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Adoption of Cloud Computingin Emerging Countries: The Role of the Absorptive Capacity

Adel Ben Youssef, Walid Hadhri () and Téja Meharzi
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Téja Meharzi: GREDEG - Groupe de Recherche en Droit, Economie et Gestion - UNS - Université Nice Sophia Antipolis - UCA - Université Côte d'Azur - CNRS - Centre National de la Recherche Scientifique

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Abstract: This paper aims at developing a theoretical framework that explains the decision of cloud computing (CC) adoption in Emergent Countries. It emphasizes the specific role of the technological absorptive capacity especially when the firm is seeking innovation by adopting CC. The absorptive capacity considered in this work is close to the work of Todorova and Durisin (2007) who proposed a framework linking both the contributions of Cohen and Levinthal (1989) and Zahra and Georges (2002).To test our theoretical claims, we estimated two models predicting the probability of adopting CC and adopting CC for innovative aims with (1) competitive pressure and external environment, (2) Technology perceived impacts, and (3) technological absorptive capacity of the firm. We use control variables such as size, sector of activity and seniority in order to control the general purposes of our claims. We use a bivariate probit model in order to understand the determinants of the decision of adoption and an ordered probit with sample selection in order to understand the determinant of adoption of CC for innovative aims. Based on a face-to-face questionnaire administered to a random sample of 350 Tunisian firms, and using a Heckman selection method. Our empirical findings confirm our theoretical claims and show that technology perception is key factor for CC adoption (for general purposes) and that the absorptive capacity is fundamental when the adoption of CC is for innovation goals.We found also that competition pressureis an important explanatory factor:the more competitors that adopt this technology, the more likely the firm adopt it.

Keywords: Technology Adoption; IPRs; ProbitModel; Absorptive Capacity; Tunisia; Innovation; Heckman selection method; Cloud Computing; Information and Communication Technologies (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cse, nep-ino and nep-sbm
Date: 2015-12-15
Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-01302772
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Published in Systèmes d'Information et Management, Eska, 2015, 20 (4)

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