题名

Internet Celebrity Economy: Exploring the Value of Viewers' Comment Features and Live Streamers' Marketing Strategies in Forecasting Revenue

并列篇名

網紅經濟:檢驗觀眾留言特質和直播主行銷策略對營收之預測價值

DOI

10.6226/NTUMR.202204_32(1).0003

作者

林郁翔(Yu-Hsiang Lin);任立中(Li-Chung Jen)

关键词

word-of-mouth ; discrete emotion theory ; live streamer's behavior and characteristics ; gift-sending ; Hierarchical Bayesian model ; 口碑 ; 分立情緒理論 ; 直播主行為特質 ; 送禮 ; 層級貝氏模型

期刊名称

臺大管理論叢

卷期/出版年月

32卷1期(2022 / 04 / 01)

页次

93 - 125

内容语文

英文

中文摘要

Few past studies have tackled the relationship between marketing strategies and revenue forecasts of live streamers, not to mention the influence of streamer heterogeneity. This study applies the Hierarchical Bayesian (HB) model to examine the predictive effects of viewers' comments and streamer' behaviors on viewers' gift-sending behavior in live streaming while considering the effect of streamer heterogeneity. In particular, we empirically analyze 38,183 samples of time data from 10 food live-stream samples. We find that the effects of viewers' comment features and streamers' marketing strategies on viewers' gift-sending behavior are mainly influenced by the cross-level effect of streamers' heterogeneities. These results reveal that existing live-streaming studies might have overlooked the impact of streamers' heterogeneities, offering only biased conclusions. Finally, the model proposed in this study has good predictive accuracy for live streamer revenue.

英文摘要

過去有關直播主的行銷策略與營收預測之研究十分匱乏,且忽略考慮直播主異質性之影響。本研究應用層級貝氏模型,檢驗在考慮直播主異質性下,觀眾的留言特質和直播主行銷策略對觀眾送禮行為之預測價值。本研究針對10部美食直播共38,183筆時間資料進行分析,發現留言特質和直播主行銷策略對觀眾送禮行為之效果主要受到直播主異質性的跨層次影響。此顯示過去忽略直播主異質性影響的研究結論可能有偏誤。最後,本研究提出的模型對直播主營收有很好的預測力。

主题分类 基礎與應用科學 > 資訊科學
基礎與應用科學 > 統計
社會科學 > 經濟學
社會科學 > 財金及會計學
社會科學 > 管理學
参考文献
  1. 任立中, L. C.,陳靜怡, C. I.(2007)。顧客價值遷移路徑分析:馬可夫鏈模型。臺大管理論叢,17(2),133-158。
    連結:
  2. 林婷鈴, T. L.,陳靜怡, C. I.,任立中, L. C.(2007)。解析自有品牌策略與績效關係的迷思:層級貝氏迴歸模式之運用。臺大管理論叢,18(1),117-150。
    連結:
  3. 倪家珍, J. J.,利怡萱, Y. H.,林孟彥, T. M. Y.(2021)。廉航服務品質與顧客滿意度:評論參與的調節效果。臺大管理論叢,31(1),1-34。
    連結:
  4. Allenby, G. M.,Jen, L.,Leone, R. P.(1996).Economic trends and being trendy: The influence of consumer confidence on retail fashion sales.Journal of Business & Economic Statistics,14(1),103-111.
  5. Allenby, G. M., Rossi, P. E., and McCulloch, R. E. 2005. Hierarchical bayes models: A practitioners guide. Social Science Research Network. https://faculty.washington.edu/bajari/iosp07/rossi1.pdf. Accessed Aug. 15, 2020.
  6. Appel, G.,Grewal, L.,Hadi, R.,Stephen, A. T.(2020).The future of social media in marketing.Journal of the Academy of Marketing Science,48(1),79-95.
  7. Bae, S.,Lee, T.(2011).Gender differences in consumers' perception of online consumer reviews.Electronic Commerce Research,11(2),201-214.
  8. Bagozzi, R. P.,Gopinath, M.,Nyer, P. U.(1999).The role of emotions in marketing.Journal of the Academy of Marketing Science,27(2),184-206.
  9. Bearne, S. 2017. Meet the millennials who are making a living from livestreaming. The Guardian. https://www.theguardian.com/money/2017/oct/07/millennials-making-a-living-from-livestreaming. Accessed Jan. 12, 2020.
  10. Bharadwaj, N.,Ballings, M.,Naik, P. A.,Moore, M.,Arat, M. M.(2022).A new livestream retail analytics framework to assess the sales impact of emotional displays.Journal of Marketing,86(1),27-47.
  11. Chang, J. H.,Zhu, Y. Q.,Wang, S. H.,Li, Y. J.(2018).Would you change your mind? An empirical study of social impact theory on Facebook.Telematics and Informatics,35(1),282-292.
  12. Chen, M. Y.,Teng, C. I.(2013).A comprehensive model of the effects of online store image on purchase intention in an e-commerce environment.Electronic Commerce Research,13(1),1-23.
  13. Chiang, J.,Chib, S.,Narasimhan, C.(1999).Markov Chain Monte Carol and models of consideration set and parameter heterogeneity.Journal of Econometrics,89,223-248.
  14. Chintagunta, P. K.,Gopinath, S.,Venkataraman, S.(2010).The effects of online user reviews on movie box office performance: Accounting for sequential rollout and aggregation across local markets.Marketing Science,29(5),944-957.
  15. Chung, J.(2011).Investigating the roles of online buzz for new product diffusion and its cross-country dynamics.Journal of Business Research,64(11),1183-1189.
  16. Coblentz, K. E.,Rosenblatt, A. E.,Novak, M.(2017).The application of Bayesian hierarchical models to quantify individual diet specialization.Ecology,98(6),1535-1547.
  17. Dellarocas, C.,Zhang, X. M.,Awad, N. F.(2007).Exploring the value of online product reviews in forecasting sales: The case of motion pictures.Journal of Interactive Marketing,21(4),23-45.
  18. Duan, W.,Gu, B.,Whinston, A. B.(2008).The dynamics of online word-of-mouth and product sales─An empirical investigation of the movie industry.Journal of Retailing,84(2),233-242.
  19. Fortune Business Insights. 2021. Video streaming market share to touch usd 932.29 billion by 2028; video streaming market size 2021 to 2028. GlobeNewswire. https://www.globenewswire.com/news-release/2021/12/15/2352238/0/en/Video-Streaming-Market-Share-to-Touch-USD-932-29-Billion-by-2028-Video-Streaming-Market-Size-2021-to-2028.html
  20. Godes, D.,Mayzlin, D.(2004).Using online conversations to study word-of-mouth communication.Marketing Science,23(4),545-560.
  21. Haugh, M. 2017. MCMC and Bayesian modeling, IEOR E4703: Monte-carlo simulation. Columbia University. http://www.columbia.edu/~mh2078/MachineLearningORFE/MCMC_Bayes.pdf. Accessed Jun. 1, 2020.
  22. Hennig-Thurau, T.,Gwinner, K. P.,Walsh, G.,Gremler, D. D.(2004).Electronic word-of-mouth via consumer-opinion platforms: What motivates consumers to articulate themselves on the internet?.Journal of Interactive Marketing,18(1),38-52.
  23. Hu, M.,Zhang, M.,Wang, Y.(2017).Why do audiences choose to keep watching on live video streaming platforms? An explanation of dual identification framework.Computers in Human Behavior,75,594-606.
  24. Huang, X.,Liu, J. W.(2016).Research on the controllability of social financing scale-based on the perspective of “Origin Theory”.Research in Financial Economics,1,26-36.
  25. James, G.,Witten, D.,Hastie, T.,Tibshirani, R.(2013).An Introduction to Statistical Learning: With Applications in R.New York, NY:Springer Science and Business Media.
  26. Lee, J.,Cho, Y.,Lee, J. D.,Lee, C. Y.(2006).Forecasting future demand for large-screen television sets using conjoint analysis with diffusion model.Technological Forecasting & Social Change,73(4),362-376.
  27. Lerner, J. S.,Keltner, D.(2000).Beyond valence: Toward a model of emotion-specific influences on judgement and choice.Cognition and Emotion,14(4),473-493.
  28. Li, J. 2019. Tmcn: A text mining toolkit for Chinese. The Comprehensive R Archive Network. https://cran.r-project.org/web/packages/tmcn/index.html. Accessed Aug. 21, 2021.
  29. Lin, Y.,Yao, D.,Chen, X.(2021).Happiness begets money: Emotion and engagement in live streaming.Journal of Marketing Research,58(3),417-438.
  30. Liu, Y.(2006).Word of mouth for movies: Its dynamics and impact on box office revenue.Journal of Marketing,70(3),74-89.
  31. Lynch, S. M.(2007).Introduction to Applied Bayesian Statistics and Estimation for Social Scientists.New York, NY:Springer.
  32. Miss Game. 2019. Observation of live streaming data from 2018 to 2019, analyzing the internal reasons for Douyu’s leading data. https://kknews.cc/zh-tw/tech/o54jk3m.html. Accessed Jan, 22, 2022.
  33. Moon, S.,Bergey, P. K.,Iacobucci, D.(2010).Dynamic effects among movie ratings, movie revenues, and viewer satisfaction.Journal of Marketing,74(1),108-121.
  34. Mudambi, S. M.,Schuff, D.(2010).What makes a helpful online review? A study of customer reviews on amazon.com.MIS Quarterly,34(1),185-200.
  35. Phonthanukitithaworn, C.,Sellitto, C.(2017).Facebook as a second screen: An influence on sport consumer satisfaction and behavioral intention.Telematics and Informatics,34(8),1477-1487.
  36. Ramírez-Hassan, A.,Montoya-Blandón, S.(2020).Forecasting from others’experience: Bayesian estimation of the generalized Bass model.International Journal of Forecasting,36(2),442-465.
  37. Rossi, P. E.,Gilula, Z.,Allenby, G. M.(2001).Overcoming scale usage heterogeneity: A Bayesian hierarchical approach.Journal of the American Statistical Association,96(453),20-31.
  38. Shmueli, G.(2010).To explain or to predict?.Statistical Science,25(3),289-310.
  39. Shmueli, G.,Koppius, O. R.(2011).Predictive analytics in information systems research.MIS Quarterly,35(3),553-572.
  40. Singleton, J. P.,Mclean, E. R.,Altman, E. N.(1988).Measuring information systems performance: Experience with the management by results system at Security Pacific Bank.MIS Quarterly,12(2),325-337.
  41. Sjöblom, M.,Hamari, J.(2017).Why do people watch others play video games? An empirical study on the motivations of Twitch users.Computers in Human Behavior,75,985-996.
  42. Tan, Y. S. 2019. Is Douyu weak?. Commercial Times. https://ctee.com.tw/bookstore/world-news/130701.html. Accessed Jan, 21, 2022.
  43. Tang, M.,Zhu, J.(2019).Research of O2O website based consumer purchase decision-making model.Journal of Industrial and Production Engineering,36(6),371-384.
  44. Teixeira, T.,Wedel, M.,Pieters, R.(2012).Emotion-induced engagement in internet video advertisements.Journal of Marketing Research,49(2),144-159.
  45. Turney, P. D.,Littman, M. L.(2003).Measuring praise and criticism: Inference of semantic orientation from association.ACM Transactions on Information Systems,21(4),315-346.
  46. Ullah, R.,Amblee, N.,Kim, W.,Lee, H.(2016).From valence to emotions: Exploring the distribution of emotions in online product reviews.Decision Support Systems,81,41-53.
  47. Van den Bulte, C.,Joshi, Y. V.(2007).New product diffusion with influentials and imitators.Marketing Science,26(3),400-421.
  48. Vraga, E. K.,Edgerly, S.,Bode, L.,Carr, D. J.,Bard, M.,Johnson, C. N.,Kim, Y. M.,Shah, D. V.(2012).The correspondent, the comic, and the combatant: The consequences of host style in political talk shows.Journalism & Mass Communication Quarterly,89(1),5-22.
  49. Wan, J.,Lu, Y.,Wang, B.,Zhao, L.(2017).How attachment influences users’willingness to donate to content creators in social media: A socio-technical systems perspective.Information & Management,54(7),837-850.
  50. Wang, Y.,Yu, C.(2017).Social interaction-based consumer decision-making model in social commerce: The role of word of mouth and observational learning.International Journal of Information Management,37(3),179-189.
  51. Wohn, D. Y.,Freeman, G.(2020).Live streaming, playing, and money spending behaviors in Esports.Games and Culture,15(1),73-88.
  52. Xu, K. 2017. What is “internet celebrity economy” in China. Target China. https://targetchina.com.au/article/internet-celebrity/. Accessed Dec. 15, 2018.
  53. Yin, D.,Bond, S. D.,Zhang, H.(2014).Anxious or angry? Effects of discrete emotions on the perceived helpfulness of online reviews.MIS Quarterly,38(2),539-560.
  54. You, Y.,Vadakkepatt, G. G.,Joshi, A. M.(2015).A meta-analysis of electronic word-of-mouth elasticity.Journal of Marketing,79(2),19-39.
  55. Yu, E.,Jung, C.,Kim, H.,Jung, J.(2018).Impact of viewer engagement on gift-giving in live video streaming.Telematics and Informatics,35(5),1450-1460.
  56. Zhang, X.,Xiang, Y.,Hao, L.(2019).Virtual gifting on China’s live streaming platforms: Hijacking the online gift economy.Chinese Journal of Communication,12(3),340-355.
  57. Zhou, J.,Zhou, J.,Ding, Y.,Wang, H.(2019).The magic of danmaku: A social interaction perspective of gift sending on live streaming platforms.Electronic Commerce Research and Applications,34,Article 100815.
  58. Li, J. B. 2020. The live streaming e-commerce market scale will reach 900 billion RMB, accelerating the “live stream economy”. People’s Daily Online-People’s Daily Overseas Edition. http://media.people.com.cn/BIG5/n1/2020/0316/c40606-31632864.html(李嘉寶,2020,直播電商市場規模將達9000億「直播經濟」加速走來,人民網—人民日報海外版。http://media.people.com.cn/BIG5/n1/2020/0316/c40606-31632864.html)
  59. 黃俊堯, C. Y.,柳秉佑, P. Y.(2016)。消費者線上口碑與評論研究:國內外相關文獻回顧與討論。臺大管理論叢,26(3),215-256。
  60. Information Café. 2022. Counting the top streamers in the Douyu food area. https://inf.news/zh-hant/game/5a6240e8dd02913c2f3d0e0e9f5d4ee6.html. Accessed Jan. 21, 2022.(資訊咖,2022,細數鬥魚美食區的頂流主播,https://inf.news/zh-hant/game/5a6240e8dd02913c2f3d0e0e9f5d4ee6.html, 搜尋日期:2022 年 1 月 21 日。)
被引用次数
  1. 林郁翔(2023)。棒球直播環境的社群動態和體驗對社群情感氛圍之形塑與衍生價值。觀光休閒學報,29(2),197-231。
  2. (2024)。電玩直播主之粉絲滿意度與黏著度關鍵影響因素之研究。管理資訊計算,13(1),1-19。