Understanding Users’ Preference to Engage in YouTubers

Wen-Yu Tsao


The YouTubers are the new vocations to make money. People like to access the videos to relax or learn from the special YouTuber. Despite the growth and commercial potential of virtual worlds, relatively little is known about what users’ motivations to favor specific YouTubers. This paper offered and empirically tested a conceptual model to fill this gap. Given the system characteristics (mobility, reachability, compatibility, convenience) and YouTuber specific characteristics (escapism and post popularity) integrated extrinsic and intrinsic motivation as their preference determinants. Using PROCESS on a survey of 349 users of YouTube. The results confirmed the role of extrinsic and intrinsic motivation as preference determinants and showed the two system and two YouTuber specific characteristics as motivational basis. Implications for research and practice are discussed.

Full Text:



Amabile, T. M. (1993). Motivational synergy: Toward new conceptualizations of intrinsic and extrinsic motivation in the workplace. Human resource management review, 3(3), 185-201. https://doi.org/10.1016/1053-4822(93)90012-S

Arvidsson, N. (2014). Consumer attitudes on mobile payment services – results from a proof of concept test. Int. J. Bank Mark., 32(2), 150-170. https://doi.org/10.1108/IJBM-05-2013-0048

Asraar, A. K. A. (2015). Utilitarian and hedonic motives of university students in their online shopping-A gender based examination. Global Management Review, 9(4), 75-91.

Au, Y. A., & Kauffman, R. J. (2008). The economics of mobile payments: Understanding stakeholder issues for an emerging financial technology application. Electronic Commerce Research and Applications, 7(2), 141-164. https://doi.org/10.1016/j.elerap.2006.12.004

Bhattacherjee, A., & Premkumar, G. (2004). Understanding changes in belief and attitude toward information technology usage: A theoretical model and longitudinal test. MIS Quarterly, 28(2), 229-254. https://doi.org/10.2307/25148634

Bhattacherjee, A., & Sanford, C. (2006). Influence processes for information technology acceptance: An elaboration likelihood model. MIS Quarterly, 30(4), 805-825. https://doi.org/10.2307/25148755

Chang, Y. T., Yu, H., & Lu, H. P. (2015). Persuasive messages, popularity cohesion, and message diffusion in social media marketing. Journal of Business Research, 68(4), 777-782. https://doi.org/10.1016/j.jbusres.2014.11.027

Correa, T., Hinsley, A. W., & De Zuniga, H. G. (2010). Who interacts on the Web? The intersection of users’ personality and social media use. Computers in Human Behavior, 26(2), 247-253. https://doi.org/10.1016/j.chb.2009.09.003

Cronin, J. J., Brady, M. K., & Hult, G. T. M. (2000). Assessing the effects of quality, value, and customer satisfaction on consumer behavioral intentions in service environments. Journal of retailing, 76(2), 193-218. https://doi.org/10.1016/S0022-4359(00)00028-2

Daskapan, S., Van den Berg, J., & Ali-Eldin, A. (2010). Towards a trustworthy short-range mobile payment system. Int. J. Inf. Technol. Manag., 9(3) 317-336. https://doi.org/10.1504/IJITM.2010.030947

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003. https://doi.org/10.1287/mnsc.35.8.982

De Vriesa, L., Gensler, S., & Leeflang, P. S. H. (2012). Popularity of brand posts on brand fan pages: An investigation of the effects of social media marketing. Journal of Interactive Marketing, 26(2), 83-91. https://doi.org/10.1016/j.intmar.2012.01.003

Deci, E. L., & Ryan, R. M. (1985). The general causality orientations scale: Self-determination in personality. Journal of research in personality, 19(2), 109-134. https://doi.org/10.1016/0092-6566(85)90023-6

Dong, X., Chang, Y., Wang, Y., & Yan, J. (2017). Understanding usage of Internet of Things (IOT) systems in China: Cognitive experience and affect experience as moderator. Information Technology & People, 30(1), 117-138. https://doi.org/10.1108/ITP-11-2015-0272

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservables and measurement error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.1177/002224378101800104

Gilbert, R. L., Murphy, N. A., & Avalos, M. C. (2011). Realism, idealization, and potential negative impact of 3D virtual relationships. Computers in Human Behavior, 27(5), 2039-2046. https://doi.org/10.1016/j.chb.2011.05.011

Grant, M. M. (2004). Learning to teach with the web: Factors influencing teacher education faculty. The Internet and higher education, 7(4), 329-341. https://doi.org/10.1016/j.iheduc.2004.09.005

Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis. Englewood Cliffs, NJ: Prentice Hall International.

Hayes, A. F. (2018). Partial, conditional, and moderated mediation: Quantification, inference, and interpretation. Communication Monographs, 85(1), 4-40. https://doi.org/10.1080/03637751.2017.1352100

Hayes, A. F., & Preacher, K. J. (2014). Statistical mediation analysis with a multicategorical independent variable. British Journal of Mathematical and Statistical Psychology, 67(3), 451-470. https://doi.org/10.1111/bmsp.12028

Henning, B., & Vorderer, P. (2001). Psychological escapism: Predicting the amount of television viewing by need for cognition. Journal of Communication, 51(1), 100-120. https://doi.org/10.1111/j.1460-2466.2001.tb02874.x

Hirschman, E. C. (1983). Aesthetics, ideologies and the limits of the marketing concept. The journal of marketing, 47(3), 45-55. https://doi.org/10.1177/002224298304700306

Hossain, M. A., Hossain, M. S., & Jahan, N. (2018). Predicting continuance usage intention of mobile payment: An experimental study of bangladeshi customers. Asian Economic and Financial Review, 8(4), 487-498.

Hsu, C. L., & Lin, J. C. C. (2008). Acceptance of blog usage: The roles of technology acceptance, social influence and knowledge sharing motivation. Information & management, 45(1), 65-74. https://doi.org/10.1016/j.im.2007.11.001

Huizinga, J. (1955). Homo ludens: A study of the play element in culture, The Beacon Press, Boston, MA.

Johnson, D. H. (1980). The comparison of usage and availability measurements for evaluating resource preference. Ecology, 61(1), 65-71. https://doi.org/10.2307/1937156

Joiner, T. A. (2001). The influence of national culture and organizational culture alignment on job stress and performance: evidence from Greece. Journal of Managerial Psychology, 16(3), 229-242. https://doi.org/10.1108/02683940110385776

Jung, Y., & Kang, H. (2010). User goals in social virtual worlds: A means-end chain approach. Computers in Human Behavior, 26(2), 218-225. https://doi.org/10.1016/j.chb.2009.10.002

Kim, C., Mirusmonov, M., & Lee, I. (2010). An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behavior, 26(3), 310-322. https://doi.org/10.1016/j.chb.2009.10.013

Kim, H. Y., & Kim, Y. K. (2005). Escapism, consumer lock in, attitude, and purchase: An illustration from an online shopping context. Journal of Shopping Center Research, 12(2), 103-115.

Kim, S. S., & Son, J. Y. (2009). Out of dedication or constraint? A dual model of postadoption phenomena and its empirical test in the content of online services. MIS Quarterly, 33(1), 49-70. https://doi.org/10.2307/20650278

Li, H., Liu, Y., & Heikkilä, J. (2014). Understanding the factors driving NFC-enabled mobile payment adoption: An empirical investigation. In PACIS (p. 231).

Lim, A. S. (2007). Inter-consortia battles in mobile payments standardization. Electronic Commerce Research and Applications, 2(2), 15-23.

Lin, J., Lu, Y., Wang, B., & Wei, K. K. (2011). The role of inter-channel trust transfer in establishing mobile commerce trust. Electronic Commerce Research and Applications, 10(6), 615-625. https://doi.org/10.1016/j.elerap.2011.07.008

Mallat, N. (2007). Exploring consumer adoption of mobile payments–A qualitative study. The Journal of Strategic Information Systems, 16(4), 413-432. https://doi.org/10.1016/j.jsis.2007.08.001

Mathwick, C., Malhotra, N., & Rigdon, E. (2001). Experiential value: conceptualization, measurement and application in the catalog and Internet shopping environment. Journal of retailing, 77(1), 39-56. https://doi.org/10.1016/S0022-4359(00)00045-2

McRoberts, L. M., Paczkowski, L. W., & Rondeau, D. E. (2016). U.S. Patent No. 9,282,898. Washington, DC: U.S. Patent and Trademark Office.

Nunnally J. C., & Bernstein, I. H. (1994). Psychometric Theory, McGraw-Hill, New York, NY.

Overby, J. W., & Lee, E. J. (2006). The effects of utilitarian and hedonic online shopping value on consumer preference and intentions. Journal of Business research, 59(10), 1160-1166. https://doi.org/10.1016/j.jbusres.2006.03.008

Park, D. H., & Kim, S. (2008). The effects of consumer knowledge on message processing of electronic word-of-mouth via online consumer reviews. Electronic Commerce Research and Applications, 7(4), 399-410. https://doi.org/10.1016/j.elerap.2007.12.001

Park, E., Sung, J., & Cho, K. (2015). Reading experiences influencing the acceptance of e-book devices. The Electronic Library, 33(1), 120-135. https://doi.org/10.1108/EL-05-2012-0045

Perea y Monsuwé, T., Dellaert, B. G., & De Ruyter, K. (2004). What drives consumers to shop online? A literature review. International journal of service industry management, 15(1), 102-121. https://doi.org/10.1108/09564230410523358

Preacher, K. J., & Hayes, A. F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior research methods, 36(4), 717-731. https://doi.org/10.3758/BF03206553

Ramos-Serrano, M., & Herrero-Diz, P. (2016). Unboxing and brands: YouTubers phenomenon through the case study of Evantubehd. Revista Prisma Social, 90-120.

Ryan, R. M., & Deci, E. L. (2000a). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68-78. https://doi.org/10.1037/0003-066X.55.1.68

Ryan, R. M., & Deci, E. L. (2000b). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary Educational Psychology, 25(1), 54-67. https://doi.org/10.1006/ceps.1999.1020

Saade, R., & Bahli, B. (2005). The impact of cognitive absorption on perceived usefulness and perceived ease of use in on-line learning: An extension of the technology acceptance model. Information and Management, 42(2), 317–327. https://doi.org/10.1016/j.im.2003.12.013

Sethi, V., & King, W. R. (1994). Development of measures to assess the extent to which an information technology application provides competitive advantage. Management science, 40(12), 1601-1627. https://doi.org/10.1287/mnsc.40.12.1601

Siklander, P., Kangas, M., Ruhalahti, S., & Korva, S. (2017). Exploring triggers for arousing interest in the online learning. In Proceedings of the 11th Annual International Technology, Education and Development Conference, INTED2017 (pp. 9081-9089). https://doi.org/10.21125/inted.2017.2150

Sinclair, R. C., Moore, S. E., Mark, M. M., Soldat, A. S., & Lavis, C. A. (2010). Incidental moods, source likeability, and persuasion: Liking motivates message elaboration in happy people. Cognition and Emotion, 24(6), 940-961. https://doi.org/10.1080/02699930903000206

Smith, P., & Sankaranarayanan, S. (2012). Smart agent based mobile shopping and secured payment. Int. J. Emerg. Trends Technol. Comput. Sci., 1(3), 240-254.

Teo, A. C., Tan, W. H., Keng-Boon, O., Teck-Soon, H., King-Tak, Y. (2015). The effects of convenience and speed in m-payment. Ind. Manag. Data Syst., 115(2), 311-331. https://doi.org/10.1108/IMDS-08-2014-0231

Trakulmaykee, N., SuhaimiBaharudin, A., Low, R. Q., & Arshad, M. R. M. (2013). Investigating determinants of tourist intention and associations of perceived usefulness, ease of use and mobility in the context of mobile tourism guide. International journal of accounting and business management, 1(1), 123-130.

Vallerand, R. J. (1997). Toward a hierarchical model of intrinsic and extrinsic motivation. In Advances in experimental social psychology (Vol. 29, pp. 271-360). Academic Press. https://doi.org/10.1016/S0065-2601(08)60019-2

Venkatesh, V. (1999). Creation of favorable user perceptions: exploring the role of intrinsic motivation. MIS quarterly, 23(2), 239-260. https://doi.org/10.2307/249753

Verhagen, T., Feldberg, F., van den Hooff, B., Meents, S., & Merikivi, J. (2012). Understanding users’ motivations to engage in virtual worlds: A multipurpose model and empirical testing. Computers in Human Behavior, 28(2), 484-495. https://doi.org/10.1016/j.chb.2011.10.020

Wang, S. T. (2013). The influence of visual packaging design on perceived food product quality, value, and brand preference. International Journal of Retail & Distribution Management, 41(10), 805-816. https://doi.org/10.1108/IJRDM-12-2012-0113

Westenberg, W. (2016). The influence of YouTubers on teenagers. Ensenada: University of TWENTE. https://essay.utwente.nl/71094/1/Westenberg_MA_BMS.pdf.

Wong A., & Dean, A. (2009). Enhancing value for Chinese shoppers: The contribution of store and customer characteristics. Journal of Retailing and Consumer Services, 16(2), 123-134. https://doi.org/10.1016/j.jretconser.2008.11.004

Xu, Z., Turel, O., & Yuan, Y. (2012). Online game addiction among adolescents: motivation and prevention factors. European Journal of Information Systems, 21(3), 321-340. https://doi.org/10.1057/ejis.2011.56

Yang, S., Lu, Y., Gupta, S., Caso, Y., and Zhang, R. (2012). Mobile payment services adoption across time: an empirical study of the effects of behavioral beliefs, social influences, and personal traits. Computer in Human Behavior, 28(1), 129-142. https://doi.org/10.1016/j.chb.2011.08.019

Yen, Y. S., & Wu, F. S. (2016). Predicting the adoption of mobile financial services: The impacts of perceived mobility and personal habit. Computers in Human Behavior, 65, 31-42. https://doi.org/10.1016/j.chb.2016.08.017

Ylitalo, J. (2009). Controlling for common method variance with partial least squares path modeling. http://salserver.org.aalto.fi/vanhat_sivut/Opinnot/Mat-2.4108/pdf-files/eyli09b.pdf.

Zhang, X., de Pablos, P. O., Wang, X., Wang, W., Sun, Y., & She, J. (2014). Understanding the users’ continuous adoption of 3D social virtual world in China: A comparative case study. Computers in Human Behavior, 35, 578-585. https://doi.org/10.1016/j.chb.2014.02.034

Zhou, T. (2014). Understanding the determ inants of mobile payment continuance usage. Ind. Manag. Data Syst., 114(6), 936-948. https://doi.org/10.1108/IMDS-02-2014-0068

DOI: https://doi.org/10.5296/ijhrs.v9i1.14357

To make sure that you can receive messages from us, please add the 'macrothink.org' domain to your e-mail 'safe list'. If you do not receive e-mail in your 'inbox', check your 'bulk mail' or 'junk mail' folders.

Copyright © Macrothink Institute   ISSN 2162-3058

'Macrothink Institute' is a trademark of Macrothink Institute, Inc.