Search Results (435)

Problem: Entrepreneurial decision-making is widely recognized as central to startup outcomes, yet how founders make decisions during the startup execution phase remains underexplored. Prior research rarely distinguishes between strategic decisions (e.g., market entry, scaling) and operational decisions (e.g., coordination, problem-solving), even though these two decision types differ in their uncertainty, reversibility, and cognitive demands. Objective: This study investigates how founder attributes relate to self-reported decision-making styles across strategic and operational decision contexts during startup execution. Methodology: Drawing on Dual-Process Theory, decision-making is viewed as an interplay between intuitive (System 1) and analytical (System 2) cognitive processes. A sequential exploratory mixed-methods design was employed, beginning with semi-structured interviews with 20 Indian startup founders to develop the conceptual framework, followed by quantitative examination using Partial Least Squares Structural Equation Modelling (PLS-SEM) on data from 350 funded startup founders, with separate structural models estimated for strategic and operational decision contexts. Results: The findings revealed context-specific patterns of association between founder attributes and self-reported decision-making styles across strategic and operational decision contexts. In the strategic model, cognitive orientation, domain experience, and risk appetite were significantly associated with decision-making style, explaining 49.7% of the variance (R² = 0.497). In the operational model, only risk appetite remained significant, with substantially lower explanatory power (R² = 0.125). Taken together, the findings indicate stronger patterns of association between founder attributes and decision-making style in the strategic context than in the operational context. Conclusions: The study contributes to entrepreneurial cognition research by demonstrating that founder attributes exhibit context-specific patterns of association with decision-making styles. These findings underscore the importance of considering decision context when examining entrepreneurial decision-making. Full article

This study examines how venture capital investors in Kazakhstan evaluate women-led enterprises within a frontier-emerging market context characterized by institutional transition and evolving entrepreneurial ecosystems. Addressing a gap in the literature on gendered investment behavior beyond mature markets, the research adopts an exploratory mixed-methods design combining survey data (n = 21) with open-ended qualitative responses from VC professionals. Descriptive and bivariate analyses are used to examine associations between investor characteristics and evaluation criteria, while exploratory factor analysis is employed as a heuristic tool to assess whether survey items cluster around broadly interpretable evaluative orientations shaping investment judgments. The findings suggest the presence of two indicative evaluative orientations—market orientation and impact orientation—that appear to structure how respondents in this sample prioritize dimensions such as scalability, innovation, teamwork, and social value. These orientations are interpreted as context-specific and exploratory rather than statistically generalizable. The study contributes to entrepreneurial finance and institutional theory by developing an exploratory evaluative framework that captures the coexistence of commercial and developmental considerations in venture investment decision-making within a transitional economy. The findings further highlight how gendered investment dynamics are shaped by both market criteria and institutional environments, offering implications for policymakers, investors, and scholars seeking to understand capital allocation processes in underexplored venture ecosystems. Full article

This study examines how digital technology development affects entrepreneurial activity from a spatial perspective. Existing studies have mainly emphasized the local entrepreneurial effects of digital technology, while paying relatively limited attention to whether such effects extend across cities through spatial linkages. Using manually compiled large-scale business registration data, this study constructs a balanced panel dataset covering 281 prefecture-level and above cities in China from 2006 to 2020. Spatial autocorrelation tests and spatial econometric models are applied to identify the local and spatial spillover effects of digital technology. The findings suggest that urban entrepreneurial activity exhibits significant spatial dependence. After controlling for spatial correlation, digital technology development significantly promotes local entrepreneurial activity and generates positive spillover effects on surrounding cities. Effect decomposition results show that the indirect effect of digital technology is stronger than its direct effect, suggesting that spatial spillover is an important channel through which digital technology affects entrepreneurial activity. Further analysis finds that this effect differs across technology types, city size, urban hierarchy, and geographical location. Distance-band tests indicate that the positive spillover effect weakens as geographical distance increases. Overall, digital technology can promote entrepreneurial activity through regional linkages, but its spatial influence depends on actual intercity connections. Full article

This study examines how the resource configurations of early-stage startups are associated with intellectual property (IP) management capability. To achieve this objective, a dual analytical framework integrating hierarchical regression analysis (OLS) with machine learning techniques (XGBoost and SHAP) is employed. Because conventional linear models may not capture complex associations, the analysis also explores potential nonlinear patterns among key variables, which are interpreted as exploratory, model-based tendencies rather than as causal or temporal effects. The empirical findings reveal several important insights. First, the results of the linear regression analysis indicate that the main effects of simple quantitative indicators—such as firm age and organizational size—are not statistically significant. The interaction between the startup period and pre-startup education (H1) is the only relationship to approach statistical significance, although it is borderline and not robust to alternative variable coding. This pattern suggests that IP management capability is associated not with the quantity of inputs but with the preparedness of the entrepreneur’s knowledge resources. Second, the explainable artificial intelligence (XAI)-based analysis surfaces nonlinear patterns that are not captured by conventional linear models. Specifically, the model-estimated contribution of entrepreneurial education is comparatively small among firms in their first two years and larger among firms around the third year, and the model-estimated contribution of organizational size diminishes once the firm reaches roughly thirty employees. These inflections are model-based tendencies observed in SHAP dependence plots and are corroborated by formal segmented (breakpoint) regressions (spline terms p = 0.010 and p = 0.002). Methodologically, the study shows how integrating hierarchical regression with explainable machine learning (XGBoost and SHAP) can reveal nonlinear and threshold patterns that conventional linear models overlook. Building on this, it proposes resource latency as an interpretive lens, rather than an established construct, for age-related patterns in startup resource utilization, to be examined in future longitudinal research. From a practical perspective, the findings suggest the value of sustained support during the early scale-up period and of more systematic management structures as firms grow, while recognizing that these patterns are cross-sectional associations. Full article

Rural entrepreneurship is a key driver of rural economic development. However, limited evidence indicates how financial support affects rural households’ entrepreneurship through integrated mechanisms. Using 2109 micro-survey data points from rural Henan Province, Probit and OLS models were used to examine the impacts, moderating effects, and mediating pathways of formal and informal finance on rural households’ entrepreneurial decision-making and performance. This study makes two contributions. First, it differentiates entrepreneurial decision-making and performance as two stages of the entrepreneurial process. Second, it proposes an integrated three-path framework incorporating one moderating effect (the interaction between financial support and financing constraints) alongside two mediating mechanisms (risk-taking willingness and investment scale), which enables a more refined interpretation of the heterogeneous impacts exerted by financial support throughout distinct entrepreneurial stages. Both formal and informal finance can positively facilitate entrepreneurial decision-making, with formal support having stronger marginal effects. Financial support has varied impacts on rural household entrepreneurship, depending on household income, entrepreneurship type, and region. By alleviating financing constraints and optimizing resource allocation, financial support improves rural households’ entrepreneurial probability and business performance. By enhancing households’ risk-taking willingness and expanding asset investment, this support injects endogenous impetus into rural development. This financial empowerment mechanism can remove entrepreneurship barriers, facilitate the expansion of opportunity-based entrepreneurship, drive rural economic resilience, and promote inclusive, sustainable regional development. Full article

Although the literature on entrepreneurial ecosystems recognizes institutional, economic, technological, and social factors, integrated empirical tests of their interrelationships at the regional level remain limited, particularly in transition economies. This paper analyzes a structural-mechanism model of regional entrepreneurial ecosystems in Serbia using survey data from 401 enterprises in four regions. The study applies partial least squares structural equation modeling (PLS-SEM) to assess the measurement model, structural pathways, indirect effects, and predictive relevance of the proposed model. Additional regional comparisons and official regional GDP indicators are used to contextualize the survey-based findings. The results support the reliability and convergent validity of the reflective constructs. The structural model indicates that economic and social factors are associated with institutional and technological conditions, while institutional, technological, and social factors are associated with innovation development, new product and service development, innovation capacity, entrepreneurial activity, and entrepreneurial motivation. The indirect effects further support the proposed mechanism logic, especially through institutional and technological pathways. Regional comparisons show significant differences across the observed regions, with Southern Serbia recording less favorable perceived ecosystem conditions. The findings suggest that regional entrepreneurial ecosystems should be analyzed as context-dependent systems in which structural conditions and operating mechanisms are connected, but the cross-sectional and perception-based design does not allow definitive causal conclusions. Full article

This study examines the associations among entrepreneurial self-efficacy, entrepreneurial resilience, financial constraints, and sustainable business practices among micro and small women entrepreneurs in the West Bank, Palestine. Drawing on Social Cognitive Theory and Conservation of Resources Theory, a moderated mediation model is proposed and explored in which entrepreneurial resilience mediates the relationship between entrepreneurial self-efficacy and sustainable business practices, while financial constraints moderate this indirect pathway. Survey data were collected from 282 micro and small women entrepreneurs through a purposive stratified sample facilitated by microfinance institution and NGO networks, and the model was assessed using partial least squares structural equation modeling via SmartPLS 4. The findings indicate that entrepreneurial self-efficacy is positively associated with sustainable business practices both directly and indirectly through entrepreneurial resilience. Financial constraints significantly weaken the resilience-to-practices pathway, and the moderated mediation analysis reveals that the indirect association diminishes as financial constraints intensify. These findings contribute to sustainable entrepreneurship theory by identifying the sequential psychological pathway through which self-efficacy translates into responsible business conduct and by establishing material resource scarcity as a boundary condition of that pathway in fragile economy contexts. Full article

Drawing on signaling theory, this study investigates the role of lead founders’ human capital signals in the success outcomes of equity crowdfunding (ECF) campaigns. While prior research emphasizes entrepreneurial teams or broadly defined founder characteristics, the role of dominant entrepreneurial actors remains underexplored. We focus on the lead founder, defined as the individual combining founder status, CEO authority, and ownership concentration, as the primary signal carrier in ECF contexts. Using a multi-platform dataset of 1067 campaigns from Republic Europe, Crowdcube, Mamacrowd, and Invesdor (2012–2024), we examine how lead founders’ education and experience shape investor decisions. Our results indicate that industry-related education is the strongest predictor of the number of investors. Furthermore, while industry experience alone can positively predict investor engagement, its role disappears once education is accounted for, suggesting that education in industry-related fields can outweigh industry experience in shaping investor perceptions. Additionally, our findings suggest that entrepreneurial experience and attendance at a top-ranked university do not contribute meaningfully to explaining investor participation. Accordingly, the study contributes to the human capital signaling literature by showing that investors evaluate the incremental informational value of human capital signals rather than assessing each signal independently, and highlights the centrality of the lead founder in decision-making under highly uncertain crowdfunding environments. Full article

This study aims to assess whether micro-, small-, and medium-sized enterprises in Ecuador’s Amazon region show evidence of sustained reorientation toward selected non-extractive activities under persistent extractive dependence. Guided by four empirical propositions concerning sectoral reorientation, differential firm viability, temporal discontinuity and limited reallocation, and territorial heterogeneity, the study uses a longitudinal administrative panel of 769,344 firm-year observations for 2006–2021, complemented by descriptive evidence for 2022–2024. The empirical strategy combines fixed-effects models, non-parametric trend and structural break tests, cohort analysis, survival analysis, and transition matrices. The results indicate an emerging but constrained diversification pattern. New-economy firms increased their relative participation after the 2015–2016 commodity downturn and showed higher survival rates and stronger formal employment generation than extractive firms. However, intersectoral mobility remained limited, and the evidence does not support the interpretation of a completed structural transformation. Provincial heterogeneity further shows that extractive expansion continues to influence local entrepreneurial dynamics, especially in mining-frontier territories. The main limitation is that the analysis captures formally registered firms and does not directly measure informal-sector activity, productivity upgrading, or full regional structural transformation. The study contributes to debates on regional development, sustainability, and firm-level transformation by showing that non-extractive reorientation may emerge in peripheral resource-dependent regions without fully displacing extractive dependence. Full article

There is renewed interest in local sourcing, regional supply chains, and the rebuilding of fiber-to-fashion systems. However, limited attention has been paid to the upstream role of fiber farmers and the infrastructure that enables or constrains regional textile economies. This study investigates the opportunities and challenges of fiber farming in West Virginia and explores the motivations that drive participation in this sector. Using a qualitative approach, semi-structured interviews were conducted with 16 fiber farmers across West Virginia. The findings revealed five interconnected themes: heterogeneous actants, the translation of wool, regional network breakdown, festivals and social media as network hubs, and institutional gaps and network fragility. The results indicate that fiber farming persists through strong community networks, adaptive entrepreneurial strategies, and deep attachments to place. However, its economic viability is constrained by declining processing infrastructure, labor shortages, weakened institutional support, and fragmented supply chains. These challenges also have important sustainability implications. Most notably, wool is often discarded because processing and transportation costs exceed its market value, resulting in the waste of a renewable and biodegradable fiber that could otherwise remain in productive use. This study contributes to the literature on local sourcing, rural entrepreneurship, and sustainable and circular economies by highlighting the relational infrastructures required to rebuild regionally embedded textile systems in Appalachia and beyond. Full article

Using panel data from Chinese cities spanning 2010–2023 and leveraging the natural experiment provided by the establishment of the National Big Data Comprehensive Pilot Zone (NBDPZ), we employed the difference-in-differences (DID) method alongside double machine learning (DML) to systematically examine how these policies influence urban economic resilience efficiency. The empirical results demonstrate that the NBDPZ significantly enhances urban economic resilience efficiency. This finding is robust under parallel trend and placebo tests, confirming that the improvement is a policy-driven causal effect. Mechanism analysis reveals that the policy enhances urban economic resilience efficiency primarily by promoting the upgrading and rationalization of industrial structure to consolidate the micro-foundation of sustainable economic transformation; increasing innovation output to facilitate the sustainable accumulation of knowledge capital; and enhancing urban entrepreneurial activity to inject sustainable endogenous vitality into the economic system. Heterogeneity analysis indicates that the positive effects are more pronounced in eastern and western regions, second-tier cities, and cities with lower industrial agglomeration, better digital infrastructure, and stronger legal and regulatory environments. The study’s findings offer both theoretical support and practical guidance for refining the policy framework of the NBDPZ policy and promoting sustainable urban economic development. Full article

Sustainability-oriented entrepreneurship is becoming more widely acknowledged as a mean of addressing social and environmental issues while promoting economic development, though little research has looked at the cognitive processes by which innovation-related thinking translates into sustainability entrepreneurial intention. The relationships between innovative mindset, entrepreneurial mindset, and sustainability entrepreneurial intention among university students are examined in this study. A mediation model is proposed in which innovative mindset positively influences entrepreneurial mindset (H1), entrepreneurial mindset positively influences sustainability entrepreneurial intention (H2), and entrepreneurial mindset mediates the relationship between innovative mindset and sustainability entrepreneurial intention (H3). In total, 163 university students in the United Arab Emirates provided the data, which was then analyzed using partial least squares structural equation modeling (PLS-SEM). All of the proposed hypotheses are supported by the results. These findings offer preliminary and partial support for a theoretically defined cognitive pathway connecting sustainability entrepreneurial intention, innovative mindset, and entrepreneurial mindset. In particular, the findings indicate a positive correlation between innovation-oriented cognitive abilities and entrepreneurial cognition, which is linked to sustainability-oriented intentions. The low explained variance in sustainability entrepreneurial intention, however, suggests that the model only partially explains the variables influencing SEI. As a result, this study advances a more complex, mechanism-based understanding of one potential cognitive pathway in sustainability entrepreneurship and emphasizes the need for more thorough models that include contextual, motivational, and sustainability-related predictors. Additionally, it provides cautious practical implications for entrepreneurship education, especially when it comes to combining learning that is focused on sustainability with the development of an innovative and entrepreneurial mindset. Full article

Despite the growing literature on entrepreneurial ecosystems and Industry 4.0, few studies systematically link ecosystemic dynamics to structural transformation in the Global South; even fewer compare BRICS Plus economies with G7 benchmarks using a unified econometric framework. This study addresses that gap. Its objective is to assess how the configuration of such ecosystems shapes the trajectory of sustainable industrialization, comparing the BRICS Plus group with the G7 economies over 2002–2021, a period determined by the most recent harmonized data available across all panel countries from the World Bank, UNIDO and OECD. Methodologically the study employs a balanced panel applying panel unit root and cointegration tests, Vector Error Correction Models, Generalized Method of Moments estimation and Granger causality analysis applied to manufacturing value added (MVA), GDP excluding manufacturing (GDPNOTMVA), industrial employment and productivity indices. The results indicate a long-run interaction between manufacturing and non-manufacturing output in BRICS Plus economies that is consistent with—though not a direct measurement of—entrepreneurial ecosystem dynamics, whereas G7 economies show no cointegration and only a weak unidirectional Granger causality from non-manufacturing to manufacturing (significant at the 10% level), consistent with post-industrial ecosystemic autonomy driven by AI and knowledge-intensive services. The contribution of this work is threefold: (i) theoretically, it operationalizes entrepreneurial ecosystems as macro-structural outcomes within a unified econometric framework; (ii) empirically, it identifies a systematic divergence between BRICS Plus and G7 ecosystemic regimes; and (iii) for policy, it shows that industrial upgrading in emerging economies depends on the coherent integration of industrial policy, digital infrastructure, and entrepreneurship, rather than on manufacturing scale alone. Full article

With an exploratory survey administered to 101 alumni who voluntarily and anonymously participated, since its inception in 1999, in the social service program at the Yunus Center, at the Mexican public Autonomous University of Baja California (UABC), five core dimensions of entrepreneurship were assessed: learning, entrepreneurial intention, skill development, inspiration and confidence, and opportunity recognition. The findings indicate that engagement with social microentrepreneurs (marginalized and impoverished) during social service served as a facility for developing entrepreneurial skills and intentions. Over 87% reported increased inspiration, motivation, and confidence, and more than 88% identified entrepreneurial opportunities through their participation. That suggests that interaction with necessity-driven microentrepreneurs as role models can create an innovative, inclusive learning environment among university students, and a possible low-cost method approach for fostering social and economic entrepreneurship, according to the UN’s sustainable development goals SDG 4 (Quality Education) and SDG 8 (Decent Work and Economic Growth). Full article

Human development is increasingly expected to reflect progress in health, education, living conditions, and sustainability. Yet evidence on how specific Sustainable Development Indicators (SDIs) relate to such progress remains limited, especially in studies that jointly consider cross-income heterogeneity, high-dimensional indicators, and nonlinear relationships. This study examines the SDI–HDI relationship across low-, lower-middle-, upper-middle-, and high-income countries using 408 World Bank SDG indicators and UNDP HDI series for 1990–2020. An interpretable Random Forest framework, combined with SHAP rankings and Partial Dependence Plots, identifies the most influential predictors and marginal associations with HDI. The model shows strong predictive performance across income groups and marked heterogeneity in the predictors associated with HDI. In low-income countries, HDI is mainly associated with early-life health conditions and human capital; in lower-middle-income countries, electrification and service access become more prominent; and in upper-middle- and high-income groups, digital connectivity, higher education, and institutional factors gain importance. Mortality-related indicators are consistently associated with lower predicted HDI, whereas literacy, electricity access, and internet use are associated with higher HDI. These results highlight how AI-based analytical tools can support sustainable economic development by identifying income-specific development priorities and structural constraints. They also suggest that disparities in health, education, infrastructure, and digital connectivity may influence the conditions under which entrepreneurial opportunities emerge or remain constrained across development stages. Overall, the SDI–HDI relationship is nonlinear and income-specific, supporting more differentiated, data-driven development strategies. Full article