What makes you feel attached to smartwatches? The stimulus-organism-response (S-O-R) perspectives

Purpose The purpose of this paper is to answer the question of whether smartwatches will survive and gain their own niche within the consumer electronics market. Based on the stimulus-organism-response (S-O-R) framework, this study identifies and validates the impacts of both technological and fashion-related factors (interactivity, autonomy, visual aesthetics and self-expression) on product attachment towards smartwatches through user satisfaction and pleasure derived from their smartwatches. Design/methodology/approach The authors collected the survey data via online surveys from 198 respondents and tested measurement and structural models with the partial least square technique. Findings The authors found that both technological characteristics (interactivity and autonomy) and fashion-related characteristics (visual aesthetics and self-expression) have an impact on product attachment through pleasure. Research limitations/ implications - Several other important characteristics of traditional wrist- watches such as durability or workmanship are not considered in this study, but should be included in future studies. The three- item measure of autonomy may be insufficient for more sophisticated wearable devices in the future. In future studies, the impact of product attachment on users' continued usage should be examined. Practical implications - This study provides important practical implications for smartwatch makers interested in product development, as users were found to consider fashion- related characteristics to be as important as technological characteristics. Originality/ value - This study is the first study that considers both aesthetic and technological factors for IT acceptance in the context of wearable devices. Also, instead of traditional IT acceptance measures such as continued use, this study investigates users' product attachment, which is more relevant to the case of wearable devices. Keywords Behaviour change, Structural equation modelling, Empirical study, Partial least squares, Human computer interaction ( HCI), User satisfaction, IT- enabled social innovations, Hypothesis testing, Disruptive technologies