In the context of accelerating digital transformation and technological turbulence, firms increasingly rely on digital dynamic capabilities (DDC) to achieve breakthrough technological innovation (BKTI). However, the mechanisms through which DDC are associated with such innovation outcomes remain insufficiently specified, particularly regarding how digitally enabled capabilities translate into knowledge processes. Drawing on dynamic capability theory and the knowledge-based view, we develop and test a theoretical framework in which ambidextrous knowledge integration, exploratory and exploitative, mediates the relationship between DDC and BKTI. Furthermore, we theorize organizational inertia as a critical boundary condition that may constrain the efficacy of this capability to innovation pathway. Using a multi-source dataset from firms across diverse industries in China, we find that DDC's primary impact on BKTI occurs through AKI, with XKI exerting a stronger mediating effect than EKI. Organizational inertia significantly weakens these effects, particularly for XKI, highlighting the contingent nature of capability-driven innovation. This study contributes to the literature in three ways. First, it clarifies how the “digital” dimension of dynamic capabilities relates to knowledge integration processes. Second, it refines the ambidexterity perspective by specifying how EKI and XKI jointly support BKTI without assuming rigid sequencing. Third, it introduces a more contingent view of capability-innovation relationships by incorporating organizational inertia. Given the China-based sample, the findings should be interpreted as contextually embedded, particularly in digitally intensive environments.
Organizations that innovate with emerging digital technologies increasingly manage portfolios in which activities differ not only in risk and maturity, but in the kind of management they require. Research on innovation portfolio management has often approached the portfolio as a managerial object whose practices can be optimized, offering limited guidance for managing heterogeneous portfolios in contexts shaped by emerging digital technologies. Drawing on interviews with 26 informants in seven incumbent Scandinavian organizations, this study explores how organizations differentiate and configure their innovation portfolio management practices. Through an abductive analysis, we develop a taxonomy comprising three innovation portfolio management practice configurations: the product-developing, platform-mediating, and problem-solving configuration. The taxonomy helps explain portfolio heterogeneity by showing how qualitatively different innovation activities correspond to different configurations of innovation portfolio management practices. By reconceptualizing portfolio heterogeneity as the coexistence of qualitatively different practice configurations, the study extends innovation portfolio management theory and offers a practical framework for managing innovation portfolios in contexts shaped by emerging digital technologies.
As artificial intelligence (AI) becomes a central driver of innovation and competitive advantage, firms increasingly rely on AI-related narratives to signal technological capabilities to external stakeholders. However, such signaling may deviate from actual technological activities, giving rise to AI washing (AIwash), which can distort the interpretation of firms' technological capabilities and undermine the credibility of AI-related signals in emerging technology markets. Drawing on a contract-based perspective, we examine how heterogeneous forms of patient capital are associated with AI signaling distortion. Using a sample of Chinese A-share listed firms from 2007 to 2024, we find that equity-type patient capital (PCS) is negatively associated with AIwash, and this association is related to stronger governance and reputational discipline. In contrast, debt-type patient capital (PCD) is positively associated with AIwash, and this association is related to earnings management. The decomposition of disclosure–activities divergence indicates that PCS is primarily associated with lower levels of AI over-claiming, whereas PCD is associated with higher levels of over-claiming. Moreover, financing constraints positively moderates the relationship between PCD with AIwash. Heterogeneity analyses show that the negative association between PCS and AIwash is stronger in high-technology industries, star firms, and firms in mature and declining stages, whereas the positive association between PCD and AIwash is primarily concentrated in non-high-technology industries, non-star firms, and growth-stage firms. Overall, the findings contribute to the literature on innovation signaling and technology governance by showing that different financial contract structures are systematically associated with the credibility of AI-related technological signaling in emerging technology markets.
This study examines the growth hacking mechanism and its antecedents in enhancing Small and Medium-sized Enterprises (SME) entrepreneurial performance in developing economies. Despite growing interest in growth hacking, prior studies remain limited in providing a comprehensive theoretical explanation and empirical validation, particularly within the context of developing countries. Using Partial Least Squares Structural Equation Modeling, this study analyzes data from 318 SMEs that have adopted digitalization practices. Drawing on the Technology–Organization–Environment (TOE) framework, it examines technological factors (big data analytics and digital transformation), organizational factors (entrepreneurial leadership and learning ambidexterity), and environmental factors (government support and university partnership). The findings indicate that big data analytics, digital transformation, entrepreneurial leadership, and learning ambidexterity significantly enhance growth hacking effectiveness. Government support emerges as a key external enabler, while university partnership shows no significant effect. This study contributes to the literature by positioning growth hacking as a cross-functional capability within the TOE framework and highlighting the contextual importance of institutional support in developing economies.
