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Mobile app use has increased significantly (Chen, Meserv & Gillenson, 2012) since the introduction of the Wireless Application Protocol (WAP) in Europe and iMode in Japan at the end of the 20th century, and the release of the BlackBerry smartphone in the US in 2002. These apps allow users to trade stocks, obtain paperless store coupons, receive reminders for to do lists, and use GPS to find arrival and departure times for public transportation (Chen et al., 2012).
Information-Oriented Mobile Applications (IOMA) are programs offering users timely, personalized, and/or localized information on mobile devices (Chen et al., 2012). Consumer adoption of these mobile apps is forecast to grow significantly as mobile providers open their platforms to third-party applications (Malhotra & Segars, 2005; Chen et al., 2012). IOMAs require a smartphone connected to mobile Internet or local area wireless (Wi-Fi).
There is a large body of research on innovation acceptance patterns (Davis, 1989; Davis, Baggozi & Warshaw, 1989; Venkatesh & Morris, 2000; Venkatesh et al., 2003), though there is little knowledge of how consumers adopt technology-based self-services (TBSSs) (Reinders, Dabholkar & Frambach, 2008; Claudy, Garcia & O’Driscoll, 2015). Reinders, Dabholkar and Frambach (2008) show that offering interaction with an employee as a fall back option offsets the negative consequences of forced use of a TBSS. Claudy, Garcia, and O’Driscoll (2015) confirm that reasons for and against adoption are not just opposites of each other but they are qualitatively distinct constructs which influence consumers’ adoption decisions in different ways. The marketing field investigates the factors behind consumer intentions to use TBSSs. These services and factors are likely to grow as technology advances (Taylor & Strutton, 2010; Shuster, Drennan & Lings, 2013), especially since the traditional attitudinal models (Dabholkar & Bagozzi, 2002; Curan & Meuter, 2005) fail to recognize that most high-involvement behaviors, such as using a credence service, are means to achieve goals (Schuster et al., 2013).
Credence services are professional services requiring specialized knowledge to produce and are difficult for consumers to evaluate, even after trial (Ostrom & Iacobucci, 1995; Schuster et al., 2013). These models also fail to account for the impact of pre-factual appraisals of outcomes, which are less concrete in credence services (Ostrom & Iacobucci, 1995; Schuster et al., 2013). This study addresses these gaps using a model inspired by the model of goal-directed behavior (MGB) (Perugini & Bagozzi, 2001), to overcome these shortcomings (Schuster et al., 2013), and the technology acceptance model (TAM) (Davis, 1989), to examine consumer acceptance of a particular TBSS – a coaching app to help students succeed in their studies.