Abstract

The world is going to be more and more digital with effective utilization of information and communication technologies in government services to provide services to their citizens. In developing countries, public cloud is now considered a powerful platform, for providing scalable and cost effective public services to the citizens, due to their limited resources and budget. Public cloud has been adopted by both developed and developing countries for providing e-government services. User’s adoption is equally essential just like the government’s adoption of new services. Government needs to assess the user’s behavior intention and use behavior before choosing public cloud as platform for their innovative citizen’s services also known as government to citizen’s services (G2C). As citizen’s information is stored on public cloud, which is provided by a third party, so user’s concerns about privacy of information may affect the adoption of these services. The aim of this study is to find out the privacy factors that influence the adoption of e-government services by choosing and recommend suitable technology adoption model. As a methodology, the Unified Theory of Acceptance and Use of Technology (UTAUT) Model was amended to add two additional privacy variables from e-commerce domain i.e., Perceived Internal Privacy Risk (PIPR) and Cloud Information Privacy Concern (CIPC). Thus the new model included in addition to PIPR and CIPC, its own four elements of performance expectancy (PE), Effort Expectancy (EE), Social Influence (SI), and Facilitating Condition (FC). The data was collected from respondents who had used both public cloud and e-government services. Structure Equation Modeling (SEM) was used to investigate the effect of all variables on Behavior Intention (BI) and Use Behavior (UB). The findings show that Performance Expectancy (PE), Effort Expectancy (EE) and Social Influence (SI) had positive effects on user’s Behavior Intention (BI) while Cloud Information Privacy Concerns (CIPC) and Perceived Internet Privacy Risks (PIPR) had negative effects on Behavior Intention (BI). The Facilitating Conditions (FC) and Behavior Intention (BI) had a strong positive effect on User Behavior (UB).

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