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The Cyclical Transition Characteristics of the Bull and Bear States in China's Stock Market: Based on the DMCPSO-HSMM Model Yang Jie, Feng Yun, Yang Hao Management Review    2024, 36 (11): 3-13.   Abstract （280）      PDF （3327KB）（2620）       Knowledge map    This paper studies the periodic transition of the state of China’s stock market and discusses the time-varying distribution characteristics of returns of CSI300 in depth. By introducing the dynamic population reorganization based on the K-means + + clustering algorithm and the chaotic search strategy into the standard particle swarm optimization algorithm, a dynamic multi-population chaotic particle swarm optimization algorithm is proposed, and the initial values of hidden semi-Markov model are further optimized based on this algorithm. The empirical analysis shows that there exist three states in China’s stock market, namely the bear, bull, and volatile markets. A bull market generally follows a bear market, and after a bullish situation, the market has a greater probability of turning to a volatile situation. The volatile state and the bearish state play key roles in the leptokurtic and heavy-tailed characteristics of the stock market, respectively. Based on the decoding results, a mode transformation network is constructed using the coarse-grained method, and key hub modes are identified. Further analysis is conducted on the co-movement of bull and bear states of large-, medium-, and small-cap stocks. There is a significant cyclical polarization between large-cap and medium-or small-cap stocks. Finally, we propose a more accurate out-of-sample forecasting method for the hidden semi-Markov model and prove the practical value of our model via a simple market timing strategy. Reference | Related Articles | Metrics

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Robust Optimization-based Inventory Level and Allocation Strategy for Sharing Platform under Service Level Constraint Qiu Ruozhen, Ji Yuanyuan, Shao Songshi Management Review    2023, 35 (6): 275-287.   Abstract （146）      PDF （1714KB）（2211）       Knowledge map    Assuming there is a supply chain composed of a single inventory sharing platform and multiple retailers, this paper studies the optimal inventory level and allocation strategies of the inventory sharing platform with and without demand information sharing. A robust optimization model is established, with the retailer's service level constraint taken into consideration and only demand mean and variance information known. Under the condition of information sharing, the inventory sharing platform can accurately obtain the retailers' demand mean and variance. The retailer's service level constraint is transformed into an easy-to-handle chance constraint problem. Under that condition, the optimal inventory level and allocation strategies are deduced, and the changes of the strategies with the changes of the related parameters are analyzed. Under the condition of not sharing demand information, the inventory sharing platform only knows the uncertain set of the retailers' demand mean and variance. In particular, the ellipsoidal uncertain set is used to describe the mean and variance of uncertain demand, the dual theory is used to transform the inventory optimization model and studies are conducted to analyze the impact of information sharing on the optimal inventory level and allocation strategy. The results show that, under different information conditions, the inventory level of the inventory sharing platform increases with the increase of the mean, variance and service level requirements; the information shared by the retailers has a positive impact on the inventory optimization of the inventory sharing platform, namely, the better information sharing among the retailers, the lower inventory level on the inventory sharing platform; when the retailers do not share information, the inventory level of the inventory sharing platform increases with the uncertainty of mean and variance increases, and the uncertainty of mean has a greater impact on the inventory level. Reference | Related Articles | Metrics

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A Research into the Mechanism of How New Infrastructure Projects Drive Integrated Urban-Rural Development Wu Guobin, Li Yuhan, Yang Fan, Li Yulong Management Review    2025, 37 (9): 3-14.   Abstract （116）      PDF （1215KB）（105）       Knowledge map    New infrastructure has great potential to promote integrated urban-rural development. Based on the panel data of 31 provincial-level administrative regions in China from 2012 to 2021, this paper applies spatial lag modeling to test the mechanism of how new infrastructure drives integrated urban-rural development. The results demonstrate that the new infrastructure has a driving effect on integrated urban-rural development, and there is a significant spatial spillover effect. The three types of new infrastructure, namely information-based infrastructure, integrated infrastructure, and innovation infrastructure, all have a positive effect on integrated urban-rural development. Specifically, the effect of information-based infrastructure relies on the digital economy, the effect of innovation infrastructure relies on industrial structure upgrading, and the effect of integrated infrastructure can be transmitted through both the digital economy and industrial structure upgrading. Therefore, the investment and construction of the three types of new infrastructure should be planned scientifically, considering the digital economy and industrial structure of the region, and the interregional planning of new infrastructure should be strengthened, to give full play to the spatial spillover effect of the new infrastructure, and to promote integrated urban-rural development. Reference | Related Articles | Metrics

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Recommendation Algorithm Based on Link Prediction and Node Degree Using a Social-Attribute Network Jiang Ruoran, Zhang Lingling    2019, 31 (2): 119-129.   Abstract （347）      PDF （1760KB）（908）       Knowledge map    Social networking platforms disruptively change the way modern people communicate. More and more researches have focused on social networks from the social and technological perspectives. Link recommendation is a very important task. It not only can enhance internal linkage, but also will help improve the user experience. The existing link prediction algorithms in social-attribute network model do not comprehensively utilize the network structure information and attribute node information. This paper proposes several improved algorithms of link prediction based on local information, which combine effects of different types of common neighbors on social-attribute network model. These improved algorithms are given diverse treatment for the different influence from user common neighbor node and attribute common neighbor nodes. The test results in Google+ data set show that improved algorithm outperforms the algorithm, which does not consider the influence of common neighbor nodes on social-attribute model. After summarizing the different effects of diverse common neighbor nodes on link prediction, this paper provides corresponding suggestions on processing of different types of nodes. Reference | Related Articles | Metrics

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Forecasting the Volatility of Chinese Crude Oil Market Based on Geopolitical Risk Yang Kun, Wei Yu, Li Shouwei, Liu Liang Management Review    2023, 35 (1): 16-31.   Abstract （243）      PDF （1473KB）（1041）       Knowledge map    Frequent geopolitical events in recent years are often regarded as a main cause of the intense fluctuations in crude oil market. Therefore, this paper first uses the GARCH-MIDAS-GPR-type models which incorporate geopolitical risk (GPR) indexes to analyze the impacts of the geopolitical risks of different countries, categories and severity on Chinese oil market volatility and the forecasting accuracy of the models. Then, the robustness of conclusions is further discussed from six perspectives: volatility forecasting with different lengths, volatility forecasting before and after the launch of Chinese crude oil futures, alternative basic model, direction-of-change of crude oil volatility forecasts, crude oil risk forecasting and portfolio management. Furthermore, three macroeconomic uncertainties and six economic policy uncertainties are introduced to compare how helpful different uncertainties are for prediction. The empirical results show that, first, the country-specific, overall and serious GPR indexes have significantly positive effects on the long-run volatility of Chinese crude oil market. Second, geopolitical risk indicators contribute to improving the accuracy of Chinese oil volatility forecasts to varying degrees, and the three GPR indexes which reflect the overall geopolitical risk of the world perform better than other GPR indexes. Finally, compared with the commonly used macroeconomic uncertainties and economic policy uncertainties, geopolitical risk can provide most useful information for forecasting crude oil volatility. All the above-mentioned conclusions are robust in statistical accuracy and applications. Reference | Related Articles | Metrics

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Digital Business Model Design:Multiple Case Studies of Enterprise's Digital Transformation and Business Model Innovation Qian Yu, Sun Xinbo Management Review    2021, 33 (11): 67-83.   Abstract （1038）      PDF （2110KB）（1006）       Knowledge map    Under the wave of digital economy, in the face of increasing integration between cross-border disruptors and technologies, traditional enterprises have to implement digital transformation. Although digital technology provides opportunities for enterprises to develop and adjust business models to achieve digital transformation, relevant researches focus only on the nature of digital transformation, without in-depth attention to changes in the business model architecture system in the digital context. The study uses multiple case studies to analyze 5 business models related to digitization in manufacturing companies, extracting 4 different types of digital business models, and then deconstruct digital business models into digital value proposition, digital value creation and digital value acquisition. After that, the design principles of digital business models are explained in detail. Finally, the dual attributes of business models are used to identify the innovative sources of digital business models. Reference | Related Articles | Metrics

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A Study on Predicting Green Credit Default Risk of Publicly Listed Companies through a Hybrid Deep Learning Model Chen Wei, Zhou Quanshi, Chen Zhensong, Yao Yinhong Management Review    2025, 37 (9): 27-41.   Abstract （73）      PDF （2649KB）（69）       Knowledge map    In recent years, green credit has played an increasingly important role in promoting the construction of China’s green financial system and facilitating high-quality economic development. However, default activities of listed companies in green credit may pose a trust crisis in the financial market and hinder the achievement of the "dual carbon" goals. Therefore, accurately identifying and predicting the green credit default risk of listed companies has become a focus in both academia and the industry. To address this, this paper first constructs a comprehensive measure of default risk, by incorporating the proportion of green credit defaults and the credit ratings of entities. And we process feature engineering by excavating the characteristics of green credit data for listed companies. Subsequently, a hybrid deep learning model, named AE-MACNN-LSTM, is designed by incorporating an AutoEncoder mechanism and various neural networks to predict the green credit default risk of listed companies. Finally, an empirical test is conducted based on samples of A-share listed companies in China. The results indicate that the proposed method achieves significant improvements in multiple evaluation metrics, such as high recall rates and AUC values. This research provides a novel perspective for identifying and mitigating the green credit risk of listed companies, offering valuable insights for the government and investors to timely grasp the dynamics of corporate green credit. Reference | Related Articles | Metrics

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The Influence of Inclusive Leadership on Employees' Proactive Behavior: The Mediating Effects of Organizational-based Self-esteem and Error Management Climate Kong Liang, Li Xiyuan, Zhang Fawang    2020, 32 (2): 232-243.   Abstract （542）      PDF （1207KB）（1564）       Knowledge map    In the new normal economic background, an employer expects its employees not only to meet basic job requirements, but also to break through routine work requirements by showing initiative and thinking proactively to help their company respond effectively to environmental challenges. Globalization has brought about an increase in cross-regional population flows. The new generation of employees has gradually become the main force in the workplace, and staff in the workplace is becoming increasingly diversified. In view of the diversification of employees, a challenge that management team has to face is to find out how to carry out diversified management and give full play to the diversification of the employees' work initiative. This issue has also attracted the attention of academia. Inclusive leadership can inspire the initiative of diversified employees because of its openness, availability, and accessibility. Based on the theory of self-determination, this paper constructs a multiple mediator model with organizational self-esteem and error management climate to explore the influencing mechanism of inclusive leadership on employees' proactive behavior in organizations. Data are collected through paired questionnaire survey of 67 team leaders and 304 employees. The results show that inclusive leadership has a positive effect on employees' proactive behavior. HLM results reveal that organizational-based self-esteem and error management climate play a full mediating role between the two in the individual and the team level. The conclusion of the research reveals the influencing path of inclusive leadership on employees' proactive behavior. This not only confirms the inclusive leadership has the characteristics of fault tolerance, but also enriches the research of the influence factor of error management climate. At the same time, this research also confirms the positive effect of the error management climate on the employee's proactive behavior, and provides a theoretical reference and management inspiration for the cultivation of the leadership's inclusiveness and the construction of organizational error management climate. Reference | Related Articles | Metrics

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Digital Technology Adoption and Employment Structure: Empirical Evidence from Listed Companies Guan Rong, Wang Heting, Wang Huijuan Management Review    2025, 37 (8): 3-15.   Abstract （295）      PDF （1242KB）（219）       Knowledge map    The transformation and development of enterprises applying digital technology is the kernel guarantee to promote the high-quality development of China’s digital economy, and the resulting impact and influence on the micro labor market is an issue that needs to be urgently resolved for the development of the country’s major strategies. Based on the data of Chinese listed companies from 2011 to 2020, this paper takes a micro perspective to explore the impact of digital technology application on the employment structure of enterprises and the mechanism underlying the impact. It is found that the application of digital technology has an “inverted U-shaped” relationship with the total number of employees and the number of unskilled employees, but there is a significant positive relationship with the number of skilled employees, indicating that the application of digital technology can help optimize the employment structure of enterprises and thus has an empowering effect. Further analysis reveals that the application of digital technology affects the employment structure of enterprises mainly by enhancing innovation capability, affecting the level of skill premium, and improving productivity. The spillover effect of digital technology on enterprises varies significantly, depending on their production scale, social burden and likelihood of being substituted. The relevant conclusions bring more empirical support for clarifying the mechanism of how digital technology influences the employment structure of enterprises, and provide certain policy insights for promoting the integration of digital technology with the real economy. Reference | Related Articles | Metrics

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Can Margin Trading Regulations Enhance Audit Quality for Large Audit Firms?—Evidence from Cases of Accounting Fraud Yao Yuan, Li Fangfang, Lu Pu Management Review    2025, 37 (9): 15-26.   Abstract （59）      PDF （1218KB）（53）       Knowledge map    It is prevalent in the audit market that larger audit firms tend to have higher audit quality. This study employs the occurrence of accounting fraud as a proxy variable for audit quality to investigate whether the implementation of margin trading rules can enhance audit quality for large-scale audit firms. The research finds that the implementation of margin trading rules significantly enhances the ability of large-scale audit firms to deter accounting fraud. Furthermore, the impact of margin trading rules on the audit quality of large-scale firms is more pronounced in highly market-oriented regions, companies under poor internal governance and privately-owned companies. Mechanism tests reveal that margin trading rules enhance the ability of large-scale audit firms to prevent accounting fraud through two channels: facilitating negative information dissemination and increasing litigation risks. This study enriches theoretical perspectives on audit reputation and litigation risk theories, and practically provides experiential insights for the transformation of Chinese audit firms from “expansion” to “strengthening”. Reference | Related Articles | Metrics

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Can the China’s “Manufacturing Superpower” Policy Improve the Industrial Base Capability?—An Empirical Analysis Based on the Continuous Spatial DID Model Ji Kaiwen, Luo Luyi, Tang Wenying, Yuan Zichen Management Review    2025, 37 (9): 42-55.   Abstract （75）      PDF （2009KB）（53）       Knowledge map    Weak industrial base capacity has become a key factor limiting the improvement of China’s industrial chain supply chain level. Based on the data of Chinese provinces from 2013 to 2019, this paper constructs an index system for evaluating industrial base capacity, analyzes the change characteristics of industrial base capacity in China’s provinces by using the coefficient of variation σ convergence model, and empirically analyzes the effect of China’s “manufacturing superpower” policy on the industrial base capacity in China by using continuous and spatial continuous DID models. The main conclusions are as follows. (1) China’s provincial industrial base capacity shows an upward trend in general, especially after the implementation of the China’s “manufacturing superpower” policy in 2015, when China’s provincial industrial base capacity began to break away from the convergence trend as proposed by the neoclassical economic growth theory and instead show further growth potential without σ convergence. (2) China’s “manufacturing superpower” policy has improved the industrial base capacity to a certain extent, and the positive promoting effect of the policy is more sustainable. (3) Considering the spatial dimension of the policy, it is evident that China’s “manufacturing superpower” policy has a positive spatial impact on industrial basic capabilities, benefiting not only local and neighboring areas, but also the entire region. Furthermore, the spillover effect on neighboring areas and the entire region is more substantial than the direct effect it has on local area. (4) Further analysis reveals that the China’s “manufacturing superpower” policy mainly improves industrial base capacity by enhancing industrial innovation capacity and industrial infrastructure service capacity. Its impact on industrial supply capacity exists only in terms of total spatial effects, with no clear impact on industrial competitiveness and industrial chain control capacity. (5) Mechanism analysis indicates that the digital economy and financial technology are two mechanisms through which China’s “manufacturing superpower” policy affects industrial base capacity. These mechanisms positively influence both local area and the entire region, but negatively affect neighboring areas. Reference | Related Articles | Metrics

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The Double-edged Effects of Coworkers’ After-hours Electronic Communication Expectations on Employees’ Job Performance Liu Xin, Dong Jingni, Ge Yuhan Management Review    2025, 37 (8): 131-142.   Abstract （83）      PDF （1264KB）（90）       Knowledge map    In the digital age, after-hours electronic communication expectations (AECE) are increasingly prevalent. While existing research has explored the impact of leaders’ AECE on employees’ job performance, limited attention has been paid to coworkers’ AECE. Guided by the transactional theory of stress, we argue that coworkers’ AECE as a workplace stressor can result in either challenge or hindrance appraisal that subsequently influences employees’ job performance in a positive or negative manner. Further, we propose that reward interdependence serves as a key moderator in the above-mentioned pathways. Specifically, when reward interdependence is higher, employees are more likely to develop challenge appraisal in the face of coworkers’ AECE, which promotes their job performance. In comparison, when reward interdependence is lower, employees tend to develop hindrance appraisal in the face of coworkers’ AECE, which inhibits their job performance. To test these hypotheses, we collect two-wave survey data from 328 employees and their 65 direct leaders in a construction company. The results of multilevel path analysis fully support our hypotheses. Overall, by introducing the transactional theory of stress to explore the “double-edged” effects of coworkers’ AECE on employees’ job performance, our research offers novel theoretical contributions to the after-hours electronic communication literature. In addition, our findings can also provide crucial insights for organizations to handle AECE more effectively in practice. Reference | Related Articles | Metrics

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Exertion or Hesitation? A Dual-path Model of Leadership Emergence on Employees’ Job Performance Lv Ledi, Ji Shunhong, Gao kai, Zhang Haomin Management Review    2025, 37 (9): 137-148.   Abstract （47）      PDF （1276KB）（50）       Knowledge map    Owing to the increasingly dynamic and complex external environment, informal leadership is beneficial to teams in effectively changing procedures and coordination, which is favored by practitioners and scholars. However, dispute exists regarding whether leadership emergence can improve employees’ job performance, so the relationship between them and its mechanism need to be further explored. Drawing on the cognitive appraisal theory and through 507 dyads (87 supervisors and 507 subordinates), we examine the dual-path model of leadership emergence, involving strengthening path and weakening path, to explain why and when leadership emergence affects employees’ job performance. The results show that leadership emergence not only improves employees’ strengths use which in turn increases employees’ job performance, but also aggravates employees’ image risk, which in turn decreases employees’ job performance. In addition, distributed leadership can enhance the positive indirect effect of leadership emergence on employees’ job performance via strengths use, and buffer the negative effect of leadership emergence on employees’ job performance via image risk. These findings offer significant implications for theoretical research and practices. Reference | Related Articles | Metrics

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Research on the Evolution Mechanism of Enterprise Digital Dynamic Capabilities: Based on the Perspective of Cognitive and Behavioral Coevolution Yin Ximing, Wu Peiqi, Li Jizhen Management Review    2025, 37 (9): 262-273.   Abstract （50）      PDF （2616KB）（47）       Knowledge map    Enterprise digital transformation entails more than technological shift; the comprehensive upgrade of cognition, decision-making, and operational collaboration across levels is crucial for cultivating essential digital dynamic capabilities to overcome transformation bottlenecks. However, existing research rarely explores digital dynamic capability evolution from the perspective of cognition-behavior interaction in transformation. This study employs East China Institute as a case-advancing individual, organizational, and inter-organizational cognition-behavior coevolution via its leadership project-to explore theoretical mechanisms driving digital dynamic capability evolution. Findings reveal that individual, organizational, and inter-organizational digital transformation cognition and digital resource action spiral together, drive enterprise digital dynamic capabilities’ construction, enhancement, and leap. Enterprise digital transformation sensemaking involves two rounds of transferring meaning from individual to organizational to inter-organizational level. Thus, this study distills the three-level dual-transfer cognition coupled with piecing, arranging, and orchestrating digital resources, driving digital dynamic capabilities’ construction, enhancement, and leap. It expands research on digital dynamic capability, sensemaking, and resource action, offering practical insights for enterprises to accelerate digital/intelligent transformation by cultivating these capabilities to promote China’s high-quality economic development. It also provides references for understanding how leading enterprises construct digital ecosystems and empower industrial digitization. Reference | Related Articles | Metrics

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The Double-edged Sword Effect in Organizational Behavior Research: Typical Patterns and Strategy Suggestions Zhang Jiaojiao, Luo Wenhao Management Review    2022, 34 (9): 195-207.   Abstract （556）      PDF （1371KB）（1706）       Knowledge map    Mainstream organizational scholars tend to look at either the positive or negative influence of independent variables on dependent variables. However, this simple approach contrasts with the complicated phenomena in management practices. It is also less conducive to the meaningful integration of different studies. As a result, research on the double-edged sword effect has emerged in recent years. Though there are increasing studies examining the double-edged sword effect, it is worth noting that the interpretation of the effect remains unclear, the underlying mechanism is ambiguous, and the corresponding research pattern is often inappropriately used. By systematically analyzing 137 organizational behavior studies demonstrating the double-edged sword effect in both Chinese and English, this study clarifies the nature of the double-edged sword effect, identifies two major motives for conducting research on the topic, and classifies the existing research pattern into three main types (direct effect, indirect effect and moderating effect) and six sub-types. This study also offers five explanations of the potential theoretical basis for research on the double-edged sword effect. Finally, we offer practical suggestions for future researches. The present study is expected to demonstrate the potential contribution of researches on the double-edged sword effect, and to inspire more valuable future studies. Reference | Related Articles | Metrics

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Venture Capital-driven Transformation of Scientific Achievements in Hard Technology Enterprises: A Case Study of the Xiguang Model of Zhongke Chuangxing Guo Xin, Yu Mei, Bian Jiangze, Qiao Han, Zhang Xiaoxu Management Review    2024, 36 (9): 261-273.   Abstract （342）      PDF （1363KB）（249）       Knowledge map    In the development strategy driven by technological innovation, exploring how to fully leverage the role of technology incubators and accelerate the achievement transformation of hard technology enterprises has important practical significance. This paper takes the “Xiguang Model” of Zhongke Chuangxing as a research case to explore the path and mechanism of the transformation of scientific and technological achievements in hard technology enterprises, as well as the important role of venture capital in its model. It is found that introducing venture capital can accelerate the innovation and development of hard technology enterprises. At the same time, the appreciation of enterprise valuation can attract more capital to enter, forming a new circular development model of capital driven innovation. However, hard technology enterprises have the characteristics of high development risks and long development cycles, and the transformation of scientific and technological achievements requires continuous financial investment. Therefore, the development of hard technology enterprises needs to rely on relevant channels such as national policies and financial finance. Moreover, to solve the “financing difficulties” of hard technology enterprises, it is not only necessary to guide more social capital to participate through the leverage of state-owned capital, but also to fully leverage the role of market-oriented resource allocation. The case enterprise has promoted the development of hard technology enterprises through the “talent+technology+capital+service” four in one technological achievement industrialization model, and achieved its own growth, further enhancing its social service capabilities. The research in this paper lays the foundation for the development theory of hard technology enterprises with Chinese characteristics and provides a policy basis for the relevant decision-making departments. Reference | Related Articles | Metrics

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An Analytical Framework of Derivatives Sniper Attack Risk Based on the Case Study of Tsingshan Group’s Forced Liquidation Incident in LME Nickel Xu Yang, Bu Hui Management Review    2024, 36 (2): 257-272.   Abstract （327）      PDF （3628KB）（621）       Knowledge map    The nickel futures prices on the London Metal Exchange (LME) experienced a sharp surge during the two trading days from March 7th to 8th, 2022. As a result, Tsingshan Holdings Group, a Chinese company heavily involved in nickel hedging, suffered a significant loss, which marks another risk event where a domestic enterprise participating in overseas derivative trading was targeted by international capital. This paper provides a detailed case analysis of the sniper activity among “LME nickel futures incidents”, and proposes an analytical framework for analyzing sniper events and sniper risk in the futures market from four dimensions: objective conditions, market environment, sniper strategies, and sniper motivation behind. The study reveals that the weak physical delivery capacity caused by cross-hedging became an objective condition for Tsingshan Group to be targeted, and the market environment of low-level nickel inventories triggered by geopolitical risks further limited Tsingshan Group's inventory control and delivery capacity. The design of LME contracts exposes trading positions and motivations, while the LME trading system facilitates short-term price manipulation and other sniper behaviors, allowing the inference of the using contract, timing, and price manipulation ways employed in this sniper attack. Analysis of large position reports reveals that the essence of this sniper attack may be a battle for nickel resources. Finally, this study utilizes event analysis to confirm that the sharp increase in nickel futures prices on March 7th, 2022, was driven by trading factors rather than fundamental factors. The analytical framework proposed in this research, which combines case analysis, data analysis, and empirical analysis, is of significant value in identifying sniper risks, recognizing market manipulation, and better evaluating related risks for early warning and prevention. Reference | Related Articles | Metrics

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The Effect of Charismatic Leadership on Followership: A Moderated Mediation Model Jia Jianfeng, Niu Xueyan, Zhao Ruonan, Li Zhigang Management Review    2021, 33 (6): 181-191.   Abstract （541）      PDF （1244KB）（850）       Knowledge map    With the flat development of organizations and the embodiment of the value of human capital, employees’ followership has increasingly become a key to enhancing enterprise competitiveness and maximizing corporate benefits. As an influential factor, charismatic leadership style plays an important role in inspiring followership. Based on the conservation of resources theory, this research collects a sample of 223 employees’ data by questionnaire at three time points. Hierarchical regression and bootstrap are adopted to reveal the relationship between charismatic leadership and followership, the mediating effect of psychological availability and the moderating effect of perceived human resource management strength, thus building a moderated mediation model. The research shows: Firstly, charismatic leadership has a positive influence on followership. Secondly, psychological availability partially mediates the relationship between charismatic leadership and followership. Thirdly, perceived human resource management strength plays a positive moderating role between charismatic leadership and psychological availability. Fourthly, perceived human resource management strength also moderates the mediating role of psychological availability. The research results not only confirm the mechanism of charismatic leadership on followership, uncover the black box of influencing process and discover the boundary conditions, but also enrich the utilization of conservation of resources theory. At the same time, this research provides practical enlightenment for managers to develop charismatic leadership style in organizational situations to enhance employees’ followership. Reference | Related Articles | Metrics

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Social Amplification Effect of Public Perception Based on Big Data Text Mining—A Case Study of Business Environment in Heilongjiang Province Liu Kan, Sun Xueying, Zhou Hongrui Management Review    2025, 37 (9): 222-236.   Abstract （33）      PDF （5828KB）（41）       Knowledge map    In the we-media information age, the role of public perception is becoming more and more obvious, and the deviation of public perception will bring significant negative impact. Establishing an effective analysis method of the dimensions of public perception and theme evolution can provide a theoretical basis for identifying public opinion biases and optimizing public opinion ecology. However, it is difficult to identify and describe the evolution process of public perception, which is characterized by fragmentation, diversification and multi-dimensionality. Based on the social amplification effect theory and big data text mining method, this paper identifies the evolution process of public concerns and sentimental attitudes from the perspective of public “amplification station” and dynamic evolution by dividing time slices, and constructs a system framework for the evolution analysis of public perception. Based on the data of public comments from 2016 to 2022, this paper explores the social amplification effect of public perception of business environment in Heilongjiang Province and its influencing factors. The results show that the combination of social amplification theory and text mining method can effectively identify the evolution of public perception and the formation process of public opinion bias, and optimize the cultural ecological environment. Under the effect of social amplification, the public perception shows an evolution process from objectiveness to subjectiveness, and finally forms the deviation of public opinion. The public perception of business environment is mainly affected by economic development, government policies and efficiency, and tourism. At the same time, the empirical analysis shows that the negative sentiment of public perception of business environment in Heilongjiang Province is caused mainly by economic depression, and intensified by the epidemic, economic downturn and the slowdown of tourism development. These conclusions provide guidance for Heilongjiang Province to formulate effective strategies for improving public perception of business environment. Reference | Related Articles | Metrics

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External Technology Acquisition in Open Innovation and Product Diversification: The Moderating Effect of Dynamic Capabilities Zhao Feng, Wang Tienan, Wang Yu    2016, 28 (6): 76-85,99.   Abstract （375）      PDF （1435KB）（1124）       Knowledge map    In the open innovation, external technology acquisition and its effect on enterprise performance have been concerned widely. But there are few studies about the effect of external technology acquisition on product diversification. This paper conducts a multivariate hierarchical regression analysis using the data of high-tech listed companies in 2010-2012 to test the effect of external technology acquisition on product diversification and the moderating effect of three elements of dynamic capabilities on the relationship. The result shows that external technology acquisition has a positive impact on product diversification significantly, and absorptive capability, adaptive capability and innovative capability of dynamic capabilities moderate the relationship between external technology acquisition and product diversification positively. The study enriches and expends the findings in the field of external technology acquisition and product diversification, providing theoretical guidance for the companies to promote product diversification through external technology acquisition. Reference | Related Articles | Metrics