Provision Model Choices of Online Video Content under Social Influence

Abstract

Abstract: We make an analysis about the mode choices of online video content under social influence. The equilibrium solution of the video platform is calculated under three situations, that is pay-per-view model, free-to-watch model and hybrid model. Our analysis shows that:when a video has a less social influence, its platform prefers the pay-per-view model. When a video has a great social influence, its platform prefers the hybrid model. When a video has a moderate social influence and a smaller consumer utility discount coefficient, free-to-watch model will become the optimal strategy of its platform. The price of the video has no connection with social influence in the pay-per-view model, so does the advertising in the free-to-watch model. In the hybrid model, both the price of the video and the advertising are positively related to the social influence. In addition, the consumer surplus under the three situations is also related to the consumer utility discount coefficient and social influence.

Key words: online video platform, content provision model, social influence, video pricing

Wang Wenyi, Guo Qiang, Shi Chunlai. Provision Model Choices of Online Video Content under Social Influence[J]. Management Review, 2021, 33(1): 164-176.

References

[1] 中国互联网络信息中心. 第40次中国互联网络发展状况统计报告[R]. 北京:国家互联网信息办公室, 2017
[2] 朱宁. 网络视频平台的供应链金融服务研究[J]. 图书情报工作, 2015,59(S1):256-260
[3] 艾瑞咨询. 2016年中国移动付费视频用户白皮书[R]. 上海:艾瑞咨询, 2017
[4] 李振鹏,唐锡晋. 外生变量和非正社会影响推动群体观点极化[J]. 管理科学学报, 2013,16(3):73-81
[5] Venkatesh V., Morris M. G., Davis G. B., et al. User Acceptance of Information Technology:Toward a Unified View[J]. Mis Quarterly, 2003,27(3):425-478
[6] Asch S. E. Social Psychology[M]. Englewood Cliffs, New Jersey:Prentice-Hall, 1952
[7] Sherif M. The Psychology of Social Norms[J]. American Psychological Association, 1936,42(3):420-421
[8] Hu M., Milner J., Wu J. H. Liking and Following and the Newsvendor:Operations and Marketing Policies Under Social Influence[J]. Management Science, 2016,62(3):867-879
[9] Carare O. The Impact of Bestseller Rank on Demand:Evidence from the App Market[J]. International Economic Review, 2012,53(3):717-742
[10] 侯建荣,赵丽. 社会认同与个性追求对消费者选择的联合影响研究[J]. 中国管理科学, 2014,22(S1):148-153
[11] Hong S. J., Thong J. Y. L., Moon J. Y., et al. Understanding the Behavior of Mobile Data Services Consumers[J]. Information Systems Frontiers, 2008,10(4):431-445
[12] Bapna R., Umyarov A. Do Your Online Friends Make You Pay? A Randomized Field Experiment on Peer Influence in Online Social Networks[J]. Management Science, 2015,61(8):1902-1920
[13] Yang H. C., Wang Y. Social Sharing of Online Videos:Examining American Consumers' Video Sharing Attitudes, Intent, and Behavior[J]. Psychology & Marketing, 2015,32(9):907-919
[14] Moretti E. Social Learning and Peer Effects in Consumption:Evidence from Movie Sales[J]. Review of Economic Studies, 2011,78(1):356-393
[15] Susarla A., Oh J. H., Tan Y. Social Networks and the Diffusion of User-Generated Content:Evidence from YouTube[J]. Information Systems Research, 2012,23(1):23-41
[16] Zhang K., Theodoros E., Padmanabhan V., et al. Content Contributor Management and Network Effects in a UGC Environment[J]. Marketing Science, 2012,31(3):433-477
[17] Zhang K., Miklos S. Differentiation with User-Generated Content[J]. Management Science, 2015,61(4):898-914
[18] Godes D. E., Ofek M. S. Content vs. Advertising:The Impact of Competition on Media Firm Strategy[J]. Marketing Science, 2009,28(1):20-35
[19] Balasubramanian S., Bhattacharya S., Krishnan V. V. Pricing Information Goods:A Strategic Analysis of the Selling and Pay-per-Use Mechanisms[J]. Marketing Science, 2015,34(2):218-234
[20] Chen Y., Xie J. Online Consumer Review:Word-of-Mouth as a New Element of Marketing Communication Mix[J]. Management Science, 2008,54(3):477-491
[21] Paulo B. G., Lin M. F., Yeung C. A. "Popularity Effect" in User-Generated Content:Evidence from Online Product Reviews[J]. Information Systems Research, 2014,25(2):222-238
[22] Bruce I. C., Li J., Stephen A. S. Millennial-Style Learning:Search Intensity, Decision Making, and Information Sharing[J]. Management Science, 2018,64(7):3313-3330
[23] 龚诗阳,李倩,余承锬. 在线社交对消费者需求的影响研究——基于网络视频产业的实证分析[J]. 中国软科学, 2017,(6):39-48
[24] Toubia O., Stephen A. T. Intrinsic vs. Image-Related Utility in Social Media:Why do People Contribute Content to Twitter?[J]. Marketing Science, 2013,32(3):368-392
[25] 李子庆,谭德庆. 网络视频运营商广告定价模式的选择[J]. 统计与决策, 2017,(2):54-57
[26] 谭德庆,李子庆. 网络视频内容提供模式选择、价格及嵌入广告量研究[J]. 管理评论, 2017,29(4):91-97
[27] Kumar A., Tan Y. R. The Demand Effects of Joint Product Advertising in Online Videos[J]. Management Science, 2015,61(8):1921-1937
[28] 易成,周密. 用户控制权对视频广告效果的影响[J]. 中国管理科学, 2017,25(2):139-146
[29] 黄健,何坚,吴迪. 视频站点版权竞价博弈的建模和分析[J]. 系统仿真学报, 2013,25(12):2801-2805
[30] Cai H., Chen Y., Fang H. Observational Learning:Evidence from a Randomized Natural Field Experiment[J]. American Economic Review, 2009,99(3):864-882
[31] Salganik M. J., Dodds P. S., Watts D. J. Experimental Study of Inequality and Unpredictability in an Artificial Cultural Market[J]. Science, 2006,311(5762):854-856
[32] 胥莉,陈宏民. 具有网络外部性特征的企业定价策略研究[J]. 管理科学学报, 2006,9(6):23-30
[33] 倪得兵,唐小我. 网络外部性、柔性与市场进入决策[J]. 管理科学学报, 2006,9(1):1-7