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    Stock Index Prediction Based on LSTM Network and Text Sentiment Analysis
    Xiaojian Yu,Guopeng Liu,Jianlin Liu,Weilin Xiao
    Chinese Journal of Management Science    2024, 32 (8): 25-35.   DOI: 10.16381/j.cnki.issn1003-207x.2021.0084
    Abstract1201)   HTML108)    PDF(pc) (868KB)(1621)       Save

    Investment decision-making can be a complex process, influenced by various factors, including investor behavior preferences. Therefore, it's important to understand and capture investor sentiment for predicting future changes in the stock market trend. In this regard, machine learning algorithms can be helpful in analyzing investor sentiment in the financial market. It aims to construct a predictive model for stock indices using an LSTM network and text sentiment analysis in this paper.To begin with, a web crawler program is used to collect text comments on individual stocks in the East Money Stock Bar. The text data are analyzed using the SVM sentiment classification algorithm to construct a market sentiment index that reflects investor sentiment. Additionally, the LSTM deep learning network is used to extract the features of the market sentiment index and make short-term predictions on the SSE 50 index.Various traditional time series analysis models and machine learning models are compared. The results show that the LSTM neural network has higher accuracy and precision in financial time series prediction. After incorporating market sentiment features, the accuracy and precision of the LSTM network prediction results can be improved. This indicates that investor market sentiment is highly effective and applicable for market index prediction. It is also found that error correction of the LSTM network prediction results can effectively optimize the prediction results.Overall, a new method is provided for understanding investor sentiment and predicting future changes in the stock market trend. It is hoped that our research results can provide useful reference and guidance for financial investors and analysts.

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    Equilibrium Analysis of Manufacturers' Digital Transformation Strategy under Supply Chain Competition
    Hua Zhang,Xin Gu
    Chinese Journal of Management Science    2024, 32 (6): 163-172.   DOI: 10.16381/j.cnki.issn1003-207x.2021.1572
    Abstract664)   HTML46)    PDF(pc) (2407KB)(1317)       Save

    The digital economy is profoundly changing the fundamental principles and value creation logic of the manufacturing industry and has become a new driving force leading economic growth. However, the digital economy also exerts great pressure on the traditional development model of the manufacturing industry. Some firms implementing digital transformation may not only use their market power to occupy excess monopoly profits but also curb the living space of traditional manufacturers by technological advantages. Therefore, choosing an appropriate opportunity to implement digital transformation is an important decision issue faced by manufacturers.Two competitive supply chains consisting of one manufacturer and one retailer are consided, and dynamic game models are employed to analyze the optimal strategy and game equilibrium of manufacturers' digital transformation. The results show that either of the two manufacturers can maximize its own profits, downstream retailer profits, and supply chain market share by implementing digital transformation ahead of its competitors. It is also found that manufacturers' digital transformation will generate technological shocks and technological spillovers on the competitor who adopt traditional technologies, and the effect of technological shocks is greater than technological spillovers, which not only reduces the competitor's profits but also grabs its supply chain's market share. Regarding the strategic decision of digital transformation, whether the two manufacturers make decisions in sequence or at the same time, both of them implementing digital transformation will have a win-win effect, increasing manufacturers' profits and forming a Nash equilibrium of supply chain competition.Two key contributions are made to the literature. On the one hand, different from the previous research on digital transformation, not only the technological spillovers of digital transformation to incumbent firms are considered but also the impact of technological shocks about digital transformation on market competition is examined. The strategic decision of manufacturers' digital transformation is analyzed from the perspective of supply chain competition and theoretical support is provided for a deeper understanding of the mechanism of digital transformation on market competition. On the other hand, the literature in the field of supply chain competition and dynamic games mainly focuses on the game among firms in the traditional economic context, and seldom pays attention to the new business phenomena in the digital economy. The dynamic game models are used to analyze the Nash equilibrium of manufacturers' digital transformation in supply chain competition, the conditions for achieving a win-win effect between manufacturers are investigated, and the strategic decision for manufacturers is discussed to maximize profits under different strategy profiles, thereby enriching the literature in the field of supply chain competition and dynamic game.

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    Economic Policy Uncertainty and Renminbi Exchange Rate Volatility: Evidence from CARR-MIDAS Model
    Xinyu Wu,Haibin Xie,Chaoqun Ma
    Chinese Journal of Management Science    2024, 32 (8): 1-14.   DOI: 10.16381/j.cnki.issn1003-207x.2021.1654
    Abstract607)   HTML49)    PDF(pc) (726KB)(1033)       Save

    Financial volatility modeling and forecasting has always been a hot topic in financial econometrics, due to its great importance for derivative pricing, asset allocation and risk management. Typically, GARCH model is used to describe the dynamics of financial volatility. However, the GARCH model uses squared return to measure volatility, ignoring the information of intraday price movements. An alternative approach for measuring volatility is to employ the intraday range, which is calculated using the intraday high and low prices. Apparently, the intraday range makes full use of the intraday price information (extreme value information), which is a more efficient volatility estimator than the squared return volatility estimator.A classical model for describing the dynamics of the intraday range is the conditional autoregressive range (CARR) model, which produces more accurate volatility forecasts than the return-based GARCH model. Despite the empirical success of the range-based CARR model, it cannot capture the impact of macroeconomic variables (macroeconomic information) on financial volatility. In recent years, the level of economic policy uncertainty (EPU) keeps rising, due to a series of events including the US-China trade war and the coronavirus (COVID-19) pandemic. Intuitively, high EPU may affect investors' investment decisions and hence financial market. The foreign exchange market is one of the largest and most liquid financial markets in the world, which is of great relevance for investors and policy-makers and would have a close relation to EPU. As the currency of the world's second largest economy, renminbi plays a more and more important role in the world economy. Since the implementation of renminbi exchange rate regime reform in 2005, the renminbi exchange rate has experienced significant fluctuations. Accurate prediction of the renminbi exchange rate volatility has become increasingly important. To our knowledge, there are few studies investigating the impact of EPU on the renminbi exchange rate volatility.Inspired by the return-based GARCH-MIDAS model, this paper extends the classical range-based CARR model to the range-based CARR-MIDAS model to model the renminbi exchange rate volatility. The model framework explores the intraday extreme value information and allows the low-frequency macroeconomic variable (macroeconomic information) such as EPU directly impacts the volatility via the long-run component of volatility and the flexible MIDAS structure.Using the monthly global EPU index and daily US Dollar against Chinese Yuan (USD/CNY) exchange rate data, the impact and predictive ability of the EPU on USD/CNY exchange rate volatility are investigated relying on the range-based CARR-MIDAS model with the EPU (CARR-MIDAS-EPU). The empirical results show that the EPU has a significant positive impact on the long-run volatility of USD/CNY exchange rate. That is, an increase in the EPU level predicts higher level of the long-run volatility of USD/CNY exchange rate. The range-based CARR-MIDAS-EPU model produces more accurate out-of-sample forecasts of the USD/CNY exchange rate volatility compared to a variety of competing models, including the return-based GARCH model, GARCH-MIDAS model and GARCH-MIDAS-EPU model as well as the range-based CARR model and CARR-MIDAS model, for forecast horizons of 1 day up to 3 months. This finding suggests that the range and EPU contain valuable information for forecasting USD/CNY exchange rate volatility. The robustness analysis based on the alternative global EPU index as well as the out-of-sample forecasting windows further supports the above conclusion.

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    Re-exploration of Small and Micro Enterprises' Default Characteristics Based on Machine Learning Models with SHAP
    Xinnan Lei,Lefan Lin,Binqing Xiao,Honghai Yu
    Chinese Journal of Management Science    2024, 32 (5): 1-12.   DOI: 10.16381/j.cnki.issn1003-207x.2021.0027
    Abstract528)   HTML49)    PDF(pc) (794KB)(1137)       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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    Researchon Multi-class Sentiment Classification Based on BERT and Dynamic Ensemble Selection
    Zhongliang Zhang,Qinjun Fei,Yuyu Chen,Xinggang Luo
    Chinese Journal of Management Science    2024, 32 (6): 140-150.   DOI: 10.16381/j.cnki.issn1003-207x.2021.1159
    Abstract481)   HTML32)    PDF(pc) (2270KB)(735)       Save

    To handle semantic deficiency of text feature vector extracted by classic methods and the issue of multi-classsentimentclassification in the text emotion recognition task, a novel multi-class sentiment classification strategy based onBidirectional Encoder Representations from Transformers (BERT) and dynamic ensemble selection (DES) is proposed. First, BERT is used to vectorize the text.Then, the OVO strategy is used to divide the multi-class sentiment classification problem into multiple binary classification sub-problems.Next, the dynamic ensemble selection strategy is developed to construct binary classifier for dealing with each sub-problem.Finally, the final prediction result is obtained based on the aggregation strategy. A public movie review data set is employed to carry out the experimental analysis. The experimental results indicate that(1) the BERT model is helpful in improving the multi-class sentiment classification performancewith respect to these traditional methods, namely TFIDF and Wor2Vec, (2) it is effective to use the DES strategy for dealing with each sub-problem in multi-class sentiment classification, and (3)the performance of the proposed method is also significantlybetter than that of the existing well-known methods for multi-class sentiment analysis.

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    Marketing Transformation in the Age of Artificial Intelligence
    Feng Shi, Yang Yang, Yun Yuan, Jianmin Jia
    Chinese Journal of Management Science    2025, 33 (1): 111-123.   DOI: 10.16381/j.cnki.issn1003-207x.2024.1913
    Abstract451)   HTML67)    PDF(pc) (908KB)(1029)       Save

    The rapid development of artificial intelligence (AI) has catalyzed new corporate practices and marketing models, transforming the way companies interact with consumers and revolutionizing the theory and practice of marketing science. To reveal the full picture of this transformation, the gradual three-stage process of AI-driven marketing transformation is reviewed and mapped out, spanning from its emergence and development to its deepening, based on representative literature in the interdisciplinary field of AI and marketing science in recent years. A theoretical analysis framework of "AI Cognition—AI Empowerment—AI Interaction—AI Integration" is then proposed. Finally, combined with this framework, future research directions are outlined, including constructing more explanatory AI adoption models, developing fair AI pricing algorithms, exploring the psychological mechanisms of consumers in AI interactions, and designing effective human-machine collaborative management mechanisms, with the aim of promoting theoretical development and practical applications in the interdisciplinary field of artificial intelligence and marketing.

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    Cooperation Modes and Decision Optimization in Live Streaming Commerce
    Yongwei Cheng
    Chinese Journal of Management Science    2024, 32 (5): 297-306.   DOI: 10.16381/j.cnki.issn1003-207x.2022.2589
    Abstract437)   HTML18)    PDF(pc) (1271KB)(865)       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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    Review of Research on Economics and Management Based on Generative Artificial Intelligence
    Xiangpei Hu, Yaxian Zhou
    Chinese Journal of Management Science    2025, 33 (1): 76-97.   DOI: 10.16381/j.cnki.issn1003-207x.2024.1390
    Abstract432)   HTML43)    PDF(pc) (2541KB)(1034)       Save

    Using 87 high-quality Chinese management journals and 1177 high-quality English management journals as the basis for literature retrieval, a bibliometric analysis is conducted on research related to Generative Artificial Intelligence in Economics and Management. The analysis covers journal distribution, author and institution collaboration networks, and keyword-based literature analysis, organized according to the four subfields under the Management Science Department of the National Natural Science Foundation of China: Management Science and Engineering, Business Administration, Economic Sciences, and Macro Management and Policy. The findings include: 1) There are differences between Chinese and English-language literature. Chinese literature focuses on information resource management and library and information science. Collaborative relationships are primarily influenced by disciplinary, institutional, and geographical similarities. In contrast, English literature spans a wider range of journals, and institutions. However, consistent research outputs from cross-institutional collaboration have yet to emerge. Strengthening cross-disciplinary, cross-regional, and cross-institutional collaboration remains a need for both Chinese and English research. 2) In both Chinese and English literature, studies are mainly concentrated in the subfields of Macro Management and Policy, as well as Management Science and Engineering, with a strong emphasis on empirical and applied research. Business Administration and Economics have relatively fewer studies, and literature focusing on generative artificial intelligence technologies and associated risks is also limited. Furthermore, English-language literature exhibits a broader range of research themes and application areas than Chinese literature, with higher research volumes and greater thematic focus. Future research should emphasize the integration of generative artificial intelligence with management tools, theoretical theories, and complex management scenarios, as well as on addressing specific management research paradigms.

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    Risk Science: A New Interdisciplinary Science
    Jianping Li, Weixuan Xu, Dengsheng Wu
    Chinese Journal of Management Science    2025, 33 (1): 98-110.   DOI: 10.16381/j.cnki.issn1003-207x.2024.1264
    Abstract425)   HTML61)    PDF(pc) (699KB)(766)       Save

    As an important technical tool in today’s economy and society, risk analysis has shown its significant application value in many fields such as energy, finance, natural disasters and emergency response. However, risk analysis has not been widely regarded as an independent science, and its related theories and methods are still scattered in different subject areas, lacking systematic integration and systematic development. In addition, the traditional risk analysis method based on probability and loss modeling is relatively narrow, and it is difficult to fully and accurately reflect the diversity and complexity of risks in modern society and system. In view of this, based on the new ideas and theories emerging in the field of risk analysis in recent years, the construction of a new interdisciplinary science of “risk science” is advocated. Through in-depth analysis of the connotation and development process of risk science, a systematic framework system of risk science is put forward, and the research progress and future trends are summarized in six sub-fields of risk understanding, risk identification, risk assessment, risk perception, risk communication and risk control. It aims to integrate cutting-edge risk management concepts, integrate knowledge and methods in the field of risk analysis and management, and then promote the construction of a more complete and systematic risk management system to cope with the increasingly complex and changeable risk challenges in this paper.

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    Selection of Hybrid Channel Recycling Modes and Carbon Emission Reduction Decisions for the Electric Vehicle Battery Manufacturer
    Chuan Zhang,Yuxin Tian,Mengyu Cui
    Chinese Journal of Management Science    2024, 32 (6): 184-195.   DOI: 10.16381/j.cnki.issn1003-207x.2022.2221
    Abstract423)   HTML16)    PDF(pc) (2630KB)(879)       Save

    The rapid adoption of electric vehicles (EVs) in China has led to a substantial number of power battery retirements. Establishing an efficient recycling mechanism for these spent power batteries is of pivotal importance. It delves into the selection of recycling modes and the determination of carbon abatement strategies within a closed-loop supply chain (CLSC) governing EV power batteries, operating under the carbon cap-and-trade policy. Four hybrid channel recycling modes are proposed: (1) joint recycling involving the manufacturer and the retailer; (2) joint recycling involving the manufacturer and the third-party recycler; (3) joint recycling involving the retailer and the third-party recycler; (4) joint recycling involving the manufacturer, the retailer, and the third-party recycler. The Stackelberg game model is employed to derive optimal pricing decisions, maximum profits, and carbon emission reduction strategies for different modes. A comparative analysis of optimal profits across distinct modes is performed. In addition, an exhaustive exploration of the influences of pivotal parameters on equilibrium outcomes is conducted.The results show that the optimal carbon emission reduction level for the manufacturer decreases with increasing initial carbon emissions, decreases with a higher carbon emission reduction investment coefficient, and exhibits an initial rise followed by a decline and then another rise with increasing unit carbon trading price. When the sensitivity coefficient of the recycling price exceeds a specific threshold and the competition coefficient of recycling falls below another threshold, the optimal recycling mode for the manufacturer involves joint participation of the manufacturer, the retailer, and the third-party recycler. Otherwise, the optimal recycling mode for the manufacturer includes joint participation by the manufacturer and the retailer, or by the manufacturer and the third-party recycler. The total collecting quantity of retired power batteries in the CLSC diminishes as the competitive coefficient of recycling channels increases, while it rises with an increase in the consumer sensitivity coefficient to recycling prices. It contributes to enhancing the power battery recycling and utilization system for EVs in China, enriching the existing research pertaining to CLSCs for EV power batteries under carbon policies, thereby providing substantive insights for operational decision-making of EV battery manufacturers.

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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
    Chinese Journal of Management Science    2024, 32 (5): 122-132.   DOI: 10.16381/j.cnki.issn1003-207x.2021.0778
    Abstract414)   HTML14)    PDF(pc) (871KB)(617)       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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    Evolutionary Game Analysis of Government and Enterprises Carbon-reduction under the Driven of Carbon Trading
    Guochang Fang,Yu He,Lixin Tian
    Chinese Journal of Management Science    2024, 32 (5): 196-206.   DOI: 10.16381/j.cnki.issn1003-207x.2021.1401
    Abstract400)   HTML19)    PDF(pc) (872KB)(706)       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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    Research on Government Subsidy Model of Dual-sales Channel Closed-loop Supply Chain
    Wenbin Wang,Ye Liu,Shiyuan Quan,Luosheng Zhong,Jia Lv
    Chinese Journal of Management Science    2024, 32 (7): 258-269.   DOI: 10.16381/j.cnki.issn1003-207x.2021.1474
    Abstract388)   HTML17)    PDF(pc) (2684KB)(513)       Save

    In today’s society, a large number of waste electrical and electronic products increase dramatically. If these waste products cannot be effectively recycled, it will not only bring greater harm to the environment, but also make the production cost of the enterprise high. The Chinese government implements a subsidy policy to encourage the development of the recycling industry. Although the government subsidy policy has a positive effect on the recycling of waste electronic products by enterprises, the government is facing the problem that the subsidy amount cannot make ends meet. How to choose the subsidy object to achieve the optimal benefit of the limited subsidy amount is urgently needed to study.Therefore, a closed-loop supply chain game model with different government subsidies is constructed under dual sales channels composed of a manufacturer, a retailer, and a recycler, and the government’s choice of different subsidy objects on supply chain members’ decisions, supply chain members’ profits, consumption surplus and the impact of social welfare is analyzed. The correctness of the conclusions is verified through data simulation on the basis of reference to relevant literature and enterprise research.Research shows:(i) the best government subsidy pattern is that simultaneously subsidize manufacturers and collectors, allocate approximately equal subsidies to both manufacturers and collectors, and appropriately implement as many subsidies as possible for unit product when consumer surplus and social welfare are optimal; (ii) there is a unique subsidy ratio that maximizes consumer surplus, manufacturers and retailers profit, and product prices when unit product subsidy is fixed. Moreover, the profit of collectors and the collection rate are higher than the situation where the government subsidizes manufacturers separately and without government subsidies under this ratio; (iii) when the market size is greater than the threshold, the government subsidizing manufacturers and collectors at any ratio can reduce the direct sales price, the wholesale price and retail price, and increase the collection rate; (iv) improving the intensity of competition between dual sales channels and expanding the remanufacturing cost advantageare both beneficial to increase the collection rate.Some management suggestions are provided for the government, manufacturing companies and waste product recycling companies. For the government, it is necessary to comprehensively consider the market scale and recycling scale of the product when choosing subsidies. For manufacturers, it is possible to reduce the cost of product remanufacturing through technological innovation or improved management. For recyclers, they can reduce recycling costs, increase the recycling rate of waste products, and increase recycling profits through technological innovation and narrowing the scope of business operations.

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    Overnight Information and Option Pricing Model
    Sicong Cheng,Tianyi Wang
    Chinese Journal of Management Science    2024, 32 (9): 1-10.   DOI: 10.16381/j.cnki.issn1003-207x.2021.0905
    Abstract388)   HTML29)    PDF(pc) (571KB)(507)       Save

    The fact that most assets are not traded around the clock raises a natural decomposition of the daily return. The intraday return covers the price movement between open and close, while the overnight return covers the price movement between the previous close and current open. Previous literature documented that overnight information has a significant impact on financial activities. It can help explain the market anomalies and improve the volatility forecasting accuracy. However, there is little research investigating the effects of option pricing. In this paper, the daily log returns are decomposed into intraday and overnight components and a new model that extends the Heston-Nandi GARCH framework to a bivariate structure is proposed to describe the two return processes simultaneously. Such decomposition is different from those with high-frequency data (such as semivariance-based good-bad volatility framework) as we only require daily frequency data. Using the variance-dependent pricing kernel, a closed-form option pricing formula is derived and the pricing performance of SSE 50 ETF options is assessed. The empirical results using SSE 50 ETF options from 2015 to 2019 show that distinguishing the overnight component from daily returns can potentially reduce the pricing errors, both in-sample and out-of-sample. The results enrich the current literature on return decomposition by adding a piece of option pricing evidence and call for more research on option pricing in this new direction.

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    Bayesian Equilibrium Analysis with Information Asymmetry and Credit Guarantee
    Xiang Liu,Zhaojun Yang,Suhua Liu
    Chinese Journal of Management Science    2024, 32 (7): 1-10.   DOI: 10.16381/j.cnki.issn1003-207x.2021.1522
    Abstract384)   HTML24)    PDF(pc) (2178KB)(537)       Save

    Micro-, Small and Medium-sized Enterprises (MSMEs) are the backbone of science and technology invention and social productivity improvement, which are crucial to development strategies of a country. The 2019 central economic work congress of China delivered five signals, one of which is to increase the support for high-tech enterprises. Financing for MSMEs is difficult and expensive over the world. The fundamental reason lies in asymmetric information between borrowers and lenders on investment profitability. Although there are many theories of credit guarantee and corporate finance in the literature, there is no academic research to quantify how information asymmetry impacts on the existing credit guarantee methods, say the fee-for-guarantee swaps (FGSs), equity-for-guarantee swaps (EGSs) and option-for-guarantee swaps (OGSs). A single-period model for an MSME is developed to start a project. The enterprise must borrow to start the project from a bank after entering into an FGS, EGS or OGS agreement with an insurer. A credit guarantee pricing method is proposed. Bayesian game theory is used to characterize FGSs, EGSs and OGSs. The novelties of the paper are summarized as follows. The degree of the negative influence of information asymmetry on three different guarantee swaps is different. The effect is highest for OGSs, the second highest for EGSs and the lowest for FGSs agreement. High-profit enterprises may transfer their part of profits to insurers instead of low-profit ones to prevent the imitation of low-profit enterprises. Surprisingly, it is possible that the net present value of a high-profit enterprise would increase with the investment cost. Information asymmetry does not surely lead to the loss of social welfare.

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    Platform Supply Chain Management: New Challenges and Opportunities
    Weihua Liu, Zhe Li, Shangsong Long, Yugang Yu, Baofeng Huo, Yanjie Liang
    Chinese Journal of Management Science    2025, 33 (1): 165-181.   DOI: 10.16381/j.cnki.issn1003-207x.2024.1643
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    The continuous emergence of new-generation information technology has driven the deep integration of supply chain and platform economy, and supply chain management has stepped into a new stage of platform supply chain. The development of platform supply chain, while driving the evolution and transformation of business model, is also reshaping the boundaries between different market participants, which raises numerous challenges for academics and practitioners. Despite extensive research on platform supply chain has been conducted in recent years, a systematic literature review on this field is still lacking, especially regarding how to address the complex challenges in platform supply chain management and how to seize new opportunities in future development.Driven by reality and theoretical needs, a combination of descriptive statistics and content analysis is adopted to conduct a comprehensive and systematic review of the relevant research in the field of platform supply chain management in the core set of Web of Science and CNKI database from 2013 to 2023. Through quantitative analysis of literature from the past decade, the research hotspots and development trends in this field are identified, and further content analysis is conducted from both problem-oriented and method-driven perspectives. Based on the logic of “why-what-how”, the issues of platform supply chain management are summarized that have been addressed in the past decade from three angles: “why promote the construction of platform supply chain-what are the obstacles to promoting the construction of platform supply chain-how to promote the construction of platform supply chain”. The research challenges are then discussed, and opportunities for future research are identified.It is found that the research challenges in platform supply chain management include the complexity of collaboration and integration, the dual dilemmas of technology and data, the pressure of ecological design and innovation, and the governance dilemma and regulatory issue. Based on these findings, new opportunities of platform supply chain management in the future are proposed from four aspects: new environment, new technology, new ecology and new governance, which are platform supply chain collaborative operation under complex environment, platform supply chain operation decision-making considering technology empowerment, platform supply chain operation mode innovation under ecological background, and platform supply chain governance with multi-subject participation. It is hoped that new perspectives for theoretical innovation and deeper research in academia are provided and reference and practical guidance are offered for enterprises and organizations in coping with real-world challenges.

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    Digital Empowerment Strategies of E-commerce Platform and Competitive Merchants
    Qiang Hu,Jiaping Xie,Guangsi Zhang
    Chinese Journal of Management Science    2024, 32 (6): 46-56.   DOI: 10.16381/j.cnki.issn1003-207x.2021.1414
    Abstract370)   HTML17)    PDF(pc) (2455KB)(619)       Save

    With the development of digital economy, digital construction has attracted attention from all walks of life. The government is accelerating the digital reform to improve the modernization of government governance, and enterprises are accelerating digital transformation to seek a living space in a new market environment. Digital empowerment can improve the operational efficiency of enterprises, and better serve consumers and create greater business value through demand creation, value co-creation and supply chain reconstruction. For example, Alibaba’s “Business Staff” data services, more than 30 million merchants have enjoyed the data services brought by Alibaba’s big data technology. Amazon’s “Selling Coach” allows merchants to track several key indicators on Amazon.com, including sales, traffic, and conversion rates. Therefore, it is of practical significance to study how e-commerce platforms implement digital empowerment strategies and whether the merchants choose to accept paid digital empowerment services.Two competitive merchants settled on an e-commerce platform are considered in this paper, and a digital empowerment strategy that is a fee-based data service provided by the e-commerce platform to merchants is studied. The Hotelling model is used to characterize the market demand, and the Stackelberg game models between the e-commerce platform and the competitive merchants are constructed in four scenarios: (i) No digital empowerment (ND); (ii) Digital empowerment is only accepted by the relatively superior merchant (DH); (iii) Digital empowerment is only accepted by the relatively inferior merchant (DL); (iv) Digital empowerment are accepted by both merchants (DD). According to the game equilibriums, the implementation plan of the digital empowerment strategy of the e-commerce platform is discussed, and the two merchants’ choices of the digital empowerment service are analyzed. Finally, the conclusions are verified by numerical examples, and the impacts of important parameters on the profits of all parties and the implementation and selection of the digital empowerment strategy are intuitively reflected.In this paper, the main conclusions and managerial implications are summarized as follows: (i) Whether merchants decide to accept the digital empowerment service depends on the charging standard, and the level of the charging standard also affects the Nash equilibrium of the two competitive merchants. The game equilibrium conditions of only the relatively superior merchant and both merchants choosing to accept the digital empowerment service, and the conditions of both merchants choosing not to accept the digital empowerment service are obtained. (ii) The e-commerce platform can determine the digital empowerment scenario based on the principle of profit maximization, and the optimal charging standard of digital empowerment service and the e-commerce platform’s digital empowerment level under each digital empowerment scenarios are obtained. Based on this, the e-commerce platform carries out strategic investment in the field of big data and implementation of digital empowerment strategies. (iii) The degree of difference between the superior and inferior merchants in the market (mainly refers to the difference between the level of data application by merchants and the unit production cost of products) is more conducive to promoting e-commerce platforms to invest in the field of big data, relatively speaking, e-commerce platforms prefer digital empowerment for superior merchants to inferior merchants, and expect that the quality of merchants is different, rather than convergent. For example, the quality of merchants settled on e-commerce platforms such as JD.com and Tmall.com is diversified. (iv) To a certain extent, the digital empowerment strategy leads to intensifying the market competition. As far as the relatively inferior merchants are concerned, they need to improve their level of data utilization and reduce the unit production cost to narrow the gap with the superior merchants, thereby enhancing their competitiveness in the market.The e-commerce platform’s digital empowerment strategy and competitive merchants’ choices of the digital empowerment service are explored, which can guide the ecommerce platform to implement digital empowerment strategies and help guide the formulation of charging standards and the investment intensity of digital empowerment. In addition, a reference for whether merchants choose to accept the digital empowerment service is provided, including relatively superior and inferior merchants. It enriches the theory of platform-based operations and supply chain management for this paper.

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    Research on Optimization Strategy of Food Delivery Crowdsourcing Delivery Considering Order Preference
    Xingguang Chen,Xinyu Li,Luqiang Cheng
    Chinese Journal of Management Science    2024, 32 (6): 86-97.   DOI: 10.16381/j.cnki.issn1003-207x.2021.1262
    Abstract363)   HTML11)    PDF(pc) (2648KB)(506)       Save

    With the gradual development of the sharing economy model of food delivery, the current food delivery has changed from the original stage of market expansion to the connotative development stage of improving service quality. The mobile crowdsourcing distribution model in the current mainstream food delivery is focused on, and the optimization of the takeaway crowdsourcing distribution strategy is discussed considering the order destination preference. Firstly, three models are established that consider the service speed of the distribution system, the total income of the distributor and the waiting time of the customer as the optimization goals. Secondly, a calculation example is designed to verify the model. According to the order matching range radius, the ideal order distribution rate and the delivery staff's basic income and other parameters, the optimization strategy of the delivery system to minimize the waiting time of customers and maximize the income of the delivery staff is discussed. The simulation results show that the model proposed in this paper based on queuing theory can better describe the characteristics of actual food delivery crowdsourcing, and the relevant conclusions have theoretical value and practical significance in the operation and management of the food delivery industry.

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    Research on Pricing Strategy of Competitive E-commerce Platforms Considering Return Freight Insurance
    Jizhou Zhan,Yaqi Jin
    Chinese Journal of Management Science    2024, 32 (5): 325-334.   DOI: 10.16381/j.cnki.issn1003-207x.2021.1736
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    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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    Research on the Influence of Carbon Trading on Carbon Emission Reduction Effect and Coordination Mechanism under Carbon Quotas
    Biao Li,Xiqiang Xia,Qiuyue Li
    Chinese Journal of Management Science    2024, 32 (8): 250-260.   DOI: 10.16381/j.cnki.issn1003-207x.2023.0576
    Abstract358)   HTML16)    PDF(pc) (852KB)(473)       Save

    In the face of escalating global concerns about climate change, industries ubiquitously confront the daunting task of mitigating their carbon footprints. The manufacturing sector, a pivotal arena for the attainment of the “dual carbon” objectives, is experiencing an exigent demand for holistic emission curtailment throughout its supply chain. This investigation elucidates the ramifications of carbon quota trading in refining carbon mitigation methodologies and their synergistic frameworks. Leveraging insights from carbon quota trading, models are formulated under a decentralized decision-making paradigm, wherein component vendors and manufacturers undertake emission reductions either in isolation or collaboratively. A centralized emission reduction decision-making model is also proposed. The carbon reduction magnitudes, product price structures, sales trajectories, and supply chain advantages are juxtaposed across these divergent emission curtailment models. Predicated on the intensity of emission abatement and value generation, the quintessential model for emission reduction within the ambit of carbon quota trading is indentified.Drawing on the example of a tire manufacturing supply chain, Company A (an upstream component purveyor) delivers essential rubber additives and adjuncts requisite for Company B's (a downstream tire producer) manufacturing processes. Collectively, this firm' strategic initiatives within the supply chain facilitate pronounced carbon reduction in products. The findings underscore that galvanizing supply chain stakeholders to coalesce via profit-sharing and cost-allocation agreements not only averts losses stemming from game-theoretic dynamics but also accentuates the scale of emission abatement and amplifies supply chain yields. Such insights proffer invaluable strategic direction for government entities striving to expedite emission reduction trajectories in the manufacturing domain, concurrently furnishing a theoretical scaffold for supply chain businesses aspiring for win-win synergies.The primary findings of the research are as follows (1) Within the carbon quota trading framework, a centralized decision-making approach engenders a more pronounced product emission diminution than its decentralized counterpart. Notably, the concurrent emission abatement strategy within the decentralized model manifests the most substantial product emission curtailment. (2) Emission abatement endeavors spearheaded by both upstream and downstream entities in the supply chain augment product turnover and enhance the cumulative supply chain yield. Products' turnover and supply chain yields under a centralized framework conspicuously eclipse those under decentralized decision-making. (3) Pertaining to carbon quota trading, supply chain entities can actualize an optimal coordination blueprint intrinsic to the centralized model by mutually committing to emission reductions and initiating profit-sharing and cost-allocation compacts.

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