Research Article
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Year 2018, Volume: 10 Issue: 2, 83 - 98, 31.12.2018

Abstract

References

  • Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179-211.
  • Beckham, J. (2012). Fitness trackers use psychology to motivate couch potatoes. https://www.wired.com/2012/04/fitness-tracker-psychology/ Accessed 2016/11/10.
  • Bevan-Dye, A.L. (2013). Black Generation Y students’ attitudes towards Web advertising value. Mediterranean Journal of Social Sciences, 4(2), 155-164.
  • Bevan-Dye, A.L. & Surujlal, J. (2011). Attitudes towards materialism in sport and materialism tendencies amongst Black Generation Y students. African Journal for Physical, Health Education, Recreation and Dance, 1(1), 43-55.
  • Blut, M., Wang, C. & Schoefer, K. (2016). Factors Influencing the Acceptance of Self-Service Technologies: A Meta-Analysis. Journal of Service Research, 19(4), 396-416.
  • Choi, J. & Kim, S. (2016). Is the smartwatch an IT product or a fashion product? A study on factors affecting the intention to use smartwatches. Computers in Human Behavior, 63, 777-786.
  • Chae, J.-M. (2009). Consumer acceptance model of smart clothing according to innovation. International Journal of Human Ecology, 10:23-33.
  • Dean, G. (2010). Understanding consumer attitudes. https://marketography.com/2010/10/17/understanding-consumer-attitudes/ Accessed 2018/06/18.
  • Del Río, A.B., Vázquez, R., Iglesias, V. (2001). The role of the brand name in obtaining differential advantages. Journal of Product and Brand Management, 10(7), 452–465
  • Field, A. (2009). Discovering statistics using SPSS. 3rd ed. London: Sage.
  • Hair, J.F., Black, W.C., Babin, B.J. & Anderson, R.E. (2010). Multivariate data analysis: a global perspective. 7th ed. Upper Saddle River, NJ: Pearson PrenticeHall.
  • Hamari, J. & Koivisto, J. (2015). ‘‘Working out for likes’’: An empirical study on social influence in exercise gamification. Computers in Human behavior, 50, 333- 347.
  • Haslam, C. (2016). Counting sleep: the best sleep tracker and monitors. https://www.wareable.com/withings/best-sleep-trackers-and-monitors Accessed 2016/11/06.
  • Hong, S-K. (2015). An explorative study of the features of activity trackers as IoT based wearable devices. Journal of Internet Computing and Services, 16(5), 93- 98.
  • International Data Corporation. (2017). Worldwide Wearables Market to Nearly Double by 2021, According to IDC.
  • https://www.idc.com/getdoc.jsp?containerId=prUS42818517 Accessed 2018/06/14.
  • Joubert, P., Erdis, C., Brijball Parumasur, S. & Cant, M.C. (2013). Introduction to consumer behaviour. 2nd ed. Cape Town: Juta.
  • Kim, E., Ham, S., Yang, I. S. & Choi, J. G. (2013). The roles of attitude, subjective norm, and perceived behavioral control in the formation of consumers’ behavioral intentions to read menu labels in the restaurant industry. International Journal of Hospitality Management, 35, 203-213.
  • Kim, K. J. & Shin, D.-H. (2015). An acceptance model for smart watches. Internet Research, 25(4), 527-541.
  • Kingston, K. (2015). Devices to track the calories you burn. http://www.livestrong.com/article/499335-devices-to-track-the-calories-you-burn/ Accessed 2016/11/06.
  • Lee, M.-C. (2009). Factors influencing the adoption of internet banking: An integration of TAM and TPB with perceived risk and perceived benefit. Electronic Commerce Research and Applications, 8, 130-141.
  • Lee, U-J. (2015). Are fitness trackers worth the money? https://www.cbsnews.com/news/are-fitness-trackers-worth-the-money/ Accessed 2018/06/17.
  • Liébana-Cabanillas, F., Muñoz-Leiva, F. & Sánchez-Fernández, J. (2013). The impact of risk on the technological acceptance of mobile payment services. Journal of Global Business Perspective, 1, 309-328.
  • Lin, C-P. & Bhattacherjee, A. (2010). Extending technology usage models to interactive hedonic technologies: a theoretical model and empirical test. Information Systems Journal, 20, 163-181.
  • Livingston, A. (2017). Are Fitness Activity Trackers & Watches Worth the Money? https://www.moneycrashers.com/fitness-activity-trackers-watches-worthit/ Accessed 2018/06/10.
  • Maher, C., Ryan, J., Ambrosi, C. & Edney, S. (2017). Users' experiences of wearable activity trackers: a cross-sectional study, BMC Public Health, 17, 1-8.
  • Markert, J. (2004). Demographics of age: generational and cohort confusion. Journal of Current Issues and Research in Advertising, 26(2), 12-25.
  • Moore, G.C. & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology adoption. Information Systems Research, 2(3), 192-222.
  • Nedbank. (2018). Annual average exchange rates. https://www.nedbank.co.za/content/dam/nedbank/siteassets/AboutUs/Economics_Unit/Forecast_and_data/Daily_Rates/Annual_Averag e_Exchange_Rates.pdf Accessed 2018/06/17.
  • Nield, D. (2017). How to do more with your fitness tracker: Harvest that activity data. https://www.popsci.com/do-more-with-fitness-tracker-data Accessed 2018/06/10.
  • Pallant, J. (2010). SPSS survival manual. 4th ed. London: Open University Press.
  • Park, E., Kim, K. J. & Kwon, S. J. (2016). Understanding the emergence of wearable devices as next-generation tools for health communication. Information Technology & People, 29:717-732.
  • Rettner, R. (2014). How well do fitness trackers monitor heart rate? http://www.livescience.com/44170-fitness-tracker-heart-rate-monitors.html Accessed 2016/11/06.
  • Richardson, P.S., Dick, A.S & Jain, A.K. (1994). Extrinsic and intrinsic cue effects on perceptions of store brand quality. Journal of Marketing, 58(4), 28-30.
  • Richter, F. (2015). The predicted wearables boom is all about the wrist. https://www.statista.com/chart/3370/wearable-device-forecast/ Accessed 2017/03/26.
  • Statista. (2018a). Wearables: Worldwide. https://www.statista.com/outlook/319/100/wearables/worldwide#market-users Accessed 2018/06/10.
  • Statista. (2018b). Wearables: South Africa. https://www.statista.com/outlook/319/112/wearables/south-africa#market-users Accessed 2018/06/10.
  • Statistics South Africa. (2017). Statistical release P0302: 2017 mid-year population estimates.
  • http://www.statssa.gov.za/publications/P0302/P03022017.pdf Accessed 2018/06/16.
  • Techopedia. (2018). Activity tracker. https://www.techopedia.com/definition/32502/activity-tracker Accessed 2018/06/16.
  • Valaei, N. & Nikhashemi, S.R. (2017). Generation Y consumers’ buying behaviour in fashion apparel industry: a moderation analysis. Journal of Fashion Marketing and Management: An International Journal, 21(4), 523-543.
  • Venkatesh, V., Morris, M. G., Davos, G. B. & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 27(3), 425-478.
  • Wu, L.-H., Wu, L.-C. & Chang, S.-C. (2016). Exploring consumers’ intention to accept smartwatch. Computers in Human Behavior, 64, 383-392.
  • Yang, H., Yu, J., Zo, H. & Choi, M. (2016). User acceptance of wearable devices: an extended perspective of perceived value. Telematics and Informatics, 33, 256- 269.

RELATIONSHIP BETWEEN SOCIAL IMAGE, BRAND NAME, SUBJECTIVE NORMS AND SOUTH AFRICAN GENERATION Y STUDENTS’ ATTITUDE TOWARDS WEARABLE ACTIVITYTRACKING DEVICES

Year 2018, Volume: 10 Issue: 2, 83 - 98, 31.12.2018

Abstract

Wearable health-promoting technological devices such as chest straps, fitness
bracelets, pedometers, smart wireless headphones known as hearables, smart
clothing, fitness watches and the like have transformed health and sports
monitoring. The wearable activity-tracking device market is expected to generate
significant revenues in 2018. The demographic that dominates this market is the
youth, with 33.7 percent of this market comprising individuals aged between 18
and 24 years, who form part of the Generation Y cohort (individuals born between
1986 and 2005). However, the literature pertaining to their attitude towards
wearable activity-tracking devices, which explains their adoption behaviour
thereof, is limited. As such, this study explores Generation Y students’ attitude
towards wearable activity-tracking devices, by examining the relationship
between social image, brand name, subjective norms, and attitude towards such
devices.
Following a descriptive research design, self-administered questionnaires were
completed by a non-probability convenience sample of 480 students registered at
the campuses of three registered public higher education institutions (HEIs) in
South Africa’s Gauteng province. The captured data were analysed using
principle component analysis, internal-consistency reliability and nomological
validity analysis, descriptive statistics, and correlation analysis.The findings indicate a significant positive relationship between social image,
brand name, subjective norms, and South African Generation Y students’ attitude
towards wearable activity-tracking devices. A device’s brand name, social image,
and the subjective norms pertaining to such a device relate significantly to
Generation Y students’ attitude towards wearable activity-tracking devices. It is
therefore paramount for device manufacturers and marketing managers to
emphasise the brand name and how such devices not only improve overall
physical health, but also increase social image and promote approval amongst
peers within this generation. 

References

  • Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179-211.
  • Beckham, J. (2012). Fitness trackers use psychology to motivate couch potatoes. https://www.wired.com/2012/04/fitness-tracker-psychology/ Accessed 2016/11/10.
  • Bevan-Dye, A.L. (2013). Black Generation Y students’ attitudes towards Web advertising value. Mediterranean Journal of Social Sciences, 4(2), 155-164.
  • Bevan-Dye, A.L. & Surujlal, J. (2011). Attitudes towards materialism in sport and materialism tendencies amongst Black Generation Y students. African Journal for Physical, Health Education, Recreation and Dance, 1(1), 43-55.
  • Blut, M., Wang, C. & Schoefer, K. (2016). Factors Influencing the Acceptance of Self-Service Technologies: A Meta-Analysis. Journal of Service Research, 19(4), 396-416.
  • Choi, J. & Kim, S. (2016). Is the smartwatch an IT product or a fashion product? A study on factors affecting the intention to use smartwatches. Computers in Human Behavior, 63, 777-786.
  • Chae, J.-M. (2009). Consumer acceptance model of smart clothing according to innovation. International Journal of Human Ecology, 10:23-33.
  • Dean, G. (2010). Understanding consumer attitudes. https://marketography.com/2010/10/17/understanding-consumer-attitudes/ Accessed 2018/06/18.
  • Del Río, A.B., Vázquez, R., Iglesias, V. (2001). The role of the brand name in obtaining differential advantages. Journal of Product and Brand Management, 10(7), 452–465
  • Field, A. (2009). Discovering statistics using SPSS. 3rd ed. London: Sage.
  • Hair, J.F., Black, W.C., Babin, B.J. & Anderson, R.E. (2010). Multivariate data analysis: a global perspective. 7th ed. Upper Saddle River, NJ: Pearson PrenticeHall.
  • Hamari, J. & Koivisto, J. (2015). ‘‘Working out for likes’’: An empirical study on social influence in exercise gamification. Computers in Human behavior, 50, 333- 347.
  • Haslam, C. (2016). Counting sleep: the best sleep tracker and monitors. https://www.wareable.com/withings/best-sleep-trackers-and-monitors Accessed 2016/11/06.
  • Hong, S-K. (2015). An explorative study of the features of activity trackers as IoT based wearable devices. Journal of Internet Computing and Services, 16(5), 93- 98.
  • International Data Corporation. (2017). Worldwide Wearables Market to Nearly Double by 2021, According to IDC.
  • https://www.idc.com/getdoc.jsp?containerId=prUS42818517 Accessed 2018/06/14.
  • Joubert, P., Erdis, C., Brijball Parumasur, S. & Cant, M.C. (2013). Introduction to consumer behaviour. 2nd ed. Cape Town: Juta.
  • Kim, E., Ham, S., Yang, I. S. & Choi, J. G. (2013). The roles of attitude, subjective norm, and perceived behavioral control in the formation of consumers’ behavioral intentions to read menu labels in the restaurant industry. International Journal of Hospitality Management, 35, 203-213.
  • Kim, K. J. & Shin, D.-H. (2015). An acceptance model for smart watches. Internet Research, 25(4), 527-541.
  • Kingston, K. (2015). Devices to track the calories you burn. http://www.livestrong.com/article/499335-devices-to-track-the-calories-you-burn/ Accessed 2016/11/06.
  • Lee, M.-C. (2009). Factors influencing the adoption of internet banking: An integration of TAM and TPB with perceived risk and perceived benefit. Electronic Commerce Research and Applications, 8, 130-141.
  • Lee, U-J. (2015). Are fitness trackers worth the money? https://www.cbsnews.com/news/are-fitness-trackers-worth-the-money/ Accessed 2018/06/17.
  • Liébana-Cabanillas, F., Muñoz-Leiva, F. & Sánchez-Fernández, J. (2013). The impact of risk on the technological acceptance of mobile payment services. Journal of Global Business Perspective, 1, 309-328.
  • Lin, C-P. & Bhattacherjee, A. (2010). Extending technology usage models to interactive hedonic technologies: a theoretical model and empirical test. Information Systems Journal, 20, 163-181.
  • Livingston, A. (2017). Are Fitness Activity Trackers & Watches Worth the Money? https://www.moneycrashers.com/fitness-activity-trackers-watches-worthit/ Accessed 2018/06/10.
  • Maher, C., Ryan, J., Ambrosi, C. & Edney, S. (2017). Users' experiences of wearable activity trackers: a cross-sectional study, BMC Public Health, 17, 1-8.
  • Markert, J. (2004). Demographics of age: generational and cohort confusion. Journal of Current Issues and Research in Advertising, 26(2), 12-25.
  • Moore, G.C. & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology adoption. Information Systems Research, 2(3), 192-222.
  • Nedbank. (2018). Annual average exchange rates. https://www.nedbank.co.za/content/dam/nedbank/siteassets/AboutUs/Economics_Unit/Forecast_and_data/Daily_Rates/Annual_Averag e_Exchange_Rates.pdf Accessed 2018/06/17.
  • Nield, D. (2017). How to do more with your fitness tracker: Harvest that activity data. https://www.popsci.com/do-more-with-fitness-tracker-data Accessed 2018/06/10.
  • Pallant, J. (2010). SPSS survival manual. 4th ed. London: Open University Press.
  • Park, E., Kim, K. J. & Kwon, S. J. (2016). Understanding the emergence of wearable devices as next-generation tools for health communication. Information Technology & People, 29:717-732.
  • Rettner, R. (2014). How well do fitness trackers monitor heart rate? http://www.livescience.com/44170-fitness-tracker-heart-rate-monitors.html Accessed 2016/11/06.
  • Richardson, P.S., Dick, A.S & Jain, A.K. (1994). Extrinsic and intrinsic cue effects on perceptions of store brand quality. Journal of Marketing, 58(4), 28-30.
  • Richter, F. (2015). The predicted wearables boom is all about the wrist. https://www.statista.com/chart/3370/wearable-device-forecast/ Accessed 2017/03/26.
  • Statista. (2018a). Wearables: Worldwide. https://www.statista.com/outlook/319/100/wearables/worldwide#market-users Accessed 2018/06/10.
  • Statista. (2018b). Wearables: South Africa. https://www.statista.com/outlook/319/112/wearables/south-africa#market-users Accessed 2018/06/10.
  • Statistics South Africa. (2017). Statistical release P0302: 2017 mid-year population estimates.
  • http://www.statssa.gov.za/publications/P0302/P03022017.pdf Accessed 2018/06/16.
  • Techopedia. (2018). Activity tracker. https://www.techopedia.com/definition/32502/activity-tracker Accessed 2018/06/16.
  • Valaei, N. & Nikhashemi, S.R. (2017). Generation Y consumers’ buying behaviour in fashion apparel industry: a moderation analysis. Journal of Fashion Marketing and Management: An International Journal, 21(4), 523-543.
  • Venkatesh, V., Morris, M. G., Davos, G. B. & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 27(3), 425-478.
  • Wu, L.-H., Wu, L.-C. & Chang, S.-C. (2016). Exploring consumers’ intention to accept smartwatch. Computers in Human Behavior, 64, 383-392.
  • Yang, H., Yu, J., Zo, H. & Choi, M. (2016). User acceptance of wearable devices: an extended perspective of perceived value. Telematics and Informatics, 33, 256- 269.
There are 44 citations in total.

Details

Primary Language English
Subjects Economics
Journal Section Research Article
Authors

Chantel Muller This is me

Natasha De Klerk This is me

Ayesha Lian Bevan-dye This is me

Publication Date December 31, 2018
Published in Issue Year 2018 Volume: 10 Issue: 2

Cite

APA Muller, C., De Klerk, N., & Bevan-dye, A. L. (2018). RELATIONSHIP BETWEEN SOCIAL IMAGE, BRAND NAME, SUBJECTIVE NORMS AND SOUTH AFRICAN GENERATION Y STUDENTS’ ATTITUDE TOWARDS WEARABLE ACTIVITYTRACKING DEVICES. International Journal of Business and Management Studies, 10(2), 83-98.
AMA Muller C, De Klerk N, Bevan-dye AL. RELATIONSHIP BETWEEN SOCIAL IMAGE, BRAND NAME, SUBJECTIVE NORMS AND SOUTH AFRICAN GENERATION Y STUDENTS’ ATTITUDE TOWARDS WEARABLE ACTIVITYTRACKING DEVICES. IJBMS. December 2018;10(2):83-98.
Chicago Muller, Chantel, Natasha De Klerk, and Ayesha Lian Bevan-dye. “RELATIONSHIP BETWEEN SOCIAL IMAGE, BRAND NAME, SUBJECTIVE NORMS AND SOUTH AFRICAN GENERATION Y STUDENTS’ ATTITUDE TOWARDS WEARABLE ACTIVITYTRACKING DEVICES”. International Journal of Business and Management Studies 10, no. 2 (December 2018): 83-98.
EndNote Muller C, De Klerk N, Bevan-dye AL (December 1, 2018) RELATIONSHIP BETWEEN SOCIAL IMAGE, BRAND NAME, SUBJECTIVE NORMS AND SOUTH AFRICAN GENERATION Y STUDENTS’ ATTITUDE TOWARDS WEARABLE ACTIVITYTRACKING DEVICES. International Journal of Business and Management Studies 10 2 83–98.
IEEE C. Muller, N. De Klerk, and A. L. Bevan-dye, “RELATIONSHIP BETWEEN SOCIAL IMAGE, BRAND NAME, SUBJECTIVE NORMS AND SOUTH AFRICAN GENERATION Y STUDENTS’ ATTITUDE TOWARDS WEARABLE ACTIVITYTRACKING DEVICES”, IJBMS, vol. 10, no. 2, pp. 83–98, 2018.
ISNAD Muller, Chantel et al. “RELATIONSHIP BETWEEN SOCIAL IMAGE, BRAND NAME, SUBJECTIVE NORMS AND SOUTH AFRICAN GENERATION Y STUDENTS’ ATTITUDE TOWARDS WEARABLE ACTIVITYTRACKING DEVICES”. International Journal of Business and Management Studies 10/2 (December 2018), 83-98.
JAMA Muller C, De Klerk N, Bevan-dye AL. RELATIONSHIP BETWEEN SOCIAL IMAGE, BRAND NAME, SUBJECTIVE NORMS AND SOUTH AFRICAN GENERATION Y STUDENTS’ ATTITUDE TOWARDS WEARABLE ACTIVITYTRACKING DEVICES. IJBMS. 2018;10:83–98.
MLA Muller, Chantel et al. “RELATIONSHIP BETWEEN SOCIAL IMAGE, BRAND NAME, SUBJECTIVE NORMS AND SOUTH AFRICAN GENERATION Y STUDENTS’ ATTITUDE TOWARDS WEARABLE ACTIVITYTRACKING DEVICES”. International Journal of Business and Management Studies, vol. 10, no. 2, 2018, pp. 83-98.
Vancouver Muller C, De Klerk N, Bevan-dye AL. RELATIONSHIP BETWEEN SOCIAL IMAGE, BRAND NAME, SUBJECTIVE NORMS AND SOUTH AFRICAN GENERATION Y STUDENTS’ ATTITUDE TOWARDS WEARABLE ACTIVITYTRACKING DEVICES. IJBMS. 2018;10(2):83-98.