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Top1. 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).