Consumer Differences in the United States and India on Wearable Trackers
Bibliographic Data
| ID | 6061988 |
|---|---|
| Authors | Sumin Helen Koo (0000-0002-0333-0190, Konkuk University, corresponding author) |
| Year | 2017 |
| Volume | 46 |
| Issue | 1 |
| Pages | 40-56 |
| Publication date | 2017-09-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Family and Consumer Sciences Research Journal (JOURNAL) |
| Journal identifiers | ISSN: 1077-727X • E-ISSN: 1552-3934 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/fcsr.12230 |
| OpenAlex | W2754913783 |
| Language | EN |
| Citations received | 3 |
| References cited | 28 |
The purpose of this research was to compare consumers in the United States and India with different demographic backgrounds and to investigate their preferences, perceptions, attitudes, and behavioral intentions toward wearable trackers. An online survey was conducted and a series of independent t‐tests, Welch's analysis of variance, and Duncan's post hoc test were performed to investigate differences among groups. Simple and multiple linear regression analyses were performed to investigate relationships among variables. The results demonstrated that there were significant differences in country of residence, gender, marital status, and age. Also, there were significant relationships among tracking attributes preferences, perceived usefulness and ease of use, attitudes on using, and the behavioral intention to use wearable trackers. These results can benefit developers and marketers of wearable trackers by increasing their knowledge of the differences among targeted consumer groups. The outcome could be to increase adoption of wearable trackers in the United States and India
Activity tracker · Advertising · BitTorrent tracker · Business · Machine learning · Marital status · Perception · Regression analysis · Residence · Sociology · Wearable computer · Wearable technology · Applied Psychology · Computer Science · Consumer Retail Behavior Studies · Demography · Digital Marketing and Social Media · Psychology · Social Psychology · Technology Adoption and User Behaviour · Artificial Intelligence
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| Citations per year | 0.6 |
|---|---|
| Citation span | 2021 - 2024 (4) |
| Highly cited | No |