Critical Factors Influencing the Intention to Adopt m-Government Services by the Elderly

Critical Factors Influencing the Intention to Adopt m-Government Services by the Elderly

Md. Shamim Talukder (Huazhong University of Science and Technology, Wuhan, China), Raymond Chiong (The University of Newcastle, Callaghan, Australia & Fuzhou University, Fuzhou, China), Brian Corbitt (RMIT University, Melbourne, Australia) and Yukun Bao (Huazhong University of Science and Technology, Wuhan, China)
Copyright: © 2020 |Pages: 21
DOI: 10.4018/JGIM.2020100105
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While the elderly population is growing rapidly, acceptance and use of m-government services by them are far below expectation. Previous studies on acceptance and use of m-government services have predominantly focused on younger citizens with skills and experience of information technologies. Drawing upon the dual factor model, this study investigates the enablers and inhibitors of the elderly's m-government service adoption behavior. Four constructs from the unified theory of acceptance and use of technology (UTAUT), namely, performance expectancy, effort expectancy, facilitating conditions, social influence; and self-actualization are treated as enablers, while user resistance to change, technology anxiety, and declining physiological conditions are regarded as inhibitors. Results show that adoption of m-government by the elderly is significantly influenced by all tested enablers and inhibitors, except for social influence. This study contributes by providing an integrative model of technology acceptance for the elderly along with practical implications for policy makers.
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1. Introduction

Population aging has become a major concern for governments worldwide. At present, approximately 11% of the world’s population is aged 60 years and over, but this proportion is projected to increase to about 16.5% by 2030 (UN-DESA, 2017). Due to diminishing sensory input, cognitive dysfunction, disability, and impaired physiologic reserve, elderly people need personalized services and support from their government regarding healthcare, emergency contact, or power of attorney (Turner et al., 2018). Accordingly, the provision of efficient and effective delivery of these fundamental services to the elderly has become increasingly critical. The phenomenon of population aging is not limited to developed countries. Low- and middle- income countries are estimated to be more likely to bear much of this growth. Bangladesh, for example, has more than 13 million of its population over 60 years of age (Bangladesh Bureau of Statistics, 2017).

Mobile government (m-Government) services can provide better access for the elderly. m-government expands service delivery, improves levels of information sharing, provides precision and personalization in targeting users (such as the elderly), helps deliver content with greater cost optimization, and promotes stronger digital equality (Ahmad & Khalid, 2017; Hung, Chang, & Kuo, 2013). m-Government can also considerably improve support for the elderly, as physical presence or waiting at government institutions is no longer necessary, while active participation in politics and in other decision-making processes become more accessible (Choudrie, Alfalah, & Spencer, 2017). However, there are issues regarding the acceptance and adoption of m-Government services by the elderly. It is widely accepted that elderly people are relatively less skillful at using mobile technologies, and also have less experience in using them (Deng, Mo, & Liu, 2014). They also do not show as much enthusiasm for adopting new technologies as the younger generation do, due to age-related vulnerability (Bao, Hoque, & Wang, 2017).

To understand the issues related to m-Government service adoption, we need to consider not only the benefits brought by the services but also barriers inhibiting the adoption behavior. Past studies along this line of research have focused predominantly on m-Government adoption related to technical and non-technical barriers (Al-Hadidi & Rezgui, 2010), organizational culture (Hussain & Imran, 2015), roles of social networks (Tscherning & Mathiassen, 2010), service quality perspectives (Al-Hubaishi et al., 2017), and trust, security or privacy issues (Liu et al., 2014; Susanto & Goodwin, 2011; Wang, 2014). It is worth pointing out that researchers have paid more attention to the benefits of m-Government services than on the barriers (Ahmad & Khalid, 2017; Talukder, Shen, Hossain Talukder, & Bao, 2019). In addition, existing studies have primarily targeted the younger generation, such as middle-aged professionals or students who are relatively healthier, more sociable and active (Abdelghaffar & Magdy, 2012; Liu et al., 2014).

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