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http://dx.doi.org/10.13088/jiis.2022.28.3.001

A Dynamic Analysis of Digital Piracy, Ratings, and Online Buzz for Korean TV Dramas  

Kim, Dongyeon (Department of Business Administration, Catholic University of Korea)
Park, Kyuhong (Department of Business Administration, Inha University)
Bang, Youngsok (School of Business, Yonsei University)
Publication Information
Journal of Intelligence and Information Systems / v.28, no.3, 2022 , pp. 1-22 More about this Journal
Abstract
We investigate the dynamic relationships among digital piracy activities, TV ratings, and online buzz for Korean TV dramas using a panel vector autoregression model. Our main findings include 1) TV ratings are negatively affected by digital piracy activities but positively affected by google buzz, 2) digital piracy activities are negatively affected by TV ratings and social buzz, and 3) social buzz and google buzz are positively influenced by each other. While many empirical studies were conducted to reveal the effects of music or movie piracy, our understanding of drama piracy is limited. We provide empirical evidence of the dynamic relationships between drama piracy, TV ratings, and online buzz. Our findings show the presence of indirect piracy effects on TV ratings through online buzz. Further, we reveal that social buzz and google trends play different roles in promoting TV ratings and piracy activities. We discuss the implications of our findings for theory and practitioners.
Keywords
TV dramas; digital piracy; TV ratings; online buzz; panel vector autoregression model;
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1 Lu, S., Wang, X., & Bendle, N. (2020). Does piracy create online word of mouth? An empirical analysis in the movie industry. Management Science, 66(5), 2140-2162.   DOI
2 Luo, X., & Zhang, J. (2013). How do consumer buzz and traffic in social media marketing predict the value of the firm?. Journal of Management Information Systems, 30(2), 213-238.
3 Maddala, G. S., & Wu, S. (1999). A comparative study of unit root tests with panel data and a new simple test. Oxford Bulletin of Economics and Statistics, 61(S1), 631-652.   DOI
4 MUSO (2017). Game of Thrones season 7 opener pirated 91.74 million times. Available at: www.muso.com/magazine/game-of-thrones-season-7-opener-pirated-91-74-million-times
5 Penny, H. A. (1971). The effects of three levels of positive reinforcement on promptness behavior. School Applications of Learning Theory, 3(2), 13-18.
6 Philippas, D., Rjiba, H., Guesmi, K., & Goutte, S. (2019). Media attention and Bitcoin prices. Finance Research Letters, 30, 37-43.   DOI
7 Danaher, B., Dhanasobhon, S., Smith, M. D., & Telang, R. (2010). Converting pirates without cannibalizing purchasers: The impact of digital distribution on physical sales and internet piracy. Marketing Science, 29(6), 1138-1151.   DOI
8 Den Haan, W. J., Sumner, S. W., & Yamashiro, G. M. (2011). Bank loan components and the time varying effects of monetary policy shocks. Economica, 78(312), 593-617   DOI
9 Choi, B. (2018). Integrative Analysis on Digital Piracy: Focused on Attitude, Personal Norm, and Habit, The Journal of Society for e-Business Studies, 23(3), 85-109.   DOI
10 Feng, N., Feng, H., Li, D., & Li, M. (2020). Online media coverage, consumer engagement and movie sales: A PVAR approach. Decision Support Systems, 131, 113267.   DOI
11 Frino, A., Xu, C., & Zhou, Z. I. (2022). Are option traders more informed than Twitter users? A PVAR analysis. Journal of Futures Markets, 42, 1755-1771.   DOI
12 Godinho de Matos, M., Ferreira, P., & Smith, M. D. (2018). The effect of subscription video-on-demand on piracy: Evidence from a household-level randomized experiment. Management Science, 64(12), 5610-5630.   DOI
13 Holtz-Eakin, D., Newey, W., & Rosen, H. S. (1988). Estimating vector autoregressions with panel data. Econometrica, 56(6), 1371-1395.   DOI
14 Jeon, S. (2021). Increased piracy... Online content copyright protection becomes more important. Aju Business Daily, Available at: https://www.ajunews.com/view/20210120170939479
15 Koop, G., Pesaran, M.H., & Potter, S.M. (1996). Impulse response analysis in nonlinear multivariate models, Journal of Econometrics, 74(1), 119-147.   DOI
16 Korea Creative Content Agency (2021). Contents Industry 2021 Prospect Report. Available at: https://www.kocca.kr/kocca/bbs/view/B0000180/1843756.do?searchCnd=&searchWrd=&cateTp1=&cateTp2=&useAt=&menuNo=204164&categorys=0&subcate=0&cateCode=&type=&instNo=0&questionTp=&uf_Setting=&recovery=&option1=&option2=&year=&categoryCOM062=&categoryCOM063=&categoryCOM208=&categoryInst=&morePage=&delCode=0&qtp=&pageIndex=1
17 Kretschmer, T., & Peukert, C. (2020). Video killed the radio star? Online music videos and recorded music sales. Information Systems Research, 31(3), 776-800.   DOI
18 The Conversation (2019). Game of Thrones: for HBO, piracy is 'better than an Emmy' as it battles Netflix. Available at: theconversation.com/game-of-thrones-for-hbo-piracy-is-betterthan-an-emmy-as-it-battles-netflix-115384
19 Sottek, T. C. (2013). 'Game of Thrones' director David Petrarca shrugs off piracy, says it doesn't hurt the show. The Verge, Available at: www.theverge.com/2013/2/27/4035390/gameof-thrones-director-piracy
20 Smith, M. D., & Telang, R. (2009). Competing with free: The impact of movie broadcasts on DVD sales and Internet piracy. MIS Quarterly, 33(2), 321-338.   DOI
21 Transparency Market Research (2019). Digital content creation market. Available at: www.transparencymarketresearch.com/digital-content-creation-market.html
22 Yi, J., Lee, C., & Cha, K. (2015) An analysis of IT trends using Tweet data. Journal of Intelligence and Information Systems, 21(1), 143-159.   DOI
23 Zhang, L. (2018). Intellectual property strategy and the long tail: Evidence from the recorded music industry. Management Science, 64(1), 24-42.   DOI
24 Andrews, D. W., & Lu, B. (2001). Consistent model and moment selection procedures for GMM estimation with application to dynamic panel data models. Journal of Econometrics, 101(1), 123-164.   DOI
25 Barnichon, R., & Matthes, C. (2018). Functional approximation of impulse responses. Journal of Monetary Economics, 99, 41-55   DOI
26 Chae, J., & Son, J. Y. (2020). The Effect of Heuristic Cues on the Intention to Watch Contents in Searching Information on YouTube. Information Systems Review, 22(3), 119-142.   DOI
27 Chen, M. C., & Patel, K. (1998). House price dynamics and Granger causality: an analysis of Taipei new dwelling market. Journal of the Asian Real Estate Society, 1(1), 101-126
28 Cho, Y., Sohn, K., & Kwon, O. (2021) Comparison of Models for Stock Price Prediction Based on Keyword Search Volume According to the Social Acceptance of Artificial Intelligence. Journal of Intelligence and Information Systems, 27(1), 103-128.   DOI
29 Da, Z., Engelberg, J., & Gao, P. (2015). The sum of all FEARS investor sentiment and asset prices. The Review of Financial Studies, 28(1), 1-32.   DOI
30 Liu, M., & Lim, G. (2019) Word-of-Mouth Effect for Online Sales of K-Beauty Products: Centered on China SINA Weibo and Meipai. Journal of Intelligence and Information Systems, 25(1), 197-218.   DOI
31 Liu, Z. (2018). Quantifying the heterogeneous effects of piracy on the demand for movies, Working Paper.
32 Ma, L., Montgomery, A. L., Singh, P. V., & Smith, M. D. (2014). An empirical analysis of the impact of pre-release movie piracy on box office revenue. Information Systems Research, 25(3), 590-603.   DOI
33 Koschmann, A., & Bowman, D. (2017). Simultaneous estimation of legal and illegal supply and demand: the case of motion pictures. International Economic Journal, 31(4), 555-577.   DOI
34 Liebowitz, S. J. (2008). Testing file sharing's impact on music album sales in cities. Management Science, 54(4), 852-859.   DOI
35 Love, I., & Zicchino, L. (2006). Financial development and dynamic investment behavior: Evidence from panel VAR. The Quarterly Review of Economics and Finance, 46(2), 190-210.   DOI
36 Park, K, & Kim, D. (2020). Can TV ratings reflect hidden viewers regarding digital piracy? An analysis of TV ratings, online buzz, and digital piracy. The Journal of Internet Electronic Commerce Research, 20(2), 21-34.   DOI
37 Ray, S. (2014). Can buzz on Twitter predict TV ratings and viewers?: A study of US TV shows premiering in fall 2013 (Doctoral dissertation, Massachusetts Institute of Technology).
38 Tassi, P. (2014). 'Game of Thrones' sets piracy world record, but does HBO care?. Forbes, Available at: www.forbes.com/sites/insertcoin/2014/04/15/game-of-thrones-sets-piracy-worldrecord-but-does-hbo-care/?sh=2333b1df4196
39 Dewan, S., & Ramaprasad, J. (2014). Social media, traditional media, and music sales. MIS Quarterly, 38(1), 101-122   DOI
40 Xiong, G., & Bharadwaj, S. (2014). Prerelease buzz evolution patterns and new product performance. Marketing Science, 33(3), 401-421.   DOI
41 Geng, X., & Lee, Y. J. (2013). Competing with piracy: A multichannel sequential search approach. Journal of Management Information Systems, 30(2), 159-184.   DOI
42 Lee, J., & Park, C. (2019). The Effect of Online Word of Mouth on Movie Sales: Moderating Roles of Types of Social Media. Information Systems Review, 21(1), 29-50   DOI
43 Hill, R. C., Griffiths, W. E., & Lim, G. C. (2018). Principles of Econometrics. John Wiley & Sons.
44 Kim, D., Park, K., & Bang, Y. (2022). The effect of TV drama piracy: An analysis of digital piracy users, internet buzz, and TV drama viewership. Information & Management, 59(2), 103599.   DOI
45 Hennig-Thurau, T., Henning, V., & Sattler, H. (2007). Consumer file sharing of motion pictures. Journal of Marketing, 71(4), 1-18.   DOI