RESUMO
Persuasive strategies are used to influence the behavior or attitude of people without coercion and are commonly used in online systems such as e-commerce systems. However, in order to make persuasive strategies more effective, research suggests that they should be tailored to groups of similar individuals. Research in the traits that are effective in tailoring or personalizing persuasive strategies is an ongoing research area. In the present study, we propose the use of shoppers' online shopping motivation in tailoring six commonly used influence strategies: scarcity, authority, consensus, liking, reciprocity, and commitment. We aim to identify how these influence strategies can be tailored or personalized to e-commerce shoppers based on the online consumers' motivation when shopping. To achieve this, a research model was developed using Partial Least Squares-Structural Equation Modeling (PLS-SEM) and tested by conducting a study of 226 online shoppers. The result of our structural model suggests that persuasive strategies can influence e-commerce shoppers in various ways depending on the shopping motivation of the shopper. Balanced buyers-the shoppers who typically plan their shopping ahead and are influenced by the desire to search for information online-have the strongest influence on commitment strategy and have insignificant effects on the other strategies. Convenience shoppers-those motivated to shop online because of convenience-have the strongest influence on scarcity, while store-oriented shoppers-those who are motivated by the need for social interaction and immediate possession of goods-have the strongest influence on consensus. Variety seekers-consumers who are motivated to shop online because of the opportunity to search through a variety of products and brands, on the other hand, have the strongest influence on authority.
RESUMO
Research has shown that persuasive technologies aimed at behavior change will be more effective if behavioral determinants are targeted. However, research on the determinants of bodyweight exercise performance in the context of behavior modeling in fitness apps is scarce. To bridge this gap, we conducted an empirical study among 659 participants resident in North America using social cognitive theory as a framework to uncover the determinants of the performance of bodyweight exercise behavior. To contextualize our study, we modeled, in a hypothetical context, two popular bodyweight exercise behaviors - push ups and squats - featured in most fitness apps on the market using a virtual coach (aka behavior model). Our social cognitive model shows that users' perceived self-efficacy (ßT = 0.23, p < 0.001) and perceived social support (ßT = 0.23, p < 0.001) are the strongest determinants of bodyweight exercise behavior, followed by outcome expectation (ßT = 0.11, p < 0.05). However, users' perceived self-regulation (ßT = -0.07, p = n.s.) turns out to be a non-determinant of bodyweight exercise behavior. Comparatively, our model shows that perceived self-efficacy has a stronger direct effect on exercise behavior for men (ß = 0.31, p < 0.001) than for women (ß = 0.10, p = n.s.). In contrast, perceived social support has a stronger direct effect on exercise behavior for women (ß = 0.15, p < 0.05) than for men (ß = -0.01, p = n.s.). Based on these findings and qualitative analysis of participants' comments, we provide a set of guidelines for the design of persuasive technologies for promoting regular exercise behavior.