E-Governance Adoption: Identification of Success Factors from Teachers’ Perspectives in Greece

E-Governance Adoption: Identification of Success Factors from Teachers’ Perspectives in Greece

Ioannis Karavasilis (University of Macedonia,Greece), Kostas Zafiropoulos (University of Macedonia, Greece) and Vasiliki Vrana (Technological Education Institute of Serres, Greece)
DOI: 10.4018/978-1-61350-192-4.ch007
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This chapter introduces Technology Acceptance Model, the Diffusion of Innovation model and constructs of trust, risk and personal innovativeness as a means of studying e-governance adoption. As governments around the world are moving forward in e-governance development it is important to identify factors that determine acceptance under specific circumstances prevailing in each country and give strategic insight to increase the usage of e-governance services. Primary and secondary education teachers responded to an online survey resulting to 230 questionnaires. A SEM validation of the proposed model reveals that Personal Innovativeness, Compatibility and Relative advantage are stronger predictors of intention to use, compared to trust, and perceived risk. The findings give some clues and directions for planning effective e-governance practices and could assist policy-makers with the first guidelines about which areas should be improved in order to enhance e-governance services.
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National and local governments as well as many international organizations across the world, under the pressure of globalization, the changes in technology and the de-regulation in economic and social life, have made significant investments in bringing better governance to the people through the use of improved information and communication technologies (ICT) (Gupta, 2004; Mistree, 2007; Panagis et al., 2008). Information and communication technologies not only have the potential to improve the quality of services, but also to produce cost savings, make government policies and programs more effective, become more transparent, reduce discretionary decision making and introduce simpler methods and procedures in order to address the expectations of the citizens (Singh, 2007). Moreover, they can help public administrations to cope with the many challenges (Commission of European Communities, 2003; Gil-Garcia & Pardo, 2006). However, governments need to understand that e-governance is much more than technical issues (Lau, 2004) and should not focus on ICT itself. A mix of technological, administrative, social, human, legal disciplines must be created (Biasiotti & Nannucci, 2004) and governments should use ICT combined with organizational change and new skills in order to improve public services, democratic processes and public policies (Commission of European Communities, 2003).

Governments have largely left out the most legitimate stakeholders of e-governance the public users, during the conceptualization, development and implementation of the e-governance programs (Jain & Patnayakuni, 2003) and up to now are driving the development agenda of e-governance and the investment in electronic services based on their understanding of what citizens need and without measuring what increases citizens’ willingness to adopt e-governance services. Mofleh & Wanous (1999 p.1) wrote “Governments must first understand variables that influence citizens’ adoption of e-Government in order to take them into account when delivering services online”.

In order to explain and analyze the factors influencing the adoption and use of computer technologies several models have been proposed. They take into consideration attitudes, beliefs and intentions as these are important factors in the adoption of computer technologies (Bagozzi et al., 1992). The theory of reasoned action (TRA) (Fishbein & Ajzen, 1975); the Technology Acceptance Model (TAM) (Bagozzi et al., 1992; Davis, 1980) the theoretical extension of the TAM (TAM2) (Venkatesh & Davis, 2000); the Diffusion of Innovation (DOI) (Rogers, 1995) the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh et al., 2003); the Perceived Characteristics of Innovating (PCI) (Moore & Benbasat 1991); the Prior Experience Model (Taylor & Todd 1995a); the Personal Computing Model (Thompson et al., 1991); the Task-Technology Fit Model (Goodhue 1995; Goodhue & Thompson 1995); the D&M IS Success Model (DeLone & McLean, 1992) and the Updated D&M IS Success Model Model (DeLone & McLean, 2003), are models widely used, alone or in combinations among them or in combination with related theories, to study the users’ acceptance of the new technologies from different perspectives.

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