Characterization of Cloud Computing Reversibility as Explored by the DELPHI Method

Wafa Bouaynaya ()
Additional contact information
Wafa Bouaynaya: CRIISEA - Centre de Recherche sur les Institutions, l'Industrie et les Systèmes Économiques d'Amiens - UR UPJV 3908 - UPJV - Université de Picardie Jules Verne

Post-Print from HAL

Abstract: Cloud computing already raises numerous security questions related to outsourced data confidentiality. Several companies are starting to require the reversibility of their cloud computing. They want to redirect their information systems to another provider or backsourcing their activities. Cloud computing reversibility is considered to be one of the first obstacles to service development; however, few researches have been conducted on this field. We propose characterizing the reversibility of cloud computing using a deductive approach. We suggest ten research hypotheses that identify the guarantees, objectives and process of reversibility. This research is based on a three-lap Delphi method, supported by 18 experts working on cloud computing projects. This article contributes to characterizing cloud computing reversibility and parametric theorization through a new coefficient of concordance proposal. This indicator helps to assess the experts' agreement to or rejection of a hypothesis. \textcopyright 2019, Springer Science+Business Media, LLC, part of Springer Nature.

Keywords: Outsourced datum; Reversibility; Service development; Backsourcing; Cloud computing; Computer networks; Concordance coefficient; Delphi method; Information systems (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Published in Information Systems Frontiers, 2020, 22 (6), pp.1505--1518. ⟨10.1007/s10796-019-09947-5⟩

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-03678283

DOI: 10.1007/s10796-019-09947-5

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().