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A method for emerging technology evaluation. Application to Blockchain and smart data discovery

Author

Listed:
  • Jacky Akoka

    (IMT-BS - DSI - Département Systèmes d'Information - TEM - Télécom Ecole de Management - IMT - Institut Mines-Télécom [Paris] - IMT-BS - Institut Mines-Télécom Business School - IMT - Institut Mines-Télécom [Paris], CEDRIC - Centre d'études et de recherche en informatique et communications - ENSIIE - Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise - CNAM - Conservatoire National des Arts et Métiers [CNAM] - HESAM - HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université)

  • Isabelle Comyn-Wattiau

    (ESSEC Business School)

Abstract

Emerging technologies represent a major innovation that offers significant advances to both private and public organizations. Examples of these technologies are the "Blockchain technology" which combines cryptographic mechanisms and peer-to-peer (P2P) architecture and "Smart Data Discovery" combining artificial intelligence and analytics. The importance of these emerging technologies requires the use of evalua-tion methods in order to understand their contribution and the associat-ed risks. The objective of this article is to propose a method supporting the evaluation of emerging technologies. A guidance approach is pro-posed. It is based on the recognition that emerging technologies are complex systems. Our approach combines three conceptual frame-works: the underlying theory of complex information systems, systems theory, and the ISO 25001 standard devoted to software quality. We propose a multi-criteria hierarchy which serves as the basis for the eval-uation. To illustrate this approach, we apply it to the particular cases of "Blockchain" technology and "Smart Data Discovery".

Suggested Citation

  • Jacky Akoka & Isabelle Comyn-Wattiau, 2017. "A method for emerging technology evaluation. Application to Blockchain and smart data discovery," Post-Print hal-02374089, HAL.
    • Handle: RePEc:hal:journl:hal-02374089
    DOI: 10.1007/978-3-319-67271-7_17
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    Citations

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    Cited by:

    1. Bai, Chunguang & Zhu, Qingyun & Sarkis, Joseph, 2021. "Joint blockchain service vendor-platform selection using social network relationships: A multi-provider multi-user decision perspective," International Journal of Production Economics, Elsevier, vol. 238(C).
    2. Juhyun Lee & Jiho Kang & Sangsung Park & Dongsik Jang & Junseok Lee, 2020. "A Multi-Class Classification Model for Technology Evaluation," Sustainability, MDPI, vol. 12(15), pages 1-16, July.

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