Factors Influencing Viewing Behavior of Streaming Self-produced Movies Among Shanxi Province Chinese College Students

Main Article Content

Xiaoyu Wu
Eksiri Niyomsilp

Abstract

College students are the core movie consumption group. Based on the theory of planned behavior, movie-viewing preferences and behaviors of 430 college students in Shanxi Province were studied against the background of the rapid rise of original content movies made by streaming media platforms—streaming self-produced movies. Multiple regression analysis was carried out on the factors influencing college students’ movie-viewing behavior. A model was constructed applicable to the movie-viewing behavior relevant to streaming self-produced movies in college students in Shanxi Province. The main results showed that three movie-viewing behaviors of college students (paid viewing, first selection, and recommendation to others) were affected by eight factors to different degrees, namely, film traits, social environment, internet word-of-mouth, perceived cost, perceived usefulness, perceived quality, attitudes to enterprise image, attitudes to movie product. This paper is expected to provide an important reference for development trends and investment decisions adopted for streaming self-produced movies.

Downloads

Download data is not yet available.

Article Details

Section
Original Articles

References

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior & Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T

Ajzen, I., & Madden, T. J. (1986). Prediction of goal-directed behavior: Attitudes, intentions, and perceived behavioral control. Journal of Experimental Social Psychology, 22(5), 453–474. https://doi.org/10.1016/ 0022-1031(86)90045-4

Bigne‐Alcaniz, E., Ruiz‐Mafe, C., Aldas‐Manzano, J., & Sanz‐Blas, S. (2008). Influence of online shopping information dependency and innovativeness on internet shopping adoption. Online Information Review, 32(5), 648–667. https://doi.org/10.1108/14684520810914025

Blatt, M. (2019, January 20). How Netflix is changing the film industry. http://www.china.org.cn/opinion/2019-01/20/content_74385699.htm

Bray, J. P., Johns, N., & Kilburn, D. (2011). An exploratory study into the factors impeding ethical consumption. Journal of Business Ethics, 98(4), 597–608. https://doi.org/10.1007/S10551-010-0640-9

Burroughs, B. (2019). House of Netflix: Streaming media and digital lore. Popular Communication, 17(1), 1–17. https://doi.org/10.1080/15405702.2017.1343948

Chang, J. (2020). Streaming media and the future film industry: Aesthetics, industry, culture. Contemporary
Cinema, (7), 4–10. https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CJFD&dbname=CJFDLAST2020& filename=DDDY202007004&v=MjY1NzlQSVNuUGQ3RzRITkhNcUk5RllJUjhlWDFMdXhZUzdEaDFUM3FUcldNMUZyQ1VSN3FmYnVkbUZDcmdVYnI=

Cheng, J., Chen, Y., Dou, H., Liu, L., & Yang, L. (2019). Research on the Intention of ontinuous payment for college students’ video websites in Beijing based on TPB extension model. Research on Transmission Competence, 3(34), 264–266. https://kns.cnki.net/KXReader/Detail?TIMESTAMP=637375940557968750& DBCODE=CJFD&TABLEName=CJFDLAST2020&FileName=CBLY201934227&RESULT=1&SIGN=y697l7sS%2fFIjZQzjJ65RtMM9ALw%3d

Churchill, G. A. (1979). A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16(1), 64–73. https://doi.org/10.2307/3150876

Cui, N. N., & Tang, J. (2012). Research of Chinese movie box-office influencing factors based on regression analysis. Jiangsu Commercial Forum, 8, 35–39. https://doi.org/10.13395/j.cnki.issn.1009-0061.2012. 08.005

Dutta, S. (2012). Analyzing consumer intention to pay for online content: A systematic approach. Journal of Theoretical & Applied Information Technology, 38(1), 89–102. http://citeseerx.ist.psu.edu/viewdoc/ download;jsessionid=315F3EFAA094BB4B54F6721354212317?doi=10.1.1.299.9934&rep=rep1&type=pdf

Economic Daily. (2018, June 25). The global film industry is growing rapidly. https://www.imsilkroad.com/ news/p/100533.html

Evans, A., & Matthews, S. (2018, November 1). From screening to streaming: Film industry in transition. Executive Insights, 20(53), 1–5. https://www.lek.com/insights/ei/screening-streaming-film-industry-transition

Fan, X. (2016). Research on the motivation and behavior intention of superhero movie audiences—Take Marvel movies as an example [Master's thesis, Jinan University, China]. https://kns.cnki.net/kcms/detail/ detail.aspx?dbcode=CMFD&dbname=CMFD201702&filename=1016733770.nh&v=LCT57RJ7b%25mmd2BPunrI9HSEoaOLGPJrqscWsY17z6blXeHmMoExeDpzGw0RryGgfyZq4

Garlin, F. V., & McGuiggan, R. L. (2002). Sex, spies and celluloid: Movie content preference, choice, and involvement. Psychology & Marketing, 19(5), 427–445. https://doi.org/10.1002/MAR.10018

Huang, S., & Xu, B. (2019). College students’ movie-viewing behavior and its influencing factors. Knowledge Economy, 1, 139+141. https://doi.org/10.15880/j.cnki.zsjj.2019.01.078

Jenner, M. (2015). Binge-watching: Video-on-demand, quality TV and mainstreaming fandom. International Journal of Cultural Studies, 20(3), 127–136. https://doi.org/10.1177/1367877915606485

Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39(1), 31–36. https://doi.org/10.1007/ BF02291575

Kjus, Y. (2016). Musical exploration via streaming services: The Norwegian experience. Popular Communication, 14(3), 127–136. https://doi.org/10.1080/15405702.2016.1193183

Lee, K. J., & Chang, W. (2009). Bayesian belief network for box-office performance: A case study on Korean movies. Expert Systems with Applications, 36(1), 280–291. https://doi.org/10.1016/J.ESWA.2007.09.042

Li, Z., & Wang, L. (2016). Study on the motivation of college students' online movie ticket purchase behavior. Journal of News Research, 7(18), 72–73. https://kns.cnki.net/KXReader/Detail?TIMESTAMP= 637375991433906250&DBCODE=CJFD&TABLEName=CJFDLAST2016&FileName=XWDK201618043&RESULT=1&SIGN=pLvfu8WgRRws4lHkSk4DIv0sPsk%3d

Lu, X. (2019). A study on the cost of production in film project management: Taking small-budget films in China as an example. Open Journal of Social Sciences, 7(3), 75–88. https://doi.org/10.4236/jss.2019.73006

McKechnie, S. A., & Zhou, J. (2003). Product placement in movies: A comparison of Chinese and American consumers’ attitudes. International Journal of Advertising, 22(3), 349–374. https://doi.org/10.1080/ 02650487.2003.11072858

Nelson, R. A., & Glotfelty, R. (2012). Movie stars and box office revenues: An empirical analysis. Journal of Cultural Economics, 36(2), 141–166. https://doi.org/10.1007/S10824-012-9159-5

Quico, C. (2019). Television reshaped by big data: Impacts and implications for Netflix-like platforms in the age of dataism. International Journal of Film and Media Arts, 4(1), 48–55. https://doi.org/10.24140/ijfma.v4. n1.04

Rovinelli, R., & Hambleton, R. (1977). On the use of content specialists in the assessment of criterion-referenced test item validity. Tijdschrift Voor Onderwijsresearch, 2, 49–60. https://eric.ed.gov/?id= ED121845

Ru, Y., Li, B., Chai, J., & Liu, J. (2019). A movie box office prediction model based on deep learning. Journal of Communication University of China (Science and Technology), 26(1), 27–32. https://doi.org/10.16196/ j.cnki.issn.1673-4793.2019.01.005

Statista. (2019, October 16). Penetration rate of subscription video on demand (SVOD) services worldwide in the 1st quarter of 2019, by country. https://www.statista.com/statistics/813698/svod-reach-by-country/

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

Tvoao. (2019, March 26th). The motion picture association of america report: Global streaming video subscriptions surpassed cable TV for the first time in 2018. https://www.tvoao.com/a/197216.aspx

Wand, B. (1968). Television viewing and family choice differences. Public Opinion Quarterly, 32(1), 84–94. https://doi.org/10.1086/267581

Wang, J., Li, Z., & Zhao, Y. (2018). Influencing factors of Chinese movies in overseas streaming media transmission–Take Chinese movies shown on YouTube from 2015 to 2017 as an example. China Journalism and Communication Journal, 2, 85–103. https://kns.cnki.net/kcms/detail/detail.aspx?dbcode =CCJD&dbname=CCJDLAST2&filename=XWCJ201802007&v=dIuvlRwTL7PpD3dWdaq65lcHAKe XnQ2SPL kui8gUAoVI2H3O%25mmd2BlUzMH5HxaozGex3&UID=WEEvREcwSlJHSldTTEYzVTFPV2pUd0RFbU05TmZrUlQ4b3RVdWFaSEpCST0%3d%249A4hF_YAuvQ5obgVAqNKPCYcEjKensW4IQMovwHtwkF4VYPoHbKxJw!!&autoLogin=0
Xiao, R. (2017). The study on factors affecting customers' purchase intention of web fiction ip incubation film and television products based on the perspective of consumer perception [Master's thesis, JiLin University, China]. https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CMFD&dbname= CMFD201801&filename= 1017153179.nh&v=A4QQDw6%25mmd2BzffjQFuh4t6NF1h%25mmd2BDkzvgEJusMweacyfCQLdj25nxa6LPxFT093ur3Zn

Yuqi, J. (2018, April 12). Netflix was retired by Cannes, and the streaming media and traditional film industry officially declared war? https://www.huxiu.com/article/239679.html

Zhang, Y., Yu, X., Cheng, J., Chen, X., & Liu, T. (2017). Recreational behavior and intention of tourists to rural scenic spots based on TPB and TSR models. Scientia Geographica Sinica, 36(9), 1725–1741. http://www.dlyj.ac.cn/EN/10.11821/dlyj201709010