TAILORING EFFECTIVE USE MODEL OF BIG DATA IN MANAGERIAL CONTEXT: INSIGHTS FROM AN EMPIRICAL STUDY IN ARMENIAN COMPANIES
Résumé
This article explores the managerial dimensions of big data phenomenon, focusing on the challenge of customizing an effective use model within companies. The central inquiry revolves around tailoring such a model to suit the specific needs of big data user companies. To address this, the study adopts a conceptual framework proposed by Surbakti and his co-authors, which delineates the effective use of big data. The primary methodology involves quantitative analysis of data gathered from 211 surveys completed by Armenian industry professionals. Examination of the collected data through statistical analysis reveals the presence of two distinct cohorts within the realm of big data users: "novice users" and "advanced users". The main theoretical contribution that we aim for in this research is empirically proving the global validity of the studied model and demonstrating its flexibility of application in these two types of use cases of big data. While the conceptual model is found to be applicable to both types of users, its implementation varies significantly between the two groups. Therefore, from a managerial point of view, our results lead a manager to think at first on the maturity of its company in terms of big data. Implementing a solution is not enough. By thinking in terms of novice vs advanced, it creates two different managerial courses of action. Moreover, we propose the variables a manager has to analyze depending on this maturity.
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