PMID- 31487812 OWN - NLM STAT- MEDLINE DCOM- 20200131 LR - 20200309 IS - 1660-4601 (Electronic) IS - 1661-7827 (Print) IS - 1660-4601 (Linking) VI - 16 IP - 18 DP - 2019 Sep 4 TI - An Exploration and Confirmation of the Factors Influencing Adoption of IoT-Based Wearable Fitness Trackers. LID - 10.3390/ijerph16183227 [doi] LID - 3227 AB - In recent years, IoT (Internet of Things)-based smart devices have penetrated a wide range of markets, including connected health, smart home, and wearable devices. Among the IoT-based smart devices, wearable fitness trackers are the most widely diffused and adopted IoT based devices. Such devices can monitor or track the physical activity of the person wearing them. Although society has benefitted from the conveniences provided by IoT-based wearable fitness trackers, few studies have explored the factors influencing the adoption of such technology. Furthermore, one of the most prevalent issues nowadays is the large attrition rate of consumers no longer wearing their device. Consequently, this article aims to define an analytic framework that can be used to explore the factors that influence the adoption of IoT-based wearable fitness trackers. In this article, the constructs for evaluating these factors will be explored by reviewing extant studies and theories. Then, these constructs are further evaluated based on experts' consensus using the modified Delphi method. Based on the opinions of experts, the analytic framework for deriving an influence relationship map (IRM) is derived using the decision-making trial and evaluation laboratory (DEMATEL). Finally, based on the IRM, the behaviors adopted by mass customers toward IoT-based wearable fitness trackers are confirmed using the partial least squares (PLS) structural equation model (SEM) approach. The proposed analytic framework that integrates the DEMATEL and PLS-SEM was verified as being a feasible research area by empirical validation that was based on opinions provided by both Taiwanese experts and mass customers. The proposed analytic method can be used in future studies of technology marketing and consumer behaviors. FAU - Kao, Yu-Sheng AU - Kao YS AD - Department of Technology Management for Innovation, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan. sunkao1035@gmail.com. FAU - Nawata, Kazumitsu AU - Nawata K AD - Department of Technology Management for Innovation, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan. nawata@tmi.t.u-tokyo.ac.jp. FAU - Huang, Chi-Yo AU - Huang CY AD - Department of Industrial Education, National Taiwan Normal University, Taipei 106, Taiwan. georgeh168@gmail.com. LA - eng PT - Journal Article PT - Research Support, Non-U.S. Gov't DEP - 20190904 PL - Switzerland TA - Int J Environ Res Public Health JT - International journal of environmental research and public health JID - 101238455 SB - IM MH - Adult MH - *Consumer Behavior MH - *Decision Making MH - Female MH - Fitness Trackers/*statistics & numerical data MH - Humans MH - Internet of Things/*statistics & numerical data MH - Male MH - Middle Aged MH - Models, Theoretical MH - Monitoring, Physiologic/*psychology MH - Young Adult PMC - PMC6765920 OTO - NOTNLM OT - decision making trial and evaluation laboratory (DEMATEL) OT - internet of things (IoT) OT - modified delphi method OT - partial least squares (PLS) OT - technology adoption OT - wearable fitness trackers COIS- The authors declare no conflict of interest. EDAT- 2019/09/07 06:00 MHDA- 2020/02/01 06:00 PMCR- 2019/09/01 CRDT- 2019/09/07 06:00 PHST- 2019/07/24 00:00 [received] PHST- 2019/08/27 00:00 [revised] PHST- 2019/09/02 00:00 [accepted] PHST- 2019/09/07 06:00 [entrez] PHST- 2019/09/07 06:00 [pubmed] PHST- 2020/02/01 06:00 [medline] PHST- 2019/09/01 00:00 [pmc-release] AID - ijerph16183227 [pii] AID - ijerph-16-03227 [pii] AID - 10.3390/ijerph16183227 [doi] PST - epublish SO - Int J Environ Res Public Health. 2019 Sep 4;16(18):3227. doi: 10.3390/ijerph16183227.