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Conceptualizing and qualifying disruptive business models

Author

Listed:
  • Giovana Sordi Schiavi
  • Ariel Behr
  • Carla Bonato Marcolin

Abstract

Purpose - This paper aims to elaborate a set of characteristics that conceptualize and qualify a disruptive business model. Design/methodology/approach - The literature on disruptive business models will be analyzed using the latent semantic analysis (LSA) technique, complemented by content analysis, to obtain a more precise qualification and conceptualization regarding disruptive business models. Findings - The results found described concepts already described in the theory. However, such findings, highlighted by the LSA, bring new perspectives to the analysis of the disruptive business models, little discussed in the literature and which reveal important considerations to be made on this subject. Research limitations/implications - It should be noted, about the technique used, a limitation on the choice of the number of singular values. For this to be a problem in the open literature, the authors tried to work not just with the cost-benefit ratio given the addition of each new dimension in the analysis, as well as a criterion of saturation of the terms presented. Practical implications - The presentation of this set of characteristics can be used as a validation tool to identify if a business is or is not a disruptive business model by managers. Originality/value - The originality of this paper is the achievement of a consolidated set of characteristics that conceptualize and qualify the disruptive business models by conducting an in-depth analysis of the literature on disruptive business models through the LSA technique, considering the difficulty of obtaining precise concepts on this subject in the literature.

Suggested Citation

  • Giovana Sordi Schiavi & Ariel Behr & Carla Bonato Marcolin, 2019. "Conceptualizing and qualifying disruptive business models," RAUSP Management Journal, Emerald Group Publishing Limited, vol. 54(3), pages 269-286, July.
  • Handle: RePEc:eme:rauspp:rausp-09-2018-0075
    DOI: 10.1108/RAUSP-09-2018-0075
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    Cited by:

    1. Jing Yang & Jun Wang & Mengyang Gao, 2023. "Community Evolution Analysis Driven by Tag Events: The Special Perspective of New Tags," Mathematics, MDPI, vol. 11(6), pages 1-18, March.

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