Article Preview
TopIntroduction
Understanding why individuals continue to use a particular technology or not has attracted great interest in the industry. Retaining customers is relevant because it affects profitability. Acquiring new clients can be more expensive than retaining existing ones due to the costs of finding new customers, establishing new relationships, and training new users. Moreover, consumers who bought technology and abandoned it after months of use may be reluctant to rebuy it (Bölen, 2020; Gallo, 2014). Because of this practical relevance, the continuance of usage has emerged as a prominent area of research in recent years (Bhattacherjee & Lin, 2014).
Previous research on discontinuance has focused on finding different predictors to explain this phenomenon. Recent literature reviews reveal several theoretical lenses to explain this behavior, and these reviews also show a confluence of factors as the main predictors (e.g., usefulness, hedonic value, attitude, satisfaction, commitment) (Franque et al., 2020; Shaikh & Karjaluoto, 2015). Another view of prior research suggests two theoretical approaches to explain this phenomenon. The cognitive models (e.g., Theory of Reasoned Action or Theory of Planned Behavior) rely on perception, reasoning, and judgment (i.e., what a person thinks) to explain continuance. In this case, the logic would be that if the individuals perceive that they will benefit by performing a particular behavior, they will be more motivated to perform such conduct (Ajzen, 2005). On the other hand, the cognitive-affective models (Bhattacherjee, 2001; Kim et al., 2007) recognize that continuance decisions also have an affective component (i.e., how a person feels about it). In this case, when individuals employ an affective-based mechanism, they try to choose the behavior that offers a superior hedonic state (Kim et al., 2007; Osatuyi & Qin, 2018).
Advances in the field have provided an understanding of the main drivers of the phenomenon of interest. However, a question remains: Why do some individuals base their decisions more on rational factors than affective ones while others rely more on their feelings than their reasoning? (Hong et al., 2011; Trafimow et al., 2004).
Grounded in dual processing theories, some authors have shed some light on the cognitive mechanisms of the decision-making process to answer the previous question. In general, dual processing theories from the cognitive psychology field, particularly Cognitive Experiential Theory (CET) (Epstein, 2014), postulate that decision-making can be described as a function of an experiential type of information processing or Type 1 (fast, effortless, and affective) and another one rational or Type 2 (slow, effortful and logical). In the information systems (IS) arena, Gwebu et al. (2014) mention that while no explicit links had been established between dual processing theories and continuance research, they postulate that existing models implicitly represent experiential and rational processing types. The cognitive models center on reasoning and analysis and generally view continuance decisions as involving slower, effortful, and deliberate evaluation (Type 2 information processing). Thus, rational processing could underlie cognitive factors (e.g., perceived usefulness, cognitive attitude). Conversely, affective models recognize that these decisions are probably handled emotionally and more quickly (Type 1 information processing). So experiential processing could be behind affective factors (e.g., satisfaction).