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An Empirical Study on the Complexity of China's Real Estate Market Zhang Pinyi, Yang Juanni Management Review    2022, 34 (7): 47-56.   Abstract （310）      PDF （1301KB）（2230）       Knowledge map    The abnormal fluctuations of the real estate market and the uncertainty of the impact of economic policy adjustments on the real estate market have drawn great attention of the government and scholars. Based on the theory of complexity science, this paper uses complexity methods to study the complexity characteristics of China's real estate market by correlation dimension tests, Lyapunov index tests, dissipative entropy method and R/S analysis method. The results imply that China's real estate system has the non-linear characteristics of "spikes and thick tails" and the chaotic characteristics of inherent randomness and sensitivity to initial values. Moreover, under the monetary policy, the real estate system is in an orderly state, with the characteristics of dissipative structure, long-term memory and self-similar fractal structure. Therefore, China's real estate system cannot achieve an orderly situation by itself, and it is necessary to combine with the continuous monetary policy regulation to achieve a healthy and orderly development of the real estate market. Reference | Related Articles | Metrics

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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 （355）      PDF （3327KB）（4945）       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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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 （201）      PDF （1826KB）（451）       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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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 （293）      PDF （1473KB）（1728）       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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Quality Effects: Evidence from Chinese Stock Market Li Bin, Feng Jiajie    2019, 31 (3): 14-26.   Abstract （889）      PDF （1290KB）（1756）       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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Vertically and Horizontally: Customer Concentration, Coupling Coordination Degree and Firm Performance Shi Jinyan, Yu Conghui, Li Yanxi Management Review    2024, 36 (6): 229-242.   Abstract （241）      PDF （1692KB）（838）       Knowledge map    This research explores the impact of customer concentration (CC) on firm performance from the perspective of vertical supply chain, and further discusses the moderating effect of the coordinate interaction and competitive coercion between customers from the perspective of horizontal supply chain. Based on the data of Shanghai and Shenzhen A-share listed companies and their top five customers, the empirical results show an inverted U-shaped relationship between CC and firm performances, which is more pronounced in non-stateowned enterprises. Furthermore, we build a set of customer coupling coordination degree metrics from the perspective of major customers’ purchasing behavior, and find that the inverted U-shaped relationship between CC and firm performance is strengthened by customer coupling coordination degree. In other words, the improvement of customer coupling coordination degree will strengthen both the positive relationship between moderate concentration and firm performance and the negative relationship between over-concentration and firm performance. This paper deepens the research into the mechanism of how CC influences firm performance, and provides empirical evidence for explaining the impact of principal relationship in supply chain on firm performance from multiple perspectives. 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 （216）      PDF （3649KB）（929）       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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An Empirical Study on Borrowers' Paying Behavior of “Robbing Peter to Pay Paul” Lan Rujia Management Review    2024, 36 (5): 25-39.   Abstract （201）      PDF （2960KB）（488）       Knowledge map    The rapid development of China's Fintech online lending platforms has provided borrowers with more accesses to funds, espe-cially by “robbing Peter to pay Paul”. Using micro data from one of the largest cash loan platforms in China, this paper empirically stud-ies the paying behavior of borrowers “robbing Peter to pay Paul” from two perspectives:payday loans' order level and borrower level. This study shows borrowers who are “robbing Peter to pay Paul” have higher probability of default or late payment. The more frequently a borrower uses payday loan “huabei”, the more likely the borrower is to default or delay payment. Default or late payment is more likely to occur in male than in female, and in those who live in small cities than those who live in big cities. This paper tries to explain the bor-rowers' default from the aspect of “robbing Peter to pay Paul”, and the conclusions are helpful for supervising China' online lending market, improving personal credit system and regulating the cash loan market. Reference | Related Articles | Metrics

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Research on Railway Commonweal Transportation Subsidy Mechanism in China Based on Game Theory Zhang Yinyan, Tong Qiong    2018, 30 (4): 235-246.   Abstract （365）      PDF （1250KB）（880）       Knowledge map    Railway transportation bears heavily on the people's livelihood and especially on public welfare as commonweal transportation service is provided at prices lower than market prices. Therefore, developing a railway transportation subsidy mechanism is of great significance for railway transportation to play a role as a commonweal tool in China. First, by analyzing different railway commonweal transportation subsidy mechanisms of China, Britain, France and Norway, this paper summarizes four railway commonweal transportation subsidy schemes, i.e., cross-subsidy and loss subsidy scheme, franchise and the lowest subsidy bid, fixed subsidy for each unit of freight contract and performance subsidy contract. Then, this paper observes the benefits associated different situations directly, by analyzing players' best responses under different institutional arrangements from the perspective of game theory. At last, based on our own national conditions, this paper analyzes the applicability of four railway commonweal transportation subsidy schemes in China, and presents recommendations:cross-subsidy and loss subsidy scheme has the lowest efficiency, so it must be reformed as soon as possible; in the short term, performance subsidy contract is suitable for China; in the medium term, the most appropriate subsidy mechanism should be fixed subsidy for each unit of freight contract; and in the long term, competition should be introduced into the railway transport industry and the structure of railway transportation market should be adjusted in such a manner as to ensure that multiple railway transportation players will be invited for the franchise bidding with the lowest-subsidy. Reference | Related Articles | Metrics

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Measurement and Application of News-based Equity Market Volatility in China Yang Jianlei, Yang Chunpeng, Cui Wenxiao Management Review    2023, 35 (9): 26-36,101.   Abstract （283）      PDF （1666KB）（762）       Knowledge map    This paper constructs a newspaper-based Chinese Equity Market Volatility (CEMV) tracker that moves with the realized volatility of the Chinese stock market. Using the macroeconomic data from January 2005 to October 2020, we further estimate a structural vector autoregressive (SVAR) model to assess the impact of CEMV on the Chinese economy and equity prices. We find that:(1) The CEMV index peaks are closely related to the large market fluctuations. Regressing the realized volatility of the stock market index on contemporaneous EMV values yields a significant slope coefficient. (2) Parsing the underlying text, we construct the CEMV indexes of four policy categories that respond differently to specific market shocks. (3) The stock market volatility driven by policy news foreshadows declines in output growth, price levels and equity returns. Moreover, CEMV has an overall positive impact on money supply growth and exacerbates the short-term fluctuations in investor sentiment. Reference | Related Articles | Metrics

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Interpretable Corn Futures Price Forecasting with Multivariate Heterogeneous Data Zeng Yurong, Wu Binrong, Wang Lin, Zhang Jinlong Management Review    2023, 35 (12): 40-52.   Abstract （371）      PDF （2708KB）（499）       Knowledge map    The prediction and early warning of corn futures prices can help guide the high-quality development of the agricultural economy. Since June 2020, the corn futures prices have fluctuated violently, and accurate and efficient corn futures price forecasting methods are urgently needed. Given the problem that the existing researches do not fully consider the pandemic situation, policy regulation, and potential forecast information in news texts, this research, based on both qualitative and quantitative data, proposes an effective forecast framework for corn futures price interpretability, which takes multiple factors into consideration, such as the supply and demand relationship of the corn market, policy adjustments, international market shocks, epidemic shocks, the impact of emergencies and other factors that lead to the fluctuation of corn prices. At the same time, aiming at the problem of insufficient interpretability of existing corn futures price prediction, a novel DE-TFT interpretable corn futures price prediction model is proposed. The differential evolution algorithm is used to efficiently optimize the parameters of the Temporal Fusion Transformers (TFT). TFT is a novel attention-based deep learning model that combines high-performance forecasting with temporal dynamic interpretable analysis, showing excellent performance in forecasting research. The TFT model can produce interpretable corn futures price prediction results, including attentional analysis of time steps and importance ranking of input variables. In the empirical study, the latent dirichlet allocation topic model is used to analyze the content and topics of corn news information and policy adjustments collected by “China Grain Network”, and the CNN classification model is used to extract the potential prediction information of news information. The interpretable experimental results show that the introduction of the Baidu index “pandemic”, which reflects the domestic epidemic situation and the quantified corn news text features, can further improve the accuracy of corn futures price prediction. 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 （355）      PDF （2788KB）（663）       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 （469）      PDF （3628KB）（871）       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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Estimating the Social Cost of Carbon: Research Progress and Policy Implications Wu Bingbing, Li Xiuting, Ouyang Lu Management Review    2025, 37 (5): 53-66.   Abstract （120）      PDF （1639KB）（285）       Knowledge map    The social cost of carbon (SCC) is a quantitative benchmark and an important analytical tool for climate policy. There have been extensive related international experience in estimating SCC values and applying SCC in policy analysis and formulation, but there is no official SCC calculation result in China. To provide a useful reference for improving the carbon peak and carbon neutrality policy system, this paper sorts out the relevant research results of SCC from the aspects of conceptual analysis and comparison, measurement methods and key parameters, policy significance and international practices and focuses on controversial issues such as the relationship between SCC and carbon pricing, international SCC and regional SCC, equity weighting, uncertainty, etc. This paper believes that in the process of building and improving the carbon peak and carbon neutrality policy system in China, we can try to introduce SCC valuation as a quantitative benchmark for carbon pricing and carbon trading tools. Based on the status quo of carbon emissions and carbon trading practices in China, as well as the characteristics of existing institutional frameworks and policy tools, we can also promote various carbon trading tools to manage carbon emissions coordinately, keep carbon prices within a reasonable range, and balance the fair relationship between generations, industries, and regions in the process of reducing carbon emissions. Reference | Related Articles | Metrics

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Guarantee Network Risk Contagion Mechanism： Path Analysis and Empirical Research Lv Jing, Wang Ying, Guo Pei Management Review    2022, 34 (3): 67-78.   Abstract （431）      PDF （1485KB）（466）       Knowledge map    From the network structure of relations in guarantee network, we apply network analysis and the data of listed companies from 2003 to 2017 on the Shanghai and Shenzhen stock exchanges to analyze guarantee network risk contagion mechanism. The results show that negative shock or the increase of relations significantly exacerbates risk contagion. But negative shock can only lead to risk contagion through guarantee chain, which demonstrates that the path of guarantee network risk contagion has relationship transitivity, which de- pends on the relation of guarantee chain. In the process of guarantee network formation, the ineffective guarantee contract and asymmetric information caused by lack of legal environment and the rigid restriction of guarantee contracts or implicit guarantee of state-owned enter- prises caused by low financial marketization are drivers underlying enterprises' motivation to join the guarantee chain and this will finally lead to risk contagion in guarantee network. Furthermore, the negative shock has a great influence on these enterprises with a high be- tweenness and those highly related enterprisess tend to gain prosperity or sufer loss jointly. Therefore, the government should improve in- stitutional environment and visual supervision of network structure of guarantee behavior among listed companies. Reference | Related Articles | Metrics

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A Research on the Mechanism of How Multi-factor Linkage Effect Drives Knowledge Workers' Taking Charge: Qualitative Comparative Analysis Based on AMO Theory Ma Ling, Liu Shuo, Zhao Shuming, Wang Siqi Management Review    2023, 35 (6): 205-216.   Abstract （230）      PDF （1465KB）（311）       Knowledge map    With the increasing environmental uncertainty, how to motivate knowledge workers' taking charge behavior has become a focus of researchers at home and abroad. Based on AMO theory and fsQCA method, this paper makes a two-stage survey of knowledge workers in 210 enterprises and explores the driving configuration of knowledge workers' taking charge behavior driven by multi-factors such as role breadth self-efficacy, prosocial motivation, empowering leadership, task significance and organizational support. It is found that the driving mechanism of knowledge workers' high taking charge behavior has six configurations, which can be summarized and integrated into three types: capability-driving based on leadership empowerment, capability-driving based on task guidance and motivation-driving based on leadership empowerment. The driving mechanism of knowledge workers' non high taking charge behavior has four configurations, which are divided into two types: self-efficacy deficiency and organizational support deficiency. And there is an asymmetric causal relationship with the driving configuration of high taking charge behavior. This paper reveals effective ways to motivate knowledge workers to take charge, which are helpful for enterprises to achieve sustainable development in the face of challenges and competition. Reference | Related Articles | Metrics

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New Infrastructure Construction and High-quality Economic Development Tong Jian, Zhang Cong, Yan Yong Management Review    2024, 36 (6): 81-93.   Abstract （185）      PDF （1271KB）（295）       Knowledge map    Coordinating the infrastructure construction is a clear requirement of the Report of the 20th National Congress of the Communist Party of China, where the coordinated development of “new” and “old” infrastructure is the key to high-quality economic development in China. Based on identification of the production externalities of “old infrastructure” and the network externalities of the “new infrastructure”, breaking through the static research frame, this paper studies the structural change effect of infrastructure investment on the path of economic growth. It finds that the short-term stimulus effect of “old infrastructure” is stronger than that of the “new infrastructure”, while the long-term economic stimulus effect and innovation incentive effect of the “new infrastructure” are obviously stronger than that of the “old infrastructure”. Meanwhile, “term constraint” is the key variable for the government to set the time point of the structural transformation of infrastructure investment. Government concerning more on the short-term economic growth target with less policy attention period often delays the time point of the structural transformation of infrastructure investment, which leads to the “step down” phenomenon of economic growth however. The empirical results further verify that “old infrastructure” has given full play to production externalities in the early stage of economic growth, whereas the incentive effect of “old infrastructure” on economic growth and innovative development is significantly weakened. While, the incentive effect of “new infrastructure” on economic growth and innovative development is significantly enhanced. Therefore, the government should combine the relative changes of marginal output of “new” and “old” infrastructure, adapting to local conditions, to promote the transformation of “new” and “old” infrastructure as soon as possible, and to coordinate the effective improvement of economic quality and reasonable growth of quantity. Reference | Related Articles | Metrics

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A Case Study on the Ecological Dominance of Technologically Leading Enterprises in Emerging Technology Innovation Ecosystems He Jianhong, Su Yuan, Li Lin, Gao Ping Management Review    2025, 37 (8): 276-288.   Abstract （166）      PDF （3323KB）（121）       Knowledge map    Enabling technologically leading enterprises to acquire and maintain ecological dominance in the emerging technology innovation ecosystem is an important measure for nurturing “chain leaders” and enhancing the autonomy of the innovation chain industry chain. However, this goal often faces challenges such as dynamic environmental changes, resource misallocation within the enterprise, and strategic misalignment. The paper, based on the “Condition-Action-Outcome” analytical approach, takes CATL as a case study, and divides the process of acquiring and maintaining dominance in the emerging technological innovation ecosystem into two stages: “riding on the wind” and “achieving long-term success.” It explores how CATL, guided by strategic thinking, orchestrates resources to acquire and sustain its dominance, and constructs a process model for technologically leading enterprises to gain and maintain dominance in emerging technological innovation ecosystems. The findings are as follows. First, the coupling of the external industrial environment and technological environment opens a window of opportunity for enterprises to develop strategic foresight and strategic symbiosis thinking based on different stages of ecosystem dominance development. Second, implementing different resource orchestration methods based on the resource differences at various development stages is key to improving resource orchestration efficiency, locking in and amplifying existing advantages, and thereby acquiring and maintaining ecosystem dominance. The research conclusions provide valuable insights for technologically leading enterprises in acquiring and maintaining dominance in emerging technology innovation ecosystems in a complex and ever-changing environment, thereby providing beneficial guidance for nurturing and growth of technologically leading enterprises. Reference | Related Articles | Metrics

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Fund "Holding Together": Performance and Crash Risk Su Zhi, He Xu, Zhang Yongji Management Review    2024, 36 (3): 30-44,145.   Abstract （184）      PDF （1462KB）（401）       Knowledge map    From 2006 to 2020, China’s mutual funds “held together” four times, each of which witnessed a process of deepening and rapid disintegration. In this paper, we take China’s open-ended active equity funds as a sample and use the funds’ shareholding matrix and industry matrix to construct a fund overlap index to study their “holding together” and its impact on them. The results show that: first of all, China’s funds have obviously similar stock portfolio and industry portfolio, funds show obvious characteristics of “holding together” and “holding together” can significantly improve the performance of funds; second, “holding together” help funds with weaker investment abilities and more conservative investment styles to achieve higher returns, but it is not conducive to funds with stronger investment abilities. Further research finds that “holding together” increases fund crash risk, which is not conducive to the stability of the securities market. The research of this paper is of great significance to the investment strategy selection of fund managers and the prevention of fund market risks. 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 （251）      PDF （2603KB）（803）       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