Against the backdrop of accelerating agricultural and rural modernization, the systematic assessment of the regional competitiveness of agricultural enterprises has become crucial for revealing the evolution of new agricultural productive forces. Based on a self-constructed “star-shaped network hierarchy model” this study designs an indicator system for evaluating the regional competitiveness of agricultural enterprises using the ANP method. Using monitoring data on leading agricultural industrialization enterprises from 2,648 counties， it systematically analyzes the spatio-temporal patterns, dynamic evolution characteristics, and influencing factors of regional competitiveness across the nation and within the three major grain functional zones. The results indicate that: (1) The Gini coefficients of competitiveness for the nation and the three major grain functional zones show a trend of first increasing and then decreasing. Although regional disparities have somewhat eased, unbalanced characteristics remain prominent, with internal disparities within major grain-producing areas expanding significantly; (2) The regional competitiveness of agricultural enterprises nationwide exhibits a “cold in the west, hot in the east” spatial distribution; (3) Both the competitiveness and absolute differences have increased nationwide, and within the three major grain functional zones and significant agglomeration occurs in areas where grain production and marketing are balanced; (4) The regional competitiveness of agricultural enterprises nationwide exhibits “club convergence” yet major producing and marketing areas demonstrate a trend of leapfrog development; (5) The regional competitiveness of agricultural enterprises shows a spatial correlation characterized by a “trickle-down effect” while industrial agglomeration, economic development level, and digital transformation all have significant positive effects on enhancing competitiveness. By innovatively constructing an analytical framework, this study deepens the understanding of the connotation and evolutionary patterns of regional competitiveness of agricultural enterprises, provides an important theoretical basis for its scientific and systematic evaluation, and offers valuable practical insights for enhancing new agricultural productive forces and ensuring national food security.

High-quality development of the urban economy provides solid support for exploring the value creation potential of multiple production factors and promoting sustainable economic growth. This paper takes prefecture-level cities across the country as research samples, and empirically examines the impact of digital-real integration on the high-quality development of the urban economy as well as the mechanism underlying the impact. The study finds that digital-real integration significantly improves the total factor productivity of cities. The results of the mechanism test shows that digital-real integration improves the quality of urban economic development by enhancing urban innovation capabilities, upgrading industrial structure and stimulating digital consumption demand. Heterogeneity analysis reveals that in regions characterized by higher levels of commercial credit and more robust legal institutions, digital-real integration exerts a more pronounced positive effect on promoting high-quality urban economic development. In regions exhibiting a high degree of market fragmentation, digital-real integration demonstrates a substitutive effect, primarily enhancing urban total factor productivity rather than the overall quality of economic development. This study effectively expands the research scope of the digital economy and provides important inspiration for the high-quality development of the urban economy and the optimization of the institutional environment supported by the digital-real integration.

As an important means of resource reallocation, mergers and acquisitions (M&As) play a vital role in value creation and transformation and upgrading for real estate firms. Unlike previous literature that focuses on acquiring firms, this paper takes M&A events of Chinese A-share listed real estate firms in Shanghai and Shenzhen stock markets from 2010 to 2022 as samples, and employs the multi-period difference-in-differences (DID) model to investigate M&As’ effect on the value of target real estate firms as well as the underlying mechanism. The empirical results show that M&As temporarily reduce the short-term value of target real estate firms, but significantly increase their long-term value. These conclusions remain robust after a series of endogeneity and robustness checks. Mechanism tests indicate that M&As enhance the long-term value of target real estate firms by alleviating their financing constraints. Heterogeneity tests based on M&A transaction characteristics show that vertical M&As and local M&As have a more significant positive effect on the long-term value of target real estate firms. Heterogeneity tests based on the external environment show that the positive impact of M&As on the long-term value of target real estate firms is more pronounced when monetary policy is accommodative and regional digital financial inclusion is higher. Heterogeneity tests based on internal firm characteristics show that M&As exert a stronger positive effect on the long-term value of small, high-growth, under-invested and risk-seeking target real estate firms. The conclusions of this paper provide useful implications for motivating real estate firms to seek being acquired, for the government to formulate and implement policies promoting M&As and restructuring of real estate firms, and for the practice of M&As among real estate firms.

Under carbon allowance mechanisms, power generators have incentives to misreport their carbon emissions. Considering the practical constraint of feed-in tariff caps, this study incorporates generators’ carbon misreporting and renewable energy investment decisions to examine the misreporting behavior and investment strategies under total allowance and unit allowance mechanisms. By analyzing the equilibrium outcomes, the study finds that: (1) as the misreporting cost coefficient increases, renewable energy investment rises, while the level of misreporting and the profits of supply chain firms both decline; (2) when the feed-in tariff cap is low, the unit allowance mechanism is more effective in promoting renewable energy investment and results in lower misreporting, whereas when the cap is high, the total allowance mechanism performs better in both dimensions; and (3) when the unit allowance is relatively small, generators disclose higher carbon emissions under the unit allowance mechanism, whereas when the unit allowance is relatively large, disclosed emissions are higher under the total allowance mechanism.

Corporate green transformation, which underlies ‘quality enhancement and green expansion’, constitutes a critical pathway toward comprehensive socioeconomic green transition and represents an inherent requirement for achieving high-quality development. This study examines the mechanisms and characteristics of green investor engagement in driving corporate green transformation through a capital market lens, utilizing a sample of China’s A-share listed companies from 2008 to 2022. The findings demonstrate that green investors’ entry effectively achieves a ‘dual-win’ outcome: simultaneously enhancing corporate productivity and improving environmental performance, thereby catalyzing green transformation. These results withstand robustness checks addressing indicator discrepancies, endogeneity concerns, and sample selection bias. The incentive effect is primarily due to the resource integration and green innovation effects triggered by the entry of green investors. This not only provides financial security for green transformation by stimulating increases in environmental protection expenses and green M&A activities, but also facilitates green transformation by inducing green management innovation and technological innovation within enterprises. Further investigation reveals that the entry of green investors serves the dual role of enhancing quality and expanding greenness for enterprises in the growth phase, capital-intensive and technology-intensive enterprises, and those in areas where local governments pay high attention to environmental protection. In contrast, for enterprises in the maturity and decline phases, labor-intensive enterprises, and those in regions with low local government attention to environmental protection, the entry of green investors predominantly contributes to quality improvement. Additionally, this paper verifies that China’s ‘Go Green’ financial system, green financial reform, and green credit policy can lead to a linkage effect with green investors to promote the green transformation of enterprises. These conclusions deepen the theoretical understanding of corporate green transition mechanisms while providing practical insights for activating microeconomic entities’ green development potential.

Deep integration of the innovation chain, industrial chain, capital chain, and talent chain is an important path for the modern industrial system. As a “test field” for high-level opening up, free trade zones provide a unique environment for the integration of the “four chains” through policy innovation and flexible strategies. Based on an RDD empirical analysis of 31 provinces across China from 2010 to 2022, this paper finds that the construction of free trade zones significantly promotes the growth of the tertiary industry, accelerates the integration of the industrial chain and the innovation chain, and retards the rise of foreign investment and innovation levels, with a more significant response from the talent chain. Although the initial stage of construction faces challenges of enterprise adjustment, the long-term effects are significant, and regional differences are obvious. This study not only expands the policy application scenarios of the four-chain integration theory, but also provides an effective reference for free trade zones to formulate precise development strategies.

Existing literature often frames corporate social value and economic value as an irreconcilable antinomy, neglecting their potential synergies and resulting in fragmented research on the drivers of business model innovation (BMI) in new ventures. To solve this issue, based on the Optimal Distinctiveness Theory, this study collects two-stage survey data from 305 new ventures in China and uses the PLS-SEM method (SmartPLS4.0) to explore the relationship between social entrepreneurial orientation (SEO) and new ventures’ BMI, as well as the mediating roles of bricolage and organizational legitimacy and the moderating role of digital technology adoption. The findings show that SEO has a significant positive effect on new ventures’ BMI; bricolage fully mediates the impact of SEO on both novelty-centered and efficiency-centered BMI, while organizational legitimacy only partially mediates the link between SEO and efficiency-centered BMI. Moreover, digital technology adoption positively moderates the mediating effect of bricolage on BMI, but negatively moderates the mediating effect of organizational legitimacy on efficiency-centered BMI. This study enriches the theoretical systems of SEO and BMI research, clarifies the “black box” of SEO’s influence on new ventures’ BMI, and provides actionable implications for new ventures to balance social responsibility and economic benefits, and accelerate BMI through the rational application of digital technology.

Although existing studies have extensively explored corporate digitalization and green transformation, systematic research on how firms, under capital market pressure, leverage digital capabilities to balance short-term financial goals with sustained green innovation remains scarce. Drawing on dynamic capability theory, we empirically analyze the impact of merger and acquisition (M&A) performance commitments on the sustained green innovation of manufacturing firms, with a particular focus on the moderating role of data assets. Based on panel data from Chinese A-share listed manufacturing firms from 2010 to 2024, we find that M&A performance commitments significantly inhibit the sustained green innovation of manufacturing firms by increasing performance pressure, intensifying managerial myopia, and raising agency costs. Data assets play a negative moderating role in the relationship between M&A performance commitments and sustained green innovation, effectively mitigating the adverse effects of such commitments. By improving resource allocation efficiency, correcting strategic decision biases, and strengthening organizational governance mechanisms, data assets alleviate the resource crowding-out effect caused by short-term capital market orientation. The findings enrich the literature on the relationship between capital market pressure and green innovation, enrich the theoretical connotations of data assets empowering corporate dynamic capabilities, and underscore the necessity for firms to develop and apply data assets to promote the sustained green innovation in uncertain environments. This study offers new theoretical perspectives and practical insights for optimizing resource allocation and advancing green and low-carbon transformation of manufacturing firms.

Against the backdrop of innovation-driven development strategy and the construction of a unified national market, this study empirically examines the impact of city clusters policies on inter-firm collaborative innovation. The findings reveal that: (1) city clusters policies significantly enhance collaborative innovation among enterprises within the same region by facilitating the flow and integration of technological factors; (2) the policies operate through three main channels—increasing government subsidies, strengthening intellectual property protection, and deepening specialization and industrial division of labor; (3) heterogeneity analysis indicates that the effect is more pronounced in regions with lower levels of social trust, weaker industrial agglomeration, and more intense market competition, with particularly strong impacts observed in cross-provincial and multi-core city clusters. These policies also significantly promote various types of collaboration, including “firm-firm,” “firm-university,” and “firm-research institute” partnerships; (4) the improvement in collaborative innovation further contributes to the growth of firms’ total factor productivity. This study provides empirical evidence and policy insights for reshaping enterprise innovation models amid the advancement of China’s unified national market.

Artificial intelligence (AI) technology, as an important driving force of new-quality productivity, has become an important force in promoting the intelligent transformation and sustainable growth of specialized, refined, differentiated and innovative (SRDI) firms. Based on situated AI capability theory, this paper empirically studies the impact of AI technology on the growth of enterprises by taking SRDI firms listed in A-share market from 2014 to 2022 as samples. The results show that AI technology negatively affects the current growth of SRDI firms, but technological sophistication and internationalization can effectively alleviate the negative impact of AI technology on the growth of firms. Mechanism analysis reveals that while AI adoption facilitates routine restructuring, it simultaneously increases factor inputs, triggers strategic change, and reduces operational efficiency, thereby hindering firm growth. Heterogeneity tests further show that the negative impact of AI is more pronounced in SRDI firms that are in high-tech industries, have high labor costs per employee, exhibit low levels of digitalization, or are smaller in scale. This study reveals the actual challenges and potential advantages of SRDI firms during their AI technology adoption, promotes the deepening of the growth theory of SRDI firms in the AI era, and enriches the research on AI technology adoption from the perspective of situated AI capability.

With the deepening of sustainable development, sustainable green innovation of enterprises has become a key means to realize the win-win situation of economic growth and environmental protection. Based on the TOE framework, this paper uses interpretable machine learning models to comprehensively examine the importance and effect of the driving factors of sustainable green innovation of enterprises. The research results are as follows: The established gradient boosting tree has high prediction accuracy and robustness in exploring the driving factors of sustainable green innovation of enterprises; industrial robot application and R&D intensity at the technology level, absorbed slack resources, unabsorbed slack resources, and enterprise size at the organizational level, and ESG ratings at the environmental level are the key drivers of sustainable green innovation of enterprises, and there is a non-linear relationship with sustainable green innovation of enterprises; there are positive interaction effects among industrial robot application, R&D intensity, absorbed slack resources and enterprise size, which can promote sustainable green innovation of enterprises. This paper clarifies the driving factors of sustainable green innovation of enterprises, enriches the related research on sustainable green innovation of enterprises, and provides theoretical guidance for enterprises to make decisions on sustainable green innovation.

From the perspective of the innovation value chain, this paper examines three stages (early-stage R&D innovation, mid-stage commercialization of research outcomes, and late-stage technology diffusion) to reveal the theoretical mechanisms through which institutional supply at different stages enhances the innovation quality of “specialized, sophisticated, distinctive, and innovative” (SSDI) enterprises. Furthermore, drawing on more than 180,000 manually collected policy documents and SSDI patent records, this study exploratorily employs a text-based configurational matching approach to investigate the complex effects of three types of innovation-oriented institutional supply on the innovation quality of SSDI enterprises. The findings are as follows: (1) Deepening institutional supply oriented toward the innovation value chain can effectively improve the innovation quality of SSDI enterprises, with the effect being particularly pronounced during the commercialization stage. (2) Promoting continuous innovation, facilitating profit realization, and alleviating risk-bearing pressures are effective channels through which institutional supply empowers high-quality innovation in SSDI enterprises. (3) Configuration effects indicate that China’s current institutional supply for high-quality innovation in SSDI enterprises has not yet formed a full-cycle, full-chain virtuous interaction; in particular, greater attention should be paid to enabling SSDI enterprises to achieve compatibility between maintaining specific technological advantages and accelerating the marketization of R&D outcomes. (4) Differentiated characteristics show that institutional supply exerts a more significant positive effect on innovation quality for SSDI enterprises with relatively weak innovation foundations, while, from the perspective of regional development levels, the impact of institutional supply exhibits a pronounced “Matthew effect.” These conclusions provide important insights for fostering new drivers of high-quality development in China through deepening reform of the science and technology system in the new era.

Drawing on adaptive structuration theory and sociotechnical theory, this study examines the relationship between HRM digitalization and the effectiveness of HRM implementation, focusing on the moderating factors that influence this relationship. By considering HRM socialization and HRM system maturity as contextual factors, the research develops a “technology-relationship-institution” framework and constructs a three-way interaction model. Based on data from a paired survey of HR professionals and line managers (N=201) and a two-wave survey of line managers (N=308), the research concludes that HRM digitalization enhances departmental HR effectiveness by improving internal service quality. Furthermore, a three-way interaction is identified among HRM digitalization, HRM socialization, and HRM system maturity, affecting both internal service quality and the indirect impact of HRM digitalization on HR effectiveness. This study highlights the critical factors and coupling mechanisms underlying the effectiveness of digital HRM implementation, providing practical guidance for bridging the gap between digital aspirations and implementation challenges.

Team psychological safety refers to a shared belief among team members that it is safe to take interpersonal risks. We summarize the relevant literature through the four-phase flow recommended by PRISMA statement and find that previous studies have dominantly focused on the formation mechanism of team psychological safety concerning leadership characteristics and team characteristics. However, as an important unit embedded in the external environment, team is vulnerable to changes in the political, economic, social and technological environment, and the vulnerability is ignored by existing research. Therefore, to make up for the lack of external perspective in the previous research, we discuss the formation mechanism of team psychological safety via selecting representative political, economic, social and technological environments which have an important impact on team development. Finally, we propose that future research should explore the mechanism of policies and institutions based on management communication strategies; clarify the connotation of the gig economy and explore how to cultivate psychological safety within teams; examine the impact of sudden public health incidents using event system theory; investigate the empowerment by digital technology to cultivate team psychological safety.

This study uses the China Family Panel Studies (CFPS) database and employs fixed effects and Tobit models to examine how the accessibility and quality of basic education resources affect household human capital investment. The findings indicate that better access to educational resources has the effect of “choosing the good to follow” and “looking forward to the success of children”, which significantly raises families’ academic expectations for their children, thereby enhancing human capital investment through increased regional competitive pressure. In contrast, improvements in educational quality encourage families to invest more by boosting children’s academic performance, which is manifested as the effect of “famous teachers and high apprentices”. These effects vary according to factors such as resource allocation equity, levels of digitalization, and household income. Therefore, optimizing the allocation of educational resources is essential to fostering a virtuous cycle between households and society, and ultimately improving both the quantity and quality of human capital in the country.

Existing research on corporate tax avoidance has largely overlooked the critical dimension of interactive effects among peer firms within the same industry. Using panel data from Chinese A-share listed companies from 2008 to 2020, this study systematically examines the correlation of corporate tax avoidance behaviors within industry groups. The findings reveal a significant peer effect in tax avoidance behavior among listed companies: for every 1 percentage point increase in the level of tax avoidance by peer firms, the target firm’s tax avoidance level rises by approximately 0.2 percentage points. Further analysis indicates that this peer effect in tax avoidance is attenuated when firms exhibit a stronger nationalist cultural orientation, operate in regions with higher tax enforcement intensity, face lower economic policy uncertainty, and receive positive media coverage. Additionally, firms tend to imitate industry-leading peers when making tax avoidance decisions, and the peer effect is significantly stronger for private enterprises than for state-owned enterprises. Notably, the spillover effect of peer tax avoidance behavior ultimately leads to a decline in the target firm’s value. This study not only expands the theoretical explanation of tax avoidance behavior from the perspective of inter-firm interactions, but also provides important insights for regulatory authorities to improve the tax governance policies.

ESG performance serves as a crucial lever for corporations to practise sustainable development and is essential for high-quality corporate growth. While executives’ environmental experience may steer corporate attention towards environmental issues, can this experience be internalized into strategic decision-making, further influencing corporate social responsibility and governance, thereby enhancing ESG performance? This study empirically analyzes the impact of executives’ environmental experience on firms’ ESG performance using a sample of China’s A-share listed enterprises from 2009 to 2023. The findings reveal that executives’ environmental experience significantly promotes firms’ ESG performance. Mechanism analysis further indicates that this experience boosts ESG performance by building the firm’s cognitive understanding and development capacity in ESG. Moderation effect tests show that both the participation of the Party organization in corporate governance and media attention positively moderate the impact of executives’ environmental experience on ESG performance. Further analysis reveals heterogeneity in this impact. The effect is more pronounced in smaller firms, firms where executives do not hold vertical concurrent positions, non-heavy polluters and firms located in cities with higher levels of digital economy development and stronger environmental regulation intensity. Economic consequence analysis demonstrates that executives’ environmental experience drives improvements in operational returns and reductions in operational risk by enhancing corporate ESG performance. This study enriches the upper echelons theory and imprinting theory and contributes to improving corporate ESG performance, thereby continuously advancing the synergistic development of society, economy, and environmental protection in China.

Digital transformation, viewed as a key “CEO-driven initiative,” fundamentally reshapes traditional management authority. Using panel data from A-share listed companies in Shanghai and Shenzhen from 2015 to 2022, this study explores the differentiated impacts of CEO power on corporate digital transformation. The findings are as follows: (1) CEO power, expert power, and reputational power promote digital transformation, whereas organizational and ownership power inhibit it. (2) Confucian culture moderates the relationship between CEO power and digital transformation. (3) mechanism analysis reveals that expert power and reputational power foster digital transformation by enhancing innovation efficiency and human resource input, while organizational power and ownership power weaken this mechanism. (4) Heterogeneity tests indicate that these effects vary across industries, cultural contexts, and regions. In high-tech sectors, the positive impact of CEO, expert, and reputational power is stronger, while the negative effect of organizational power is weaker. In regions with strong Confucian influence, the positive effect of CEO power is less pronounced, mainly in terms of organizational power and ownership power. In western regions, the positive role of expert power and reputational power is more evident, with weaker inhibitory effects from organizational power and ownership power. These findings enrich understanding of how heterogeneous CEO power shapes digital transformation and offer insights for rational power allocation and strategic decisions in the digital economy.

In recent years, the government has introduced various subsidy policies to promote the smart transformation of the manufacturing industry. This paper uses the government, the platform, and the manufacturer as the research subjects to examine the impact that subsidies for platforms, manufacturers, and consumers respectively have on the smart innovation decisions of an IoT platform and a manu-facturer. The platform provides IoT technology services to the manufacturer, which develops and sells smart products to consumers through the platform. As a result, the manufacturer can gain demand spillover benefits based on the platform’s remote data processing capabilities. However, the cybersecurity risks associated with IoT also influence consumer purchasing decisions, ultimately affecting the smart innovation levels of both the platform and the manufacturer. By analyzing the smart innovation decisions of manufacturers and platforms under different government subsidy scenarios, this study identifies factors influencing the smart transformation of manufacturing and determines the optimal subsidy levels and forms for the government. The conclusions are as follows: (1) The level of demand spillover and software-hardware compatibility have a positive effect on smart innovation equilibrium outcomes, while the unit innovation costs and cybersecurity externalities of the IoT platform and manufacturer negatively impact the service levels and fees of the platform, as well as the profits of the manufacturers. (2) The impact of different government subsidies on the innovation of IoT platforms and manufacturers varies; subsidizing platforms and manufacturers helps increase their innovation levels, while subsidizing consumers only reduces the cost of purchasing smart devices without promoting innovation in the IoT platform company and device manufacturer. (3) No matter whether the government aims to maximize social welfare or promote the market coverage of smart products, it should allocate subsidies to IoT platforms and manufacturers, rather than subsidizing consumers.

Disinformation created by generative AI models has increased the difficulty of information governance on e-commerce platforms, which results in the increasingly prominent problem of AI information pollution. Based on the perspective of information generation and dissemination, this paper integrates the prospect theory into evolutionary game to construct a four-party evolutionary game model including generative AI service providers, merchants, e-commerce platforms, and the government, characterizes the optimal strategies for generative AI disinformation governance, and performs simulation analysis. The results show that for generative AI service providers, the cost of technological constraints and social influence affect their strategy choices, and increasing user fees and fines for non-compliant users can effectively curb non-compliant use by merchants. For e-commerce platforms, higher auditing professionalism can promote the maturity of information management in the e-commerce industry, and at the same time, a higher level of incentives and penalties is helpful for merchants to comply with the proper use of generative AI services, and differentiated governance should be implemented for heterogeneous merchants. For the government, appropriately increasing the rewards and punishments for generative AI service providers and e-commerce platforms can promote collaborative governance between the two parties, and the improvement of the level of government supervision and social influence can make the governance environment more stable.

Industrial internet platforms serve as the core infrastructure of modern industrial systems, yet their entrepreneurial journey consistently grapples with the fundamental contradiction between value creation and capture. Taking Dahan as a case study through the theoretical lens of dominant logic, this study explores how industrial internet platforms deal with the contradiction between value creation and capture. It reveals that platforms translate abstract value behavior contradictions into phased strategic actions through a dynamic closed-loop process of “contradictions identification-dominant logic-value creation-value capture.” Specifically, during the initial phase, platforms employ a strategic forbearance logic to address profit distribution contradictions by trading short-term profit concessions for scale effects and data resource accumulation. In the growth phase, transformative logic addresses technology resource contradictions by converting technological resources into data asset pools and capital operation pivots. Ultimately in the maturity stage, platforms adopt a co-governance logic to address governance power contradictions, transcending the traditional centralization-decentralization dichotomy to achieve rule co-creation and value sharing. This study elucidates the dynamic process mechanism for dealing with value creation and capture contradictions in industrial internet platforms, enriching the conceptual connotation and expanding the application boundaries of dominant logic, while providing theoretical insights for constructing sustainable platform development pathways.

To address the dual pressures of inheritance and innovation while achieving the dual objectives of preserving family bonds and enhancing corporate performance, second-generation successors in family businesses must develop the capacity for “inward action”, that is, forging an entrepreneurial identity that commits to the family enterprise while embracing innovation and development. This paper examines the identity development process and mechanisms of second-generation successors, starting from their entry into the family business and drawing on multiple case studies. Findings reveal that successors initially accept the “successor identity” driven by foundational motivations of self-reinforcement and relationship maintenance. They then undergo a three-stage process (identity maintenance, identity validation, and identity integration), ultimately committing to the “entrepreneurial identity of the second generation.” This process is triggered by parental empowerment behaviors, develops through parents providing specialized and emotional empowerment tailored to different developmental stages, and is completed through parental identity transfer and the second generation’s innovative actions. The underlying mechanism driving parental behaviors in second-generation identity development is the individual’s pursuit of identity unity and consistency, coupled with goal alignment between generations based on emotional connection. This study enriches identity theory within the unique context of family enterprises, deepens research on successor development guided by “inward action,” and provides a systematic theoretical foundation for succession practices in family businesses.