Lean management (LM) is widely deployed to improve operational efficiency, yet its implications for innovation remain debated. We conducted a meta-analysis of 22 empirical studies (K = 71; N = 25,867) linking LM to innovation outcomes. Results reveal a moderate positive association between LM and overall innovation, but its strength varies across innovation types and contexts. Sustainable innovation, innovation capabilities, and process innovation benefit most, whereas the association with product innovation is not statistically significant. Lean workplace organisation and structure yield the strongest association, followed by lean strategic orientation, social practices, and technical practices. Industry type and innovation category explain heterogeneity, while firm size does not.
This paper examines how market and technological turbulence (MT, TT) influence AI-enabled inbound and outbound open innovation (IOI, OOI), their mediating effects on innovation performance (IP), and the moderating roles of effort expectancy (EE) and performance expectancy (PE) within the Industry 5.0 framework. A dual-method approach combining PLS-SEM and NCA was applied to survey data from 245 industry professionals collected between November 2024 and February 2025. Both IOI and OOI significantly enhance IP, with OOI emerging as the stronger predictor. MT positively influences both IOI and OOI, while TT affects only OOI. EE and PE moderate the turbulence–IOI relationship, and several mediation effects through open innovation are supported. The study extends Dynamic Capability Theory (DCT) and UTAUT by integrating AI-enabled open innovation into the Industry 5.0 paradigm, emphasizing the human factor in innovation management.
Disruptive innovation is recognized as an effective strategy for breaking established paradigms and achieving substantial growth through technological advancement.While existing literature highlights digital technology as a critical catalyst for enhancing firms’ innovation capabilities,research on the relationship between digital technology investment rhythm and disruptive innovation has been largely overlooked.Using empirical data from Chinese A-share manufacturing firms (2013–2023),we demonstrate that a sustained rhythm of digital technology investment promotes disruptive innovation.This relationship is mediated by resource reconstruction capability and resource allocation disparity.Moreover,organizational resilience positively moderates this link.Ultimately,our findings provide nuanced understanding of how firms orchestrate the digital technology investment rhythm to drive disruptive innovation.
The UNESCO Creative Cities Network (UCCN) represents a global initiative that aligns cultural and creative industries (CCIs) with sustainable development goals through innovation and technological integration. This study explores the uneven global distribution of Creative Cities by examining how national-level innovation systems, technological capacity, and socio-economic structures influence city nominations. Using Poisson fixed effects, Poisson pseudo maximum likelihood, and generalized linear models, we assess the impact of variables such as GDP per capita, human capital, urban density, and institutional quality. Our findings reveal that while economic development and strong human capital are key enablers, high institutional quality in innovation does not necessarily correlate with more UNESCO Creative City designations. This paradox underscores the need for more inclusive and context-sensitive innovation policies. The results contribute to the debate on how CCIs can better leverage innovation and technology to foster sustainable urban development and cultural resilience.
Drawing on organizational learning theory and the knowledge-based view, this study addresses the underexplored question of how ambidextrous learning affects innovation quality, particularly the moderating role of knowledge resources. We deconstruct ambidextrous learning into two dimensions, namely, balance and synergy, and we empirically investigate their effects on innovation quality using a sample of 463 listed manufacturing firms in China. We further incorporate the knowledge stock and research and development (R&D) partner diversity as critical moderators to clarify the relevant boundary conditions. The results reveal an inverted U-shaped relationship between ambidextrous learning balance and innovation quality, while ambidextrous learning synergy has a positive effect on innovation quality. Moreover, the positive effect of synergy is weakened by both the knowledge stock and R&D partner diversity. Heterogeneity analyses indicate that the negative moderating effect of the knowledge stock is stronger in high-tech industries and in highly dynamic environments, whereas the negative moderating effect of R&D partner diversity is more salient in academic‑led and weak-tie collaborations. These findings extend organizational learning theory by explaining the dual mechanisms through which ambidextrous learning influences innovation quality and by revealing the contextual constraints imposed by knowledge resources.
This study provides a comprehensive, updated overview of the literature on accelerators, highlighting their evolving role as cohort-based programs in supporting entrepreneurship and innovation. Accelerators have become central in helping startups overcome financial, skill-related, and legitimacy challenges. However, existing research on the topic remains fragmented. To address this, we conduct a bibliometric analysis of 174 peer-reviewed articles, collected from the Scopus database over the period 2005-2024. The findings reveal five thematic clusters: (1) Accelerators as open innovation tools; (2) Performance measurement and effectiveness; (3) Strategic approaches to startup growth; (4) The role of accelerators in entrepreneurial ecosystems; and (5) Design and evolution of accelerator models. We complement this analysis with an examination of the most cited works from the last five years. By integrating quantitative and qualitative insights, we identify gaps in the accelerator literature associated with these clusters and develop a research agenda structured around five research avenues: (1) Institutional and geographical contexts; (2) Diversity in selection processes; (3) Social and environmental impacts; (4) Collaboration dynamics; and (5) University-based and corporate accelerator roles. The results offer a solid foundation for scholars and practitioners to navigate the evolving landscape of accelerators and their impact on startup ecosystems in a context of post-pandemic environment and ongoing transformation.
The integration of digital technologies has significantly influenced the evolution of servitization strategies, leading to the transformation of traditional business models (BMs) into more service-oriented frameworks. Considering the rise of the topic, this study aims to offer a comprehensive and theoretically grounded synthesis of the extant literature on the integration of digital technologies, servitization and BM, by employing a systematic literature review, with the objective of identifying prevailing research trends and gaps that warrant further investigation. To this end, we identified and analysed a sample of 131 articles, ranging from 2005 to 2025. The article presents the content analysis of these articles according to the type of servitized offering, starting from the more general ones, namely general product-service systems (PSSs), to the more specified product-oriented services, until the most sophisticated use- and outcome-oriented services. The analysis reveals that, as service offerings become more complex, the three domains of digital technologies, servitization and BMs are progressively addressed not as isolated phenomena, but as interdependent elements. Building on this evidence, the article offers a novel contribution by systematizing a fragmented body of literature and by providing a clearer and more structured specification of digital servitization and its implications for BMs. Hence, from a theoretical perspective, the study advances existing knowledge by explicitly linking the three domains and clarifying their integration across different service configurations. From a managerial perspective, findings support managers in navigating digitalization and servitization, highlighting how they translate into distinct effects on BMs.
This study examines how artificial intelligence (AI) enables sustainability transformation in small and medium-sized enterprises (SMEs) in emerging economies. Using sequential mixed-methods design and drawing on Organizational Change (OC) and Organizational Transformation (OT) theories, the study of SMEs shows that AI drives sustainability through managerial enablement and organizational mechanisms. Strategic sensemaking, ethical framing, and participatory communication translate AI capabilities into sustainability goals, while governance routines and feedback systems institutionalize adaptive learning. The study contributes by integrating OC–OT perspectives and offers practical guidance for designing adaptive, ethically grounded AI-driven governance initiatives in resource-constrained contexts.
Artificial intelligence has evolved from rule-based systems to agentic AI: autonomous agents capable of perception, reasoning, and interaction with minimal human supervision. This transformation positions AI as a general-purpose technology with profound implications for labor markets. Autonomous agent capability is accelerating; the length of tasks frontier agents can complete unaided has been doubling roughly every seven months, yet measurement of labor effects has not kept pace, leaving managers and policymakers reliant on indices that capture only job elimination. This article reviews agentic AI through an interdisciplinary lens, integrating insights from computer science, economics, and organizational studies. It introduces the Labor Disruption Index (LDI), a composite framework capturing four dimensions of technological impact: displacement, automation potential, productivity enhancement, and new task creation. Unlike prior automation-risk indices that focus solely on job elimination, the LDI incorporates both negative and positive effects, enabling the identification of net outcomes at the occupational level. Each component is operationalized using existing datasets, and calibration procedures are demonstrated with sensitivity analyses across alternative weighting schemes. The analysis is organized through a micro–meso–macro framework: the micro level concerns agent design and technical capabilities; the meso level concerns organizational adoption patterns and governance structures; and the macro level concerns economy-wide impacts and policy responses. The synthesis draws on peer-reviewed empirical studies, including randomized controlled trials, adoption surveys, and macroeconomic projections. Findings reveal substantial heterogeneity across sectors: some roles face net displacement while others benefit from productivity gains and task creation. Applications are analyzed across healthcare, finance, manufacturing, legal services, education, and government. The article concludes with policy recommendations and an interdisciplinary research agenda organized around the LDI, advancing the measurement of labor disruption and providing actionable tools for scholars, managers, and policymakers.
The increasing complexity of innovation processes has led to the conceptualization of innovation ecosystems as complex systems. This study focuses on one underexplored property of such systems: their resilience to exogenous shocks. Specifically, we explore how digital platform adoption – accelerated since the COVID-19 pandemic – can facilitate internal reorganization within ecosystems following a shock by examining its effect on key systemic properties such as openness, diversity, coherence, and flexibility. Using network-based metrics and tests, we analyze a startup ecosystem on Twitter, advancing theoretical understanding of innovation ecosystem resilience and offering practical insights into the role of digital platforms.
Entrepreneurial support organizations (ESOs), such as incubators and accelerators, have rapidly become integral to modern entrepreneurial ecosystems. This study investigates how organizational and contextual factors affect the performance of technology startups accelerated under the European Space Agency’s BIC program from 2005 to 2025. Utilizing negative binomial regression models on a dataset of 1326 European New Space startups, we examine the roles of ESO geographical location, cohort density, and institutional experience in shaping startup outcomes. Our findings indicate that: ESO geographical location significantly shapes startup employment size; accumulated ESO institutional experience is a robust predictor of startup employment growth; and cohort characteristics show secondary effects. Grounded in the Resource-Based View, these insights enhance our understanding of the value and effectiveness of ESOs in technology-intensive sectors, particularly the New Space industry.
There is growing research interest in how inclusive innovation can overcome myriad local challenges related to the exclusion of the base of the pyramid (BoP). However, mechanisms that drive and create such innovations within resource-scarce environments and the amorphous institutional fabric are poorly understood. Drawing on the largest development organization in the world from the Global South, this study proposes a process framework and posits that institutional voids serve as an antecedent to the emergence of inclusive innovation. Proposing a multi-level perspective, this study shows that developing inclusive innovation is a complex process requiring synergistic efforts across multiple levels. At the micro-level, which focuses on the organization and its proximate context, inclusive innovation is enabled by effective social mobilization that purposely engages, builds capability, and empowers grassroots communities. At higher levels, inclusive innovation is enabled by an ecosystem approach. At the meso-level, which focuses on organizational and sector-specific institutional arrangements, inclusive innovation is facilitated by collaboration between traditional actors, such as public-private institutions, and non-traditional actors, such as key civil actors, non-profits, and non-governmental organizations. At the macro level, which focuses on the broader political domain, the strategic alignment of business goals with government priorities helps devise supportive policies, create enabling environments, and optimize the use of scarce resources. Furthermore, involving previously disenfranchised members of the BoP population as users, creators, and market actors across multiple levels enables deep co-creation to develop effective solutions. These integrated mechanisms facilitate higher adoption and greater impact of innovation and bridge institutional gaps.
Many antecedents of renewable energy technology innovation (RETI) have been examined independently; less is known about how these antecedents combine to affect RETI. Drawing on the resource-based view and resource orchestration theory, we conceptualize management compensation incentives, equity incentives, and gender diversity as resource allocation levers that motivate and guide resource toward RETI. Using a sample of Chinese renewable energy firms, we develop a configurational framework and draw on fuzzy-set qualitative comparative analysis to investigate how these levers combine to facilitate RETI across different innovation subjects (e.g., firms with different size and financial performance) and innovation environments (e.g., different economic development level, industry competition, and environmental regulation). Our results identify four high-level configurations that can facilitate RETI by tailoring resource allocation levers to innovation subject and innovation environment. Comparing the high-level configurations with the low-level configurations, we find that the same lever in different configurations may yield the opposite effect. We also find that even lacking innovation-conducive environments, firms can still achieve high-level RETI by using tailored levers. These findings guide renewable energy firms on how to promote RETI by utilizing internal levers effectively when facing different situations.
This prototyping experiment evaluates the technical and economic feasibility of integrating Digital Twins of Customer Demands (DTCD) with different production strategies. DTCD is defined as data-driven and digital representations of customer preferences and product usage. Results demonstrate that DTCD enables the accurate digital capture and transformation of customer-specific data, allowing for both fully customised products and the optimisation of standardised production. The findings show that precise demand information, rather than customisation itself, drives value creation. DTCD enables near-custom quality at moderate cost, opening a new cost--performance window and redefining the efficiency-responsiveness trade-off.
As manufacturing firms adopt digital technologies to improve efficiency, they increasingly collaborate with system integrators to compensate for internal capability gaps. Such collaborations, however, are prone to interpretive uncertainty-cognitive misalignments about goals, processes, and technologies-that complicate coordination and value creation. This study examines how governance mechanisms shape the performance implications of these collaborations by analyzing survey data from 101 Italian automotive manufacturers. Focusing on two relational governance practices-co-creation and continuous collaboration-and two types of digital technologies-network and physical-digital interface technologies-we find that governance effectiveness is strongly contingent on technological characteristics. Co-creation is associated with lower cost efficiency when applied to more standardized physical-digital interface technologies, whereas relational governance is associated with higher cost efficiency in more systemically integrative digital initiatives involving network technologies. These findings advance research on inter-organizational governance and digital transformation by demonstrating how governance-technology alignment shapes operational outcomes and by highlighting the underexplored role of system integrators in manufacturing digitalization. The study also offers managers and policymakers guidance on tailoring governance to technological and relational contexts to support effective digital adoption.
The growing importance of innovation management in the Web 3.0 era requires companies to rethink organizational strategies and training approaches. Characterized by decentralization, interoperability, and user empowerment, Web 3.0 reshapes corporate processes, enabling new forms of collaboration, knowledge sharing, and value creation. However, its adoption poses significant challenges, as organizations must develop both technical and organizational competences to remain competitive. This study investigates the competences required by companies to navigate the technological transformation driven by Web 3.0, adopting the theoretical lens of dynamic capabilities and their individual-level micro-foundations. A qualitative multiple case study approach was conducted across six companies, analyzing how hard and soft skills underpin the sensing, seizing, and transforming dimension of dynamic capabilities within innovation management. Findings show that hard skills-such as programming, AI, and cloud infrastructure management-support the exploitation of technological opportunities, while soft skills-such as teamwork, adaptability, and problem-solving-enhance the capacity to reconfigure processes and sustain collaborative innovation. These competencies act together to strengthen organizational agility and the strategic management of innovation. The study contributes theoretically by linking human resource competencies to dynamic capabilities, advancing the understanding of individual-level micro-foundations in digital innovation contexts. Practically, it offers guidance for designing training programs and preparing hybrid profiles capable of addressing the challenges and opportunities of Web 3.0.
The design sector represents a pivotal yet underexplored component of the Cultural and Creative Industries (CCIs), playing a strategic role in fostering innovation, competitiveness, and sustainability across the broader economy. This paper addresses this gap by investigating how creativity relates to technology, innovation and environmental sustainability within the design industry. We rely on an original dataset covering a sample of Italian design firms operating in 2023. We complement firm-level information with novel data collected through a web-scraping algorithm that identifies the presence and intensity of keywords related to creativity, innovation, technology, and sustainability on designers' websites. Combining descriptive statistical analysis with econometric estimations, we show that creativity is the most salient dimension in designers' selfpresentation, while sustainability receives comparatively less emphasis. The results show how creativity is linked to the use of diverse technologies rather than to higher overall levels of technological innovation. Creativity is also positively correlated with both the presence and intensity of sustainability-related content. Regarding technological innovation, sectoral heterogeneity emerges clearly, and interaction designers appear to be the most technologically oriented. Lower sectoral difference emerges, however, in environmental sustainability practises.
This study investigates how environmental, social, and governance (ESG) practices influence innovation performance in technological mergers and acquisitions (M&A) in the semiconductor industry. Drawing on stakeholder theory, we examine whether acquiring firms emphasize ESG when targeting technologically similar companies and how this affects post-M&A exploitative innovation. By analyzing semiconductor M&A transactions, we find a directionally consistent but empirically weak curvilinear pattern between technological similarity and post-acquisition exploitative innovation. More importantly, social and governance practices significantly condition the curvature of this relationship, whereas environmental practices do not.
