Information Systems Review (경영정보학연구)

The Korea Society of Management Information Systems (한국경영정보학회)
권호 표지
DOI QR코드

DOI QR Code

An Empirical Study on the Effects of Regulation in Online Gaming Industry via Vector Autoregression Model

벡터자기회귀(VAR) 모형을 활용한 온라인 게임 규제 영향에 대한 실증적 연구: 웹보드 게임을 중심으로

  • Moonkyoung Jang (College of Business Administration, Seoul National University) ;
  • Seongmin Jeon (College of Business, Gachon University) ;
  • Byungjoon Yoo (Graduate School of Business, Seoul National University)
  • 장문경 (서울대학교 경영대학) ;
  • 전성민 (가천대학교 경영대학) ;
  • 유병준 (서울대학교 경영전문대학원)
  • Received : 2017.02.02
  • Accepted : 2017.03.28
  • Published : 2017.03.31
Download PDF
⟨ Previous Next ⟩

Abstract

This study empirically examines the effects of regulation on online gaming. Going beyond ad hoc heuristic approaches on individual behavior, we investigate the effects of regulation on dynamic changes of games or service providers. In particular, we propose three theoretical perspectives: social influence to investigate the regulation effect, the role of prior experience to determine the difference in the regulation effect size through users' prior experience, and network externalities to discover the difference in the regulation effect size according to the number of users on an online gaming platform. We use the vector autoregression methodology to model patterns of the co-movement of online games and to forecast game usage. We find that online gamers are heterogeneous. Therefore, policy makers should make suitable regulations for each heterogeneous group to effectively avoid generating gaming addicts without interrupting the economic growth of the online gaming industry.

한국의 게임시장은 전 세계 시장의 약 29%의 시장점유율을 차지할 정도로 급성장하였다. 특히, 온라인게임의 수출 규모는 24억 USD를 달성할 정도로 국가경제에서 큰 비중을 차지하고 있다. 이렇게 게임 산업이 급성장하면서 게임 산업에 대한 국가적 차원의 정책과 규제에 대해 여러 논의가 이루어지고 있다. 특히, 웹보드 게임에 대해 정부는 여러 주무 부처를 통한 셧다운제, 행정처분, 게임산업진흥법 시행령 등 다양한 규제정책을 시행하고 있는 실정이다. 이러한 배경에서 본 연구는 2012년 11월에 이루어진 웹보드 규제정책의 영향을 분석하기 위해 2010년 12월부터 2014년 11월까지 약 4년여 간의 게임 트릭스 시계열 자료를 단위근 검정, 벡터자기회귀(VAR, Vector Auto-Regression) 분석, 그랜저 인과관계 검정을 수행하였다. 이를 통해 웹보드 규제 정책 시행 전후의 웹보드 게임서비스 간의 충격 파급효과와 예측 이용시간 변화를 알아보았다. 분석 결과를 바탕으로 웹보드 규제 정책이 실질적으로 정부가 의도한 결과대로 나타냈는지 알아보고, 나아가 웹보드 게임 산업을 보다 건강하게 발전시키기 위한 전략을 제시하고자 한다.

Keywords

Acknowledgement

Byungjoon Yoo is thankful for the support by the Institute of Management Research at Seoul National University.

References

  1. Auer, M. and M. D. Griffiths, "Voluntary limit setting and player choice in most intense online gamblers: An empirical study of gambling behaviour", Journal of Gambling Studies, Vol.29, No.4, 2013, pp. 647-660.  https://doi.org/10.1007/s10899-012-9332-y
  2. Awokuse, T. O. and D. A. Bessler, "Vector autoregressions, policy analysis, and directed acyclic graphs: An application to the US economy", Journal of Applied Economics, Vol.6, No.1, 2003, pp. 1-24.  https://doi.org/10.1080/15140326.2003.12040583
  3. Bagliano, F. C. and C. A. Favero, "Measuring monetary policy with VAR models: An evaluation", European Economic Review, Vol.42, No.6, 1998, pp. 1069-1112.  https://doi.org/10.1016/S0014-2921(98)00005-1
  4. Bernanke, B. S., J. Boivin, and P. Eliasz. "Measuring the effects of monetary policy: A factor-augmented vector autoregressive (FAVAR) approach", Quarterly Journal of Economics, Vol.120, No.1, 2005, pp. 387-422.  https://doi.org/10.1162/qjec.2005.120.1.387
  5. Business Korea, "Online game addiction bill: Undergoing rapid legislation amid blowing-up opposition", 2013, Available at http://www.businesskorea.co.kr/article/2717/online-gaming-addiction-bill-undergoing-rapid-legislation-amid-blowing-opposition. 
  6. Castaneda, J. A., F. Munoz-Leiva, and T. Luque, "Web acceptance model (WAM): Moderating effects of user experience", Information & Management, Vol.44, No.4, 2007, pp. 384-396.  https://doi.org/10.1016/j.im.2007.02.003
  7. Chandra, S. R. and H. Al-Deek, "Predictions of freeway traffic speeds and volumes using vector autoregressive models", Journal of Intelligent Transportation Systems, Vol.13, No.2, 2009, pp. 53-72.  https://doi.org/10.1080/15472450902858368
  8. Chen, P.-Y. and L. M. Hitt, "Measuring switching costs and the determinants of customer retention in Internet-enabled businesses: A study of the online brokerage industry", Information Systems Research, Vol.13, No.3, 2002, pp. 255-274.  https://doi.org/10.1287/isre.13.3.255.78
  9. Cooley, T. F. and M. Dwyer, "Business cycle analysis without much theory: A look at structural VARs", Journal of Econometrics, Vol.83, No.1, 1998, pp. 57-88.  https://doi.org/10.1016/S0304-4076(97)00065-1
  10. Cotte, J. and K. A. Latour, "Blackjack in the kitchen: Understanding online versus casino gambling", Journal of Consumer Research, Vol.35, No.5, 2009, pp. 742-758.  https://doi.org/10.1086/592945
  11. Davis, F. D., "Perceived usefulness, perceived ease of use, and user acceptance of information technology", MIS Quarterly, Vol.13, No.3, 1989, pp. 319-340.  https://doi.org/10.2307/249008
  12. Deng, Z., Y. Lu, K. K. Wei, and J. Zhang, "Understanding customer satisfaction and loyalty: An empirical study of mobile instant messages in China", International Journal of Information Management, Vol.30, No.4, 2010, pp. 289-300.  https://doi.org/10.1016/j.ijinfomgt.2009.10.001
  13. Eadington, W. R., "The future of online gambling in the United States and elsewhere", Journal of Public Policy and Marketing, Vol.23, No.2, 2004, pp. 214-219.  https://doi.org/10.1509/jppm.23.2.214.51399
  14. Enders, W., Applied Econometric Time Series, John Wiley & Sons, 2008. 
  15. Etnews, "Need to change the regulation policy on online gambling (in Korean)", 2015, Available at http://www.etnews.com/20150213000164. 
  16. Friesendorf, C., "Squeezing the balloon?", Crime, Law and Social Change, Vol.44, No.1, 2005, pp. 35-78.  https://doi.org/10.1007/s10611-006-9005-9
  17. Gainsbury, S. M., N. Suhonen, and J. Saastamoinen, "Chasing losses in online poker and casino games: Characteristics and game play of Internet gamblers at risk of disordered gambling", Psychiatry Research, Vol.217, No.3, 2014, pp. 220-225.  https://doi.org/10.1016/j.psychres.2014.03.033
  18. Gainsbury, S., J. Parke, and N. Suhonen, "Consumer attitudes towards Internet gambling: Perceptions of responsible gambling policies, consumer protection, and regulation of online gambling sites", Computers in Human Behavior, Vol.29, No.1, 2013, pp. 235-245.  https://doi.org/10.1016/j.chb.2012.08.010
  19. Gainsbury, S., R. Wood, A. Russell, N. Hing, and A. Blaszczynski, "A digital revolution: Comparison of demographic profiles, attitudes and gambling behavior of Internet and non-Internet gamblers", Computers in Human Behavior, Vol.28, No.4, 2012, pp. 1388-1398.  https://doi.org/10.1016/j.chb.2012.02.024
  20. Granger, C. W., "Investigating causal relations by econometric models and cross-spectral methods", Econometrica, Vol.37, No.3, 1969, pp. 424-438.  https://doi.org/10.2307/1912791
  21. Griffiths, M., "Internet gambling: Issues, concerns, and recommendations", CyberPsychology & Behavior, Vol.6, No.6, 2003, pp. 557-568.  https://doi.org/10.1089/109493103322725333
  22. Grohman, C., "Reconsidering regulation: A historical view of the legality of Internet poker and discussion of the Internet gambling ban of 2006", Journal of Legal Technology Risk Management, Vol.1, No.1, 2006, pp. 34-74. 
  23. Gupta, S. and C. F. Mela, "What is a free customer worth? Armchair calculations of nonpaying customers' value can lead to flawed strategies", Harvard Business Review, Vol.86, No.11, 2008, pp. 102-109. 
  24. Hamilton, J. D., Time Series Analysis, Princeton University Press Princeton, 1994. 
  25. Han, K. H. and T. U. Kim, "Factors influencing users' intension to play mobile games: A Combination of game-contents traits and mobile handset's capabilities into the technology acceptance model", Information Systems Review, Vol.7, No.2, 2005, pp. 41-59. 
  26. Heckman, J. J., "Causal parameters and policy analysis in Economics: A twentieth century retrospective", Quarterly Journal of Economics, Vol.115, No.1, 2000, pp. 45-97.  https://doi.org/10.1162/003355300554674
  27. Hsu, C.-L. and H.-P. Lu, "Why do people play on-line games? An extended TAM with social influences and flow experience", Information & Management, Vol.41, No.7, 2004, pp. 853-868.  https://doi.org/10.1016/j.im.2003.08.014
  28. Huhh, J.-S., "Culture and business of PC bangs in Korea", Games and Culture, Vol.3, No.1, 2008, pp. 26-37.  https://doi.org/10.1177/1555412007309525
  29. Karahanna, E., D. W. Straub, and N. L. Chervany, "Information technology adoption across time: A cross-sectional comparison of pre-adoption and post-adoption beliefs", MIS Quarterly, Vol.23, No.2, 1999, pp. 183-213.  https://doi.org/10.2307/249751
  30. Katz, M. L. and C. Shapiro, "Network externalities, competition, and compatibility", The American Economic Review, Vol.75, No.3, 1985, pp. 424-440. 
  31. Kim, B., M. Choi, and I. Han, "User behaviors toward mobile data services: The role of perceived fee and prior experience", Expert Systems with Applications, Vol.36, No.4, 2009, pp. 8528-8536.  https://doi.org/10.1016/j.eswa.2008.10.063
  32. Kim, E. and B. Lee, "An economic analysis of customer selection and leveraging strategies in a market where network externalities exist", Decision Support Systems, Vol.44, No.1, 2007, pp. 124-134.  https://doi.org/10.1016/j.dss.2007.03.006
  33. Kim, S. K. and S. Y. Lee, "'The causal relationship between ICT growth and employment in Korea", Information Systems Review, Vol.16, No.2, 2014, pp. 77-95.  https://doi.org/10.14329/isr.2014.16.2.077
  34. Kim, S. S. and J. Y. Son "Out of dedication or constraint? A dual model of post-adoption phenomena and its empirical test in the context of online services", Management Information Systems Quarterly, Vol.33, No.1, 2009, pp. 49-70.  https://doi.org/10.2307/20650278
  35. Klemperer, P., "Markets with consumer switching costs", The Quarterly Journal of Economics, Vol.102, No.2, 1987, pp. 375-394.  https://doi.org/10.2307/1885068
  36. Korea Creative Content Agency, "2013 White paper on Korean games: Guide to Korean games industry and culture", 2013, Available at https://www.kocca.kr/knowledge/publication/indu/__icsFiles/afieldfile/2013/11/19/UM3mpLQqzHbm.pdf. 
  37. Lin, C.-P. and A. Bhattacherjee, "Elucidating individual intention to use interactive information technologies: The role of network externalities", International Journal of Electronic Commerce, Vol.13, No.1, 2008, pp. 85-108.  https://doi.org/10.2753/JEC1086-4415130103
  38. Lin, K. and H. Lu, "Why people use social networking sites: An empirical study integrating network externalities and motivation theory", Computers in Human Behavior, Vol.27, No.3, 2011, pp. 1152-1161.  https://doi.org/10.1016/j.chb.2010.12.009
  39. Ma, X., S. H. Kim, and S. S. Kim, "Online gambling behavior: The impacts of cumulative outcomes, recent outcomes, and prior use", Information Systems Research, Vol.25, No.3, 2014, pp. 511-527.  https://doi.org/10.1287/isre.2014.0517
  40. Ministry of Culture, Sports and Tourism, "Draft notice of web-board game regulation policy", 2012, Available at http://www.mcst.go.kr/web/s_data/ordinance/legislation/legislationView.jsp?pSeq=1063&pMenuCD=0405030000&pCurrentPage=1&pType=&pSearchType=01&pSearchWord=%EA%B2%8C%EC%9E%84. 
  41. Monaghan, S., "Responsible gambling strategies for internet gambling: The theoretical and empirical base of using pop-up messages to encourage self-awareness", Computers in Human Behavior, Vol.25, No.1, 2009, pp. 202-207.  https://doi.org/10.1016/j.chb.2008.08.008
  42. Mora, F. O., "Victims of the balloon effect: Drug trafficking and US policy in Brazil and the Southern Cone of Latin America", The Journal of Social, Political, and Economic Studies, Vol.21, No.2, 1996, p. 115. 
  43. Online Poker, "Types of poker", 2011, Available at http://www.onlinepoker10.com/types-of-poker-games. 
  44. Ray, S., S. S. Kim, and J. G. Morris, "Research note-online users' switching costs: Their nature and formation", Information Systems Research, Vol.23, No.1, 2012, pp. 197-213.  https://doi.org/10.1287/isre.1100.0340
  45. Siemens, J. C. and S. W. Kopp, "The influence of online gambling environments on self-control", Journal of Public Policy & Marketing, Vol.30, No.2, 2011, pp. 279-293.  https://doi.org/10.1509/jppm.30.2.279
  46. Sieroty, C., Panel says critical mass matters for online poker, Las Vegas Business Press, 2011. 
  47. Sims, C. A., "Are forecasting models usable for policy analysis?", Federal Reserve Bank of Minneapolis Quarterly Review, Vol.10, No.1, 1986, pp. 2-16.  https://doi.org/10.21034/qr.1011
  48. Sledgianowski, D. and S. Kulviwat, "Using social network sites: The effects of playfulness, critical mass and trust in a hedonic context", The Journal of Computer Information Systems, Vol.49, No.4, 2009, p. 74. 
  49. Stewart, D. O. and L. Gray, "Online gambling five years after UIGEA", Washington, DC: American Gaming Association, 2011, Available at https://www.americangaming.org/sites/default/files/research_files/final_online_gambling_white_paper_5-18-11.pdf. 
  50. Stock, J. H. and M. W. Watson, "Vector autoregressions", Journal of Economic Perspectives, Vol.15, No.4, 2001, pp. 101-115.  https://doi.org/10.1257/jep.15.4.101
  51. Taylor, S. and P. Todd, "Assessing IT usage: The role of prior experience", MIS Quarterly, Vol.19, No.4, 1995, pp. 561-570.  https://doi.org/10.2307/249633
  52. Teaching poker, "Types of poker", 2002, Available at http://teachingpoker.com/Types.html. 
  53. Van der Heijden, H., "User acceptance of hedonic information systems", MIS Quarterly, Vol.28, No.4, 2004, pp. 695-704.  https://doi.org/10.2307/25148660
  54. Venkatesh, V., M. G. Morris, G. B. Davis, and F. D. Davis, "User acceptance of information technology: Toward a unified view", MIS Quarterly, Vol.27, No.3, 2003, pp. 425-478.  https://doi.org/10.2307/30036540
  55. Watson, S., P. Liddell Jr, R. S. Moore, and W. D. Eshee Jr., "The legalization of internet gambling: A consumer protection perspective", Journal of Public Policy & Marketing, Vol.23, No.2, 2004, pp. 209-213.  https://doi.org/10.1509/jppm.23.2.209.51401
  56. Yang, J. and E. S. Mai, "Experiential goods with network externalities effects: An empirical study of online rating system", Journal of Business Research, Vol.63, No.9, 2010, pp. 1050-1057.  https://doi.org/10.1016/j.jbusres.2009.04.029
  57. Yi, S. Y., M. Y. Kim, S. D. Han, and J. H. Ahn, "Market success factors of mobile games: Differences by genres and changes over time", Information Systems Review, Vol.10, No.3, 2008, pp. 21-38. 
  58. Yoon, V. Y., R. E. Hostler, Z. Guo, and T. Guimaraes, "Assessing the moderating effect of consumer product knowledge and online shopping experience on using recommendation agents for customer loyalty", Decision Support Systems, Vol.55, No.4, 2013, pp. 883-893.  https://doi.org/10.1016/j.dss.2012.12.024
  59. Yu, J., I. Ha, M. Choi, and J. Rho, "Extending the TAM for a t-commerce", Information & Management, Vol.42, No.7, 2005, pp. 965-976. https://doi.org/10.1016/j.im.2004.11.001