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Strategic Knowledge Arbitrage and Serendipity (SKARSE™) in Action

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  • Elias Carayannis

Abstract

In today’s globalizing and hypercompetitive marketplace, knowledge, and learning are the only capabilities that can provide sustained competitive advantage. “Knowledge” is the content of learning and a firm gains competitive superiority either by knowing something that its competitors do not know or by having a certain type of knowledge that cannot easily be replicated. “Learning” is the process of gaining new knowledge, so that the firm is constantly accumulating and assimilating knowledge and this becomes the basis for creating and improving organizational routines. Learning is the also the basis of what strategists are calling firms’ “dynamic capabilities”, which enable them to build new competences in an evolutionary cycle to maintain an edge in an ever-changing industrial environment. This paper briefly explores conceptually and attempts to validate empirically the nature and dynamics of strategic knowledge arbitrage and serendipity (SKARSE™) as real options drivers (RODs). The author reviews and assesses how, why, and when SKARSE™ serve as high value-adding RODs and identifies critical success and failure factors in designing and implementing real options that leverage SKARSE™. He also examines the lessons learned from actual mergers and acquisitions. Finally, he addresses the operation of SKARSE™ in the context of a complex evolutionary ecosystem shaped by the dynamics of co-opetition, co-evolution, and co-specialization. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Elias Carayannis, 2014. "Strategic Knowledge Arbitrage and Serendipity (SKARSE™) in Action," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 5(2), pages 203-211, June.
  • Handle: RePEc:spr:jknowl:v:5:y:2014:i:2:p:203-211
    DOI: 10.1007/s13132-012-0142-3
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    Citations

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    Cited by:

    1. Jan Stejskal & Petr Hajek, 2019. "Modelling collaboration and innovation in creative industries using fuzzy set qualitative comparative analysis," The Journal of Technology Transfer, Springer, vol. 44(3), pages 981-1006, June.
    2. G. Martinidis & N. Komninos & E. Carayannis, 2022. "Taking into Account the Human Factor in Regional Innovation Systems and Policies," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 13(2), pages 849-879, June.
    3. Elias G. Carayannis & Mike Provance & Evangelos Grigoroudis, 2016. "Entrepreneurship ecosystems: an agent-based simulation approach," The Journal of Technology Transfer, Springer, vol. 41(3), pages 631-653, June.

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