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Using predictive analytics for user segmentation in e-government

Using predictive analytics for user segmentation in e-government

Proceedings of the Internationsl Conference on Electronic Governance and Open Society Challenges in Eurasia - eGose '17, 2017
Bojan Cestnik
Abstract
Studying relations between customer characteristics and usability requirements for online services remains a challenging task in e-government services development. In this paper we present the findings from a survey conducted among the users of an e-government service in public housing tender for buying housing facilities, where citizens were allowed to choose between two application submission channels: electronic submission and paper submission. Our aim was to detect the user characteristics that can be used to differentiate between the users that deliberately decide for the electronic form submission channel and those that prefer using the paper one. We show that such factors can be used to identify citizen groups that might require a more focused communication strategy to reduce the risks of potential e-government services dropouts. Our approach is aligned with the user centricity principle used in related studies, where the focus is on the ease and speed of using digital services online as perceived by the users.

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