The Moderating Effect of Motivation to Comply and Perceived Critical Mass in Smartphones' Adoption

The Moderating Effect of Motivation to Comply and Perceived Critical Mass in Smartphones' Adoption

Abdou Illia (Eastern Illinois University, USA), Assion Lawson-Body (University of North Dakota, USA), Simon Lee (Eastern Illinois University, USA) and Gurkan I. Akalin (Eastern Illinois University, USA)
Copyright: © 2018 |Pages: 18
DOI: 10.4018/IJTHI.2018070102
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The testing of the technology acceptance model over the years has shown that its explanatory power is about 50%; which led researchers to revisit the model in an attempt to gain a better understanding of technology adoption. Some of the studies found social influence to be a key factor, but others have yielded mixed results. This article questions the assumption made in some previous studies that most people would comply with social influence. Using data collected from 210 smartphone users, we investigated the moderating effect of motivation to comply on the relationship between social influence, on the one hand, and perceived usefulness and perceived ease-of-use on the other hand. Also, based on the theory of critical mass, we investigated the moderating effect of the perceived critical mass on the relationship between perceived usefulness and perceived ease of use on the one hand, and actual usage on the other hand. The results showed a significant moderating effect of both motivation to comply and perceived critical mass. Theoretical and practical implications are discussed.
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1. Introduction

Grounded on the theory of reasoned action or TRA (Fishbein & Ajzen, 1975), the technology acceptance model (TAM) is an implementation of the belief-attitude-intention-behavior relationship. According to the TAM, the actual use of a technology is determined by beliefs a user holds about its perceived usefulness and its perceived ease of use. Perceived usefulness refers to the extent to which people believe that a technology will help them perform their job better, while perceived ease of use refers to the degree to which a person believes that using a particular IT would be free of effort (Davis, 1989). In the early 1990s, empirical testing of the TAM indicated that the constructs in the model explain about 40% of technology usage at best (Adams, Nelson, & Todd, 1992; Davis, 1993; Mathieson, 1991). As a result, researchers carried out more studies in order to gain a better understanding of IT adoption and use by individuals and organizations. More specifically, researchers began revisiting the TRA from which the TAM emerged. According to the TRA, people’s beliefs about the perceived usefulness and the perceived ease of use of a tool are, in part, determined by social influence (SI).

In recent years, several studies have investigated the extent to which various forms of social influence can impact people’s intention to use technology (Burton-Jones & Hubona, 2006; Homburg, Wieseke, & Kuehnl, 2010; Malhotra & Galleta, 1999; Schmitz & Fulk, 1991; Shin, 2009; Sivo, Pan, & Hahs-Vaughn, 2007; Teo, 2010) with some mixed results. One of the limitations of most of the studies is that they didn’t explicitly take people’s motivation to comply into account and assumed that people would comply with social norms. But, it is a well-known fact in social psychology that people differ in terms of the extent to which they conform to social norms (Griskevicius, Goldstein, Mortensen, Cialdini, & Kenrick, 2006). According to Ajzen (1991), motivation to comply plays a key role in the cognitive process that leads to actual behavior. Venkatesh et al. (2003) noticed that in the IS literature a variety of constructs including social factors, image, normative beliefs, and subjective norms are used to represent social influence. Their study summarized the item scales used to operationalize each of SI related concepts. But none of the scales captures motivation to comply, that is, the extent to which people are willing to comply with social influence.

From the theoretical viewpoint, it is important to investigate the direct effect of social influence as most studies in the IS field have done. But it is also important to investigate the possible mediating or moderating effect of motivation to comply in the relationship between social influence on the one hand, and people’s attitude or behavior on the other hand. The study of Walster (1989) about normative influences analyzed the TRA and suggested that to get a full measure of the impact of social influence, one should account for motivation to comply. The study recommended assessing the moderating effect of motivation to comply on the impact of SI. Therefore, our first research question is:

  • RQ1: To what extent does motivation to comply moderates the impact of social influence in the context of technology use?

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