Citizens’ adoption of an electronic government system: towards a unified view

By Nripendra P. Rana, Yogesh Kumar Dwivedi, Banita Lal, Michael D. Williams, Marc Clement. Information Systems Frontiers, 2015

380 citations recorded by the source corpus.

Sluggish adoption of emerging electronic government (eGov) applications continues to be a problem across developed and developing countries. This research tested the nine alternative theoretical models of technology adoption in the context of an eGov system using data collected from citizens of four selected districts in the state of Bihar in India. Analysis of the models indicates that their performance is not up to the expected level in terms of path coefficients, variance in behavioural intention, or the fit indices of the models. In response to the underperformance of the alternative theoretical models to explain the adoption of an eGov system, this research develops a unified model of electronic government adoption and tests it using the same data. The results indicate that the proposed research model outperforms all alternative models of technology adoption by explaining 77 % of variance in behavioural intention, with acceptable values of fit indices and significant relationships between each pair of hypothesised factors.

Subfields: Information Systems and Management, Political Science and International Relations, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/ff3ef6faf7e454c83914b95d5ec9cff4eef6d0df

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Citations in the corpus

Mobile food ordering apps: An empirical study of the factors affecting customer e-satisfaction and continued intention to reuse (2020, background): “Furthermore, the applicability of UTAUT2 was shown in relation to mobile banking applications in Jordan (Alalwan, Dwivedi, & Rana, 2017).”
Investigating the impact of social media advertising features on customer purchase intention (2018, methodology): “Informativeness was articulated by Rotzoll and Haefner (1990) as the extent to which a firm can provide adequate information based on which customers can make better purchasing decisions.”
Re-examining the Unified Theory of Acceptance and Use of Technology (UTAUT): Towards a Revised Theoretical Model (2017, methodology): “Meta-analysis enables results from multiple studies (Glass 1976; Hunter and Schmidt 1990; Rana et al. 2015a; Wu and Du 2012; Wu and Lederer 2009) to be accumulated for estimates of the true effect sizes of relationships.”
Blockchain adoption in operations and supply chain management: empirical evidence from an emerging economy (2020, background): “…studies that used facilitating conditions (H1) in technology adoption (Venkatesh et al. 2003; Venkatesh, Thong, and Xu 2012; Hew et al.2015; Rana et al.2017), our model showed that facilitating conditions positively affect the behavioural intention to adopt a technology (in this case, BCT).”
Understanding consumer adoption of mobile payment in India: Extending Meta-UTAUT model with personal innovativeness, anxiety, trust, and grievance redressal (2020, methodology): “Attitude has also been used as a mediating variable between performance expectancy and effort expectancy across several studies (e.g., Alshare & Lane, 2011; Rana et al., 2017; Šumak et al., 2010) that have used UTAUT as a basic model.”
An empirical validation of a unified model of electronic government adoption (UMEGA) (2017, background): “Prior literature on perceived risk found that 80 percent of Internet users are concerned about making their personal identities known on the web (Gonsalves, 2005; Rana et al., 2015; Schaupp & Carter, 2010).”
Advances in Social Media Research: Past, Present and Future (2017, background): “It is noteworthy that dominant IS adoption theories such as Unified Theory of Acceptance and Use of Technology (Dwivedi et al. 2017b, c; Rana et al. 2017; Venkatesh et al. 2003), Technology Acceptance Model (Davis 1989) and Innovation Diffusion Theory (Kapoor et al. 2015) are less widely utilised.”
Consumer use of mobile banking (M-Banking) in Saudi Arabia: Towards an integrated model (2019, background): “Such results are comparable with those of prior studies that have examined related issues of mobile banking (i.e. Alalwan et al., 2017; Lee and Chung, 2009; Rana et al., 2017; Wang and Shih, 2009; Yu, 2012; Zhou et al., 2010).”