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Effective and efficient usage of big data analytics in public sector

Effective and efficient usage of big data analytics in public sector 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/approachThis 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.FindingsTechnological 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/implicationsThe 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 implicationsPolicy and decision-makers may need to upgrade pertinent technologies such as internet security, frame policies toward information technology (IT) and train the users.Originality/valueThis 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Transforming Government: People, Process and Policy Emerald Publishing

Effective and efficient usage of big data analytics in public sector

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Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
1750-6166
eISSN
1750-6166
DOI
10.1108/tg-08-2019-0083
Publisher site
See Article on Publisher Site

Abstract

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/approachThis 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.FindingsTechnological 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/implicationsThe 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 implicationsPolicy and decision-makers may need to upgrade pertinent technologies such as internet security, frame policies toward information technology (IT) and train the users.Originality/valueThis 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.

Journal

Transforming Government: People, Process and PolicyEmerald Publishing

Published: May 20, 2020

Keywords: Big data efficiency; Data effectiveness; Data security; Analytic hierarchy process

References