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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 （332）      PDF （3327KB）（4083）       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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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 （277）      PDF （1473KB）（1483）       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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Risk Spillover and Dynamic Conduction among Oil, Gold and Stock Markets: New Evidence from Implied Volatility He Meng, Zhu Xuehong, Chen Jinyu, Liao Jianhui Management Review    2025, 37 (1): 3-15.   Abstract （230）      PDF （2603KB）（687）       Knowledge map    The outbreak of COVID-19 has had a systematic impact on global financial markets. Based on a new perspective of implied volatility, a cutting-edge risk spillover network model is adopted to comprehensively examine the intensity, scale, and time-varying characteristics of risk spillovers among oil, gold, and major global stock markets. Then, based on the marginal spillover analysis method, the sources and dynamic transmission paths of risk spillovers among oil, gold, and stock markets are observed. The results show that there is a significant and asymmetric risk spillover effect among global oil, gold and stock markets, and the effect increased rapidly in the COVID-19 period, during which the spillover index reached its peak. The oil and gold markets are important sources of risk in the stock market, and the mainland Chinese stock market is the most important exporter of risk. After the outbreak of the epidemic, especially during the first two circuit breakers in the US stock market, the intensity of risk spillovers in the oil market and the Brazilian stock market increased sharply. With the effective control of the domestic epidemic, the mainland Chinese stock market has gradually transformed into a risk-taker. Reference | Related Articles | Metrics

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China's Financial Cycle: Index Construction and Its Interaction with Business Cycle Lu Xiaofan, Wang Pin, Hou Chengqi Management Review    2024, 36 (11): 50-60.   Abstract （182）      PDF （1826KB）（222）       Knowledge map    Because there is no unified standard to choose related financial variables in measuring financial cycle, according to the characteristics that financial variables are the leading indicators of business cycle and can predict the economic recession, this paper builds multiple financial cycle indexes, tests the ability of financial cycle indexes to predict economic recession by receiver operating characteristic curve, and then chooses the best financial cycle index. We find the best method is to measure credit scale by the credit provided by banks to the private non-financial sector, and estimate the dynamic factors by using credit, credit / GDP, housing price and stock price. The empirical analysis using TVP-SV-VAR model shows that, the impact on business cycle of positive financial cycle shock has obvious hump line characteristics and there is no significant time-varying effect; the impact on financial cycle of positive business cycle shock has obvious U-shaped curve characteristics and there is a significant time-varying effect; the impact on financial cycle of positive business cycle shock in the COVID-19 period is significantly different compared with other periods; the impact on business cycle of monetary policy shock gradually increases with the increase of the number of lag periods and is very lasting, and the impact on the financial cycle of it will peak very quickly and begin to weaken. Reference | Related Articles | Metrics

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Dynamic Analysis of the Risk Measurement in China’s Commodity Futures Market Zhang Tianding, Zeng Song Management Review    2023, 35 (4): 12-26.   Abstract （211）      PDF （3649KB）（733）       Knowledge map    The coexistence of high growth and high volatility over recent years in China’s commodity futures market where even “roller coaster” market conditions emerged in parallel with the international bulk commodity market have aroused wide concern over potential risks. Therefore, identifying and measuring commodity futures market risks is worth an in-depth exploration. In this paper, an observation-driven model based on score function is used to construct a dynamic semi-parametric model to estimate the expected shortfall and value at risk to measure and predict the risk of China’s commodity futures market. The results show that the generalized autoregressive scoring models based on student-T distribution, skewed student-T distribution, and asymmetric Student-t distribution have a good application. In this paper, the single-factor generalized autoregressive score model applied to risk measurement shows that the average loss of the single-factor generalized autoregressive score model is relatively smaller than that of the two-factor model, and the risk change of commodity futures can be observed more dynamically. The average Expected Shortfall of chemical futures is rather prominent, but the fluctuation range is small. In contrast, the Expected Shortfall extreme value of energy futures is higher, and the expected loss is as low as -13.03%. Comparatively speaking, the risk degree of the commodity futures market of agricultural and sideline products is relatively low. Commodity futures have exhibited varying degrees of risk accumulation in the near term since January 2021. Energy, chemicals, grains, soft commodities and grease oils futures showed significant expected losses from March 22 to April 14, 2021, while precious metals and non-ferrous metals futures showed significant expected losses from January 12 to January 15, 2021. Under the background of global economic recovery, the effective avoidance of commodity market risks has attracted the attention of market participants, policymakers and researchers. For the risk monitoring of the commodity market, we should pay attention to the impact of exogenous events and the persistence of risk events and carry out dynamic measurement of futures market risks. Reference | Related Articles | Metrics

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The Theoretical Logic and Level Measurement of New-quality Productive Forces Development under the Perspective of Artificial Intelligence Chen Xiaohong, Huang Chengdong, Yuan Yige, Tang Xiangbo Management Review    2025, 37 (11): 3-14.   Abstract （196）      PDF （1750KB）（150）       Knowledge map    Grasping the developmental patterns of productivity under the perspective of artificial intelligence holds significant value for propelling the qualitative transformation of productivity. This paper incorporates the transformative characteristics of AI into the theoretical analytical framework and systematically elucidates the conceptual connotations of the new type of productivity. Based on the three-factor theory of productivity, it reveals the theoretical logic through which the productivity system achieves qualitative leaps by renewing the connotations of its elements and optimizing their combinations, under the context of AI altering the modes of social production. On this basis, the paper further summarizes the measurement indicators of the three elements of productive forces from the perspective of AI and proposes a framework for measuring new-quality productive forces. It then uses this framework to assess the current state of new-quality productive forces at the provincial level. From a spatial dimension, the visualization of the characteristics of new-quality productive forces development reveals a polarization phenomenon among provinces and a stepwise development pattern of “coastal—riverine—inland” regions. Meanwhile, the regional imbalanced development of new-quality productive forces overlaps to some extent with that of economic levels, although some provinces at relatively lower economic levels have already shown a trend of using new-quality productive forces to achieve economic catch-up. This paper aims to enrich the theoretical system of new-quality productive forces and provide decision-making support for the practical application of AI in driving qualitative changes in productive forces by measuring the level of new-quality productive forces development. Reference | Related Articles | Metrics

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Quality Effects: Evidence from Chinese Stock Market Li Bin, Feng Jiajie    2019, 31 (3): 14-26.   Abstract （854）      PDF （1290KB）（1533）       Knowledge map    This paper studies the effect of quality factor in asset pricing based on Chinese A stock market. Derived from Gordon's growth model, we measure the quality of a listed stock by its profitability, safety, growth and dividend payout. This paper calculates "Quality Score" for each stock and examines how the Quality Score affects its price and return. This paper further constructs a QMJ (Quality Minus Junk) portfolio that goes long quality stocks and shorts junk stocks. The empirical results show that the stocks with higher quality score have higher relative prices and risk-adjusted returns; QMJ portfolio earns significant risk-adjusted return and is unaffected by market fluctuation; controlling for the QMJ factor, the size effect is significantly enhanced. For the robustness test, we also divide the samples into two subsamples according to the Non-Tradable Shares Reform, and empirical results are still robust. Reference | Related Articles | Metrics

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A Study of Linkage between Crude Oil and Natural Gas in North American Market: Based on the Empirical Analysis of Bayesian DCC-GARCH Model and LSTAR Model Chai Jian, Lin Jie, Liang Ting Management Review    2021, 33 (7): 16-28.   Abstract （341）      PDF （2788KB）（564）       Knowledge map    The characteristic of oil and gas as substitutes for each other makes the two show a certain correlation. The changes and linkage of oil and gas prices in the world's largest oil and gas consumer market will affect the global energy development pattern and investment strategy. Firstly, the paper studies the overall correlation between crude oil and natural gas yields in North America based on the Bayesian DCC-GARCH (Dynamic Conditional Correlation GARCH) model. In the case that the overall correlation between the two was less significant, the dynamic correlation characteristics of the two in trend, season and remainder are studied by STL decomposition. And then we analyze the nonlinear characteristics of correlation between oil and gas in trend through the LSTAR (Logistis Smooth Transformation Autoregressive) model. The results show the dynamic correlation between crude oil and natural gas yields in North American market is always positive, with a correlation range of[0.137,0.216] and a median of 0.181, the result of which could better reflect the time-varying characteristics of oil and gas linkage compared with the CCC-GARCH model (Constant Conditional Correlation GARCH). The correlation range of oil and gas is small, showing that there is no significant correlation between them. The results of STL decomposition show that there is a significant correlation between oil and gas yields in trend. And, LSTAR model could better characterize the correlation fluctuation and have a higher degree of fitting than AR model. The correlation between oil and gas in trend has a smooth transition at 2.026, and the transform speed from low zone to high zone is very fast. The results of the study have guiding significance for investors to increase their income, producers to control their costs, and the relevant government departments to formulate corresponding energy strategies. 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 （422）      PDF （3628KB）（770）       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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Risk Identification Model of Related Loans Based on Analysis of Multi-layer Complex Network Structure Zhang Enyong, Liu Chao, Li Yongli, Xia Lijuan Management Review    2024, 36 (5): 3-11.   Abstract （291）      PDF （2602KB）（419）       Knowledge map    Related loans refer to loans that are linked together due to a certain (or several) relationship(s) and these loans as a whole are likely to cause group default. Because of the complicated cross-bank loan and concealed influence relationship in related loans, it is difficult for banks to identify related loans and take effective measures. Based on the loan guarantee data of several commercial banks, this paper constructs a multi-layer complex network, then designs an algorithm to identify the related loan structure and analyzes the ef-fectiveness; the default rate of different related loans structures is calculated and compared with 4 risk indicators; finally, the signifi-cance of default risk of different related loans structures is tested. The result shows:(1) the multi-layer network related loan model and the recognition algorithm constructed in this paper greatly improve the efficiency and accuracy of related loan identification, and overcome the dual concealed problem of related loans that cannot be solved by the single layer network; (2) the betweenness and clustering coeffi-cient indicators are more consistent with the true default rate of related loans, while the indicators based on the clearing payment capacity and risk distance fail to predict the true default rate; (3) when there are circle-linked structure and sink structure in related loans net-work, the default risk of loans increases significantly. The model and method constructed in this paper provide a theoretical basis for identifying multi-bank and multi-relationship related loans, and have practical significance for banks to detect risk network structures and to control related loan risks. 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 （579）      PDF （1371KB）（1815）       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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The Impact of Corporate Digital Technology Innovation on the Development of New Quality Productivity in Local Economies Chen Rongda, Zhai Jiajun, Zhang Shuonan, Tao Kerun, Zhang Youbin Management Review    2025, 37 (11): 15-26.   Abstract （121）      PDF （1128KB）（115）       Knowledge map    Against the backdrop of deep integration between the real economy and the digital economy, digital technology innovation serves as a crucial driving force for the development of new quality productive forces. This paper examines the impact of enterprise digital technology innovation on local new quality productive forces and its underlying mechanisms, using a sample of listed companies on the Shanghai and Shenzhen Main Boards from 2015 to 2021. The empirical findings reveal that: (1) Enterprise digital technology innovation significantly promotes the enhancement of local new quality productive forces, a result further validated by robustness tests; (2) This promoting effect is realized through the optimization of human capital structure, improvement of investment efficiency, and advancement of high-quality enterprise development; (3) The promoting effect is inhibited in highly labor-intensive enterprises, amplified in regions with a developed digital economy, yet insignificant in less developed western regions and areas with lower levels of intellectual property protection. This study provides a new perspective for understanding how micro-level enterprise innovation improves local economic endowments and offers empirical support for advancing new quality productive forces. Reference | Related Articles | Metrics

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How does the Coupling Effect of Digital Transformation and Green Transformation Promote New-quality Productivity?—A Mixed-methods Study Based on the Dynamic Capability Theory Chen Yantai, Hao Yajie, Pan Dapeng Management Review    2025, 37 (11): 27-40.   Abstract （127）      PDF （4257KB）（101）       Knowledge map    Against the backdrop of deep integration between the global digital economy and green economy, the dual transition (synergistic digital and green transformation) has emerged as a core pathway for driving new quality productive forces. This study constructs an evolutionary game model to analyze the preconditions for government, enterprises, and digital service providers during the dual transition, revealing the mechanism through which this synergy promotes new quality productive forces. Key findings indicate that embedded innovation of green and digital technologies, self-reinforcing dynamic feedback of cost-benefit structures, and innovation ecosystems built through multi-agent collaborative networks are crucial for advancing new quality productive forces. Using FENGDENG as a case study, we dissect an enterprise’s evolution from singular green transition to dual transition, demonstrating how its “mutual-construction and co-change” mechanism between green dynamic capabilities and new quality productive forces achieves win-win economic-environmental outcomes. This research provides theoretical guidance and practical references for Chinese enterprises implementing dual transition. Reference | Related Articles | Metrics

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How does Digital Economy Promote the High-quality and High-benefit Development of Agriculture?—Evidence from Sample Data of 30 Chinese Provinces Zhang Mingyu, Wu Zheng, Su Zhiwen, Zhang Yihua Management Review    2025, 37 (12): 16-27.   Abstract （89）      PDF （1175KB）（51）       Knowledge map    As digital economy accelerates its penetration into agriculture and rural areas, it has become a crucial engine for promoting high-quality and high-benefit development of agriculture. How does the digital economy facilitate this agricultural advancement? Based on an in-depth interpretation of the connotation of high-quality and high-benefit development of agriculture, this paper systematically analyzes the mechanism by which digital economy promotes agricultural development. Using data from 30 Chinese provinces from 2011 to 2022 as research samples, we empirically examine the promoting effects of digital economy on high-quality and high-benefit development of agriculture. The main conclusions are as follows: First, digital economy can directly promote high-quality and high-benefit development of agriculture. This promoting effect is stronger in central regions, plain areas, and areas with higher levels of industrialization. Second, digital economy can indirectly promote high-quality and high-benefit development of agriculture by fostering agricultural technological innovation and enhancing rural entrepreneurship levels. Third, the promoting effect of digital economy on high-quality and high-benefit development of agriculture exhibits non-linear characteristics. Rural human capital positively moderates the relationship between digital economy and high-quality and high-benefit development of agriculture. When rural human capital surpasses 6.635, the promoting effect of digital economy development on high-quality and high-benefit development of agriculture undergoes a structural leap. This study helps reveal the mechanism by which digital economy affects high-quality and high-benefit development of agriculture, providing valuable policy insights for leveraging digital economy to promote agricultural advancement. To promote high-quality and high-benefit development of agriculture, efforts should be made to accelerate the construction of new digital rural infrastructure, stimulate the momentum of agricultural technological innovation, deepen support policies for rural entrepreneurship, and enhance the level of rural human capital. Reference | Related Articles | Metrics

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Literature Review and Prospects of Social Media Marketing: A Comprehensive Analysis of Core Database of Web of Science and CNKI Wang Yonggui, Wang Haoyue, Yang Jianglin, Liu Junqin Management Review    2024, 36 (8): 146-160.   Abstract （650）      PDF （1481KB）（798）       Knowledge map    In the era of the digital economy, the use of social media has transcended its traditional role in user communication and opinion sharing. Increasingly, enterprises are harnessing social media as a powerful marketing tool to improve their efficiency and enhance their brand assets. Consequently, social media marketing has attracted more attention from scholars and managers. However, research that aims at constructing a holistic framework for social media marketing is still in its exploratory stage, with several key issues to be resolved. Based on the core database of Web of Science and CNKI, this paper meticulously analyzes 1,472 pieces of English literature and 519 pieces of Chinese literature to construct an integrated framework for social media marketing research. The theoretical foundations of social media marketing research are summarized from three perspectives:individual perspective, interaction perspective and contextual perspective. Furthermore, the influencing factors are elucidated from four dimensions:consumers, enterprises, platforms and society, and the significant role is expounded from three dimensions:enterprise benefits, consumer benefits and society benefits. In addition, this paper explores the mediating effects of product innovation, brand assets and perceived value, as well as the moderating effects of societyrelated factors, enterprise-related factors, customer-related factors and technology-related factors. Then this paper further highlights the main issues in the existing social media marketing research and identifies future research directions to provide insights for developing more systematic theory of social media marketing and guiding social media marketing practices in future. Reference | Related Articles | Metrics

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Research on the Influence of Personalized Intelligent Recommendation on Consumers’ Online Impulse Buying Intention Fan Wenfang, Wang Qian Management Review    2022, 34 (12): 146-156,194.   Abstract （1177）      PDF （1390KB）（1654）       Knowledge map    With the rapid development of mobile internet era and the continuous application of high-tech such as artificial intelligence, personalized intelligent recommendation has become an important marketing method for e-commerce platform enterprises to meet consumers’ diversified preferences. Practice shows that personalized recommendation has an important impact on consumers’ buying behavior, and it helps to improve the performance of e-commerce platforms. Based on the flow experience theory and the perceived value theory, this paper discusses the influence of personalized intelligent recommendation on consumers’ online impulse purchase intention, and this mechanism of flow experience, perceived practical value and quality of online reviews. Through the investigation of 548 e-commerce platform consumers, the empirical study finds that personalized intelligent recommendation and its related dimensions (information presentation, system interaction and community influence) positively affect consumers’ online impulse purchase intention. Flow experience and perceived practical value mediate the positive relationship between personalized intelligent recommendation and consumers’ online impulse purchase intention. The quality of online reviews plays a moderating role in the impact of personalized intelligent recommendation on consumers’ online impulse purchase intention. The higher the quality of online reviews, the stronger the positive impact of personalized intelligent recommendation on consumers’ impulse purchase intention. Reference | Related Articles | Metrics

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Momentum Effect and Reversal Effect under Sticky Expectation and Overconfidence Wang Xianjia, Yu Zhiying, Chen Cong, Wu Liang, Rao Yulei, Yuan Ying Management Review    2025, 37 (12): 3-15.   Abstract （67）      PDF （2291KB）（42）       Knowledge map    This paper constructs an investor behavior model to describe investors’ belief bias by using sticky expectation and overconfidence and explains some typical asset price anomalies by discussing the correlation of the asset return in the model. The research results show that the model can explain the momentum effect and reversal effect in the market, and the larger the stickiness coefficient is, the later the inversion occurs. The overconfidence coefficient has a non-monotonic effect on the reversal period. The short-term momentum effect of the asset prices is robust over the whole period. The model can also effectively explain other financial anomalies, such as post-event price drift in event study and lead-lag effect of stock returns in the same industry. Empirical results show that sticky expectations and overconfidence provide a good explanation for the momentum and reversal effects. Among them, the momentum effect is more significant in portfolios with a higher stickiness coefficient. In portfolios with the same degree of stickiness, stocks with a higher level of overconfidence show a more significant long-term reversal effect. 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 （553）      PDF （1244KB）（958）       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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A Study into the Mechanism of How High-performance Work System Influences Employee Proactive Behaviors： A Cross-level Model Based on Social Context Theory Cao Man, Xi Meng, Zhao Shuming Management Review    2020, 32 (6): 244-254.   Abstract （670）      PDF （1237KB）（862）       Knowledge map    In recent years, proactive behavior has become an important research topic in the field of organizational behavior. Based on social context theory, this paper intends to explore the influence mechanism between high-performance work system and employee proactive behavior. We collect data from 110 senior managers, 110 human resources managers and 1105 employees. Research results show that high-performance work systems have a positive effect on proactive behaviors and employee relations climate fully mediates the relationship. And, environment uncertainty plays a moderating role in the relationship between high-performance work systems and employee relations climate such that the relationship between high-performance work systems and employee relations climate will be weaker when environmental uncertainty is high rather than low. This study contributes to both strategic human resource management and proactive behaviors literature. By examining the mediating role of employee relations climate, this study investigates the mechanism between high-performance work system and employee proactive behavior. Furthermore, the paper considers the effect of environmental uncertainty, thus extending the boundary conditions of proactive behaviors. Reference | Related Articles | Metrics

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Research on the Impact of Support Policies on the Promotion of New Energy Vehicles in China Li Xiaomin, Liu Yiran, Jing Bolun Management Review    2022, 34 (3): 55-65.   Abstract （639）      PDF （1306KB）（862）       Knowledge map    Quantitative evaluation of the effects of the new energy vehicle industry policy is conducive to providing a basis for the formu- lation and adjustment of China's follow-up policies. Based on the behavioral utility function of consumer vehicle demand and by choosing the monthly data of China's new energy passenger car market share in 2012-2018 as dependent variable, four government policies (re- garding financial subsidies, purchase tax exemption, no restrictions on the use and purchase of new energy vehicles and government/pub- lic procurement respectively) as independent variables and the selling price of new energy vehicles, battery prices, the difference be- tween oil and electricity prices, the number of new energy vehicle battery patent applications and the number of charging piles as control variables, this paper uses the time series cointegration model and error correction model to quantitatively evaluate the effects of the four policies. The findings are as follows. Firstly, in 2012-2018, the four policies all have a positive effect on the promotion of China's new energy vehicles and among them, the financial subsidy policy has the largest effect. Secondly, the effect of financial subsidies gradually increased from 2012 to 2016, but began to decrease from 2017 to 2018. In addition, each 1% increase in the new energy vehicle pro- curement by government and public institutions will lead to an increase of 0.331% in the market share of new energy vehicles; each 1% increase in car purchase demand suppressed by the purchase restriction policy will lead to a 0.312% increase in the new energy vehicles market share. So far as the controll variables are concerned, an increase in the price of new energy vehicles and battery is not conducive to the promotion of new energy vehicles, and the difference in the prices of petrol and electricity, the number of battery technology patent applications, and an increase in the number of charging piles has a positive effect on the promotion of new energy vehicles in the long term. Reference | Related Articles | Metrics