Purpose This study aims to investigate how different layers of artificial intelligence (AI) technologies jointly shape urban innovation, addressing the puzzle of why cities with high AI adoption often display uneven innovation outcomes. Rather than treating AI as a single technology, the study conceptualises AI as a three-tier capability structure consisting of foundational, core and general-purpose technologies, and examines whether urban innovation benefits more from isolated technological investments or from coordinated development across these layers in an emerging-economy context.Design/methodology/approach Using patent-based indicators, this study constructs city-level measures of foundational, core and general-purpose AI technologies for a balanced panel of 120 Chinese cities from 2010 to 2021. Fixed-effects models with interaction terms are used to estimate both direct and complementary effects across AI layers. An instrumental-variable strategy based on historical communication infrastructure is further applied to address potential endogeneity concerns, and heterogeneity analyses are conducted across different urban contexts.Findings The results show that the innovation effects of AI are layered and uneven. Foundational and core AI technologies are more strongly associated with urban innovation capacity, whereas the contribution of general-purpose AI technologies is more contingent on local development conditions. The findings further suggest that complementarities across AI layers are conditional and that sustainable urban innovation depends on both upstream capability accumulation and downstream application diffusion.Research limitations/implications The analysis is based on city-level data from 2010 to 2021 and therefore does not fully capture the post-2022 diffusion of generative AI. Future research could extend the framework to examine whether large-model technologies reshape the relationships among different AI layers and urban innovation outcomes.Practical implications The study suggests that policymakers should adopt differentiated AI development strategies, balancing application expansion with sustained investment in foundational infrastructure, core technologies and local innovation capabilities.Originality/value This study advances innovation research by reconceptualising AI as a layered technology stack rather than a monolithic general-purpose technology. It reveals a hierarchical complementarity mechanism through which AI capabilities translate into urban innovation, offering new insights into why application-led AI strategies often fail. The findings provide actionable implications for urban and regional innovation policy in emerging economies by highlighting the importance of balanced, context-sensitive AI capability development.
Purpose This study aims to examine how artificial intelligence (AI) maturity translates into entrepreneurial success in incubators and accelerators by testing startup adaptability as a key mechanism and governance as a contextual boundary condition. Design/methodology/approach Cross-sectional survey data from 101 incubator and accelerator professionals in leading innovation economies were analyzed using partial least squares structural equation modeling to estimate direct, mediation and interaction effects. Findings AI maturity contributes to entrepreneurial success primarily through startup adaptability, while AI usage and knowledge transfer show no consistent direct performance effects. Interaction tests indicate no significant moderation effects for ethical governance or sectoral context in this sample, suggesting that contextual influences may operate through upstream enabling conditions rather than short-term interaction patterns. Research limitations/implications The cross-sectional design limits causal inference about capability development over time. Single-informant, program-level perceptions may introduce common-source bias and reduce sensitivity to founder-level learning dynamics. The modest sample size restricts statistical power for interaction testing, and limited variance in governance and sectoral conditions within leading innovation economies may attenuate detectable moderation effects. The marginal AVE for knowledge transfer suggests construct heterogeneity; future research should disaggregate exposure versus enactment and use behaviorally anchored indicators. Longitudinal, multirespondent and sector-balanced designs are needed to validate boundary conditions. Practical implications Managers of incubators and accelerators should prioritize AI maturity investments in data quality, system integration and analytical skills before expecting measurable performance gains. AI-generated insights yield value when embedded into routines that support disciplined iteration, such as structured selection panels, milestone reviews and mentoring processes. Given the weak role of knowledge transfer, programs should shift from exposure-oriented training toward co-execution models that translate learning into enacted practice. Governance should be implemented as enabling infrastructure (auditability, accountability, transparency) that supports trustworthy routine integration. Social implications Strengthening AI maturity and responsible governance in entrepreneurial support organizations can improve transparency, fairness and accountability in venture selection and resource allocation. When AI insights are routinized into decision-making, incubators and accelerators may better support evidence-based experimentation, reduce informational asymmetries and increase the effectiveness of public and private innovation investments. Emphasizing governance as enabling infrastructure - rather than compliance alone - can enhance stakeholder trust and legitimacy of AI-assisted judgments. Over time, such practices may contribute to more resilient entrepreneurial ecosystems and more inclusive access to high-quality support mechanisms. Originality/value The study advances mechanism-based explanation beyond descriptive tool-focused accounts by integrating institutional theory and dynamic capabilities theory to clarify how AI-enabled routines convert capability foundations into program-level outcomes.
Purpose This study aims to examine the influence of clan culture on women’s entrepreneurship through the lens of the challenge-based entrepreneurship model and explore how women’s education and social trust moderate this relationship. Design/methodology/approach Using data from the China Family Panel Studies (CFPS) from 2014 to 2018, this study conducted multilevel mixed-effects logistic regression to test proposed model. Findings Results indicate that clan culture positively influences women’s entrepreneurship. However, this effect is attenuated for women with higher education level or greater social trust, highlighting the moderating role of cognitive and relational embeddedness within the clan system. Practical implications These findings highlight the need for targeted entrepreneurial support services for women navigating traditional sociocultural constraints. Policymakers should adopt a dialectical perspective on the role of clan culture and design differentiated strategies to promote women’s entrepreneurship in diverse cultural contexts. Originality/value This research represents an early attempt to empirically examine the relationship between clan culture and women’s entrepreneurship, introducing a relatively novel triggering factor for women entrepreneurs. It also verifies and extends the challenge-based entrepreneurship model by applying it to women’s entrepreneurship, reflecting the role of sociocultural challenges in shaping entrepreneurial activities.
PurposeAs environmental imperatives increasingly reshape competitive landscapes, the purpose of this study is to explain how strategic leadership translates sustainability-oriented vision into tangible green innovation (GI) outcomes in small and medium-sized enterprises (SMEs), particularly in emerging economies where resource constraints remain salient.Design/methodology/approachDrawing on the resource-based view and upper echelons theory, this study develops a moderated mediation framework in which green corporate entrepreneurship and corporate social responsibility mediate the relationship between green strategic leadership and GI, while big data analytics capacity moderates these mechanisms. Survey data collected from 558 middle managers in SMEs were analyzed using multiple regression analysis and Hayes' PROCESS macro.FindingsThe results of this study indicate that green strategic leadership exerts a significant indirect effect on GI through both green corporate entrepreneurship and corporate social responsibility. Unexpectedly, big data analytics capacity was found to attenuate rather than amplify the indirect relationships, suggesting a substitution effect whereby advanced data-driven systems may reduce the strategic discretion afforded to green leaders in SME contexts.Originality/valueBy integrating leadership, sustainability and digital analytics perspectives, this study advances existing theory by clarifying the mechanisms and boundary conditions through which strategic leadership fosters GI in resource-constrained firms. The findings of this study also provide actionable insights for SME managers seeking to leverage leadership orientation and analytical capabilities to support sustainable innovation strategies.
Purpose This study aims to examine how government agencies in Bangladesh collaborate to support startups. Design/methodology/approach This study used a modified exploratory sequential mixed-methods approach, which was anchored in a theoretical framework and integrated established theories with surveys, interviews and collaboration mapping, to examine how government agencies coordinate and share information to support startups. Findings This research identified several institutional and cultural factors that shape collaboration among government agencies in Bangladesh's startup ecosystem. Hierarchical communication structures, collectivist organizational norms, fragmented institutional mandates and limited startup literacy among policymakers hinder effective information sharing and inter-agency coordination. The findings also highlight the absence of key collaboration mechanisms, including horizontal collaboration frameworks and a shared understanding of startup ecosystem dynamics, which weaken the effectiveness of startup-related policies. Strengthening inter-agency coordination and enhancing policymakers' understanding of startups emerged as crucial steps to improve government support for entrepreneurship. Research limitations/implications This study involved 15 participants. The sample size was determined based on the influence of a few key stakeholders shaping the early-stage startup ecosystem, especially those from the public sector. Originality/value This study adds to the growing body of research on the startup ecosystem in Bangladesh and offers relevant insights for policymakers in emerging economies aiming to support startups. Additionally, it fills a gap in the literature by presenting broad perspectives of stakeholders in the startup ecosystem and connecting them to the prevailing organizational culture.
PurposeEntrepreneurial ecosystems consist of interactions among diverse actors and key elements, support, culture, finance, policies, human capital and markets, that shape venture development. This research aims to investigate how these elements interrelate and influence the ecosystem's innovative performance.Design/methodology/approachThis research evaluates the perceptions of 87 actors involved in a Brazilian entrepreneurial ecosystem through a quantitative study, employing multiple correspondence analysis in SPSS 22. Each dimension was analyzed using two categories: high and low.FindingsThe analysis revealed four clusters that explain how the core elements sustain innovative performance within the ecosystem. In Clusters 1 and 3, associations were observed between creative performance and the market, policy, finance and human capital, classified as "high" and "low," respectively. Clusters 2 and 4, in turn, showed links between culture and support, also in the "high" and "low" categories. These findings indicate that sustaining innovative performance depends on specific patterns of association among elements rather than on the isolated presence of each component.Originality/valueThis research contributes to the literature on entrepreneurial ecosystems in three ways: (1) it advances the theoretical understanding of ecosystem dynamics by showing how the orchestration of key elements reduces fragmentation and supports innovative performance in emerging economies; (2) it offers an empirically grounded framework with strategic management practices to guide actors in orchestrating and activating their ecosystems; and (3) it introduces a data-driven multiple correspondence analysi based methodology as a robust tool for diagnosing synergies and gaps in the development of entrepreneurial ecosystems in emerging economies.
PurposeThe purpose of this study is to examine a unique typology of women's empowerment (WE) and its role in enhancing human capital development (HCD) and total factor productivity (TFP) in Pakistan. This study investigates how WE acts as both a moderating and mediating factor between human capital and economic growth, thereby improving the quality of life.Design/methodology/approachThis study uses the Autoregressive Distributed Lag (ARDL) co-integration technique using annual data from 1990 to 2022. This approach allows for analysing both short- and long-run dynamics between WE, HCD and TFP, providing a macroeconomic perspective on the productive role of WE. Granger Causality tests are also applied to determine directional relationships among the variables.FindingsEmpirical results indicate that WE has significant moderating and mediating effects on TFP through HCD in both the short and long run. Granger Causality analysis reveals unidirectional causality from WE to TFP and from WE to HCD, highlighting the interactive and dynamic role of WE in fostering economic productivity. The findings of this study suggest that leveraging the potential of Pakistan's female population can enhance human capital and improve the quality of life for future generations.Originality/valueTo the best of the author's knowledge, this study is among the first to examine WE as a productive resource influencing HCD and TFP in Pakistan. This study provides novel insights for policymakers, emphasising the social and economic benefits of promoting women's empowerment to achieve inclusive and sustainable economic growth.
PurposeThe purpose of this study is to address the challenges of ambiguous topics and unclear development paths in technological evolution by identifying disruptive technology topics. This work is of strategic significance for nations to proactively plan for and lay out future industries.Design/methodology/approachThis paper innovatively integrates natural language processing techniques with the latent Dirichlet allocation (LDA) topic model to construct a disruptive technology topic identification framework based on multi-source heterogeneous data. Taking the field of quantum communication as a case study, it selects scholarly papers and patents as heterogeneous data sources and uses multi-dimensional indicators - including topic similarity, novelty and intensity - to identify technology topics.FindingsThe results indicate the following: the complementary fusion of scholarly papers and patent data significantly enhances the comprehensiveness and accuracy of technology theme identification. The classification framework based on theme novelty and intensity effectively distinguishes technical characteristics at different development stages, providing a quantitative basis for optimizing innovation resource allocation. The algorithm-driven theme identification method offers an extensible analytical tool for technological foresight.Research limitations/implicationsFuture research on identifying disruptive technological innovations should focus on the dynamic weighted fusion of multi-source data, the precise management of technology life cycles and the balance between quantitative analysis and situational flexibility.Practical implicationsThis study provides scientific decision support for the research and development of disruptive technologies.Originality/valueThis study lays a methodological foundation for the strategic layout of future industries by proposing a novel, data-driven framework for technology foresight.
PurposeIn the era of human–AI symbiosis, artificial intelligence (AI) is increasingly reshaping cognition, knowledge production and labor structures. These transformations, in turn, place growing pressure on higher education institutions to reform entrepreneurship education (EE). This study aims to examine how AI-enabled EE influences students’ entrepreneurial competencies by uncovering the underlying psychological mechanisms that remain resistant to AI substitution.Design/methodology/approachGrounded in the Stimulus–Organism–Response (SOR) model, this study explores how AI-enabled EE influences university students’ entrepreneurial competencies. This study conceptualized “AI adoption in higher education (AAHE)” in “entrepreneurship education (EE)” as the stimulus (S), “perceived usefulness (PU)” and “entrepreneurial self-efficacy (ESE)” as organismic states (O) and “entrepreneurial competency (EC)” as the response (R). A sample of 558 undergraduates from Shanghai and Zhejiang, China’s AI hub, was surveyed, and hypotheses were tested by Structural Equation Modeling.FindingsThe empirical results showed AAHE positively predicted EE; AAHE and EE both boosted PU and ESE; and PU and ESE mediated the path to EC. These findings highlight the critical role of psychological mechanisms in translating AI integration into competencies development.Originality/valueThis study makes two key contributions: theoretically, it extends the application of the SOR model to AI-enabled EE and clarifies the mediating mechanisms of PU and ESE; practically, this research provides guidance for higher education institutions to cultivate students’ entrepreneurial competencies by optimizing AI integration.
PurposeThe purpose of this study is to examine whether initial public offerings (IPOs) can reduce the cost of debt for small and medium-sized enterprises (SMEs).Design/methodology/approachThis study uses a sample of 5,770 firm-year observations, with 44.51% (55.49%) of them obtained from listed (unlisted) firms in China, for regression analyses. In addition, the authors construct an instrumental variable (IV) based on the change in the IPO approval rate over time, which is largely affected by political factors and considered exogenous to corporate management, to demonstrate the causal effect of IPOs on the cost of debt.FindingsThe results of baseline regressions suggest that IPOs reduce the cost of debt by 16.2162%. Additional analyses show that IPOs have positive effects on the number of corporate employees, R&D expenses and the ratio of employees with bachelor's or postgraduate degrees, which is consistent with the notion that IPOs alleviate firms' financial constraints by reducing the cost of debt.Originality/valueThis study makes three important contributions. First, the authors use a sample containing unlisted firms and conduct IV analyses to address potential selection bias and endogeneity issues and by doing so, demonstrate the negative effect of IPOs on the cost of debt. Second, the authors lend support to agency theory in explaining the cost of debt. Third, the authors highlight that the reduced cost of debt after the IPO provides a new perspective in explaining why firms are willing to accept puzzlingly high IPO underpricing.
PurposeThis paper aims to quantitatively analyze the intergovernmental network structures within China's high-tech enterprise (HTE) policies, with a focus on how these networks influence policy formulation and innovation support. The study seeks to provide both theoretical foundations and practical recommendations for optimizing the development and implementation of HTE policies.Design/methodology/approachUsing social network analysis (SNA), this research systematically examines the interactive relationships among policy actors during the policy-making process for HTEs in four representative regions: Shanghai, Jiangsu, Beijing and Guangdong. The study analyzes the structural characteristics and dynamic evolution patterns of policy networks across these regions.FindingsRegional economic development levels and innovation environments significantly influence collaboration models - taking Beijing and Shanghai as examples, both cities leverage their strong economic foundations and well-established industrial policies to foster favorable innovation ecosystems, thereby enhancing the synergistic effects of HTE policies. Fiscal and science and technology departments play a dominant role in HTE policy formulation, though their influence exhibits notable regional heterogeneity. Departments with structural hole advantages (characterized by high effective size and low constraint) often exhibit greater policy autonomy. This feature contributes to divergent HTE governance patterns across different regions.Originality/valueThis study innovatively uses SNA to deeply investigate intergovernmental policy network relationships within the context of HTE development in China. By systematically identifying the differentiated characteristics and underlying implications of regional policy networks, the research not only enriches the theoretical foundations of innovation policy networks but also provides significant insights for policy practice. The findings offer scientific evidence for policymakers to optimize governance frameworks, thereby more effectively promoting the sustainable development of HTEs.
PurposeThis paper aims to develop an integrated understanding of open data as a source of digital entrepreneurship for start-up entrepreneurs in Malaysia.Design/methodology/approachThe study adopted qualitative case study research design within the interpretivist research worldview. The author conducted 24 online semi-structured interviews with start-up Chief Executive Officers, founders and co-founders in Malaysia. Interview transcripts were coded inductively through thematic analysis by using NVivo 12 software. Then, the author developed a theoretical model based on research findings.FindingsThree essential components of the proposed model include the dynamic relationship between data owners and start-up entrepreneurs, the critical importance of open data enablers for greater entrepreneurial effects and the roles of broader contexts such as policies and infrastructure readiness. Surprisingly, the research found two emerging open data enablers from the interviews: a sandbox program and a quadruple helix partnership. Joining a sandbox program allowed a HealthTech start-up to collaborate with regulatory partners. A quadruple helix partnership enabled this start-up to collaborate with industry, academia, government and civil society. Also, the study came across a local open data movement initiated by a start-up association. One of the agendas of this movement was to urge the government to prioritize the disclosure of open data API in the public sector.Practical implicationsOpen data scholars can explore the proposed model further for future studies. Policymakers can integrate a sandbox program and quadruple helix collaboration to nurture open data innovation. Also, there is a need to strengthen laws and regulations to inspire confidence in the ethical use of open data for innovation and entrepreneurship.Originality/valuePrevious research has considered open data for entrepreneurial benefits. However, there is a lack of an integrated model on this subject. Hence, this study offers a novel integrated model to understand open data entrepreneurship for start-ups in the data economy.
PurposeSocial network structures significantly impact business opportunity recognition, but existing evidence reveals that not all social network structures work in favor. This study aims to examine the effects of international entrepreneurs' network centrality and constraints on opportunity recognition in a host country. Also, it analyzes the contextual mechanism of the home country's cultural tightness and looseness on the relationships between network structures and opportunity recognition.Design/methodology/approachThis study adopts a quantitative research approach, using survey data from 220 international entrepreneurs in China to test the hypotheses through multiple regression analysis.FindingsThis research finds that international entrepreneurs' network centrality (not the network constraints) in the host country positively contributes to opportunity recognition. Furthermore, this study suggests that international entrepreneurs' home country cultural tightness negatively moderates the relationship between network centrality and opportunity recognition.Originality/valueThis study contributes a novel integrative framework to international entrepreneurship by linking entrepreneurs' social network structures (centrality and constraint) with their home country cultural tightness. Unlike prior studies that view networks or culture in isolation, this paper demonstrates the cross-level contingency effect between individual embeddedness and societal norms. It responds to recent calls for contextualized models in international opportunity recognition (Pidduck et al., 2024; Wang et al., 2019).
Purpose-This study aims to investigate how the classical academic resources of universities contribute to their innovation and entrepreneurship performance. Academic inputs such as the total number of academic publishing, citation scores, scientific documents, number of PhD studies and faculty-to-student ratios are used for this analysis. The criteria used for innovation and entrepreneurship rating are competence in scientific and technological research, intellectual property pool, cooperation and interaction and economic contribution and commercialization. Design/methodology/approach-Two ranking systems for Turkish universities are used in this study. Academic performance (URAP) is used as input, and entrepreneurial performance (TUBITAK) is the output. A sample of 48 Turkish universities (32 public universities and 16 private universities) is evaluated via data envelopment analysis (DEA). Findings-The results of the DEA show that 23% of the selected universities are fully efficient, while 62% are partially efficient - of which 81.7% are public universities and 44% are private universities. Furthermore, the study's slack analysis of outputs indicates that although the academic performance of the selected universities is relatively high, these universities have difficulty converting the outcomes of their academic studies into real-life socioeconomic applications. Originality/value-The goal of higher education institutions has traditionally been purely academic, focusing on teaching and scientific research. However, contemporary universities are expected to consistently focus on innovation and entrepreneurship in addition to their traditional roles of teaching and research. This study examines the relationship between classical academic resources and the contemporary entrepreneurial aspect of the universities in a sample of 48 Turkish universities. Two well-established university ranking systems are used to evaluate performance and efficiency, constituting a novel contribution to the academic entrepreneurship field.
Purpose This study aims to examine the relationship between corporate environmental, social and governance (ESG) performance and capital-market value creation in China, with a focus on testing for U-shaped effects and exploring the underlying mechanisms that drive this relationship. Design/methodology/approach Panel data on Chinese A-share listed firms from 2007 to 2022 are used. The study uses fixed-effects panel regression models and a generalized propensity score approach, and also investigates financing constraints and green innovation mechanisms. Besides, conduct subgroup analyses by ownership type, industry pollution intensity and firm size to assess heterogeneity in the relationship between corporate ESG performance and capital-market value creation. Findings Corporate ESG performance and capital-market value creation exhibit a U-shaped relationship. Firms with very high or very low ESG scores outperform those with moderate ESG engagement in terms of market valuation. The analysis of mechanisms shows that ESG performance has an inverted U-shaped effect on financing constraints and a U-shaped effect on green innovation. Furthermore, the U-shaped effect is more pronounced for private firms, firms in less-polluting industries and smaller firms, whereas it is muted or nonexistent for state-owned enterprises, firms in high-pollution industries and larger firms. Originality/value To the best of the authors’ knowledge, this study is the first to provide comprehensive evidence of a U-shaped relationship between corporate ESG performance and capital-market value creation. It identifies financing constraints and green innovation as key channels through which ESG performance creates value. The findings offer novel insights into how context factors – such as ownership structure, industry environmental risk and firm size – modulate the returns on corporate sustainability investments. These insights have practical implications for managers seeking to maximize the value impact of ESG initiatives, investors evaluating corporate ESG efforts and policymakers aiming to support sustainable corporate practices in emerging markets.
PurposePreservice teachers (PSTs) often face challenges in STEM teaching, including cognitive conservatism, limited collaboration experience and weak innovation capacity. To address this, based on cognitive conflict and collaborative innovation theories, this study aims to propose the Cognitive Conflict in Community of Practice (CCCP), following an "Activation-Reinforcement-Diversification" pathway. Anchored in a university-school-enterprise collaboration, the model aims to explore effective support mechanisms and assess its impact on STEM PSTs' Interdisciplinary Teaching Competence (ITC) and innovative design ability.Design/methodology/approachA mixed-methods approach was used, combining quasi-experimental design and qualitative analysis. Centered on the CCCP, interdisciplinary teaching practices were implemented to assess its impact. Questionnaires measured ITC improvement between experimental and control groups, while interviews and textual analysis explored the development of instructional design innovation.FindingsThe model significantly improved PSTs' ITC and fostered innovative awareness in a STEM course, facilitating a shift from idealized to practical design. It also promoted cognitive interaction and professional growth among in-service teachers, supporting a mutually empowering development pathway.Originality/valueThis study presents an innovative integration of cognitive conflict theory and multidimensional collaboration, offering a practical and scalable framework for interdisciplinary teacher education. It contributes to the theoretical understanding of cognitive conflict transformation in pedagogical contexts and provides actionable guidance for PSTs course reform.
PurposeWhile the financing sources available in the market do not provide sufficient financial support for the establishment of companies with high innovative impact, the public sector financing sources play an effective role in granting non-reimbursable resources to these companies, especially during the initial phases that involve greater risks in innovation. This study aims to construct a risk estimation model for subsidized financing of innovation-promoting organizations in emerging economy countries.Design/methodology/approachA database was used with historical data of 77 projects submitted to public notices to promote innovation from a promoting organization. The analyses were conducted using the technique of discriminant analysis and three risk models were considered in the analysis.FindingsIt was evident that, the more the benefited project teams have high academic qualification (Human Capital) and the more these same teams are socially integrated within a closed cohesive structure (Clustering Social Capital), greater are its innovative qualities and lower are the levels of technological and management risk associated with the economic subsidy program. This study demonstrates that a risk prediction tool can contribute to the local economic subsidy program by signaling the need for actions to be taken during the project selection phase for funding.Originality/valueThe main contribution of this paper is the proposal and construction of an important tool for use in risk perception and aid in fund decision-making public financing for business innovation projects, proposing a risk management tool with a reasonable degree of assertiveness.
Purpose The paper aims to explore the intricate relationship between the university entrepreneurial ecosystem and the entrepreneurial intentions of students in Vietnam. Design/methodology/approach By using the structural equation modelling approach, the study examines how various components of the ecosystem – including entrepreneurship policy, access to culture and entrepreneurial education – influence students’ motivation to pursue entrepreneurial ventures. Findings The findings reveal that a robust entrepreneurship education significantly enhances students’ entrepreneurial intention, while the theory of planned behaviour construct is insignificant for business administration majors. Entrepreneurship education mediates the relationship between entrepreneurial policy and intention, with notable differences between public and private university systems. Originality/value This research provides valuable insights for educators and policymakers seeking to create a more conducive environment for fostering entrepreneurship among university students in Vietnam.
Purpose - This study aims to investigate the development of growth hacking capability (GHC) in small and medium-sized enterprises (SMEs) and its impact on organisational performance, drawing on the resource-based view (RBV) and dynamic capability theory (DCT). Design/methodology/approach - Using a hybrid analytical approach that combines structural equation modelling and artificial neural network, 392 respondents across 51 SMEs in China's service and manufacturing sectors were surveyed. Findings - The findings reveal that innovation (ss = 0.354), initiative (ss = 0.299) and management capability (ss = 0.176) significantly enhance GHC, which, in turn, directly improves organisational performance (ss = 0.342). Although organisational agility does not directly impact performance, it contributes indirectly through GHC. The findings highlight the strategic importance of data-driven decision-making in digital transformation and confirm the mediating role of GHC as a dynamic capability. Research limitations/implications - This study is limited by its exclusive focus on Chinese SMEs, thus, suggesting the need for future research that conducts cross-national comparisons and longitudinal analyses.Practical implicationsPractically, SMEs are encouraged to foster an innovative culture, adopt forward-looking strategic planning and enhance managerial data literacy to cultivate GHC. Theoretically, the integration of the RBV and the DCT offers a novel lens for examining organisational capabilities in the digital era. Originality/value - This study introduces GHC as a mediating variable, clarifying how innovation, initiative and managerial capability affect SME performance in digital contexts. It extends the RBV and the DCT to illustrate performance mechanisms.
Purpose - This study aims to examine how noneconomic goals, specifically those related to socioemotional wealth (SEW), influence the process of selecting strategic partners for collaborative innovation (CI) in family firms. In doing so, it contributes to the literature with a nuanced process view from the non-Western context. Design/methodology/approach - This study employs a qualitative, single case study methodology to explore the process of partner selection for CI in a Malaysian family firm operating in the oil and gas industry. This approach allows for an in-depth examination of how family-specific values and SEW influence decisions on the identification and selection of external partners for CI. Findings - Findings show that the selection process of strategic partners for CI is predominantly influenced by family-specific values and the preservation of SEW, a clan-like behavior. The family firm's reliance on a close-knit network of trusted partners, driven by cultural norms of reciprocity and loyalty, often leads to the exclusion of potentially beneficial new partnerships. The findings underscore the tension between maintaining family control and pursuing opportunities, where family goals and SEW can significantly limit the firm's openness to external collaboration, subsequently impacting its innovation capabilities. Research limitations/implications - Future research could expand on these findings by adopting multiple case studies across diverse contexts to extend the insights gained. In addition, exploring the long-term outcomes of CI partnerships in family firms would gain a more nuanced understanding of the implications of SEW-driven decisions. Originality/value - This study addresses gaps in the literature by providing a nuanced understanding of how cultural norms, family values, family goals and SEW shape CI in family businesses, particularly in non-Western context. It highlights the role of cultural norms like guanxi in influencing strategic decisions in family firm, addressing the contradictory findings in existing literature and offering theoretical and practical contributions.
