The potential of organizational hybridity, characterised by a highly balanced combination of state and private ownership, to yield better outcomes remains unclear in the existing literature, due to conflicting predictions from institutional logics theory and the resource-based view (RBV). This paper investigates the impact of organizational hybridity on innovation quality by introducing the construct of hybrid resource orchestration and complementary governance structures, using a mixed-methods design. Study 1, based on quantitative data from Chinese listed tourism firms (2013-2024), reveals a positive correlation between organizational hybridity and innovation quality, moderated by perceived uncertainty and foreign ownership. To further explore the corporate governance conditions driving this relationship, Study 2 employs fuzzy-set qualitative comparative analysis (fsQCA) to identify governance configurations that facilitate the transition from hybridity to innovation quality. The study contributes to the literature by providing new insights into how hybridity shapes governance structures that drive innovation outcomes. Additionally, the managerial implications suggest that hybrid firms should tailor their monitoring and incentive mechanisms based on their ownership type to optimise innovation quality.
Cross-border technology mergers and acquisitions (M&As) play a vital role in global technology diffusion, yet their network formation mechanisms and evolution patterns remain underexplored. Based on 40,761 high-tech cross-border M&As from 1997 to 2022, this study applies complex network analysis and the exponential random graph model (ERGM) to examine the structural characteristics and driving mechanisms of the global cross-border technology M&A network. Results show that the network exhibits small-world characteristics and core-periphery structures, and further evolves into a multi-center pattern as its scale and complexity increase. At the same time, the network exhibits significant reciprocity. High- and low-income countries (regions) tend to select partners with similar economic levels, while middle-income countries (regions) show significant sender and receiver effects. Geographical, linguistic, and institutional proximity positively influence network formation, with geographical proximity the most prominent. We show that global cross-border technology M&As are not borderless market transactions, but an evolving network in which reciprocity, economic hierarchy, and proximity systematically govern access to technological assets.
Traditional patent licensing literature primarily adopts a licensor-centric view. Shifting to the licensee's strategic dilemma, we analyse how capital-constrained firms under R&D uncertainty choose between Upfront Lump-Sum (ULS) and Pay-After-Use (PAU) contracts in a non-exclusive environment. Using a Stackelberg framework that endogenises payment choice as a risk-governance mechanism, we reveal: (1) A 'capital-risk map' where ULS is optimal for well-funded firms with high success probabilities to lock in production efficiency, while PAU serves as a hedge for the resource-constrained. (2) Structural inefficiencies in competition, specifically a liquidity-driven Prisoner's Dilemma and an over-investment paradox where excessive capital triggers destructive price wars. (3) A Value-Erosion Paradox for licensors, whose returns decline as improving licensee capabilities drive a shift from royalty-based to fixed-fee payments. This study bridges corporate finance and innovation strategy to provide a foundation for designing adaptive licensing contracts.
Innovation and green development drive economic growth, and innovative environmental policies resolve the environment-economy contradiction. This study investigates the impact of the Central Environmental Protection Inspection (CEPI) on urban green technological innovation, utilising Double Machine Learning (DML) with panel data from 255 prefecture-level cities in China spanning 2014-2021. It also explores the synergistic effects of market and administrative mechanisms. Results indicate CEPI significantly enhances urban green innovation. Heterogeneity analysis shows CEPI has a stronger effect on green innovation in China's Northwestern and Northeastern regions, the Pearl River Delta urban agglomeration and state-designated key environmental protection cities. Mechanistic tests indicate CEPI promotes green innovation through command-based environmental regulations and green credit activation. Moreover, green bond market development enhances CEPI's positive impact on green innovation. Government environmental penalty intensity, environmental attention and green development funds significantly boost green innovation. Therefore, a systematic evaluation of key factors (e.g. regional economies, innovation vitality), differentiated CEPI standards with supporting policies, an improved green financial framework and synergistic governance tools are needed to strengthen CEPI's promotion of urban green innovation.
In Industry 5.0, integrating advanced technologies like generative artificial intelligence (Gen-AI) is driven by user and system factors. While previous research has predominantly focused on user factors in AI adoption, limited attention has been given to system attributes. This study empirically examines the impact of both user and system factors on employees' attitudes, behavioural intentions and actual use of Gen-AI. Using the meta-UTAUT and Task Technology Fit (TTF) frameworks, our structural analysis of 247 respondents from multinational corporations operating in Turkey reveals that user and system factors positively influence attitudes and behavioural intentions towards Gen-AI adoption, whereas performance expectancy directly strengthens Gen-AI usage. Additionally, system factors significantly enhance user-related factors, highlighting the reciprocal relationship between the two. However, performance expectancy insignificantly relates to employees' attitudes towards Gen-AI. Our findings underscore the importance of how employees perceive and engage with Gen-AI, influencing their willingness to adopt and utilise it, which in turn fosters creativity. This research provides a comprehensive understanding of the interplay between user and system factors in Gen-AI adoption, offering insights into how their integration can enhance creative outcomes, drive employee innovation and promote widespread engagement with Gen-AI in Industry 5.0.
Complex product development networks (CPDNs) are typically characterised by co-opetition relationships and restricted communication structures between manufacturers and suppliers. Traditional investment decision models often fail to capture these two inherent features simultaneously. To bridge this gap, this study proposes a novel biform game model that integrates the Position value from the graph cooperative game framework. In the non-cooperative stage, firms determine their investment levels. In the cooperative stage, collaborative benefits are allocated based on the Position value, which effectively reflects firms' marginal contributions and their brokerage roles within the network topology. Furthermore, we explore the impact of key parameters on investment decisions and extend the model to networks with n suppliers to verify the robustness of our conclusions. The finding reveals that the optimal investments derived from the biform game model are higher than those from a pure non-cooperative model, underscoring the role of cooperation in incentivizing investment. This research presents a novel theoretical framework for analyzing strategic investment under co-opetition and communication constraints, offering practical insights to enhance investment efficiency and collaboration in CPDNs.
