CONTEXTUAL MISMATCH AND STARTUP MORTALITY: A COMPARATIVE CASE STUDY OF REPLICATED SILICON VALLEY LOGISTICS MODELS IN NIGERIA

The Silicon Valley logistics model which is characterised by algorithmic routing, gig-economy labour, asset-light scaling, and on-demand delivery has proven viable in mature markets, this is due to standardised infrastructure and high digital payment penetration. However, its direct transplantation into emerging economies frequently produces operational friction and venture failure. In Nigeria, numerous logistics startups have attempted to replicate U.S.-based platforms, yet many have exited, pivoted, or scaled back despite substantial venture capital inflows. This paper presents the conceptual architecture of a qualitative multiple-case study investigating the causal relationship between contextual mismatch and startup mortality in Nigeria's logistics sector. Drawing on Institutional Theory (North, 1990; Scott, 2014) and Resource Dependence Theory (Pfeffer & Selznick, 1978), the study contrasts four failed or heavily pivoted platform clones; Jumia Food, Bolt Food, Kwik, and Kobo360 against four contextually adapted and viable firms: GIG Logistics, Chowdeck, MAX, and Red Star Express (Click & Ship). Key mismatch dimensions include infrastructural voids, payment system constraints, addressing gaps, and trust deficits. Expected outputs include a Logistics Mismatch Matrix, a contextual adaptation framework, and evidence-based policy recommendations for emerging market logistics development.