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Dynamic Business Models: a Proposed Framework to Overcome the Death Valley

Author

Listed:
  • Angelo Corallo

    (University of Salento)

  • Fabrizio Errico

    (University of Salento)

  • Maria Elena Latino

    (University of Salento)

  • Marta Menegoli

    (Naica S.C.)

Abstract

The ex ante definition of business model offers the possibility to create a static picture of “how” the company is able to generate value in a given moment. But is this business model able to generate value over time? The time factor of the value proposition life cycle is not usually taken into account. This paper, starting from the lean canvas model (Maurya 2012), proposes a framework able to consider the temporal factor and, coming from Rogers’s innovation diffusion theory (Die Diffusion von Innovationen in der Telekommunikation, 17, 25–38, Rogers 1995), to evolve the business model from a single picture to a set of pictures representing the many phases of the value proposition life cycle. A local context analysis was conducted, interviewing 10 CEOs of University of Salento start-ups, and the framework’s tool kit was developed: application methodology, questionnaire, and glossary. To validate the tools and methodology, a real business case was considered. Using the framework proposed in the business model definition would allow managers of start-ups to identify several marketing strategies, channels, and key metrics dedicated to each customer category.

Suggested Citation

  • Angelo Corallo & Fabrizio Errico & Maria Elena Latino & Marta Menegoli, 2019. "Dynamic Business Models: a Proposed Framework to Overcome the Death Valley," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 10(3), pages 1248-1271, September.
    • Handle: RePEc:spr:jknowl:v:10:y:2019:i:3:d:10.1007_s13132-018-0529-x
    DOI: 10.1007/s13132-018-0529-x
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    References listed on IDEAS

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    3. B. Demil & X. Lecocq, 2010. "Business model evolution : in search of dynamic consistency," Post-Print hal-00572915, HAL.
    4. Corbett, Andrew C., 2007. "Learning asymmetries and the discovery of entrepreneurial opportunities," Journal of Business Venturing, Elsevier, vol. 22(1), pages 97-118, January.
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    Cited by:

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    2. Kirill V. Simonov & Natalia A. Girfanova, 2023. "Managing a high-tech startup: A case of machine vision for the poultry industry," Upravlenets, Ural State University of Economics, vol. 14(2), pages 47-61, May.

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