Consumers’ Use of Smartphone Fitness Applications: Adaptation of the Unified Technology Acceptance and Usage Model-2 to Turkish Culture

Öz

This paper highlights technological changes and developments in the field of participation sports allow individuals to track their performances, provide feedback and be more motivated for physical movement through various features via smartphone fitness applications. These technological changes in the sports industry provide individuals with the opportunity to embody sports products or services at the same time. These concretization attempts allow marketers to be more user-oriented, especially in the field of smartphone fitness applications. In this context, the purpose of the research is to test the suitability of smartphone fitness applications by consumers in Turkish culture in line with the “Unified Technology Acceptance and Use Model-2” (UTAUT-2). A total of 385 (X̄Age=34.63±10) participants, 226 (X̄Age=34.35±10.72) female and 159 (X̄Age=35.04±8.86) male, participated in the study. Participants were given a “Personal Information Form” and “Neeraj et al. the measurement model”, which consists of 7 sub-dimensions and 21 items developed in line with UTAUT-2 for smartphone fitness applications and in which the items are evaluated in a 7-point Likert type, is presented. The SmartPLS 4 program was used to test the model in Turkish culture.

Anahtar Kelimeler

• fitness
• smarphone apps
• consumer behavior
• UTAUT-2

Tüketicilerin Akıllı Telefon Fitness Uygulamaları Kullanımı: Birleştirilmiş Teknoloji Kabul ve Kullanım Modeli-2’nin Türk Kültürüne Uyarlanması

Öz

Katılım sporu alanında yaşanan teknolojik değişimler ve gelişimler bireylerin akıllı telefon fitness uygulamaları aracılığıyla performanslarını takip etmesini, geri dönüt sağlamasını ve çeşitli özellikler aracılığıyla fiziksel hareket için daha fazla güdülenmesini sağlamaktadır. Aynı zamanda spor endüstrisinde yaşanan bu teknolojik değişimler, bireylere spor ürünü veya hizmetini somutlaştırma imkânı tanımaktadır. Bu somutlaştırma girişimleri pazarlamacıların özellikle akıllı telefon fitness uygulamaları alanında daha fazla kullanıcı odaklı olmasını sağlamaktadır. Bu bağlamda araştırmanın amacı, akıllı telefon fitness uygulamalarının tüketiciler tarafından kabul ve kullanımının Birleştirilmiş Teknoloji Kabul ve Kullanım Modeli-2 (BTKKM-2) doğrultusunda Türk kültürüne uygunluğunun sınanmasıdır. Araştırmada 226 (X̄Yaş=34,35±10,72) kadın ve 159 (X̄Yaş=35,04±8,86) erkek olmak üzere toplamda 385 (X̄Yaş=34,63±10) katılımcı yer almıştır. Katılımcılara “Kişisel Bilgi Formu” ve “Neeraj ve ark. tarafından akıllı telefon fitness uygulamaları için BTKKM-2” doğrultusunda geliştirilen 7 alt boyut ve 21 maddeden oluşan ve maddelerin 7’li Likert tipinde değerlendirildiği ölçüm modeli sunulmuştur. Modelin Türk kültüründe sınanması amacıyla SmartPLS 4 programından yararlanılmıştır.

Anahtar Kelimeler

• Akıllı Telefon Uygulamaları
• Fitness
• BTKKM-2
• Tüketici Davranışı

Kaynakça

1. Aksoy, G. (2020). An investigation of the factors affecting behavioural intention towards virtual tour usage, based on the "Technology Acceptance Model" (Unpublished doctoral dissertation). Department of Business Administration, Gazi University.
2. Barbosa, F., Fernández, G. J., Pedrogosa, V., & Carrión, C. G. (2021). The use of fitness centre apps and its relation to customer satisfaction: A UTAUT-2 perspective. International Journal of Sports Marketing and Sponsorship, 23(5), 966-985. https://doi.org/10.1108/IJSMS-01-2021-0010
3. Binyamin, S., & Hoque, R. (2020). Understanding the drivers of wearable health monitoring technology: An extension of the unified theory of acceptance and use of technology. Sustainability, 12(24), 9605. https://doi.org/10.3390/su12249605
4. Büyüköztürk, Ş., Çakmak, K. E., Akgün, E. Ö., Karadeniz, Ş., & Demirel, F. (2019). Eğitimde bilimsel araştırma yöntemleri [Scientific research methods in education]. Ankara: Pegem Akademi.
5. Çakır, F. S. (2019). Partial least squares structural equation modeling (PLS-SEM) and an application. Social Research and Behavioral Sciences, 5(9), 111-128.
6. Cheng, K. L., Huang, L. H., & Lai, C. (2022). Continuance intention in running apps: The moderating effect of relationship norms. International Journal of Sports Marketing and Sponsorship, 23(1), 132-154. https://doi.org/10.1108/IJSMS-08-2020-0143
7. Dal, Ö. (2021). Big data in health services: Examination of factors affecting the use of mobile health applications with the extended technology acceptance model (Unpublished doctoral dissertation). Department of Business Administration, Beykent University.
8. Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results (Doctoral dissertation). Massachusetts Institute of Technology.

9. Davis, F. D. (1989). Technology acceptance model: TAM. In M. N. Al-Suqri & A. S. Al-Aufi (Eds.), Information seeking behavior and technology adoption (pp. 205-219). Hershey, PA: IGI Global.
10. Demir, E. B. K., & Akbulut, Y. (2017). Development of a scale for the acceptance and use of online social networks for instructional purposes. Turkish Journal of Computer and Mathematics Education, 8(1), 52-82.
11. Dhiman, N., Arora, N., Dogra, N., & Gupta, A. (2020). Consumer adoption of smartphone fitness apps: An extended UTAUT2 perspective. Journal of Indian Business Research, 12(3), 363-388. https://doi.org/10.1108/JIBR-05-2019-0152
12. Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
13. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.1177/002224378101800104
14. George, D., & Mallery, P. (2019). IBM SPSS statistics 26 step by step: A simple guide and reference. Routledge.
15. Ha, K., Kang, J. S., & Pil, H. (2015). A conceptual framework for the adoption of smartphones in a sports context. International Journal of Sports Marketing & Sponsorship, 16(4), 19-36. https://doi.org/10.1108/IJSMS-16-04-2015-B005
16. Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24.
17. Hair Jr, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Evaluation of reflective measurement models. In Partial least squares structural equation modeling (PLS-SEM) using R: A workbook (pp. 75–90).
18. Hooper, D., Coughlan, J., & Mullen, M. (2008). Structural equation modelling: Guidelines for determining model fit. Electronic Journal of Business Research Methods, 6(1), 53–60.
19. Hwang, H., Yang, H., Williams, A., & Pedersen, P. (2020). A gratification model of sport team mobile application usage. Sport Marketing Quarterly, 29(3), 163–176.
20. International Test Commission. (2018). ITC guidelines for translating and adapting tests (Second Edition). International Journal of Testing, 18(2), 101–134.
21. Kim, Y., Rogol, E., & Kim, S. (2017). The effects of consumer innovativeness on sport team applications acceptance and usage. Journal of Sport Management, 31(3), 241–255.
22. Kwak, H. D., & McDaniel, R. S. (2011). Using an extended technology acceptance model in exploring antecedents to adopting fantasy sports league websites. International Journal of Sports Marketing & Sponsorship, 12(3), 240–253.
23. Purwanto, A., & Sudargini, Y. (2021). Partial least squares structural equation modeling (PLS-SEM) analysis for social and management research: A literature review. Journal of Industrial Engineering & Management Research, 2(4), 114–123.
24. Ringle, C. M., Sarstedt, M., Mitchell, R., & Gudergan, S. P. (2020). Partial least squares structural equation modeling in HRM research. The International Journal of Human Resource Management, 31(12), 1617–1643.
25. Ruiz, G. A., Ruiz, G. P., Bocenegra, L., & Fernandez, G. J. (2022). Investigating the intention to use fitness apps: The role of the perceived attractiveness of fitness center customers. Sport, Business and Management: An International Journal, 12(4), 537–553.
26. Sarstedt, M., Ringle, C. M., & Hair, J. F. (2021). Partial least squares structural equation modeling. In C. Homburg, M. Klarmann, & A. Vomberg (Eds.), Handbook of market research (pp. 587–632). Springer
27. Şen, Ö. (2017). Investigation of online purchase behavior through the Theory of Planned Behavior, Technology Acceptance Model, Diffusion of Innovations Theory, consumer habits, and trust factors (Unpublished doctoral dissertation). Haliç University, Institute of Social Sciences, Istanbul, Türkiye.
28. Tavakol, M., & Dennick, R. (2011). Making sense of Cronbach’s alpha. International Journal of Medical Education, 2, 53–55. https://doi.org/10.5116/ijme.4dfb.8dfd
29. Tiryaki, İ. (2021). An investigation of consumer behavioral intentions to use Internet of Things (IoT) technology within the extended technology acceptance model (Unpublished doctoral dissertation). Ufuk University, Institute of Social Sciences, Istanbul, Türkiye.
30. Tiryaki, İ., & Önder Gökmerdan, L. (2022). Investigation of consumers’ behavioral intentions toward the use of smart wearable objects through the extended technology acceptance model. Journal of Business Research-Turk, 14(1), 182–202. https://doi.org/10.20491/isarder.2022.1387
31. Toker, A., & Oc, Y. (2022). An acceptance model for sports technologies: The effects of sports motivation, sports type and context-aware characteristics. International Journal of Sports Marketing and Sponsorship, 23(4), 785–803. https://doi.org/10.1108/IJSMS-04-2021-0082
32. Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178. https://doi.org/10.2307/41410412
33. Yim, H. B., Byon, K. K., Baker, T. A., & Zhang, J. J. (2021). Identifying critical factors in sport consumption decision-making of millennial sport fans: Mixed-methods approach. European Sport Management Quarterly, 21(4), 484–503. https://doi.org/10.1080/16184742.2020.1742645
34. Yuan, S., Ma, W., & Kanthawala, S. (2015). Keep using my health apps: Discover users’ perception of health and fitness apps with the UTAUT-2 model. Telemedicine and e-Health, 21(9), 735–741. https://doi.org/10.1089/tmj.2014.0196