R&D Management

Businesses increasingly rely on data to enhance operations, drive innovation, and create new products and services. Data has become a critical organizational asset, and the Open Innovation (OI) paradigm highlights its potential to be shared or freely released to stimulate innovation. The Open Data (OD) movement builds on this idea, promoting transparency, social development, and innovation through the “opening” of data. This study investigates the intersection of OD and OI by examining how organizations engaged in OD initiatives structure their business models and the impact of these models on financial performance. Open Data Business Models (ODBM) are essential for companies to leverage freely accessible, non‐proprietary data effectively, enabling them to create value through innovative services, enhanced customer engagement, or improved decision‐making processes. Using a sample of 406 UK companies, the study employs a qualitative approach to identify ODBM archetypes. A quantitative analysis investigates the relationship between industry sector, ODBM adoption, and financial performance. Findings reveal key ODBM characteristics, their prevalence, and potential links to financial performance, offering insights into the long‐term viability of ODBMs. Summed up, the study provides a foundational resource for researchers, policymakers, and practitioners to maximize OD benefits while ensuring economic resilience and sustainability.

In the dynamic landscape of Research and Development (R&D), there is still a gap in the evaluation of projects dealing with big data and open innovation. Integrating the resource‐based view (RBV) as a theoretical basis and the Frascati Manual principles to bridge theory and practice, this paper aims to provide a methodology for analyzing in a quantitative way the value of R&D projects dealing with big data. Leveraging Analytic Hierarchy Process (AHP) and Fuzzy Set Theory (FST), the proposed approach provides a hierarchical structure that measures the relative significance of the resources. The findings underscore a comprehensive evaluation methodology that captures the nuanced challenges of R&D projects in big data and open innovation fields, thus improving the capacity for strategic decision‐making by enabling companies to optimize their projects. Policymakers can employ the insights from this contribution to develop policies that encourage innovation and the efficient use of resources in R&D investments.

Artificial intelligence (AI) has revolutionized many industries, particularly tourism. Using the diffusion of innovation theory, value‐based adoption model, and technology readiness theory, this study examines AI adoption through perceived enjoyment, perceived usefulness, perceived fees, and technicality on perceived value in the tour, travel, and hospitality sectors. Data were analyzed using PLS‐SEM via SMARTPLS version 3.3.9, and an artificial neural network (ANN). The findings show that perceived fees and usefulness significantly impact perceived value. Travelers are more likely to value AI services if they perceive reasonable fees and enhanced search performance, leading to increased adoption intention. The study revealed that perceived enjoyment and technicality are not primary drivers of perceived value, underscoring the importance of pricing, perceived benefits, convenience, and cost‐effectiveness in promoting tourism offerings to enhance AI service value perception. In addition, the high perceived value of benefits, convenience, and cost‐effectiveness encourages AI adoption. The moderation effect of age and perceived innovativeness indicates a strong relationship between PV and AI adoption intentions among Gen Z.

This paper presents findings from a qualitative study that explored the factors affecting start‐up employees' adoption of AI technology for innovation ecosystems. Using thematic analysis based on interviews with 35 employees from start‐ups, we employed a grounded theory approach due to the newness of the context and the limited prior research. Our analysis identified several key themes, including perceived benefits of AI, technical considerations, organizational culture and values, employee attitudes and beliefs, access to resources, legal and ethical considerations, and industry‐specific factors. We found that technical considerations, such as data quality and technical infrastructure, played a significant role in determining AI adoption. Additionally, organizational culture and values were important in shaping employees' attitudes towards AI. Our study highlights the importance of addressing both technical and cultural factors when promoting the adoption of AI technology for innovation ecosystems in start‐ups. Our findings provide valuable insights for start‐up managers, policy makers, and researchers seeking to better understand the factors influencing AI adoption in this context.

Research on open innovation (OI) in SMEs, particularly in the context of digital innovations and big data (BD), often highlights the potential for these innovations to drive SME growth. While digital innovations and BD can indeed enhance OI practices by presenting new opportunities, there is a significant gap in understanding how the challenges posed by these innovations can also act as catalysts for OI in SMEs. This study addresses this gap by examining the challenges faced by SMEs when leveraging digital innovations and BD for service delivery in the agri‐food sector, and how they address them through OI practices. Focusing on Agritech firms in Ghana's agri‐food sector as an empirical case, we conducted qualitative exploratory research using interviews and secondary data to fill the research gap. Our findings showcase how Agritech firms adopt OI practices through strategic collaborations and partnerships with external organizations interested in agricultural interventions which was triggered by the challenges they faced in leveraging digital innovations and BD. These partnerships and collaborations also serve as anticipatory measures to tackle potential future challenges. Our findings are not only applicable to Agritech firms in the agri‐food sector but also offer valuable insights for other SMEs with limited financial resources and portfolio diversification in other sectors for anticipating related challenges.

Despite the increasing attention to innovation in emerging markets, there remains a dearth of studies that specifically examine how and when R&D support drives firm-level innovation through digital entrepreneurship. Utilizing time-lag data collected from 212 firms in an emerging market using digital platforms, the study examines the impact of R&D support on product innovation through the mediating role of digital entrepreneurship. Our results indicate a positive intervening role of digital entrepreneurship in R&D support and product innovation relationship. The findings contribute to the product innovation and digital entrepreneurship literature by highlighting the mechanism through which R&D support yields greater product innovation outcomes.

This study addresses the role of national culture in shaping hackathon teams' ideation outcomes. Drawing on the innovation and creativity literature and Schwartz’ theory of cultural value orientations, we propose that hierarchical values decrease the quality of ideas that teams develop over the course of a hackathon and that intellectual autonomy and mastery improve it. Using archival data, including pitch presentations from an international hackathon and data on cultural value orientations, we compiled a sample of 308 teams to investigate the influence of cultural value orientations and employed linear mixed‐effects regression analysis to test our hypotheses. We found that hierarchical cultural values are negatively associated with the quality of ideas, which suggests that hackathon teams that operate in such cultures suffer from a “liability of hierarchy.” We also found that teams from societies that emphasize mastery of the natural and social environment are more likely than other teams are to develop high‐quality ideas to tackle the (grand) challenges that hackathons address. We found no relationship between intellectual autonomy and idea quality. The study findings support the notion that culture manifests in hackathon teams' behavior and so shapes the quality of ideas they develop, thus laying the foundation for success or failure.

Research on innovation policies has primarily focused on their immediate effects on shaping firms' innovation strategies, often overlooking their long‐term impacts. Drawing on the imprinting perspective, we proposed the concept of the policy imprint and investigated its influence on firms' subsequent innovation strategies through a survey of 1080 innovative enterprises in China. Using a multiperiod regression discontinuity design (MRDD), our analysis reveals that firms founded under different innovation policy regimes exhibit distinct policy imprints. These imprints significantly shape their subsequent innovation strategies, including innovation investment strategies, business‐level innovation strategies, and corporate‐level innovation strategies. Our findings provide theoretical contributions by identifying the policy imprint in the transition economy, as well as its complementary role in the strategic stability under a dynamic environment. Furthermore, practical implications for enterprise managers and policymakers are highlighted by our study.

The feasibility of ecosystem‐level business model alignment by focal firms depends on whether it can make meaningful changes in content, structure, and governance to obtain widespread recognition from participants. How does this alignment and sensemaking process work? We design a multicase study based on four Chinese manufacturing companies to propose a comprehensive perspective on the ecosystem‐level business model alignment process. We find that business model alignment at the ecosystem level involves three key components: Content alignment to promote mutual adaptation between internal and external businesses, structural alignment to promote an interdependent and coordinated structure for actor interactions, and governance alignment to balance focal control and actor relationships. We also find that the effectiveness of ecosystem‐level business models depends on the focal firm's sensemaking around these alignments: Interpreting to facilitate actors' understanding of the business model, monitoring to evaluate the implementation of the business model, and repositioning to facilitate the ongoing alignment of the business model. Our work contributes to the existing literature while providing managerial insights for practitioners.

This study adds to the previous literature on outbound open innovation (OI)—that is, external knowledge commercialization activities—by exploring the effects of “make and/or buy decisions” on outbound OI. Notwithstanding the critical role of outbound OI in shaping firms' competitive advantages, there has been a notable gap in research regarding the drivers of outbound OI. Drawing on the knowledge‐based view, this empirical paper addresses this research gap by exploring an array of identified determinates of outbound OI. Through analyzing 468 New Zealand firms, we found that larger and more established firms show a stronger connection between research and development (R&D) investment and outbound OI, whereas smaller firms benefit more from external knowledge sourcing. Additionally, inbound OI positively affects outbound OI, yet the effect diminishes with more international collaborations. Interestingly, small and medium‐sized enterprises (SMEs) favor formal appropriation strategies, such as patents and contracts, while larger firms prioritize informal methods, such as secrecy.

This study investigates the impact of digital technologies on firm radical innovation and explores the mediating mechanisms of knowledge transfer and knowledge co-creation. Utilizing a sample of 152 high-technology entrepreneurial firms, we present compelling evidence that digital technologies positively influence the radical innovation of these firms. Furthermore, our analysis reveals that knowledge transfer and knowledge co-creation serve as critical mediating mechanisms, elucidating how digital technologies affect firm radical innovation. These findings significantly contribute to the existing literature by bridging the gap between research on technology adoption, knowledge management, and firm radical innovation. By highlighting the role of digital technologies and the underlying knowledge processes in firm radical innovation, this study enhances the understanding of the dynamics involved in fostering innovation within entrepreneurial contexts.

Using dynamic capabilities theory, this study investigates how the reconfiguration of a firm's technology portfolio influences its performance. Analyzing data from S&P 500‐listed firms (an unbalanced panel of 587 firm‐year observations) in the ICT industry, we identify an inverted U‐shaped relationship between such reconfiguration and performance. We also find that this relationship is moderated by entrepreneurial orientation. Specifically, the positive impact of technology portfolio reconfiguration on firm performance at relatively low levels of reconfiguration and the negative impact at relatively high levels are both more pronounced in firms with high levels of entrepreneurial orientation than in those with low levels. However, we do not find evidence that market dynamism moderates this inverted U‐shaped relationship. These findings form a significant contribution to the body of knowledge on technology portfolio management and organizational change.

In the rapidly evolving technological landscape, effective Research and Development (R&D) investments are critical for companies aiming to maintain competitiveness. This paper examines the dynamic adjustments of R&D investments in firms, with a focus on the role of political connections. We analyze a dataset of Chinese manufacturing firms from 2010 to 2019, employing a partial adjustment model to assess how these firms align their R&D expenditures with optimal targets. Our findings reveal that politically connected firms, while still falling short of their targets, demonstrate a significantly faster adjustment speed compared to their non‐connected counterparts. This advantage is primarily attributed to enhanced access to government subsidies and reduced costs of debt and equity financing. This study provides valuable insights for policymakers and firms in developing countries, elucidating how political relationships can shape innovation strategies and outcomes.

According to the silo mentality theory, companies are reluctant to share data between organizations. This study explores the reasons for this corporate behavior. To gain empirical insights, we conducted 42 semi‐structured interviews with the chief executive officers (CEOs) of German small‐ and medium‐sized enterprises (SMEs). Not only can the CEOs of SMEs control their private data, but they are also gatekeepers for business decisions, such as corporate data sharing. Following grounded theory, we identified four factors that influence data sharing. (1) Data characteristics —CEOs perceive social and financial data as sensitive in both private and corporate contexts. Furthermore, CEOs perceive additional types of corporate data as critical and are generally more skeptical of data sharing because of the complexity of data security. (2) Relationships via platforms— companies are often forced to participate in platforms, despite preferring long‐term personal relationships. (3) Competition —platforms enable easy and rapid product comparison. SMEs want to avoid transparency and fear that platform providers may compete for specific products. (4) Individual motivation —increased visibility among potential customers is an important incentive for participating in platforms, although CEOs perceive such participation to be time‐consuming. The findings extend the theory of silo mentality by indicating that the theory is not only relevant in the intra‐organizational context but also in the inter‐organizational context. Finally, we provide three propositions for future research.

Innovation ecosystems (IE) are increasingly regarded as important vehicles for creating value from complex value propositions and addressing grand challenges through the development of a circular economy (CE). While current research emphasizes that inter‐organizational relationships can facilitate transformation toward a CE, this study enhances our understanding of collaboration in ecosystem emergence. We conducted an 18‐month ethnographic case study of an IE aimed at developing data‐driven CE solutions within the German automotive industry. This study sheds light on ecosystem dynamics by examining how the roles of partners within an IE evolve during the highly volatile emergence phase to maximize value creation. We uncover two role dimensions that differ in their temporal dynamics and offer an integrative process model of role evolution. Our study thereby contributes to the literature on role theory and CE ecosystems by outlining how partner firms collaborate in IEs to develop data‐driven CE solutions.

This study explores how the use of a standard‐based Innovation Management System approach influences the legitimacy for innovation management—a management discipline often subject to innovation fads and fashions. Utilizing neo institutional theory as a lens, we explore how this approach increased legitimacy for innovation management in case studies of two large organizations, and how this in turn affected innovation activities. Theoretically, we contribute by adding construct clarity to the concept of legitimacy, in relation to management systems, and by increasing understanding of the role of legitimacy in innovation activities. Managerial implications include the potential use of an Innovation Management Systems Standard to create a common language for innovation, to systematize innovation efforts and improve the perceived seriosity of innovation management, which in turn enables more robust and continuous innovation efforts in organizations.

This work aims to clarify the role of intermediate imports on the innovation performance of non‐multinational enterprises (non‐MNEs) by examining the geographic proximity and diversity of international suppliers. Firstly, it has been argued that importing from nearby suppliers will contribute more to innovation performance than distant suppliers. Secondly, it is postulated that importing from several foreign suppliers will contribute more to innovation performance than importing from only one supplier. The analysis was conducted in the country of Spain, where, as in many other developed countries, intermediate imports have registered an upward trend in recent years. Using the ESEE (Spanish Survey on Business Strategies) database from the period 2006 to 2018, a joint analysis of product and process innovations was conducted. The empirical findings of 2000 Spanish non‐MNEs support the theoretical arguments. The results highlight the relevance of studying both product and process innovations and the importance of knowing their causes to improve innovation performance. Moreover, the results provide a basis for understanding the importance of geographic location when choosing foreign suppliers.

We investigate an important platform‐based technological innovation—equity crowdfunding syndicates—where crowd investors ( co‐investors ) use online platforms to co‐invest with lead investors in the form of syndicates into innovative startups. We concentrate on lead investors and what drives their success in drawing crowd investors to co‐fund innovative startups. Based on conceptualizing internal and external social capital, we investigate the effects of lead investors' social capital developed inside and outside the crowdfunding platform on their fundraising success. Using data from a sample of 178 individual lead investors on AngelList, we find that internal social capital is, as predicted, positively associated with lead investors' fundraising success. Surprisingly, the joint use of internal and external social capital will harm lead investors' fundraising success. This paper contributes to the debate on the role of social capital in crowdfunding and innovation management more generally by unveiling its competing effects and complex nuances as part of a crowdfunding investment strategy.

This article explores the role of digital technologies in innovation ecosystems. Using the systematic literature review (SLR) technique, we have reviewed and analyzed 71 articles published in major innovation journals. Our review was conducted using a comprehensive search strategy, to identify, select, evaluate, and synthesize pertinent literature on this topic. The findings of this review are categorized into three main sections: i) quantitative descriptive analysis-highlighting existing research profile, ii) thematic content analysis-delineating extant literature into key streams and presenting a comprehensive synthesis, and iii) critical analysis-highlighting knowledge gaps in the current literature and to set a future research agenda by developing specific research questions. A key contribution of this review is the development of a synthesized framework that provides a bird's eye view of the scholarship at the intersection of digital technologies and the innovation ecosystem. The findings of this article provide novel insights into how digital technologies can be effectively used to support innovation ecosystems, as well as the challenges that need to be addressed to fully realize their potential.

The circular economy is a new sustainability paradigm and a major driver of innovation in industrial firms. Digital servitization, enabled through smart products and their embeddedness in Internet of Things networks, represents a significant lever to generate product life cycle information and achieve collaboration between actors in the value cycle. Empirical studies on how product-service system business models enable smart circularity are bourgeoning, but a gap exists regarding their microfoundations. Against this background, we adopt an activity system perspective to explore boundary-spanning and interdependent business model activities. We conducted a qualitative interview study in business-to-business industries, from which we derived a funnel framework of smart circular systems (SCS) that spans three layers of the activity system. This contributes to theory in three ways: First, we identify 20 distinct microlevel activities. Second, we explain their interdependencies by classifying them based on the product life cycle into smart use, smart circular, and cross-strategy activity sets. We also order these activity sets by their data transaction frequency , environmental and economic value, and a firm's typical learning pathway, as well as link them back into circular product design. Third, we highlight increasing servitization to develop the activity system across multiple circular activity sets. Managers can use the funnel as a template to drive circular business models on multiple levels, from adopting individual activities to redesigning the entire activity system.

Firm innovation strategy (FIS) is crucial for new product development (NPD) performance. Few studies have revealed how the FIS that recognizes the importance of supply chain (SC) resources can improve NPD performance through SC management. This study emphasizes the mediating role of supply management, including innovativeness in supply management and firm‐supplier relationship. We argue that supply chain transformational leadership (SCTL) moderates the relationship between FIS and supply management. Using data from 232 Chinese manufacturing firms and applying structural equation modeling and regression analysis, we tested the hypotheses. The results show that innovativeness in supply management and firm‐supplier relationship mediate the relationship between the FIS and NPD performance. SCTL positively moderates the influence of FIS on supply management. These findings contributes to NPD outcomes. This study offers theoretical and empirical insights into SC management.

Disruption and uncertainty are distinct but related concepts with fundamental impact on firms' R&D. Management of R&D under disruption and uncertainty has become a critical issue in innovation management. With the advent of the fourth industrial revolution, firms are increasingly facing disruptions along multiple dimensions: technological, market, environmental, and institutional. Such disruptions increase the level of uncertainty firms perceive, bringing about both challenges and opportunities. What will be the impact of such disruption and uncertainty on firms? How can they navigate and mitigate its consequences? In this special issue, we present seven research articles and one commentary that address different aspects of R&D management under disruption and uncertainty in the context of a conceptual framework describing how firms might address different types of disruption and uncertainty through an open innovation system approach.

The paper aims to contribute to the debate on open data and public open innovation policies by focusing on hackathons as initiatives supporting value creation, innovation, and regional development. The paper refers to open data hackathons as a powerful open innovation tool to activate mechanisms of collaboration and collective intelligence within a regional ecosystem populated with data and a plurality of stakeholders. Despite the actuality of the issues and the large consensus around them, their integration in a consolidated theoretical framework is still far from a full achievement and requires additional contributions. Therefore, a theoretical framework has been developed for defining the research gap and addressing the development of an exploratory qualitative study carried out on OpenTusk, an open data hackathon promoted by the Department of Economic Development of the Apulia Region (south Italy) in the frame of a participatory public policy aimed at exploiting the value of regional open data. Findings demonstrate that the hackathon can create positive conditions for the preliminary exploration of the entrepreneurial value of open data by shaping several thematic areas of interest for the regional agenda of smart specialization. Furthermore, the case suggests that the effectiveness of an open data hackathon derives from an articulated strategy consisting of sensitization campaigns and preparation activities useful to stimulate the development of entrepreneurial ideas. Implications for theory and practice have been synthesized in the conclusion in terms of areas for future investigation and practical contexts of applications.

Users are an important source of innovation. Scholars suggest that established firms can gain product‐related insights by working with user communities and studies documenting various ways of working with users, as well as managers' interest in doing so. However, the link between working with user communities for product development purposes and its value for firms is not established. Coupling the use of event study methodology and regression analysis, I examine stock market reactions to corporate announcements stating that the firm is contributing software code to the community. I find that when firms state that generating insights from users regarding new and improved features and functionality is a motivation for contributing code, the market's reaction to the announcement is greater than for announcements that do not state this goal. Additional analysis provides evidence supporting the hypothesis that firms can and do benefit by working with user communities and achieve increased R&D efficiency, which leads to greater firm value.