Entrepreneurial Ecosystem Dynamics and Startup Survival in Emerging Markets

Thesis Abstract

This study investigates how entrepreneurial ecosystem dynamics influence startup survival in emerging markets, addressing the persistent high failure rates and uneven ecosystem development that constrain entrepreneurial growth and job creation. The aim is to identify the mechanisms through which ecosystem components—policy, finance, networks, human capital, and market interfaces—jointly affect startup survival trajectories, and to develop a parsimonious model linking ecosystem maturity to venture persistence. Specific objectives are (1) to examine the association between policy stability, access to early-stage finance, and startup survival; (2) to assess how network centrality and collaboration intensity moderate the relationship between entrepreneurial capability and survival outcomes; (3) to evaluate the role of human capital quality and availability in sustaining ventures over time; (4) to test the mediating effect of market access and customer validation on survival; and (5) to compare survival determinants across three representative emerging markets with differing institutional contexts. The study adopts a sequential explanatory mixed-methods design, combining a large-scale quantitative survey with a subsequent qualitative inquiry to illuminate mechanisms. The population comprises active registered startups within the information and communications technology, consumer services, and manufacturing sectors across Nigeria, Kenya, and Vietnam. A stratified random sample of 600 startups will be surveyed, followed by 40 in-depth interviews with founders, investors, and ecosystem actors selected through purposive sampling to capture diverse experiences. Data collection will employ a structured questionnaire aligned to established scales for ecosystem maturity, entrepreneurial orientation, social capital, access to finance, and resilience, complemented by interview guides exploring contextual nuances. Validity will be enhanced through pilot testing, expert reviews, and triangulation with secondary data from policy documents and ecosystem reports. Reliability will be ensured via Cronbach’s alpha for multi-item scales and test-retest procedures on a subsample. Quantitative analysis will proceed with descriptive statistics to profile the sample, followed by multivariate regression analyses to test direct effects of ecosystem components on startup survival, and structural equation modeling (SEM) to assess the proposed model with latent constructs for ecosystem maturity, entrepreneurial capability, and survival propensity. Network measures will be derived from respondent-reported collaboration intensity using social network analysis (SNA) metrics such as degree centrality and betweenness. Mediation analyses will examine indirect effects of human capital and market access, while moderation analyses will test the buffering role of network density on capital-equipped ventures. Qualitative data will be analyzed thematically using a deductive-inductive approach, drawing on the resource-based view (RBV) and the effectuation theory to interpret pragmatic survival strategies under uncertainty. Thematic triangulation will clarify how contextual features in each country shape the observed relationships. Key expected findings include (i) stronger policy consistency and accessible patient capital positively correlate with higher survival rates, (ii) higher network centrality amplifies the positive impact of entrepreneurial orientation on survival, (iii) superior human capital quality increases persistence through enhanced adaptability and learning, (iv) robust market validation acts as a key mediator between ecosystem support and survival, and (v) institutionally diverse contexts yield different magnitudes of ecosystem effects, underscoring the importance of tailored policy and ecosystem interventions. The study contributes to knowledge by integrating RBV and constructivist interpretations of effectuation within an ecosystem perspective to elucidate survival pathways in resource-constrained environments. It advances measurement of ecosystem maturity and demonstrates how network dynamics interact with human and financial capital to influence venture outcomes in emerging markets. Policy implications include prioritizing coherent regulatory regimes, targeted early-stage financing, and programs to strengthen founder networks and talent pipelines. Practical implications highlight the need for ecosystem builders to design context-sensitive interventions that align policy, finance, and human capital development with demand-side market access. Limitations include potential response bias and cross-country comparability constraints; future work could extend to longitudinal tracking and incorporation of additional sectors such as agriculture and health tech.