is conducted using Chinese electricity market data for 2020 and 2021. It is found that there are improper incentives in the TGC. The technical input of renewable energy enterprises has a positive effect on the overall energy market. The existing possibility of technical cooperation will stimulate the virtuous circle between TGC market and energy market. When the quota is low， the preference of renewable energy enterprises to choose technical cooperation is also low， it could be promoted by Nash bargaining mechanism. The research provides a possible solution to the current situation of high TGC prices in China， which could be referred by the government. Figures and Tables | References | Related Articles | Metrics

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Joint Decision of Freshness-keeping Effort and Promotion Effort in a Dual-channel Fresh Produce Supply Chain from a Dynamic Perspective Wenlong Wang, Zhuyun He, Suxian Zhang 2025, 33 (9):  301-311.  doi: 10.16381/j.cnki.issn1003-207x.2022.2070 Abstract ( 24 )   HTML ( 0 )   PDF (1271KB) ( 8 )   Save With the implementation of the project of “promoting agriculture through digital commerce”， the fresh e-commerce market in China is growing rapidly. In a dual channel supply chain， a supplier usually needs to dynamically adjust environmental factors in storage， transportation and distribution over time according to the current freshness level of fresh products， that is， to make dynamic freshness-keeping efforts. At the same time， as an effective means to stimulate consumers to buy quickly， promotion is an important decision for a retailer to attract consumers. It is worth noting that in order to cope with the dynamic changes in freshness of fresh products， the retailer needs to make dynamic promotion efforts to maximize profit. Therefore， the freshness-keeping efforts of the supplier and the promotion efforts of the retailer will jointly affect the operation performance of a fresh supply chain.Under this background， based on the dynamic perspective of time dimension， the supplier’s freshness-keeping efforts and retailer's promotion efforts， and the multiple effects of product freshness， goodwill and price on market demand are considered. Focusing on a dual channel supply chain of fresh products in which the supplier has both online and offline channels， a differential game model is constructed， and the optimal control theory is used to solve the dynamic joint decisions of supply chain members under centralized and decentralized decisions. A revenue sharing contract is designed to optimize supplier’s freshness-keeping efforts and retailer's promotion efforts and improve the performance of the supply chain.The results show that　（1） Under the three decision-making situations， the freshness level of fresh food is monotonically increasing， however， the changes of goodwill are diversified. In addition， the profits of the supplier and the retailer will increase to a stable state over time， and at this time， they are the highest under the centralized decision-making situation， higher under the revenue sharing contract， and the lowest under the decentralized decision-making situation. （2） Under centralized decision making， the optimal level of promotional efforts and the optimal level of freshness-keeping efforts increase with market demand， consumer freshness preference and brand preference， and decrease with the decaying degree of product goodwill and input cost. （3） Under decentralized decision-making， the market share of traditional channel has a positive impact on retailer's promotion efforts， and a negative impact on supplier's freshness-keeping efforts. （4） As consumers' freshness preference and brand preference become more and more obvious， the revenue sharing contract is easier to promote member's input in freshness-keeping and promotion efforts， thus bringing more market demand and increasing supply chain profit. Revenue sharing contract can realize Pareto improvement， effectively alleviate the "double marginal effect"， and significantly improve the overall revenue of the fresh supply chain. Figures and Tables | References | Related Articles | Metrics

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A Newsboy Model Considering Credit Line Based on CVaR Qiang Lin, Zhenjie Shan, Wenzhuo Li 2025, 33 (9):  312-324.  doi: 10.16381/j.cnki.issn1003-207x.2023.0256 Abstract ( 23 )   HTML ( 0 )   PDF (1086KB) ( 2 )   Save Small and medium-sized retailers are the main force of national economic and social development， but they often face the problem of capital shortage in their production and operation processes. Small and medium-sized retailers mainly obtain loans from financial institutions such as banks to solve their capital shortage problems. After evaluating the credit and repayment ability of small and medium-sized retailers， banks provide funds within the credit line for small and medium-sized retailers in need. Based on these， the impact of bank credit constraints and retailer risk aversion characteristics is considered， and Conditional value-at-risk （CVaR） is used to characterize the risk aversion features of retailers. Three models are constructed： the newsboy model without funding constraints， the full credit exposure model provided by banks， and the newsboy model with credit constraints. The impact of bank credit line and retailer risk aversion characteristics on joint decision-making for retailer ordering and loan procurement is explored.The main results suggest that （i） Providing loans to the retailer can share some market uncertainty risks and stimulate the retailer to increase product orders， mitigating the negative impact of retailer risk aversion characteristics. Specifically， when the degree of risk aversion of the retailer is high， their optimal ordering quantity is higher than the optimal ordering quantity without funding constraints. （ii） A risk-neutral retailer only applies for gap funding loans from banks， while a risk-averse retailer may apply for high-value loans to transfer bankruptcy risks to banks in order to obtain more stable returns. （iii） A risk-neutral retailer will not over-borrow， and their optimal ordering decisions will be determined by market factors and credit line. For a risk-averse retailer， when the bank's credit line is high， they may choose credit line loans and the optimal ordering quantity is consistent with that without funding constraints. It should be noted that when the bank endogenously determines the credit line， the above research conclusions can still be obtained. Moreover， the numerical analysis indicate that although increasing market uncertainty may reduce the utility of the retailer， it does not necessarily lead to a decrease in their ordering quantity. In addition， when banks provide lower credit line and the retailer have a higher degree of risk aversion， the impact of market uncertainty on the optimal ordering quantity of the retailer is more significant， which will also significantly affect their utility. In other words， market demand uncertainty will amplify the impact of bank credit line and retailer risk aversion characteristics on the decision-making of retailer ordering and loan amounts.The management implications are as follows. First， retailers need to develop reasonable financing and ordering strategies based on their own risk aversion characteristics and market demand uncertainty. With the support of a certain credit line provided by banks， retailers can adjust their ordering decisions to achieve the optimal ordering quantity. Second， banks should flexibly adjust credit line based on factors such as retailer risk aversion characteristics and market demand uncertainty to meet retailers’ funding needs. At the same time， banks need to consider risk control to avoid losses caused by retailers’ inability to repay loans. Figures and Tables | References | Related Articles | Metrics

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Research on Cooperative Recycling Operation Method of New Energy Vehicle Power Battery Weizhen Rao, Yue Chang, Peng Liu 2025, 33 (9):  325-338.  doi: 10.16381/j.cnki.issn1003-207x.2023.0112 Abstract ( 27 )   HTML ( 0 )   PDF (2127KB) ( 6 )   Save Currently， the lack of collaboration among new energy vehicle brands has led to significant time consumption for owners during the battery recycling process， thereby hindering the timely and efficient recovery of batteries and potentially giving rise to safety hazards and environmental issues. In response， the formation of collaborative alliances among recycling outlets of different new energy vehicle brands is proposed to reduce the travel distance and time cost for owners， thereby enhancing their willingness to participate in recycling and increasing the recycling rate. Centered on this model and operational approach， a collaborative recycling mechanism relying on a third-party information platform is designed. Subsequently， a route optimization plan for owners is developed to reach recycling outlets and a time cost model is established for the recycling process. Furthermore， based on the Shapley value method， a fair calculation is conducted to allocate the time cost savings among alliance members resulting from the collaborative model. Then， through a questionnaire survey， current recycling demands of owners are investigated to characterize the relationship between the recycling rate and time cost. Finally， a numerical example demonstrates that owners’ time cost can be reduced by 40% to 70%， and combined with survey results， the recycling rate is projected to increase by 8.23% to 10.71%. If implemented nationwide， this model is expected to increase the recycling volume by approximately 94，700 to 123，200 tons， validating the practical effectiveness of the multi-party collaborative recycling model. Figures and Tables | References | Related Articles | Metrics

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Carbon Audit Strategies to Managing Supplier Emission Reduction Noncompliance: Independent vs Joint Hongyong Fu, Yifeng Lei, Bin Dan, Shuguang Zhang 2025, 33 (9):  339-348.  doi: 10.16381/j.cnki.issn1003-207x.2022.2262 Abstract ( 33 )   HTML ( 0 )   PDF (1136KB) ( 7 )   Save Carbon emissions are recognized as a major contributor to global warming. To combat climate change， many countries and regions have implemented regulations to guide enterprises to reduce carbon emissions. Therefore， the compliance or non-compliance with the carbon emission regulations becomes a critical factor in assessing enterprises’ environmental responsibility， especially in a supply chain with a supplier and two competing manufacturers. The downside effect caused by the supplier non-compliance is often attributed to the downstream manufacturers’ fault， thereby motivating the latter to conduct a audit to prevent negative impacts on their goodwill. Based on the competition theory， there are two audit strategies for the two manufacturers： independent audit and joint audit. Specifically， under independent audit， the manufacturers conduct their respective audits and impose penalties independently. Under joint audit， the manufacturers conduct a audit jointly， and impose a collective penalty if the supplier fails their joint audit. Then， which audit strategy should be choosed by the two manufacturers？To answer the above question， simultaneous game model with the supplier and the two manufacturers is used to analyze and compare the equilibrium decisions and the optimal profits under independent audit and joint audit. The study results show that， first of all， there is the feasible region that independent audit is dominant. Moreover， independent audit is a “perfect” audit strategy in this region. That is， independence audit not only can improve the supplier’s carbon reduction compliance but also can benefit the manufacturers and the supplier. Secondly， when joint audit is dominant， it is unexpectedly finds that joint audit is a “imperfect” strategy， i.e.， it is only beneficial to the improvement of the supplier’s carbon emission reduction compliance and the two manufacturer’s profit， even is a “failure” strategy， that is， it is only beneficial to both manufacturers. For this， a carbon emission reduction compliance cost-sharing mechanism based on the purchase price is designed to improve the carbon emission reduction compliance and profit of the supplier， thus allowing joint audit to also become a “perfect” strategy. Finally， whether independent audit or joint audit， the two manufacturers should keep a prudent attitude toward the price premium to prevent falling into the “price trap” and thus avoid the risk of reducing carbon emission reduction compliance.In summary， through this study， it aims to comparative analysis independent audit and joint audit， and then to provide insights for how the two competing manufacturers should conduct a audit to manage the supplier non-compliance with emission reduction. Figures and Tables | References | Related Articles | Metrics

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Incentives for Carbon Emission Reduction in the Supply Chain under the Demand and the Trading Price of the Emission Permit Uncertainty Bo Wu, Jianheng Zhou 2025, 33 (9):  349-358.  doi: 10.16381/j.cnki.issn1003-207x.2022.2686 Abstract ( 34 )   HTML ( 0 )   PDF (1123KB) ( 2 )   Save In recent years， as the global environmental situation has become more and more severe， the topic of how to “educing carbon” has triggered extensive discussions among many enterprises and scholars. It is found under the carbon tax policy and cap-and-trade policy， the two-part tariff contract is conducive to mitigating double marginalization， but the extent of mitigation is closely related to the carbon policy， as the carbon tax policy is more stable， so the space to reduce the wholesale price is more constant； the cap-and-trade policy is affected by the uncertainty of the carbon price market， and the coordinating effect of the contract will be strengthened with the increase of the uncertainty of the carbon price. Secondly， the two-part tariff contract can realize the overall coordination of the supply chain under the carbon tax policy， but under the cap-and-trade policy， it depends on the correlation coefficient， and the two-part tariff contract can be beneficial to the supply chain participants only when the correlation coefficient meets certain conditions. In addition， it is found that the two-part tariff contract can bundle the risk of uncertainty with suppliers， and use the “risk-passing” effect to reduce the negative impacts of uncertainty on the brand. At the same time， the brand can use flexible pricing to amplify the positive effects of carbon reduction in the supply chain， thereby increasing supply chain profits. Moreover， under the carbon tax policy， the brand can only transfer the uncertainty of market demand brought by the supply chain’s low-carbon investment efforts to the upstream. Under the cap-and-trade policy， the brand can transfer the uncertainty of market demand， the uncertainty of carbon price， and the volatility of carbon trading price on demand upstream at the same time. Figures and Tables | References | Related Articles | Metrics

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Renewable Energy Maintenance Strategies for Power Supply Chain Considering Extreme Weather Wei Chen, Yongle Tian, Chunguang Bai, Yongkai Ma 2025, 33 (9):  359-368.  doi: 10.16381/j.cnki.issn1003-207x.2022-2669 Abstract ( 26 )   HTML ( 0 )   PDF (945KB) ( 8 )   Save Aiming at the influence of extreme weather on renewable energy maintenance， a two-level electricity supply chain composed of an electricity generator and an electricity retailer is constructed. Maintaining renewable energy by electricity generator will optimize the energy structure； Maintaining renewable energy by electricity retailer will increase electricity demand. The two models are compared， which are renewable energy maintenance by electricity generator and electricity retailer， and the boundaries of renewable energy maintenance are identified. The equilibrium model is solved by backward induction and the following conclusions are drawn. （1） With the increase in the maintenance cost coefficient of renewable energy or the probability of extreme weather， the demand for renewable energy decreases. （2） When the probability of extreme weather is small， electricity retailer is more motivated to maintain more renewable energy， while when the probability of extreme weather is large， electricity generator is more motivated to maintain more renewable energy. The main research contributions are as follows （1） Extreme weather is introduced into the electricity supply chain， based on the situation where there are electricity generator maintaining renewable energy and electricity retailer maintaining renewable energy in reality. It is identified that the boundaries of renewable energy maintenance will improve the efficiency of the power supply chain. （2） Few scholars have studied the issue of who will maintain renewable energy. Chen et al. （2020） studied the investment of upstream and downstream electricity supply chain investment of renewable energy. It is found that the probability of extreme weather occurring affects the selection strategy of electricity supply chain， which further enriches existing research on the electricity market. Figures and Tables | References | Related Articles | Metrics