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ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
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Determinants of Technological Innovation Adoption: An Overview of Modern Theories

Authors: Meryeme, Morchid; Cherqaoui, Mariam; Issami, Jihad;

Determinants of Technological Innovation Adoption: An Overview of Modern Theories

Abstract

L'adoption des innovations technologiques est un processus complexe, influencé par divers facteurs individuels, sociaux et organisationnels. Cet article propose une synthèse des principales théories modernes expliquant ce phénomène. La théorie de la diffusion des innovations (Rogers, 1962) met en avant le rôle des catégories d’adoptants et des réseaux de communication, tandis que le modèle d'acceptation de la technologie (Davis, 1989) et la théorie de l’action raisonnée (Fishbein & Ajzen, 1975) s’attachent aux perceptions cognitives et aux attitudes individuelles. La théorie du comportement planifié (Ajzen, 1991) et sa version décomposée (Taylor & Todd, 1995) introduisent le concept de contrôle comportemental perçu. Plus récemment, les modèles UTAUT1 et UTAUT2 (Unified Theory of Acceptance and Use of Technology) ont élargi ces cadres en intégrant des facteurs additionnels tels que l’habitude, la motivation hédonique et les influences contextuelles.À travers une analyse comparative de ces modèles, cette étude met en évidence leurs complémentarités et leurs limites. Elle souligne la nécessité d’une approche plus intégrative et dynamique afin de mieux comprendre l’adoption des technologies dans un environnement numérique en constante évolution. Enfin, l’article discute des perspectives d’amélioration des cadres théoriques existants pour offrir une compréhension plus globale et adaptative des transformations technologiques.

The adoption of technological innovations is a complex process influenced by various individual, social, and organizational factors. This paper provides an overview of key modern theories explaining this phenomenon. The Diffusion of Innovation Theory (Rogers, 1962) highlights the role of adopter categories and communication networks, while the Technology Acceptance Model (Davis, 1989) and the Theory of Reasoned Action (Fishbein & Ajzen, 1975) focus on cognitive perceptions and individual attitudes. The Theory of Planned Behavior (Ajzen, 1991) and its decomposed version (Taylor & Todd, 1995) introduce the concept of perceived behavioral control. More recently, the UTAUT1 and UTAUT2 models (Unified Theory of Acceptance and Use of Technology) have expanded these frameworks by incorporating additional factors such as habit, hedonic motivation, and contextual influences.Through a comparative analysis of these models, this study highlights their complementarities and limitations. It emphasizes the need for a more integrative and dynamic approach to better understand technology adoption in an ever-evolving digital landscape. Finally, the paper discusses perspectives for enhancing existing theoretical frameworks to provide a more comprehensive and adaptive understanding of technological transformations.

Keywords

Théories modernes, Technological innovation; Adoption of innovations; Determinants of adoption; Modern theories; Influential factors., Déterminants de l'adoption, Adoption des innovations, Technological innovation, African Scientific Journal, Determinants of adoption, Influential factors, Facteurs d'influence, Technological innovation Adoption of innovations Determinants of adoption Modern theories Influential factors, Modern theories, Innovation technologique, [SHS.GESTION] Humanities and Social Sciences/Business administration, Adoption of innovations

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green