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Macroeconomic Conditions and Corporate Capital Structure: Empirical Evidence from Chinese Listed Companies Liu Shuntong, Yang Boyu, Wang Chenghao, Hu Yi Management Review    2023, 35 (10): 22-32.   Abstract （150）      PDF （1243KB）（497）       Knowledge map    Macroeconomic conditions are vital factors affecting the optimal capital structure of a company. Based on the economic situation of China, this paper systematically analyzes the impact of changes in macroeconomic conditions on corporate capital structure, and adds the shadow banking factor into the research framework for the first time. Using the financial data of listed companies, we construct corresponding static and partial dynamic adjustment models for analysis, and focus on the impact of shadow banking on corporate capital structure and adjustment speed. The empirical results can be summarized as follows. First, total market value and profitability are negatively correlated with book leverage, and book-to-market value ratio, capital expenditure and total non-current assets are positively correlated with book leverage. The influence of total assets is heterogeneous, which pushes up the book leverage of state-owned enterprises and reduces the book leverage of private enterprises. Second, the growth rate of industrial added value and the total market value of listed companies reduce the level of capital structure while inflation increases the level of capital structure. The growth of shadow banking reduces the level of capital structure, highlighting the structural contradictions in China’s financial system. Third, the capital structure adjustment cost and the difference in asset liquidity cause the difference between the adjustment of book leverage and market leverage, in which market leverage adjustment is faster. Fourth, shadow banking reduces the optimal corporate capital structure and positively regulates the speed of capital structure adjustment. Reference | Related Articles | Metrics

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Multiple Driving Paths and Performance of Green Supplier Integration: A Research Based on the Configurational Perspective Zhang Qiansong, Cheng Jiazhen, Feng Taiwen, Du Yunzhou Management Review    2023, 35 (7): 323-338.   Abstract （207）      PDF （2543KB）（392）       Knowledge map    Since 2010, China has become the world's largest industrial producer. However, the traditional energy-consuming and high- polluting manufacturing development model that has brought about increasingly obvious environmental issues is no longer able to meet the requirements of green transformation and high-quality development. Green supplier integration is a significant way to realize green transformation and improve the sustainable competitiveness of firms, and it is necessary to fully consider the matching role of technology, organization and environment to improve the level of green supplier integration. Accordingly, the multiple driving paths and performance of green supplier integration are important issues to be addressed. Based on the TOE framework and configurational perspective, we conduct a configuration analysis on 317 Chinese manufacturing firms and a typical case analysis on configuration solutions by integrating fuzzy set qualitative comparative analysis (fsQCA) and propensity score matching (PSM) methods to explore the differential driving path of supplier green integration and its effect on firm performance. The findings are as follows:(1) Any single factor does not constitute the necessary condition of high green supplier integration, but green training and development play a universal role in producing high green supplier integration; (2) There are four driving paths that constitute high green supplier integration, namely, big data analysis capability and green human resource-driven path under the dual culture of flexibility and control, big data analysis capability and green human resource-driven path under control culture, big data analysis capability and strategic green human resource-driven path under control culture-dominant, incremental big data analysis capability and green human resource-driven path under flexibility culture; (3) The absence of big data analysis capability and green human resource management is the key reason for non-high green supplier integration; (4) High green supplier integration generated by four driving paths has a differential impact on firm performance. The research conclusions can help better understand the complex interaction among multiple factors behind green supplier integration of China's manufacturing industry, and bring practical enlightenment for firm performance management and high-quality development. Reference | Related Articles | Metrics

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The Role of Joining Industry Associations in Improving the Survival of Member Enterprises: Latest Evidence from Online Lending Industry Hou Xinyu, Li Guangzhong, Zhang Shuai Management Review    2023, 35 (7): 3-13.   Abstract （239）      PDF （1270KB）（297）       Knowledge map    To analyze the effectiveness of the reputation mechanism in a typical information asymmetric market of peer-to-peer online lending, this paper develops a three-party evolutionary game model including lending platforms, industry associations and investors. Regarding joining an industry association as a reputation signal, it focuses on analyzing the evolutionary stabilization strategy of the system. Empirical data are collected to verify the reputation-enhancing effect of the industry association. The findings suggest that the effectiveness of reputation mechanism in online lending platforms depends on the certification and screening carried out by third-party institutions, i.e., the active screening by industry associations directly affects the proportion of online lending platforms operating in a self-regulatory manner as well as the survival of the group, and serves as an effective mechanism to achieve an equilibrium separation of high- and low-risk platforms. The empirical results of the coarsened exact matching method reveal that joining industry associations reflects a certain amount of reputation information, which indeed helps platforms strengthen their reputation and thus directly improves the survival of lending platforms. The intermediary effect model supports that the industry association enables the function of social capital empowerment and motivates platforms to apply for and obtain fund depository provided by commercial banks. Reference | Related Articles | Metrics

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The Impact of E-commerce Live Streaming on Consumers’ Purchase Intention: A Study Based on Grounded Theory Liu Luchuan, Liu Chenglin Management Review    2023, 35 (12): 182-189.   Abstract （198）      PDF （1324KB）（289）       Knowledge map    E-commerce live streaming has brought consumers a new shopping experience. Studying the mechanism of how e-commerce live streaming influences on consumers' purchase intention is of great significance to improve the quality of live streaming service and promote the healthy development of e-commerce live streaming business ecology. Through in-depth interviews with 57 respondents, this study constructs the mechanism model of the influence of e-commerce live streaming on consumers' purchase intention. The results show that, in the context of e-commerce live streaming, commodity factors, streamer factors and live streaming context factors affect consumers' engagement in e-commerce live streaming, and on this basis, they will ultimately affect consumers' purchase intention by influencing consumers' cognitive attitude and emotional attitude; At the same time, consumers' personal internal factors play a moderating role in the influence of commodity factors, streamer factors and live streaming context on consumers' engagement in live streaming. Reference | Related Articles | Metrics

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Research on the Construction Mechanism of Data-driven Dynamic Capabilities of Traditional Manufacturing Enterprises: Based on the Case Study of Digital Practice of Wahaha Group Co., Ltd. Chen Yu, Chen Yantai, Xie Fuji Management Review    2023, 35 (10): 340-352.   Abstract （201）      PDF （1421KB）（276）       Knowledge map    Traditional manufacturing enterprises are facing both new opportunities and challenges in the digital environment. How to build data-driven dynamic capabilities is the key to the success of traditional enterprise transformation. Taking Hangzhou Wahaha Group Co., Ltd. as a case study, this paper discusses the construction mechanism of data-driven dynamic capabilities. There are some main findings as follows. First, the data-driven dynamic capabilities of traditional manufacturing enterprises are composed of four dimensions: data-driven opportunity perception capability, data-driven industrial chain synergy capability, data-driven organizational transformation capability and data-driven value ecosystem capability. Second, these four capabilities can be subdivided into 13 main categories. Third, these four capabilities are progressive and mutually reinforcing. Among them, data-driven opportunity perception capability is the basis and prerequisite. Data-driven industrial chain synergy capability is the key and means of implementation. Data-driven organizational transformation capability is the guarantee and the supporting condition. Data-driven value ecosystem capability is leverage, with an amplification effect. The contribution of the paper is that a four-dimensional analysis framework is proposed, then the sources and interaction mechanisms of different dimensions are deeply analyzed. The conclusion of the paper has implications for how traditional manufacturing enterprises should carry out digitalization and transform digital resources into their data-driven dynamic capabilities. Reference | Related Articles | Metrics

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Substitution or Creation: How Intelligentization Affects China's Manufacturing Employment Cao Yaru, Liu Jun, Shao Jun Management Review    2023, 35 (9): 37-49.   Abstract （163）      PDF （1299KB）（274）       Knowledge map    This paper analyzes the mechanism of how intelligentization impacts the employment of China's manufacturing industry, and based on China's 2010-2019 provincial panel data, empirically tests the impact of intelligentization on the employment and skill structure of manufacturing industry. The results show that there is a "U-shaped" relationship between intelligentization and total employment in China's manufacturing. When the level of intelligentization is low, the substitution of employment will be the main factor, but the higher level of intelligentization will significantly promote employment growth. The employment creation effect is achieved through intermediate channels such as extending industrial chain and promoting technological innovation. Among them, the mediating effect of industrial chain extension is particularly obvious. Intelligentization is conducive to advanced manufacturing employment structure. With the increase in intelligentization, the demand for high-skilled and medium-skilled labor will increase, while the demand for low-skilled labor will decline. There is regional heterogeneity in the impact of intelligentization on manufacturing employment and its skill structure. To cope with the differential impact of intelligentization on manufacturing employment, we should further improve the quality of higher education and vocational education, optimize the content and model of skills training, formulate differentiated regional policies, and guide intelligentization to promote high-quality manufacturing employment. Reference | Related Articles | Metrics

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Data Element Empowerment, R&D Decision and Innovation Performance——Empirical Evidence from China Industry Song Wei, Cao Wenjing, Zhou Yong Management Review    2023, 35 (7): 112-121.   Abstract （208）      PDF （1242KB）（267）       Knowledge map    The new round of technological revolution and industrial reform determine that innovation performance depends not only on the improvement of factor allocation efficiency caused by data factor empowerment, but also on R&D decisions to a great extent. Using China's industrial panel data from 2005 to 2018, this paper estimates the effects of data element empowerment and R&D decision-making on innovation performance. The results show that with the significant improvement of data factor enhanced empowerment on the marginal productivity of traditional factors, exploratory R&D decisions motivated by the pursuit of complementary innovation resources and dedicated high-end assets can significantly improve innovation performance. The biased empowerment of data elements improves the high-end allocation efficiency of traditional elements. Aiming at absorbing the energy level of data elements, promoting the utilization R&D decision of high-end allocation of traditional elements contributes to the improvement of innovation level and has a significant positive effect on the improvement of innovation performance. The above findings have profound policy implications:to improve innovation performance, in addition to strengthening the scalability of data element empowerment, it also depends on a greater extent on unblocking the transmission channel of empowerment, improving the top-level overall planning and market mechanism design of R&D decision-making, so that R&D decision-making can play the leading and guiding role of data element empowerment. Reference | Related Articles | Metrics

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Leading Poorly under Challenge Stress? Indirect Influence of Team Leader's Challenge Stress on Subordinates' Creativity Li Jiangjin, Liu Chunlin, Li Hu Management Review    2023, 35 (7): 199-208.   Abstract （169）      PDF （1269KB）（258）       Knowledge map    While challenge stress has received considerable attention in the literature, current researches generally investigate the positive results of challenge stress on employees themselves but seldom concentrate on its negative results. In fact, good stress for individuals is likely to have a bad influence on others through interpersonal interactions-particularly among unequal leader-member relations. Based on the explicit monitoring theory, leaders may become self-focused under challenge stress, immersing themselves in the coping process of self-participation but ignoring the autonomy of subordinates when they advance work. We introduce this theory to propose that challenge stress undertook by leaders would decrease their empowering behaviors, thus adversely affecting subordinates' creativity. A large-scale investigation survey is conducted by three stages to branch teams of a world's top-500 company located in China's eastern cities of an environment in need of employees' creativity. This paper reveals the process about how team leaders' challenge stress brings negative effects on employees' creativity by the mechanism of leader's empowering behaviors. Moderating effects of leaders' accountability to superiors on the above mediating effect are verified, while the moderating role of leaders' accountability to inferiors is not found. This paper expands the research on the role of work stress from the intra-person effect on oneself to the interpersonal impact of leaders on subordinates, and has implications for the theoretical research and management practice of work stress and creativity in organizations. Reference | Related Articles | Metrics

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The Impact of Market Segmentation on Carbon Emissions from a Spatial Spillover Perspective——Empirical Evidence from 30 Provinces in China Pan Xiongfeng, Yuan Sai, Li Jiaqi Management Review    2023, 35 (7): 14-27.   Abstract （185）      PDF （1383KB）（237）       Knowledge map    Resolving the contradiction between balanced regional economic development and the achievement of carbon emission reduction targets is an important prerequisite for promoting regional market integration and formulating emission reduction policies. Nevertheless, few studies have taken a spatial spillover perspective to explore the mechanisms by which market segmentation affects carbon emissions. Drawing upon China's provincial panel data from 2006 to 2018 and employing spatial Durbin model, this paper tests the direct and indirect (spillover) effects of market segmentation on carbon emissions and further reveals the effect mechanism from a spatial spillover perspective. The findings show that market segmentation has a significant impact on carbon emissions. Local market segmentation has a positive direct effect on carbon emissions while neighboring market segmentation has a negative spillover effect on carbon emissions. Market segmentation promotes the inward shift of carbon emissions closer to home and limits the outward shift of carbon emissions closer to home, but does not inhibit the growth of carbon emissions. In terms of effect mechanisms, market segmentation significantly affects carbon emissions through the effects of economic scale change, industrial restructuring, energy structure optimization and technological innovation. In addition, there is spatial heterogeneity in the impact of market segmentation on carbon emissions between the North and the South, with it being more pronounced in the North. Reference | Related Articles | Metrics

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Analysis of New Energy Vehicle Enterprises' Technological Innovation Behavior Based on China's Dual-credit Policy Rao Yibang, Shu Tong Management Review    2023, 35 (7): 74-85,111.   Abstract （155）      PDF （1281KB）（228）       Knowledge map    The dual-credit policy implemented by the Chinese government has had a significant impact on the new energy vehicle industry. In order to study corporate-related innovation practices of new energy vehicles, the quantities of patent applications and research and development (R&D) investment are used as the measure of enterprise technological innovation practices, based on the 2009-2019 public enterprise data in the new energy vehicle industry. Also, the benchmark model is deployed to test the specific implementation effect of the dual-credit policy. The findings show that the dual-credit policy has promoted corporate R&D investment to a certain extent and stimulated corporate innovation, whereas what is more manifest is that there is a significant increase in non-patentable inventions. Additionally, the pursuit of innovation quantity is greater than that of innovation quality. Various industrial links of industrial chains in new energy vehicles have a certain degree of heterogeneity in innovation, and the intensity of R&D investment in the field of power batteries and electric motor control is significantly higher than that in the field of complete vehicles. In terms of policy recommendations, further refinement can be made according to the difficulty, depth, and potential value of the enterprises' innovative practices. With regard to high-tech R&D projects, especially the upstream power battery and motor electronic control fields of new energy vehicle industrial chains, increased early support is supposed to promote enterprises' substantial innovation. As regards low-fuel-consumption vehicles, the government should request and encourage the fuel vehicle companies to further upgrade the corresponding technology to reduce fuel consumption continuously. Also, certain discounts can be offered when new energy vehicle points are calculated against the standard value. Reference | Related Articles | Metrics

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Rating with a Mask? The Effect of Air Quality on Credit Ratings Lang Xiangxiang, Tian Yanan, Wu Yuhui Management Review    2023, 35 (7): 56-73.   Abstract （240）      PDF （1326KB）（225）       Knowledge map    Based on the data of Chinese corporate bonds over 2013-2017, we examine whether bond rating analysts, who are supposed to be unbiased in ratings, are affected by air quality. We find that the released credit ratings are generally lower on days of low air quality, which is consistent with the literature that air pollution can affect the mood of rating analysts. This negative impact is more pronounced when the bond issuers are in high-polluting industries. Nevertheless, intense competition among rating agencies can mitigate this negative impact. Further research reveals that the negative effect of air pollution is stronger if analysts work in heavily polluted areas. In our extension study, we also find that on days of high air pollution, rating analysts are less accurate in issuing credit ratings and investors are less sensitive to ratings adjustments made by rating analysts. Our results are robust to controlling for agency*time fixed effects, as well as additional specifications employing the instrumental variable approach, RDD test and placebo tests. Overall, these findings are consistent with the notion that air pollution represents a hidden cost to the capital market. Reference | Related Articles | Metrics

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The Effect of Supervisor Incivility from the Perspective of Bystander: A Dual Approach Study of Emotion and Cognition Zhan Xiaojun, Wan Yi, Li Zhicheng, Li Mingze Management Review    2023, 35 (7): 209-220,249.   Abstract （190）      PDF （1773KB）（217）       Knowledge map    In recent years, researchers have paid more and more attention to workplace incivility from bystanders' perspective. But most of the existing researches are based on the "deontic justice" perspective and few studies investigate the potential "rational cognition" of bystanders. Drawing on social information processing theory, we explore the effect of supervisor incivility from bystanders' perspective. Based on the three-period survey data from 347 employees, we find that workplace anxiety mediates the relationship between observed supervisor incivility and bystander's self-improvement behavior, while self-concern mediates the relationship between observed supervisor incivility and bystander's ingratiation behavior. Workplace resilience negatively moderates the relationship between observed supervisor incivility and bystanders' workplace anxiety, as well as the indirect effects of workplace anxiety. Workplace resilience positively moderates the relationship between observed supervisor incivility and bystanders' self-concern and the indirect effects of self-concern. Finally, we discuss the theoretical contribution and practical implication of this study. Reference | Related Articles | Metrics

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Research on Consumer Identification Path in the Context of Social New Retail Business Model Wang Bingcheng, Zhao Jingyi, Yang Zhenhua Management Review    2023, 35 (8): 198-208.   Abstract （164）      PDF （1293KB）（202）       Knowledge map    Consumer identification is an important factor affecting the sustainable development of social new retail business model. However, existing researches pay little attention to the consumer identification path of social new retail business model, so they cannot better guide enterprises to enhance consumer stickiness and promote the development of social new retail business model. Based on this, this paper takes the consumers under the social new retail business model as the sample, and applies the grounded theory to construct a consumer identification path model of the social new retail business model. The results show that:(1) Consumers' use of social new retail business model is influenced by such factors as scene touch, word-of-mouth attraction, brand trust and profit drive; (2) Flow experience is the key reason for consumers to identify with the social new retail business model, including continuous engagement in interaction, platform content immersion and product consumption satisfaction; In addition, network externality will further affect consumers' flow experience; (3) When consumers identify with the social new retail business model, they will generate value transfer behaviors such as use feedback, active sharing and communication, as well as value creation behaviors such as social fission diversion and platform content creation; (4) The continuous identification of consumers needs to be achieved through sticky maintenance, which requires enterprises to strengthen the links of community relations and enhance the value of content, so as to further enhance the cognitive identification and emotional identification of consumers. On this basis, the paper further analyzes and discusses the research results, and puts forward some relevant suggestions. Reference | Related Articles | Metrics

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Will Green Consumption Be Contagious?——Social Diffusion Effect and Formation Mechanism of Green Consumption Wang Jianming, Feng Yu Management Review    2023, 35 (7): 185-198.   Abstract （184）      PDF （1345KB）（197）       Knowledge map    The social spreading effect of green consumption behavior is increasingly prominent under the mobile internet situation, which plays an important role in promoting the "common green" of the whole society. Taking green consumption as the research starting point, 1056 micro-data are collected through online questionnaire survey to test the social diffusion effect of green consumption and its multiple interaction influence paths in the era of mobile Internet. The research results show that consumers' green purchase behavior, green use behavior and recycling behavior can all promote their intention to care and share green information, forming social diffusion effect; Both product-level and social-level green information play a partial mediating role in the "behavior-sharing" relationship; Marital status and gender roles have partial dual regulatory effects in the first half of the "behavior-concern-sharing" mediation model, but the role of marital status is not stable. On this basis, the dual path behavior diffusion theory is constructed, and the green consumption diffusion mechanisms of "behavior handling behavior (A-C-A)" and "behavior input/output behavior (A-I/O-A)" are proposed. This research extends the theory of green consumption and the theory of social network contagion and diffusion, and provides management enlightenment for society to achieve "common green". Reference | Related Articles | Metrics

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Impact of Enterprise Digital Transformation on the Risk Prediction of Stock Price Crash——Based on the ED-SPCBoost Model Hu Jinjin, Zhao Xuefeng, Wu Delin, Wu Weiwei Management Review    2023, 35 (8): 15-30.   Abstract （181）      PDF （2827KB）（194）       Knowledge map    Enterprise digital transformation came into being under the effective coupling of digital technology and enterprise development, which has profoundly impacted China's stock price. Based on the optimization of characteristic relationships, this paper constructs an ED-SPCBoost model to explore the impact of enterprise digital transformation on the risk of stock price collapse and the underlying mechanism. The findings are as follows. (1) Digital transformation can effectively reduce the risk of the stock price crash, and the risk of stock price crash shows a phased downward trend of "stable-sensitive-stable" as the degree of transformation increases. (2) Digital transformation plays a more significant role in reducing the risk of the share price collapse of state-owned enterprises. In the mature period of transformation, non-state-owned enterprises account for 78.03%. Non-state-owned enterprises are more willing to accept digital transformation than state-owned enterprises. (3) Digital transformation can reduce the risk of stock price collapse by enhancing enterprise information transparency, improving market evaluation expectations, and improving internal financial stability. The mechanisms underlying the three paths of impact are different. The ED-SPCBoost model proposed in this paper has high robustness and a low error rate. Empirical data verify that it aligns with the prediction law of digitization and stock price collapse. It can provide a valuable reference for digital technology to optimize the governance environment of listed companies and improve the monitoring of financial market risks. Reference | Related Articles | Metrics

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Economic Journey of Women across the Centuries: A Review of the Contributions of the 2023 Nobel Prize Winner in Economics and the Implications for China Meng Lei Management Review    2023, 35 (10): 3-9.   Abstract （276）      PDF （1192KB）（193）       Knowledge map    The 2023 Nobel Memorial Prize in Economic Sciences was awarded to Claudia Goldin, who used historical data across the centuries to study the long-term changes of the economic roles of women, and reached important conclusions that enable us to better understand the relationship between female labor market performance and economic development. This paper introduces her major work on female labor force participation rate and gender wage gap, and also discusses in which ways her research can shed a light on the study of the female labor force in China. Reference | Related Articles | Metrics

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The Mechanism of How Business Model Innovation and Digital Empowerment Drive Digital Transformation——A Case Study Based on TJ-QCA Liu Sihui, Li Wen, Yu Rongjian, Mei Lei Management Review    2023, 35 (8): 342-352.   Abstract （119）      PDF （1536KB）（188）       Knowledge map    Digital empowerment and business model innovation are two important driving factors for enterprises to realize digital transformation. This paper uses case studies and trajectory-based qualitative comparative analysis to explore the mechanism of how the two factors synergistically act on manufacturing enterprises' digital transformation, and tracks the evolution path of their transformation process. The research finds that the transformation mechanism of digital empowerment includes control empowerment, analytical empowerment and cascade empowerment; the business model innovation mechanism mainly includes income-generating business model and orchestration business model; there are four paths for the two factors to synergistically drive the digital transformation:industry coupling drive, independent innovation drive, capacity connection drive and control auxiliary drive; and among them, industrial coupling drive and independent innovation drive are the most conservative paths. Analytic empowerment, cascade empowerment, income-generating business model and orchestration business model are core conditions to promote the digital transformation of manufacturing enterprises, while control empowerment is a marginal condition. The research results reveal the trajectory along which digital empowerment and business model innovation synergistically promote digital transformation, and reveal the laws behind it, so the conclusions can be used as a reference for manufacturing enterprises to carry out their digital transformation. Reference | Related Articles | Metrics

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Meaningful Innovation: Conceptual Dimensions, Measurement and Innovation Performance Qu Guannan, Jie Yuan, Chen Jin, Wang Luyao, Juan Rogers Management Review    2023, 35 (7): 86-95.   Abstract （165）      PDF （1277KB）（184）       Knowledge map    Meaningful Innovation (MI), as a new paradigm that leads enterprises to actively respond to social demands in the new era and helps them comprehensively improve their sustainable competitive advantages and achieve systematic transcendence, starts to get attention. However, the relevant studies are still to be mature, especially evidenced by the lack of reliable measurement of the key concepts of the MI and the empirical test of the core framework. Based on the existing literature, this study systematically reviews the theoretical basis of the MI, summarizes and identifies its basic framework and core concepts. Furthermore, interview and questionnaire are used to conduct scale development, and reliability and validity test aiming at the five core dimensions of meaningful innovation, and further verify the significant positive influence of meaning orientation (MO) on innovation performance. On this basis, a reliable measurement model of the MI is built in order to provide implications for the further development of this paradigm. Reference | Related Articles | Metrics

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Data Factor Utilization, Intelligence Technology Progress and Endogenous Growth Liu Zhengchi, Chen Wenwu, Wei Sichao Management Review    2023, 35 (10): 10-21.   Abstract （226）      PDF （1372KB）（182）       Knowledge map    Data-intelligence transformation is a core driving force for the sustained economic growth in the new era. The existing literature has discussed the mechanisms of how data factor or intelligent technology affect economic growth respectively, but ignored the key role of data factor in promoting the progress of intelligent technology. Based on this, this paper integrates the utilization of data factors and the progress of intelligent technology into the endogenous growth model framework to explore their joint impact on economic growth. It is found that data factor utilization can promote sustained economic growth by promoting the progress of intelligent technology. Further analysis shows that the model economy has two “restricting effects” and a “growth trap”. The promoting effect of data factor utilization on long-term economic growth is restricted by consumers’ aversion to privacy infringement. The contribution of intelligent technology progress to long-term economic growth is restricted by population growth. The difference in the sequence of digitalized transition may lead to diverged long-term economic growth rate, and the economy with a late transition may fall into a growth trap where the growth rate is continuously lower than that of the economy with an early transition. This study not only provides a theoretical reference for understanding the macro growth mechanism in the era of digital economy, but also provides a theoretical explanation for the fierce competition among major economies in the technological and industrial fields such as big data and artificial intelligence. Reference | Related Articles | Metrics

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People Prefer New Products as They Become Older: The Effect of Aging Perception on New Product Purchase Intention Zhang Huiying, Ding Zhihua, Jiang Xin, Wang Yawei, Xuan Shanqi Management Review    2023, 35 (7): 174-184.   Abstract （163）      PDF （1980KB）（181）       Knowledge map    With the increasing aging of China's population, the consumption behavior of the elderly has attracted more and more attention, but the research on older consumers' intention to purchase new products needs to be further discussed. From the perspective of aging perception, this paper explores the influence of aging perception on new product purchase intention through four studies. Study 1 verifies that compared with negative aging perception, older consumers with positive aging perception have higher intention to purchase new products. Study 2 tests the mediating role of perception control in the above effects and finds that, compared with the older consumers with negative aging perception, those with positive aging perception have higher perception control ability for new products, and thus have higher purchase intention for new product. Study 3 excludes the alternative explanations of compensation mechanisms. Study 4 finds that social support not only positively moderates the effects of aging perception and new product purchase intention, but also moderates the mediating effect of perception control. In this paper, the mechanism of how aging perception influences new product purchase intention is discussed, and some suggestions are provided for enterprises in terms of market positioning and product service. Reference | Related Articles | Metrics