Global Journal of Management and Business Research, E: Marketing, Volume 23 Issue 1

Understanding the Age Differences in Adopting WFTs: An Extension of the UTAUT2 Model 15 Global Journal of Management and Business Research Volume XXIII Issue I Version I Year 2023 ( )E © 2023 Global Journals 29. Dwivedi, Y. K., Shareef, M. A., Simintiras, A. C., Lal, B. and Weerakkody, V. (2016), “A generalized adoption model for services: a cross-country comparison of mobile health (m-health)”, Government Information Quarterly, Vol. 33 No. 1, pp. 174-187. https://doi.org/10.1016/j.giq.20 15.06. 003 30. Ehmen, H., Haesner, M., Steinke, I., Dorn, M., Gövercin, M., & Steinhagen-Thiessen, E. (2012). Comparison of four different mobile devices for measuring heart rate and ECG with respect to aspects of usability and acceptance by older people. Applied Ergonomics, 43 (3), 582–587. doi:10.1016/j.apergo.2011.09.003 31. Epstein, D. A., Jacobson, B. H., Bales, E., McDonald, D. W., & Munson, S. A. (2015). From “nobody cares” to “way to go!” Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing. doi:10.11 45/2675133.2675135. 32. Ericsson. (2018). Wearable Technology and the IoT. Retrieved from www.ericsson.com/en/trends ‐ and ‐ insights/consumerlab/consumer ‐ insights/reports/we arable ‐ technology ‐ and ‐ the ‐ internet ‐ of ‐ things. 33. Falk, R. F., Miller, N. B., 1992. A Primer for Soft Modeling. Akron, OH. US: University of Akron Press. 34. Fornell, C., & Larcker, D. F., 1981. Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. 35. Gao, T., Rohm, A. J., Sultan, F. and Huang, S. (2012), “Antecedents of consumer attitudes toward mobile marketing: a comparative study of youth markets in the United States and China”, Thunderbird International Business Review, Vol. 54 No. 2, pp. 211-224. 36. Gao, Y., Li, H., & Luo, Y. (2015). An empirical study of wearable technology acceptance in healthcare. Industrial Management & Data Systems, 115 (9), 1704–1723. 37. Girard, C. (1993). Age, gender, and suicide: A cross-national analysis. American Sociological Review, 58 (4), 553-574. 38. Goulão, A. P. B. A. (2014). E-Health individual adoption-empirical model based on UTAUT2 (Doctoral dissertation). Retrieved from: https://run. unl.pt/bitstream/10362/13760/1/TGI0019.pdf. 39. Hair, J., Hult, G. T. M., Ringle, C., Sarstedt, M., 2016. A Primer on Partial Least Squares Structural Equation Modeling (Pls-Sem). Sage Publications, London: Thousand Oaks. 40. Hein, D. W. and Rauschnabel, P. A. (2016) ‘Augmented reality smart glasses and knowledge management: a conceptual framework for enterprise social networks’, Enterprise Social Networks, pp. 83–109, Springer, Fachmedien Wiesbaden. 41. HelpAge International, 2015. Policy Mapping on Ageing in Asia and the Pacific Analytical Report, Chiang Mai: HelpAge International East Asia/Pacific Regional Office. 42. Henseler, J., Ringle, C. M., Sinkovics, R. R., 2009. The use of partial least squares path modeling in international marketing. Adv. Int. Market. (20:1), 277–319. 43. Hill, J. O., Wyatt, H. R. Role of physical activity in preventing and treating obesity. J Appl Physiol 2005; 99: 765-70. 44. Horovitz, B. AfterGen X, Millennials, what should next generation be?. USA Today, 2012. 45. Huang, C. Y., & Yang, M. C. (2020). Empirical investigation of factors influencing consumer intention to use an artificial intelligence-powered mobile application for weight loss and health management. Telemedicine and e-Health, 26 (10), 1240-1251. 46. Islam, Z., Kim Cheng Low, P., Hasan, I. Intention to use advanced mobile phone services (AMPS), Manag. Decis. 51 (2013) 824–838. 47. 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. 48. Kock, N., 2015. Common method bias in PLS-SEM: a full collinearity assessment approach. Int. J. e- Collaboration (11: 4), 1–10. 49. Kraft, F. B. and Goodell, P. W., “Identifying the health conscious consumer,” Journal of Health Care Marketing, vol. 13, no. 3, pp. 18–25, 1993. 50. Kranthi, A. K., & Ahmed, K. A. A. (2018). Determinants of smartwatch adoption among IT professionals—An extended UTAUT2 model for smartwatch enterprise. International Journal of Enterprise Network Management, 9 (3/4), 294. 51. Kruk, J., “Physical activity and health,” Asian Pac J Cancer Prev, vol. 10, no. 5, pp. 721-728, 2009. 52. Ledger, D., & McCaffrey, D. (2014). Inside wearables: How the science of human behaviour change. Endeavour Partners. http://endeavour- partners.net/assets/Endeavour ‐ Partners ‐ Wearables ‐ White ‐ Paper ‐ 20141.pdf 53. Lee, H. H., Fiore, A. M., & Kim, J. (2006). The role of the technology acceptance model in explaining effects of image interactivity technology on consumer responses. International Journal of Retail & Distribution Management, 34 (8), 621-644. 54. Lee, S. Y. and Lee, K. “Factors that influence an individual’s intention to adopt a wearable healthcare device: the case of a wearable fitness tracker,” Technological Forecasting and Social Change, vol. 129, pp. 154–163, 2017.

RkJQdWJsaXNoZXIy NTg4NDg=