An Empirical Investigation into the Impact of Social Media Fitness Videos on Users’ Exercise Intentions
Abstract
:1. Introduction
2. Theoretical Background
2.1. The S-O-R Model
2.2. Source Credibility Theory
3. Hypothesis Development
3.1. Social Media Fitness Influencers’ Attributes, Information Credibility, and Perceived Usefulness
3.1.1. Social Media Fitness Influencers’ Attributes and Information Credibility
3.1.2. Social Media Fitness Influencers’ Attributes and Perceived Usefulness
3.2. Content Quality of Fitness Videos, Information Credibility, and Perceived Usefulness
3.3. Electronic Word-of-Mouth of Fitness Videos, Information Credibility, and Perceived Usefulness
3.4. Information Credibility and Exercise Intention
3.5. Perceived Usefulness and Exercise Intention
4. Methodology
4.1. Measures
4.2. Data Collection and Sample
5. Data Analysis and Results
5.1. Measurement Model Evaluation
5.2. Structural Model Evaluation
6. Discussion
7. Implications
7.1. Theoretical Implications
7.2. Practical Implications
8. Limitations and Future Directions
9. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
Construct | Measurement Items |
---|---|
Trustworthiness | The influencer is trustworthy. |
The influencer is sincere. | |
The influencer is honest. | |
The influencer is dependable. | |
Expertise | The influencer is knowledgeable. |
The influencer is experienced. | |
The influencer is skilled. | |
The influencer is expert. | |
Attractiveness | The influencer is classy. |
The influencer is beautiful. | |
The influencer is sexy. | |
The influencer is attractive. | |
Content Quality | The content of fitness video is reliable. |
The content of fitness video is updated. | |
The content of fitness video is accurate. | |
The content of fitness video is high-quality. | |
eWOM | I often gather information from other fitness enthusiasts’ online reviews before using fitness videos for workouts. |
If I didn’t read the online reviews before using a fitness video, I worry about my decision. | |
I often read reviews from other fitness enthusiasts to find out which fitness video make a good impression on them. | |
I often consult other fitness enthusiasts’ online reviews to help me choose a good fitness video. | |
To make sure I choose the right fitness video, I often read other fitness enthusiasts’ online reviews. | |
Information Credibility | I think fitness video information is credible. |
I think fitness video information is trustworthy. | |
I think fitness video information is truthful. | |
I think fitness video information is reliable. | |
I think fitness video information is believable. | |
Perceived Usefulness | Using fitness videos helps me improve my fitness performance. |
Using fitness videos helps me reach my fitness goals faster. | |
Using fitness videos helps me improve my fitness efficiency. | |
Exercise Intention | I intend to use this fitness video to exercise in the near future. |
I intend to use this fitness video more when I exercise. | |
If I want to exercise, I will consider to use this fitness video. |
References
- Bull, F.C.; Al-Ansari, S.S.; Biddle, S.; Borodulin, K.; Buman, M.P.; Cardon, G.; Carty, C.; Chaput, J.P.; Chastin, S.; Chou, R.; et al. World Health Organization 2020 guidelines on physical activity and sedentary behaviour. Br. J. Sport. Med. 2020, 54, 1451–1462. [Google Scholar] [CrossRef] [PubMed]
- Durau, J.; Diehl, S.; Terlutter, R. Motivate me to exercise with you: The effects of social media fitness influencers on users’ intentions to engage in physical activity and the role of user gender. Digit. Health 2022, 8, 20552076221102769. [Google Scholar] [CrossRef]
- Jong, S.T.; Drummond, M.J. Exploring online fitness culture and young females. In Re-Thinking Leisure in a Digital Age; Routledge: Oxfordshire, UK, 2020; pp. 50–62. [Google Scholar]
- Vaterlaus, J.M.; Patten, E.V.; Roche, C.; Young, J.A. # Gettinghealthy: The perceived influence of social media on young adult health behaviors. Comput. Hum. Behav. 2015, 45, 151–157. [Google Scholar] [CrossRef]
- Johnston, C.; Davis, W.E. Motivating exercise through social media: Is a picture always worth a thousand words? Psychol. Sport Exerc. 2019, 41, 119–126. [Google Scholar] [CrossRef]
- Oh, Y. The Relationship between Exercise Re-Participation Intention Based on the Sports-Socialization Process: YouTube Sports Content Intervention. Behav. Sci. 2023, 13, 187. [Google Scholar] [CrossRef]
- Kiecker, P.; Cowles, D. Interpersonal communication and personal influence on the Internet: A framework for examining online word-of-mouth. J. Euromark. 2002, 11, 71–88. [Google Scholar] [CrossRef]
- Wiedmann, K.-P.; Von Mettenheim, W. Attractiveness, trustworthiness and expertise–social influencers’ winning formula? J. Prod. Brand Manag. 2020, 30, 707–725. [Google Scholar] [CrossRef]
- Lutkenhaus, R.O.; Jansz, J.; Bouman, M.P. Tailoring in the digital era: Stimulating dialogues on health topics in collaboration with social media influencers. Digit. Health 2019, 5, 2055207618821521. [Google Scholar] [CrossRef] [PubMed]
- Cai, J.; Zhao, Y.; Sun, J. Factors influencing fitness app users’ behavior in China. Int. J. Hum.–Comput. Interact. 2022, 38, 53–63. [Google Scholar] [CrossRef]
- Beldad, A.D.; Hegner, S.M. Expanding the technology acceptance model with the inclusion of trust, social influence, and health valuation to determine the predictors of German users’ willingness to continue using a fitness app: A structural equation modeling approach. Int. J. Hum.–Comput. Interact. 2018, 34, 882–893. [Google Scholar] [CrossRef]
- Ohanian, R. Construction and validation of a scale to measure celebrity endorsers’ perceived expertise, trustworthiness, and attractiveness. J. Advert. 1990, 19, 39–52. [Google Scholar] [CrossRef]
- Xiao, M.; Wang, R.; Chan-Olmsted, S. Factors affecting YouTube influencer marketing credibility: A heuristic-systematic model. J. Media Bus. Stud. 2018, 15, 188–213. [Google Scholar] [CrossRef]
- Reinikainen, H.; Munnukka, J.; Maity, D.; Luoma-Aho, V. ‘You really are a great big sister’–parasocial relationships, credibility, and the moderating role of audience comments in influencer marketing. J. Mark. Manag. 2020, 36, 279–298. [Google Scholar] [CrossRef]
- Santateresa-Bernat, P.; Sánchez-García, I.; Curras-Perez, R. I like you, or I like what you say? Effect of influencer on tourists’ behaviours. Curr. Issues Tour. 2023, 26, 3160–3174. [Google Scholar] [CrossRef]
- Slater, M.D.; Rouner, D. How message evaluation and source attributes may influence credibility assessment and belief change. J. Mass Commun. Q. 1996, 73, 974–991. [Google Scholar] [CrossRef]
- Duan, W.; Gu, B.; Whinston, A.B. The dynamics of online word-of-mouth and product sales—An empirical investigation of the movie industry. J. Retail. 2008, 84, 233–242. [Google Scholar] [CrossRef]
- Zhao, J.-D.; Huang, J.-S.; Su, S. The effects of trust on consumers’ continuous purchase intentions in C2C social commerce: A trust transfer perspective. J. Retail. Consum. Serv. 2019, 50, 42–49. [Google Scholar] [CrossRef]
- Davis, F.D.; Bagozzi, R.P.; Warshaw, P.R. User acceptance of computer technology: A comparison of two theoretical models. Manag. Sci. 1989, 35, 982–1003. [Google Scholar] [CrossRef]
- Mehrabian, A.; Russell, J.A. An Approach to Environmental Psychology; The MIT Press: Cambridge, MA, USA, 1974. [Google Scholar]
- Zhang, H.; Lu, Y.; Gupta, S.; Zhao, L. What motivates customers to participate in social commerce? The impact of technological environments and virtual customer experiences. Inf. Manag. 2014, 51, 1017–1030. [Google Scholar] [CrossRef]
- Song, Z.; Liu, C.; Shi, R. How do fresh live broadcast impact consumers’ purchase intention? Based on the SOR Theory. Sustainability 2022, 14, 14382. [Google Scholar] [CrossRef]
- Kim, A.J.; Johnson, K.K. Power of consumers using social media: Examining the influences of brand-related user-generated content on Facebook. Comput. Hum. Behav. 2016, 58, 98–108. [Google Scholar] [CrossRef]
- Bhattacherjee, A.; Sanford, C. Influence processes for information technology acceptance: An elaboration likelihood model. MIS Q. 2006, 30, 805–825. [Google Scholar] [CrossRef]
- Hovland, C.I.; Janis, I.L.; Kelley, H.H. Communication and Persuasion; Yale University Press: New Haven, CT, USA, 1953. [Google Scholar]
- Ayeh, J.K. Travellers’ acceptance of consumer-generated media: An integrated model of technology acceptance and source credibility theories. Comput. Hum. Behav. 2015, 48, 173–180. [Google Scholar] [CrossRef]
- Smith, G. The 2001 general election: Factors influencing the brand image of political parties and their leaders. J. Mark. Manag. 2001, 17, 989–1006. [Google Scholar] [CrossRef]
- Djafarova, E.; Trofimenko, O. ‘Instafamous’–credibility and self-presentation of micro-celebrities on social media. Inf. Commun. Soc. 2019, 22, 1432–1446. [Google Scholar] [CrossRef]
- McKnight, D.H.; Kacmar, C.J. Factors and effects of information credibility. In Proceedings of the Ninth International Conference on Electronic Commerce, Minneapolis, MN, USA, 23–26 July 2007; pp. 423–432. [Google Scholar]
- Erdogan, B.Z. Celebrity endorsement: A literature review. J. Mark. Manag. 1999, 15, 291–314. [Google Scholar] [CrossRef]
- Lê Giang Nam, H.T.D. Impact of social media Influencer marketing on consumer at Ho Chi Minh City. Int. J. Soc. Sci. Humanit. Invent. 2018, 5, 4710–4714. [Google Scholar]
- Schouten, A.P.; Janssen, L.; Verspaget, M. Celebrity vs. Influencer endorsements in advertising: The role of identification, credibility, and Product-Endorser fit. In Leveraged Marketing Communications; Routledge: Oxfordshire, UK, 2021; pp. 208–231. [Google Scholar]
- Pornpitakpan, C. The persuasiveness of source credibility: A critical review of five decades’ evidence. J. Appl. Soc. Psychol. 2004, 34, 243–281. [Google Scholar] [CrossRef]
- Wathen, C.N.; Burkell, J. Believe it or not: Factors influencing credibility on the Web. J. Am. Soc. Inf. Sci. Technol. 2002, 53, 134–144. [Google Scholar] [CrossRef]
- Crisci, R.; Kassinove, H. Effect of perceived expertise, strength of advice, and environmental setting on parental compliance. J. Soc. Psychol. 1973, 89, 245–250. [Google Scholar] [CrossRef]
- Yadav, M.S.; De Valck, K.; Hennig-Thurau, T.; Hoffman, D.L.; Spann, M. Social commerce: A contingency framework for assessing marketing potential. J. Interact. Mark. 2013, 27, 311–323. [Google Scholar] [CrossRef]
- Patzer, G.L. Source credibility as a function of communicator physical attractiveness. J. Bus. Res. 1983, 11, 229–241. [Google Scholar] [CrossRef]
- Till, B.D.; Busler, M. The match-up hypothesis: Physical attractiveness, expertise, and the role of fit on brand attitude, purchase intent and brand beliefs. J. Advert. 2000, 29, 1–13. [Google Scholar] [CrossRef]
- Palmer, C.L.; Peterson, R.D. Halo effects and the attractiveness premium in perceptions of political expertise. Am. Politics Res. 2016, 44, 353–382. [Google Scholar] [CrossRef]
- Kamins, M.A. An investigation into the “match-up” hypothesis in celebrity advertising: When beauty may be only skin deep. J. Advert. 1990, 19, 4–13. [Google Scholar] [CrossRef]
- Hu, H.; Zhang, D.; Wang, C. Impact of social media influencers’ endorsement on application adoption: A trust transfer perspective. Soc. Behav. Personal. Int. J. 2019, 47, 1–12. [Google Scholar] [CrossRef]
- Hu, X.; Huang, Q.; Zhong, X.; Davison, R.M.; Zhao, D. The influence of peer characteristics and technical features of a social shopping website on a consumer’s purchase intention. Int. J. Inf. Manag. 2016, 36, 1218–1230. [Google Scholar] [CrossRef]
- Tien, D.H.; Rivas, A.A.A.; Liao, Y.-K. Examining the influence of customer-to-customer electronic word-of-mouth on purchase intention in social networking sites. Asia Pac. Manag. Rev. 2019, 24, 238–249. [Google Scholar] [CrossRef]
- Chaiken, S. Communicator physical attractiveness and persuasion. J. Personal. Soc. Psychol. 1979, 37, 1387. [Google Scholar] [CrossRef]
- Carlson, J.; Rahman, M.; Voola, R.; De Vries, N. Customer engagement behaviours in social media: Capturing innovation opportunities. J. Serv. Mark. 2018, 32, 83–94. [Google Scholar] [CrossRef]
- Kim, D.J.; Ferrin, D.L.; Rao, H.R. A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents. Decis. Support Syst. 2008, 44, 544–564. [Google Scholar] [CrossRef]
- Vila, N.; Kuster, I. Consumer feelings and behaviours towards well designed websites. Inf. Manag. 2011, 48, 166–177. [Google Scholar] [CrossRef]
- Saima; Khan, M.A. Effect of social media influencer marketing on consumers’ purchase intention and the mediating role of credibility. J. Promot. Manag. 2020, 27, 503–523. [Google Scholar] [CrossRef]
- Lin, J.C.-C.; Lu, H. Towards an understanding of the behavioural intention to use a web site. Int. J. Inf. Manag. 2000, 20, 197–208. [Google Scholar] [CrossRef]
- Liao, C.; Palvia, P.; Lin, H.-N. The roles of habit and web site quality in e-commerce. Int. J. Inf. Manag. 2006, 26, 469–483. [Google Scholar] [CrossRef]
- Wei, J.; Zhang, L.; Yang, R.; Song, M. A new perspective to promote sustainable low-carbon consumption: The influence of informational incentive and social influence. J. Environ. Manag. 2023, 327, 116848. [Google Scholar] [CrossRef] [PubMed]
- Cheung, M.Y.; Luo, C.; Sia, C.L.; Chen, H. Credibility of electronic word-of-mouth: Informational and normative determinants of on-line consumer recommendations. Int. J. Electron. Commer. 2009, 13, 9–38. [Google Scholar] [CrossRef]
- Wei, P.-S.; Lu, H.-P. An examination of the celebrity endorsements and online customer reviews influence female consumers’ shopping behavior. Comput. Hum. Behav. 2013, 29, 193–201. [Google Scholar] [CrossRef]
- Hennig-Thurau, T.; Walsh, G.; Walsh, G. Electronic word-of-mouth: Motives for and consequences of reading customer articulations on the Internet. Int. J. Electron. Commer. 2003, 8, 51–74. [Google Scholar] [CrossRef]
- Bickart, B.; Schindler, R.M. Internet forums as influential sources of consumer information. J. Interact. Mark. 2001, 15, 31–40. [Google Scholar] [CrossRef]
- Gu, B.; Park, J.; Konana, P. Research note—The impact of external word-of-mouth sources on retailer sales of high-involvement products. Inf. Syst. Res. 2012, 23, 182–196. [Google Scholar] [CrossRef]
- Huang, C.-C. Cognitive factors in predicting continued use of information systems with technology adoption models. Inf. Res. Int. Electron. J. 2017, 22, n2. [Google Scholar]
- Shen, X.L.; Zhang, K.Z.; Zhao, S.J. Herd behavior in consumers’ adoption of online reviews. J. Assoc. Inf. Sci. Technol. 2016, 67, 2754–2765. [Google Scholar] [CrossRef]
- Hu, Y.; Shyam Sundar, S. Effects of online health sources on credibility and behavioral intentions. Commun. Res. 2010, 37, 105–132. [Google Scholar] [CrossRef]
- Choi, K.; Wang, Y.; Sparks, B. Travel app users’ continued use intentions: It’sa matter of value and trust. J. Travel Tour. Mark. 2019, 36, 131–143. [Google Scholar] [CrossRef]
- Kim, D.J.; Ferrin, D.L.; Rao, H.R. Trust and satisfaction, two stepping stones for successful e-commerce relationships: A longitudinal exploration. Inf. Syst. Res. 2009, 20, 237–257. [Google Scholar] [CrossRef]
- Liu, C.; Marchewka, J.T.; Lu, J.; Yu, C.-S. Beyond concern—A privacy-trust-behavioral intention model of electronic commerce. Inf. Manag. 2005, 42, 289–304. [Google Scholar] [CrossRef]
- Lee, S.W.; Sung, H.J.; Jeon, H.M. Determinants of continuous intention on food delivery apps: Extending UTAUT2 with information quality. Sustainability 2019, 11, 3141. [Google Scholar] [CrossRef]
- Alzaza, N.S. Mobile Learning Services Acceptance Model among Malaysian Higher Education Students. Ph.D. Thesis, Universiti Utara Malaysia, Bukit Kayu Hitam, Malaysia, 2012. [Google Scholar]
- Chen, S.-C.; Liu, M.-L.; Lin, C.-P. Integrating technology readiness into the expectation–confirmation model: An empirical study of mobile services. Cyberpsychol. Behav. Soc. Netw. 2013, 16, 604–612. [Google Scholar] [CrossRef] [PubMed]
- Abubakar, A.M.; Ilkan, M. Impact of online WOM on destination trust and intention to travel: A medical tourism perspective. J. Destin. Mark. Manag. 2016, 5, 192–201. [Google Scholar] [CrossRef]
- Magno, F. The influence of cultural blogs on their readers’ cultural product choices. Int. J. Inf. Manag. 2017, 37, 142–149. [Google Scholar] [CrossRef]
- Lederman, R.; Fan, H.; Smith, S.; Chang, S. Who can you trust? Credibility assessment in online health forums. Health Policy Technol. 2014, 3, 13–25. [Google Scholar] [CrossRef]
- Nagy, J.T. Evaluation of online video usage and learning satisfaction: An extension of the technology acceptance model. Int. Rev. Res. Open Distrib. Learn. 2018, 19, 160–184. [Google Scholar] [CrossRef]
- Davis, F.D. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 1989, 13, 319–340. [Google Scholar] [CrossRef]
- Hair, J.F.; Sarstedt, M.; Ringle, C.M.; Mena, J.A. An assessment of the use of partial least squares structural equation modeling in marketing research. J. Acad. Mark. Sci. 2012, 40, 414–433. [Google Scholar] [CrossRef]
- Hair, J.F.; Ringle, C.M.; Sarstedt, M. PLS-SEM: Indeed a silver bullet. J. Mark. Theory Pract. 2011, 19, 139–152. [Google Scholar] [CrossRef]
- Hair, J.F., Jr.; Hult, G.T.M.; Ringle, C.M.; Sarstedt, M.; Danks, N.P.; Ray, S. Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R: A Workbook; Springer Nature: Berlin/Heidelberg, Germany, 2021. [Google Scholar]
- Hair Jr, J.F.; Sarstedt, M.; Hopkins, L.; Kuppelwieser, V.G. Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. Eur. Bus. Rev. 2014, 26, 106–121. [Google Scholar] [CrossRef]
- Henseler, J.; Ringle, C.M.; Sinkovics, R.R. The use of partial least squares path modeling in international marketing. In New Challenges to International Marketing; Emerald Group Publishing Limited: Bingley, UK, 2009; Volume 20, pp. 277–319. [Google Scholar]
- Fornell, C.; Larcker, D.F. Structural equation models with unobservable variables and measurement error: Algebra and statistics. J. Mark. Res. 1981, 18, 382–388. [Google Scholar] [CrossRef]
- Bonner, B.L.; Baumann, M.R.; Lehn, A.K.; Pierce, D.M.; Wheeler, E.C. Modeling collective choice: Decision-making on complex intellective tasks. Eur. J. Soc. Psychol. 2006, 36, 617–633. [Google Scholar] [CrossRef]
- McGinnies, E.; Ward, C.D. Better liked than right: Trustworthiness and expertise as factors in credibility. Personal. Soc. Psychol. Bull. 1980, 6, 467–472. [Google Scholar] [CrossRef]
- Bhattacherjee, A. Understanding information systems continuance: An expectation-confirmation model. MIS Q. 2001, 25, 351–370. [Google Scholar] [CrossRef]
Item | Content | Frequency | Percentage |
---|---|---|---|
Gender | Male | 127 | 34.60% |
Female | 240 | 65.40% | |
Age | Aged 18 and under | 27 | 7.36% |
19–35 | 158 | 43.05% | |
36–59 | 150 | 40.87% | |
Aged 60 and above | 32 | 8.72% | |
Education | High school degree or below | 98 | 26.70% |
College degree | 88 | 23.98% | |
Bachelor’s degree | 141 | 38.42% | |
Graduate degree | 40 | 10.90% |
Constructs | Item | Factor Loading | Cronbach’s α | Composite Reliability | AVE |
---|---|---|---|---|---|
Trustworthiness (TRU) | TRU1 | 0.952 | 0.960 | 0.971 | 0.894 |
TRU2 | 0.945 | ||||
TRU3 | 0.941 | ||||
TRU4 | 0.944 | ||||
Expertise (EXP) | EXP1 | 0.891 | 0.943 | 0.959 | 0.854 |
EXP2 | 0.949 | ||||
EXP3 | 0.943 | ||||
EXP4 | 0.911 | ||||
Attractiveness (ATT) | ATT1 | 0.937 | 0.926 | 0.947 | 0.819 |
ATT2 | 0.916 | ||||
ATT3 | 0.907 | ||||
ATT4 | 0.857 | ||||
Content Quality (CQ) | CQ1 | 0.932 | 0.923 | 0.946 | 0.814 |
CQ2 | 0.903 | ||||
CQ3 | 0.854 | ||||
CQ4 | 0.918 | ||||
Electronic Word-of-Mouth (eWOM) | eWOM1 | 0.862 | 0.931 | 0.948 | 0.784 |
eWOM2 | 0.928 | ||||
eWOM3 | 0.888 | ||||
eWOM4 | 0.845 | ||||
eWOM5 | 0.902 | ||||
Information Credibility (INC) | INC1 | 0.946 | 0.962 | 0.971 | 0.870 |
INC2 | 0.913 | ||||
INC3 | 0.925 | ||||
INC4 | 0.930 | ||||
INC5 | 0.948 | ||||
Perceived Usefulness (PU) | PU1 | 0.961 | 0.950 | 0.968 | 0.910 |
PU2 | 0.970 | ||||
PU3 | 0.930 | ||||
Exercise Intention (EXI) | EXI1 | 0.876 | 0.881 | 0.926 | 0.806 |
EXI2 | 0.916 | ||||
EXI3 | 0.902 |
ATT | CQ | EXI | EXP | INC | PU | TRU | eWOM | |
---|---|---|---|---|---|---|---|---|
ATT | 0.905 | |||||||
CQ | 0.883 | 0.902 | ||||||
EXI | 0.702 | 0.731 | 0.898 | |||||
EXP | 0.868 | 0.882 | 0.691 | 0.924 | ||||
INC | 0.838 | 0.884 | 0.714 | 0.831 | 0.933 | |||
PU | 0.794 | 0.844 | 0.735 | 0.769 | 0.862 | 0.954 | ||
TRU | 0.745 | 0.806 | 0.617 | 0.799 | 0.795 | 0.807 | 0.945 | |
eWOM | 0.758 | 0.794 | 0.674 | 0.747 | 0.813 | 0.791 | 0.680 | 0.885 |
Hypothesis | Relationship | Path Coefficients | T Statistics | p-Values | Result |
---|---|---|---|---|---|
H1a | TRU → INC | 0.181 | 4.048 | 0.000 | Supported |
H1b | TRU → PU | 0.353 | 6.039 | 0.000 | Supported |
H2a | EXP → INC | 0.041 | 0.654 | 0.513 | Not supported |
H2b | EXP → PU | −0.154 | 1.889 | 0.059 | Not supported |
H3a | ATT → INC | 0.152 | 2.264 | 0.024 | Supported |
H3b | ATT → PU | 0.155 | 2.075 | 0.038 | Supported |
H4a | CQ → INC | 0.367 | 4.119 | 0.000 | Supported |
H4b | CQ → PU | 0.334 | 3.578 | 0.000 | Supported |
H5a | eWOM → INC | 0.252 | 2.989 | 0.003 | Supported |
H5b | eWOM → PU | 0.284 | 4.041 | 0.000 | Supported |
H6 | INC → EXI | 0.313 | 3.209 | 0.001 | Supported |
H7 | PU → EXI | 0.465 | 4.766 | 0.000 | Supported |
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Yin, H.; Huang, X.; Zhou, G. An Empirical Investigation into the Impact of Social Media Fitness Videos on Users’ Exercise Intentions. Behav. Sci. 2024, 14, 157. https://doi.org/10.3390/bs14030157
Yin H, Huang X, Zhou G. An Empirical Investigation into the Impact of Social Media Fitness Videos on Users’ Exercise Intentions. Behavioral Sciences. 2024; 14(3):157. https://doi.org/10.3390/bs14030157
Chicago/Turabian StyleYin, He, Xin Huang, and Guangming Zhou. 2024. "An Empirical Investigation into the Impact of Social Media Fitness Videos on Users’ Exercise Intentions" Behavioral Sciences 14, no. 3: 157. https://doi.org/10.3390/bs14030157
APA StyleYin, H., Huang, X., & Zhou, G. (2024). An Empirical Investigation into the Impact of Social Media Fitness Videos on Users’ Exercise Intentions. Behavioral Sciences, 14(3), 157. https://doi.org/10.3390/bs14030157