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Dani Abu Ghaida

Diplômé DBA - 2016

Titre de thèse

BI Adoption in the Telecom Industry, an MEA outlook.

Superviseur(s)

Isabel-Maria Bodas-Freitas

Dr. Dani Abu Ghaida oversees the IT and digital functions across Dar Group. He leads the IT and digital organisations through their largest transformation to date.
Dani is responsible for global relations continuity with the IT and digital ecosystem players across the U.S., EMEA ,and Asia. Previously, he served as head of the Group PMO at MTN Group, CIO of two MTN OPCOs and at the Telecom Center of Excellence for EY MENA.  Dani holds a DBA from GEM, an MS from LAU, and ExPs from MIT, Stanford, and Oxford.

The primary aim of the study is to identify the main factors that drive the diffusion of technology innovations, and the market as well as efficiency benefits associated with the adoption of such innovations. Based on the examined literature, I thereby propose to examine how various factors from the four adoption dimensions (organizational, technological, economic and social dimensions) influence the adoption decision, as well as how the adoption motivations influence the achieved benefits. Empirically, this study investigates the adoption of Business Intelligence (BI) in the telecom industry in the Middle East and Africa (MEA) based on an original survey performed by telecom professionals from MEA. The objectives of the survey were to gain a better understanding of why companies decide to adopt BI, what are the barriers to adoption and what the BI adoption benefits are. We used Logit and Heckman models to estimate the impact of organizational, technological, economic and social factors on BI adoption and their benefits. The analysis accounts for the characteristics of the firm and the forms in which BI was implemented. Results show that the company characteristics such as the multinational identity, the company’s revenue per user and the use of best practices explain BI adoption. Results also show that various characteristics of the company along with the motivations for BI adoption and forms of BI implementations significantly explain market and efficiency benefits from BI. Results and their implications for policy, as well as limitations of this research study are discussed in the last chapter.