Laboratory Experiments as a Tool in Empirical Economic Analysis of High-Expectation Entrepreneurship

  • Thomas Andersson
  • Martin G. Curley
  • Piero Formica
Chapter
Part of the Innovation, Technology, and Knowledge Management book series (ITKM)

Abstract

Experimentation for the entrepreneur will often focus on adoption of the innovation and the value that is created for both the end consumer of the innovation and the entrepreneur and the potential ecosystem that is required to deliver the innovation. For an innovation to be sustainable the innovation has to deliver value to the end consumer, the entrepreneur, and the innovation and delivery ecosystem, otherwise the innovation and entrepreneurial activity half-life will be short.

Experiments point out how high-expectation entrepreneurs should cultivate market outcomes, which behavior should guide trust building between the former and their potential financiers, and how policy makers should design and test “rules of the game.” Persistent beta states (i.e., states associated with normal waking consciousness) for the business model and underpinning venture offerings become the norm. Rapid experiment iteration and rapid solution prototyping go hand-in-hand for the high-expectation entrepreneur, with plateaus of stability introduced to the iteration cycles, to enable commercialization and value capture from the evolving offerings.

The educational context under which high-expectation entrepreneurship could be cultivated would draw benefits from experiences made in the medical schools where different performance learning modes are created whose real impact is part of the educational and research activity. In particular, a business school should go beyond doing detached diagnoses, to really developing experiments, even of a therapeutic kind, and testing them clinically in interaction with private and public organizations.

Keywords

Venture Creation Business Idea Entrepreneurial Experimentation Experimental Element Entrepreneurial Team 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Thomas Andersson
    • 1
  • Martin G. Curley
    • 2
  • Piero Formica
    • 3
  1. 1.Jönköping Int. Business School, Jönköping UniversityJönköpingSweden
  2. 2.Intel Corporation and National University of IrelandMaynoothIreland
  3. 3.Jönköping University International Entrepreneurship AcademyBolognaItaly

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