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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 （322）      PDF （3327KB）（3574）       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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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 （181）      PDF （1750KB）（139）       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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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 （105）      PDF （1128KB）（100）       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 （110）      PDF （4257KB）（94）       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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Research on the Mechanism of How Digital-Green Synergistic Transformation Influences Firm Performance in Manufacturing Sector Zhang Zhiwei, Zhang Ning, Xiao Tusheng Management Review    2025, 37 (11): 67-80.   Abstract （77）      PDF （1184KB）（77）       Knowledge map    The digital-green synergistic transformation (referred to as “dual synergy”) in manufacturing firms is an inevitable requirement for developing new quality productive forces and advancing high-quality development, as well as a critical pathway to enhance corporate competitiveness. Existing studies, both domestic and international, have separately explored the impacts of digital and green transformations on the performance of manufacturing enterprises, yet research on the impacts of dual synergy transformation remains scarce. This paper, based on data from China’s A-share listed manufacturing firms from 2007 to 2022, constructs a dual synergy index for manufacturing firms using the coupling model method and empirically tests the impact of dual synergy on firm performance. The findings reveal a nonlinear U-shaped relationship between dual synergy and firm performance, where positive benefits emerge only after a threshold is crossed. Mechanism analysis indicates that both efficiency and cost channels mediate this relationship: dual synergy first suppresses and then promotes efficiency (U-shaped), while initially increasing and subsequently reducing costs (inverted U-shaped), thereby influencing performance. Environmental regulation and industrial structure rationalization moderate the U-shaped relationship between dual synergy and firm performance, with stronger environmental regulation and higher industrial structure rationalization flattening the curve. Heterogeneity analysis shows that the U-shaped relationship holds for both heavily and non-heavily polluting firms (more pronounced in the latter), as well as for firms in central/eastern regions and high-tech industries, but not for western regions or non-high-tech firms. This study provides empirical evidence for theoretical and practical research on dual synergy and offers strategic insights for manufacturing firms to enhance competitiveness. Reference | Related Articles | Metrics

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Digital Green Technological Convergence Asset Structure Mismatch and High-quality Development of Enterprises—Moderating Effect of Knowledge Combination Ability Li Weiming, Cao Xia, Zhang Xin Management Review    2025, 37 (11): 54-66.   Abstract （85）      PDF （1169KB）（71）       Knowledge map    The integration of digital technology and green technology can drive enterprises to optimize resource allocation and play an important role in achieving high-quality development. This research uses invention patent information to measure the digital and green technology integration behavior of enterprises, and takes A-share listed companies in emerging industries as samples to study the impact of digital and green technology integration on the high-quality development of enterprises and its mechanism. The study finds that the width and depth of the digital and green technology integration of enterprises have a positive impact and a positive U-shaped impact on the high-quality development of enterprises respectively, and the above conclusions are still valid after the robustness test. The mechanism analysis shows that the width and depth of digital and green technology integration can promote the high-quality development of enterprises by improving the mismatch of asset structure. Knowledge combination ability only positively moderates the relationship between the breadth of integration and the high-quality development of enterprises. The heterogeneity analysis shows that the significance of the impact of the width of digital and green technology integration on the high-quality development of enterprises shows a heterogeneity pattern of “eastern region>central region>western region,” and shows a more significant positive impact in the samples of non-state-owned enterprises, while the depth of digital and green technology integration only shows a significant U-shaped impact in the samples of eastern enterprises and non-state-owned enterprises. The research conclusions of this paper can enrich and expand the relevant theories of digital and green technology convergence, and provide practical support and policy enlightenment for China’s enterprises to promote the convergence of digital and green technology and promote the high-quality development of enterprises. Reference | Related Articles | Metrics

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Dynamic Analysis of Financial Innovation, Risks and Supervision Based on Tripartite Evolutionary Game Gong Qingbin, Diao Xundi, Wu Chongfeng Management Review    2025, 37 (7): 3-14.   Abstract （208）      PDF （1620KB）（327）       Knowledge map    Based on the strategic interaction and behavioral assumptions of financial institutions, investors and market regulators, a tripartite evolutionary game model of the financial innovation is constructed. The study establishes a time-varying return matrix for the game by taking account of the correlation between investor participation and market risk levels, as well as their impacts on participant behavior. With the dynamical system method, the equilibria of the model are solved, and the asymptotic stability conditions of equilibria are investigated. The result shows that the mixed strategies are not evolutionary stable strategies (ESS). The evolutionary dynamics are influenced by many factors such as the risk level of financial innovation, the efficiency of supervision, the innovation costs, and investment costs. In order to achieve the low-risk regulatory goals, regulators need to take measures to reduce regulatory costs, improve regulatory efficiency, and increase input costs of high-risk financial products. The numerical simulations further demonstrate the complexity of market dynamics under different parameter conditions, as well as the impact of regulatory policy on market evolution. When there are multiple equilibria, regulators should take several measures simultaneously by changing the initial market conditions and equilibrium stability conditions. This study enriches the theoretical research on financial innovation and regulation, and provides significant implications for formulating and adjusting regulatory strategies. Reference | Related Articles | Metrics

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How Artificial Intelligence Affects Corporate Disruptive Green Innovation: A Knowledge Recombination Perspective Zhou Yuan, Dai Xingliang, Xu Guannan Management Review    2025, 37 (11): 206-218.   Abstract （78）      PDF （1315KB）（63）       Knowledge map    Disruptive green innovation (DGI) is essential for achieving carbon neutrality goals; however, its development is constrained by the dual challenges of externalities and substantial knowledge burdens. Artificial Intelligence (AI), with its potential to act as an “invention of a method of invention,” raises important yet underexplored questions concerning whether and how it influences firms’ DGI. Drawing on the knowledge recombination perspective, this study develops a theoretical framework to elucidate the mechanisms through which AI technologies can facilitate DGI at the firm level. To empirically validate this framework, we utilize panel data from China’s A-share listed manufacturing firms spanning 2007 to 2019. To improve measurement accuracy, we employ the BERT machine learning model to analyze corporate annual reports and construct firm-level AI adoption indicators, while the disruptiveness of green innovation is measured using the CD index derived from patent citation networks. The results reveal that AI significantly promotes DGI, primarily through dual pathways of expanding knowledge search breadth and deepening knowledge search depth. Heterogeneity analysis demonstrates that AI’s positive effects on DGI are more pronounced in regions with advanced digital infrastructure, weaker environmental regulation intensity, and firms receiving higher R&D subsidies. This study deepens the understanding of AI’s role in driving DGI at the micro-enterprise level, providing empirical evidence and theoretical insights for fostering synergistic development of intelligent and green transformation in corporations. Reference | Related Articles | Metrics

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AI Adoption, Dynamic Capabilities and the New Quality Productivity of Manufacturing Enterprises Guo Runping, Wang Kecai, Lu Xiaoxuan, Jiang Hu Management Review    2025, 37 (11): 81-93.   Abstract （70）      PDF （1191KB）（57）       Knowledge map    Artificial Intelligence (AI) is an important engine of the new quality productivity. AI adoption is of great significance for manufacturing enterprises to build dynamic capabilities and thereby enhance the new quality productivity. However, few studies have deeply analyzed the mechanism of AI adoption acting on the new quality productivity of manufacturing enterprises from the perspective of dynamic capabilities. Therefore, this paper, based on the theory of dynamic capabilities, uses the data of manufacturing enterprises listed on China’s A-share market from 2015 to 2021 to empirically analyze the impact of AI adoption on the new quality productivity of manufacturing enterprises, and examines the mediating role of the different dimensions of dynamic capabilities and the moderating role of market competition intensity. The research findings are as follows: (1) Al adoption significantly and positively enhances the new quality productivity level of manufacturing enterprises, with the results remaining robust after multiple robustness tests; (2) Dynamic capabilities mediate the relationship between AI adoption and the new quality productivity of manufacturing enterprises; (3) Market competition intensity plays positive moderating roles among AI adoption and the new quality productivity of manufacturing enterprises；(4) Market competition intensity exerts differential moderating effects: it positively moderates the association between innovation capability and the new quality productivity in manufacturing enterprises, negatively moderates the relationship between absorptive capacity and the new quality productivity in manufacturing enterprises, while demonstrating no significant moderating effect on the linkage between adaptive capability and new quality productivity. The research findings contribute to a deeper understanding of the mechanisms through which AI influences new quality productive forces in manufacturing enterprises, extend the theoretical exploration of dynamic capability into AI-driven contexts, deepen the understanding of the boundaries of different dynamic capability dimensions, and enrich the antecedent research on the new quality productivity of manufacturing enterprises. Furthermore, this study offers actionable strategies for Chinese manufacturing enterprises to cultivate and enhance their new quality productive forces. 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 （571）      PDF （1371KB）（1790）       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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Research on the Process of Achieving Sustainable Digital Transformation in Manufacturing Enterprises: From the Perspective of “Digital” and “Green” Resource Orchestration Wang Yonggui, Zeng Jing, Wang Linlin Management Review    2025, 37 (11): 245-259.   Abstract （62）      PDF （1720KB）（49）       Knowledge map    Promoting the integration of digitalization and greenification is an objective requirement for enterprises to achieve green and low-carbon transformation, and it is also an essential part of promoting the comprehensive green transformation of the entire economy and society. As the micro-level drivers of ecological progress and economic growth, enterprises should implement a sustainable digital transformation strategy oriented by the integration of digitalization and greenification. This is a key measure to achieve the “dual-carbon” goals and increase benefits. Based on the theoretical perspective of resource orchestration and taking Schneider Electric as a case study, this paper explores how manufacturing enterprises can orchestrate resources and form corresponding organizational capabilities to achieve sustainable digital transformation. The research findings indicate that the sustainable digital transformation of manufacturing enterprises is an iterative process of gradually realizing technological sustainability, economic sustainability, and environmental sustainability. During this process, enterprises go through the stages of resource development and capability generation, resource revitalization and capability response, and resource linking and capability leap. On this basis, this paper constructs a process model for manufacturing enterprises to achieve sustainable digital transformation. This paper opens the “black box” of the sustainable digital transformation process for manufacturing enterprises and provides theoretical support for enterprises to promote the integrated development of digitalization and greenification. 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 （664）      PDF （1237KB）（843）       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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How do Private Resource-based Enterprises Achieve Green Transformation under the Drive of Institutional Logic? Li Yuchen, Gao Xia, Ma Caiyun Management Review    2025, 37 (11): 260-272.   Abstract （56）      PDF （3994KB）（47）       Knowledge map    Under the background of the “Carbon Peaking and Carbon Neutrality Goals” and the development of New Quality Productive Forces, green transformation and upgrading of resource-based enterprises has become important keys to promote China’s path to modernization. Previous studies have mostly explored green transformation of manufacturing enterprises as a whole, lacking systematic characterization and in-depth analysis of the dynamic evolution process of resource-based enterprises’ green transformation driven by institutional logic. This study adopts a longitudinal single case study method to deeply analyze the internal formation mechanism of the evolution process of green transformation of resource-based enterprises, which is driven by institutional logic→resource action process→dynamic capability improvement→green transformation results. The research results indicate that: (1) resource-based enterprises have undergone a process of green transformation from “survival oriented” to “development oriented”. Government logic is the driving force behind the green transformation of resource-based enterprises, while market logic is the guiding foundation for the transformation. (2) Resource based enterprises strengthen dynamic capacity building through resource actions, deeply shaping and ultimately determining the effectiveness of green transformation through capacity building. (3) Resource based enterprises have successfully overcome the traditional productivity development model that relies heavily on resource inputs and high energy consumption during the transformation process, promoting the accelerated formation of new quality productivity. In summary, this study responds to the urgent need of the academic community for research on the green transformation and development of new quality productivity in small and medium-sized enterprises, providing a new theoretical perspective for the green transformation of local resource-based enterprises, and also providing beneficial management insights for the green transformation and upgrading of resource-based enterprises in China under the “Carbon Peaking and Carbon Neutrality Goals”. 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 （248）      PDF （2602KB）（401）       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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Research on the Mechanism and Path of Green Energy Efficiency Improvement Empowered by New Quality Productive Forces Shen Lizhong, Geng Chen, Li Xiuting, Dong Jichang Management Review    2025, 37 (11): 41-53.   Abstract （74）      PDF （1144KB）（46）       Knowledge map    Under the “dual carbon” strategic goal, cultivating and developing new quality productive forces has become a crucial approach to addressing energy shortages and enhancing green energy efficiency. This paper utilizes fixed-effect model, mediating model, and threshold model to examine the impact of new quality productive forces on green energy efficiency based on provincial panel data from China spanning 2013 to 2022. The findings indicate that the advancement of new quality productive forces effectively empower green energy efficiency, particularly in provinces with high resource dependence, a high level of industrialization, and significant industrial agglomeration. Green technology innovation and digital financial construction are the key mechanisms for new quality productive forces to empower green energy efficiency. Furthermore, it is observed that new quality productive forces exhibit a typical nonlinear effect on green energy efficiency. Specifically, when the level of the digital economy surpasses a certain threshold, the impact of new quality productive forces on improving green energy efficiency follows a nonlinear trajectory characterized by “U” shape of “restrain-hysteresis-excitation”. However, when the degree of environmental regulation exceeds a specific threshold value, its promoting effect demonstrates a nonlinear trend marked by marginal decline. 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 （268）      PDF （1473KB）（1206）       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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Institutional Foundations and the Spark of Innovation: A Commentary on the 2025 Nobel Prize in Economics Liu Meng, Liu Xielin Management Review    2025, 37 (10): 3-9.   Abstract （156）      PDF （1163KB）（133）       Knowledge map    This paper provides a systematic review of the foundational contributions made by Joel Mokyr, Philippe Aghion, and Peter Howitt, the 2025 Nobel laureates in Economics, to the understanding of “innovation-driven economic growth”. The three scholars jointly constructed a systematic framework for understanding how innovation drives economic growth from different dimensions: Mokyr, adopting a historical perspective, profoundly revealed the importance of the institutional environments and cultural beliefs that sustain innovation, emphasizing the foundational role of an open knowledge ecology and a culture of growth in nurturing sustained innovative dynamism; meanwhile, Aghion and Howitt, building on the Schumpeterian growth model, transformed the insight of “creative destruction” into verifiable micro-mechanisms, articulating the inverted-U relationship between competition and innovation and the “escape-competition effect”, which means firms engage in “quality‐ladder” type innovations in pursuit of monopoly rents, thereby constructing a dynamic balance between creation and destruction. Their research inherits and extends the theoretical traditions of Solow, Romer, Schumpeter, and the institutional school, collectively demonstrating that sustained economic growth depends on an ecosystem that fosters innovation, tolerates failure, and ensures the free flow of knowledge. The institutional implications for China’s new era of innovation-driven high-quality economic development are as follows: To achieve a strategic shift from the “catch-up paradigm” to the “frontier paradigm”, it is necessary to move beyond simply increasing research and development investments. The focus must be on fostering a culture that encourages exploration, establishing a fair and competitive market mechanism, and implementing tailored industrial policies that align with different stages of development. These efforts will lay a solid institutional and cultural foundation for leading innovation. Reference | Related Articles | Metrics

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Resource Buffer Sizing of Critical Chain Project Based on Time Value Zhang Junguang, Zhou Shang Management Review    2024, 36 (6): 212-218.   Abstract （118）      PDF （4768KB）（259）       Knowledge map    Classic researches on the critical chain project buffer sizing focus on the time buffer but ignore the impact of the resource buffer. In order to absorb the uncertainty of resources over time and determine a reasonable resource buffer size, a resource buffer sizing method is proposed based on time value. Firstly, the concept of resource time value is proposed considering the risk of resource effectiveness decreasing with time, and the changes of resources over time are calculated by combining the risk exposure. Secondly, the time of resource buffers are determined based on the duration and location of activities, and the location of resource buffers are determined based on the demand for resources. The resource buffers are set by reserving some resources before the execution of activities. Finally, Monte Carlo simulation is carried out by using MATLAB to verify the effectiveness of the proposed method. The experimental results indicate that this resource buffer sizing method can effectively reduce the consumption of project buffer and shorten the project duration. 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 （553）      PDF （1207KB）（1663）       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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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 （407）      PDF （3628KB）（724）       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