ABSTRACT Creative destruction, though underexamined in platform ecosystem research, is a core mechanism of innovation and economic transformation. By disrupting established structures, it enables technological progress and increases diversity among innovators. This study investigates the dynamics of complementors within platform ecosystems and their interactions with platform owners' technological capabilities, highlighting their joint influence on generativity. Drawing on data from video game platforms, patent registrations, and quantitative analyses, we integrate creative destruction and technological capability to evaluate their combined impact on innovation outcomes. The findings indicate that platform owners' technological capability strengthens the positive effect of creative destruction on generativity. Furthermore, technological capability equips platform owners with the governance tools necessary to navigate the complexities of a diverse influx of new innovators. The study advances theory by unpacking the interplay between creative destruction and technological capability in platform ecosystems and offers managerial insights for leveraging these dynamics to sustain innovation and competitive advantage.
ABSTRACT The adoption of biodiversity loss mitigation innovations (BLMIs) in business markets depends on customers recognizing their value. Current literature lacks sufficient understanding of the decision processes, through which suppliers and customers make the ecological value of BLMIs visible, credible, and economically actionable. This paper explores decision‐making concerning and development of BLMIs at the supplier‐customer interface, using an interventionist research approach. The paper combines the switching path analysis technique (SPAT) and the Gioia method to analyze interview data on how decisions on BLMIs are currently being made and how these innovations could be developed to accelerate their adoption. Our results suggest that BLMI decisions currently rely on identifying cost‐efficient approaches that sufficiently address the biodiversity‐related concerns, while merely hoping to also capture the more ambiguous but broader ecological value in economic terms. Moreover, our study suggests that in addition to introducing the BLMIs themselves, the measurement of the ecological value and its translation into economic customer value need to be developed to enhance the adoption of BLMIs. The paper contributes to literature on biodiversity innovations and customer value by identifying the core business challenges related to BLMI.
These days, a wave of artificial intelligence applications is arriving in the way we manage innovation. But where are we now, and how can one use AI practically in innovation management? Against this background, we first extend an earlier literature review in text classification to demonstrate that the field remains scarce. We then address the current research gap by successfully conducting a machine learning project to evaluate ideas using text classification with transformer models. For this, we semi-automatically extracted customer needs in the field of smart speakers by downloading a Twitter dataset containing 473,301 tweets. We classified 107,738 tweets using a machine learning model, identified 12,641 potential need-containing tweets, and manually coded the first 1000. Our results can assist innovation managers and researchers in implementing high-performing machine learning models to support their innovation management tasks in different ways. We documented the design choices for this machine learning project in detail, deriving guidelines for creating text classification projects tailored to the domain of innovation management.
Leveraging the exogenous shock of the implementation of China's Environmental Protection Tax Law, this study empirically examines the impact of green tax reform on corporate R&D manipulation. Using the sample of Chinese listed firms and employing a difference-in-differences approach, we find that green tax reform significantly curbs corporate R&D manipulation, specifically by reducing abnormal R&D expenditures. This conclusion remains robust after a series of tests. Mechanism analyses reveal that this effect operates primarily through three channels: the optimization of environmental information disclosure, enhanced supervisory governance by external stakeholders, and the reduction of transaction costs associated with regulatory compliance. Further analysis suggests that by mitigating R&D manipulation, green tax reform ultimately enhances both the quality and efficiency of corporate innovation. Our findings contribute to the growing literature on environmental regulation and corporate innovation by highlighting the governance role of green taxation, and provide important policy implications for designing market-based environmental instruments to foster genuine and sustainable innovation.
Business model innovation (BMI) is a key decision faced by entrepreneurial firms. Yet, a firm's entrepreneurial team can hold diverse cognitive views of business models, leading to an incomplete understanding of how entrepreneurial teams can actually leverage these diverse cognitive resources for BMI. Drawing on the cognitive view of BMI, we explore how domain-specific schemas-a key aspect of managerial cognition gleaned from prior industry experience-may influence BMI. Rather than assuming the influence of schemas is uniform across situations, we conceptualize it as contingent on two salient situated factors-namely, team faultlines and industry competition logic. We posit that while the sharing of schemas in entrepreneurial teams is critical for BMI, whether those teams are able to bring about actual innovation depends on the industry context in which their new venture operates. Empirical analysis of 799 IT-based firms in China provides general support for our arguments. Our study contributes to the cognitive view of BMI and deepens our understanding of the role of situated context in BMI.
Generative AI (GenAI) is reshaping firm innovation through advanced content generation. While prior studies have emphasized GenAI's contributions to both market-facing and operational innovation, most remain fragmented observations, lacking theoretical integration and large-scale empirical validation. To address this gap, this study integrates the Dynamic Capability View and Institutional-Based View to propose and test a conceptual framework that includes demand-related (product/marketing) and supply-related (process/organizational) innovations. Analyzing survey data from 335 Chinese manufacturing and Information and Communication Technology firms using PLS-SEM, we find that GenAI routine use enhances market agility, thereby facilitating product and marketing innovation, and improves operational agility, which in turn boosts process and organizational innovation. Crucially, the moderating effect of environmental dynamism is negative and uniquely observed among state-owned enterprises. These findings underscore GenAI's dual innovation value and highlight organizational agility as a critical pathway linking technology embeddedness to ambidextrous innovation. They also suggest that realizing the full potential of GenAI requires alignment between a firm's underlying dynamic capabilities and the dynamism of its external environment.
This study investigates how CEOs' political ideology affects corporate decisions to sue for patent infringement. Integrating upper-echelons and behavioral-agency perspectives, we theorize that conservative-leaning CEOs-marked by heightened threat sensitivity and low tolerance for ambiguity-frame infringement as a looming loss and therefore favor litigation as the most rule-bound, controllable response. Liberal CEOs, by contrast, are less likely to initiate litigation. We further contend that recent firm performance amplifies this ideological imprint: when results exceed aspirations, the ideology-litigation relationship steepens, with conservative CEOs becoming more likely to file and liberal CEOs less likely to do so; when performance weakens, this divide narrows. These propositions are tested on an unbalanced panel of 1275 US firm-year observations, obtained by linking political-donation records with patent, financial and litigation data. Results confirm that conservative CEOs significantly raise the odds of initiating a patent suit; the effect strengthens at high performance levels and weakens when performance falls below industry benchmarks. By exposing the ideological microfoundations of patent enforcement, the study extends competitive-dynamics research, demonstrates how personal values shape nonmarket strategies and competitive tactics. Consequently, we alert boards, R&D managers and investors to a behavioral driver of costly patent disputes.
Reverse innovation refers to an innovation first developed or adopted in an emerging economy before being further developed and/or adopted in advanced ones. Despite the growing research on reverse innovation over the past decade, its firm-level antecedents remain relatively unexplored. We examine how different dimensions of CEO professional experience can impact reverse innovation in multinational firms from emerging markets, drawing on Upper Echelons Theory and data from the ORBIS IP dataset alongside manually collected data. On a sample of 8301 India-USA patent dyads representing the reverse innovation of 143 pharmaceutical firms between 2014 and 2023, we find that firm-level experience and international experience of the CEO are positively associated with reverse innovation. In contrast, CEOs' overall professional work experience has a negative influence on a firm's reverse innovation capability, whereas multi-industry experience of CEOs shows no significant impact on reverse innovation. Our study contributes to the reverse innovation debate by disaggregating the specific aspects of CEO experience that enhance or hinder reverse innovation, with a specific focus on emerging market multinational firms.
Idiosyncratic geographical characteristics of regions play a critical role in determining how economic forces may display different directional and magnitude effects that are often neither symmetric nor reciprocal. This manuscript advances the understanding of the potential implications of the Knowledge Spillover Theory of Entrepreneurship, as the transmission of knowledge and related spillovers is conditional by geographic invisible barriers depicted in the conditional proximity hypothesis. The concept of Conditional Proximity is introduced to better understand the moderating potential magnitude and direction of knowledge spillover effects as a complementary perspective to the Marshallian channels. We validate this argumentation using a novel database of Italian innovative startups at the 2-Dig NAICS level of classification. The evidence indicates the strong presence of conditional proximity between neighboring regions as observed in the persistent differences in new firm formation and resulting differences in firm intensity by economic sector in neighboring regions. The same level of cross-interaction across border-sharing regions creates idiosyncratic heterogeneous knowledge spillover effects across sectors and neighboring regions. Evidence shows that conditional proximity explains the different transferability across proxime regions and demonstrates why some sectors perform better than others. In addition, the asymmetric relationship between neighboring regions explains that distance is conditional to the presence and dynamics of the entrepreneurial ecosystems of the regions.
Public procurement is increasingly employed as an instrument to stimulate innovation. However, little is known about how public actors manage problem-framing processes in the context of public procurement of innovation. Drawing on the literature of problem-framing and public procurement, we conduct an exploratory case study of three innovation procurement processes involving public buyers, private suppliers and other stakeholders. Our findings reveal how problems and potential solutions co-evolve through interaction among actors and how public managers adopt different strategies to steer these processes. We develop a framework that conceptualises problem framing and management of the problem framing by three distinct approaches to control-keep, share and give-which vary in how control over elements of problem-framing is distributed between public and private actors. Each approach to control shapes the public actor's facilitation role and influences suppliers' scope for action, learning and innovation. By placing problem framing as a key yet underexplored lever in collaborative innovation, our study contributes to both public procurement and innovation management research. We offer practical guidance on managing problem framing and orchestrating collaborative innovation across organisational boundaries.
Generative artificial intelligence (AI) can transform research and development (R&D) by enhancing efficiency, accelerating product development, and fostering innovation. As companies seek to integrate this technology, understanding the role of organizational readiness and AI literacy as well as generative AI's impact on innovation capacity becomes increasingly important. This study examines whether cultural and structural readiness and AI literacy affect the use of generative AI and how generative AI influences R&D activities and innovation capacity. The study employs a qualitative pre-study and survey data, analyzed with structural equation modeling. The findings show that cultural readiness, reflecting an organization's openness to AI-driven change, is a key enabler of successful adoption. Structural readiness, defined by the technological and procedural alignment with AI applications, appears to play a conditional role, depending on the level of employees' AI literacy. The findings also demonstrate that generative AI supports R&D processes and, in turn, enhances innovation capacity. By providing insights into the interplay between organizational readiness, AI literacy, generative AI utilization, and its impact on R&D activities and innovation capacity, this research advances the academic understanding of how generative AI can contribute to innovation processes and provides practical implications for organizations aiming to leverage generative AI for competitive advantage.
While industrial internet platforms effectively coordinate physical assets, their capacity to manage human capital remains under-theorized. To address this gap, this study introduces the concept of an industrial internet-based shared talent ecosystem and investigates the central question: How do industrial internet platforms extend their orchestration capabilities to shape a shared talent ecosystem? Drawing on an in-depth case study of COSMOPlat, we develop a four-stage process model: (1) identifying talent pain points, (2) matching supply and demand, (3) establishing collaboration, and (4) stabilizing symbiosis. We find the collaboration stage is pivotal, where the platform builds a networked structure for talent selection, utilization, development, and retention through multi-dimensional sharing models. This ensures that the unique social development needs of talent are met in the sharing process, which sets them apart from non-human resources. This ecosystem then iterates by diffusing its established practices and transferring its model to new industries and regions. Theoretically, we advance platform orchestration theory by conceptualizing the platform as an institutional entrepreneur that manages human capital by addressing the tension between talent as a resource and as a social agent. For practice, our findings provide a roadmap for managers to build and sustain a symbiotic talent ecosystem.
China's New Energy Vehicle (NEV) industry has typical characteristics in the development of global manufacturing and has achieved remarkable results. This study employs the Quadruple Helix model to analyze and explain the complex dynamics of China's NEV industry, revealing the roles and interactions of multiple innovation entities, including the government, industry, the market, and universities, in the industry's development. The study finds that the Chinese government plays a key driving role in the early stage, accurately designing and adjusting the development direction of the industry by determining the technology roadmap, building R&D platforms, formulating marketing strategies, and technology policies. As the market matures, the government's role has gradually shifted from direct financial incentives to establishing a sustainable long-term mechanism to ensure the stable growth of the industry. This sustained but flexible involvement of the government ensures the continuity of industrial policy and the dynamic adaptability of the market. Through empirical analysis and case study, this study points out that government-led collaborative innovation and the continuous enhancement of local R&D capabilities are crucial driving forces for the industry's evolution. This study aims to provide theoretical and practical insights for the development of the global automotive industry and offer valuable experiences and references for other countries in the development of the NEV sector.
How do video game developers balance the pursuit of creative freedom with the demands of market responsiveness? Based on 62 in-depth qualitative interviews with Swedish game developers, this article advances a theory of individual ambidexterity in the creative digital industries. We identify two core dimensions: creative autonomy, characterized by experimental playfulness, personal vision and independence, and resistance to market conformity, and market alignment, marked by responsive iteration, stakeholder engagement, and commercial mobilization. Rather than operating as simple trade-offs, these dimensions constitute generative tensions that developers actively navigate and leverage. The study contributes to research on ambidexterity and paradox theory in innovation management by showing that contradictory demands in creative work are managed not only through structural and temporal separation but also through emergent, situated practices that allow creative intent and market logic to dynamically interpenetrate. By conceptualizing ambidexterity as a contextually enacted individual capability shaped by cognitive reframing, the study offers a practice-based perspective on innovation in R&D-intensive, culturally embedded sectors. These insights have important implications for how organizations structure autonomy, engage users, and sustain creative innovation under commercial constraints.
R&D collaborations involving multiple types of partners have the potential to generate impactful innovations but also pose significant coordination challenges. Taking a coordination perspective, this study develops and tests a theoretical framework on the optimal temporal coordination of partner relationships in such collaborations. We argue that the effective coordination of multiple types of collaboration partners in R&D projects requires a balanced approach, combining episodes of simultaneous involvement of all partners with periods of sequential engagement with individual partners. Moreover, we propose that the relative emphasis on simultaneous versus sequential involvement depends on project-specific factors, including the complexity of technology development and the availability of managerial resources. Our analysis of 454 R&D projects undertaken by a major European electronics firm, in collaboration with diverse partner types (science-based partners such as universities and research institutions, versus market-based partners such as suppliers and customers), provides robust empirical support for these hypotheses.
This study examines the role of domain knowledge diversity within corporate R&D teams and its impact on the development of significant innovations in the Climate Change Mitigation Technologies (CCMTs) sector. The research emphasizes the moderating effects of team size, embeddedness, and interconnectivity on the relationship between domain knowledge diversity and high-impact innovations. Analyzing 10,293 CCMT patents filed with the USPTO by 28 Japanese automotive companies between 1994 and 2016, findings reveal that knowledge diversity is crucial for impactful climate technology innovations, and its benefits are amplified in larger teams with a broader expertise range. Moreover, deeply embedded teams with shared values and trust, combined with higher interconnectivity, effectively leverage domain knowledge diversity to drive premier climate technology innovations. This study contributes to theory in green R&D management by highlighting the importance of domain knowledge diversity in corporate R&D teams for groundbreaking climate technology innovations, demonstrating the advantages of this diversity in larger teams, and elucidating the synergistic dynamics of team embeddedness and inter-team connectivity. Practically, the research suggests that businesses addressing climate change should emphasize domain knowledge diversity and nurture intra-organizational networks to enhance R&D initiatives and foster sustainable advancements.
This research fills the gap identified in the extant literature regarding the relationship between eco-innovation and innovation performance, employing the Fuzzy Set Qualitative Comparative Analysis (fsQCA) approach within the configuration theory framework. We analyze data from 2123 innovative manufacturing firms across eight European countries. The results highlight how the combination of product and process eco-innovations, and the firm's internal and external knowledge sources, leads to high innovation performance. Configurations vary significantly with firm size. Small firms benefit from simultaneous engagement in product and process eco-innovation when supported by innovation collaborations. Medium-sized firms benefit from comprehensive investments in their internal knowledge base combined with eco-innovations. Large firms benefit from product eco-innovation combined with R&D investments. This research offers valuable insights into the application of eco-innovation to achieve high innovation performance, providing eco-innovation strategies for managers to focus on sustainable business practices.
Although 5G is considered an enabling technology (ET), subject to ongoing technical improvements and permitting several complementary innovations, its transformative potential and pervasiveness are still limited. The unrealized potential of 5G is particularly burdensome for mobile network operators (MNOs), who have traditionally played a central role in the telecommunications sector. For MNOs, 5G represents a significant opportunity to renew their strategy, especially in light of the substantial investments in spectrum licenses and infrastructure made in recent years. Through an exploratory multiple case study of incumbent MNOs and 5G pioneering end-user companies in Italy, this study puts forward the 5G strategic ambiguity spectrum of MNOs in terms of value proposition, creation, and capture, framed along two main dimensions: (i) the choice between a strategy of technological innovation or servitization; and (ii) the scope of 5G commercialization (narrow vs. broad) across industrial verticals. By merging these two perspectives, which belong to two distinct streams of literature-business models (BMs) and enabling technology-this study offers an original view of the 'strategy in the making' challenges MNOs are currently facing during this shift in technology. We contribute to the open debate concerning technology and business model innovation, highlighting ambiguities in the value architecture that can arise when commercializing an ET, which are not so evident in the existing literature. Finally, three BM archetypes are proposed, based on key determinants of value proposition, creation, and capture, to provide managerial guidance on developing appropriate 5G business models and identifying the main aspects to consider.
Considerable research has established the performance implications of knowledge mobilization through individuals' informal ties. Scholars have also explored how the formal organization and the informal patterns of ties in organizations intermingle. Less is known, however, about how formal organizational elements influence what flows through these informal ties. We develop and test a theory about how granting autonomy in R&D activities impact the type of knowledge individuals choose to acquire from one another through informal ties. In particular, we study knowledge ties among researchers working in an R&D laboratory in a global pharmaceutical company. Results from our analysis show that there is a U-shaped relationship between granted autonomy to researchers in their R&D projects and cross-project knowledge ties. Our findings reveal the nuanced relationship between formal and informal organization, suggesting new implications for the organization of innovative activities within firms.
