Journal
GOVERNMENT INFORMATION QUARTERLY
Volume 38, Issue 1, Pages -Publisher
ELSEVIER INC
DOI: 10.1016/j.giq.2020.101496
Keywords
Framework; Data analytics; Value; Government; Supervision; eCommerce; Capabilities; Collective capability
Categories
Funding
- PROFILE Project [786748]
- European Union
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This paper explores how to identify the value of data analytics in a government supervision context and what barriers and trade-offs need to be considered and overcome to realize this value. The Value of Data Analytics in Government Supervision (VDAGS) framework, developed based on leading models from the information system literature and case studies from the customs domain, can aid managers and policymakers in understanding the benefits and trade-offs of using data analytics for developing strategies or embarking on new projects. Future research can investigate the applicability of the VDAGS framework in other domains of government supervision.
eCommerce, Brexit, new safety and security concerns are only a few examples of the challenges that government organisations, in particular customs administrations, face today when controlling goods crossing borders. To deal with the enormous volumes of trade customs administrations rely more and more on information technology (IT) and risk assessment, and are starting to explore the possibilities that data analytics (DA) can offer to support their supervision tasks. Driven by customs as our empirical domain, we explore the use of DA to support the supervision role of government. Although data analytics is considered to be a technological breakthrough, there is so far only a limited understanding of how governments can translate this potential into actual value and what are barriers and trade-offs that need to be overcome to lead to value realisation. The main question that we explore in this paper is: How to identify the value of DA in a government supervision context, and what are barriers and trade-offs to be considered and overcome in order to realise this value? Building on leading models from the information system (IS) literature, and by using case studies from the customs domain, we developed the Value of Data Analytics in Government Supervision (VDAGS) framework. The framework can help managers and policymakers to gain a better understanding of the benefits and trade-offs of using DA when developing DA strategies or when embarking on new DA projects. Future research can examine the applicability of the VDAGS framework in other domains of government supervision.
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