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    Research on Human-machine Integration Complex Social System
    WANG Hong-wei, LI Jue, LIU Jian-guo, FAN Ying, MA Liang, HUO Hong, LIU Zuo-yi, DING Lie-yun
    Chinese Journal of Management Science    2023, 31 (7): 1-21.   DOI: 10.16381/j.cnki.issn1003-207x.2023.07.001
    Abstract2586)      PDF(pc) (1642KB)(2721)       Save
    The deepening of the new round of scientific-technological revolution is profoundly affecting and transforming the way of social living and production. The social system is evolving into a complex system coupled with human social space, information systems, and the physical environment. In the social system, actors, social relations, social structure, and social functions are profoundly changing. Human beings are entering a new social form characterized by the integration of human and machine. Such changes have brought significant challenges to the understanding, research, and governance of social systems. The definition of the human-machine integration social system is expounded from the perspective of the social system theory. It analyzes the unique connotation of human-machine integration complex social system from the aspects of social constituent subjects and structures, communication and media, and social differentiation and evolution. On this basis, the basic problems that need to be solved urgently in the research of human-machine integration complex social systems are proposed: (1) Human-machine collaboration in human-machine integration complex social systems; (2) Social networks in the environment of human-machine integration; (3) Emergence mechanism and evolution law of human-machine integration complex social system. Finally, aiming at the difficulties faced by previous social science research methods in solving the integrity problem of complex social systems, a research paradigm of complex social systems based on the system theory is proposed.
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    Artificial Intelligence and Management Transformation
    YANG Shan-lin, LI Xiao-jian, ZHANG Qiang, JIAO Jian-ling, YANG Chang-hui
    Chinese Journal of Management Science    2023, 31 (6): 1-11.   DOI: 10.16381/j.cnki.issn1003-207x.2023.06.001
    Abstract2298)      PDF(pc) (2837KB)(2398)       Save
    Since the advent of deep learning, artificial intelligence has made tremendous progress, gradually moving from pure academic research to large-scale deployment. In particular, a series of application-level AI content generation algorithms such as text generation, image generation, and 3D model generation emerged in 2022, indicating that AI has first acquired the ability to produce digital content and is gradually breaking through many barriers, such as logical reasoning and common sense cognition, moving towards general AI. Based on a review of the development history and recent trends in AI, it focuses on exploring the impact of AI technology on the research paradigms of the natural and social sciences in this paper, analyzing the development laws of AI technology itself and its integration with domain-specific sciences. Finally, the transformative impact of AI on the management is analyzed.
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    Good Shopping DecisionsandBad Shopping Decisions: Research on the Quality Issues and Governance of Internet Celebrity Live Marketing
    Yan-lu GUO,Gong-li LUO,Gui-sheng HOU,Xiao-tong WANG
    Chinese Journal of Management Science    2023, 31 (10): 162-174.   DOI: 10.16381/j.cnki.issn1003-207x.2020.1937
    Abstract1184)   HTML89)    PDF(pc) (1157KB)(2346)       Save

    With the development and expansion of short video live broadcast platforms, online celebrity live-streaming has become a new form of consumer shopping. However, in this process, the problems of poor quality of products with online celebrities and difficulty in protection have also emerged. Based on this background, a tripartite evolutionary game model is used to study the tripartite strategy selection and evolution of internet celebrities, short video live broadcast platforms, and consumers, and further discusses the impact of changes in live broadcast internet celebrities’ risk attitudes on their efforts to selling goods and select products. The innovations of this article are: ①The dual attributes of consumers and the live broadcast platform are considered. ②The benefits that consumers get from online celebrity products are divided into emotional benefits and functional benefits, which is more in line with the existing empirical evidence and facts, and the conclusion proves that emotional benefits will produce more “negative action” in certain situations. ③In the existing evolutionary game literature, few scholars discuss in detail the changes and transitions of equilibrium points under different parameter conditions, while parameter changes which leads to the transition of the equilibrium point often contains profound policy enlightenment.④The risk attitudes of Internet celebrities on the efforts to bring goods is also discussed,which further explains the causes of the quality problems of products brought by Internet celebrities. In addition, it is also found an interesting insight: consumers' strategy choices when facing the quality trouble of online celebrity live broadcast products will be affected by product types. The higher the functional benefit of the product, the more powerful consumers' motivation to defend their rights. This means that not all products are suitable for online celebrity live broadcast mode for sales.It is found that as the functional benefits that consumers obtain from online celebrity products increase, consumers are more inclined to choose active accountability, and as emotional benefits increase, consumers are more inclined to choose passive accountability, this kind of virtual intimacy on the emotional benefits brought by the products partly explain the phenomenon of the current proliferation of online celebrity product quality problems. Secondly, the influence of basic income parameters on the equilibrium state is far more significant than the influence of coefficient parameters. This should be the focus of supervision. Moreover, consumers’ strategy will be affected by product types when they face the quality problems of online celebrities’ live streaming products. The higher the product’s functional benefits, the greater the motivation for consumers to defend their rights. Finally, the risky attitudes of live streaming internet celebrities will affect their attitudes of product selection. And as the effort to bring goods, risk-averse Internet celebrities' efforts to sell goods and select products are lower than those under certain circumstances.

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    Blockchain-Based Dual-Channel Supply Chain Pricing Decision and Online Channel Selection Strategy
    LIANG Xi, XIAO Jin-feng
    Chinese Journal of Management Science    2023, 31 (5): 29-38.   DOI: 10.16381/j.cnki.issn1003-207x.2020.1755
    Abstract874)      PDF(pc) (1609KB)(2011)       Save
    Blockchain technology is widely used in various industries. In this paper, the application of blockchain technology to product certification in the supply chain can reduce the certification time and fidelity. In the two dual channel supply chain systems of online direct selling and online distribution, the Stackelberg game in which the manufacturer is the leader and the other participants are followers is considered. The sensitive coefficient of the consumer’s time for product inspection and evaluation, the false probability of the inspection result and the unit verification fee of the blockchain are introduced. The pricing and channel selection strategies of four dual channel supply chains are compared and analyzed. The results show that: when using the blockchain technology, the manufacturer’s profit under the direct selling mode is higher than that of the distribution mode, the traditional retailer’s profit under the direct selling mode is lower than that of the distribution mode, and the total profit of the supply chain under the direct selling mode is higher than that of the distribution mode; in the direct selling mode, the manufacturer’s profit, the traditional retailer’s profit and the total profit of the supply chain are higher than that of the distribution mode. In the distribution mode, when the fixed fee for manufacturers to introduce blockchain technology is small, the profits of manufacturers, traditional retailers, online retailers and the total profits of supply chain with blockchain technology are higher than those without blockchain technology.
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    Research on Government Subsidy Strategy of Low-carbon Supply Chain Based on Block-chain Technology
    Ling-rong ZHANG,Bo PENG,Chun-qi CHENG
    Chinese Journal of Management Science    2023, 31 (10): 49-60.   DOI: 10.16381/j.cnki.issn1003-207x.2020.2362
    Abstract971)   HTML95)    PDF(pc) (907KB)(1905)       Save

    With the continuous progress of China's economy and society, green development has become a national strategy, and carbon emission reduction is an important measure. The government can promote the investment of enterprises' emission reduction technology and increase social welfare through moderate low-carbon subsidies to enterprises. The introduction of block-chain technology into the low-carbon supply chain can improve the coordination degree of low-carbon decision-making among the main bodies of the supply chain and promote the emission reduction of enterprises. Therefore, it is of great significance to study the government subsidy strategy of low-carbon supply chain based on block-chain technology. In this paper, a two-level low-carbon supply chain composed of a manufacturer and a retailer is taken as the research object, and the government subsidy strategy of the low-carbon supply chain is taken as the research topic. The government invests in the construction of the application platform of block-chain technology, and the supply chain enterprises pay to use the block-chain technology. Under this background, considering consumers' low-carbon preference and green trust, this paper set up before and after the application block chain technology under R&D investment subsidy policy or output subsidy policy of these four situations of three stages Stackelberg game models, in which the government takes the lead and manufacturers and retailers follow and the government to the social welfare maximization as the goal, manufacturers and retailers in order to maximize their own interests as the goal, through comparing the four kinds of situations of the optimal rate of social welfare, carbon reduction and low carbon product production, discusses the government low carbon subsidies strategy of optimal problem. And the validity of the results is verified through the analysis of examples. The results show that when the product of consumers' low-carbon preference coefficient and green trust coefficient is greater than a certain fixed value, the government can obtain higher social welfare through output subsidies, and promote enterprises to reduce emissions more effectively. Governments have been able to boost demand for low-carbon products through output subsidies. When the cost coefficient of emission reduction approaches infinity, the demand for low-carbon products when the government implements output subsidies is 4 times that when the government implements R&D investment subsidies. When the single-cycle cost sharing of block-chain platform and the unit cost of enterprises' application of block-chain technology are less than a certain threshold, the government's construction of block-chain platform can obtain higher social welfare, promote enterprises' emission reduction and improve consumers' demand for low-carbon products. Therefore, the government should increase investment in science and technology, and to make efforts to reduce the block chain platform construction cost and prolong the cycle of block chain platform, for low carbon green products to create a fair, just and open market environment, and control technology of enterprise application block chain unit cost within a reasonable range, encourage enterprises to actively application block chain technology, in order to obtain higher social welfare.

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    Heterogeneous Institutional Investors and Corporate Reputation:Social Responsibility: Intermediate Effect Test Based on Corporate Social Responsibility
    SONG Yan, LIU Yue-ting, ZHANG Lu-guang
    Chinese Journal of Management Science    2023, 31 (7): 103-114.   DOI: 10.16381/j.cnki.issn1003-207x.2021.0070
    Abstract469)      PDF(pc) (1356KB)(1803)       Save
    With the development of the economy and the continuous improvement of the capital market, the rapid development of institutional investors has been attracted more and more attention. Institutional investors have many advantages such as capital, information and expertise, so they can participate more in the daily operation and decision-making of the company, so people have high expectations of them in supervising the development of the invested enterprises and improving the capital market. At the same time, as the economic structure of our country is upgraded and developed, the focus of development is transformed into quality and sustainability, and all kinds of problems in the process of deepening the reform of enterprises are also increasingly prominent. Especially in the pandemic of Covid-19, the quasi-insurance role of corporate social responsibility has been fully confirmed, and the role of corporate social responsibility and corporate reputation in crisis is becoming more and more significant, so exploring the relationship between heterogeneous institutions and corporate reputation is worth studying.
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    Hybrid Air Quality Early Warning System Based on XGBoost and ELM: A Case Study of Nanjing
    GAO Xiao-hui, ZHOU Kun, LI Lian-shui
    Chinese Journal of Management Science    2023, 31 (5): 269-278.   DOI: 10.16381/j.cnki.issn1003-207x.2020.1780
    Abstract401)      PDF(pc) (1449KB)(1710)       Save
    With the frequent occurrence of air pollution in recent years, it is urgent to establish an effective air quality early warning system. However, most of the existing researches neglect the importance of data preprocessing and air quality evaluation in the design of early warning system, leading the lack of data mining and the deviation of prediction results. A hybrid air quality early warning system is proposed, which consists of three modules namely data preprocessing, prediction and air quality evaluation, respectively. According to the characteristics of the original data, the classical empirical mode decomposition (EMD) is used to decompose the training set. The Lempel Ziv complexity algorithm is applied to identify the sequence after decomposing as high frequency and low frequency components. The data input matrix is obtained according to the average mutual information (AMI). In order to improve the prediction accuracy and stability, the extreme learning machine (ELM) is used to predict the low-frequency sequences. Extreme gradient boosting (XGBoost) algorithm is applied into high-frequency sequences with added multiple factors. Finally, in the air quality assessment module, the primary pollutants of each day is confirmed. In this paper, Nanjing air quality is taken as an example. The results show that the prediction method has higher accuracy and stronger stability than other single models. The evaluation module also provides certain air quality information, forming a complete early warning system and providing scientific basis for decision makers to control air pollution.
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    A Study on the Relationship between Liquidity Shock and Stock Return in Chinese A-Share Market
    KANG Wen-jin, ZHANG Kang
    Chinese Journal of Management Science    2023, 31 (7): 68-77.   DOI: 10.16381/j.cnki.issn1003-207x.2021.0447
    Abstract469)      PDF(pc) (1015KB)(1653)       Save
    Previous studies have shown that liquidity is an important pricing factor in stock market. Since there exists substantial time-series variation in stock liquidity, the change of liquidity (i.e., liquidity shock) could also have impact on stock return. Because of market friction, the information contained in the change of liquidity may not be fully reflected in the contemporaneous stock return in the first time. Therefore, it is interesting to examine whether liquidity shock can predict stock return in Chinese A-share market.
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    Research on Collaborative Pricing Strategy of Multi-mode Shared Mobility Platform with Consideration of Passenger Utility
    Xiang Li,Yanan Li,Hongguang Ma
    Chinese Journal of Management Science    2024, 32 (7): 172-180.   DOI: 10.16381/j.cnki.issn1003-207x.2021.1370
    Abstract321)   HTML9)    PDF(pc) (1994KB)(1652)       Save

    With the rapid growth of personalized and diversified travel demand, and the rapid development of technical means such as Internet, big data and mobile payment, the shared mobility platform is constantly transforming and upgrading, and aims at providing multi-mode services for passengers.In busy urbantransportation networks, choosing a suitable and efficient transport mode is important. Under this background, how to establish collaborative pricing strategies for the multi-mode services has been a pain point, which seriously handicaps the development of the platform.For a shared mobility platform with customized bus service and ride-hailing service, collaborative pricing models for four scenarios, including “driver-owned ride-hailing + centralized pricing”, “driver-owned ride-hailing + decentralized pricing”, “platform-owned ride-hailing + centralized pricing” and “platform-owned ride-hailing + decentralized pricing”, with the consideration of the impact of price, waiting time and ride comfort on passenger utility. The corresponding optimal pricing strategies are proved. The numerical results show that for customized bus service and ride-hailing service, the better one between centralized pricing and decentralized pricing with driver-owned ride-hailing is determined by the initial passengers share of customized bus service and the commission to driver’s income charged by the platform; the better one between centralized pricing and decentralized pricing with platform-owned ride-hailing is determined by the initial passengers share of customized bus and the cost per ride-hailing order. In addition, ride comfort is an important factor for passenger utility. Ignoring ride comfort will make customized bus service raise pricing, which reduces the number of passengers and the profit of customized bus service, and ultimately affects the total profit of the platform.The contribution of this paper to the theory and practice of collaborative pricing of diversified shared mobility platform includes the following three aspects.First, the optimal pricing strategies of ride-hailing service and customized bus service under different platform operation modes and pricing methods are deduced.Secondly, the impacts of pricing mode on platform profit, customized bus service profit and ride-hailing service profit under different operation modes are analyzed.Thirdly, it is revealed that ride comfort is an important factor affecting passenger utility.

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    Pricing and Green Input Decisions of a Competitive Supply Chain with Consumers’ Product Preference and Different Channel Powers
    CHEN Ke-bing, KONG Ying-qi, LEI Dong
    Chinese Journal of Management Science    2023, 31 (5): 1-10.   DOI: 10.16381/j.cnki.issn1003-207x.2020.1924
    Abstract845)      PDF(pc) (1400KB)(1651)       Save
    With the increase of customers’ environmental awareness and the intensification of market competition, the right sales decisions are significantly important for any green product enterprises to enter, occupy, consolidate and expand their markets. For this, a supply chain system consisting of one traditional manufacturer, one green manufacturer and one retailer is developed. Depending on the channel powers of two manufacturers in the system, three supply chain game models, i.e., traditional-manufacturer-leader Stackelberg game model, green-manufacturer-leader Stackelberg game model and Nash game model between both manufacturers, are considered. How the different channel power structures and the consumers’ green preference affect the decisions of wholesale prices, retail prices, order quantities, green input and supply chain profits is mainly investigated in this study. Furthermore, a cost-sharing and two-part-tariff contract is proposed to coordinate such a supply chain, and the Pareto improvement condition for each supply chain member’s profit is given.
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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
    Abstract1206)   HTML108)    PDF(pc) (868KB)(1623)       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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    Investor Sentiment, Order Flow Imbalance and Stock Liquidity
    YIN Hai-yuan, WU Xing-ying
    Chinese Journal of Management Science    2023, 31 (5): 60-70.   DOI: 10.16381/j.cnki.issn1003-207x.2020.1754
    Abstract402)      PDF(pc) (1035KB)(1599)       Save
    With the development of Web2.0, social media has gradually evolved into an online expression carrier. Different subjects, for their interests, using this channel to create and share content. Individual investors are more willing to express their true feelings through online platforms. This information has significant explanatory power to the stock market, but will not be reflected in the market data. In the process of continuous aggregation and fermentation, it intensifies the sentimental tendency of investors, fundamentally changes the information structure of the stock market.
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    Intelligent Quality Management: Theoretical Framework, Key Technologies, and Research Prospect
    Huchen Liu,Heming Wang,Hua Shi
    Chinese Journal of Management Science    2024, 32 (3): 287-298.   DOI: 10.16381/j.cnki.issn1003-207x.2023.0399
    Abstract740)   HTML51)    PDF(pc) (762KB)(1527)       Save

    The rapid development of a new generation of information technology, such as big data, Internet of Things, and artificial intelligence, has provided opportunities for the transformation and development of the manufacturing industry. To enhance the competitiveness of China’s manufacturing industry, it should focus on quality improvement, starting from the digital, network and intelligent transformation of quality management, to drive the upgrading of manufacturing industry. At present, there is no theoretical guidance for the upgrading and transformation of quality management in China’s manufacturing industry. Therefore, it aims to propose the concept of intelligent quality management based on the current research progress and the actual development of China’s manufacturing industry is this paper. The theory model of intelligent quality management from the technical, activity, and value dimensions is proposed, and nine key technologies (i.e., Internet of Things, big data platform, cloud computing and edge computing, machine learning, machine vision, digital twins, wireless communication, visualization, and blockchain) and their application scenarios are introduced. Finally, the future researches of intelligent quality management are pointed out from the perspectives of theoretical research, technical research, and application research. This study can provide strong guidance for the transformation and upgrading of quality management in China’s manufacturing industry by establishing the theoretical framework of intelligent quality management, exploring the development path of quality, and promoting the development of China’s manufacturing industry with high quality.

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    Two-stage Mean Semi-variance Portfolio Optimization with Stock Return Prediction Using Machine Learning
    Peng ZHANG,Shi-li DANG,Mei-yu HUANG,Jing-xin LI
    Chinese Journal of Management Science    2023, 31 (12): 96-106.   DOI: 10.16381/j.cnki.issn1003-207x.2021.2308
    Abstract849)   HTML110)    PDF(pc) (2248KB)(1426)       Save

    Since accurately predicting stock return sequences can improve the performance of portfolio optimization models, the results have indicated that machine learning methods have a greater capacity to confront problems with nonlinear, nonstationary charateristics than econometric models. Consequently, a novel two-stage method is proposed for well-diversified portfolio construction based on stock return prediction using machine learning, which includes two stages. To be specific, the purpose of the first stage is to select diversified stocks with high predicted returns, where the returns are predicted by machine learning methods, i.e. eXtreme Gradient Boosting(XGBoost), support vector regression(SVR), K-Nearest Neighbor(KNN), and evaluate and select the model. In the second stage, considering the constraints such as transaction costs and threshold constraints, the predictive results are incorporated into the mean semi-variance (M-SV) model, mean-variance model and equally weighted model to determine optimal portfolio. Finally, using China Securities 300 Index component stocks as study sample, the empirical results demonstrate that the XGBoost+MSV model achieves better results than similar counterparts and market index in terms of return and return-risk metrics.

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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
    Abstract666)   HTML46)    PDF(pc) (2407KB)(1373)       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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    Sales Mode Selection of Fresh E-commerce with Asymmetric Production Cost Information
    LIN Qiang, MA Jia-xin, CHEN Liang-jun, LIN Xiao-gang, ZHOU Yong-wu
    Chinese Journal of Management Science    2023, 31 (6): 153-163.   DOI: 10.16381/j.cnki.issn1003-207x.2020.1797
    Abstract440)      PDF(pc) (1596KB)(1336)       Save
    In recent years, the tremendous growth of the e-commerce industry are witnessed by us, and a large number of manufacturers who produce fresh products have started to sell through online platforms (e.g., JD.com and Tmall). In practice, the online platforms can choose to act as online marketplaces for the manufacturers (i.e., agency selling). Under this selling format, the manufacturers participate on the platforms by paying a proportional fee and directly sell their products to customers at a selling price. Besides, the platforms can also act as resellers for the manufacturers (i.e., reselling). Under this selling format, the manufacturers sell their products to the platforms at a wholesale price and then the platforms sell the products to customers at a selling price. This raises an important question of which selling format should both the online platforms and the manufacturers adopt. In fresh-product e-commerce supply chains, the upstream manufacturers often need to determine the optimal production levels by incurring costs, and the costs are uncertain to the downstream online platforms. The platforms thus cannot infer the qualification rate and will carry out sampling test to improve the quality level of the products, although the platforms fail to find out all unqualified products. Moreover, if the agency selling (reselling) format is employed, the manufacturers (online platforms) would improve the freshness of the products by incurring costs as much as possible. It is investigated how the production costs’ information asymmetry and the accuracy of the sampling test affect the selling format selections of the platforms and manufacturers.
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    Effects of Supplier's Store Brand on Manufacturer's Product Extension Strategy
    Ling ZHONG,Jia-jia NIE
    Chinese Journal of Management Science    2023, 31 (8): 151-161.   DOI: 10.16381/j.cnki.issn1003-207x.2020.2037
    Abstract395)   HTML28)    PDF(pc) (729KB)(1323)       Save

    To better meet the rapidly changing demand of the consumers, manufacturers have been dedicated to introduce new products by extending their existed product line. However, extending product line inevitably requires more sources of critical components, which may have indirect effects on the upstream suppliers, especially when the supply of those critical components is highly concentrated thus the pricing power is controlled by suppliers. Moreover, besides supplying core components for the manufacturer, suppliers themselves may introduce their own store brands, which make the manufacturer facing the threats of substituted products competition in the demand market. At this point, whether to extend its product line when facing the supplier’s store brand threat may be an important issue for the manufacturer. Based on this point, by using game theory, under supplier’s two store brand strategies, i.e., introduces store brand and forgoes introducing store brand, manufacturer’s two product line extension strategies models are build, solved and analyzed.In the rest of this paper, firstly, game theory is used to develop the manufacturer’s two product line extension strategies models under supplier’s two store brand strategies. Secondly, the equilibrium quantity and the optimal profits of both supplier and manufacturer are derived by the standard backward induction. Thirdly, the conditions for manufacture to extend product line under supplier’s two different store brand strategies are obtained. Finally, the impact of supplier’s two different store brand strategies on the manufacturer’s product line extension strategies is discussed.Through the above analysis, this study sheds light on the manufacturer’s product line extension strategies when facing the supplier’s store brand threat. Specifically, the supplier always introduces store brand when the marginal cost of critical components is low. Meanwhile, the introduction of store brand by the supplier may be detrimental to the extension of manufacturer’s product line. When the difference of quality level between the manufacturer’s new product and the supplier’s store brand is negligible, the introduction of supplier’s store brand makes the manufacturer unable to extend product line. When the difference of quality level between the manufacturer’s new product and the supplier’s store brand is remarkable, if the cost of core components is small, the manufacturer chooses to extend product line whether the supplier introduces store brand or not. Otherwise, the manufacturer foregoes to extend product line. What’s more, when facing the threats of supplier’s store brand threat, it is not always profitable for the manufacturer to extend product line.

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    Human Factors Capability Assessment in Human-machine Collaborative Decision-making
    Xiangwen Li,Cheng Song,Shuai Ding
    Chinese Journal of Management Science    2024, 32 (3): 145-155.   DOI: 10.16381/j.cnki.issn1003-207x.2021-2403
    Abstract543)   HTML24)    PDF(pc) (773KB)(1323)       Save

    With the development of artificial intelligence technology, humans are increasingly dependent on machines intelligence to make the correct decisions. The evolution of machine intelligence is changing from detecting and recognizing human beings to perceiving and understanding human beings. The evolution process of decision-making model from the perspective of human-machine collaboration is reviewed, the definition of human factors capability is proposed and the characteristics such as measurability, individual differences, dynamics, and strong correlation are pointed out. Thus a calculation model of human factors capability is established and each index is measured. A human factors capability assessment method that incorporates a capability scale is proposed. The task scenarios of human-machine collaborative decision-making with human factor capabilities are focused on, and the interactive activities of human, machine, and environment are studied with full consideration of human characteristics and factors. Finally, the feasibility and effectiveness of the human factor capability assessment method is analyzed in specific application scenarios. This paper also look forward to the research directions of human factors capability research, in order to providing theoretical and practical references for solving the problem of human-machine collaborative decision-making in the era of artificial intelligence.

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    Research on the Uncertainty of Economic Policy and the Contagion of Tail Risk between Global Financial Networks
    GONG Xiao-li, LIU Jian-min, XIONG Xiong, ZHANG Wei
    Chinese Journal of Management Science    2023, 31 (7): 78-90.   DOI: 10.16381/j.cnki.issn1003-207x.2021.0849
    Abstract552)      PDF(pc) (1647KB)(1273)       Save
    Affected by the global COVID-19 epidemic in 2020, the economic downside risk and financial market uncertainty in various countries have increased significantly. In response to the impact of global emergencies, the Federal Reserve and the European Union have taken measures to “rescue the market.” With the synchronous follow-up of national policies, the degree of global economic policy uncertainty has deepened. EPU will affect the expectations of economic entities for the future, and the market expectation will affect the development of the real economy and the stability of the financial market through activities such as consumption and investment. Therefore, economic policy uncertainty (EPU) is playing an increasingly important role in global risk contagion, and will even accelerate the process of financial risk contagion. The impact of the global epidemic has prompted investors to pay more attention to the economic policy uncertainty and global market network characteristics as well as tail risk transmission mechanism. the model of risk spillover effects between economic policy uncertainty and global financial markets is constructed from the perspective of interconnected networks. And then the transmission route of tail risks in global stock markets, currency markets, foreign exchange markets, bond markets, and derivatives markets is investigated. Specifically, based on GED-GJR-GARCH model, the volatility of EPU index and international financial market from February 2003 to October 2020 is calculated. And after incorporating the non-normal distribution caused by the tail risk shock into the model, the variance decomposition spillover index based on TVP-VAR is used to construct the financial network tail risk spillover model. The model is used to describe the dynamic characteristics of the global EPU index and the tail risk contagion of the international financial network. Compared with previous studies, the main contributions of this paper include several aspects. (1) The tail risk factor is taken into account into the international financial network risk spillover model in the form of non-normal distribution of returns on assets; (2) Variance decomposition spillover index based on TVP-VAR can describe the dynamic of the global structure of the high-dimensional network; (3) Elastic Net method is used to optimize the estimation algorithm of time-varying high-dimensional parameters, and solve the “dimension disaster” problem faced in the current financial network risk measurement; (4) By measuring a series of indicators to measure the stability of the network topology, a more in-depth analysis of the tail risk contagion between the international financial network structure and the uncertainty of global economic policies is carried out. The research results show that stock market and derivative market are the sources of tail risk, and their volatility will induce the EPU to rise. The rise of economic policy uncertainty intensifies the spillover effect of tail risk between the markets, so EPU has become an important node in the transmission path of tail risk. With the opening of capital accounts of different countries, the foreign exchange market has become an intermediate bridge for the contagion of tail risks. The results of the global risk spillover network show that during the financial crisis, the risk linkage between markets has increased significantly. And it has formed the tail risk contagion path with EPU and foreign exchange market as the hub, stock market and derivatives market as the source of risk. The comparison of risk spillover networks in different periods shows that the tail risk contagion mechanism between international financial markets is time-varying. The research conclusions are helpful to prevent financial market risk contagion under the background of uncertain economic policies of different countries, and provide new ideas for improving national financial security.
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    Application of Blockchain Technology to Preventing Supply Chain Finance Based on Evolutionary Game
    Rui Sun,Dayi He,Huilin Su
    Chinese Journal of Management Science    2024, 32 (3): 125-134.   DOI: 10.16381/j.cnki.issn1003-207x.2021.1538
    Abstract651)   HTML39)    PDF(pc) (1028KB)(1262)       Save

    Because of the risks existing in supply chain finance, taking accounts receivable factoring business as the research object, the factors affecting the decision-making of the participants in supply chain finance are analyzed, an evolutionary game model between small and medium-sized enterprises and financial institutions is constructed, and the mechanism of blockchain to solve the financial risks of the supply chain is analyzed by comparing the changes of evolutionary stability strategies before and after the introduction of blockchain technology. And taking the actual case as the background for example analysis, the main conclusions are verified. It is found that firstly, credit risk plays a decisive role in whether financial institutions accept financing business decisions. Blockchain technology can reduce the operational risk of financial institutions and improve the business income of financial institutions; Secondly, the strict regulatory environment formed by blockchain technology makes the default behavior of small and medium-sized enterprises and core enterprises in a high-risk state at all times. No matter the profit distribution proportion that small and medium-sized enterprises can obtain through collusion, they will not choose to default, which effectively solves the paradox that small and medium-sized enterprises cannot obtain loans from financial institutions despite the increased probability of compliance. Then, the evolutionary game between financial institutions and small and medium-sized enterprises is balanced in that financial institutions accept business applications, small and medium-sized enterprises abide by the contract, and the convergence effect is better. Therefore, blockchain technology not only reduces the financing risk of financial institutions, but also helps to solve the financing problems of small and medium-sized enterprises.

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