Exploring the Plausibility of Pre-Purchase Decision Process in User Acceptance of Smart Wearable Technology Devices
DOI:
https://doi.org/10.17010/ijom/2022/v52/i4/169109Keywords:
Pre-Purchase Decision Process
, Need Recognition, Information Search, Evaluation of Alternatives, Smart Technology Wearables (SWT), Consumer Behavior, Purchase Intention.Paper Submission Date
, May 10, 2021, Paper Sent Back for Revision, July 8, Paper Acceptance Date, December 28, Paper Published Online, April 15, 2022.Abstract
The market for smart wearable technology products is growing rapidly. Although wearable technology is still in its early stages, a longer-term outlook is required. This study inspected the existence of consumers’ pre-purchase stage for smart wearable technology devices. It further analyzed the factors that influenced customers’ decisions in the pre-purchase phase. The methodology adopted was quantitative, using which 240 users of smart wearables were given a structured questionnaire to fill up. The Smart PLS 3.0 software was used for structural equation modeling and path analysis. The results indicated that customers go through a pre-purchase decision journey. Their decisions are influenced by individual characteristics, product description, information source utility, data usefulness, trust, visibility of the product, and demonstrability. Together, these factors resulted in the customers’ successful transition from the pre-purchase stage to the purchase decision stage.Downloads
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Amyx, S. (2014). Wearables gushing with emotions : A new brand-engagement architecture. In, IEEE Consumer Electronics Magazine, 4(1), 87–89. https://doi.org/10.1109/MCE.2014.2361162
Dehghani, M., Kim, K. J., & Dangelico, R. M. (2018). Will smart watches last ? Factors contributing to intention to keep using smart wearable technology. Telematics and Informatics, 35(2), 480–490. https://doi.org/10.1016/j.tele.2018.01.007
Dehghani, M. (2016, March). An assessment towards adoption and diffusion of smart wearable technologies by consumers: The cases of smart watch and fitness wristband products. HT (Extended Proceedings), 1– 6.
Dehghani, M. (2018). Exploring the motivational factors on continuous usage intention of smartwatches among actual users. Behaviour & Information Technology, 37(2), 145–158. https://doi.org/10.1080/0144929X.2018.1424246
Jung, Y., Kim, S., & Choi, B. (2016). Consumer valuation of the wearables : The case of smart watches. Computers in Human Behavior, 63, 899–905. https://doi.org/10.1016/j.chb.2016.06.040
Kalantari, M. (2017). Consumers' adoption of wearable technologies : Literature review, synthesis, and future research agenda. International Journal of Technology Marketing, 12(3), 274–307. https://dx.doi.org/10.1504/IJTMKT.2017.089665
Kesharwani, A., & Roy, S. (2017). Diffusion of mobile health apps among smartphone users: Role of neighbourhood effects, informational network effects, and social ties in health 3.0. Indian Journal of Marketing, 47(4), 19–34. https://doi.org/10.17010/ijom/2017/v47/i4/112679
Kim, K. J., & Shin, D. - H. (2015). An acceptance model for smart watches : Implications for the adoption of future wearable technology. Internet Research, 25(4), 527–541. https://dx.doi.org/10.1007/978-3-030-50252-2_23
Lazar, A., Koehler, C., Tanenbaum, T. J., & Nguyen, D. H. (2015). Why we use and abandon smart devices. In, UbiComp '15: Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing (pp. 635–646). ACM. https://doi.org/10.1145/2750858.2804288
Lee, C., & Coughlin, J. F. (2015). PERSPECTIVE: Older adults' adoption of technology: An integrated approach to identifying determinants and barriers. Journal of Product Innovation Management, 32(5), 747–759. https://doi.org/10.1111/jpim.12176
Mani, Z., & Chouk, I. (2017). Drivers of consumers' resistance to smart products. Journal of Marketing Management, 33(1–2), 76–97. https://dx.doi.org/10.1080/0267257X.2016.1245212
Motti, V. G., & Caine, K. (2016, September). Smart wearables or dumb wearables? : Understanding how context impacts the UX in wrist worn interaction. In, SIGDOC '16: Proceedings of the 34th ACM International Conference on the Design of Communication (pp. 1–10). ACM. https://doi.org/10.1145/2987592.2987606
Ozer, L., & Gultekin, B. (2015). Pre-and post-purchase stage in impulse buying: The role of mood and satisfaction. Journal of Retailing and Consumer Services, 22, 71–76. https://doi.org/10.1016/j.jretconser.2014.10.004
Pfeiffer, J., von Entress - Fuersteneck, M., Urbach, N., & Buchwald, A. (2016). Quantify-me: Consumer acceptance of wearable self-tracking devices (Research Papers 99). https://aisel.aisnet.org/ecis2016_rp/99
Rashel, A., Ahmed, F., & Lee, S. (2017). Consumer buying behaviour in high-tech product markets: An empirical study on analog wrist watches from the Bangladeshi perspective. Indian Journal of Marketing, 47(10), 42–63. https://doi.org/10.17010/ijom/2017/v47/i10/118696
Rauschnabel, P. A., & Ro, Y. K. (2016). Augmented reality smart glasses: An investigation of technology acceptance drivers. International Journal of Technology Marketing, 11(2), 123–148. https://doi.org/10.1504/IJTMKT.2016.075690
Rawassizadeh, R., Price, B. A., & Petre, M. (2014). Wearables: Has the age of smart watches finally arrived? Communications of the ACM, 58(1), 45–47. https://doi.org/10.1145/2629633
Talukder, M. S., Chiong, R., Bao, Y., & Hayat Malik, B. (2019). Acceptance and use predictors of fitness wearable technology and intention to recommend: An empirical study. Industrial Management & Data Systems, 119(1), 170 – 188. https://doi.org/10.1108/IMDS-01-2018-0009
Wu, L. - H., Wu, L. - C., & Chang, S. - C. (2016). Exploring consumers' intention to accept smartwatch. Computers in Human Behavior, 64, 383–392. https://dx.doi.org/10.1016%2Fj.chb.2016.07.005
Zhang, N., Guo, X., & Chen, G. (2008). IDT-TAM integrated model for IT adoption. Tsinghua Science and Technology, 13(3), 306 – 311. https://doi.org/10.1016/S1007-0214(08)70049-X
