Chinese-style fiscal decentralization has led local governments to prioritize transport infrastructure construction while paying insufficient attention to maintenance. This study develops a stochastic evolutionary game model involving the central government, two competing local governments, and private firms, and combines it with numerical simulations based on the Chinese context. The aim is to uncover the dynamic interactions among fiscal relations, intergovernmental competition, and market feedback, thereby identifying an optimal fiscal arrangement for improving transport infrastructure maintenance. The results show that, first, in regions where firms enjoy higher returns and market activity is strong, a decentralized system is more effective in stimulating local initiative. By contrast, in regions with weak market feedback, a more centralized arrangement is needed to strengthen central supervision. Second, compared with the free-rider incentives generated by spatial spillovers, local governments are more concerned with whether maintenance inputs can be translated into capital agglomeration and tax growth. Third, high-quality maintenance attracts business investment by reducing operating costs, while increased investment reinforces governments' incentives to invest in maintenance through higher tax revenues. This study provides both a theoretical basis and policy implications for optimizing the allocation of fiscal powers and responsibilities in the transport sector.

Purpose This study aims to examine whether horizontal digital mergers and acquisitions (M&A) enhance acquiring firms' post-acquisition digitalization. Drawing on organizational learning theory, it further investigates how degree centrality and geographic distance shape this effect by influencing explicit and tacit knowledge transfer. Design/methodology/approach Using Chinese A-share listed manufacturing firms from 2012 to 2019, this study constructs a text-based measure of acquiring firms' digitalization from annual reports and employs a propensity score matching difference-in-differences (PSM-DID) design to examine the effect of horizontal digital M&A. It further tests the moderating roles of degree centrality and geographic distance. Findings Horizontal digital M&A enhances acquiring firms' digitalization; the effect is strengthened by degree centrality and weakened by geographic distance, consistent with organizational learning through facilitated explicit knowledge transfer and constrained tacit knowledge transfer. Originality/value This study extends digital M&A research beyond deal performance by examining acquiring firms' post-acquisition digitalization as a transformation outcome. By benchmarking horizontal digital M&A against non-horizontal digital M&A, it isolates the incremental value of horizontality in digital acquisitions. It further develops a learning-based account that distinguishes explicit and tacit knowledge transfer and identifies degree centrality and geographic distance as key boundary conditions.

Digital mergers and acquisitions (M&A) have become an important strategy for firms seeking to acquire digital technologies and advance digitalization, yet their effectiveness in improving digitalization in acquiring firms remains insufficiently understood. Drawing on the knowledge-based view, this study examines how technological similarity and technological complementarity, as two different knowledge relationships between the acquiring and target firms, shape post-acquisition digitalization. Using a sample of listed manufacturing firms from 2012 to 2019, we find that both technological similarity and complementarity are positively associated with the acquiring firm's digitalization. Geographic distance attenuates the positive effect of technological complementarity but does not significantly moderate the effect of technological similarity, suggesting that the impact of spatial separation depends on the knowledge relationship between the acquiring and target firms. Extensive robustness checks, including instrumental variable estimation and alternative measures, confirm the stability of our findings. This study contributes to the technology management literature by explaining how digital M&A supports acquiring firms' digitalization and by extending the knowledge-based view to the digital M&A context.

PurposeGreen innovation in mega transportation infrastructure projects (MTI-GI) requires balancing technological progress and economic growth with environmental protection and sustainable development. Due to the multiple participants, temporary project-based arrangements and significant spillover effects, innovation actors form highly complex and dynamic collaborative networks under the obligation of shared responsibilities. This research aims to analyze the structural characteristics and dynamic evolution of multi-actor collaborative networks of green innovation in mega transportation infrastructure projects, thereby revealing how collaborative relationships operate as a network mechanism within megaproject-based organizations.Design/methodology/approachThe research compiles relevant cases from the Zhan Tianyou Award to build a database and extracts collaboration data to construct the MTI-GI collaborative network. Descriptive statistics present the temporal and spatial characteristics of the case data. Complex network modeling, including social network analysis (SNA) and the Barrat, Barth & eacute;lemy and Vespignani (BBV) model, is employed to measure the static structural features and dynamic evolutionary pathways.FindingsThe results indicated that the past decade (i.e. 2014-2023) was pivotal for MTI-GI development. Rail transit and railway projects are the most active in implementing green innovation, and the innovation actors are distributed mainly across relatively developed regions and relatively less developed yet strategically important areas. SNA metrics revealed that the MTI-GI collaborative network remains weakly connected overall and presents a clear scale-free pattern. This underscores the dominant role of state-owned enterprises in capability-driven and responsibility-supported innovation within the temporary, multi-level and multi-stakeholder context of megaprojects. BBV evolutionary analysis further indicated that a larger evolutionary scale, preferential attachment based on comprehensive strength and fewer cooperative ties of new entrants reinforce the scale-free properties of the collaborative network. Moreover, the MTI-GI collaboration network demonstrates its dynamic feature of enabling an adaptive balance between short-term project collaboration and long-term governance capacity.Originality/valueThe findings of this research enhance the understanding of green innovation network governance in megaproject-based organizations and offer more refined strategies for managing multi-actor collaboration in complex systems.

The rapid spread of user-generated video content on social media has raised pressing ethical concerns, requiring a holistic approach to moderate the contents. While current research primarily focuses on explicit text-content violations detection, it overlooks the ethical dimensions of content responsibility and users' needs for clear explanations and specific guidance. In response, we construct a novel video moderation system for user-generated content (UGC) platforms, shifting from traditional reactive approaches to a proactive, distributed human-machine workflow. We design a detection tool framework called ResponSight that collaborates with users to promote responsible content creation. ResponSight contains two core modules: the explainable evaluation module and the adaptive suggestion module, which driven by multimodal large language models (MLLMs). By offering transparent, explainable feedback, this system enables users to understand the rationale behind moderation decisions and refine their videos to align with ethical and social responsibility standards.

Mechanistic algorithmic management is widely implemented in online labor platforms (OLPs) to ensure consistent delivery of high-quality services by their workers. To address humanized needs that are overlooked by algorithms, workers may use cheating tools to discover and exploit algorithmic loopholes. This poses challenges to the efficient operation of OLPs and markets. With the goal of facilitating OLPs to foster humanistic algorithmic management and reduce workers’ cheating behavior, this study constructs a two-player evolutionary game model, which is applied to characterize the dynamic decision-making processes of both players regarding algorithmic management. From a theoretical perspective, this study identifies four equilibrium strategies at different game stages and deduces the stability and constraints of these strategies, with “humanistic algorithmic management” and “no cheating” serving as the ideal strategies. Further, the data from Guangzhou’s Didi and Suzhou’s Amap platform and numerical simulation methods are adopted to analyze the impact of key factors on OLPs and workers’ decision-making at different game stages. These factors include government regulation, platform regulation, cheating efficiency, negative utility, and social learning, not just costs and benefits. Finally, this study elucidates the co-constitutive relationship between platform algorithms and workers’ behavior, confirms workers’ agency in the establishment of humanistic algorithmic management systems, and provides practical insights into how platforms can improve the performance and well-being of their employees.

PurposeIn the era of a knowledge-driven economy, corporate venture capital (CVC) has emerged as a vital mechanism for fostering innovation and strategic growth among incumbents. However, a crucial aspect that has been somewhat overlooked is why incumbents choose to invest in technology ventures in specific areas rather than others. This study aims to fill this gap by exploring the relationship between firm knowledge diversity and the strategy of CVC investment based on the knowledge-based view.Design/methodology/approachThe authors' analysis is based on data covering CVC investments from established Chinese manufacturing firms. The authors integrated data from CV Source, IncoPat, the Chinese Research Data Services Platform and China Stock Market and Accounting Research (CSMAR) to create the data set. Given the discrepancy between the industry classifications for startups in CV Source and those for investors in CSMAR, we implemented a large language model to analyze textual business descriptions of startups to map them onto industry codes consistent with the National Economic Industry Classification system used by CSMAR.FindingsThe empirical results reveal that incumbents' knowledge diversity has an inverted U-shaped effect on the industry distance of CVC investments. Moreover, technological dynamism and CEO tenure negatively moderate this curvilinear relationship. These findings contribute to strategic management theory and have implications for corporate investment strategies.Originality/valueThis study advances the CVC literature by revealing a nonlinear relationship between firm knowledge diversity and industry distance of CVC investments, while taking into account boundary conditions.

The rapid development of smart services has driven the evolution of social responsibility among global enterprises, while also presenting new challenges to their operational management. In the continuous iterations of smart services, the emerging digital ecosystem has demonstrated multidimensional characteristics, virtual-real integration, and multi-stakeholder interactions in management practices. This study introduces smart service social responsibility (SSSR), a comprehensive framework that extends traditional CSR and ESG models by integrating multidimensional, cross-space, and multi-stakeholder panoramic analyses to address the unique ethical and operational challenges of the digital ecosystem. Using a hybrid text-analysis methodology (TF-IDF scoring and LLM-based evaluation), we analyze 7858 sustainability reports across five major sectors (consumer goods, technology, financial, healthcare, and services) to reveal how firms prioritize sustainability issues and identify sector-specific patterns in smart-service industries. Our analysis reveals that environmental topics dominate, accounting for an average of 49.0% of dimension-level mentions and leading in four of the five sectors studied, whereas legal and ethical themes receive 42.25% fewer mentions on average. Meanwhile, physical space topics constitute nearly three-quarters (76.5%) of the total, in contrast to virtual space themes, which represent approximately one-quarter (23.5%). Furthermore, analysis of stakeholder attention reveals a strong focus on platforms (42.4%) and communities (23.8%), which together account for over 66.2% of the discourse, while emerging agents, such as algorithm engineers and smart bots, remain significantly underrepresented. The novelty of our research is demonstrated through uncovering how firms prioritize topics of social responsibility in sustainability reporting and revealing sector-specific patterns that highlight prominently featured content. These insights offer important guidance for regulators, businesses, and investors seeking to align smart-service frontiers with responsible practices.

The environmental, social, and governance (ESG) report is globally recognized as a keystone in sustainable enterprise development. However, current literature has not concluded the development of topics and trends in ESG contexts in the twenty-first century. Therefore, we selected 1114 ESG reports from global firms in the technology industry to analyze the evolutionary trends of ESG topics by text mining. We discovered the homogenization effect toward low environmental, medium governance, and high social features in the evolution. We also designed a strategic framework to look closer into the dynamic changes of firms' within-industry representiveness and cross-sector distinctiveness, which demonstrates corporate social responsibility and sustainability. We found that companies are gradually converging toward the third quadrant, which indicates that firms contribute less to industrial outstanding and professional distinctiveness in ESG reporting. Firms choose to imitate ESG reports from each other to mitigate uncertainty and enhance behavioral legitimacy.

Smart technologies are reshaping service operations across sectors while raising critical concerns related to privacy, fairness, and accountability. Given the complexity of risks arising from interactions among diverse service agents, effective governance demands a holistic understanding of how responsibility is generated and managed within smart service ecosystems. To address these dynamics, we conduct a systematic literature review in order to establish a foundational under-standing of smart service social responsibility (SSSR). We propose a novel “I-D-G” (identify-deconstruct-govern) framework, providing an integrated lens through which to analyze responsibility emergence, attribution, and governance in multi-agent systems. Our review identifies key dimensions of responsibility, clarifies the roles and interactions of agents, and synthesizes governance practices along three pathways: technological governance, institutional regulation, and multi-party supervision. This study advances the literature on service, operations, and engineering management by offering a structured framework with which to enhance social responsibility and collaborative governance in smart service operations. Finally, we propose several future research directions to strengthen the adaptive and effective governance of SSSR from both theoretical and practical perspectives.

Acquirer firms are used to leverage contingent earnouts to mitigate exchange hazards in mergers and acquisitions. However, in technology acquisition, the costs of such flexible contractual arrangements may exceed the benefits. Drawing on the real options theory and the incomplete contract theory, we predict that target firms, concerned about defaulting on staging performance commitments and thus triggering punitive clauses, are likely to divert their efforts from innovation. Using a dataset that comprised publicly listed companies acquiring privately held targets, we verify the crowding-out effect of contingent earnouts on the target firm's post-acquisition innovation. We further examine the heterogeneities among different contractual designs-commitment duration, governance modes, and payment modes-unearthing the nuanced behavioral changes within the acquired parties.

Purpose The numerous spoil grounds brought about by mega transportation infrastructure projects which can be influenced by the ecological environment. To achieve better management of spoil grounds, this paper aims to assess their comprehensive risk levels and categorize them into different categories based on ecological environmental risks. Design/methodology/approach Based on analysis of the environmental characteristics of spoil grounds, this paper first comprehensively identified the ecological environmental risk factors and developed a risk assessment index system to quantitatively describe the comprehensive risk levels. Second, this paper proposed a comprehensive model to determine the risk assessment and categorization of spoil ground group in mega projects integrating improved projection pursuit clustering (PPC) method and K-means clustering algorithm. Finally, a case study of a spoil ground group (includes 50 spoil grounds) in a mega infrastructure project in western China is presented to demonstrate and validate the proposed method. Findings The results show that our proposed comprehensive model can efficiently assess and categorize the spoil grounds in the group based on their comprehensive ecological environmental risk. In addition, during the process of risk assessment and categorization of spoil grounds, it is necessary to distinguish between sensitive factors and nonsensitive factors. The differences between different categories of spoil grounds can be recognized based on nonsensitive factors, and high-risk spoil grounds which need to be focused more on can be identified according to sensitive factors. Originality/value This paper develops a comprehensive model of risk assessment and categorization of a group of spoil grounds based on their ecological environmental risks, which can provide a reference for the management of spoil grounds in mega projects.

Recent years have witnessed a proliferation of digital innovation research on the relationship between digital technology and corporate innovation. However, the evidence across different disciplines and contexts regarding the innovation outcomes of digital technology has been contradictory. Using the meta-analysis approach, we examined 176 253 observations from 113 studies and found a positive relationship between digital technology and corporate innovation. From a knowledge-based perspective, we argue that the positive impact of digital technology on corporate innovation stems from knowledge generation, knowledge flow, and knowledge absorption. Furthermore, we posit that the benefits that digital technology brings to corporate innovation depend upon the external conditions in which the corporations are situated. In particular, our study presents empirical evidence showing that the relationship is stronger in countries with weak institutional support of innovation and a weak rule of law. In this study, we find no evidence to suggest that the effect size varies across various industrial contexts and innovation paradigms. Moreover, we find that the positive impacts of digital technology on corporate innovation appear to grow with time. Our article contributes both to technology management and corporate innovation management, delivering possibilities for and insights into managerial practices.

By integrating the political strategy literature and research on innovation, this article develops a theoretical framework and empirically tests how and why political turnover affects firm innovation. Drawing on the attention-based view, we argue that firms also use innovation as an attention-catching strategy to seek opportunities in uncertain environments. Furthermore, we highlight how the uncertainty rooted in political turnover varies by identifying two contingent values: 1) politicians' career concerns and 2) firms' political hierarchy. Using a longitudinal data set of industrial enterprises in the context of China, we find that there is a significant positive relationship between the replacement of government leaders at prefectural city level and firm innovation. Moreover, this positive relationship is strengthened when new government leaders are promoted locally, but is less salient if the politicians are at an early stage of their career or firms are affiliated with higher hierarchies. Our research expands the literature on uncertainty by highlighting the role of political agents, contributes to the theory of the attention-based view by treating attention from key external stakeholders as a key resource, and advances the understanding of how firms strategically respond to political shocks in China.

Prior literature on ownership suggests that in the majority of cases, state ownership in state-owned enterprises (SOEs) is not an optimal structure for firm performance, especially in emerging economies. Mixed-ownership structures are designed to overcome this disadvantage. However, their impacts on innovation are not well understood. We examine whether and how SOEs' innovation efforts benefit from mixed-ownership reform, using a sample of 375 publicly listed SOEs operating in China between 2003 and 2019. We discuss principal-principal and principal-agent conflicts in SOEs and argue that the increase in managerial autonomy that accompanies mixed-ownership reform releases SOEs from state control and orients them toward engagement with market forces, encouraging higher levels of innovation. Our results suggest that both the frequency and the impact of innovation in SOEs are improved by mixed-ownership reform. We further find that this relationship is more pronounced when SOEs are affiliated with the central government, and it is strengthened through an anti-corruption policy. This study provides fresh insights into the role of mixed-ownership reform in emerging economies.

Transport infrastructure has been found to shape various outcomes of economic organizations by lowering travel costs and improving market access. In this article, we examine the spillover effect of highways on firm-level productivity and introduce innovation as a potential underlying mechanism. We argue that connection to national highways overcomes the localization of knowledge spillover by connecting ideas, information, knowledge, and talent across regions, which further improves firm productivity. Using a manufacturing sample from 1998 to 2007 in the context of China, we find a positive relationship between connection to the highways and firm productivity, and this relationship is mediated by innovation performance. Our results also suggest that such a mediating effect is strengthened when a firm is located in a region with greater market liberalization or intermediary development. Our findings add to the knowledge of economic geography by providing new insights into the interplay between infrastructure and organizational outcomes.

PurposeThis research aims to propose a model for the complex decision-making involved in the ecological restoration of mega-infrastructure (e.g. railway engineering). This model is based on multi-source heterogeneous data and will enable stakeholders to solve practical problems in decision-making processes and prevent delayed responses to the demand for ecological restoration.Design/methodology/approachBased on the principle of complexity degradation, this research collects and brings together multi-source heterogeneous data, including meteorological station data, remote sensing image data, railway engineering ecological risk text data and ecological restoration text data. Further, this research establishes an ecological restoration plan library to form input feature vectors. Random forest is used for classification decisions. The ecological restoration technologies and restoration plant species suitable for different regions are generated.FindingsThis research can effectively assist managers of mega-infrastructure projects in making ecological restoration decisions. The accuracy of the model reaches 0.83. Based on the natural environment and construction disturbances in different regions, this model can determine suitable types of trees, shrubs and herbs for planting, as well as the corresponding ecological restoration technologies needed.Practical implicationsManagers should pay attention to the multiple types of data generated in different stages of megaproject and identify the internal relationships between these multi-source heterogeneous data, which provides a decision-making basis for complex management decisions. The coupling between ecological restoration technologies and restoration plant species is also an important factor in improving the efficiency of ecological compensation.Originality/valueUnlike previous studies, which have selected a typical section of a railway for specialized analysis, the complex decision-making model for ecological restoration proposed in this research has wider geographical applicability and can better meet the diverse ecological restoration needs of railway projects that span large regions.

Under severe competition and the pressures of regulations and stakeholders, it is important for all firms, in addition to successful peers, to gain legitimacy and maintain a competitive advantage by transitioning to ecologically sustainable business practices. By integrating information-based imitation and rivalry-based imitation theories, in this article, we investigate how access to successful peers’ information enables focal firms to engage in green innovation. Using a sample of Chinese listed firms over the period 2007–2017, we find that focal firms are likely to imitate successful peers’ green innovation behavior; we call this the “benchmarking effect.” The effect is stronger when focal firms have a high degree of directors’ network centrality or are geographically close to successful peers. These findings extend the research on who firms imitate and highlight the importance of information accessibility in promoting organizational homogenization.