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From MVPs to Pivots: A Hypothesis-Driven Journey of Two Software Startups

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Software Business (ICSOB 2018)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 336))

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Abstract

Software startups have emerged as an interesting multiper-spective research area. Inspired by Lean Startup, a startup journey can be viewed as a series of experiments that validate a set of business hypotheses an entrepreneurial team make explicitly or inexplicitly about their startup. It is little known about how startups evolve through business hypothesis testing. This study proposes a novel approach to look at the startup evolution as a Minimum Viable Product (MVP) creating process. We identified relationships among business hypotheses and MVPs via ethnography and post-mortem analysis in two software startups. We observe that the relationship between hypotheses and MVPs is incomplete and non-linear in these two startups. We also find that entrepreneurs do learn from testing their hypotheses. However, there are hypotheses not tested by MVPs and vice versa, MVPs not related to any business hypothesis. The approach we proposed visualizes the flow of entrepreneurial knowledge across pivots via MVPs.

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Author information

Authors and Affiliations

  1. Free University of Bozen-Bolzano, 39100, Bolzano, Italy

    Dron Khanna & Xiaofeng Wang

  2. University of Southeast Norway, 3800, Bø i Telemark, Norway

    Anh Nguyen-Duc

Authors
  1. Dron Khanna
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  2. Anh Nguyen-Duc
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  3. Xiaofeng Wang
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Corresponding author

Correspondence to Dron Khanna .

Editor information

Editors and Affiliations

  1. Blekinge Institute of Technology, Karlskrona, Sweden

    Krzysztof Wnuk

  2. Utrecht University, Utrecht, The Netherlands

    Sjaak Brinkkemper

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Khanna, D., Nguyen-Duc, A., Wang, X. (2018). From MVPs to Pivots: A Hypothesis-Driven Journey of Two Software Startups. In: Wnuk, K., Brinkkemper, S. (eds) Software Business. ICSOB 2018. Lecture Notes in Business Information Processing, vol 336. Springer, Cham. https://doi.org/10.1007/978-3-030-04840-2_12

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  • DOI: https://doi.org/10.1007/978-3-030-04840-2_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-04839-6

  • Online ISBN: 978-3-030-04840-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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