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1 – 1 of 1Jason Lortie, Kevin Cox, Sean DeRosset, Regina Thompson and Scott Kelly
Entrepreneurial practice often relies on the minimum viable product (MVP) to test business model hypotheses, yet the conceptualization of its makeup remains inadequately defined…
Abstract
Purpose
Entrepreneurial practice often relies on the minimum viable product (MVP) to test business model hypotheses, yet the conceptualization of its makeup remains inadequately defined, particularly in uncertain startup contexts. This paper aims to clarify how entrepreneurs should think about MVPs in terms of their uses, goals and essential components to enhance their effectiveness as a tool for navigating uncertainty.
Design/methodology/approach
Existing literature on MVPs is broad and often overlapping, leading to confusion regarding essential components and best practices for MVP development. Through a systematic analysis of existing published definitions, this paper offers clarity by proposing a framework that breaks the MVP concept up into process, goals and the fundamental elements necessary to launch an MVP. By doing so, it provides actionable guidance for entrepreneurs seeking to utilize MVPs in their business model testing endeavors.
Findings
This conceptual paper critically examines the lean startup approach, seeking to disentangle the complexities surrounding MVP development. Drawing on existing literature and practical insights, the study identifies and articulates a framework that clarifies the MVP concept along with the core elements required for creating a viable MVP, including (a) artistic elements, (b) a robust distribution channel and (c) an effective user feedback mechanism.
Originality/value
This paper contributes to theory development and pedagogical practices by providing a structured framework for understanding and implementing MVPs in entrepreneurial contexts. By identifying the minimal category elements of an MVP, it offers practical insights into entrepreneurs and educators alike, facilitating effective business model hypothesis testing in varied and uncertain environments.
Details