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A Systematic Review for Predictive Models of IS Adoption

Rhouma Naceur, Yan Cimon and Robert Pellerin
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Rhouma Naceur: Laval University, Canada
Yan Cimon: Laval University, Canada
Robert Pellerin: École Polytechnique de Montréal, Canada

International Journal of Enterprise Information Systems (IJEIS), 2021, vol. 17, issue 1, 1-21

Abstract: The implementation of a new information system could be a risky decision for any company. In fact, many implementation decisions fail. Studying the success of IS adoption is necessary to identify the factors that impact success and to prevent risk. Many predictive algorithms and models have been used in order evaluate the IS adoption. This paper surveys the relevant predictive models that have been used in this area in the past 20 years. The authors aim to focus on information system adoption, as well as existing adoption models and theory, to put forth a state of the art survey on the issue to further understand the predictive models behind a successful adoption. Therefore, this paper opted for a systematic review to identify all of the articles that study IS adoption and that are using or suggesting a predictive model.

Date: 2021
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International Journal of Enterprise Information Systems (IJEIS) is currently edited by Gianluigi Viscusi

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Handle: RePEc:igg:jeis00:v:17:y:2021:i:1:p:1-21