The Reasons of Low E-Government Take-Up in Europe: An Exploratory Analysis

The Reasons of Low E-Government Take-Up in Europe: An Exploratory Analysis

Aykut Arslan (Piri Reis University, Turkey)
DOI: 10.4018/978-1-4666-5868-4.ch013
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Abstract

Despite the efforts in terms of policies and investments, take-up of e-government services is slow, obscuring the overall benefits of e-government itself and still far from satisfactory today. Differences in uptake of e-government services across European countries seem to be independent from the quality and quantity of the supply. The data show a gap between the supply and use of e-government services in general; in other words, suggesting a limited correlation between the provisions of sophisticated e-government services on the one hand and the take-up of e-government services on the other. This signals a broader and diversified situation. To explore the determinants of low e-government take-up in European context, this chapter examines the aggregate data of 29 countries by conducting T-tests and Mann-Whitney U analyses.
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1. Introduction

The soaring adoption of information and communication technologies (ICTs) in the world has enhanced hopes for proliferation of benefits such as the improvement of public services in terms of quality and productivity through the reduction of costs and time to deliver public services (Ferro & Molinari, 2010); the increase of transparency, accountability (Colesca, 2009), and trust in public institutions (User satisfaction and impact, 2008; Colesca, 2009). However, to realize such benefits and return on investments, the only possible way is the widespread use of the e-government services (Verdegem & Verleye, 2009). There are assertions that, in terms of practical experiences and in the light of researches, citizens’ acceptance of public e-services is quite below (Bavec, 2008; User satisfaction and impact, 2008; OECD, 2009; Ferro & Molinari, 2010). In support of this argument the resent figures regarding the use of the Internet for interaction with public authorities in the EU27+ highlight that only 42% of individuals aged between 16 to 74 use e-government services despite the 82% average online availability of the services (9th Benchmark Report, 2010, p. 13). What’s more, the differences between countries, ranging from take-up figures of 85% for the most advanced to 29% for the bottom of the league are remarkable. The report argues that the preference of conventional ways of interacting by significant numbers of citizens forces even the most innovative public administrations to run a great deal of their services through more traditional and often cost-intensive way. On the other hand it continues to pinpoint a substantial gap between investment in making public services available and their take-up which is “too great”(9th Benchmark Report, 2010, p. 80) (up to 85%, with a 46% average in EU27+). In addition, the report holds a negative belief about the quality and availability of information regarding improvements and criticizes the methods of delivery for these services as inadequate. A similar view which supports the criticism above holds the governments responsible for spending billions of dollars on “e-enabling” of vertical silos or stovepipes since 1990s disregarding citizens’ needs (CS Transform White Paper, 2010). Yet, there are endeavors to become more citizen-centric instead of one-size-fits-all approaches and thus applying methods for user needs identification and more segmentation for personalization.

Differences in uptake of e-government services across European countries seem to be independent from the quality and quantity of the supply (OECD, 2009). The data show a gap between the supply and demand (use of e-government services) in general; in other words, suggesting a limited correlation between the provisions of sophisticated e-government services on the one hand and the take-up of e-government services on the other. This signals a broader and diversified situation. Therefore, unlike studies grounded on behavioral theories of technology acceptance, and to provide more generalizable cause and effect relationship, this paper seeks answers in analyzing panel data from different sources by employing T-test and Mann-Whitney U analyses.

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