Examining the Inter-relationships of UTAUT Constructs in Mobile Internet Use in India and Germany

Examining the Inter-relationships of UTAUT Constructs in Mobile Internet Use in India and Germany

Jayanth Jacob (Anna University, Chennai, India) and Murugan Pattusamy (University of Hyderabad, Chennai, India)
Copyright: © 2020 |Pages: 13
DOI: 10.4018/JECO.2020040103
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The authors have tested the relationships between UTAUT constructs and the behavioral intention to use mobile internet technology with samples drawn from India and Germany. They have also tested the moderating role of age, gender, and user experience between UTAUT constructs and behavioral intention using hierarchical regression analysis. Partial Least Square Structural Equation Modelling (PLS SEM) was used to test the UTAUT without moderating effects. The results show that UTAUT constructs influence behavioral intention. Behavioral intention also predicts the use of technology. Empirical evidence was established for the UTAUT model based on the samples from both countries. “Experience of use” moderated the relationship between effort expectancy and behavioral intention in the Indian sample. The last section of the article discusses the contributions of this research to theory, its practical implications, limitations, and the scope for future research.
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Mobile internet technology is a billion-dollar industry across the globe and till June 2017 there are 320.57 million users of mobile internet in India (Statista, 20018), ranked third after China (where 97.5% of the netizens were mobile internet users (CINIC, 2018)) and the United States of America (USA) (Kant, Mairaj, & Kamna, 2015). In Germany, 37% of the daily communications were happening through digital platforms using digital media (Berger, 2014) and 98% of the internet users were also using mobile internet (CNNIC, 2018)) out of the 63.3 million internet users (Statista, 20018).

In the domain of Information Systems (IS) the Unified Theory of Acceptance and Use of technology (UTAUT) has gained significant use and application. The earliest UTAUT model published by Venkatesh, Morris, Davis, and Davis (2003) yielded 22,381 citations (Google Scholar citation on 28-12-2018 at 11.00 p.m.). In the initial model Venkatesh and his colleagues had posited that four UTAUT constructs (performance expectancy, effort expectancy, social influence and facilitating conditions) influence behavioral intention which in turn resulted in the adoption or use of a specific technology primarily in organizations. Demographic attributes such as age, gender, experience and voluntariness have been posited as moderators between UTAUT constructs and behavioral intention. In the year 2012, this model had been expanded by adding constructs such as hedonic motivation, price value and habit as antecedents to behavioral intention (Venkatesh, Thong, & Xu, 2012). Between 2003 and 2012 (use of the first UTAUT model) and after 2012 (the augmented model UTAUT2) most studies had applied the UTAUT model to test their technology acceptance or intent to use behavior of the consumers in varied applications (Venkatesh et al., 2012). This model has been primarily relevant in organizational contexts (e.g., Neufeld, Dong, & Higgins, 2007; Pai & Tu, 2011; Shibl, Lawley, & Debuse, 2013). Maruping, Bala, Venkatesh, and Brown (2017) integrated behavioral intention into the UTAUT arguing that in the organizational context, it was a better predictor than behavioral intention. Overtime, the application of UTAUT has been tested in multiple studies for consumer' acceptance and use of technology. Multiple studies have also tested the boundary conditions between UTAUT constructs and behavioral intention and the use of technology with age, gender, experience and voluntariness as moderators. Most research evidence that had been published show a mix of support for moderating hypotheses (e.g., King & He, 2006; Venkatesh et al., 2012). In India, to the best of our knowledge one study exists to test the UTAUT model, specifically in the context of e-governance technology acceptance and not in the context of Mobile internet use. The results of Gupta, Dasgupta, and Gupta (2008) study did not highlight significant contributions since they did not find a significant relationship between behavioral intention and use. They had documented 10.9 percent of the variance for behavioral intention. Correspondingly the moderating role of gender was found to be insignificant. Other studies in the literature have found larger variance for behavioral intention and use (e.g., Venkatesh et al., 2003; Venkatesh et al., 2012).

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