Achieving sustainable development goals relies mainly on the transition from fossil fuels to green alternatives. Rising environmental concerns have created a new market for low-carbon technologies and products. As a result, achieving a competitive advantage in low-carbon technologies has become increasingly important for sustainable economic development. This study explores the impact of environmental management practices on competitive advantage in low-carbon technologies across 37 OECD countries, using panel data from 1995 to 2023. Specifically, the study examines the role of environmental invention, environmental taxation, low-carbon technology imports, public R&D in industrial production, and public R&D in energy technologies. To achieve this objective, the study employs advanced instrumental variable quantile regression analysis to capture heterogeneous effects across different levels of competitiveness. The findings reveal heterogeneous effects of environmental inventions, environmental taxation, low-carbon technology imports, public R&D in industrial production, and public R&D in energy technologies on competitive advantage in low-carbon technologies. An increase in environmental taxation has a significant positive effect on competitive advantage, which supports the Porter hypothesis, whereas environmental inventions, low-carbon technology imports, and public R&D spending have differential impacts based on the maturity of prevailing innovation ecosystems. The findings provide practical implications for policymakers and industry stakeholders by highlighting the importance of green innovation incentives, low-carbon technology imports, and adaptive public R&D funding. These policies can strengthen national competitiveness in low-carbon technologies and facilitate the transition toward a sustainable low-carbon economy.
The twin transition is widely expected to support decarbonization, yet the conditions under which it does so remain poorly understood. This study examines whether and how the twin transition is associated with per-capita CO2 emissions across countries, distinguishing between aggregate transition progress and structurally distinct configurations: digital-green synergy, transition imbalance, and directional emphasis. Using an original composite Twin Transition Index constructed from digital connectivity and renewable-energy indicators, and a two-way fixed-effects framework with Driscoll-Kraay standard errors applied to a panel of 74 countries over 2000-2020, the analysis produces four main findings. First, aggregate twin transition progress carries no stable unconditional association with per-capita emissions; environmental outcomes depend critically on transition structure rather than transition scale. Second, digital-green synergy is robustly associated with lower per-capita CO2 emissions, while digital-first trajectories are associated with higher emissions; the absolute gap between dimensions carries no independent effect. Third, the emission-reducing association of coordinated transition progress strengthens after 2010, consistent with a structural shift in the digital-energy-emissions nexus as renewable technologies became cost-competitive. Fourth, mechanism tests indicate that effects operate through changes in energy composition and efficiency rather than reductions in aggregate demand and are amplified in countries with stronger economic and infrastructural readiness. These findings demonstrate that the twin transition is associated with lower emissions only when digital and green capabilities advance in coordination and establish transition configuration (not transition speed) as the central determinant of environmental performance.
This study examines the influence of an open innovation mindset, design thinking, and strategic thinking skills on innovative entrepreneurship among new-generation Thai SME entrepreneurs operating in the small and medium enterprise (SME) sector. Data were collected from 315 Thai SME entrepreneurs aged 25 to 45 years through online questionnaires and analyzed using structural equation modeling (SEM). The results indicate that the open innovation mindset has a significant positive influence on both design thinking skills and strategic thinking skills and that these two types of cognitive skills have a direct effect on innovative entrepreneurship. The open innovation mindset does not have a significant direct effect on innovative entrepreneurship; instead, its influence occurs entirely through the mediating roles of design thinking skills and strategic thinking skills. This indicates that in the Thai context, an open mindset must be transformed into concrete thinking abilities to generate real innovative outcomes. The study contributes theoretically by extending the understanding of the Southeast Asian context and identifying key mediation mechanisms. Practical contributions include recommendations for entrepreneurial development programs, government policies, educational curricula, and network-based collaboration aimed at strengthening the long-term competitiveness of Thai SMEs. Future research should incorporate longitudinal designs, compare different entrepreneur groups, integrate qualitative approaches to explore deeper mechanisms, and include broader contextual factors to enhance the robustness and generalizability of the findings.
Emerging digital technologies generate persistent paradoxes: they enable trust and efficiency while constraining flexibility and control. Prior research explains adoption through drivers, barriers, or institutional alignment, treating innovation as a matter of fit between organizations and environments. This view overlooks how managers actively configure technologies to stabilize innovation under institutional complexity. This study reframes adoption as innovation stabilization and conceptualizes dynamic institutional fit as a mid-range configurational explanation of how paradoxical digital infrastructures become operationally viable and institutionally legitimate under institutional complexity. Using systematic evidence synthesis combined with set-theoretic qualitative comparative analysis (QCA), it examines 75 blockchain studies across manufacturing, finance, logistics, healthcare, and agriculture. The findings show that viable innovation does not stem from a single driver but from multiple equifinal combinations of design and governance choices across sectors. Four recurring design mechanisms are identified from cross-sector configurations and interpreted through paradox theory and institutional theory, namely, the selective prioritization of attributes, controlled autonomy, managed openness, and temporal sequencing. Sustainability considerations appear less recurrent than regulatory, efficiency, and capability conditions, suggesting a possible sequencing logic for further investigation. These results reframe innovation viability as an active configuration rather than a passive institutional alignment and show how similar outcomes arise through different sector-specific pathways. This study contributes a cross-sector configurational explanation of institutional viability under a paradox and provides structured guidance for managers and policymakers seeking to stabilize digital innovations in complex environments.
In the digital era marked by accelerated technological disruption, open collaboration has become a strategic imperative for innovation and provides an important background for how projects are organized and governed. This paper investigates how project marketing, through an open value co-creation strategy, can support open innovation within open-source ecosystems. Drawing on stakeholder theory, service-dominant logic, and knowledge creation model, the study argues that project marketing fosters open innovation by orchestrating heterogeneous actors, facilitating knowledge flows, and aligning innovation efforts with project success. Empirically, the paper employs a quantitative research design using partial least squares structural equation modeling (PLS-SEM). The paper’s novelty lies in empirically assessing the role of project marketing as an intermediary that links an open value co-creation strategy, stakeholder engagement, and staged knowledge creation—before the project and during the project—to open-source project success rather than presenting another study of open-source communities or modeling these elements as isolated predictors. Data from 62 respondents with project-management or project-leadership experience in open-source projects (OSPs) show that project marketing significantly strengthens stakeholder engagement and pre-project knowledge assets, which in turn support in-project knowledge creation, with knowledge creation subsequently contributing to project success. The open value co-creation strategy supports success through engagement and knowledge-based intermediaries, demonstrating that project marketing functions not only as a communication activity but also as an orchestration capability that supports durable open innovation outcomes in OSPs. The findings extend project-marketing theory by situating it within the broader discourse of digital open innovation and open collaboration. Practically, the study offers guidance to managers seeking to design inclusive innovation ecosystems that use marketing as a coordinating force among technical, organizational, and community actors.
This study examines whether investments in artificial intelligence (AI) and Big Data technologies are associated with changes in firm-level market power. Drawing on the Resource-Based View and the economics of intangible assets, we hypothesize that the unique cost structure of AI, characterized by large sunk costs and near-zero marginal costs, enables early adopters to structurally expand their price-cost margins. Using a representative sample of Italian firms, we implement a difference-in-differences model to obtain estimates avoiding the negative weighting biases of staggered technology adoption. Our findings indicate that early AI integration is followed by a substantial post-adoption increase in the accounting-based Lerner index, equal to a 17% rise relative to the sample mean. A detailed analysis reveals that this markup expansion is mechanically driven by a reduction in the variable-cost share of sales, with no evidence of immediate market share consolidation. Furthermore, AI adoption is heavily scale-dependent and concentrated among large, financially resilient firms across diverse sectors. Our findings provide quasi-experimental evidence that early AI investments reward firms through internal cost efficiency rather than market-share consolidation, underscoring the need for policies that accelerate AI diffusion among smaller enterprises to prevent a structural digital divide.
Design thinking has emerged as a core methodology for innovation and entrepreneurship, providing human-centered approaches to complex problem-solving. Scholarship in this domain, however, remains fragmented and rapidly expanding. This study presents a multi-method quantitative review combining bibliometric mapping and non-negative matrix factorization (NMF) topic modeling to synthesize 1,700 Web of Science-indexed articles. The findings reveal a marked acceleration in publication activity and a concentration of influential outlets, authors, and institutional contributors. Bibliometric analysis identifies the key sources, affiliations, and collaboration patterns that structure the intellectual landscape of the field. Topic modeling uncovers recurrent thematic clusters encompassing (i) organizational practice and capability-building; (ii) design thinking in entrepreneurship and STEM/engineering education; and (iii) innovation applications in product, service, healthcare, social, and digitally enabled contexts, including agile and collaborative modes of working. Synthesizing these thematic structures, the study advances the recombinant innovation logic of design thinking (RILD), a conceptual framework characterizing design thinking in entrepreneurial contexts as operating through three interlocking mechanisms: cognitive reframing of problems and opportunities, iterative boundary-crossing across disciplinary and organizational domains, and empathy-anchored legitimation of novel ventures through stakeholder participation. By integrating bibliometric and computational semantic analyses, this study provides a multi-level, data-driven mapping of the field, clarifies its intellectual architecture and thematic evolution, introduces RILD as a theoretical lens extending dynamic capability and effectuation perspectives in entrepreneurship research, and delineates strategically significant directions for future research on design-driven entrepreneurship and innovation management.
Sustainable food systems are now negotiated within a polycrisis defined by climate and biodiversity breakdown, persistent malnutrition, geopolitical fragmentation, and accelerating technological change. However, the prevailing innovation discourse in agri-food systems remains constrained by two recurring simplifications: an economistic framing of ‘innovation’ as productivity enhancement, and a technocratic framing of ‘digital transformation’ as inherently progressive. In this editorial, we position the International Journal of Innovation Studies special issue on Digital Transformation, Stakeholder Engagement, and Innovation in Sustainable Food Systems as an opportunity to re-politicise the agri-food innovation agenda. Drawing on a socio-technical transition lens and a co-creation perspective, we identify three structural tensions that shape contemporary agri-food innovation: (i) regeneration versus extraction, (ii) participation versus capture, and (iii) data sovereignty versus data enclosure. We argue that the credibility of sustainability-oriented innovation depends less on the novelty of technologies than on how innovation is governed, whose knowledge counts, and how risks, costs, and value are distributed across actors and territories. We also introduce the contributions in this special issue, showing how they illuminate the politics of trust, legitimacy, participation, and public value in digital and institutional innovation across food consumption, governance, and producer engagement. We close with a research agenda centred on ethical experimentation, accountable AI, and mission-oriented governance that prioritizes planetary boundaries, distributive justice, and epistemic pluralism in agri-food transformation.
This study analyzes the link between innovation-system enabling conditions and Sustainable Development Goal (SDG) outcomes in 43 African countries from 2005 to 2023 using a pillar-based framework informed by national innovation systems theory. Key indicators such as R&D expenditure, public education spending, labor force participation, and institutional quality serve as proxies for innovation capacity. Empirically, the study estimates goal-specific two-way fixed-effects panel regressions for each of the 17 SDGs and complements them with instrumental variable (IV/2SLS) estimation to address potential endogeneity. The findings show significant variability among SDG outcomes, with positive associations for health (Goal 3), education (Goal 4), gender equality (Goal 5), industrial development (Goal 9), and institutional strength (Goals 16 and 17). However, negative correlations were found for poverty reduction (Goal 1), inequality (Goal 10), climate action (Goal 13), and responsible consumption (Goal 12), indicating that innovation-driven development has not led to inclusive or sustainable progress. To address potential overlaps between innovation-system indicators and the SDGs, sensitivity analyses were performed, confirming the robustness of the results; however, some overlapping goals showed reduced effects. Additional analyses suggest caution in interpreting relationships, especially concerning poverty outcomes. This study highlights the need for innovation policy to focus on inclusivity, poverty reduction, environmental sustainability, and stronger institutional coordination to achieve the 2030 Agenda’s goals.
While small and medium-sized enterprises (SMEs) are widely recognized as agile drivers of innovation, assessing their impact on future innovation trajectories is constrained by a severe shortage of timely data, as official statistics often entail lags of one to two years. This study bridges this gap by introducing a novel framework designed to capture regional asymmetries in the SME innovation contribution to regional development using near real-time data. We propose an integrated indicator system structured around direct innovation output, indirect engagement, and institutional enablers. The implementation of our approach is based on the development of a data extraction and processing pipeline that automatically collects and systematizes monthly, regionally disaggregated data from Russia’s Unified SME Registry. This pipeline enables the continuous generation of relevant statistics on SMEs in innovation-intensive activities. Applying this framework across 85 Russian regions revealed significant asymmetries and key findings: broad regional support measures (e.g., general tax incentives) effectively increase the overall number of SMEs but weakly increase the growth of innovative SMEs specifically. The results provide a foundation for designing timely, evidence-based policy interventions to cultivate innovation-driven entrepreneurial ecosystems. This approach equips policymakers with a dynamic tool to shape future economic landscapes, enhancing regional resilience and advancing progress toward Sustainable Development Goals, particularly SDG 9 (Industry, Innovation, and Infrastructure).
Entrepreneurship education programmes in high schools have been recognised as a valuable strategy for developing an entrepreneurial mindset among learners. Grounded in curriculum theory and theory of planned behaviour, the study emphasises the importance of such programmes in preparing learners for the challenges of the modern business world. Thus, this study aims to explore the effect of entrepreneurship education programmes on high school learners’ mindset. A systematic literature review was conducted, including peer-reviewed articles, books, and reports focused solely on entrepreneurship education programmes in high schools. Hence, the following were excluded from this review: materials focusing on primary and tertiary schools, informal or non-school environments, and countries other than the 10 selected for their entrepreneurship programmes. The different programmes aimed at providing high school learners with hands-on experience, networking prospects, and opportunities for knowledge exchange have generally been effective in enhancing their entrepreneurial mindsets. The findings are of considerable importance to educators, policymakers, and stakeholders involved in designing and implementing entrepreneurship education programmes in high schools. The results can guide the creation of more effective and impactful programmes that enhance learners’ readiness for future entrepreneurial pursuits. Schools should implement advanced entrepreneurship education policies and curricula to ensure a higher standard of learning and development in this area.
Marketing intelligence implies the application of advanced and digital technologies in making strategic marketing decisions. The objective of the research is to analyze the impact of marketing intelligence, organizational-centered strategic and tactical decision-making on customer satisfaction and loyalty. The study collected responses from 366 industry professionals holding key strategic, tactical and operational positions and evaluated them through a two-stage process. In the first stage, structural equation modeling (SEM) was used to examine the linear relationship among the identified constructs. The second stage involves evaluating the predicting efficacy of the relevant parameters derived from the SEM using an artificial neural network (ANN) analysis. The results of SEM analysis indicate that strategic decision-making significantly impacts customer loyalty. Further, tactical decision-making is found to be negatively associated with customer satisfaction. The model also has acceptable predictive accuracy. The research results are highly useful for researchers and practitioners looking to enhance customer loyalty. The research proposes a novel framework to investigate how business organizations incorporate marketing intelligence as a developmental strategy for strategic and tactical decision-making to develop swift responses to enhance customer satisfaction and loyalty.
The intervention aimed to increase parents’ awareness of their children’s nutritional status through a customized digital nutrition education package (DNEP). A total of 328 parents of primary school children in Tbilisi, Georgia, participated in a 10-week DNEP intervention to educate parents about children’s healthy food choices and dietary habits. To assess its effectiveness, the results from a semi-quantitative Food Frequency Questionnaire (FFQ) and a Knowledge, Attitudes and Practices (KAP) Questionnaire were compared before and after the intervention. After the intervention, daily breakfast consumption among children increased by 8.3 % (p = 0.010), and vegetable intake increased significantly (up by 150 %) from 77g to 116 g per day. While the overall macronutrient ratio remained consistent (p > 0.05), average daily vegetable consumption surged by 192 % in private schools and 131 % in public schools. The DNEP effectively increased vegetable intake among school children and can potentially enhance their physical and cognitive development. Our findings highlight that a healthy home eating environment promotes balanced nutrition habits among families, making DNEP a viable strategy for addressing malnutrition in Tbilisi. The results of this study contribute to Georgia’s national nutrition guidelines for children and align with UN Sustainable Development Goals (SDGs) (3, 4, 5, and 10).
This study explores the intricate dynamics between organizational factors and employee well-being within the unique cultural and economic landscape of an entrepreneurial IT firm in Pakistan. Recognizing that employee well-being is not solely the product of personal disposition but is significantly shaped by the organizational environment, this research aimed to examine how workplace elements such as organizational climate, team dynamics, leadership quality, and the availability or strain of work-related resources influence employees’ psychological well-being. Importantly, the study positions perceived unit-level creativity as a central mediating mechanism through which these factors exert their influence. Grounded in the belief that creative environments empower individuals and instill a sense of purpose, autonomy, and belonging, the study proposes that fostering creativity within organizations may yield broader emotional and psychological benefits for employees.Data were collected from a purposive sample of 103 employees at an entrepreneurial IT firm in Pakistan. These firms are often characterized by resource constraints, rapid innovation cycles, and informal structures, making them fertile ground for exploring the intersection of creativity and well-being. The research employed both LISREL structural equation modeling and regression analyses to rigorously test the proposed mediation model. The findings revealed that when firms cultivate climates and leadership styles conducive to creativity, they simultaneously enhance employees’ well-being, thereby offering a dual advantage for organizational performance and human sustainability.The study contributes to the literature by offering empirical evidence from a non-Western, entrepreneurial context, highlighting the universality and contextual relevance of creativity as a pathway to employee flourishing. The paper concludes with a discussion of its methodological limitations, such as a cross-sectional design and limited generalizability due to sample size. It provides avenues for future research, particularly longitudinal studies and comparative analyses across different organizational types and cultures.
This paper develops a conceptual framework explaining how startup ecosystems act as catalysts within regional innovation systems and strengthen regional competitiveness. It integrates three complementary perspectives: the structural foundations of regional innovation systems, the behavioral dynamics of startup ecosystems, and the connective role of knowledge spillovers. The framework proposes that competitiveness emerges from the interaction between institutions, networks and learning rather than from isolated innovation or entrepreneurship. Startups not only generate technologies but also create feedback loops that enhance institutional capacity and policy learning. Trust, governance quality and absorptive capacity moderate these relationships, ensuring collaborative outcomes. The study contributes to theory by linking previously separate strands of regional innovation and entrepreneurship literature and offers guidance for policymakers seeking to build open, resilient and continuously renewing innovation systems.
This study examines how complementors’ positioning in categories within a platform ecosystem shapes the product development orientation that sustains their viability. Category representativeness is the degree to which a category within a platform ecosystem embodies ecosystem identity and is collectively regarded as representative of ecosystem participants, including platform owners, complementors, and consumers. The analysis investigates whether the representativeness of the categories adopted by complementors alters the viability implications of exploitation, exploration, and ambidexterity. Using data from the Japanese video game market—12 hardware platforms, 182 firms, and 8,577 software products—the author constructed a dataset of 399 complementor–platform survival patterns and estimated Cox proportional hazards models. The results show that complementors positioned in highly representative categories exhibit greater viability when they adopt an ambidextrous orientation. This pattern does not appear in less representative categories. The findings suggest that complementors’ viable innovation strategies differ with category representativeness: in less representative categories, complementors may specialize in either exploitative or exploratory innovation, whereas in highly representative categories, they need a more balanced approach.
This research investigates the impact of Information Sharing (IS) on individual innovation performance within engineering organizations. While the general link between information sharing and innovation is known, the specific mechanisms in private engineering firms remain underexplored. Drawing on an integrated framework of Social Exchange Theory and Social Development Theory, this study proposes and tests a model that unpacks these pathways. Data were collected via a survey of 287 engineers from electronic manufacturing firms in Hong Kong and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results confirm that IS has a significant positive relationship with learning motivation, individual learning, and adaptability to change. Furthermore, these three factors are substantially and significantly associated with individual innovation performance. The findings reveal that IS does not directly drive innovation but does so by fostering a learning-oriented environment that simultaneously enhances motivation and cognitive adaptability. This study's main contribution is a nuanced, mechanism-based understanding of how information sharing influences innovation, offering valuable theoretical and practical insights for fostering innovation in knowledge-intensive engineering settings.
In recent years, research systems have faced increasingly complex sustainability challenges, and improving system resilience has become the key to ensure their continuous and efficient operation. Based on the data of Web of Science co-authored papers, we constructed a research cooperation network from 2005 to 2024. Subsequently, complex network analysis and principal component analysis (PCA) were used to quantitatively assess the overall resilience of the research system in terms of structural attributes and functional resilience, and to explore the adaptive mechanisms and evolutionary trends of the system in the face of external shocks by combining with the identification of policy events. The results of the study include: ① Policy events have a phased impact on the resilience of the system, and the study captures the dynamic response to resilience under policy shocks with the help of the difference-in-differences approach and finds that the scientific research system shows a certain degree of resilience in the face of the Sino-US scientific research friction around 2018; ② The study defines the resilience of the system as structural and functional resilience. The structural toughness of the research system reflects the structural robustness of the network in different dimensions, such as hierarchy, matching, access, aggregation, and heterogeneity; ③ Functional toughness is quantified based on the area under the curve of GC (Giant Component), which intuitively reflects the ability of the scientific research system to maintain functional output when suffering from local node failures; ④ The comprehensive resilience assessment framework uses PCA to effectively integrate the structural resilience indicators of the system and combines structural and functional analyses. It is found that the overall resilience of the research system during the research period shows a ”fluctuating but improving” trend: The early stage of the network structure is loose, the functional stability is weak, and the impact resistance of the system is limited. However, with the expansion of the collaborative network and the optimization of the structure, the system gradually demonstrates stronger recovery and adaptive capacity.
Countries worldwide have been increasingly embracing technological innovation to achieve intelligent, resilient, and sustainable urban development. In China, innovation serves as the primary driving force and a critical pillar of the country’s revitalization strategy, which aims to advance toward high-quality development (HQD). The objective of this study is to evaluate the innovation network (IN) and its impacts on HQD in cities within the Chengdu-Chongqing Economic Circle (CCEC) and to uncover the underlying influence mechanisms of the IN. By employing social network analysis, panel regression models, and mediating effect models based on patent and socio-economic data, the results demonstrate that IN significantly drives HQD. These findings remain robust after accounting for endogeneity and conducting robustness checks. Furthermore, ICT infrastructure is identified as a significant mediating factor in the relationship between IN and HQD. In addition, the IN of patent collaboration in the CCEC is evolving, with Chongqing and Chengdu identified as the core hubs driving regional spillover. Through the IN, innovation stakeholders in the CCEC can improve resource sharing and enhance the network's overall innovation level, thereby promoting HQD. This study has important implications for understanding collaborative innovation in urban development and provides differentiated policy references for core and peripheral cities.
The integration of artificial intelligence (AI) into project management is reshaping organizational capabilities by enhancing decision-making, automating routine tasks, and optimizing resource allocation. However, this technological transformation also brings a host of ethical challenges that threaten to undermine trust, transparency, and accountability. Key concerns include algorithmic bias, opacity in decision-making processes, and the erosion of human oversight. Although global ethical frameworks such as those proposed by the EU, OECD, and IEEE offer foundational guidance, they often lack the operational specificity required for application within the dynamic and context-sensitive environment of project management. This paper contends that addressing these shortcomings necessitates a transition from abstract ethical principles to tangible, enforceable mechanisms. Focusing specifically on ethical auditing, this study explores how systematic assessments can be employed to identify, evaluate, and mitigate ethical risks throughout the AI project lifecycle. Drawing upon recent literature and case studies, this paper proposes a multi-dimensional ethical audit model designed for the unique demands of project-based work. By translating normative values into concrete evaluation criteria, ethical audits serve as both diagnostic and preventive tools that can support responsible AI deployment. The paper further emphasizes the critical role of interdisciplinary collaboration in designing audit processes that are context-aware and culturally responsive.
