Understanding Guilin Tourism Major Students Toward Financial Management Knowledge Courses In The Era Of Knowledge Payment

Zhang Jing

doi:10.61132/ijems.v1i3.40

Authors

Zhang Jing North Bangkok University

DOI:

https://doi.org/10.61132/ijems.v1i3.40

Keywords:

Tourism Major Students, Financial Management Knowledge Courses, Era of Knowledge Payment

Abstract

As internet technology advances, paying for knowledge has become a popular way of learning. This trend has increased the demand for financial management courses among non-financial majors, such as tourism. With Guilin's geographical advantage, many students in the area are pursuing non-financial tourism majors. Therefore, it is crucial to conduct extensive research on this group's willingness to purchase financial management courses, an essential and valuable topic. The knowledge payment market is developing rapidly. Understanding the purchasing intentions of non-financial tourism majors will help grasp market trends and provide market development directions for relevant institutions. The number of respondents for this study was 380. The results of this study show that students’ purchase intention on management courses for their career development would be impacted by performance expectation, effort expectation, and social impact.

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References

Ambalov, I. A. (2018). “A meta-analysis of its continuance: an evaluation of the expectation- confirmation model,” Telematics and Informatics, Vol. 35 No. 6, pp.1561-1571.

Anderson, J. Q. (2013). Individualization of higher education: How technological evolution can revolutionize opportunities for teaching and learning: Individualisation of higher education. International Social Science Journal, Vol 64(213-214), pp.305–316. doi:10.1111/issj.12046.

Anderson, J. Q. (2013). Individualization of higher education: How technological evolution can revolutionize opportunities for teaching and learning: Individualisation of higher education. International Social Science Journal, Vol 64(213-214), pp.305-316. doi:10.1111/issj.12046.

Bhagat, K. K., Wu, L. Y., & Chang, C. (2016). Development and validation of the perception of students toward online learning. Journal of Educational Technology and Society, Vol 19(1), pp.350–359.

Brown, E. A., Arendt, S. W., & Bosselman, R. H. (2014). Hospitality management graduates’ perceptions of career factor importance and career factor experience. International Journal of Hospitality Management, Vol 37, pp.58-67.

Chang, J. J., Lin, W. S., & Chen, H. R. (2019). How do attention level and cognitive style affect learning in a MOOC environment? Based on the perspective of brain-wave analysis. Computers in Human Behavior, Vol 100, pp.209–217.

DesJardins, S. L., & Toutkoushian, R. (2006). Are Students Really Rational? The Development of Rational Thought and its Application to Student Choice. Higher Education: Handbook of Theory and Research, pp.191-240.

Eccles, J. S., and Wigfield, A. (2020). From expectancy-value theory to situated expectancy- value theory: A developmental, social cognitive, and sociocultural perspective on motivation. Contemp. Educ. Psychol. Vol 61: 101859. doi: 10.1016/j.cedpsych.2020.101859.

Gheondea-Eladi, A. (2015). Understanding how people decide: Decision-making theories as mental representations. Journal of Community Positive Practices, Vol15(3), pp.3.

Hulleman, C. S., Barron, K. E., Kosovich, J. J., & Lazowski, R. A. (2016). Student motivation: Current theories, constructs, and interventions within an expectancy-value framework. In psychosocial skills and school systems in the 21st century. Cham: Springer, pp.241– 278. doi: 10.1007/978-3-319-28606-8_10.

Jones, B. D., Paretti, M. C., Hein, S. F., & Knott, T. W. (2010). Analyzing motivation constructs with first-year engineering students: Relationships among expectancies, values, achievement, and career plans. J. Eng. Educ. 99, 319–336. doi: 10.1002/j.2168- 9830.2010.tb01066.x.

Kadam, P. & Bhalerao, S. (2010). Sample Size Calculation. International Journal of Ayurveda Research, Vol 1(1), pp.55-57.

Li, M., Gu, R., Shang, X., & Wang, K. (2010). Critical Factors of Post Adoption Intention of Mobile Instant Messaging Service. J. Manag. Sci, Vol 23, pp.72–83.

Liao, C., Lin, H. N., Luo, M. M., & Chen, S. (2017). Factors influencing online shoppers repurchase intentions: The roles of satisfaction and regret. Information and Management, Vol 54(5), pp.651–668.

Lu, J., Yang, J., & Yu, C. S. (2013). Is social capital effective for online learning? Information and Management, Vol 50(7), pp.507–522.

Mao, C. M., Hovick, S. R. (2020). Adding Affordances and Communication Efficacy to the Technology Acceptance Model to Study the Messaging Features of Online Patient Portals among Young Adults. Health Commun, Vol 4, p.1–9.

Normann, U., Ellegaard, C., & Møller, M. M. (2017). Supplier perceptions of distributive justice in sustainable apparel sourcing. International Journal of Physical Distribution & Logistics Management, Vol 47(5), pp.368-386.

Qingfei, M., Shaobo, J., & Gang, Q. (2008). Mobile Commerce User Acceptance Study in China: A Revised UTAUT Model. Tsinghua Sci. Technol, Vol 13, pp.257–264.

Rosenzweig, E. Q., Wigfield, A., & Eccles, J. S. (2019). “Expectancy-value theory and its relevance for student motivation and learning,” in The Cambridge Handbook of Motivation and Learning, eds K. A. Renninger and S. E. Hidi (Cambridge: Cambridge University Press), pp.617–644. doi: 10.1017/9781316823279.026.

Ruth, R. D. (2012). “Conversation as a source of satisfaction and continuance in a question- and-answer site,” European Journal of Information Systems, Vol. 21 No. 4, pp. 427- 437.

Sair, S. A. & Danish R. Q. (2018). Effect of Performance Expectancy and Effort Expectancy on the Mobile Commerce Adoption Intention through Personal Innovativeness among Pakistani Consumers, Pakistan Journal of Commerce and Social Sciences, Vol. 12, No. 2, pp. 501–520.

Shi, X., Zheng, X., & Yang, F. (2020). Exploring payment behavior for live courses in social Q&A communities: An information foraging perspective. Information Processing and Management, Vol 57(4).

Shittu, A., Hannon, E., Kyriacou, J., Arnold, D., Kitz, M., Zhang, Z., Chan, C., & Kohli, S. R. (2020). Improving Care for Critical Care Patients by Strategic Alignment of Quality Goals with a Physician Financial Incentive Model. Qual. Manag. Health Care, Vol 30, pp.21–26.

Sweins, C., & Kalmi, P. (2008). Pay knowledge, pay satisfaction and employee commitment: Evidence from Finnish profit-sharing schemes. Hum. Res. Manag. J, Vol 18, pp.366– 385.

Tak, P., & Panwar, S. (2017). Using UTAUT 2 model to predict mobile app-based shopping: evidence from India. Journal of Indian Business Research, Vol 9(3), pp.248-264.

Tobon, S., & García-Madariaga J. (2021). Influencers vs. the power of the crowd: A research about the social influence on the digital era. Estudios Gerenciales, Vol 37(161), pp.601–609. https://doi.org/10.18046/j.estger.2021.161.4498.

Wang, Q., & Xue, M. (2022). The implications of expectancy-value theory of motivation in language education. Front Psychol, Vol 13, https://doi.org/10.3389/fpsyg.2022.992372.

Wang, X., Yu, C., & Wei, Y. (2012). Social media peer communication and impacts on purchase intentions: A consumer socialization framework. Journal of Interactive Marketing, Vol 26(4), pp.198–208.

Yadiati, W. & Bong, M. (2019). The role of information technology in E-Commerce, International Journal of Scientific and Technology Research, No. 8, pp. 173–176.

Zhang, C., Wang, X., & Wang, C. (2019). Research on Influencing Factors of Continuous Information Sharing Behavior of Usersin Network Communities. Inf. Doc. Serv, Vol 40, pp.53–62.

Zhang, C.; Wang, X.; Wang, C. Research on Influencing Factors of Continuous Information Sharing Behavior of Users in Network Communities. Inf. Doc. Serv. 2019, 40, 53–62.

Zhang, S., Wang, W., & Li, J. (2017). Research on the Influencing Factors of Users’ Online Knowledge Payment Behavior. Libr. Inf. Serv, Vol 61, pp.94–100.