Effective and efficient usage of big data analytics in public sector

Abstract

Purpose This study aims to achieve three goals: present a holistic, flexible and dynamic model; define the model’s factors and explain how these factors lead to effective and efficient usage of big data; and generate indexes based on experts’ input to rank them based on their importance. Design/methodology/approach This paper uses the analytic hierarchy process, a quantitative method of decision-making, to evaluate the importance of the factors presented in the model. The fundamental principle of the overall model is that of a dynamo which is borrowed from electromagnetic physics. The model is also based on three IS theories. Findings Technological advancements and data security are among the most important factors that may impact the effectiveness and efficiency of big data usage. Authentication, governments’ focus on it and transparency and accountability are the most important factors in techno-centric, governmental-centric and user-centric factors, respectively. Research limitations/implications The findings of this paper confirmed earlier findings in the literature and quantitatively assessed some of the factors that were conceptually presented. This paper also presented a framework that can be used in future studies. Practical implications Policy and decision-makers may need to upgrade pertinent technologies such as internet security, frame policies toward information technology (IT) and train the users. Originality/value This paper fills a gap in the literature by presenting a comprehensive study of how different factors dynamically contribute to the effective usage of big data in the public sector. It also quantitatively presents the importance of the factors based on the data collected from 12 IT experts.