This study investigates barriers to advanced servitization in the offshore equipment industry through a qualitative single-case study of a global supplier transitioning from a product-centric to a more service-oriented business model. Drawing on ten semi-structured interviews and secondary company data, the study examines how such barriers manifest in a context characterized by high product complexity, low standardization, low sales volume, and high operational risk. The findings show that, while many barriers resemble those identified in prior servitization research, they become particularly severe and mutually reinforcing in offshore settings. Financial risk, product heterogeneity, and organizational fragmentation emerge as central constraints on performance-based and lifecycle-oriented service models. By developing empirically grounded propositions, the study extends servitization research by identifying important boundary conditions for advanced servitization and showing how its viability depends on the alignment between service ambitions, product characteristics, and organizational readiness.

Distribution system operators are facing increasing peak loads as electrification and renewable energy integration accelerate, necessitating transitioning to a smarter, more flexible grid management. This systematic review explores how emerging technologies, specifically artificial intelligence and digital twins, can optimize grid capacity by improving flexibility management. Following PRISMA guidelines, the review synthesizes evidence from 61 peer-reviewed articles focusing on AI-driven forecasting and digital twin-enabled decision support. By prioritizing empirical research, this study addresses practical grid management challenges due to integration of distributed energy resources like electric vehicles, prosumers, heat pumps, data centers and energy storage. The findings highlight technological optimization as a faster, more sustainable approach to investment-heavy and carbon-intensive delayed physical grid expansion, with hybrid deep reinforcement learning integrated, federated digital twins emerging as a frequently proposed approach for advanced flexibility management. The review synthesizes evidence to inform a strategic roadmap for transitioning toward self-healing, proactive energy innovation ecosystem.

In today's rapidly evolving world, engineering graduates increasingly need to complement technical proficiency with the ability to identify opportunities, design impactful solutions, and navigate innovation ecosystems. This paper presents an experiential framework for embedding entrepreneurship and technology innovation into undergraduate engineering education through a mobile app design module using Figma as a rapid prototyping tool. Implemented in a first-year Engineering Skills & Ethics course at Qatar University, the initiative reimagines the traditional design project as a mini-startup experience. Multidisciplinary teams identify societal or sustainability-driven problems, ideate solutions, and build clickable app prototypes supported by Lean Canvas modeling. The seven-week pedagogy integrates design thinking, stakeholder-focused design, and entrepreneurial reasoning through structured phases: problem discovery, ideation, user journey mapping, interface design, prototyping, validation, and final pitching. Students assume startup roles (e.g., CEO, CTO, CBO, CSO) and use Figma to communicate usability, value, and feasibility. Assessment emphasizes design quality, innovation, teamwork, and ethical relevance, aligned with ABET outcomes.

The transition from linear to a circular economy (CE) is essential to address environmental challenges such as resource depletion, waste generation, and biodiversity loss. This shift necessitates that CE related innovation is adequately supported and incentivized. Intellectual Property Rights (IPRs) can be considered an institutional mechanism that can serve this purpose, however its role is not straightforward. Drawing on institutional theory, this study analyzes how regulative, normative, and cognitive pillars connect with the 3Rs: repair, reuse, and recycling. Using qualitative content analysis of expert interviews, supported by literature and patent data, the findings reveal significant institutional misalignment. While recycling benefits from strong regulatory support, with IPRs incentivizing investment in circular technologies, they also restrict innovation in repair and reuse. The study concludes that aligning IPR regimes with sustainability goals is critical to accelerating CE transitions and enabling more balanced innovation and diffusion.

Sustainability-oriented regulation is increasingly used to steer innovation, yet existing research largely treats policy as an external constraint or a system-level driver, offering limited insight into how firms strategically engage with regulatory environments. This paper introduces the concept of policy-enabled innovation to explain how firms leverage sustainability-oriented laws and policy mixes as inputs into innovation processes. Building on a conceptual synthesis of innovation management, innovation policy, and legal scholarship, the paper develops a firm-centric framework linking policy environments, firm-level capabilities, and translation processes. The framework explains how policy shapes opportunity spaces and why firms exposed to similar conditions exhibit different innovation outcomes. By reframing policy as a strategic resource, the paper contributes a micro-foundational perspective on the policy-innovation interface and provides a basis for future empirical research.

Electric vehicles (EV) adoption has accelerated rapidly over the past decade, driven by advances in battery technology, policy changes, and growing awareness of climate change. Lithium-ion batteries (LiBs) are central to this transition because of their high capacity, density, and long life span. However, several end of life (EOL) challenges arise as EV LiBs are typically retired at 70%-80% of their capacity, posing environmental and safety risks if not managed responsibly. Second life strategies, such as repurposing offer promising pathways to address these challenges and create additional value. This study employs a case study research design, using semi-structured interviews as primary data and peer-reviewed articles and grey literature as secondary data. It applies a systems method 'SPADE' adapted to the second life EV LiB context. SPADE provides a systemic framework to categorise stakeholders, identify problems, map value chain configurations and develop a typology of sustainable business models.

Disruptive Innovation (DI) has recently been a significant area of focus, with efforts being made to apply this concept by identifying disruptive technologies and predicting markets that may experience disruption. Two frameworks, viz., disruptive potential (DP) (Keller & Hüsig, 2009) and disruptive susceptibility (DS) by Klenner et al. (2013), have shown promise in this endeavor. This paper examines the applicability of the DP and DS frameworks in a new market where the major driver was not convergence: the US lighting industry, where solid-state lighting or LED-based lighting has disrupted the traditional lighting market broadly dominated by incandescent and fluorescent technologies. The DP framework demonstrated an accurate prediction of disruption, whereas the DS framework exhibited limitations. This paper also reviews past case studies involving the application of DS, outlines potential explanations for its challenges, examines its boundary conditions and offers recommendations for improving its future applications.

The COVID-19 pandemic deepened capability gaps across emerging economies, particularly in Africa. Organisations grapple with employees lacking fourth-industrial-revolution competencies and an innovation mindset, while social initiatives default to short-term relief with no pathway to self-sufficiency. This paper tells two real-world stories. The first draws on the author's experience as Innovation and Design Leader at TotalEnergies E&P Nigeria, where "what's in it for me" and "better together" principles connected upskilling to individual motivations, driving genuine behaviour change. The second and primary story is 5KFoodBank, founded in Nigeria in June 2024 following a March 2023 initiative for 5,000 destitute people. Through faith-based ecosystems, it delivers cooked meals, school snacks, and quarterly dry-staple distributions, leveraging relief as a gateway to skills acquisition, alternative education certifications, and training towards sustainable livelihoods. Across both contexts, a common model emerges, interweaving purpose-driven participation, ecosystem leveraging, and data-informed engagement to engineer readiness, not merely relief.

Extended Reality technologies, particularly Virtual Reality, are increasingly explored as tools in healthcare education, yet their integration into clinical training remains inconsistent and often lacks user-centered design. This case study describes the development and implementation of a VR-based training environment for delirium in nursing education within a hospital setting and outlines future application areas.The project followed a structured, theory-informed approach and was developed within the framework of an idea competition on XR applications in clinical practice. Delirium was selected as a high-impact use case. A participatory co-design approach based on the VIENNO model ensured involvement of nurses and clinical experts. The resulting VR training enables immersive, scenario-based learning and achieved strong user acceptance. Future applications include VR for second victim support, patient anxiety and pain reduction, and rehabilitation in physical medicine.VR represents a promising tool for nursing education and beyond, provided it is implemented through user-centered design.

The purpose of this study, which is in progress, is to explore the main network mechanisms that aid in transforming the Valley of Death' (VoD) into a 'Horizon of Hope' (HoH), which is rooted in strategic connections and resourcefulness. The study uses a systematic literature review to collect and synthesize knowledge on VoD-to-HoH transition networks, followed by semi- structured interviews with inventors, innovation managers and technology specialists to explore management strategies, critical factors and key challenges for VoD-to-HoH networks. Preliminary interview data analysis shows support for the user, research, and business networks captured by the literature, as well as the importance of governmental, institutional, investor, prototyping and communication networks. One main theme, concerning HoH validation accelerators that expedite innovation artefact approval processes, is emerging from the current data as well as codes surrounding trust focus and futuristic outlooks. Conceptual and methodological areas for feedback and development are also presented.

This paper examines technology transfer as a strategic enabler of sustainable development, focusing on the policy and practice conditions required for technologies to generate lasting impact. It addresses persistent inefficiencies in technology transfer, including fragmented policy frameworks, institutional misalignment, regulatory complexity and uneven absorptive capacities, particularly in developing and transition economies. Drawing on international case studies, the paper argues that successful technology transfer must move beyond transactional exchange towards integrated systems that align international cooperation, national regulation and local implementation capacity. It highlights the role of knowledge networks, public-private partnerships and inclusive innovation ecosystems in supporting this shift. Cases involving airborne synthetic aperture radar, drone technologies, data platforms and advanced sensing illustrate how digital innovations can support environmental monitoring, disaster response and infrastructure resilience when embedded in supportive governance structures. The paper contributes a holistic framework for policy coherence, capacity building and sustainable innovation.

This study explores how innovative firms embed innovation in their organisations. Using existing literature, the study postulates on an "embedded capabilities" theory that explains how firms ingrain innovation in a cycle for: (i) linking capacities, (ii) learning orientations, and (iii) legitimatising processes. Based on the cases of three Big Tech titans, Alphabet, Apple, and Microsoft, the study finds support for the theory in embedded innovation capabilities that emerge from collaborative, democratisation, divergent thinking, empowerment, open systems, and talent management philosophies. Underlying the development of these capabilities are four orchestration mechanisms: (i) co-functional structures and collaboration, (ii) co-extended models and initiatives, (iii) co-developed ecosystems and principles and (iv) co-evolutional leadership and cultures. Principally, this study adds to current understanding on how firm connect and continue to innovate by adding to knowledge on an embeddedness basis of innovation.

This article examines the social innovation ecosystems surrounding social impact businesses, focusing on a specific city in southern Brazil. It highlights the dynamic interactions between the various actors involved in solving socio-environmental problems, aiming to foster social and economic development through collaborative efforts and innovative solutions. The research is based on the activity of the Florianópolis Social Innovation Observatory (OBISF). The observatory serves as a collaborative mapping and monitoring platform based on "public research," transforming territorial experimentation into systematized knowledge and promoting dialogue between academia and communities of practice. The research explores the characteristics of social impact businesses in this region and their supporting ecosystems, addressing the pressing need to translate local experimentation into systematic knowledge that effectively tackles Brazil's socio-environmental challenges.

In today's transformative business environment, open innovation (OI) has become a prominent strategy to achieve long-term growth and competitive advantage. Considerable research has investigated the various OI models, yet collaboration models for corporate-startup co-creation are still not very well understood and are weakly managed, leading to frequent failures. This study addresses this innovation management problem by identifying the critical success factors of corporate-startup collaboration with a focus on platform-based co-creation. It centers around digital platforms provided by three major technology corporations: Google, Amazon, and Microsoft. Based on data collected from interviews with 10 start-up founders and co-founders in the Gulf Cooperation Council (GCC) region, four key themes were identified: learning curves and due diligence, industry standards and regulatory compliance, timely projects and precise utility, and advanced planning and goal orientation. These findings highlight the importance of proactive knowledge development, regulatory alignment, efficient project execution, and strategic foresight in co-creation processes.

Transforming place, destination or city branding into an innovation process is a topical innovation management problem with ramifications on tourism development. Yet, there is a paucity in research on developing measurements for city branding as innovation. This study aims to develop and validate a scale for measuring city branding as innovation with a view to supporting tourism development. Based on a cross-sectional survey with place branding, media and tourism experts in Kuwait, the study finds support for event, marketing and product dimensions of city branding as innovation. The study also finds statistically significant and positive relationships between city branding innovativeness and the different dimensions. Theoretically, the study advances a multi-dimensional model of city branding innovation based on creating positive city images and perceptions for tourists, visitors, investors and citizens. Managerially, the study supports strategic planning for smart and sustainable city innovation by identifying branding priorities for reforming and orienting cities.

This study aims to consolidate the fragmented academic literature on equity crowdfunding (ECF), with particular attention to its relevance for innovation management and the Brazilian context. Using a systematic literature review combined with bibliometric analysis, the study applies the PRISMA protocol to articles retrieved from Web of Science and Scopus, resulting in a final sample of 365 unique publications and an in-depth content analysis of the 40 most-cited studies. The results show sustained growth in ECF research since 2013, a strong concentration of influential authors and institutions in Europe and North America, and eight major thematic clusters, including signaling, governance, regulation, investor behavior, and platform dynamics. The study contributes by organizing the intellectual structure of the field, identifying theoretical and geographic gaps, and providing a foundation for future empirical research on ECF in emerging economies such as Brazil.

Small and medium sized enterprises (SME) increasingly rely on customer collaboration to support innovation, particularly in business-to-business (B2B) contexts where solutions must be adapted to complex and evolving user need. While many SMEs collaborate for exploring innovation, they struggle to convert this knowledge simultaneously to ensure exploitation into profitability. This paper examines how SME combines customer collaboration and market commercialization through a dual business model. Ambidexterity research stresses balancing exploration and exploitation but weakly explains dynamical integration. Drawing on a longitudinal case study in the chemical industry, the findings show that collaboration-based business models support opportunity exploration, co-creation and product adaption with selected customers, while market-based business models enable exploitation and efficient value capture. Cross-functional teams act as boundary mechanisms translating external customer interaction into internal interaction. The study contributes to innovation management research of customer collaboration by explaining how SMEs operationalize ambidexterity through practical arrangements rather than structural separation.

This study explores how a citizen-driven digital platform, supported by local government, can function as an arena for collaborative co-creation in a small-town context. Drawing on a qualitative longitudinal case study, the research analyses a place-based development process involving citizens, entrepreneurs, and municipal actors over time. The findings show that while the platform enabled idea generation and interaction, its effectiveness depended on its integration with formal governance structures and decision-making processes. Misalignments between entrepreneurial and public-sector logics created tensions that constrained implementation and collaboration. The study highlights the importance of orchestration, shared understanding, and institutional alignment in sustaining co-creation initiatives. It contributes to research on innovation ecosystems by emphasizing their context-dependent and processual nature, particularly in resource-constrained settings. The findings also offer practical insights for municipalities seeking to support citizen-driven innovation through digital platforms.

his paper presents a three-phase, mixed-methods study examining sustainability culture at a travel e-commerce firm operating under the structural tension of selling travel while pursuing environmental responsibility. Phase 1 applied a structured artefact review using the Sustainability Culture Assessment Framework (SCAF), which integrates models from Schein (2010), Cameron and Quinn (2011), and Visser (2011), producing Current Impact Factor (CIF) scores for seven cultural dimensions. Results placed the firm at the Aspirational stage across all dimensions, with the lowest scores in Incentives and Review (1.6-1.9) and Shared Values (1.6-1.7). Phase 2 combined a company-wide survey (n = 51) measuring aspirational enablement demand with eight semi-structured interviews. Survey dimension means ranged from 3.09 to 3.85 on a five-point scale. Interviews identified four themes: a structural business model contradiction, the primacy of senior leadership commitment, a capability gap in role-specific tools, and a preference for intrinsic over formal incentive motivation. Integrated analysis identified a High Willpower, Low Enablement condition. Phase 3 produced an Intervention Toolbox structured around a dual top-down and bottom-up Pincer Strategy with a 90-day implementation plan.

While emotions are central to hospitality experiences, the design of hospitality spaces still relies on intuition-driven decisions. The buffet breakfast, an emotionally charged and frequent guest touchpoint, offers a valuable context to examine how evidence-based design can enhance emotional responses. This research adopts a Living Lab approach and examines a case study in the breakfast restaurant of a four-star urban hotel in Barcelona, where a redesign intervention was developed based on the triangulation of guest emotional data, staff and stakeholder input, and evidence-based design principles. Results show that before the intervention, guests predominantly experienced disappointment, disinterest, and dissatisfaction. Post-intervention, neutral and satisfied emotional states arose and staff reported improved workflow and accessibility. The study demonstrates the feasibility of applying neuromarketing tools and emotional analytics in a real hotel setting and highlights the value of integrating guest- affective data with staff perspectives to inform special and service design.

This paper examines how different types of knowledge shape firms' eco-innovation intensity, conceptualized as a progression of environmental objectives ranging from regulatory compliance to holistic, organization-wide sustainability efforts. Using firm-level data from the 2016 Spanish Technological Innovation Panel (PITEC), the study investigates the influence of internal knowledge, science-based external knowledge, and practice-based external knowledge on four categories of eco-innovation: compliance-oriented, efficiency-oriented, impact-reducing, and holistic eco-innovation. The results show that internal knowledge is most strongly associated with lower-intensity eco-innovation, particularly process-based efficiency improvements that rely on operational experience and firm-specific routines. Science-based external knowledge provides stable but moderate support across all eco-innovation levels, offering analytical and technological inputs without becoming the dominant driver of higher-intensity eco-innovation outcomes. Practice-based external knowledge emerges as the most influential factor at advanced stages of eco-innovation intensity, especially for impact-reducing and holistic eco-innovations.

Emerging digital technologies, led by Artificial Intelligence (AI), introduce systemic ethical risks, algorithmic bias, and threats to user autonomy, that necessitate robust organisational governance. However, a persistent "implementation gap" exists between high-level ethical aspirations and their practical application within research workflows. This paper presents the design, implementation, and empirical validation of an ethical model specifically developed for a Research-Technology Organisation to bridge this gap. The model's development is based on a benchmarking exercise, a deep 19 semi-structured interviews, a specific use case based on a European project and a validation study covering 108 stratified R&D projects.The study shows that the model provides a structured and replicable approach to identifying, categorising, and managing ethical risks in digital innovation. The findings confirm that the model effectively identifies ethical risks without creating bureaucratic bottlenecks or obstructing technical innovation. Instead, it functions as an enabling element that strengthens researcher confidence and stakeholder trust.

This paper addresses the challenge of meaningfully exploring and anticipating eco-social and systemic impacts ex-ante and during innovation processes. It introduces the Prospective Impact Assessment Process (PIAP), developed as a transdisciplinary methodology responding to the need for cultural impact assessment. The paper presents analysis and results from applying PIAP in the Future DiverCities (FDC) project aimed at re-imagining culture-led urban regeneration. It contributed to artistic pilot objectives and project outcomes generating policy recommendations based on Theory of Change and co-created impact statements. The study suggests that PIAP differs from conventional impact assessments in its underlying logic of knowledge and value creation. Its contribution lies in combining strong empirical grounding with design-driven practices and Frame Innovation (Dorst, 2015). PIAP prioritises contextualised and experiential valuation of impacts through embedded assessment using storyboarding, the Futures Wheel and heat map analysis, making impact networks visible while preserving situational meaning.

Recent studies in innovation management emphasize combining openness and closure, yet how this balance is operationalized remains unclear, especially in university-centered ecosystems. This study examines how the transition from open exploration to collaboration is structured, based on the Open Principal Investigator Map (PI Map) and the Global Japanese Researcher Connectivity (GJRC) platform. The PI Map serves as an open interface enabling broad, non-exclusive exploration, expanding potential connections. These interactions are then refined through a multi-stage selection process, including screening and invitation, leading to focused, small-scale workshops for deeper collaboration. The findings show that dynamic open-close strategy is not a simple temporal shift, but a structured process linking open exploration with selective engagement. This study contributes by reframing the strategy as relationship design and offers practical insights for building sustainable co-creation platforms.

As AI increasingly shapes information ecosystems, concerns over its role in amplifying disinformation have grown. While existing research focuses on content-level risks, few studies treat disinformation as a systemic societal risk. This study addresses that gap by applying the Intergovernmental Panel on Climate Change (IPCC) risk framework to the domain of AI-driven disinformation across its three core determinants: hazards, exposure, and vulnerability. Hazards are operationalised through violations of foundational AI principles (e.g., accountability, and robustness) and disinformation mediums including text, video, and multimodal formats. Exposure captures the stakeholders and sectors affected, while vulnerability is conceptualised through nine distinct harm types, including psychological harm, physical injury, and economic loss. Drawing on 212 real-world incidents from the OECD AI Incident Monitoring database, the analysis reveals disinformation's systemic and interconnected nature, providing policymakers with a risk-informed roadmap for governance strategies.

This case study examines how innovation projects can be managed under conditions of extreme uncertainty, with a focus on strengthening the resilience of Ukrainian agri-businesses during wartime. It highlights the importance of continuous adaptation, rapid problem-solving, and value co-creation to sustain operations in highly volatile environments. Drawing on a broad needs assessment of agricultural actors, the study applies design thinking to identify key challenges and barriers, while the Fab City Full Stack framework supports global knowledge sharing combined with local action. A Swedish fabrication laboratory serves as a collaborative hub for testing solutions and enabling cross-border exchange. The study emphasizes challenges related to digital transformation and capacity building, while contributing to discussions on distributed innovation, resilience, and managing innovation in crisis-affected contexts.

This study analyzes the use of patents and clinical trials as indicators of innovation in the pharmaceutical industry. Innovation is presented as a complex and non-linear process, based on the interaction between multiple actors and the conversion of knowledge into practical applications. Drug development involves costly and risky steps, especially in clinical trials, which act as bottlenecks but also as collaborative networks and sources of continuous evidence. Patents, in turn, act as technological indicators and economic instruments, allowing for protection, value capture, and competitive advantage. The systematic review identified four main axes: innovation as a complex system, the role of knowledge, the economics of innovation, and the use of data. It concludes that the combination of patents and clinical trials offers a more complete view of the technological trajectory, highlighting gaps and opportunities for future research.

This paper presents the current status of the EU-funded VILinKRITIS project, which develops a Virtual Innovation Lab (VIL) to support co-creative innovation in safety-critical process industries within the critical infrastructure domain. Addressing the challenges of distributed expertise, strict regulatory requirements, and limited effectiveness of conventional virtual collaboration, the VIL is conceptualised as an immersive, browser-based VR environment. The research follows a design science research approach and reports on the first iteration of the VIL. We present preliminary results from a mixed-methods requirements analysis which informed the identification of initial design guidelines. These guidelines emphasise a browser-based solution, trust-centred AI integration and structured user onboarding. By enhancing shared understanding and engagement through shared boundary objects, the VIL aims to overcome key limitations of virtual collaboration and foster more effective co-creative incubation processes in highly regulated industrial contexts and provide a foundation for ongoing iterative development and evaluation.

This paper tackles the practical challenge of implementing a standardized Innovation Management System (SIMS) based on ISO 56001 in established organizations. Despite the fact that ISO 56000 series offers a common framework for managing innovation, organizations persistently falter to translate its requirements into a framework that can be implemented. Following an exploratory qualitative and intervention-based case study approach, this research advances and applies a stepwise implementation methodology within a real organizational setting. This research contributes to innovation management literature by providing an applicable guideline for ISO 56001 based-IMS implementation, offering valuable understanding for managers, practitioners, and researchers seeking to systematically manage innovation.

Background: Digital health solutions for chronic care are increasingly developed as complex ecosystems. However, empirical evidence on how governance translates into sustainability remains limited, as research often overlooks organizational and economic dimensions. Objectives: This study examines co-creation as a governance mechanism to simultaneously achieve clinical effectiveness, operational efficiency, and sustainability. Methodology: A mixed-methods case study was conducted on SIDERAb, a telerehabilitation ecosystem. The analysis integrates qualitative data from co-creation workshops with quantitative evaluations, including Activity-Based Costing and Budget Impact Analysis. Results: SIDERAb achieved clinical effectiveness equal to or higher than traditional pathways. Economic results showed annual savings of EUR0.67 million for a reference hospital and over EUR14.8 million for the Regional Health Service. Conclusions: Co-creation acts as a structural governance mechanism that aligns stakeholder interests and embeds sustainability into ecosystem design, enabling value creation in complex healthcare settings.

Literature on academia-practice knowledge transfer showed that researchers use active and/or passive channels. It also showed that several factors might be influential on the intensity of use of these channels by the researchers. The aim of this paper is twofold: (i) to assess whether active and passive knowledge transfer by Canadian agricultural researchers are complementary, substitutive, or independent; and (ii) to identify their common and specific determinants. Findings indicate a complementary relationship between active and passive channels. Several shared determinants shape both forms, including academic performance, motivation to apply knowledge, social capital, university culture, seniority, and institutional reputation. Distinct drivers also emerge: service-oriented motives and time investment are associated exclusively with active transfer, whereas reputation-driven motives and public funding influence only passive transfer. These findings refine understanding of knowledge transfer mechanisms and inform policies aimed at enhancing research diffusion in the agricultural sector.

As cyber threats grow in scale and complexity, cybersecurity can no longer be reduced to a technical function. This paper argues that cyber ranges, controlled simulation environments traditionally used for training, can be reconceptualized as innovation platforms capable of driving cybersecurity capacity building at the ecosystem level. Drawing on an exploratory qualitative case study embedded in a Canadian university cyber range initiative, the paper extends the operational model by introducing an explicit innovation layer structured around three functions: data and knowledge valorization, experimentation and applied research, and ecosystem orchestration. Three key learning mechanisms and governance dimensions are identified as enablers of cross-organizational coordination and collective intelligence. The findings support a shift from a capability-centric toward a platform-centric view of cybersecurity innovation, where value emerges from dynamic interactions among infrastructures, actors, and governance structures within multi-actor ecosystems.

Public funding supports firms' R&D and innovation, often promoting collaboration with Research Institutions (RIs). However, evidence on how collaboration affects different innovation stages is mixed. This paper analyzes 198 firms involved in publicly funded R&D projects in Italy, examining the relationship between firms' collaboration with RIs and three outcomes: patenting, prototyping, and transfer to production. Results show that collaboration is positively associated with prototyping and, to a lesser extent, patenting, especially for SMEs. However, it is negatively associated with transfer to production, indicating challenges in commercialization. These findings suggest a stage-dependent effect: firms' collaboration with RIs benefits early innovation phases, but may hinder downstream outcomes. The study highlights a potential trade-off in collaborative innovation and offers policy and managerial insights for designing more effective R&D support instruments.

This paper looks back at the origins of 'innovation management' (IM) as a field of study, arguing that it represents a convergence of at least three important streams of thought. It shows how IM has moved centre stage to a point where understanding how ideas can create social and commercial value and drive growth are increasingly seen as 'life skills' and form part of the policy discourse in bodies like the European Union. This makes the role of higher education institutions increasingly relevant as key centres for enabling their development. The paper explores current challenges in the world of IM pedagogy in terms of design and delivery, curriculum development, assessment and skills capture and, in particular, the implications of generative AI for the future of the field.

Medical schools represent one of the most regulated and scrutinised educational environments, yet institutional responses to artificial intelligence have been predominantly reactive. Drawing on the history of AI and on innovation management principles, this paper argues that a proactive, strategically guided approach yields better outcomes for educators and learners alike. We present a decision-support matrix that maps educational tasks against AI capabilities, enabling institutions to identify where AI augments learning most effectively. We further draw on Alan Turing's distinction between the educator who teaches and the engineer who builds, arguing that educators need not master machine learning to use AI well. Together, these instruments address both the paralysis of unfamiliarity and the risk of uncritical adoption.

Innovation ecosystems (IEs) are widely used to explain collaborative value creation, yet their empirical operationalization remains fragmented between two dominant perspectives: ecosystems-as-structure and ecosystems-as-affiliation. This paper proposes a unified, data-driven framework that reconciles these perspectives through a multi-layer network approach anchored in the notion of orchestration space. Using graph theory, we model affiliation ties (shared memberships and institutional connections) alongside structure-based interdependencies derived from co-participation in collaborative innovation projects. Applied to the Eurasanté health ecosystem in Northern France, the framework demonstrates how each perspective captures distinct dimensions-relational breadth versus effective collaboration-and how their integration reveals otherwise hidden dynamics. The combined analysis uncovers differentiated actor roles, a pronounced core-periphery structure, and significant gaps between formal affiliation and actual collaboration. By systematically aligning and cross-analyzing both layers, the study advances a replicable methodology that strengthens ecosystem delineation, improves analytical robustness, and provides actionable insights for ecosystem governance and strategic orchestration.

The transition to a sustainable energy and mobility system requires extensive infrastructure changes. Lately, electricity grids have been exposed to increasing challenges created by generation volatility and the deployment of large loads such as electric vehicles (EVs). Hence, maintaining stable and resilient grid operations has become difficult, often preventing the connection of new loads and renewable energy generators in ageing grids. This paper systematically reviews strategies for EV charging management and infrastructure deployment that support grid integration in non-residential contexts. The review found extensive efforts to reduce harmful operational impacts of high-power charging on electricity grids. However, the literature only weakly addresses the connectivity of non-residential charging infrastructure, and the implications of generation-integrated charging concepts for grid connection requirements are rarely discussed. Beyond engineering-focused research on operational optimisation, alternative approaches to improving connection efficiency could be investigated, for example through regulatory and processual optimisation of grid connection management.

Innovation foresight is strategically critical yet resource-intensive, limiting its adoption especially among smaller firms. This study examines which stages of the foresight process generative AI can substitute for expert-driven foresight without compromising quality, and with what cost-time trade-offs. We conducted an end-to-end innovation foresight process for a multinational garden equipment firm, comparing outputs from a professional human expert team against those of AI models (ChatGPT, Claude, Copilot-Premium, Copilot-Standard) under two prompting conditions. Four independent expert judges evaluated all outputs blind using stage-specific quality criteria. Results reveal a stage-dependent pattern: AI achieves quality parity with human experts at trend identification and innovation field stages, while humans substantially outperform AI at the scenario development stage, with the largest effects on novelty and organizational specificity. These quality differences must be read alongside dramatic efficiency gains: AI completed the process saving 98.70% of time and 99.27% of cost.

In emerging markets, growth stories often begin with a non-negotiable mission rather than forecasts and predictions. This paper reframes entrepreneurship through the lens of values that provide a normative compass aligning strategy, experimentation, and everyday practice. Drawing on a case study of Property Finder, we show how resilient scaling emerges from effectual action-starting with available means, learning through experiments, and building partnerships-while remaining coherent with the mission to simplify the home-finding journey. Rather than treating uncertainty as a planning problem, Property Finder approached it as a design space, using values to decide what to try, what to stop, and how to define success beyond short-term metrics. The result is coherent adaptation: a development pattern that enables innovation without losing strategic direction. For researchers, the paper illustrates how normative commitments shape entrepreneurial decision-making. For founders and executives, it offers a leadership logic for governing exploration and long-term growth in emerging contexts.

Living Labs (LLs) have gained prominence as a collaborative approach to innovation in real-life contexts. However, empirical evidence remains fragmented and conceptual clarity limited. This study addresses this gap by identifying core LL characteristics and drawing on complementary literature to strengthen methodological rigor and outcome evaluation. Building on research in innovation ecosystems, Business Model Innovation, and design-based approaches, LLs are conceptualized as multi-layered systems involving multiple stakeholders, multiple collaborations, and multiple real-life contexts. Action is identified as the central integrative mechanism enabling alignment across layers under conditions of uncertainty. The findings suggest that rigor in LL research emerges from flexible, participatory, and context-sensitive approaches rather than standardized methods. Value creation is framed as a multi-dimensional construct encompassing instrumental, moral, and intrinsic dimensions. The study provides a cross-disciplinary framework to enhance methodological rigor and evaluation in LLs.

Public innovation intermediaries are widely used to stimulate radical innovation, yet evaluation systems rely on short-term output metrics that fail to capture whether participating organizations develop durable capabilities. This research-in-progress investigates how intermediary process designs in the Swiss Innovation Boosters (IBs) build radical innovation capacity (RIC). Integrating dynamic capabilities, problem framing, and ecosystem orchestration theory, we analyse data from 17 IB programs (2021-2025), including 40+ interviews and survey data from 160+ participant companies. Preliminary findings identify four capability-building mechanisms: (1) challenge-first framing broadens opportunity search; (2) high-quality user-learning loops drive experimentation value; (3) partner diversity raises novelty only when governance quality is high; and (4) capability transfer is heterogeneous, varying by organizational intent and prior capability. We contribute an integrated mechanism model linking intermediary process choices to RIC development and specify boundary conditions explaining differential outcomes.

Since the introduction of the Dynamic Capabilities (DC) concept, it has been widely used to explain asset reconfiguration at the firm level, including the diffusion of innovation. This article investigates how DC extend beyond firm boundaries to enable ecosystem-level orchestration and innovation diffusion. It develops a framework that translates five key orchestration practices: ecosystem design, relational alignment, resource integration, technological leveraging, and innovation practices, into an ecosystem-level structure aligned with the core DC activities of sensing, seizing, and transforming. Building on an ecosystem-based perspective, these practices are conceptualized as strategic routines enacted by an orchestrator to coordinate hierarchically independent actors within an innovation ecosystem. The combination of these routines enables the orchestrator to define a shared value proposition, mobilize complementary resources, and facilitate collective asset reconfiguration. By bridging firm-level capability logic with ecosystem-level orchestration, this article provides a theoretical foundation for understanding how innovation diffuses within ecosystems.

This study examines open hardware adoption in user innovation communities through an extended UTAUT2 model. Drawing on experiential learning and free user innovation, it adds Educational Value and Recognition Benefits to the core constructs of performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, and habit. Data from 76 respondents in open hardware communities were analyzed using PLS-SEM. The initial results show that performance expectancy, effort expectancy, and educational value significantly predict behavioral intention, with performance expectancy emerging as the strongest driver. The findings suggest that practical usefulness, ease of use, and learning-related benefits for potential adopters are central to open hardware adoption, whereas reputational motivations appear less important for initial adoption. The study contributes a quantitative, theory-driven model of open hardware adoption and offers guidance for design, education, and community support.

We conduct two in-depth cases studies of two social enterprises that provide employment to people from low income, marginalized communities in India based on 34 interviews and secondary data. We analyse how the social enterprises manage the ongoing process of institutional translation towards customers and producers and how they deal with translation problems. We observe an interplay between persuasive and performative institutional translation with persuasion being more relevant to customers and performance being critical to producers. When larger barriers, e.g. differences in culture, knowledge and power, need to be overcome, institutional translation becomes a bi-directional process resulting in the social enterprise evolving. Tensions arise as narratives used in institutional translation towards customers and producers differ significantly, which explains some of the tensions observed in hybrid organizations.

Business schools aim to prepare graduates for the "real world" by focusing on leadership, growth, and competitiveness. However, many challenges in practice, such as sustainability transitions and supply chain disruption, require navigating uncertainty, interdependence, and judgement that traditional classroom teaching struggles to develop. This study examines a nature-based, place-based pedagogical experiment in a UK business school, exploring how such approaches prepare students for these realities and what institutional conditions shape their effectiveness. Using an interpretive qualitative case study of 35 semi-structured interviews with staff, students, and alumni, alongside observations of outdoor workshops and student reflections, we find that outdoor learning can create moments of disruption that help students engage with complexity, build systems-level awareness, and rethink managerial assumptions. However, these benefits are uneven and constrained by assessment practices, timetabling, and dominant academic norms. We argue that rethinking where and how management education occurs is essential for addressing contemporary organisational challenges.

It is still unclear how organizations can learn to create innovative solutions for the circular economy. This paper examines how leader-employee relationships foster circular economy innovation (CEI) using Leader-Member Exchange (LMX) and Double-Loop Learning (DLL). Findings from 24 semi-structured interviews, participant observations, and secondary documents collected from six organizations pursuing circular initiatives show that leader attention, recognition, and support build trust and psychological safety among employees. Such conditions allow employees to reflect critically on assumed routines, test alternative circular practices, and reframe problems, thereby activating DLL. DLL then transforms into CEI outcomes including increased resource efficiency, proactive problem-solving, and novel circular solutions. We present a relational microfoundations model of how LMX channels DLL into tangible circular economy innovations.

SMEs increasingly engage in public-private innovation to address public-sector challenges, yet many struggle to commercialize and gain traction in public markets, especially in their first entry. This study explains how SMEs learn over time in these collaborations through a longitudinal process study of ten Danish healthcare innovation projects. Applying a process study, we uncover what SMEs learn (across solution, public-context, and commercialization domains), how learning is activated through recurring trigger moments (observation, interaction, testing/prototyping, translation work, and internalization), and four temporal learning trajectories through which these triggers cluster over time (exposure, iterative development, institutional alignment, and organizational anchoring). The findings reveal a hybrid temporality in which rapid solution reframing coexists with slower institutional work related to procurement, compliance, evidence, and documentation. Notably, early translation of public-sector requirements and internal anchoring are core for advancing commercialization. Recognizing these mechanisms can guide SMEs and practitioners to prioritize key activities for success.

This case examines how resistance to adopting AI-enabled point-of-care diagnostics in healthcare can be overcome through an Open Innovation 2.0 (OI2) Living Lab and Design for Adoption approach. Using a quadruple helix collaboration, SME Heartpath partnered with Maynooth University and an Irish health insurer Irish Life Health to pilot advanced AI-based screening for technology executives in a non-hospital setting. The initiative applies the "Stay Left, Shift Left - 10X" (SL2-10X) paradigm, delivering diagnostics that are 10 times earlier and at significantly lower cost compared to traditional hospital-based care. The project integrates AI-enabled tools-including VO2 max assessment, point-of-care blood testing, and an AI stethoscope-within a digitally supported care pathway. Results demonstrate strong adoption and improved health insights, highlighting the effectiveness of low-risk, user-centred innovation strategies. The case illustrates how SMEs/Universities, supported by ecosystem partners, can rapidly deploy transformative digital health solutions while advancing prevention-focused, personalised healthcare and accelerating system-wide innovation.

Accelerating deep-tech industrialization is critical for future European prosperity and essential in the raw materials sector for meeting European raw materials sovereignty objectives. Practitioners need to understand which systemic design factors can be leveraged to accelerate deep-tech industrialization and overcome the systemic misalignments that cause breakthrough technologies to stall during the transition from laboratory research to industrial scale - a phenomenon known as the "Valley of Death". However, existing Innovation System research offers descriptive typologies but lacks prescriptive guidance, while Technology Transfer research reduces the systemic environment to a passive constant. This study develops a validated taxonomy of 14 systemic design factors for accelerating technology industrialization across six dimensions, following a Design Science Research approach. The taxonomy is grounded in systematic literature analysis and validated in six expert interviews with senior innovation managers from mining equipment manufacturers, providing prescriptive groundwork for TRL-sensitive ecosystem management.

This study investigates innovation and sustainability barriers in manufacturing SMEs in Western Paraná State, Brazil. Data were collected via Likert-scale questionnaires from 25 companies across seven sectors and analysed using descriptive statistics and a correlation matrix. Findings reveal that political/economic uncertainty and high initial costs are the primary innovation barriers. Sustainability efforts are mainly hindered by difficulties in measuring financial return and regulatory challenges. Notably, barriers fluctuate based on sector and company size; for instance, micro-enterprises are more sensitive to costs, while medium-sized firms struggle with regulations. The analysis identifies significant correlations between financial constraints in both areas. These results contribute to regional literature and provide a basis for public policies and private strategies aiming at mitigating the obstacles, ultimately supporting the competitive and sustainable development of the regional manufacturing industry.

Circular Economy and Energy Systems have emerged as two prominent and increasingly debated research domains over the last decade. Although these research domains have generally evolved along parallel trajectories, an emerging body of literature reveals interesting relationships between them. These relationships suggest the need for a unified conceptual framework capable of capturing the dynamics of Energy Systems through the lens of Circular Economy, or vice versa. Building on this premise and through a systematic literature review, this paper investigates the relationships between Circular Economy principles and Energy Systems characteristics, aiming to advance the conceptual framework of Circular Energy. The study frames Circular Energy as a system-level concept that goes beyond energy production and transition, focusing instead on the circularity of energy flows. The proposed framework highlights the mechanisms through which circular strategies interact with energy flow systems and clarifies the contextual enabling the emergence of a Circular Energy configuration.

As organizations increasingly turn to online settings for strategic planning and foresight endeavors, fundamental questions arise of how this affects sensemaking activities: traditional sensemaking perspectives implicitly assume the availability of physical co-presence and its associated affordances. However, when sensemaking 'moves online' these taken-for-granted foundations are diminished. Drawing on data from a series of inter-organizational foresight workshops that were held both online and offline, we identify an underlying 'sensemaking infrastructure' consisting of three pillars that appear to be fundamental for sensemaking to take place in digital arenas: cognitive involvement, social engagement and prospective entanglement. Our study contributes to the literature by extending the sensemaking perspective with an infra-structural lens, shifting the analytical focus from sensemaking processes to the resources and prerequisites necessary for sensemaking to effectively take place in the digital realm. Concurrently, we provide actionable insights and facilitation approaches for building online settings that are conducive to future-oriented sensemaking.

This paper develops a mechanism-based framework to analyse how participatory, policy-oriented foresight processes may generate impact in innovation systems. Rather than focusing on outputs or direct attribution, it conceptualises impact as emerging through underlying mechanisms at individual, group, and system level. Drawing on social constructivism and the systems of innovation perspective, the analysis highlights cognitive reframing and anticipatory learning at the individual level, collective sensemaking and trust formation at the group level, and processes of diffusion, network reconfiguration, and institutional adaptation at the system level. For each level, expected observable changes, plausible time horizons, and alternative explanations are specified. By linking mechanisms to indications of impact, the framework provides a structured basis for empirical investigation and contributes to greater conceptual clarity in understanding how foresight processes may influence innovation systems over time.

Living Labs are widely used for co-creation and experimentation, yet dominant models often assume stable funding and infrastructure, creating a disconnect with the realities of creative industries, particularly in resource-constrained and emerging economies. This presentation examines a pop-up Living Lab as a temporally bounded innovation strategy. Drawing on the Penang Creative Industries Living Lab in Malaysia, it reflects on a one-week intervention, part of a British Academy funded project, working with eight creative businesses. It highlights key design elements, including a thematic hook, structured but accessible co-creation methods, and immersive real-world experimentation. Findings emphasise the importance of location, facilitation, and intuitive engagement in generating meaningful participation. The pop-up Living Lab also functioned as a capacity-building mechanism, fostering entrepreneurial mindsets among creative practitioners. The study contributes to debates on frugal, flexible, and participatory approaches to innovation management.

This study addresses the limited adoption of innovative learning environments in higher education by integrating physical and psychosocial perspectives with diffusion theory. Building on the PLE/PSLE framework (Baars, 2023) and Everett M. Rogers' innovation-decision process, the research develops a conceptual and intervention-based approach to increase acceptance, demand, and effective use of such spaces. Two co-created learning environments-a Flexible Learning Room and an Active Learning Room-serve as empirical cases. An integrated framework is constructed that links spatial attributes with adopter categories, communication channels, and intervention strategies. Rather than evaluating isolated measures, the study conceptualizes a design logic for investigating and supporting adoption processes. In doing so, it contributes to learning environment research by shifting the focus from physical design toward adoption processes and by explicitly incorporating organizational and psychosocial dimensions into the study of innovation diffusion.

Despite the growing debate about the potential of Artificial Intelligence (AI) to substitute certain jobs, no empirical research has examined its potential to replace innovation managers. This study addresses this gap by exploring how AI influences innovation management processes, drawing on empirical evidence from of 20 large corporations through in-depth interviews as well as focus groups with innovation managers and their teams. Findings reveal that AI cannot yet replace the end-to-end innovation process, with managers remaining indispensable for governance and critical decision-making. In particular, the development of radical innovations continues to rely on human creativity, as AI currently exhibits substantial limitations in generating genuinely novel ideas. However, AI enhances managerial capabilities by supporting intermediate activities, strengthening iteration and feedback, and providing mentoring for innovation teams. Based on these insights, the study proposes an AI-Augmented Stage-Gate Model, demonstrating how human-AI collaboration can accelerate innovation, optimize decision-making, and reduce managerial time demands.

This research-in-progress study examines service quality gaps in Innovation Support Institutions (ISIs) within three university-based ecosystems: Jamaica, Uruguay and Poland. Grounded in the Expectancy-Disconfirmation Model, the paper focuses on the gap between innovators' expectations and their perceived receipt of support in resilience, digitalisation and circularity. It also considers how these gaps relate to innovators' satisfaction and loyalty, and whether ISI staff assess service delivery in similar or different ways. The study follows a comparative survey design using parallel instruments for innovators and ISI staff. Current project materials indicate a pilot phase, while the preregistered main study sets out the analytical framework, sample logic and decision rules for the full comparative analysis. The final aim is to develop a compact diagnostic framework that can support both research and practice in the evaluation of university-based innovation support systems.

Circular brine-based carbon capture offers a promising route for linking industrial waste valorisation with durable CO? utilisation, yet its transition from technical feasibility to market uptake remains weakly understood. This paper develops an innovation management framework for exploiting saline industrial waste streams through CO? mineralisation, resource recovery, and circular business model development. Drawing on literature from brine valorisation, carbon mineralisation, industrial symbiosis, CCU commercialisation, and exploitation/IPR management, the study identifies preliminary key exploitable results, including brine characterisation protocols, pilot integration methods, mineralisation solutions, digital decision-support tools, and market viability models. The proposed framework connects technical outputs with foreground IPR, stakeholder needs, business model options, and post-project scale-up pathways. It also addresses market barriers, including brine variability, uncertain product certification, energy demand, lifecycle credibility, fragmented value chains, and unclear ownership of project results. The paper contributes to circular economy and innovation management literature.

Digital transformation is a key driver of organizational renewal and innovation, yet many initiatives fail to generate sustained innovation outcomes due to insufficient organizational readiness rather than technological limitations. To address this challenge, the Digital Transformation Readiness Maturity Model (DTRMM) is introduced, conceptualizing readiness as a configuration of foundational organizational capabilities. It structures six interdependent domains across five maturity levels, enabling both systematic assessment and organizational alignment. Involving 34 experienced experts across multiple industries, the Delphi process confirms the relevance of the domains and maturity progression. Qualitative feedback further highlights key aspects such as transformation triggers, governance, and execution capability, enabling targeted refinements. The results also indicate that maturity models can serve as boundary objects that facilitate alignment between management and operational levels, positioning the DTRMM as an empirically validated artifact that supports innovation and transformation management.

Despite sustained investments in innovation, many firms struggle to translate innovation activities into measurable performance improvements. This study examines whether business model innovation (BMI) contributes to firm performance and investigates the moderating role of digital transformation. Using firm-level data from 335 Hungarian medium- and large-sized companies, we estimate regression models with interaction effects to analyse the relationship between BMI, digital transformation, and productivity. The results show that BMI does not have a significant direct effect on firm performance. However, the interaction between BMI and digital transformation is positive and statistically significant, indicating that BMI improves performance only in firms with higher levels of digital maturity. In firms with low digital readiness, BMI does not lead to productivity gains. The findings highlight the contingent nature of business model innovation and emphasise the importance of digital capabilities as an enabling condition for value creation.

This work-in-progress paper examines what shapes SMEs' entry into innovation communities and what implications follow for innovation-community design at the entry stage. It develops a literature-based framework that conceptualises entry as an early-stage matching process between SME-side receptiveness and community-side access conditions. The framework integrates insights from research on SMEs' selective external knowledge engagement, absorptive capacity, innovation ecosystems, and phase-sensitive collaboration, and distinguishes four analytical dimensions: triggering conditions, needs and expected value, search and contact pathways, and evaluation and decision. Empirically, the study follows a sequential mixed-methods design combining a survey of 747 SME respondents with a qualitative interview study centred on CirTex, a DATIpilot innovation community in the field of circular textiles. As qualitative data collection is still ongoing, the paper sketches the expected analytical structure and anticipated lines of findings in order to invite reviewer feedback on coherence, methodological fit, and contribution.

This paper explores whether and how self-organized teams can foster innovation in organizations, with a focus on holacratic and agile settings. Drawing on a mixed-methods study alongside the relevant literature, it examines the circumstances in which decentralized ways of working actually support innovative outcomes. Rather than assuming that less hierarchy automatically leads to more innovation, the paper takes a closer look at the organizational and team conditions that make self-organization effective in practice. It pays particular attention to how collaboration, communication, responsibility, and coordination are handled when formal control is reduced. In doing so, the paper offers a more nuanced perspective on the relationship between self-organization and innovation, highlighting both the promise of these models and the practical difficulties they may create.

This paper compares the Biopharma-related Entrepreneurial Ecosystems of Munich, Basel and Cambridge between 2000 and 2025. Building on the Stam framework (Stam 2015), the study retains the established ecosystem elements but adapts the indicators to the specific conditions of Biopharma: long development cycles, high capital intensity, clinical translation, regulatory dependence and specialized knowledge infrastructures. Methodologically, the study follows an exploratory, theory-guided embedded multiple-case design (Yin 2009). The analysis shows that all three regions are strong ecosystems, but their strengths are differently configured. Munich represents a broad and increasingly translational ecosystem, Basel a highly concentrated and industry-integrated ecosystem, and Cambridge a compact, science-driven and spinout-oriented ecosystem. The sector-specific adaptation adds analytical value because it makes visible differences in clinical trials, Biopharma VC, clinical infrastructure, specialized intermediaries and university-industry collaboration that a generic framework would only partially capture.

Small and medium-sized enterprises (SMEs) increasingly engage in open innovation (OI), yet the associated risks and challenges remain fragmented across the literature. This paper presents a systematic literature review of 34 peer-reviewed studies published between 2003 and 2024, synthesizing the risks and challenges SMEs face when implementing OI. Using a structured content analysis, we identify eight primary risk categories, with Process and Time, Partnerships, Team dynamics, and Knowledge Sharing/IP emerging as the most prominent. The findings reveal that these risks are fundamentally shaped by SMEs' distinctive structural characteristics - including resource constraints, limited absorptive capacity, and informal governance - and are not simply scaled-down versions of large-firm risks. We discuss the taxonomy's alignment with established theoretical frameworks and delineate critical boundary conditions. The study provides actionable guidance for SME managers and policy makers and advances a structured agenda for future research.

Limited empirical research examined how AI assimilation reshapes workplace dynamics and employee outcomes. This study investigates the effects of AI assimilation on workforce agility, employee voice, organizational voice, employee well-being, and innovative work behavior. The study develops and tests a mediation framework using survey data from 265 employees across multiple industries. Findings indicate that AI integration fosters workforce agility and promotes organizational voice, enhancing innovative behaviors. However, our findings challenge the assumption that AI improves all employee outcomes, revealing no direct or indirect positive impact on employee well-being. The study extends research on AI assimilation by demonstrating that AI-driven workplace transformation produces differentiated outcomes. While AI assimilation facilitates innovation through workforce agility and organizational voice, it does not inherently improve employee well-being. The study offers insights of how AI becomes embedded in work practices and highlights the need for organizational interventions that address employee well-being alongside innovation objectives.

This research examines how Diversity, Equity, and Inclusion (DEI) principles function as both enablers and barriers in the management of community-driven innovation initiatives. Through a meta-ethnography of 30 cases and empirical fieldwork in French 'third places', we identify what we term 'lay management': an unconventional, experience-based governance approach that reconciles strategic intentions with daily practice. Findings suggest that when DEI is integrated as a fundamental strategic orientation, it produces multi-dimensional territorial, social, and ecological value. Furthermore, the study reveals a framework of eight management enablers, such as needs-based facilitation and proximity management, and ten barriers shaping value-based innovation, including a lack of adapted management structures. Our findings contribute to strategic intent theory and innovation management by bridging organisational values with concrete practices. This offers practical insights for social economy managers, public authorities, and researchers navigating value-based innovation spaces and ecosystems oriented toward solving societal challenges.

This study explores how faculty and students at three universities -Romania, Spain and Ukraine- perceive the integration of emerging risk topics, identifies learning gaps, and assesses digital competences to use open educational resources in higher education. Two questionnaires were collected to faculty and students, focusing on curricular coverage, perceived learning gaps, and self-reported digital capacity. Results show a moderate level of curricular integration: circular economy is most covered, while climate governance and green finance receive limited attention. Both groups report gaps in green finance, geopolitical risk, and cyber risk. Digital capacity is generally high and cross-national differences appear among students. Regression analyses highlight different mechanisms: for teachers, digital confidence increases with higher curricular integration, whereas for students, digital competences are closely linked to the size of the learning gaps they perceive. Finally, a cluster analysis identifies three educational profiles with direct implications for designing modular and multilingual open educational resources.

Data has become a strategic asset for innovations. However, unless organizations are able to innovate their value capture mechanisms, the full potential of data-intensive innovation remains unrealized. Despite its critical importance, value capture has remained a rather overlooked area in innovation management research. This presentation will outline opportunities for value capture relying on space-based data, including Earth Observation and satellite data. These data afford opportunities for economic and operational value as well as societal benefits. Insights on value capture will be presented through the lens of Sarasvathy's (2001) effectuation theory, by mirroring the five core principles of Bird-in-Hand, Affordable Loss, Lemonade, Crazy Quilt, Pilot-in-the-Plane. By the end of the presentation, the audience shall gain a better understanding of the opportunities for value capture afforded by space-based data and applications.

Waste4Soil addresses the transformation of food processing residues into local, bio-based soil improvers through a circular, systemic, and multi-actor approach. Within this wider project, Work Package 6 focuses on circular business models, standards, social acceptance, and investment-oriented exploitation pathways. This research-in-progress paper reports early experiences from developing business models in Waste4Soil by applying the PREPSOIL business model canvas in connection with participatory workshops, expert-based evaluation, and case-specific business background analysis. The paper is structured around four interlinked task areas: business background analysis and drafting of canvases, standards and certification-related framing, co-creation of sustainable and circular business models, and social acceptance and investment perspectives. Methodologically, the work combines interviews, small-group interaction, brainstorming, value proposition analysis, PREPSOIL canvas drafting, and a fast-track multi-criteria expert evaluation process. Preliminary results suggest that the PREPSOIL canvas provides a useful bridge between technological development, stakeholder engagement, and exploitation planning.

This paper analyzes how a public avant-garde research institution mobilized an open innovation mechanism to respond to the disruptive rise of generative AI. Historically structured around a hybrid model combining artistic exploration and technological exploitation, IRCAM now faces increasing pressure from rapidly accessible AI tools and shifting technological leadership. In October 2025, a new Artistic Research Director initiated "hybrid research groups" bringing together internal and external actors to explore AI-driven creativity. Based on a seven-month starting qualitative case study combining participant observation and reflexive field notes, this paper examines how this mechanism functions as a tool for organizational ambidexterity and open innovation. The findings highlight emerging tensions surrounding leadership centrality, power asymmetries, coordination overload, and the progressive structuring of exploration. The case demonstrates that open innovation can revitalize exploratory capacity, but its transformative potential depends on how power redistribution and collective sensemaking are managed over time.

Over the past two decades, Innovation Ecosystems (IEs) have experienced interest in literature analyzing how heterogenous actors collaborate to produce system-level outputs. Notwithstanding, insights on the sequential processes through which collaborative innovation unfolds under real-world conditions remained limited. The present study addresses this gap by examining how collaborative innovation processes are activated, structured and coordinated within institutionally-driven innovation ecosystems. Based on a qualitative process analysis of e.INS - Ecosystem of Innovation for Next Generation Sardinia, this research traces three sequential phases, namely activation, partner selection and coordination. The findings show that collaboration is governed through regulatory frameworks, rather than relational dynamics. The study contributes to the existing literature in introducing the institutionally-pulled model of ecosystems emergence with a public entity as ecosystem architect, reveling a multi-level orchestration structure distributed across different governance layers, and reframing collaboration as directive-driven.

E-mobility infrastructures are systematically framed as transactional technical systems. Reinterpreting them as commons infrastructures - where energy functions as social currency rather than a market good - opens a more generative foundation for the energy mobility transitions. This paper develops a preliminary conceptual framework, the Regenerative Energy Commons, through a scoping review at the intersection of three bodies of literature not previously brought into dialogue: regenerative business models, energy commons scholarship, and socio-ecological-technological systems research. Thematic analysis of the corpus yields five constitutive dimensions - ontological shift, polycentric governance, techno-social integration, multi-capital value, and place-based living-systems embedding - and surfaces a conceptual gap around regenerative value retention in energy and mobility systems. The framework is offered as a normative-analytical scaffold for evaluating the integrity of a just energy transition for the energy mobility transition.

Generative artificial intelligence is transforming how students search, recombine, and evaluate knowledge. Yet broader AI access does not automatically improve performance. This paper examines how knowledge awareness-the alignment between perceived knowledge and task difficulty-shapes student performance, and how AI trust-dependence misalignment moderates this relationship. Drawing on data from 140 students across six course iterations in two innovation-oriented electives, I analyse individual and group performance under routine AI use and compare closed-book with AI-assisted open-book exam conditions. The findings indicate an inverted U-shaped relationship between knowledge awareness and individual performance, while group performance tends toward a U-shaped pattern. AI overtrust steepens the individual-level curve, whereas AI overdependence affects the group-level pattern. AI-assisted open-book exams reduce effort investments in unrelated tasks and compress score variance without materially raising mean scores. The study shows that performance under AI depends less on access than on calibrated human-AI integration.

This paper examines the shift from process-oriented innovation teaching toward identity-based approaches in higher education. Drawing on literature on future skills, creativity, and innovation competence, it argues that traditional teaching methods-focused on tools and processes-fail to foster an innovative self-concept. Using a qualitative study of 28 students engaging in 21-day self-reflections and developing "hero profiles," the research reveals that students primarily perceive themselves as stabilizers rather than innovators, emphasizing control, resilience, and structure over experimentation and risk-taking. While analytical and social skills are strong, a lack of experimentation limits innovation potential. The findings highlight a gap between innovation competence and identity, suggesting that sustainable innovation requires transformative learning processes that build creative self-beliefs, encourage reflection, and support the development of an adaptive, innovation-oriented identity in students.

This study investigates how governance characteristics influence value co-creation and capture in territorial innovation ecosystems. Using a qualitative multiple case study approach, it analyses the ecosystems of Valencia (Spain) and Florianópolis (Brazil) through the Quadruple Helix framework. Preliminary findings from Florianópolis reveal a structural plateau where historical assets, including informality, personalized relationships, and organic emergence, have become vulnerabilities. Furthermore, value capture at the organizational level is dissociated from mere ecosystem presence, depending instead on internal absorptive capacity. A critical gap persists regarding academia's participation and the integration of social-environmental value propositions. These results suggest that effective governance must move beyond physical infrastructure to enhance institutional readiness. The research contributes to the literature on territorial coordination and provides insights for public policies aimed at fostering systemic maturity and sustainable value dynamics.

One of the challenges of innovation-related education is to "provide, maintain, and update online, user-friendly, plain language summaries of the practice principles that the best available evidence supports, while sharing information regarding their effective use as well as their limitations" (Rousseau, 2007), and this in a world which is squeezed between the opportunities provided by new AI-based tools and the challenges of finding reliable, traceable and "science-based" insights. In this context, the objective of the "Innovation Essentials" project is to provide teachers and students with a structured menu of science-based « knowledge nuggets », i.e. short videos with links to selection of high-quality sources and brief self-assessment surveys. These "knowledge nuggets" can be accessed directly by learners or mobilized by a facilitator in the context of a specific teaching model (audience, objectives, methods, results; Fayolle and Gailly, 2008).

This study proposes an AI-assisted roadmapping approach that uses large language models (LLMs) to integrate data-driven and expert-based processes. Using a design science research methodology, three sequential industrial case studies were conducted to develop, test, and refine the proposed approach. The process comprises five stages: planning, roadmap definition, AI-assisted data collection, expert review, and strategy formulation. Results indicate that LLMs can effectively pre-populate roadmaps with diverse and contextually relevant information, significantly reducing the time and effort experts spend on initial data collection. This shift allows experts to concentrate on higher-value activities such as validation, analysis, and decision-making. The findings also highlight the importance of carefully defining roadmap architecture and contextual inputs to ensure output quality.

This paper describes a novel approach to achieving definition consensus amongst a panel of international, cross-disciplinary experts engaged in scoping reviews of social innovation measurement. Measuring social innovation for assessing outcomes and impact is identified as one of the most pressing issues in the field, and establishing definition consensus is considered a central objective of scoping reviews. The consensus approach involves modifying Delphi and decision tree methods to establish a structured communication technique which allows experts to systematically evaluate, chose, reflect on, and reassess different definition options. The paper describes how undertaking a thematic analysis of the consensus process can generate a rich description of how consensus methods are deployed, resulting in a level of process detail that addresses some of the criticisms made of consensus methods. The paper suggests that consensus design should include process guidance for experts that establish high levels of social capital at the outset.

Despite the clinical potential of PET-CT imaging in oncology, its adoption in France remains contested due to deeply entrenched jurisdictional boundaries between nuclear medicine and radiology. Moving beyond individualistic technology acceptance models, this study mobilizes diffusion of innovation, boundary sociology, and social exchange theory to examine this systemic phenomenon. Based on semi-structured interviews with gatekeeping clinicians across two Comprehensive Cancer Centers, our qualitative analysis explores the socio-organizational factors shaping integration. Results reveal that the fragmented PET-CT report fails as a pragmatic boundary object, significantly increasing perceived complexity. We demonstrate that these perceived technical inadequacies actually mask active professional boundary work and a breakdown of interprofessional trust. Finally, we propose actionable managerial strategies, including structured reporting and multidisciplinary collaboration, to bridge professional silos and prepare for the impending disruption of Radioligand Therapy.

This paper examines how re-awareness (re-aware), a third value beyond use and exchange value, serves as a new resource, driving re-capitalization in which Sustainability Intelligence (SI) informs the evolving logic of value creation in the fashion business. The study forms part of a broader doctoral research project on the SI systemic theory. It adopts grounded theory methodology, informed by an interpretivist epistemology, situating sustainable value creation within complex socio-industrial fashion systems. Empirical data include interviews and focus groups with fashion professionals across 13 countries, analysed using the constant comparative method by first author independently. Additionally, design-led and business-led industry perspectives reflects strategic implication of the "third value" concept illustrated through selected fashion artefacts, including its X-appeal, by assessing its applicability within real-world organisational logics and business conditions. Together, these insights articulate an SI-based mind value and demonstrate its capacity to foster re-awareness as a systemic transformation across fashion ecosystems.

This paper examines how firms protect innovations from internal leakage by focusing on internal appropriability mechanisms, including secrecy, contracts, and human resource management (HRM) practices. While prior research mainly emphasizes intellectual property rights, this study considers intrafirm mechanisms, particularly in early and uncertain stages of the innovation process. Based on a systematic literature review of 80 peer-reviewed articles, the paper synthesises existing research and develops a conceptual model linking these mechanisms to different stages of the innovation process. The findings show that effective protection requires combining multiple mechanisms and adjusting them over time. HRM practices are identified as microfoundations that shape employee behaviour and strengthen other mechanisms. The paper also introduces a preparatory stage, in which internal procedures, employee training, and contract templates are established. It provides practical guidance for managers on designing internal systems for protecting innovations.

Resource sharing in the industrial context, often referred to as industrial symbiosis, offers great ecological and economic potentials for the involved companies and for entire industrial regional ecosystems. Under the scientific conduct and project lead of Cologne University of Applied Sciences, an extensive resource-sharing-ecosystem is currently prepared and established within the industrial area of Cologne, Germany, using a digital platform as facilitator for match making and knowledge transfer between the involved companies. The work-in-progress paper presents preliminary research findings of this real-world laboratory, focusing on prerequisites and governance necessary to encourage trust and allow for cooperative open innovation. Secondly, the paper indicates, which particular categories of tangible as well as intangible resources are most suitable for cross-company sharing and how they can be identified within companies. Finally, the paper introduces a preliminary assessment model to capture and validate the economic and ecological beneficial effects of resource sharing.

Chemical companies face increasing complexity driven by sustainability pressures, evolving customer expectations, and accelerated technological change. To remain competitive, innovation must operate as an integrated system rather than a collection of isolated initiatives. This paper presents how a global chemical organization structured a connected Innovation Engine that unifies Marketing, Sales, Technology, and R&D into a cohesive end to end ecosystem linked to customers, partners, startups, and academia. The model combines internal capabilities with external collaboration to accelerate decision making, strengthen customer proximity, reduce development risk through early co creation. Digital and AI enabled tools act as key enablers, accelerating development cycles, enhancing insight generation, augmenting human expertise. The approach has resulted in higher value innovation pipelines, earlier entry into attractive markets, and stronger portfolio performance driven by differentiated and sustainability aligned solutions. Beyond technology, the Innovation Engine embeds disciplined governance, cross functional collaboration, cultural alignment across global chemical industry contexts.

This case study challenges the myth that systematic innovation is an expensive luxury reserved for large corporations with massive R&D budgets. It examines the three-year, highly collaborative Community Innovation Ecosystem (CIE) program led by Unbounded Thinking and Innovate Cochrane, which established a human-centered innovation management framework across 17 local organizations in Cochrane, Alberta, Canada. By improving innovation and organizational readiness capabilities, the program tracked a +12% improvement in systematic innovation capabilities and a +17% boost in overall organizational capabilities. The ecosystem successfully shifted resource-constrained small businesses from pursuing high-risk breakthroughs toward sustainable, cost-reducing efficiencies. This community-led approach accelerates business retention and expansion, transforming local small businesses into resilient, high-growth "gazelles" that anchor regional economic development before scaling this collaborative ecosystem model to additional Albertan municipalities.

This study examines how adaptation problems accumulate and shape scaling trajectories as digital innovations are implemented in healthcare ecosystems. Healthcare is characterized by complexity and dense interdependencies that complicate adoption. Drawing on a qualitative multiple case study of ten digital health technology vendors, we conceptualize adaptation load as the cumulative work required to adapt and implement a solution across customers over time. We show that adaptation load patterns emerge from the level and timing of alignment across interdependent elements during scaling. We identify three patterns. Upfront adaptation load can be resolved at the product level prior to deployment, enabling standardized replication. Recurring adaptation load requires repeated, context-specific alignment at the process level, enabling replication of implementation processes. Ecosystem-embedded adaptation creates a compounding load, as unresolved institutional constraints persist-limiting replication and delaying scaling. These patterns explain variation in scaling trajectories and the development of corresponding scaling routines.

Japanese incumbent firms face a persistent paradox: employees widely recognize the importance of innovation, yet sustained exploratory behavior remains rare. This paper conceptualizes innovation interruption, in which exploratory initiatives stall before approval and produce neither learning nor outcomes. Drawing on a survey of R&D employees in a Japanese manufacturer (Company A) and comparison with Company B, the study shows that this gap arises from the interaction of intergenerational motivation misalignment and approval friction. Early-career employees seek experiential learning, mid-career employees face performance and reputational risk, and senior employees are driven by generativity. These dynamics are reinforced by organizational learned helplessness and path-dependent institutional residues. The paper distinguishes direct and indirect imprinting effects across cohorts and proposes targeted interventions-micro-budgets, senior guardianship, re-exploration rotations, and structured external exposure-to restore exploratory momentum.

Artificial intelligence is increasingly integrated into innovation activities, from technological scouting to idea generation and strategic analysis. While AI is often perceived as a tool capable of optimizing innovation decisions, this perspective may conflict with the exploratory and experienced-centred nature of all innovation processes. This paper proposes a conceptual reframing of the operational role of AI in innovation management systems. Rather than positioning AI as a substitute for human reasoning, we argue that AI should be considered a cognitive mentor that expands the reasoning capabilities of innovators. The paper further conceptualizes AI as a cognitive resource embedded within the innovation capability infrastructure of organizations, supporting exploration, learning and sense-making without replacing human judgment. Drawing on the structure of the ISO 56001 innovation management system, we analyse how AI can support innovation activities at strategic, tactical and operational levels.

While social innovation is increasingly recognized as a driver of sustainable development and systemic transformation, existing evaluation approaches remain fragmented and largely technocentric, limiting their practical applicability. To address this gap, the study applies a design science research methodology, consisting of systematic literature reviews and qualitative content analysis to identify and consolidate more than 400 variables into a validated set of 100 quality criteria. The framework is structured along four interrelated dimensions: delineation, impact, process, and maturity. It enables a differentiated understanding of social innovations by capturing their characteristics, societal value creation, development processes, and levels of institutionalization. The framework improves transparency, comparability, and strategic decision-making. Validation through expert interviews and case applications demonstrates the tool's usefulness for academic research and managerial practice.

Industrial manufacturers increasingly invest in digital technologies to generate value from data embedded in equipment and connected operations, thereby extending value creation beyond physical products. However, despite the strategic potential of data, many incumbents struggle to translate data resources into scalable service- and data-centric business models with consistent value capture. In particular, it remains unclear how cyber-physical interdependencies in industrial B2B contexts both enable and constrain data-driven value creation and realization. To address this gap, this study investigates how cyber-physical interdependencies shape firms' ability to create value from data and translate it into value realization. The paper draws on a qualitative single-case study of an internationally active B2B manufacturer. The findings show that physical assets act as strategic gateways to data access and control; digital capabilities enable service and monetization innovation; and cyber-physical architecture co-evolves with business model design. The study advances research on digital innovation, servitization, and B2B platforms.

Phuket Cancer Institute has developing an innovation-driven model of cancer care that integrates prevention, early detection, diagnosis, treatment, and surveillance into a connected clinical continuum. This presentation shares practical experience in translating emerging technologies into hospital-based oncology care, with a focus on four high-impact domains: gut microbiome applications for cancer prevention and surveillance, AI-assisted polyp detection, liquid biopsy for early diagnosis and disease monitoring, and AI-assisted surgery to improve intraoperative safety and reduce complications. Rather than presenting innovation as isolated technologies, this session will demonstrate how multidisciplinary innovation can be orchestrated across the patient journey to generate measurable clinical value. The presentation will highlight implementation challenges, translational pathways, governance considerations, and lessons for scaling innovation within real healthcare systems. It will offer ISPIM participants a concrete perspective on how innovation management principles can be applied in cancer care to improve outcomes, safety, and continuity of care.

This study examines the cognitive mechanisms underlying the contribution of AI-generated information in hybrid intelligence, where humans and AI collaborate to achieve superior outcomes. Prior research has primarily evaluated outcomes such as novelty and usefulness, but has provided limited explanation of how AI expands human thinking. Focusing on the "AI Pudding" project by NEC and Kagome, this study analyzes how developers interpret and select 25 AI-generated ingredient combinations through expert interviews. The findings reveal that AI-generated information activates latent knowledge that is "known but not readily recalled," thereby facilitating distant search beyond the developers' familiar domains. Moreover, through interaction with AI outputs, developers reconstruct meaning via a process of reflective conversation and constructive perception. These results suggest that AI functions not merely as an answer-generating tool but as a dialogic trigger that enables knowledge activation and creative recombination, contributing to a deeper theoretical understanding of human-AI co-creation.

This study examines how digital twins, virtual counterparts of physical systems, are integrated into sustainability business strategies in manufacturing. While prior research emphasizes their role in improving operational efficiency, their strategic contribution to sustainability remains underexplored. Drawing on the Resource-Based View (RBV), the study conceptualizes digital twins as potential strategic resources rather than solely operational tools. Empirical insights are drawn from multiple case studies of ten Finnish manufacturing firms across diverse sectors and levels of digital twin maturity. Using thematic analysis, the study identifies nine core digital twin functionalities and present how these functionalities generate sustainable business outcomes only when enabled by complementary strategic mechanisms. The findings indicate that digital twins have the potential to contribute simultaneously to economic, environmental, and social sustainability and summarize these results by introducing a three-layer framework linking digital twin functionalities (technological layer) with strategic mechanisms (capability layer) and sustainability outcomes (value-creation layer).

This presentation introduces the Innovation & Research Caucus (IRC), a pioneering model to bridge the persistent gap between academic research and public sector policymaking. Funded by UK Research & Innovation (UKRI) and delivered through academic institutions, the IRC enables iterative, co-created collaboration between researchers and policymakers from research inception through to output dissemination. By connecting academic expertise to policy environments, the IRC has generated timely, policy-ready evidence that has informed investment design, funding bids, and strategic decision-making. Drawing on practical case studies, the session explores key collaboration mechanisms, including co-created project initiation documents and continuous engagement. It highlights the importance of trust, emotional intelligence, and adaptability in navigating cultural differences. The IRC offers a transferable and scalable framework for strengthening innovation ecosystems through closer alignment of research and policy across diverse national and institutional contexts.

This submission presents Twinity, a digital twin city platform designed to support ESG simulation and predictive decision-making across buildings, districts and urban portfolios. It addresses the limitations of existing digital twin implementations, which often remain descriptive, fragmented and poorly integrated across BIM, GIS and ESG data sources. The project introduces a workflow-based, format-agnostic data pipeline that preserves object-level semantic intelligence across heterogeneous data formats and aligns it with ISO-compliant data dictionaries. This enables consistent life-cycle analysis, CO? reduction potential assessment and ESG simulation across multiple assets. A further innovation is the use of AI- and ML-supported query mechanisms that allow non-expert users to generate complex predictive insights without manual data extraction. By moving digital twins beyond visualisation towards operational decision support, Twinity contributes to urban planning, real estate management, sustainability governance and compliance with evolving European sustainability regulations.

This study aims to better understand the differences in the ways firm manage their NPD portfolio. More specifically, our objective is to develop a conceptual model of the various NPD portfolio strategies and to identify firm specific factors that are associated with the use of a specific strategy. We apply a mixed methods research design that is mainly qualitative but also contains quantitative research elements and involves 26 case studies. Our study makes four important contributions. First, we identify four different NPD portfolio strategies (variable budget, fixed budget, strategic buckets with fixed budget, and strategic buckets with variable budget). Second, our research confirms empirically that the choice between these approaches is context dependent, it is not that one approach results in superior performance. Third, given the context dependency of NPD portfolio strategies, we identified firm specific factors that impact the choice of a particular approach.

Public healthcare systems increasingly invest in artificial intelligence that holds promise to improve efficiency and generate organizational innovation. However, these efforts often fail and may even reinforce institutional rigidity. This study approaches this paradox by examining how AI interacts with human decision processes in complex governance environments. Drawing on an abductive qualitative study in healthcare, the findings suggest that adoption barriers are not primarily technological but structural, and that AI adoption can become a useful diagnostic mirror indicating organizational readiness and revealing rational - and, importantly, addressable - adoption challenges. Rather than representing implementation failures, challenges related to fragmentation, documentation and trust signal misalignment between algorithmic logic and institutional practices, revealing how AI-human synergy, when reached, forms a systemic capability. Introducing the AI-Human Capability Loop, a conceptual framework elucidating co-evolution of cognitive understanding, collaborative confidence, and ethical adaptability, this study contributes to existing knowledge on innovation management for adaptive governance

Data privacy in the EU has been a topic of contention ever since it went into force in 2018. The rapid proliferation of AI has fostered a dynamic global ecosystem of AI start-ups. But the emergence of regulatory frameworks, such as the EU AI Act, presents a complex landscape for nascent ventures as compared to relatively mature ones. This paper investigates how start-up founders perceive and navigate regulatory obligations, examining whether these perceptions vary based on organisational maturity and resource availability. Focusing on Munich, this study employs semi-structured interviews with founders to explore their interpretive approaches to compliance. Our findings reveal that while early-stage start-up founders often view regulation as an ambiguous constraint, mature-stage start-ups increasingly leverage governance as a "USP" to enhance market legitimacy. The study concludes that AI governance in start-ups is an evolving process shaped by stakeholder expectations, suggesting a need for more technically grounded regulatory guidance.

The rise of Industry 5.0 and growing social uncertainty are fundamentally reshaping expectations for innovation management, bringing human-centered and value-driven approaches to the forefront. This study examines the role of student coaching as a structured learning space that elevates students to the position of lead users. The research employs a mixed-methods approach: simulation tasks, focus group interviews, and a quantitative questionnaire survey conducted on a sample of 597 participants. The results show a significant correlation between openness to self-development and the development of innovation competencies-such as empathy, adaptability, and collaborative willingness. The theoretical contribution of the study is the extension of the lead user theory to higher education, while from a practical perspective, it positions coaching as a strategic innovation management tool that enables future professionals to engage in socially responsible innovation. Keywords: Gen Z, coaching, lead user, co-creation, Industry 5.0, Education 5.0, higher education, innovation competencies, primary research

Digital transformation is reshaping the role of users from passive recipients of technology to active participants in its development. The integration of AI, further extends this shift as such systems start to learn and adapt based on user interactions. Co-creation, in this setting, becomes a continuous and evolving process rather than a one-time activity. Responsible Innovation (RI) offers an established approach to align technological development with societal values. However, existing RI frameworks do not adequately account for the adaptive and continuous nature of AI systems. RI provides limited guidance on ethical and regulatory considerations integrated throughout the AI development lifecycle. This paper proposes a conceptual framework that builds upon key principles from RI, user innovation and AI governance in a complementary manner, to support responsible co-creation in adaptive AI systems. The framework is applied to an AI-integrated educational platform as an illustrative case study to assess its practical relevance.

Digital twins (DTs) have demonstrated value within organizational boundaries, but extending them across organizational boundaries requires representing coordination context that operational data cannot capture. This paper addresses the coordination representation gap through Design Science Research, presenting the first iteration of the SSS-VUCA method, a diagnostic for cross-boundary coordination challenges that informs requirements for socio- technical DT architecture. The method was demonstrated in a NASA-funded airspace resilience programme. Co-occurrence analysis identified three coordination couplings around which architectural requirements were organised. The central finding: cross-boundary structural fragilities attract information- interpretation responses while repelling operational responses. Stakeholders recognise coordination challenges but lack mechanisms to address them. Theoretically, the method instruments status mismatch for diagnostic use; methodologically, it treats VUCA as a diagnostic instrument generating more targeted interventions than conventional framings; practically, it surfaces interpretive divergence invisible to current systems, with expert validation supporting cautious extension beyond aviation.

Digital Innovation Hubs (DIHs) aim to support companies by providing access to digital technologies, expertise, and innovation infrastructures. When DIH services are delivered across regional boundaries, orchestration becomes more complex due to fragmented governance, differing practices, and the absence of hierarchical control. This study examines how DIH service orchestration can be designed for cross-regional service delivery and how the innovation corridor concept can support this process. The research follows a design-oriented qualitative approach and draws on empirical material from a cross-regional development project involving higher education institutions and small and medium-sized enterprises. The findings show that effective cross-regional orchestration requires explicit coordination practices that address service scoping, responsibility allocation, and continuity. The innovation corridor concept provides a lightweight framework for aligning participating organisations around shared mission, governance, trust, and financial sustainability, thereby supporting coordinated DIH service delivery across regions.

This paper presents the development of AIJKPG, a regional platform for artificial intelligence collaboration in Jönköping County, Sweden, co-funded by the European Union. Building on earlier AI readiness initiatives, the project focuses on activities carried out between 2023 and 2025 to strengthen regional AI capabilities through coordinated, cross-sector collaboration. The region, characterised by small and medium-sized enterprises and public organisations with limited internal AI capacity, faces challenges related to fragmented initiatives, restricted access to expertise and infrastructure, and difficulties in scaling AI implementation. AI JKPG addresses these challenges by bringing together stakeholders from industry, the public sector and academia, with a strong emphasis on trust-building and shared resource use. A key feature is a reference group of senior decision-makers who act both as a steering body and an active working group. Outcomes include increased openness in knowledge sharing, joint experimentation, emerging collaborations and new research and innovation projects.

This study addresses the need for pedagogical practices supporting learning and implementation of the ISO 56002:2019 Innovation Management System standard (ISO 56002). Adopting an abductive research approach, the study iterated between empirical data and theory to develop DCAP (Do-Check-Act-Plan) as an integration of pedagogical and learning dimensions at an individual, team, and organizational level. Using a multiple case research design, empirical data were collected from organizations engaged in innovation management system development. The findings indicate that DCAP functions as a pedagogical and operational structure that helps people interpret, enact, and expand their learning of the ISO 56002 in practice, and serves as a complement to the PDCA (Plan-Do-Check-Act) approach. The study contributes empirical insight into how learning processes support the enactment of ISO based Innovation Management frameworks. Limitations and future research are discussed.

This presentation addresses the question: How can we draw on the engagement power of social media to facilitate authentic, high-quality peer-to-peer learning in an online innovation management course? It will present the case of a new 10-session online program, "Innovation for Managers" that attempts to embed social constructivist principles into its design using structured workshop tasks, peer response posts and facilitator-guided stimulus and synthesis to foster a more effective learning community among participants. This case study will directly interest the ISPIM SIG for Innovation Training, Teaching and Coaching and seeks to contribute to the ongoing conversation about how to use social techniques to build engagement with learners, especially in the online world. This presentation should also interest Academics, Program Directors in Executive Education and Innovation Managers and Corporate Learning & Development Leaders seeking to educate and improve the skills of students and practising managers.

Study examines how South African biotech ventures translate laboratory science into commercially viable and socially appropriate innovations. Integrating new product development (NPD) theory with knowledge translation and inclusive innovation perspectives, it investigates how firms adapt development processes under conditions of institutional constraint and epistemic asymmetry. Using a comparative, process-oriented multiple case study of 4-6 ventures across health and bio-based domains, the research analyses how regulatory environments, funding architectures, and global scientific validation norms shape NPD decision-making. The study argues that these factors do not merely influence firm behaviour but structure the feasible set of development pathways available, producing distinct "translation regimes." These regimes condition both commercialisation outcomes and the extent to which inclusivity, affordability, accessibility, and user participation, is embedded upstream in innovation processes. The research contributes to NPD contingency theory, advances process understandings of knowledge translation, and provides empirically grounded insights into inclusive innovation in emerging economy biotech systems.

The Întegration of Generative AI into organizational workflows has fundamentally shifted the internal economy of idea generation, funneling a higher density of proposals towards senior leadership. However, the current literature on employee-driven innovation hasn't fully captured how these dynamics work in practise - particularly in SME's. In these firms regulations play a huge role in shaping the innovtion process, yet we haven't explored how GenAI fits into that struggle. This study uses an insider's perspective to look at a six-month GenAI hackathon at a regulated Swiss Organization. Drawing on participant observation, organizational artefacts, middle manager survey and semi-structured interviews, it documents middle management activity across three phases : pre-hackathon , regulatory navigation and Post hackathon. The findings exted Hoyrup's (2012) EDI framework and Floyd and Wooldridge's (1992) middle management typology by proposing a three-phase translation model and identifying regulatory brokering as untheorised middle managment role in regulated SME contexts.

This conceptual study introduces the Innovation Corridor as a framework and novel instrument for approaching the management of innovation processes, drawing upon Frank Geels's Multi-Level Perspective (MLP) on socio-technical transitions and David Teece's dynamic capabilities approach to business modelling. The study employs the Innovation Corridor to address the persistent fragmentation of innovation activities across technological, organizational, and institutional domains in Entrepreneurial Discovery Processes (EDPs) and Smart Specialization Strategies (S3). While the MLP has been widely applied to analyze transitions across niche, regime, and landscape levels, its use has remained largely retrospective and descriptive, offering limited support for proactive innovation management and strategic decision-making. By contrast, dynamic capabilities theory has been extensively applied to innovation management and strategic decision-making in a proactive and prescriptive manner, yet it offers more limited support for analyzing processes of transition management. The study contributes by operationalizing the MLP as a dynamic capability, and conversely, dynamic capabilities within an MLP framework, while integrating foresight, business model innovation, and growth-oriented decision-making into a unified transition process. By embedding foresight as part of the dynamic capabilities cycle and aligning it with policy and cluster-level strategies, the Innovation Corridor strengthens strategic coherence across actors. It thus constitutes both a framework and a practical instrument for advancing the applicability of MLP by transforming it into a proactive tool for dynamic capabilities, the management of EDPs and innovation portfolios, and the facilitation of sustainability transitions in complex S3 socio-technical systems.

Canada's human research oversight operates within a fragmented regulatory and governance landscape, creating challenges for institutions responsible for ensuring compliant and safe research conduct. The Institutional Authorization (IA) model addresses this complexity by enabling institutions to better manage risk, improve operational efficiency, and foster a culture of quality and safety. This approach allows Research Ethics Boards (REBs) to focus on ethical feasibility and appropriateness, without extending their mandate to broader institutional responsibilities. In addition to supporting a single REB review model for multisite research, IA enables structured institutional oversight for non-research activities (e.g. data registries and quality improvement) where ethics review may not be required. Targeted implementation through a multi-year institutional pilot has resulted in measurable improvements in efficiency, timeliness, and oversight, leading to faster study activations while maintaining strong protections for research participants. Learnings will serve to establish a predictive model to better respond to delays in study activation.

Student retention and timely graduation have become growing concerns for higher-education institutions as funding models increasingly emphasise progression outcomes. Existing retention and student-support approaches, however, remain largely oriented towards full-time undergraduate students and offer limited guidance for online master's programmes targeting working professionals with family responsibilities. This qualitative case study examined study-progression challenges among working master's students and explored coaching, framed as a service innovation, as an organisational support practice for progression and degree completion. Drawing on open-ended survey data from 52 master's students with full-time employment and family commitments, inductive thematic analysis identified five interrelated challenge dimensions shaping study capability. A phase-based analysis examined how these challenges varied across study stages. The findings suggest that extended study trajectories result from cumulative strain and sensitivity to changing study structures. The paper conceptualises phase-adaptive coaching as a service innovation supporting sustainable study capability, progression, and student well-being.

Regenerative business models (RBMs) aim to restore ecological and social systems while creating economic value, yet empirical understanding of their adoption across industries remains limited. This study examines the extent and forms of RBM adoption across different industries and value chain stages and identifies key barriers and enablers shaping broader implementation. The analysis draws on documented regenerative business cases across multiple sectors and applies a value chain-based analytical lens. The findings show that RBM adoption is most commonly embedded in upstream stages, particularly in ecologically dependent industries, while manufacturing and service sectors exhibit more hybrid and stage-specific adoption patterns. Barriers and enablers vary systematically by value chain position, with ecological and verification challenges dominating upstream stages and market- and governance-related factors shaping downstream adoption. The study contributes a cross-industry perspective on RBM adoption and highlights the value of a value chain approach for understanding regenerative transition pathways.

The potential of radical innovations to address major economic and societal challenges is substantial; however, they exhibit low success rates due to uncertainty arising from limited availability of reliable market data, higher capital requirements and constrained information bases. This increases investment risk and disadvantages them in resource allocation. Insufficient data also limits corrective validation mechanisms and fosters biased assessments, making the systematic overestimation of target market potential a key root cause of failure. A Design Science Research approach will be employed to create a framework founded on reverse methodological logic. This method broadens the traditional TAM/SAM/SOM framework by adding a constraint-focused view that systematically pinpoints limiting factors across customer needs, technical competitiveness, and value chain dependencies. Incorporating these constraints as corrective measures minimises overestimation and uncertainty, thereby facilitating a more resilient, uncertainty-aware evaluation of market potential.

Poland remains an emerging innovator despite a dense architecture of innovation platforms, science parks, clusters and university technology transfer offices. Drawing on twenty in-depth interviews with innovators operating in Bia?ystok, this paper asks why these formal platforms often fail to become living, productive innovation ecosystems. The findings reveal a paradox: innovators are entrepreneurial, opportunity-oriented and skilled in personal networking, yet they consciously bypass formal institutions and construct small trusted "bubbles" instead. Public bodies, especially universities, are experienced as bureaucratic, hierarchical and feudal, "still like in the communist times." The paper reframes ecosystem design as a problem of trust, institutional culture and post-communist organizational memory. It contributes to innovation management by showing how capable individual innovators may collectively reproduce ecosystem fragmentation, and it proposes governance levers for converting atomized agency into collaborative, cross-sectoral innovation capacity.

This research idea addresses the problem that firms' probability of innovation declines over time as they age and mature, while operational activities increasingly dominate and employees' innovation activities are reduced. Organizations attempt to foster innovation by formally supporting employees, for example by providing free time, which however often does not lead to the intended results. Prior research highlights the importance of employee-driven and bottom-up innovation and assumes that autonomy, discretion, and time resources support exploratory activities. At the same time, research shows that repeated exposure to innovation initiatives with limited implementation success can result in innovation-specific fatigue and disengagement, and that formally provided slack time does not necessarily result in its effective use. Against this background, this research aims to explore how changes in organizational innovation strategy and implementation practices relate to innovation outcomes from employees' formally provided innovation time over time.

Scenario planning is a promising but resource-intensive method for navigating uncertainty. While emerging AI technologies offer strong potential to enhance efficiency and reduce bias, fully integrated AI-supported scenario processes remain underdeveloped. This paper investigates if and how AI-based techniques can reduce effort and improve quality in early phases, focusing on information retrieval and derivation of relevant topics. Following a design science research approach, we develop an integrated process combining focused web crawling, NLP-based topic modelling, and large language models. Evaluated in a comparative case study, results show that AI-supported analysis of targeted web data reproduces all expert-defined influential factors, reveals additional topics, and reduces manual effort. Comparing data sources shows that relying solely on arXiv data yield narrower, less useful topic sets for the examined case study compared to general web data. Findings demonstrate AI can augment, but not replace, expert judgement and that data source choice shapes foresight outcomes.

This study examines how funding pathway choices shape strategic development trajectories in deep tech firms. Applying event analysis to 87 ventures across Estonia, Lithuania, and Latvia over 2005-2021, the study draws on archival data, founder interviews, and EUR1.12 billion in funding. Four configurations emerged: accelerated venture capital (n=16, 18%), hybrid grant-then-equity (n=47, 54%), corporate partnership (n=4, 5%), and grant-dependent (n=20, 23%). Hybrid and Accelerated VC pathways achieved valley-of-death crossing rates of 47% and 44%, respectively, while the grant-dependent pathway yielded zero commercialisation successes, revealing a structural ceiling at the technology-to-market transition. Success required alignment between funding characteristics and venture-specific conditions: technology readiness, market structure, and ecosystem maturity. Findings extend Shane and Venkataraman's (2000) opportunity exploitation framework, demonstrating path-dependent strategic choices with lasting consequences for development trajectories, market entry, and partnership strategies.

This study examines how startups develop organizational resilience during severe disruption, with a particular focus on the COVID-19 crisis. Drawing on qualitative evidence from 28 Ontario-based startups, the paper explores how firms adapted under conditions of uncertainty, time pressure, and resource constraint. Using thematic analysis, the study identifies three emerging mechanisms that appear central to resilience building: strategic responsiveness, crisis-driven innovation, and operational flexibility. The findings suggest that startups first respond to disruption through rapid sensemaking and timely strategic adjustment, then translate that responsiveness into innovative changes in products, services, processes, and business models, while flexible operating arrangements enable and reinforce these adaptations. The paper contributes to entrepreneurship and innovation research by proposing an emerging capability-based process view of startup resilience. Rather than treating resilience as a static trait, the study presents it as an evolving outcome of fast decision-making, innovation under pressure, and flexible reconfiguration during crisis.

Narrative Innovation: A Three-Step Process for Turning Consumer Insights into Emotionally Resonant Concepts Many innovation processes rely on analytical tools and linear frameworks that provide structure but fail to create shared meaning, emotional resonance, or strategic alignment across teams. The result: innovation initiatives that struggle with stakeholder buy-in and the translation of consumer insights into compelling concepts. This workshop introduces the Narrative Innovation Process - a structured methodology that embeds storytelling principles into applied innovation practice. Developed across diverse industries and organizational contexts, the approach follows three repeatable steps: Story Mining (surfacing deep consumer tensions and cultural signals), Story Framing (transforming insights into opportunity narratives that align teams), and Story Prototyping (using narrative-driven toolkits to generate coherent innovation concepts). Participants will experience the methodology hands-on and leave with a practical facilitation framework, tools for insight translation, and exercises for narrative concept prototyping - applicable immediately in their own innovation contexts.

This paper analyses the international relocation and functional reconfiguration of innovation activities in the German metal and electrical industry. Based on a survey of 240 companies, the study reveals a growing internationalisation of innovation alongside a clear functional specialisation across locations. While Germany remains the central hub for research and product development, production-related and market-oriented innovation activities are increasingly shifted abroad. The findings highlight the emergence of globally distributed but strategically orchestrated innovation networks, in which companies leverage location-specific advantages while retaining control over core technological capabilities. The results point to a potential erosion of domestic innovation depth in German industry and underline the importance of balancing global efficiency with organisational resilience and technological sovereignty.

Rapid electrification in transportation has led to an increased demand for lithium-ion batteries (LIBs). As batteries in electric vehicles reach their end-of-life, waste and disposal problems are expected in the next years. LIBs contain critical metals such as lithium, nickel, and cobalt. With a growing interest in circular economy and securing material supply chains, there has been extensive research on the technical aspects and economic value of LIBs recycling. However, real-world case combining cluster perspective with technical process aspects received less attention. This study investigates the spatial concentration and value chain positioning of LIBs recycling facilities in South Korea. It demonstrates a mapping of EV infrastructure, industrial recycling facilities, and government-led facilities to identify emerging clusters. The activities and positions of recycling facilities are analysed and characterized based on their functional roles and facility types. In addition, relevant government policies fostering the LIBs recycling sector are investigated.

Large organisations face a fundamental challenge in scaling artificial intelligence (AI) transformation beyond isolated expert initiatives and episodic learning formats. While generative AI tools are increasingly accessible, their effective and responsible integration into everyday work requires broad-based capability building and contextual application knowledge. This paper presents a qualitative practitioner case study of Deutsche Telekom's AI Pioneers program, a peer-learning initiative designed to scale AI literacy and application capabilities. Drawing on semi-structured expert interviews, internal program documentation, and descriptive participant feedback, the paper analyses how peer learning enables decentralised knowledge creation, cross-functional diffusion, action-oriented experimentation, and role-based scaling. The findings show that peer learning can be a powerful mechanism for AI transformation when embedded in real work contexts. At the same time, the case demonstrates that decentralised learning does not scale autonomously. Active community management is required to sustain engagement and translate learning into organisational impact.

Data economy, emerging from digital transformation and platformisation, positions data as a significant economic resource, often compared to "new oil". Despite increasing attention, the concept remains blurred and evolving, lacking a clear definition. This paper aims to provide a clearer understanding of the concept of data economy and proposes a new definition: Data economy is an area of the economy, where ecosystem partners and actors share data and make it accessible and usable for others in order to create new business opportunities in data economy ecosystems. Addressing an identified research gap, the paper critically synthesises existing definitions through a literature review and conceptual analysis. The analysis demonstrates that the core elements of the data economy lie in data, ecosystem, and business opportunities. The paper concludes by outlining directions for further defining the concept to support future theoretical and managerial applications.

Innovation ecosystems depend on coordination among autonomous partners that no single actor can command. Research on ecosystem coordination has concentrated on governance and value mechanisms but says relatively little about the cognitive processes through which decision-makers come to attend to joint issues. This research-in-progress takes the attention-based view of the firm (Ocasio, 1997) and asks how attention is allocated and coordinated across firm boundaries. This multiple case study in innovation ecosystems organized around a focal firm and its complementors, beginning in Estonia. First case interviews point to four recurring ways in which attention seems to support cross-boundary coordination: shared focal points that direct independent partners onto the same objects, visible engagement signals through which drift is detected and addressed in dialogue, attention organized at multiple organizational levels rather than through a single contact point, and individuals who carry attention across firms. Further data collection and analysis is ongoing.

This proposal examines how corporations can sustain innovation amid geopolitical, economic, and technological turbulence. It argues that uncertainty pushes leaders to prioritize core operations and competencies, sidelining transformative efforts when adaptability is most needed. The analysis combines firsthand experience in a Nordic energy company with interviews of practitioners from diverse industries, showing how short-term performance pressures repeatedly crowd out innovation and leave it detached from strategy. The presentation proposes practical safeguards: build and regularly refresh future scenarios, integrate scenario planning into both strategic cycles and innovation portfolios, and establish cultural and governance mechanisms that protect time, funding, and leadership attention for experimentation. By balancing operational excellence with disciplined exploration, organizations can respond faster to shifting markets and regulation, strengthen resilience, and preserve long-term competitiveness during prolonged instability.

Algorithmic management (AM), the delegation of managerial functions to algorithms, is rapidly spreading beyond digital platforms across industries. Yet its institutionalization as a stable governance mechanism remains uneven. This study conceptualizes AM as an organizational innovation and examines the conditions under which it emerges and stabilizes. Using fuzzy-set qualitative comparative analysis (fsQCA) on survey data from about 500 employees in four Japanese industries-manufacturing, transportation, services, and hospitality-we identify key configurational patterns. The findings indicate that task specialization and low labor mobility act as quasi-necessary conditions for AM. However, no sufficient configurations consistently produce high levels of AM, and dominant causal pathways are absent. Instead, organizations tend to move toward algorithmic governance but struggle to fully embed it in routines and structures. We interpret this as an algorithmic governance paradox, where organizational barriers and mismatches between technology and work practices hinder full integration.

Organizations investing in AI agents frequently discover that the limiting factor is not model intelligence but the quality, ownership, and trustworthiness of the underlying data. This paper presents a practice-oriented case for applying Data Mesh principles as an organizational and architectural foundation for AI agents. We describe how a decentralized, domain-oriented approach - treating data as a product with clear ownership, quality guarantees, and self-service access - addresses the failure modes typical of centralized data platforms. Drawing on a practical implementation, we discuss trade-offs between decentralization and central control, mechanisms for embedding data quality and semantic clarity, and the cultural shifts required. We argue that establishing trust in data is a precondition for productive AI agents, and that innovation managers should treat the data foundation as an innovation object in its own right.

Corporate Venture Units (CVUs) are founded with the explicit mandate to drive innovation. Yet how they navigate transitions between life-cycle phases remains theoretically underdeveloped and is, in practice, a primary driver of divergence in mid-sized enterprises. This challenge is particularly consequential for Hidden Champions, whose tightly coupled identities and lean governance structures amplify the stakes of every transition. Drawing on process theory, we conduct a qualitative cross-case analysis of two CVUs embedded in German Hidden Champions, grounded in 33 longitudinal semi-structured interviews from two preceding case studies. We trace three transition-specific dynamics, namely Relational & Communication, Strategic Alignment, and Survival & Integration, and demonstrate that trust and legitimacy, rather than structure or resources, are the decisive mechanisms at each turning point. Early trust deficits create path-dependent constraints that compound across subsequent phases, reducing successful reintegration. Our findings extend Birkinshaw et al.'s life-cycle model toward a process-level of CVU transition dynamics.

This abstract summarises a Health care innovation of a Stroke assessment scale (Swansea Stroke Scale) and its potential impact on future stroke care in the UK. This is a workplace-based research project binding clinical stroke medicine and innovation management, undertaken within a Business School context to explore how a new clinimetric tool can be designed, validated and implemented in a complex health system and its broader impact on the health service. The new stroke scale for non-specialists revealed strong validity and reliability against NIHSS by specialists; has good 30-day outcome prediction with wider implications in areas deficient of stroke specialists. The upskilling of non-specialist staff to plug the gap in specialists should equate to better patient care, experience and outcome. This could provide significant financial savings for the National Health Service.

This paper investigates how formal and informal power sources within SMEs' dominant coalitions affect innovativeness through absorptive capacity (AC), conceptualized through three dimensions: external knowledge acquisition, internal knowledge sharing, and transformation. In a survey of 363 SME managers across five English-speaking countries, we find that both formal and informal power sources affect innovativeness only indirectly through AC. Formal power is associated with internal knowledge sharing and transformation, while informal power is linked to internal knowledge sharing and external knowledge acquisition. Environmental dynamism moderates several relationships: the indirect effect of formal power via transformation strengthens under dynamic conditions, while the indirect effect of informal power via external knowledge acquisition weakens as dynamism increases. The study contributes to the literature by positioning power as a key antecedent of AC and by showing how distinct power sources within the dominant coalition link AC to innovativeness.

Smart products possess functional characteristics (e.g., autonomy, adaptability, reactivity, communicativeness) that sharply distinguish them from their non-smart counterparts. Consequently, they increasingly alter consumers' lifestyles and everyday practices. In this article, we examine why and how consumers adopt practices enabled by smart products, drawing on data from various actors and analyzing the influence of social context and interaction. We show that users perceive smart products as technological advancements that either substitute inefficient parts of existing practices or enhance these practices through congruent add-ons. We also demonstrate that users often acquire smart products to signal up-to-dateness, identity, and wealth. Reluctance to adopt new practices emerges in contexts where consumers attribute sacredness to elements of an existing practice. We propose a novel approach to characterizing adopter categories and conceptualize adoption as a transition period between mutually exclusive practices.

Digitalization is recognized as a key driver of productivity, competitiveness, and sustainability in manufacturing. Existing research has examined digitalization from a firm-level perspective, focusing on internal capabilities and barriers, while overlooking the broader socio-technical context. This study addresses this gap by applying the Multi-Level Perspective for analyzing how interactions between niche innovations, regime structures, and landscape pressures shape digitalization processes. A qualitative research design was employed, based on semi-structured interviews with managers from 19 medium-sized, export-oriented firms in Estonian wood and furniture sector. The findings show that digitalization remains fragmented and largely confined to niche-level initiatives. Barriers emerge from reinforcing interactions across levels: landscape shocks increase uncertainty, regime structures constrain scaling, and niche-level challenges hinder capability development. The study contributes to MLP literature by highlighting non-linear interplay, feedback loops, and the role of external shocks in shaping digitalization trajectories.

This study examines how economic embeddedness and technological dominance shape bilateral AI technology flows among five leading manufacturing powers in the global AI value chain. Traditional models rely on economic gravity and revealed technological advantage (RTA) to interpret cross-national exchange. However, AI-as a general-purpose technology dependent on cross-field complementarity and competitive bandwagons-challenges these assumptions. Using USPTO patent citations alongside gravity and RTA measures, this ongoing analysis traces the intensity, directionality, and architectures of AI knowledge flows. Findings reveal a sharply uneven and hierarchical exchange structure, demonstrating a decoupling between structural embeddedness and technological dominance. Flow architectures vary significantly: some dyads reflect co-produced value-chain integration, while others show asymmetric, layered extensions across computational, signal-processing, and semiconductor domains. Ultimately, gravity and RTA amplify AI exchange only under subfield alignment and sufficient absorptive capacity. This indicates that economic embeddedness and technological dominance are empirically separable forces in structuring international AI interdependence.

Cities today strive not only to be energy efficient, but also liveable and sustainable. The text highlights that previous projects have often focused solely on technical aspects and savings, but this is no longer sufficient for current challenges such as climate protection and social inclusion. It explains how new projects should be planned holistically, taking into account not only technical, but also social and environmental aspects. Various groups work together, including municipalities, citizens and utility providers. Projects are designed to achieve multiple objectives - for example, reduced energy consumption, improved quality of life and greater environmental protection. There are methods and tools available to help make decisions and measure impact. The aim is to share experiences and apply these approaches in further districts or cities.

Service interactions are increasingly shaped by artificial intelligence (AI), yet its capacity to create customer value varies across market segments. This study develops a value-contingent perspective on AI service innovation by conceptualizing AI adoption as the extent to which customers permit AI to participate in value formation. Drawing on a mixed-methods experimental vignette study across budget and premium segments, we show that AI visibility constitutes the evaluative dimension through which customers interpret the legitimacy of AI within the service encounter, while AI infusion reflects the degree of customer-permitted AI participation across interaction phases. The findings reveal a structural asymmetry: AI becomes value-generative where functional value expectations dominate, but remains value-supportive where symbolic and relational expectations govern the interaction. Cognitive biases further stabilize these segment-contingent patterns of value realization. By linking AI visibility, AI infusion, and customer value formation, the study advances a processual explanation of AI adoption in service innovation.

Global competition for leadership in frontier technologies is intensifying, and identifying the human capital driving innovation has become a critical challenge for innovation management. Yet conventional R&D monitoring lacks the granularity to track high-performing researchers and to delineate emerging technology domains. This study proposes an R&D landscape monitoring framework in which LLMs are systematically applied across three stages. In data refinement, LLMs curate a high-precision corpus aligned with the National Strategic Technology categories defined by the South Korean government. In researcher identification, LLMs reduce disambiguation noise by reconciling author records across Web of Science and OpenAlex, and by detecting ethnic Korean researchers at overseas institutions. We demonstrate the framework through a case study on quantum technology, one of twelve National Strategic Technologies designated by the South Korean government, offering a replicable blueprint for evidence-based science and technology policy.

Roadmaps have been examined as strategic tools for organisational development and, more recently, as tools for circular development. However, studies have not acknowledged how roadmaps for industrial circular development can capture the multi-level agency needed for sociotechnical change or how a design approach can strengthen such roadmaps. This study addresses these research gaps and develops a design-based roadmap for the construction industry to foster circular development through concrete element reuse. The main method is participatory action research. The primary contributions of this study are a strategic roadmap for concrete element reuse and a design-based framework for roadmap development, highlighting multi-level agency in circular sociotechnical developments. These contributions address both circular construction and circular development research.

This paper conceptualizes Infrastructure Digital Twins (IDTs) to function as innovation-enabling boundary objects for early-stage coordination in rural energy systems. Rural regions face significant coordination challenges due to fragmented actors, sectoral silos, and limited shared situational awareness. Using a design-science approach applied in the German State of Brandenburg, the study shows how IDTs integrate heterogeneous spatial and actor data into a modular, GIS-based artefact. Emerging insights indicate that IDTs facilitate cross-sector dialogue through interpretive flexibility, support AI-assisted exploration rather than optimization, and enable collective sensemaking. An illustrative corridor co-use scenario demonstrates how IDTs reveal ecosystem structures and enable alignment prior to formal commitments, addressing coordination failures in infrastructure innovation. These findings highlight practical pathways for scalable coordination, improving rural innovation capacity and inclusive decision-making outcomes.

Hidalgo, Lemus-Aguilar and Urueña (2021) identified seven innovation processes coexisting in consulting firms using a nine-firm Spanish sample, establishing the foundational taxonomy of innovation management in Professional Service Firms (PSFs). This paper extends that work in three directions. First, empirically: the original sample is expanded from 9 to 15 firms across Spain and Italy (17 semi-structured interviews), enabling the first cross-national comparative analysis of PSF innovation architecture. Second, theoretically: institutional logics theory is applied to explain why the PKIBS/ T-KIBS divergence documented by Hidalgo et al. (2021) is not merely structural but institutionally produced - specifically through an institutionally amplified competence trap operating via professional governance, legitimacy, and identity mechanisms. Third, conceptually: the Strategic Architecture construct is introduced as the deliberate organizational design through which PSFs navigate the innovation paradox. These extensions advance PSF innovation theory, ambidexterity research, and Open Innovation in services.

Emerging ecosystems often lack shared criteria for steering investments and actions toward sustainability. This paper analyses how a systemic impact framework was co-created as a governance tool in the early formation of the Magallanes green hydrogen ecosystem in Chile. Using a single in-depth case study, the project applies a participatory approach that combines document analysis, interviews, field engagement and co-creation workshops with a broad range of ecosystem actors from industry, government, academia and civil society. Through this process, a multi-criteria and multi-actor impact framework was co-created to provide direction for ecosystem development and to accelerate a transition that is economically viable, socially legitimate and environmentally responsible. We show how the framework works as an alignment and negotiation device that clarifies trade-offs and responsibilities, strengthens legitimacy, and supports prioritisation and monitoring across the three sustainability pillars. The study offers a replicable approach for impact-oriented orchestration of sustainability transitions in emerging ecosystems.

This study examines how and under what conditions green procurement influences firms' green innovation. While prior research largely assumes a linear and positive relationship between green procurement and innovation, this paper challenges that view by theorizing and empirically demonstrating a non-linear relationship. Drawing on organizational learning, knowledge search, and interorganizational knowledge transfer theories, we argue that green procurement initially enhances green innovation by facilitating learning from environmentally advanced suppliers, but that excessive reliance on such procurement generates diminishing and eventually negative returns. We further contend that this relationship is contingent on governance structures and supply network configurations. Specifically, we examine the moderating roles of state ownership, long-term institutional investor ownership, and supplier concentration. Using a large panel dataset of 15,248 firm-year observations of publicly listed Chinese manufacturing firms from 2009 to 2024, we find strong empirical support for our hypotheses. We discuss the practical and research implications of our findings.

This work-in-progress study investigates how an AI-based agent, guided by ISO 56002 as an interpretive and structural framework, can support practitioners in understanding innovation management as a dynamic and functioning organizational system rather than a static concept. While prior research has demonstrated the effectiveness of AI in enabling experiential learning in education and coaching contexts, its application within the domain of innovation management remains largely unexplored. The study proposes that an AI agent can enhance practitioners' recognition of value by generating immediate, personalized, and system-oriented reflection reports based on their inputs and interactions. To explore this hypothesis, a pilot study with 15 participants was conducted, assessing perceived usefulness through a structured 7-item follow-up survey. Preliminary results show significantly positive responses, suggesting that AI-enabled experiential engagement can meaningfully support practitioners in recognizing the value and relevance of innovation management systems in practice.

Artificial intelligence (AI) is increasingly used to support supply chain decision-making, yet little is known about how managers incorporate AI outputs into decision processes under uncertainty. This research-in-progress examines how AI assistance shapes managerial cognition and decision practices across Simon's intelligence, design and choice stages. Drawing on semi-structured interviews with 10 supply chain managers from manufacturing, logistics and retail sectors, the study identifies AI as a stage-differentiated cognitive amplifier. AI accelerates environmental scanning and information synthesis during the intelligence stage, expands scenario exploration and alternative generation during the design stage, and supports preliminary comparisons during the choice stage. However, managers retain final judgment due to data reliability, contextual interpretation, and accountability concerns. The study contributes a process-based account of human-AI complementarity and offers governance implications for responsible AI-enabled innovation management.

Identifying entrepreneurial culture as a part of an entrepreneurial ecosystem dimension is a challenging task. There have been attempts to define what entrepreneurial culture is. The cultural dimensions traditionally related to entrepreneurial activity are the common traits that nascent motives in combination of individual traits such as bricolage are antecedents of an entrepreneurial culture. The aim, first; to identify nascent entrepreneurial architypes and their constituent communities within an entrepreneurial ecosystem, second; analyze how nascent entrepreneurial archetypes motives act as antecedent form an understanding of culture in communities that form entrepreneurial ecosystems and finally; Identify a suggest a future research agenda for understanding culture and its composition in entrepreneurial ecosystem, furthermore, contributing and lay the foundation for comparative studies enabling a further advancement how to identify boundaries, layers individual, communities and system as well as the utility for the individual - context nexus within entrepreneurial ecosystem.

Public procurement represents 16% of EU GDP yet remains underutilized for innovation. The EU has developed three instruments, namely Pre-commercial Procurement (PCP), Public Procurement of Innovative Solutions (PPI), and Innovation Partnerships (IP), but uncertainty persists regarding optimal instrument selection. Through systematic literature review and comparative institutional analysis, we develop a contingency framework identifying six critical factors: innovation specificity, R&D-production externalities, value verifiability, SME ecosystem role, competition levels, and procurer competency. We find IP's bundled structure proves optimal only under restrictive conditions, while PCP demonstrates broader applicability. Procurement organizational capacity emerges as the binding constraint, with competency improvements from 10th to 90th percentile yielding 143% cost and 114% time performance gains. The framework provides evidence-based guidance for leveraging procurement to strengthen innovation ecosystems and network connections.

This paper develops a conceptual framework for understanding how Responsible Research and Innovation (RRI) becomes institutionalized within complex technological innovation networks. Focusing on additive manufacturing, the study draws on empirical evidence from multi-year European research projects and Delphi-inspired expert panels to examine how responsibility-oriented practices emerge, persist, and diffuse across organizations and innovation phases. Building on neo-institutional theory, the paper introduces the concept of RRI openings, defined as institutionalized points of intervention through which responsibility can influence innovation processes in situated ways. The analysis identifies key institutional carriers including regulation, incentives, standards, organizational knowledge and culture, and education, and shows how their relevance varies across phases of ideation, development, and diffusion. The findings demonstrate that responsibility does not become consequential through isolated project-level actions, but through institutional arrangements that stabilize learning and coordinate responsibility across time and organizational boundaries.

Innovation is increasingly recognised as an organisational capability that can be designed, governed, and developed systematically rather than left to chance. This paper presents a practical, assessment-led framework for accelerating strategic innovation through Innovation Management Systems aligned with ISO 56001, the first international requirements standard for innovation management. Drawing on combined expertise from Perfect Link and Amplify, the authors outline a structured approach across three phases-prepare, conduct, and conclude-that helps organisations establish a clause-by-clause maturity baseline, define their innovation intent and strategy, and build an executive dashboard for performance evaluation. The framework addresses common implementation challenges, identifies critical success factors, and provides actionable execution strategies for practitioners moving from fragmented activity to coordinated, sustainable capability.

This paper reports ongoing research into the role of generative AI (GAI) in supporting collective creativity during the problem framing stage of wicked problems. The focus is on innovative product launches, seen as an example of a wicked problem within innovation management. The research positions problem framing as the central thread linking all wicked problems and identifies it as a critical barrier in addressing such challenges. Using a systematic literature review based on PRISMA, the study introduces an initial conceptual framework. This framework illustrates how hybrid workflows involving humans and GAI might enhance the quality, diversity, and legitimacy of problem framings from a strategic perspective. By mapping the interplay between human judgement and GAI's generative capacity, the paper highlights the potential for hybrid approaches to unlock more robust and adaptable strategic options. The research aims to provide insights for scholars and practitioners seeking to improve decision-making in complex innovation environments.

Europe faces a critical "translation gap" where doctoral excellence in academia often fails to convert into industrial impact. While Industry 5.0 demands a blend of technical depth, sustainability, and human-centric design, traditional higher academic education remains siloed. This paper presents an approach from the Horizon Europe INSIGHT initiative to co-design modular competency pathways for early-stage researchers. Using a multi-methodological analysis framework, including expert interviews and co-design workshops, we propose a two-layer competency architecture. This layers foundational translational skills (communication, project management) with Industry 5.0 literacies (data governance, value creation). Rather than proposing fixed training tracks, the paper outlines emerging pathway directions and the design principles behind them: modularity, practical relevance, mentoring-rich support, and cross-sector applicability. Its contribution is a scalable way of researcher development towards useful real-world application.

We apply an explainable machine learning framework to predict near-term changes in innovation rankings across 141 economies based on the Global Innovation Index (2022-2025). Three predictive models were trained: a binary model to predict countries likely to enter the global top 25, an imbalanced model to predict top movers (]]=5 rank improvements), and a regression model to predict continuous rank changes using Random Forests with temporal cross-validation to avoid data leakage. SHapley Additive exPlanations (SHAP) were used to split individual predictions into interpretable indicator-levels. K-means clustering (k=4) categorized countries into different innovation archetypes, revealing within-cluster heterogeneity in the Gulf Cooperation Council (GCC). Knowledge & Technology Outputs and Business Sophistication were the dominant predictors of rank ascent globally. Human Capital quality and Creative Output were the binding constraints in the GCC. Counterfactual simulations conducted at the country level show that Bahrain has the highest mover probability (34.9%) among GCC states.

Innovation managers and policymakers face critical challenges prioritizing fundamental research investments in hyperdynamic domains where traditional foresight methods prove inadequate due to compressed technology lifecycles and bibliometric lag effects. This study presents a validated two-phase hybrid methodology combining expert interviews, quantitative surveys, foresight workshops, strategic sessions, and computational semantic analysis to identify and rank transformative AI research directions. Over 250 experts participated across both phases, producing a three-tier framework of nine priority areas, thirty-eight subareas, and 228 specific research tasks for fundamental AI development through 2028. Two novel analytical instruments - Euler Circles of Transformative Potential and a Research-to-Value Matrix - enable systematic categorization of research directions by breakthrough potential and socio-economic applicability. The methodology introduces "foresight velocity" as a critical organizational capability for innovation systems operating under accelerated change cycles, with demonstrated applicability beyond AI to quantum computing, synthetic biology, and other rapidly evolving technological domains.

The widespread adoption of autonomous vehicles (AVs) is expected to transform societal dynamics within the foreseeable future. Therefore, it is essential to identify emerging trends in AV technology research and development, as this enables industry practitioners and policymakers to forecast and proactively adjust their strategies, future development investments and regulatory frameworks. Since traditional topic modeling techniques are either time-consuming or limited in data access and in their ability to capture semantic relationships, this study introduces a novel, deep learning-based approach to topic modeling. Using real-world technology fair data guarantees a comprehensive data pool with state-of-the-art technology. The findings revealed seven macro-topics (MTs) and a four-layered modular architecture that is consistent with digital innovation, reflecting the industry's shift towards software-driven, service- and platform-based structures, rather than hardware-driven ones. Furthermore, the successful deployment not only validates the proposed methodology, but also yields a streamlined, transferable workflow for future trend analysis across domains.

Circular economy transitions, as an application of sustainable innovation, increasingly depend on collaboration among multiple interdependent actors. Yet research offers limited guidance on how such collaboration can be deliberately structured during the early emergence of circular ecosystems. Existing ecosystem and circular economy frameworks have improved understanding of orchestration, governance, and value creation, but they often remain descriptive, retrospective, or focused on isolated aspects of development. This paper outlines an ongoing study that addresses this gap by developing a preliminary process framework, the Minimum Viable Circular Ecosystem (MVCE), to support orchestrators in early-stage circular ecosystem formation. Drawing on ecosystem theory, circular economy research, value co-creation, and boundary object literature, we propose four interrelated phases of emergence: visioning, ecosystem framing, experimentation and learning, and structuring and governance. Using a design science research approach, the framework and associated tools will be iteratively developed and refined in the context of reusable packaging.

Media organisations today are under constant pressure to innovate and renew themselves. In this context, intrapreneurship offers a means of advancing innovation from within existing organisations by enabling employees to initiate, develop, and promote new ideas as part of their everyday work. This article examines how intrapreneurial practices support innovation in media companies. Drawing on a practice-based, multi-level framework, the study analyses intrapreneurial activity at individual, team, and organisational levels in two Finnish news media companies. The empirical analysis is based on a multiple-case study that combines semi-structured interviews with the Critical Incident Technique, focusing on situations that media managers consider critical for innovation in media work. The findings identify six intrapreneurial practices across multiple levels as well as their specific manifestations and the conditions shaping their occurrence. The article demonstrates how innovation in media work depends on the alignment and support of intrapreneurial practices across levels and organisational contexts.

Research core facilities are critical to scientific discovery, providing advanced instrumentation and expert support that enable high-impact pre-clinical research . Yet many face challenges with sustainability, visibility, and alignment due to unstructured growth and inherited legacy processes. These issues result in inconsistent operations, uneven administrative support, and difficulty demonstrating institutional value. To address this, we developed a hub-and-spoke administrative model in which a central hub delivers coordinated support across finance, marketing, legal services, business development, innovation strategy, and client experience. Individual core laboratories function as spokes, receiving tailored support based on their scientific goals and operational maturity. This dynamic system provides needed standardization while remaining flexible, helping institutions reduce fragmentation, build financial sustainability and strengthen research infrastructure.

This study examines the organizational transition toward the Circular Economy (CE) by analyzing the catalysts that enable and shape this process. While prior research has identified multiple drivers of CE adoption, limited attention has been given to their interrelationships. Addressing this issue, the study identifies ten key catalysts and applies the DEMATEL method to explore their causal structure and interactions. The findings reveal a distinction between proactive catalysts, such as CE-oriented leadership, institutional pressures, organizational agility, and market demand, and reactive catalysts, including technology adoption, organizational culture, and dynamic capabilities. Results highlight the systemic nature of CE transition, showing that change is driven by the interplay between internal capabilities and external pressures. By offering a structured framework of catalyst interactions, the study contributes to a more nuanced understanding of how organizations can effectively initiate and coordinate circular transformation.

In response to increasing socio-environmental challenges, organizations have turned to collaborative projects to integrate competencies, resources, and knowledge in the pursuit of innovative solutions. In this context, the ability to acquire, create, and combine knowledge becomes central. This study analyzes how knowledge-based dynamic capabilities (KBDCs) manifest through organizational practices in sustainable innovation projects. A qualitative approach was adopted, based on a single case study of a collaborative project between a Brazilian petrochemical multinational and a supplier. Data were collected through interviews, observation, and documents and analyzed using content analysis. The findings contribute by empirically demonstrating the operationalization of KBDCs, highlighting their impacts on the social dimension of sustainability, and offering managerial implications by identifying practices that support knowledge mobilization in collaborative projects.

This paper reports emerging weak signals from the Wood-to-Wood project, which examines how Europe's wood-based process industries can accelerate the transition towards a circular, innovation-driven and skill-intensive cascading system. As green and digital transitions reshape material flows, technologies and workforce needs, early indicators of disruption are often ambiguous, low visibility and difficult to detect through conventional data sources. Drawing on a horizon scanning survey with experts from academia, industry, policy and civil society, the paper identifies novel and uncertain developments with potential implications for the future of work, industrial innovation and circular value chains. The findings highlight weak signals across technological, environmental, economic, political, social and values-based domains, offering early intelligence for innovation managers. The paper contributes to ISPIM by supporting anticipatory governance, agile innovation pathways and cross-sector coordination in response to emerging industrial transformation pressures.

This study examines how Austrian retail companies systematically implement Artificial Intelligence to enhance efficiency, customer interaction, and competitiveness along the value chain. It adopts a multi-stage, peer dialogue-oriented research design that combines an ex-ante conceptualization with company-specific recommendations and an ex-post analysis based on eight expert interviews conducted after one year. The findings indicate that companies are still at an early stage of implementation and that organizational and cultural factors - such as management commitment, clear use cases, governance structures, and capability development - are more critical than purely technological issues. The study contributes a context-sensitive ex-ante and ex-post implementation perspective and provides evidence-based recommendations, emphasizing top management involvement, transparent data management, pilot projects, key-user concepts, and cross-functional learning processes to achieve sustainable value creation through Artificial Intelligence in retail.

This study examines how leading toy manufacturers LEGO, Hasbro, and Mattel develop and deploy dynamic capabilities in response to digital convergence. While the toy industry has long been shaped by physical products and analog play, emerging technologies such as media integration, video game integration, and augmented reality are reshaping the organizations. Building on Teece's dynamic capabilities framework, the study investigates how the three firms differ in sensing technological opportunities, seizing them through product and business model innovation, and transforming organizational structures and processes. Methodologically, the study is designed as a comparative multiple case study based on secondary data, including annual reports, investor presentations, product portfolios, and industry publications. The dataset covers coded initiatives from 2019 to 2025. Findings indicate distinct capability profiles: Hasbro emphasizes sensing most strongly, Mattel shows a comparatively balanced profile, and LEGO focuses more selectively on seizing and transforming.

This study examines how employees apply action research models to support their personal development during periods of organisational change. It investigates the extent to which various action research models influence their growth in communication, leadership, creativity, and time management; the barriers most strongly associated with lower success in short-cycle personal action research; and how the number of reflective cycles relates to behavioural shifts. Employing secondary analysis of 86 personal development projects, the McMurray-Ryan model appeared most frequently (56.6%) and was valued for its adaptability. However, model type did not significantly affect behavioural outcomes, indicating that the primary driver of being innovative in learning and behavioural change is consistent, rather than choice of action research framework. The most common barriers for personal change included limited time, discomfort with initiating change, and either narrow or underdeveloped action plans.

European competitiveness increasingly depends on the ability of firms and regions to identify, interpret and apply emerging technologies in a timely way. For small and medium-sized enterprises (SMEs), however, strategic foresight often remains abstract. Limited resources, fragmented support services and insufficient access to experimentation environments make it difficult to translate foresight into concrete development actions. This paper presents a practice-based case from South Savo, a sparsely populated region in South-Eastern Finland, where shared research, development and innovation (RDI) infrastructures and the regional digital innovation hub DIH eSavo have been developed to support SME renewal and digital transformation. The paper propose that foresight becomes actionable when it is embedded in accessible test environments, brokerage mechanisms, differentiated service pathways and ecosystem events. It argues that shared RDI infrastructures can function as foresight-executing environments that help SMEs translate megatrends into experimentation, capability building and step-by-step development pathways.

Innovation ecosystems are increasingly recognized as central vehicles for value creation, yet the nature of innovation within ecosystems remains undertheorized, particularly at early stages of development. Prior research often treats innovation implicitly as an outcome or a process, offering limited insight into how innovation emerges through interaction among ecosystem actors. This study addresses this gap by examining innovation as an interaction-based phenomenon in a birth-stage innovation ecosystem. Adopting an ecosystem-as-structure perspective, the study draws on a qualitative single-case design based on semi-structured interviews with B2B SMEs participating in an emerging Finnish innovation ecosystem. The findings conceptualize innovation as innovation-as-interaction-outcome, encompassing both tangible outcomes (joint offerings, processes, and market access) and intangible outcomes (relational, mental, and hunch spaces). The study advances an interaction-centered understanding of innovation and contributes to innovation ecosystem management research stream by highlighting innovation as both outcome and enabler in nascent ecosystems.

This work-in-progress project presents a strategic mapping initiative to develop an integrated atlas of productive and innovation capacities within Mexico City's health ecosystem. Motivated by structural weaknesses exposed during the COVID-19 pandemic, the project addresses fragmentation, limited coordination, and the lack of integrated diagnostic tools for guiding health-related industrial and innovation policy. The atlas will identify, classify, and georeference capabilities across pharmaceutical manufacturing, medical devices, research laboratories, hospitals, universities, and technology transfer infrastructures. Methodologically, it combines structured surveys and interviews with secondary analysis of regulatory databases, patents, publications, and trade statistics, alongside Technology Readiness Level assessment. It also introduces indicators of articulation and inclusiveness, including gender and age dimensions, to increase the visibility of women-led initiatives and early-career researchers. The project contributes to innovation ecosystem research by offering a policy-oriented, replicable model for metropolitan regions seeking to strengthen health sovereignty and industrial resilience.

Creative clusters are innovation hubs where art and entrepreneurship intersect. As a result, creative clusters grapple with a the freedom paradox which represents the tension between facilitating organic artistic expression and ensuring economic viability. This study focuses on how clusters manage the paradox through the lens of organizational ambidexterity. Based on a multiple case study of four Dutch clusters (TAC, Hubert, Vogelfrei, and Keilewerf), this paper demonstrates the shift between contextual and structural ambidexterity. Preliminary findings point to the emergence of buffer entities, management layers that shield creatives from commercial pressures. This paper contributes to innovation management by applying ambidexterity theory to informal networks and offering a the buffering role of management as a framework for balancing hybrid organizational goals.

This seminar addresses the innovation management challenge of translating UK academic AI research into scalable, responsible ventures, focusing on lessons from the National Responsible AI Accelerator (AIR26). Despite strong research output, only a small proportion of UK academics form AI startups, a gap exacerbated by London's dominance in AI firm concentration and investment. AIR26 was established to address systemic barriers by supporting academic founders across all UK regions to transition responsibly from lab-based research to real-world AI ventures. Delivered through a national collaboration of universities and innovation partners, AIR26 combines responsible AI principles with venture acceleration while tackling regional capability, network, and investment disparities. The session will interest innovation management scholars, ecosystem builders, and policymakers concerned with university-based commercialisation, regional development, and AI governance. The presentation shares early reflections, challenges, and design insights from AIR26's first year and seeks to foster international dialogue and collaboration on responsible AI entrepreneurship.

This study examines how risk-reducing institutional arrangements enable corporate spin-offs, particularly in cross-industry contexts. We develop the concept of asymmetric incentives in corporate spin-offs, highlighting the divergence between employee entrepreneurs, who avoid high-risk ventures, and parent firms, which prefer to externalize non-core businesses. We argue that secondment-based entrepreneurship-allowing employees to launch spin-offs while retaining employment and income security-reduces individual-level risk and facilitates cross-industry entry. Using data on 62 spin-offs from a Japanese government program, we find that 82% entered industries different from their parent firms. We further show that inherited capabilities have heterogeneous effects on innovation: new business development experience supports both radical and incremental innovation, growth orientation promotes radical innovation, and transformative orientation discourages incremental innovation. These findings underscore the importance of institutional design in shaping entrepreneurial behavior and innovation outcomes.

Circular business model (CBM) research has identified many drivers and barriers, yet firms still struggle to turn circular ambitions into viable pathways. Our study advances an activation configuration view in which viability depends on co-occurring drivers and barriers that are linked to enabling mechanisms such as contracts, incentives, data governance, and ecosystem coordination. Drawing on 22 expert interviews in Finnish manufacturing firms pursuing value-retention strategies, we trace recurring configurations behind three pathways: lifecycle extension services, product cycling, and system recirculation through recycling and side-stream ecosystems. Preliminary results indicate that customer-value metrics such as uptime, service and monitoring capabilities, return governance for take-back and quality assurance, and ecosystem-level standards and infrastructure jointly shape pathway activation. The study contributes an actionable configuration map and propositions to guide pathway selection across industries.

Innovation teams depend on sustained learning, yet the conditions that enable it are fragile and dynamic. This study aims to examine how psychological safety and accountability co-evolve in innovation teams over time and what mechanisms drive drift in and out of the "learning zone" - the team climate where both conditions are simultaneously high. While research has established the individual importance of psychological safety and accountability for team learning, their joint dynamics remain underexplored. Responding to calls for process-oriented research on both constructs, this study aims to surface the patterns and mechanisms through which these team learning conditions erode or are sustained. The findings may help innovation leaders recognize early signals of deterioration and act before innovation performance declines.

This study investigates the impact of perceived understaffing on individual innovative behavior within the context of Japanese R&D professionals. Distinguishing between manpower understaffing and expertise understaffing, the research examines how these stressors influence innovative behavior and the moderating role of the work environment. Utilizing data from 260 R&D professionals, the results reveal that perceived manpower understaffing positively relates to innovative behavior, suggesting it can act as a constructive pressure. Conversely, expertise understaffing showed no direct significant effect. However, the study identifies critical environmental moderators: challenging tasks, interest fit, and constructive controversy effectively transform perceived understaffing into positive innovation outcomes. These findings suggest that managers should accurately diagnose the nature of understaffing and provide tailored job resources to leverage understaffing as a driving force for innovation.

This study examines how leading toy manufacturers LEGO, Hasbro, and Mattel reconfigure their business models in response to emerging digital technologies in the toy industry. Using a multiple case study approach, we analyze 18 products across media integration, video game integration, and Augmented Reality. Building on Foss and Saebi's business model innovation framework, we compare changes in value creation, value delivery, and value capture according to scope and novelty. First findings show that LEGO mainly implements architectural innovations new to the firm. Hasbro combines modular and architectural changes and delivers several products new to the industry, providing the only complex business model innovation in the sample. Mattel is characterized primarily by modular innovations, with some new-to-the-industry cases. Initial analysis suggests that a refined framework may more accurately classify BMI across the three firms. Such a framework may reveal, for example, that LEGO can be characterized as a strong fast follower.

This paper presents a conceptual Delphi-BCG framework to strengthen Entrepreneurial Discovery Processes (EDPs) within Smart Specialisation Strategies (S3) in small, open economies. It integrates expert-driven foresight with portfolio-level prioritisation to address fragmentation across industrial, innovation, and spatial policies. By combining Delphi and BCG approaches, the framework identifies emerging technological opportunities and uncertainties in regional energy ecosystems while generating actionable policy insights. Applied to the Finnish energy cluster, it highlights key domains including small modular reactors (SMRs), hydrogen, and advanced heat solutions towards 2045. "Star" areas include system-level energy optimisation, industrial waste heat recovery, high-temperature heat pumps, electricity storage, and direct current networks with smart microgrids. The framework supports targeted RDI investments, SME collaboration, and alignment between national and regional priorities, while helping policymakers manage uncertainty, prioritise investments, and advance industrial renewal and the green transition and profitable growth.

This paper examines how Japan's 2004 incorporation of national universities transformed university patenting and organisational intellectual property management. Using university-level panel data, it analyses patent applications, requests for examination and registrations, comparing national and private universities and examining post-incorporation financial indicators. The results show that national universities shifted to a higher level of organisational patent activity around 2004, with effects appearing sequentially across the patenting process. The increase was not confined to a few leading universities but was accompanied by a broader expansion of the patenting base. Supplementary analysis suggests that external funding and financial scale are associated with applications and examination requests. The findings contribute to international discussions on university intellectual property, technology transfer and innovation policy.

Although M&A activity has grown substantially, many acquisitions fail to deliver anticipated value. This challenge is particularly acute when acquirers and targets exhibit divergent strategic orientations. Drawing on the theory of generic strategies-operational-excellence, product leadership, and customer intimacy-we argue that strategic positioning alignment enhances acquisition performance. While prior studies focus predominantly on resource relatedness and cultural fit, we extend this literature by examining strategic positioning alignment as a market-facing dimension of firm compatibility. Analyzing 349 M&A deals among Japanese listed firms completed between 2003 and 2024, we employ textual analysis of annual securities reports to quantify strategic positioning. Results based on cumulative abnormal returns (CAR) and return on assets (ROA) indicate that overall alignment does not significantly influence performance. However, within the same industry, alignment enhances CAR when both firms share a product leadership or operational excellence orientation. These findings offer practical guidance for target selection.

Contemporary polycrisis demands reimagining economic futures beyond sustainability's exhausted paradigm. Drawing on the concept of social imaginaries, this research argues that resilient and regenerative futures emerge not from technocratic planning but from transforming how people imagine their social existence and collective possibilities. While national foresight networks primarily engage policy elites and technical experts, this study extends foresight democratization by including traditionally marginalized actors - craft communities, regenerative farmers, repair networks, and commons-oriented cooperatives. We ask: how can participatory scenario planning contribute to increasing adaptive capacity among regenerative community actors? Integrating horizon scanning, divergent scenario development, and reflexive visioning, the methodology reconceptualizes stakeholder workshops as sites for cultivating imaginative capacity. The research contributes methodologically by operationalizing diverse economies, and theoretically by bridging strategic foresight, degrowth, and regenerative development scholarship to cultivate regenerative cultures grounded in community agency.

This research examines how organizations in the United States jointly address sustainability and resilience within their innovation strategies to ensure long-term financial stability. We conducted qualitative research within firms in the US with specialized knowledge of industrial standards. Other than initially expected, firms show a strong response to sustainability issues whereas resilience strategies were generally less developed. Our evidence showed that this had a detrimental impact on the firm's innovation strategy. Still, resilience sells better to costumers. Hence, our findings suggest that only the combination of sustainability and resilience within an organization's strategy sufficiently prepare for the future. However, whereas resilience is less anchored in corporate processes, sustainability highly depends on external factors. We therefore aim to develop a parsimonious model that consistently integrate both approaches into a combined strategy.

Innovation systems research traditionally emphasizes formal collaboration among universities, industry, and government, as explained by the Triple Helix model. However, most studies remain institution-centric, focusing on formal governance structures such as policies and contracts, providing limited insight into the relational processes that enable collaboration and knowledge exchange. To address this gap, this study adopts a microfoundational perspective to examine how informal relational mechanisms support collaborative innovation. Drawing on social capital theory and relational governance, the research conceptualizes informal mentorship, alumni engagement, and faculty industry interactions as mechanisms that foster trust and informal knowledge exchange. Using a multi-actor survey of faculty, industry mentors, and alumni involved in university industry collaboration, the data were analyzed with Partial Least Squares Structural Equation Modeling. Results show that informal relational mechanisms strengthen trust and knowledge exchange, which in turn enhance collaborative innovation performance.

Academic spin-offs play a critical role in translating university research into economic and societal value. These ventures are highly context-dependent and are often founded by faculty members who must balance academic responsibilities with venture development, limiting the attention they can devote to the firm. Prior research has paid limited attention to how entrepreneurial ecosystem conditions shape founders' attention allocation. Drawing on the attention-based view of the firm, this study examines how ecosystem-level conditions influence founders' attention allocation in emerging ecosystems. Based on a qualitative longitudinal study of 18 ASOs in Greece and 78 interviews with founders and ecosystem actors, our findings show that ecosystem conditions redirect founders' attention toward fundraising, administrative coordination, and compliance activities rather than market development and commercialization. By identifying attention allocation as the mechanism linking ecosystem conditions to venture outcomes, the study explains why ASOs in emerging ecosystems often experience delayed commercialization despite strong technological potential.

Research costs have risen exponentially in recent decades, while scientific organizations' productivity has declined, slowing overall innovation [1]. Transition to open R&D - through collaboration, knowledge sharing, and joint use of scarce resources - is seen as a key way to reverse this trend [1,2,3]. However, effective participation in open R&D first requires strong internal management. Without streamlined processes, organizations risk losing intellectual property control, wasting resources, and facing personnel issues. Traditional hierarchical structures have proven inefficient in today's dynamic environment. Matrix management offers a better alternative by enabling strategic planning that accounts for complex patterns, proactive staffing solutions, and flexible task allocation [4]. Participatory management, involving employees in decision-making, further boosts motivation, job satisfaction, and engagement [5,6,7]. Therefore, in our opinion, the implementation of matrix and participatory management can contribute to improving the management effectiveness of scientific organizations. Previous studies have examined in detail the outcomes of changes in organizational structure. However, studies focusing on organizational changes in healthcare research organizations are currently limited and primarily theoretical. Furthermore, we were unable to find any studies devoted to the practical assessment of the effectiveness of implementing comprehensive matrix-participatory management mechanisms in medical research organizations. The purpose of this study is to analyze the results of implementing these approaches in a scientific organization as a necessary foundation for the transition to open R&D.

The future of energy is largely anticipated to be decentralised. Recent developments in renewable energy have driven this trend of decentralisation in terms of distributed generation and democratisation of power. However, these trends have started to slow, sowing doubt as to the degree of decentralisation in future energy systems. This study analyses the last ten years of the installed electricity mix in Sweden and the ownership thereof. Furthermore, an outlook thereto is provided by reviewing trends driving both increased centralisation and decentralisation. Findings show that renewable energy development is increasingly of a centralised form, and the ownership of distributed generation is slowly consolidating. These findings confirm the suspicion that the future is not inherently as decentralised as once anticipated. Implications thereof emphasise how centralised and decentralised infrastructure co-evolve. Further development in policy is required to price in the positive externalities of decentralised infrastructure and thus support neutral development.

Researchers in non-technical disciplines of social sciences, humanities, and arts (SHAPE), face a profound paradox. They are tasked with addressing complex societal grand challenges, however, evaluated using restrictive, science, technology, engineering, and mathematics (STEM) centric metrics. These traditional frameworks conceptualise impact linearly, failing to capture the qualitative, experience-based transformations generated by non-technical research. To address this disconnect, this conceptual paper shifts the ontological focus from impact as a static, linear noun to "impacting" as a dynamic, relational verb. Drawing upon the principles of engaged scholarship and the performative nature of theory, we propose a novel iterative phase process model that focuses on relational immersion, performative tinkering, and reflexive adaptation. This framework unpacks the micro-mechanisms of academic-practitioner collaboration, demonstrating how researchers and stakeholders can dissolve entrenched dualisms to co-create sustained, generative societal impact. Ultimately, this process model offers a reconceptualisation of academic engagement and roadmap for redesigning institutional evaluation systems.

This study explores how leadership behaviours shape the relationship between organisational digital skills and digital maturity in the context of digital transformation (DT). Based on ambidexterity and behavioural leadership theories, DT ambidexterity is conceptualised through digital competence (exploitation) and digital innovation (exploration). We introduce balanced leadership-a versatile behavioural orientation integrating task-, relations-, change-, and external-oriented behaviours-and assess its moderating role in converting these capabilities into digital maturity. Using survey data from 301 Finnish SMEs and hierarchical regression analysis, we find that both digital competence and digital innovation positively influence digital maturity. However, balanced leadership moderates these relationships in opposite ways: it strengthens the effect of digital innovation but weakens the effect of digital competence. This suggests that leadership versatility supports innovation-driven progress but may impede competence-based development. The findings highlight the importance of phase-specific leadership approaches in DT and contribute to ambidexterity and leadership research.

Preventive health challenges, from chronic disease risk to health inequalities, extend well beyond the remit of any single actor. They span across public authorities, healthcare providers, community organizations, firms, citizens, and investors, and siloed interventions consistently fall short. While systems thinking has shaped how we understand these interdependencies, its attention to the social and relational work through which coordination happens on the ground, has been limited. Collaborative spaces, and digital platforms in particular, are increasingly positioned as arenas where stakeholders align around shared values and goals. Their flexibility, scalability, and capacity for asynchronous engagement make them well-suited to the sensitive, and data-fragmented nature of preventive health, though governance complexities may complicate their design and use. Moreover, their system-level role remains under-theorized. In this study, we study how digital collaborative platforms enable stakeholder management and co-governance in multi-stakeholder preventive health initiatives, drawing on the perspectives of users, operators, and investors.

Innovation management research has extensively examined knowledge diffusion and recombination, yet it remains unclear why innovation emerges selectively at specific boundaries. This study proposes a framework in which innovation is driven by the interaction between knowledge diffusion (flow) and selective recombination (filter) at technological boundaries. Drawing on reaction-diffusion logic, we conceptualize innovation systems as dynamic fields where knowledge spreads across domains while boundary conditions determine which combinations are retained. To provide initial empirical grounding, we conduct an exploratory patent analysis using PATSTAT, focusing on automotive (B60) and AI (G06N) technologies. Results show that while both domains exhibit high diffusion, boundary patents display high diffusion but significantly lower diversity, indicating selective recombination. These findings suggest that innovation depends not only on openness but on the design of boundary filters, shifting the focus of innovation management toward effective selection mechanisms.

This study develops a quantitative framework to compare individual purchasing, Group Purchasing Organizations and Food Hubs for SMEs operating in perishable food supply chains. It addresses the practical challenge of identifying which cooperative procurement and distribution structures improve profitability for different SME buyers under specific spatial, operational and service conditions. The models integrate buyer-level inventory decisions, storage constraints, routing, consolidation, clustering thresholds and cost-sharing logic, enabling consistent comparison across cooperative schemes. Numerical experiments vary buyer size, spatial dispersion and delivery frequency requirements to assess profitability and distributional effects. Findings suggest that cooperative participation generally improves SME profitability, but benefits differ by design and buyer characteristics. Food Hubs tend to create stronger gains for small and medium buyers through shared logistics and flexible coordination, while Group Purchasing Organizations are more advantageous for larger buyers able to exploit procurement scale. The study offers decision guidance for SMEs, cooperative organizers and regional food-system stakeholders.

This contribution examines how human-centred innovation leadership can translate cultural diversity and AI capability into implementation-oriented outcomes. It draws on an action research case of Bridging Cultures, a one-year facilitation-based innovation programme implemented in 2025 at the Fraunhofer Institute for Applied Optics and Precision Engineering. International and interdisciplinary teams worked on real research and development challenges through six sequenced workshops, continuous facilitation, expert input and AI-supported activities across sensemaking, ideation, prototyping and early implementation. Based on facilitator field notes, team artefacts, reflective sessions and structured learning loops, the study conceptualises innovation leadership as an emergent collective practice embedded in organisational culture. Findings identify three enabling mechanisms: psychologically safe intercultural spaces, facilitation practices that align collective sensemaking with experimentation, and AI tools acting as relational and cultural mediators within socio-technical innovation systems.

This study examines how imitation as a source of innovation enables companies to create circular innovations. Although imitation is an established approach to innovation, it has not yet been studied in connection with circular innovation and development. This qualitative study reviews relevant literature on imitation and examines, through a multiple case study, how companies develop innovative solutions, that is, circular innovations, in response to their need to initiate and develop circular practices. The results identify four different strategies where existing resources are used in new ways for circular innovation. As a contribution, this study develops a novel matrix framework on imitation strategies for circular innovation. This framework guides future research on circular innovation and supports companies in seeking and developing innovative solutions in the circular transition.

Across daily life, business, and organizational settings, generative artificial intelligence (GenAI) tools have become widely accessible, enabling users to automate tasks, accelerate output, and pursue new forms of value creation. Yet this rapid diffusion marks a profound break from traditional ways of working. GenAI is reshaping job descriptions, altering skill requirements, and challenging long-standing assumptions about human contribution to organizational tasks. For many workers and leaders, these shifts arrive as a shock, raising concerns about task displacement, workforce reduction, and broader societal instability. While the benefits of GenAI adoption may ultimately outweigh its risks, the pace of change has outstripped the development of clear guidelines for how individuals and organizations should position themselves in relation to these technologies. This uncertainty underscores a critical gap: understanding not only what GenAI can do, but what human capabilities are required to engage with it responsibly, creatively, and productively. This study addresses that gap by identifying the knowledge, skills, abilities, and other attributes (KSAOs) that characterize pioneering GenAI users who are already translating these tools into meaningful innovation outcomes.

Innovation strategy becomes more effective when ambition is translated into clear choices, coherent direction, organisational learning and a credible path to value creation. This paper presents a principle-driven strategy blueprint that helps organisations structure innovation strategy as a practical system of decisions and execution conditions. The blueprint combines the innovation management principles articulated in ISO 56000 with the What, When, Who, Where and How questions from Tidd and Bessant's search strategy logic. Rather than proposing a measurement framework, it offers a fill-in structure that produces four core artefacts: a strategy narrative, explicit bets and trade-offs, a governance and operating model, and a learning loop. An anonymised ICT services case illustrates how the blueprint can clarify strategic choices, reduce fragmentation and support progressive adoption of standard-informed innovation management practices. The paper contributes a lightweight, transferable approach for making innovation strategy execution-ready by design.

The industrial metaverse is transforming industries like manufacturing, transportation, and utilities. By leveraging VR/AR/MR, 5G, and AI, companies are adopting industrial metaverse applications to enhance productivity, accelerate green transitions, and create new value for customers. This technology offers significant potential for improved planning, testing, and operations, leading to better decision-making and enhanced worker safety. This paper provides empirical evidence across multiple industry verticals regarding their expected business benefits related to digital twin utilization. Based on the analysis conducted by the authors, the business benefits of digital twins can be divided into the following categories: 1) Operational efficiency and optimization, 2) Enhanced learning, safety, and risk mitigation, and 3) Sustainability. The preliminary results show that both expected benefits and challenges vary among the industry verticals. This highlights the need to deeply co-create, test, and validate the selected use cases together with partners to capture value.

This study examines gender-based differences in perceptions of Australian manufacturing work and how these shape expectations of the future workforce. The problem addressed is the persistent gender inequality in manufacturing and the future in Australia, considering inclusive innovation and the adoption of advanced manufacturing technologies. The study aims to identify how men and women differ in their views of job quality, organisational practices, and technological change. Using a national survey of 2,252 economically active Australians, adapted from the UK Public Perceptions of Manufacturing instrument, the analysis applies descriptive statistics and comparative tests to explore gendered patterns. Results show significant gender differences in job-choice priorities, perceptions of current manufacturing roles and expectations of digital transformation. The study contributes new evidence linking gendered workforce perceptions to Manufacturing 4.0 and 5.0, offering actionable insights and a pathway model for designing inclusive workforce strategies that address skill shortages and support innovation.

Artificial Intelligence (AI) is increasingly adopted by organisations in innovation management, leading to manifold impacts (Gama and Magistretti, 2025; Mariani et al., 2023) across several industries, including Educational Technology (EdTech). AI is reshaping the education field as we know it, often manifesting as adaptive learning systems, intelligent tutoring systems, and analytical tools for predicting student performance (Guan et al., 2020; Zawacki-Richter et al., 2019). Despite these promising applications, significant barriers impede the effective and equitable deployment of AI, with literature emphasizing the need for inclusive and context-sensitive AI strategies to ensure broad societal benefits and mitigate unintended consequences for education (Bulathwela et al., 2024; Dionisio et al., 2024). Thus, merging AI developments with social innovation (SI) principles in education could bring about novel solutions that lead to new or improved capabilities and relationships, thus more equitable, inclusive, and effective learning ecosystems. Nevertheless, there is a lack of literature exploring how AI-powered solutions can be a catalyst for socially innovative educational models and EdTech developments, considering the crucial elements of the SI process, such as mobilising actors and resources, creating sustainable value, envisioning societal change, and disseminating solutions to be easily accessible (Ramkissoon, 2024).

Living Labs (LLs) have emerged as key instruments for user-centred, real-life innovation, yet their evaluation remains fragmented and largely focused on outputs rather than processes. This paper addresses this gap by proposing a process-oriented evaluation framework that integrates organisational and methodological dimensions within a coherent analytical structure. Developed through a two-phase approach combining a literature-informed design with participatory validation in European research and innovation projects, the framework conceptualises evaluation indicators as constructs operationalised through structured questionnaires. It enables the systematic assessment of LL processes across contexts while capturing their dynamic and evolving nature. By shifting the focus from outcomes to underlying processes, the framework supports comparative analysis, learning, and improved governance, contributing to a more robust and practice-oriented understanding of Living Lab performance.

The circular economy (CE) is increasingly promoted as a systemic approach to achieving sustainability across industries and societies. Within this transition, the European Union is advancing regulation under the Ecodesign for Sustainable Products framework that will require most products placed on the EU market to introduce the Digital Product Passport (DPP) as a policy and technical instrument designed to provide detailed product information to support reuse, recycling, and resource efficiency across product lifecycles. Despite strong policy momentum, research on DPP is dominated by policy reports and grey literature rather than theory driven academic studies, which remains fragmented. This research adopts a systematic literature review to address how existing studies define and implement DPPs across sectors and identify outcomes, theoretical bases, and knowledge gaps. By doing so, this research aims to provide a cross-sector synthesis and conceptual framework for future research.

Many mid-to-large businesses face systemic challenges due to an operational reliance on lagging innovation metrics, such as past revenue or total patents filed, to evaluate institutional progress. Unfortunately, these numbers primarily capture retrospective outcomes rather than providing proactive insight into an organization's capability to adapt during times of high uncertainty. While current research focuses extensively on the compliance requirements of ISO 56001, limited empirical work examines how to utilize the ISO 56004 framework as a leading diagnostic mechanism. This research idea outlines an open-cohort study proposal designed to investigate innovation routines across mid-to-large international companies. By exploring an asynchronous Innovation Readiness Assessment to capture daily employee perceptions of organizational routines, the study examines if baseline readiness data can offer insights into long-term innovation adaptability. This early-stage research idea focuses on refining baseline metrics and identifying collaborative enterprise partners.

Co-creation is widely recognized as a key mechanism for sustainable innovation, yet its depth varies significantly across living lab environments. This study examines 40 living labs, including virtual, hybrid, and place-based settings, to analyze patterns of co-creation and the role of artistic practices. Using qualitative analysis, the research develops a structured framework assessing co-creation depth, actor diversity, and stage involvement. The findings identify three modes of co-creation-technical, participatory, and strategic-and show that sustainability-oriented labs exhibit deeper and more inclusive engagement. Artistic and design-led practices are consistently associated with higher co-creation depth, particularly in early-stage processes such as problem framing and ideation. Rather than establishing causality, the study highlights how art operates within broader socio-technical configurations that enable reflexive and inclusive innovation processes. The paper contributes a typology of co-creation and offers insights for designing more effective living lab environments.

Healthcare innovation networks comprise diverse stakeholders, are often loosely coupled, and operate in complex and uncertain environments posing significant challenges for orchestration. Extant research explores orchestration predominantly from the orchestrator's perspective, and there is limited understanding of how network members experience and collectively influence orchestration over time. We use qualitative, longitudinal data from a Nordic innovation network to investigate the collective dynamics of orchestration and answer the question of how does orchestration unfold in loosely coupled healthcare innovation networks? Our findings indicate that orchestration unfolds through interactions of orchestrator's and orchestratees' activities, hence revealing broader mechanisms of emergence: collective sensemaking, value integration and securing continuity. Each mechanism is driven and kept in motion by internal and external catalysts that shape the direction of the network over time. Contributing to prior knowledge, this study moves beyond hub-centric conceptualizations of orchestration and reveals relevant new dimensions and mechanisms of orchestration.

The changing geopolitical landscape has led to a growing relevance of dual-use startups. Yet, the drivers of entrepreneurial intentions in this context remain insufficiently understood. While prior research has predominantly focused on civilian entrepreneurship, this study addresses the emerging gap by examining the configurational interplay of individual and contextual factors influencing the intention to found dual-use ventures. Drawing on a dataset from members of a university of armed forces, the study applies fuzzy-set Qualitative Comparative Analysis (fsQCA) to reveal the combinations of factors that lead entrepreneurs to found a dual-use startup. The findings reveal, for example, that political orientation and prior military experience play a significant role. The study highlights the motivations in dual-use entrepreneurship and thus contributes to innovation management theory and additionally offers practical implications for universities, policymakers, and innovation managers aiming to foster dual-use entrepreneurship. Keywords: dual-use entrepreneurship, entrepreneurial intentions, fsQCA, political orientation, military experience, innovation management

The circular economy (CE) is increasingly promoted as a response to resource overexploitation and planetary boundary constraints, emphasizing restorative and regenerative biological material flow cycles. While CE distinguishes between technical and biological cycles, existing research on circular ecosystems predominantly focuses on industrial and technical systems, leaving biological cycles and biophysical material flows underexplored. Building on natural resource circularity and industrial ecosystem perspectives, this paper expands the scope of CE systems by integrating extractive sectors within a social-ecological systems (SES) framework. We investigate how mining companies design and manage geo-bio-chemical material flow processes across site-level and industrial-ecosystem-level systems using holistic CE system design and regenerative technologies. The study develops a conceptual model that links natural and social capital with circular material flows, demonstrating that value creation in circular mining depends not only on industrial coordination but also on the reconfiguration of regenerative material flow processes embedded within SES.

This study investigates how Virtual Reality (VR) onboarding functions as a digital innovation to enhance newcomer organizational socialization. By integrating Diffusion of Innovation (DoI) theory with organizational socialization literature, we develop and test a process model linking VR experience qualities-presence and usability-to perceived innovation attributes (relative advantage, compatibility, complexity, trialability, and observability), and subsequently to newcomer adjustment outcomes. Using survey data from 375 newcomers exposed to VR onboarding, we use a two-stage analytical approach that combines measurement validation and path analysis. We examine indirect effects whereby experience qualities shape innovation perceptions, which in turn predict role clarity, self-efficacy, social acceptance, and cultural understanding. Results indicate that presence and usability enhance favourable innovation perceptions, thereby accelerating integration. By clarifying this "innovation-to-integration" process, the study contributes to digital innovation research in HRM and offers a framework for assessing the organizational value and adoption of VR onboarding solutions.

The COVID-19 pandemic exposed significant weaknesses in health system preparedness, particularly in data readiness, governance and cross-organisational intelligence. Although resilience frameworks are widely used, they give limited attention to the role of data and analytics as core enablers of innovation and system resilience. This study examines the role of data and intelligence in supporting pandemic preparedness in the Welsh health system, drawing on experiences from the COVID-19 response. Using qualitative semi-structured interviews with analysts, clinicians, policy leads and senior managers, the study explores how data was used during the pandemic. Emerging findings highlight an over-reliance on reactive data mobilisation, governance delays, fragmented documentation and a heavy dependence on tacit knowledge, reflecting challenges observed internationally. The research proposes a Data-Driven Resilience Framework that positions data infrastructure, governance and analytical capability as central to crisis response and innovation. The findings offer practical insights for strengthening preparedness and decision-making for future pandemics.

Sustainability-oriented innovation (SOI) in frontier regions is hindered by weak institutions, fragmented value-chain infrastructures, and limited technical and financial resources. This paper examines how people-centred innovation (PCI) contributes to the development of sustainable agroforestry value chains in an Amazonian context where non-state actors play a central orchestration role. Drawing on an exploratory qualitative case study of an emerging agroforestry coffee initiative, the research analyses how lived experience, iterative adaptation, and knowledge co-production shape value chain formation under conditions of institutional fragility. Preliminary findings indicate that while the agroforestry model was externally introduced, its viability depends on continuous producer engagement, adaptive design, and substitute coordination mechanisms that stabilise participation. The study highlights how PCI operates as an enabling mechanism for SOI by supporting context-appropriate solutions, while remaining constrained by land-tenure insecurity, logistical bottlenecks, and reliance on external orchestration. As a research-in-progress contribution, the paper invites feedback on ecosystem governance dynamics.

The Ecodesign for Sustainable Products Regulation (ESPR) and the Digital Product Passport (DPP) mandate information transparency, creating enabling environments for sustainable innovation. However, innovators face practical challenges in designing viable DPP use cases, struggling with conceptual, communication, and collaboration hurdles due to regulatory uncertainty and misaligned stakeholder incentives. Existing tools offer high-level guidance but lack specific support for early-stage ideation. To address this, this Design Science Research (DSR) study proposes the DPP Use Case Assessment Framework, operationalized as an Innovation Canvas comprising 19 integrated diagnostic questions. The framework acts as a structural guide to enforce alignment across policy objectives, functional necessity, and economic viability. By decoupling functional requirements from legal status and assessing ecosystem-wide incentives, the framework mitigates narrative drift and supports the transition from vague concepts to viable, policy-enabled circular business models. This is an example of the abstract style.

This contribution examines the central innovation management challenge of translating abstract ethical principles for artificial intelligence into actionable design and governance practices. Drawing on seven real-world AI innovation cases from Austrian industries, we analyse how digital humanism-a framework advocating for human-centred and societally aligned digital technologies-can guide the practical management of AI-based innovation. We identify key obstacles that innovators encounter, including the difficulty of anticipating undesirable effects of artificial intelligence, navigating an overwhelming range of design choices, hesitations around enhancing user autonomy, and the risk of workforce deskilling. We propose a digital-humanist approach to innovation management that emphasizes early-stage ethical integration, cross-disciplinary collaboration, and capability-building as foundational components for developing responsible and trustworthy AI systems.

Retail banking is being reshaped by digitalization, sustainability pressures, and rapidly shifting customer expectations, yet most foresight initiatives remain detached from actual innovation work. This study introduces foresight-by-design as a novel organizational capability that embeds future-oriented thinking directly into innovation processes through Foresight Innovation and Design (FID) behavior. Adopting a qualitative theory-building approach, the research draws on comparative case studies of European incumbent banks, combining semi-structured executive interviews, innovation process tracing, workshop observations, and organizational document analysis. The study reconceptualizes foresight not as a strategic planning activity, but as a situated behavioral and design practice through which imagined futures become operationalized within organizational innovation systems. In doing so, it identifies FID behavior as a previously overlooked micro-foundation of anticipatory innovation and challenges dominant foresight approaches that remain cognitively and structurally disconnected from innovation execution.

Academic entrepreneurship is widely recognized as a key channel through which universities foster innovation and socio-economic development, yet cross-national assessments remain limited by fragmented metrics and an overemphasis on observable outputs. This study introduces a novel system-level perspective by developing the Academic Entrepreneurship System Index (AESI), a composite indicator that captures the underlying institutional and structural conditions enabling academic entrepreneurship across OECD countries. Drawing on international datasets, the index is combined with hierarchical cluster analysis to identify distinct national configurations of academic entrepreneurship systems. The findings highlight pronounced cross- country diversity and demonstrate that comparable levels of academic entrepreneurship can arise from alternative institutional arrangements.

Europe's innovation performance is hindered by three mutually reinforcing barriers: misaligned incentives between academia and industry, inflexible public funding mechanisms and fragmented collaboration structures. The Richter Innovation Ecosystem demonstrates a scalable alternative by prioritizing structure before funding. Central to this approach is early alignment on a shared value proposition focused on unmet medical needs, ensuring that both scientific outputs and industrial translational results are recognized as success metrics. Trust-building mechanisms-including open innovation principles, clear IP rules, and unrestricted publication rights-further enable productive exchange. A multilateral governance framework defines roles, decision rights, and agile operating practices that accommodate scientific pivots even within rigid grant schemes. Supported by coordinated workshops and strong core-facility infrastructure, the ecosystem tracks collaboration intensity, translational progress and network growth as leading indicators. Initial outcomes show that structured, trust-based ecosystems can enhance Europe's competitiveness if paired with flexible governance models.

Innovation support for small and medium enterprises frequently rests on the assumption that more collaboration leads to better outcomes. This paper challenges that assumption. Drawing on a sequential mixed-methods study of manufacturing SMEs in Greater Western Sydney, Australia, it examines how different collaboration and network relationships influence SMEs' innovation readiness, technology adoption and innovation outcomes. The findings show that network value depends on partner type, relationship depth and firms' internal absorptive capacity - not simply on participation or connectivity. Strategic, trust-based ties with relevant partners consistently outperform broad but shallow networking activity. To organise these findings, the paper develops a typology of SME network relationships and argues for a shift from connectivity-focused to capability-focused innovation support. Policies that do not account for this conditionality risk reinforcing existing disadvantages rather than reducing them.

This paper examines the limitations of dominant growth-oriented innovation models in university ecosystems and explores the potential of regenerative business as an alternative conceptual lens. While universities are increasingly expected to address grand societal challenges, their innovation practices remain largely embedded in market-driven logics prioritising competitiveness, scale, and short-term impact. Drawing on the emerging literature on regenerative business, this study develops a conceptual framework for regenerative innovation in university ecosystems. The research adopts a qualitative, theory-building multiple case study design, combining analysis of strategic documents and semi-structured interviews across selected university ecosystems in Europe and Latin America. The paper identifies key tensions between extractive and regenerative innovation logics and proposes a framework structured around value regeneration, long-term stewardship, and place-based embeddedness. It contributes to innovation management by extending regenerative thinking to university ecosystems and offering an alternative approach to organising and evaluating innovation processes.

Deep technology (DT) entrepreneurs are often celebrated through their start-ups for addressing society's 'grand challenges', however, their sustainability claims frequently remain rhetorical. Researching UK DTs, the likes of biotech and quantum computing, struggle to embed sustainability into their organisational and operational fabric. This study examines how organisational attitudes, internal practices, resource constraints and cognitive limits shape the extent to which DT ventures integrate sustainability into decision-making and R&D priorities. It also explores barriers to sustainable business model adoption and their implications for long-term viability. Proposed data collection will involve semi-structured interviews with stakeholders in the DT sphere, with the intent to evaluate how tensions and paradoxes shape sustainability-aligned business models. In contribution, the aim is to develop a usable lens for actors involved in DT's ecosystem to recognise and reshape the mechanisms that keep high-impact DT ventures stuck in high-harm, low-sustainability trajectories.

Industry openness is typically defined by the quantity, direction, and content of knowledge flows. In the electric guitar industry, however, openness was not a strategic choice by leading firms-it was an inherent property of the technology. Refined in the 1940s and 1950s by Fender and Gibson and propelled by rock and roll, the modern electric guitar combined low-tech design, limited patenting, and modular architecture, enabling spillovers, imitation, and constraining incumbents' subsequent innovation. Innovation diffused across the ecosystem-amplifier makers, pedal builders, component suppliers, and boutique manufacturers-driven by professional musicians' own sonic experimentation. We review the resulting product, ecosystem, and innovation strategies, suggesting how involuntary openness shapes managerial strategy and industry structure across ecosystem-driven industries, with incumbents thriving by embracing canonical designs while newcomers innovate at the periphery.

This paper examines how Art Thinking can support innovation leadership education by developing capacity to engage with paradox and uncertainty. Drawing on qualitative data from executive workshops, we conceptualize innovation leadership as a relational and meaning-making process and introduce the Hermenaut as a paradox-aware leader. Three research questions guide inquiry: how do Art Thinking workshops make paradoxical and dilemmatic situations accessible to participants; do participants negotiate these tensions during learning process; and conditions enable or constrain the transfer of such learning into organizational practice. The findings show how participants work through tension via embodied, iterative, and relational practices, with productive dissatisfaction emerging as a key learning mechanism. While Art Thinking creates powerful experiential learning, a transfer gap to organizational practice remains. Drawing on Sutherland's (2013) concept, we develop "memories with momentum" as an extended framework to explain how aesthetic experiences may enable sustained impact beyond the learning setting.

As generative AI increasingly optimizes structured creative processes (including ideation and concept development), the conscious layer of organizational creativity is becoming progressively enhanced-and potentially commoditized. This conceptual paper argues that sustainable competitive advantage in AI-augmented innovation systems will depend on the institutional integration of non-conscious creativity. Drawing on creativity research, cognitive psychology, and neuroscience, the paper distinguishes incremental from breakthrough outcomes and demonstrates that qualitative restructuring systematically depends on state-dependent, non-conscious mechanisms such as incubation, insight, reduced top-down control, and associative recombination. Building on this synthesis, a Creative Rebalancing Model is proposed, conceptualizing institutional innovation systems as layered architectures in which creative leadership functions as the enabling condition for legitimizing and embedding non-conscious processes. The paper concludes with managerial and research implications, arguing that in the AI era, competitive differentiation shifts toward the institutional strength of non-conscious creativity integration.

The COVID-19 required a product engineering department in an aeronautical company to transition from on-site work to remote work and later to a hybrid model, influencing teams that applied SCRUM. This study assessed whether this shift affected performance related to engagement, trust, and mutual support. A survey was carried out assessing seven factors that influence performance: autonomy, communication, roles, ceremonies, engagement, trust, and mutual support. Data were collected from 132 respondents via a 5-point Likert scale questionnaire, comparing on-site (pre-pandemic) versus hybrid (post-pandemic) work environments. The PLS-SEM results indicated stability in engagement, trust, and mutual support suggesting that the hybrid model did not alter these essential performance elements. However, difficulties associated with roles and ceremonies revealed knowledge gaps in SCRUM, particularly among SCRUM Masters. The study expands the understanding of SCRUM practices in product engineering contexts outside software development and provides insights for improving its adoption in hybrid environments.

Industrial incumbents increasingly build B2B platforms by integrating digital technologies into physical products and operational infrastructures, yet how the design of this cyber-physical integration shapes innovation potential remains unclear. We investigate how incumbents' cyber-physical design choices on industrial B2B platforms create optionality for value creation across time and space. Drawing on a qualitative multiple-case study of five Nordic machinery and manufacturing firms and their ecosystem partners, we identify three distinct cyber-physical design choices-anticipatory, emergent, and retrospective-each unfolding through a physical design logic, a digital design logic, and a value design logic. We further find that cyber-physical integration reconfigures platform boundaries along relational, data, physical, and domain dimensions. Our findings contribute to digital innovation research by introducing the concept of cyber-physical optionality, extending generativity theory with a temporal and spatial lens, and theorizing how design choices in industrial platforms create, preserve, and exercise options for future value creation.

This paper addresses the absence of a formalised code of ethics in innovation management, despite the field's growing professionalisation and increasing influence over high-uncertainty technological futures. It frames this gap as the "New Innovators' Dilemma," where innovation-driven decisions can create societal harm when regulation lags behind technological development. Drawing on the Precautionary Principle, Anticipatory Ethics and Responsible Innovation, the study proposes a two-phase mixed-methods design. First, a modified Delphi study with senior innovation professionals will develop consensus around a practitioner-led code of ethics. Second, an experimental study will test whether exposure to the code affects decision-making in ethically ambiguous innovation scenarios. The paper contributes to the professionalisation of innovation management by offering an empirically grounded pathway for embedding ethics into innovation practice. It provides practical value for professional bodies, corporate innovation teams and educators working with emerging technologies such as AI and biotechnology.