January 29, 2019 0 Comment

3.3.1 Performance Expectancy: is defined “as the degree to which using a technology will provide benefits to consumers in performing certain activities” (Venkatesh et al., 2012, P.159). According to Jewer (2018) Kim et al. (2016); Hoque (2017); Houque &Sower (2015); Ndayizigamiye & Maharaj (2016) PE is the most influencing factor that affect the actual using of M-health. The customers adoption is depend on how such method_M-health_ might be effective in preventing illness threads by easing medical appointment and decreasing time and effort in the diagnosis process. It is important for the customers to feel the change after using the M-health; achieving customers goal of adopting the apps and obtain what M-health promising to improve (Sun et al.,2013; Alalwan et al.,2017; Jewer, 2018). therefore we proposed:

H1. Performance expectancy will positively influence Jordanian customers’ intention to adopt Mobile Health Applications

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3.3.2 Effort Expectancy: is “the degree of ease associated with consumers’ use of technology” (Venkatesh et al., 2012, P.159). EE has a high effect on M-health adoption (Kim et al., 2016; Hoque, 2017; Hoque ;Sorwar, 2015; Ndayizigamiye ; Maharaj, 2016). The use of training programs and technical support will efficiently effect potential customer’s capabilities and their perceptions and also increase their perceptions of M-health (Wu et al., 2007). EE is highly influential within UTAUT2 model as age is taken into account. The elderly do not like using technology because they think it is difficult to handle; If there is an expectation that M-health applications will be easy to learn and apply there will be a greater chance to be adopted especially by elderly (Hoque,2017). Therefore we proposed:


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