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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 Abstract （2967）      PDF（pc） （1642KB）（2960）       Knowledge map    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. Reference | Related Articles | Metrics | Comments（0）

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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 Abstract （1774）   HTML （78）    PDF（pc） （908KB）（2683）       Knowledge map    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. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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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 Abstract （2687）      PDF（pc） （2837KB）（2666）       Knowledge map    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. Reference | Related Articles | Metrics | Comments（0）

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“Good Shopping Decisions” and “Bad 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 Abstract （1551）   HTML （90）    PDF（pc） （1157KB）（2567）       Knowledge map    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. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Characteristics and Development Pathway of the Discipline of Management Science and Engineering within the Funding System of National Natural Science Foundation of China HUO Hong Chinese Journal of Management Science    2023, 31 (1): 1-8.   DOI: 10.16381/j.cnki.issn1003-207x.2023.01.001 Abstract （1589）      PDF（pc） （3843KB）（2562）       Knowledge map    Save Reference | Related Articles | Metrics | Comments（0）

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Study on Behavior-based Pricing Strategy and Contract Model for Platforms with Service Differentiation MA Dong-sheng, SONG Hua-ming, ZHAO Jin-xiao, ZHU Yan-ru Chinese Journal of Management Science    2023, 31 (2): 215-225.   DOI: 10.16381/j.cnki.issn1003-207x.2020.0972 Abstract （694）      PDF（pc） （1503KB）（2463）       Knowledge map    Save It is common that customers are more willing to consume on platforms matching their service preferences, which makes it difficult for platforms to attract new customers. Behavior-based pricing (BBP) is used to compete for new customers and market shares. However, cooperation between platforms and collaborators are affected by intensified price competition. In this context, dual challenges of BBP strategy and contract model are faced by competing platforms. Firstly, to solve this problem, game theory is used to construct a two-period dynamic pricing model. Secondly, platform's optimal BBP strategy and contract model are obtained through the comparative analysis of platforms’ profits, prices, and demands under different scenarios. Finally, two situations are analyzed where platforms share customer information with collaborators and collaborators can choose the contract model. The main findings are as follows: (1) platforms’ pricing decision are affected by two key factors—relative service efficiency and operating type, and specific conditions are given; (2) Customer information should be shared with collaborators，which can increase platforms’ profits and weaken internal competition. (3) Long-term contracts are the best choice for collaborators to cooperate with resell-channel platforms. These conclusions provide management inspiration for platforms to make scientific BBP and contract model choices. In addition, it also shows that BBP helps to coordinate platforms’ internal and external competition. Reference | Related Articles | Metrics | Comments（0）

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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 Abstract （1923）   HTML （127）    PDF（pc） （868KB）（2320）       Knowledge map    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. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Pricing and Cold-chain Logistics Service Decisions of Fresh Agriculture Products Supply Chain under Different Trade Modes YE Jun, GU Bo-jun, FU Yu-fang Chinese Journal of Management Science    2023, 31 (2): 95-107.   DOI: 10.16381/j.cnki.issn1003-207x.2020.0751 Abstract （1274）      PDF（pc） （1403KB）（2230）       Knowledge map    Save Though China is a major producer and consumer of fresh agricultural products, cross－border trade in fresh agricultural products is booming due to limitation of production resource and imbalance productivity. However, easy to deterioration as well as long－distance and long-time cross－border journey lead to higher transportation cost and higher risk of goods loss for cross－border trade in fresh agricultural products. Therefore, the logistics provider is desired to improve the cold－chain logistics service so as to minimize the deterioration rate during the transportation. In addition, FOB (Free on Board), CIF (Cost, Insurance and Freight) and DAP (Delivered at Place) are three different trading modes, and the cost of cold－chain logistics service and the loss of goods in transportation are undertaken by the different parties under different trading modes. Therefore, in the cross－border trade of fresh agricultural products, the choice of different trading modes and cold chain logistics service will directly affect the risk of cross－border transportation and the degree of decay of fresh agricultural products, and then have a significant impact on the profits of each party of the fresh agricultural products supply chain. To solve these problems, this study focuses on the cross－border trading mode choice and freshness preservation of fresh agricultural products. Reference | Related Articles | Metrics | Comments（0）

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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 Abstract （1988）   HTML （56）    PDF（pc） （2541KB）（2225）       Knowledge map    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. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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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 Abstract （1069）      PDF（pc） （1609KB）（2222）       Knowledge map    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. Reference | Related Articles | Metrics | Comments（0）

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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 Abstract （695）      PDF（pc） （1015KB）（2206）       Knowledge map    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. Reference | Related Articles | Metrics | Comments（0）

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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 Abstract （640）      PDF（pc） （1449KB）（2164）       Knowledge map    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. Reference | Related Articles | Metrics | Comments（0）

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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 Abstract （1349）   HTML （60）    PDF（pc） （762KB）（2161）       Knowledge map    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. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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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 Abstract （1294）   HTML （95）    PDF（pc） （907KB）（2127）       Knowledge map    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. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Incentives for Corporate Social Responsibility in a Group-purchasing Supply Chain under Cooperation and Competition Maosen Zhou,Qingyu Zhang Chinese Journal of Management Science    2024, 32 (6): 267-280.   DOI: 10.16381/j.cnki.issn1003-207x.2021.1391 Abstract （547）   HTML （14）    PDF（pc） （3246KB）（2013）       Knowledge map    Save Although consumers are concerned about social responsibility （SR）， they may not be willing to pay for corporate SR behavior in actual purchases. However， most of the literature has examined the incentives for corporate SR based on reciprocity with consumers rather than altruism towards consumers. It is necessary to explore new drivers， which are different from consumers' willingness to pay， for corporations to engage in SR， especially when consumers have insufficient awareness of SR behavior or their actual willingness to pay is not so sensitive to SR attributes of products. To narrow this gap， a supply chain where two competing manufacturers purchase a same component through a common group purchasing organization （GPO） to achieve economies of scale is studied. The manufacturers can endogenously make SR strategies simultaneously by choosing how much consumer surplus should be considered in their production decisions. By developing a stylized model to analyze the coopetition game between the manufacturers with respect to SR level and quantity decisions， the impact of SR levels on operational performance is identified and the equilibrium SR strategies are solved. From this， the impact of group purchasing on SR incentives and their sustainability is untangled， and the sustainable path of group purchasing to value creation is explored.The results indicate that SR can always benefit the GPO and consumers by increasing production while it can benefit the manufacturers only if cooperation dominates. As a result， SR can make both the supply chain and social welfare either better off at low levels or worse off at high levels. In equilibrium， the manufacturers will implement SR strategies only if cooperation and competition are unbalanced. In this scenario， the manufacturers may sink into Prisoner’s Dilemma and suffer losses from SR strategies if competition dominates， whereas SR strategies can also make the manufacturers better off and achieve the Pareto improvement of social welfare if cooperation dominates. Compared to individual purchasing， group purchasing can create values of cooperation and SR by inducing the share of purchasing power and a cooperative relationship between the manufacturers. In particular， when the competition intensity and GPO commission are sufficiently low， group purchasing can sustain SR strategies and thus creates significant social benefit， i.e.， improve the consumer surplus and social welfare at the same time. Above all， by demonstrating the mutual promotion on sustainable value creation between group purchasing and corporate SR， we propose a new strategic driver of SR for corporations under competition. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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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 Abstract （665）      PDF（pc） （1356KB）（1988）       Knowledge map    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. Reference | Related Articles | Metrics | Comments（0）

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Online Reviews for Product Demand Preference Discrimination and Customer Segmentation: A Case Study of the Smart Phone Data SUN Bing, SHEN Rui Chinese Journal of Management Science    2023, 31 (3): 217-227.   DOI: 10.16381/j.cnki.issn1003-207x.2020.0164 Abstract （665）      PDF（pc） （3431KB）（1981）       Knowledge map    Save In the data-booming epoch, online reviews have become the scholars’ focus home and abroad due to its information diversity and its mass participation character. It aims at delving into the valuable consumption information contained in online comments, discriminating the product demand preference, and thus summarizing the customer segmentation and characteristics. Based on four selling smartphones on the Jingdong and Tmall online shopping platforms, 26489 effective online reviews are obtained as text data in this study. First, the features of mobile products with the decision algorithm of boundary average entropy (BAE) are extracted, and consumers’ product demand preference is classified and discriminated on the correlation analysis of mutual information and semantic similarity. Then, the scores are obtained on consumers preference discriminating the products’ seven dimensions according to the analysis of emotional tendency, meanwhile, a multidimensional score vector is formed to represent consumers. With the improvement of two-step cluster method being used, the classification of consumer groups and the summary of features are completed. Thereafter, the consumer groups of the four smartphones are analyzed and some related revelations are provided according to the research results. The research ideas and methods applied in this paper can be of vital reference and significance for enterprises to effectively discriminate the consumers’ product demand preference and scientifically classify the consumer groups. Reference | Related Articles | Metrics | Comments（0）

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Credit Risk Warning of Listed Companies Based on Information Disclosure Text:Empirical Evidence from Management Discussion and Analysis of the Chinese Annual Report LI Cheng-gang, JIA Hong-ye, ZHAO Guang-hui, FU Hong Chinese Journal of Management Science    2023, 31 (2): 18-29.   DOI: 10.16381/j.cnki.issn1003-207x.2020.2263 Abstract （1138）      PDF（pc） （1230KB）（1952）       Knowledge map    Save With the economic globalization, the international economic situation becomes more and more complex, and Chinese listed companies will face greater challenges. The unstable economic situation such as trade friction and financial market volatility will increase the credit risk of listed companies. The establishment of credit risk early warning system is conducive to the operators to find the company’s financial problems in time, and make response and prevention. A large number of text documents disclosed by listed companies can extract certain effective information, which can be used as an effective supplement to the traditional quantitative financial indicators. As an important part of the annual report, “Management Discussion and Analysis (MD & A)” in the enterprise annual report includes the evaluation of the company’s historical operation by the company’s managers and the prospect of the future market development. Therefore, deep mining the valuable text information contained in MD&A can effectively supplement the company’s financial index information and predict the company’s credit risk. Reference | Related Articles | Metrics | Comments（0）

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New Product Operation Strategy under a Brand Merchant’s Direct Channel: Joint Decision on Quality, Price, and Channel Selection JIANG Xuan, WANG Ting, DENG Shi-ming Chinese Journal of Management Science    2023, 31 (6): 49-59.   DOI: 10.16381/j.cnki.issn1003-207x.2020.1599 Abstract （702）      PDF（pc） （2062KB）（1931）       Knowledge map    Save Nowadays, the channel expansion of internet retail brand merchant from online to offline is common phenomenon in the ecommerce industry. The brand merchant with online and offline direct channels can choose to release the new product through either a single channel or dual channels. It focuses on the optimal strategy of new product release before and after the brand merchant’s channel expansion in this paper, and the optimal combination of product quality, price and channel selection strategy and related factors that affect the optimal strategy when the brand merchant introduces the new product are studied. It is found that there are a variety of strategy combinations for the new product introduction, and the optimal one is affected by the factor such as the uncertainty of customers’ perception of the new product, online shopping revenue, and the channel threshold profit; The strategy of using dual channels to release the new product simultaneously is not always the best, and it may become the optimal one if and only if it matches the corresponding new product quality and price strategy; Compared to the online channel, since the offline channel could deliver more accurate information of the new product value to the customers, hence the brand merchant is more inclined to release new products with high quality and high price through the offline channel; For the internet retail brand merchant, if the digital attribute of the products they operate is weak, channel expansion will bring much benefit to them. Reference | Related Articles | Metrics | Comments（0）

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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 Abstract （579）   HTML （10）    PDF（pc） （1994KB）（1911）       Knowledge map    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. Table and Figures | Reference | Related Articles | Metrics | Comments（0）