Driving healthcare wearable technology adoption for Generation Z consumers in Hong Kong

Man Lai Cheung, Wilson K.S. Leung, Haksin Chan

Research output: Contribution to journalArticlepeer-review

24 Citations (Scopus)


Purpose: Young consumers have increasingly adopted wearable health-care technology to improve their well-being. Drawing on generation cohort theory (GCT) and the technology acceptance model (TAM), this study aims to illuminate the major factors that drive the adoption of health-care wearable technology products by Generation Z (Gen-Z) consumers in Hong Kong. Design/methodology/approach: A self-administrated online survey was used to collect data from a sample of Gen-Z consumers in Hong Kong with experience in using health-care wearable technology. Data analysis was performed using partial least-squares-structural equation modeling to verify four hypotheses. Findings: The results reveal that consumer innovativeness (CI) and electronic word-of-mouth referral (EWOM) are significant predictors of perceived credibility, perceived ease of use and perceived usefulness, which subsequently drive online engagement intention and adoption intention (AI). Practical implications: This research provides practical guidance for marketers of health-care wearable technology products. In particular, CI and EWOM hold the key to young consumers’ product perceptions (and thereby their online engagement and AIs). Originality/value: This research leverages the insights of GCT to enrich the TAM, specifically by including CI and EWOM as antecedents and online engagement as a consequence in the context of health-care wearable technology. The results of an empirical study enhance theoretical understanding of Gen-Z consumers’ perceptions and behavioral intentions toward health-care wearable technology. They also point to actionable recommendations for marketing this new technology to young consumers.

Original languageEnglish
Pages (from-to)10-27
Number of pages18
JournalYoung Consumers
Issue number1
Publication statusPublished - 2020


  • Adoption intention
  • Generation cohort theory
  • Generation Z
  • Health-care wearable technology
  • Technology acceptance model


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