Abstract
PurposeThis study explains and predicts smartwatch adoption trends among non-users of smartwatches based on theories of the diffusion of innovation and inertia. It explores the impact of satisfaction with the status-quo with traditional wristwatches, on attitudes toward smartwatches and intentions to adopt the technology.Design/methodology/approachThe study used PLS-SEM to conduct a multi-group analysis considering high (HSQS) and low (LSQS) status-quo satisfaction groups. The multi-group analysis followed the MICOM procedure, and the software SmartPLS three was used to analyse the data.FindingsThe results suggest that attitudes of the LSQS group were more strongly impacted by perceived ease of use and trialability. Their attitude toward innovation also had a stronger effect on their adoption intention. For the HSQS group, social influence more strongly impacted adoption intention; this group also perceived the disruption associated with an innovation as greater than the LSQS group. Analysis using PLS-Predict indicated that both models have considerable predictive power.Originality/valueMost scholarship on this subject has taken a positive view of the diffusion and adoption of smartwatches. This study considers smartwatches from positive and inhibitory perspectives. In the context of smartwatches, this is the first scholarly attempt at comparing levels of resistance to innovation adoption to consumer satisfaction with the status quo.
Subject
Industrial and Manufacturing Engineering,Strategy and Management,Computer Science Applications,Industrial relations,Management Information Systems
Reference111 articles.
1. Factors influencing the adoption of smart wearable devices;International Journal of Human-Computer Interaction,2018
2. An assessment of the use of partial least squares structural equation modeling (PLS-SEM) in hospitality research;International Journal of Contemporary Hospitality Management,2018
3. Alves, C.A., Stefanini, C.J. and Silva, L.A.d. (2018), “The effect of high and low environmental consciousness regarding Brazilian restaurants: a multigroup Analysis using PLS”, in Ali, F., Rasoolimanesh, S.M. and Cobanoglu, C. (Eds), Applying Partial Least Squares in Tourism and Hospitality Research, Emerald Publishing, Bingley, pp. 185-209.
4. Estimating nonresponse bias in mail surveys;Journal of Marketing Research,1977
5. Canalys (2018), “Wearables market up 35% in Q1 2018 as Apple and Xiaomi maintain lead”, available at: https://www.canalys.com/newsroom/wearables-market-up-35-in-q1-2018-as-apple-and-xiaomi-maintain-lead, (accessed 20 April 2019).
Cited by
34 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献