Determinants of Thai Individuals Behavioral Intention towards Online Fitness Program on YouTube during COVID-19 Pandemic
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Published
May 13, 2022
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Abstract
The purpose of this research is to investigate the determinants of Thai individuals behavioral intention towards online fitness program on YouTube during COVID-19 pandemic situation. The conceptual framework is presented on how effort expectancy, performance expectancy, social influence, attitude, desire, personal innovativeness influence behavioral intention of Thai individuals. The samples of 500 respondents were collected from online and offline questionnaires by using multi-stage sampling technique. Stratified random sampling was used to group users in three age generation and purposive sampling and convenience sampling to reach target respondents. The study applied the Structural Equation Model (SEM) and Confirmatory Factor Analysis (CFA) to analyze the data and confirm goodness-of-fit of the model and hypotheses. The results of goodness-of-fit indicated the model is consistent with empirical data and hypothesis testing results indicated that effort expectancy, performance expectancy, social influence, attitude, desire, and personal innovativeness have a significant influence on behavioral intention. The researcher also found that social influence, effort expectancy and performance expectancy showed significant impact on attitude as mediator of desire which also greatly influences behavioral intention. Behavioral intention of online fitness program on YouTube users is determined by effort expectancy, performance expectancy, social influence, attitude, desire, and personal innovativeness. Hence, fitness YouTube channel owners are recommended to apply these instruments to enhance behavioral innovation when using online fitness program on YouTube.
Keywords: Behavioral Intention, Online Fitness, YouTube, COVID-19, Thai Individuals
References
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Arbuckle, J. (1995). AMOS: Analysis of Moment Structures User’s Guide. Chicago: Small Waters.
Aroean, L., & Michaelidou, N. (2014). A Taxonomy of Mobile Phone Consumers: Insights for Marketing Managers. Journal of Strategic Marketing, 22(1), 73-89. https://doi.org/10.1080/0965254X.2013.876063
Barua, Z., & Barua, A. (2021). Acceptance and Usage of mHealth Technologies amid COVID-19 Pandemic in a Developing Country: The UTAUT Combined with Situational Constraint and Health Consciousness. Journal of Enabling Technologies, 15(1), 1-22. https://doi.org/10.1108/JET-08-2020-0030
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Chaorusmeekul, P. (2020). Explore 5 Changes Exercise Routines During-Coronavirus. Retrieved from https://thestandard.co/explore-5-changes-exercise-routines-during-coronavirus/
Chaouali, W., Yahia, I. B., & Souiden, N. (2016). The Interplay of Counter-conformity Motivation, Social Influence, and Trust in Customers’ Intention to Adopt Internet Banking Services: The Case of an Emerging Country. Journal of Retailing and Consumer Services, 28, 209-218. https://doi.org/10.1016/j.jretconser.2015.10.007
Chiu, W., Kim, T., & Won, D. (2018). Predicting Consumers’ Intention to Purchase Sporting Goods Online: An Application of the Model of Goal-directed Behavior. Asia Pacific Journal of Marketing and Logistics, 30(2), 333-351. https://doi.org/10.1108/APJML-02-2017-0028
Chopdar, P. K., Korfiatis, N., Sivakumar, V. J., & Lytras, M. D. (2018). Mobile Shopping Apps Adoption and Perceived Risks: A Cross-country Perspective Utilizing the Unified Theory of Acceptance and Use of Technology. Computers in Human Behavior, 86, 109-128. https://doi.org/10.1016/j.chb.2018.04.017
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Escobar-Rodríguez, T., & Carvajal-Trujillo, E. (2014). Online Purchasing Tickets for Low Cost Carriers: An Application of the Unified Theory of Acceptance and Use of Technology (UTAUT) Model. Tourism Management, 43, 70-88. https://doi.org/10.1016/j.tourman.2014.01.017
Esposito, G., van Bavel, R., Baranowski, T., & Duch-Brown, N. (2016). Applying the Model of Goal-directed Behavior, Including Descriptive Norms, to Physical Activity Intentions: A Contribution to Improving the Theory of Planned Behavior. Psychological Reports, 119(1), 5-26. https://doi.org/10.1177/0033294116649576
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/10.2307/3151312
Gao, Y., Li, H., & Luo, Y. (2015). An Empirical Study of Wearable Technology Acceptance in Healthcare. Industrial Management & Data Systems, 115(9), 1704-1723. https://doi.org/10.1108/IMDS-03-2015-0087
Ha, Y. (2018). Online Brand Community and Its Outcomes. The Journal of Asian Finance, Economics and Business, 5(4), 107-116. https://doi.org/10.13106/jafeb.2018.vol5.no4.107
Hair, J., Black, B., Babin, B., & Anderson, R. (2010). Multivariate Data Analysis: A Global Perspective (7th ed.). Upper Saddle River, N.J.: Pearson Prentice Hall.
Hair, J. F., Black, B., Babin, B., Anderson, R. E., & Tatham, R. L. (2005). Multivariate Data Analysis (6th ed.). Harlow, England: Pearson Education.
Han, H., & Ryu, K. (2012). The Theory of Repurchase Decision-making (TRD): Identifying the Critical Factors in the Post-purchase Decision-making Process. International Journal of Hospitality Management, 31(3), 786-797. https://doi.org/10.1016/j.ijhm.2011.09.015
Hunter, G. L. (2006). The Role of Anticipated Emotion, Desire, and Intention in the Relationship between Image and Shopping Center Visits. International Journal of Retail & Distribution Management, 34(10), 709-721. https://doi.org/10.1108/09590550610691310
Juaneda-Ayensa, E., Mosquera, A., & Murillo, Y. S. (2016). Omnichannel Customer Behavior: Key Drivers of Technology Acceptance and Use and their Effects on Purchase Intention. Frontiers in Psychology, 7, 1117. https://doi.org/10.3389/fpsyg.2016.01117
Kalantari, M., & Rauschnabel, P. (2018). Exploring the Early Adopters of Augmented Reality Smart Glasses: The Case of Microsoft HoloLens. In T. Jung, & M. C. tom Dieck (Eds.), Augmented Reality and Virtual Reality: Empowering Human, Place and Business (pp. 229-245). Cham, Switzerland: Springer.
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. https://doi.org/10.1108/IntR-05-2014-0126
Kim, M.-J., Lee, M. J., Lee, C.-K., & Song, H.-J. (2012). Does Gender Affect Korean Tourists’ Overseas Travel? Applying the Model of Goal-directed Behavior. Asia Pacific Journal of Tourism Research, 17(5),
509-533. https://doi.org/10.1080/10941665.2011.627355
Kim, M. J., & Preis, M. W. (2016). Why Seniors Use Mobile Devices: Applying an Extended Model of Goal-directed Behavior. Journal of Travel & Tourism Marketing, 33(3), 404-423. https://doi.org/10.1080/10548408.2015.1064058
Lee, J.-M., Lee, B., & Rha, J.-Y. (2019). Determinants of Mobile Payment Usage and the Moderating Effect of Gender: Extending the UTAUT Model with Privacy Risk. International Journal of Electronic Commerce Studies, 10(1), 43-64. https://doi.org/10.7903/ijecs.1644
Lee, J. W. (2017). Critical Factors Affecting Consumer Acceptance of Online Health Communication: An Application of Service Quality Models. The Journal of Asian Finance, Economics and Business, 4(3), 85-94. https://doi.org/10.13106/jafeb.2017.vol4.no3.85
Leelamanit, P. (2020). Survival of the Fitness: Some Gyms will Adapt, Some won’t Survive. Retrieved from https://thisrupt.co/business/survival-of-the-fitness-gyms-wont-survive/
Lin, Z., & Theingi, H. (2019). Extended UTAUT2 Model on Factors Influencing of Mobile Commerce Acceptance in Yangon, Myanmar. AU-GSB e-Journal, 12(2), 3-18. Retrieved from http://www.assumptionjournal.au.edu/index.php/AU-GSB/article/view/4495
Lowe, B., Fraser, I., & Souza-Monteiro, D. M. (2015). A Change for the Better? Digital Health Technologies and Changing Food Consumption Behaviors. Psychology & Marketing, 32(5), 585-600. https://doi.org/10.1002/mar.20802
Meng, B., & Han, H. (2016). Effect of Environmental Perceptions on Bicycle Travelers’ Decision-making Process: Developing an Extended Model of Goal-directed Behavior. Asia Pacific Journal of Tourism Research, 21(11), 1184-1197. https://doi.org/10.1080/10941665.2015.1129979
Moghavvemi, S., Mohd Salleh, N. A., & Standing, C. (2016). Entrepreneurs Adoption of Information System Innovation: The Impact of Individual Perception and Exogenous Factors on Entrepreneurs Behavior. Internet Research, 26(5), 1181-1208. https://doi.org/10.1108/IntR-01-2014-0024
Nguyen, H. M., & Khoa, B. T. (2019). The Relationship between the Perceived Mental Benefits, Online Trust, and Personal Information Disclosure in Online Shopping. The Journal of Asian Finance, Economics and Business, 6(4), 261-270. https://doi.org/10.13106/jafeb.2019.vol6.no4.261
Oliveira, T., Thomas, M., Baptista, G., & Campos, F. (2016). Mobile Payment: Understanding the Determinants of Customer Adoption and Intention to Recommend the Technology. Computers in Human Behavior, 61, 404-414. https://doi.org/10.1016/j.chb.2016.03.030
Parasuraman, A., & Colby, C. L. (2015). An Updated and Streamlined Technology Readiness Index: TRI 2.0. Journal of Service Research, 18(1), 59-74. https://doi.org/10.1177/1094670514539730
Perugini, M., & Bagozzi, R. P. (2004). The Distinction between Desires and Intentions. European Journal of Social Psychology, 34(1), 69-84. https://doi.org/10.1002/ejsp.186
PP. (2018, March 21). YouTube vs Mass Media Reaches Nationwide and it’s not just an Entertainment Platform. Retrieved from https://www.brandbuffet.in.th/2018/03/youtube-day-2018-ecosystem-in-thailand/
Ratten, V. (2020). Coronavirus Disease (COVID-19) and Sport Entrepreneurship. International Journal of Entrepreneurial Behavior & Research, 26(6), 1379–1388. https://doi.org/10.1108/IJEBR-06-2020-0387
Sekaran, U. (1992). Research Methods for Business: A Skill-building Approach. New York: Wiley.
Seol, S., Ko, D., & Yeo, I. (2017). UX Analysis Based on TR and UTAUT of Sports Smart Wearable Devices. KSII Transactions on Internet and Information Systems, 11(8), 4162-4179. https://doi.org/10.3837/tiis.2017.08.024
Slade, E., Williams, M., Dwivedi, Y., & Piercy, N. (2015). Exploring Consumer Adoption of Proximity Mobile Payments. Journal of Strategic Marketing, 23(3), 209-223. https://doi.org/10.1080/0965254X.2014.914075
Tan, E., & Lau, J. L. (2016). Behavioural Intention to Adopt Mobile Banking among the Millennial Generation. Young Consumers, 17(1), 18-31. https://doi.org/10.1108/YC-07-2015-00537
Thailand Board of Investment. (2021). Thailand in Brief: Demographic. Retrieved from https://www.boi.go.th/index.php?page=demographic
TTG Asia. (2021). Thailand Maintains Focus on Health and Wellness Tourism. Retrieved from https://www.ttgasia.com/2021/01/04/thailand-maintains-focus-on-health-and-wellness-tourism/
Turner, R. C., & Carlson, L. (2003). Indexes of Item-Objective Congruence for Multidimensional Items. International Journal of Testing, 3(2), 163–171. https://doi.org/10.1207/S15327574IJT0302_5
van der Wellingthon, N. K. (2020). Fitness Trend in Thailand – Earn Money Now! Retrieved from https://www.sanet.eu/en/fitness-trend-in-thailand-earn-money-now/
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2016). Unified Theory of Acceptance and Use of Technology: A Synthesis and the Road Ahead. Journal of the Association for Information Systems, 17(5), 328-376. https://doi.org/10.17705/1jais.00428
Vrontis, D., Viassone, M., Serravalle, F., & Christofi, M. (2020). Managing Technological Innovation in the Sports Industry: A Challenge for Retail Management. Competitiveness Review, 30(1), 78–100. https://doi.org/10.1108/CR-11-2019-0127
Wang, J. (2020). Think with Google: Year in Search 2020 Thailand. Retrieved from https://services.google.com/fh/files/misc/yearinsearch_th_en2020.pdf
Weng, M. (2016). The Acceptance of Wearable Devices for Personal Healthcare in China (Master’s thesis). University of Oulu, Finland. Retrieved from http://jultika.oulu.fi/files/nbnfioulu-201605111684.pdf
Wijesundara, T. R., & Xixiang, S. (2017). Intention to Use Social Networking Sites: Impact of Personal Innovativeness. Journal on Innovation and Sustainability, 8(1), 79-90. https://doi.org/10.24212/2179-3565.2017V8I1P79-90
Aksoy, N. C., Alan, A. K., Kabadayi, E. T., & Aksoy, A. (2020). Individuals’ Intention to Use Sports Wearables: the Moderating Role of Technophobia. International Journal of Sports Marketing and Sponsorship, 21(2), 225–245. https://doi.org/10.1108/ijsms-08-2019-0083
Arbuckle, J. (1995). AMOS: Analysis of Moment Structures User’s Guide. Chicago: Small Waters.
Aroean, L., & Michaelidou, N. (2014). A Taxonomy of Mobile Phone Consumers: Insights for Marketing Managers. Journal of Strategic Marketing, 22(1), 73-89. https://doi.org/10.1080/0965254X.2013.876063
Barua, Z., & Barua, A. (2021). Acceptance and Usage of mHealth Technologies amid COVID-19 Pandemic in a Developing Country: The UTAUT Combined with Situational Constraint and Health Consciousness. Journal of Enabling Technologies, 15(1), 1-22. https://doi.org/10.1108/JET-08-2020-0030
Browne, M. W., & Cudeck, R. (1993). Alternative Ways of Assessing Model Fit. In K. A. Bollen, & J. S. Long (Eds.), Testing Structural Equation Models (pp. 136–162). Newbury Park, CA: Sage.
Chaorusmeekul, P. (2020). Explore 5 Changes Exercise Routines During-Coronavirus. Retrieved from https://thestandard.co/explore-5-changes-exercise-routines-during-coronavirus/
Chaouali, W., Yahia, I. B., & Souiden, N. (2016). The Interplay of Counter-conformity Motivation, Social Influence, and Trust in Customers’ Intention to Adopt Internet Banking Services: The Case of an Emerging Country. Journal of Retailing and Consumer Services, 28, 209-218. https://doi.org/10.1016/j.jretconser.2015.10.007
Chiu, W., Kim, T., & Won, D. (2018). Predicting Consumers’ Intention to Purchase Sporting Goods Online: An Application of the Model of Goal-directed Behavior. Asia Pacific Journal of Marketing and Logistics, 30(2), 333-351. https://doi.org/10.1108/APJML-02-2017-0028
Chopdar, P. K., Korfiatis, N., Sivakumar, V. J., & Lytras, M. D. (2018). Mobile Shopping Apps Adoption and Perceived Risks: A Cross-country Perspective Utilizing the Unified Theory of Acceptance and Use of Technology. Computers in Human Behavior, 86, 109-128. https://doi.org/10.1016/j.chb.2018.04.017
David. (2019). Social Media Trends 2019: Part 4–Thailand Leads the World in Time Spent Online. Retrieved from https://lexiconthai.com/blog/thailand-leads-the-world-in-time-spent-online/
Department of Business Development, Ministry of Commerce. (2019). Business Analysis Report: November 2019. Retrieved from https://www.dbd.go.th/download/document_file/Statisic/2562/T26/T26_201911.pdf
Dessart, L., & Duclou, M. (2019). Health and Fitness Online Communities and Product Behaviour. Journal of Product & Brand Management, 28(2), 188–199. https://doi.org/10.1108/JPBM-12-2017-1710
Destination Thailand News. (2021). Thailand COVID-19 Recovery Fitness Trends by Jetts. Retrieved from https://destinationthailandnews.com/lifestyle-news/health-and-wellness/thailand-covid-19-recovery-fitness-trends-by-jetts.html
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-05-2018-0158
Electronic Transactions Development Agency. (2020, March 30). ETDA Revealed Thailand Internet User Behavior 2019. Retrieved from https://www.etda.or.th/th/NEWS/ETDA-Revealed-Thailand-Internet-User-Behavior-2019.aspx
Escobar-Rodríguez, T., & Carvajal-Trujillo, E. (2014). Online Purchasing Tickets for Low Cost Carriers: An Application of the Unified Theory of Acceptance and Use of Technology (UTAUT) Model. Tourism Management, 43, 70-88. https://doi.org/10.1016/j.tourman.2014.01.017
Esposito, G., van Bavel, R., Baranowski, T., & Duch-Brown, N. (2016). Applying the Model of Goal-directed Behavior, Including Descriptive Norms, to Physical Activity Intentions: A Contribution to Improving the Theory of Planned Behavior. Psychological Reports, 119(1), 5-26. https://doi.org/10.1177/0033294116649576
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/10.2307/3151312
Gao, Y., Li, H., & Luo, Y. (2015). An Empirical Study of Wearable Technology Acceptance in Healthcare. Industrial Management & Data Systems, 115(9), 1704-1723. https://doi.org/10.1108/IMDS-03-2015-0087
Ha, Y. (2018). Online Brand Community and Its Outcomes. The Journal of Asian Finance, Economics and Business, 5(4), 107-116. https://doi.org/10.13106/jafeb.2018.vol5.no4.107
Hair, J., Black, B., Babin, B., & Anderson, R. (2010). Multivariate Data Analysis: A Global Perspective (7th ed.). Upper Saddle River, N.J.: Pearson Prentice Hall.
Hair, J. F., Black, B., Babin, B., Anderson, R. E., & Tatham, R. L. (2005). Multivariate Data Analysis (6th ed.). Harlow, England: Pearson Education.
Han, H., & Ryu, K. (2012). The Theory of Repurchase Decision-making (TRD): Identifying the Critical Factors in the Post-purchase Decision-making Process. International Journal of Hospitality Management, 31(3), 786-797. https://doi.org/10.1016/j.ijhm.2011.09.015
Hunter, G. L. (2006). The Role of Anticipated Emotion, Desire, and Intention in the Relationship between Image and Shopping Center Visits. International Journal of Retail & Distribution Management, 34(10), 709-721. https://doi.org/10.1108/09590550610691310
Juaneda-Ayensa, E., Mosquera, A., & Murillo, Y. S. (2016). Omnichannel Customer Behavior: Key Drivers of Technology Acceptance and Use and their Effects on Purchase Intention. Frontiers in Psychology, 7, 1117. https://doi.org/10.3389/fpsyg.2016.01117
Kalantari, M., & Rauschnabel, P. (2018). Exploring the Early Adopters of Augmented Reality Smart Glasses: The Case of Microsoft HoloLens. In T. Jung, & M. C. tom Dieck (Eds.), Augmented Reality and Virtual Reality: Empowering Human, Place and Business (pp. 229-245). Cham, Switzerland: Springer.
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. https://doi.org/10.1108/IntR-05-2014-0126
Kim, M.-J., Lee, M. J., Lee, C.-K., & Song, H.-J. (2012). Does Gender Affect Korean Tourists’ Overseas Travel? Applying the Model of Goal-directed Behavior. Asia Pacific Journal of Tourism Research, 17(5),
509-533. https://doi.org/10.1080/10941665.2011.627355
Kim, M. J., & Preis, M. W. (2016). Why Seniors Use Mobile Devices: Applying an Extended Model of Goal-directed Behavior. Journal of Travel & Tourism Marketing, 33(3), 404-423. https://doi.org/10.1080/10548408.2015.1064058
Lee, J.-M., Lee, B., & Rha, J.-Y. (2019). Determinants of Mobile Payment Usage and the Moderating Effect of Gender: Extending the UTAUT Model with Privacy Risk. International Journal of Electronic Commerce Studies, 10(1), 43-64. https://doi.org/10.7903/ijecs.1644
Lee, J. W. (2017). Critical Factors Affecting Consumer Acceptance of Online Health Communication: An Application of Service Quality Models. The Journal of Asian Finance, Economics and Business, 4(3), 85-94. https://doi.org/10.13106/jafeb.2017.vol4.no3.85
Leelamanit, P. (2020). Survival of the Fitness: Some Gyms will Adapt, Some won’t Survive. Retrieved from https://thisrupt.co/business/survival-of-the-fitness-gyms-wont-survive/
Lin, Z., & Theingi, H. (2019). Extended UTAUT2 Model on Factors Influencing of Mobile Commerce Acceptance in Yangon, Myanmar. AU-GSB e-Journal, 12(2), 3-18. Retrieved from http://www.assumptionjournal.au.edu/index.php/AU-GSB/article/view/4495
Lowe, B., Fraser, I., & Souza-Monteiro, D. M. (2015). A Change for the Better? Digital Health Technologies and Changing Food Consumption Behaviors. Psychology & Marketing, 32(5), 585-600. https://doi.org/10.1002/mar.20802
Meng, B., & Han, H. (2016). Effect of Environmental Perceptions on Bicycle Travelers’ Decision-making Process: Developing an Extended Model of Goal-directed Behavior. Asia Pacific Journal of Tourism Research, 21(11), 1184-1197. https://doi.org/10.1080/10941665.2015.1129979
Moghavvemi, S., Mohd Salleh, N. A., & Standing, C. (2016). Entrepreneurs Adoption of Information System Innovation: The Impact of Individual Perception and Exogenous Factors on Entrepreneurs Behavior. Internet Research, 26(5), 1181-1208. https://doi.org/10.1108/IntR-01-2014-0024
Nguyen, H. M., & Khoa, B. T. (2019). The Relationship between the Perceived Mental Benefits, Online Trust, and Personal Information Disclosure in Online Shopping. The Journal of Asian Finance, Economics and Business, 6(4), 261-270. https://doi.org/10.13106/jafeb.2019.vol6.no4.261
Oliveira, T., Thomas, M., Baptista, G., & Campos, F. (2016). Mobile Payment: Understanding the Determinants of Customer Adoption and Intention to Recommend the Technology. Computers in Human Behavior, 61, 404-414. https://doi.org/10.1016/j.chb.2016.03.030
Parasuraman, A., & Colby, C. L. (2015). An Updated and Streamlined Technology Readiness Index: TRI 2.0. Journal of Service Research, 18(1), 59-74. https://doi.org/10.1177/1094670514539730
Perugini, M., & Bagozzi, R. P. (2004). The Distinction between Desires and Intentions. European Journal of Social Psychology, 34(1), 69-84. https://doi.org/10.1002/ejsp.186
PP. (2018, March 21). YouTube vs Mass Media Reaches Nationwide and it’s not just an Entertainment Platform. Retrieved from https://www.brandbuffet.in.th/2018/03/youtube-day-2018-ecosystem-in-thailand/
Ratten, V. (2020). Coronavirus Disease (COVID-19) and Sport Entrepreneurship. International Journal of Entrepreneurial Behavior & Research, 26(6), 1379–1388. https://doi.org/10.1108/IJEBR-06-2020-0387
Sekaran, U. (1992). Research Methods for Business: A Skill-building Approach. New York: Wiley.
Seol, S., Ko, D., & Yeo, I. (2017). UX Analysis Based on TR and UTAUT of Sports Smart Wearable Devices. KSII Transactions on Internet and Information Systems, 11(8), 4162-4179. https://doi.org/10.3837/tiis.2017.08.024
Slade, E., Williams, M., Dwivedi, Y., & Piercy, N. (2015). Exploring Consumer Adoption of Proximity Mobile Payments. Journal of Strategic Marketing, 23(3), 209-223. https://doi.org/10.1080/0965254X.2014.914075
Tan, E., & Lau, J. L. (2016). Behavioural Intention to Adopt Mobile Banking among the Millennial Generation. Young Consumers, 17(1), 18-31. https://doi.org/10.1108/YC-07-2015-00537
Thailand Board of Investment. (2021). Thailand in Brief: Demographic. Retrieved from https://www.boi.go.th/index.php?page=demographic
TTG Asia. (2021). Thailand Maintains Focus on Health and Wellness Tourism. Retrieved from https://www.ttgasia.com/2021/01/04/thailand-maintains-focus-on-health-and-wellness-tourism/
Turner, R. C., & Carlson, L. (2003). Indexes of Item-Objective Congruence for Multidimensional Items. International Journal of Testing, 3(2), 163–171. https://doi.org/10.1207/S15327574IJT0302_5
van der Wellingthon, N. K. (2020). Fitness Trend in Thailand – Earn Money Now! Retrieved from https://www.sanet.eu/en/fitness-trend-in-thailand-earn-money-now/
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2016). Unified Theory of Acceptance and Use of Technology: A Synthesis and the Road Ahead. Journal of the Association for Information Systems, 17(5), 328-376. https://doi.org/10.17705/1jais.00428
Vrontis, D., Viassone, M., Serravalle, F., & Christofi, M. (2020). Managing Technological Innovation in the Sports Industry: A Challenge for Retail Management. Competitiveness Review, 30(1), 78–100. https://doi.org/10.1108/CR-11-2019-0127
Wang, J. (2020). Think with Google: Year in Search 2020 Thailand. Retrieved from https://services.google.com/fh/files/misc/yearinsearch_th_en2020.pdf
Weng, M. (2016). The Acceptance of Wearable Devices for Personal Healthcare in China (Master’s thesis). University of Oulu, Finland. Retrieved from http://jultika.oulu.fi/files/nbnfioulu-201605111684.pdf
Wijesundara, T. R., & Xixiang, S. (2017). Intention to Use Social Networking Sites: Impact of Personal Innovativeness. Journal on Innovation and Sustainability, 8(1), 79-90. https://doi.org/10.24212/2179-3565.2017V8I1P79-90
Section
Research Articles
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How to Cite
SAMRITPRICHA, Pailin; VONGURAI, Rawin.
Determinants of Thai Individuals Behavioral Intention towards Online Fitness Program on YouTube during COVID-19 Pandemic.
Journal of Community Development Research (Humanities and Social Sciences), [S.l.], v. 15, n. 2, p. 71-84, may 2022.
ISSN 2985-0231.
Available at: <https://www.journal.nu.ac.th/JCDR/article/view/Vol-15-No-2-2022-71-84>. Date accessed: 18 apr. 2024.
doi: https://doi.org/10.14456/jcdr-hs.2022.16.