Information Systems Review (경영정보학연구)

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

DOI QR Code

The Effect of Marketing Mix Factors on Sales: Comparison of Superstars and Long Tails in the Film Industry

마케팅믹스 요소가 매출액에 미치는 영향: 영화산업에서 슈퍼스타와 롱테일의 비교

  • Jung-Won Lee (Graduate School of Information and Telecommunications, Konkuk University) ;
  • Choel Park (College of Global Business, Korea University)
  • 이중원 (건국대학교 정보통신대학원) ;
  • 박철 (고려대학교 융합경영학부)
  • Received : 2021.07.31
  • Accepted : 2022.03.26
  • Published : 2022.05.31
Download PDF
⟨ Previous Next ⟩

Abstract

Researchers are making contradictory claims through the concept of superstars and long tails about how the development of IT technology affects demand distribution. Unlike previous studies that focused on changes in demand from a macro point of view, this study explored whether the relationship between a company's marketing activities and consumer response differs depending on the product location (i.e., superstar vs. long tail) from a micro point of view. Based on the marketing mix framework, hypotheses were developed based on the relevant literature. In the case of empirical analysis, 2,835 daily data from 63 Korean films were tested using the quantile regression method. As a result of the analysis, it was found that the influence of marketing mix factors on sales varies depending on the location of the product. Specifically, the appeal breadth of the film and the effect of owned media are enhanced in superstar products, and the effect of acquisition media in long-tail products is enhanced and the negative effects of competition are mitigated. Unlike previous studies that focused on macroscopic changes in demand distribution, this study suggested marketing activities suitable for practitioners through microscopic analysis.

연구자들은 IT 기술의 발전이 수요분포에 어떠한 영향을 미치는지 슈퍼스타와 롱테일 개념을 통해 상반된 주장을 하고 있다(Brynjolfsson et al., 2010). 본 연구는 거시적 관점의 수요변화에 주목한 선행연구와 달리, 미시적 관점에서 기업의 마케팅 활동과 소비자 반응 간의 관계가 제품의 위치(i.e., 슈퍼스타 vs. 롱테일)에 따라 차이가 있는지 탐색하였다. 마케팅믹스 프레임워크를 기반으로 영화 마케팅 문헌에서 제시된 마케팅믹스 요소에 대한 가설을 개발하고, 영화산업을 대상으로 한국의 63개 영화의 45일 데이터 2,835개를 분위회귀분석 방법으로 검증하였다. 분석결과, 마케팅믹스 요소가 매출액에 미치는 영향은 제품의 위치에 따라 차이가 있다는 점을 발견하였다. 구체적으로 영화의 소구 폭과 소유 미디어의 효과는 슈퍼스타 제품에서 강화되며, 롱테일 제품은 획득 미디어의 효과를 강화하고 경쟁의 부정적 효과를 완화하는 것으로 나타났다. 본 연구는 거시적 수요분포 변화에 집중해온 선행연구와 달리, 미시적 측면의 분석을 통해 실무자에게 적합한 영화 마케팅 전략을 제안하였다.

Keywords

References

  1. 센이, 박철, "SNS(Social Network Site)를 통한 구전효과에 영향을 미치는 요인: 중국 웨이보(微博)를 중심으로", 국제지역연구, 제38권, 제1호, 2015, pp. 131-156.
  2. 이중원, 박철, "영화산업에서 심리적 각성이 온라인 구전성과에 미치는 영향", 서비스마케팅저널, 제12권, 제2호, 2019a, pp. 31-43. https://doi.org/10.22824/SMA.12.2.201912.31
  3. 이중원, 박철, "온라인 구전의 방향성과 분산이 영화매출에 미치는 영향 경쟁영화 온라인구전 특성의 조절효과를 중심으로", 경영학연구, 제48권, 제2호, 2019c, pp. 341-360. https://doi.org/10.17287/kmr.2019.48.2.341
  4. 이중원, 박철, "온라인 구전이 영화매출에 미치는 영향: 소유미디어와 획득미디어의 조절 효과를 중심으로", Information Systems Review, 제21권, 제2호, 2019b, pp. 29-50. https://doi.org/10.14329/isr.2019.21.2.029
  5. 이중원, 박철, "온라인 리뷰 특성이 영화 매출액에 미치는 영향: 한국과 미국의 비교", 경영학연구, 제49권, 재6호, 2020, pp. 1575-1594. https://doi.org/10.17287/kmr.2020.49.6.1575
  6. Ameri, M., E. Honka, and Y. Xie, "Word of mouth, observed adoptions, and anime-watching decisions: The role of the personal vs. the community network", Marketing Science, Vol.38, No.4, 2019, pp. 567-583. https://doi.org/10.1287/mksc.2019.1155
  7. Anderson, C., The long tail: Why the future of business is selling less of more, Hachette Books, 2006.
  8. Arabie, P., L. Hubert, and G. De Soete, Clustering and classification, World Scientific, 1996.
  9. Babic Rosario, A., F. Sotgiu, K. De Valck, and T. H. Bijmolt, "The effect of electronic word of mouth on sales: A meta-analytic review of platform, product, and metric factors", Journal of Marketing Research, Vol.53, No.3, 2016, pp. 297-318. https://doi.org/10.1509/jmr.14.0380
  10. Bordley, R., "Determining the appropriate depth and breadth of a firm's product portfolio", Journal of Marketing Research, Vol.40, No.1, 2003, pp. 39-53. https://doi.org/10.1509/jmkr.40.1.39.19126
  11. Brynjolfsson, E., Y. Hu, and M. D. Smith, "Research commentary-long tails vs. superstars: The effect of information technology on product variety and sales concentration patterns", Information Systems Research, Vol.21, No.4, 2010, pp. 736-747. https://doi.org/10.1287/isre.1100.0325
  12. Calantone, R. J., S. Yeniyurt, J. D. Townsend, and J. B. Schmidt, "The effects of competition in short product life-cycle markets: The case of Motion Pictures", Journal of Product Innovation Management, Vol.27, No.3, 2010, pp. 349-361. https://doi.org/10.1111/j.1540-5885.2010.00721.x
  13. Chintagunta, P. K., S. Gopinath, and S. Venkataraman, "The effects of online user reviews on movie box office performance: Accounting for sequential rollout and aggregation across local markets", Marketing Science, Vol.29, No.5, 2010, pp. 944-957. https://doi.org/10.1287/mksc.1100.0572
  14. Colicev, A., A. Malshe, K. Pauwels, and P. O'Connor, "Improving consumer mindset metrics and shareholder value through social media: The different roles of owned and earned media", Journal of Marketing, Vol.82, No.1, 2018, pp. 37-56. https://doi.org/10.1509/jm.16.0055
  15. De Vries, L., S. Gensler, and P. S. Leeflang, "Effects of traditional advertising and social messages on brand-building metrics and customer acquisition", Journal of Marketing, Vol.81, No.5, 2017, pp. 1-15. https://doi.org/10.1509/jm.15.0178
  16. Dewan, S., and J. Ramaprasad, "Social media, traditional media, and music sales", Mis Quarterly, Vol.38, No.1, 2014, pp. 101-122. https://doi.org/10.25300/MISQ/2014/38.1.05
  17. Ding, C., Cheng, H. K., Duan, Y., and Y. Jin, "The power of the "like" button: The impact of social media on box office", Decision Support Systems, Vol.94, 2017, pp. 77-84. https://doi.org/10.1016/j.dss.2016.11.002
  18. Divakaran, P. K. P., A. Palmer, H. A. Sondergaard, and R. Matkovskyy, "Pre-launch prediction of market performance for short lifecycle products using online community data", Journal of Interactive Marketing, Vol.38, 2017, pp. 12-28. https://doi.org/10.1016/j.intmar.2016.10.004
  19. Duan, W., B. Gu, and A. B. Whinston, "Do online reviews matter?: An empirical investigation of panel data", Decision Support Systems, Vol.45, No.4, 2008, pp. 1007-1016. https://doi.org/10.1016/j.dss.2008.04.001
  20. Elberse, A., "Should you invest in the long tail?", Harvard Business Review, Vol.86, No.7/8, 2008, pp. 1-10.
  21. Eliashberg, J. and M. S. Sawhney, "Modeling goes to Hollywood: Predicting individual differences in movie enjoyment", Management Science, Vol.40, No.9, 1994, pp. 1151-1173. https://doi.org/10.1287/mnsc.40.9.1151
  22. Fang, E., R. W. Palmatier, and R. Grewal, R., "Effects of customer and innovation asset configuration strategies on firm performance", Journal of Marketing Research, Vol.48, No.3, 2011, pp. 587-602. https://doi.org/10.1509/jmkr.48.3.587
  23. Fleder, D. and K. Hosanagar, "Blockbuster culture's next rise or fall: The impact of recommender systems on sales diversity", Management Science, Vol.55, No.5, 2009, pp. 697-712. https://doi.org/10.1287/mnsc.1080.0974
  24. Gould, E. D., B. P. Pashigian, and C. J. Prendergast, "Contracts, externalities, and incentives in shopping malls", Review of Economics and Statistics, Vol.87, No.3, 2005, pp. 411-422. https://doi.org/10.1162/0034653054638355
  25. Hinz, O., J. Eckert, and B. Skiera, "Drivers of the long tail phenomenon: An empirical analysis", Journal of Management Information Systems, Vol.27, No.4, 2011, pp. 43-70. https://doi.org/10.2753/MIS0742-1222270402
  26. Hollenbeck, B., "Online reputation mechanisms and the decreasing value of chain affiliation", Journal of Marketing Research, Vol.55, No.5, 2018, pp. 636-654. https://doi.org/10.1177/0022243718802844
  27. Jabr, W. and Z. Zheng, "Know yourself and know your enemy: An analysis of firm recommendations and consumer reviews in a competitive environment", MIS Quarterly, Vol.38, No.3, 2014, pp. 635-654. https://doi.org/10.25300/MISQ/2014/38.3.01
  28. Koenker, R. and G. Basset, "Asymptotic theory of least absolute error regression", Journal of the American Statistical Association, Vol.73, No.363, 1978, pp. 618-622. https://doi.org/10.1080/01621459.1978.10480065
  29. Kotler, P., Marketing in the twenty-first century. Marketing Management, 10th Edition, Millenium, New Jersey, 2000.
  30. Kumar, A., M. D. Smith, and R. Telang, "Information discovery and the long tail of motion picture content", Mis Quarterly, Vol.38, No.4, 2014, pp. 1057-1078. https://doi.org/10.25300/MISQ/2014/38.4.06
  31. Lehmann, D. R. and C. B. Weinberg, "Sales through sequential distribution channels: An application to movies and videos", Journal of Marketing, Vol.64, No.3, 2000, pp. 18-33. https://doi.org/10.1509/jmkg.64.3.18.18026
  32. Likas, A., N. Vlassis, and J. J. Verbeek, "The global k-means clustering algorithm", Pattern Recognition, Vol.36, No.2, 2003, pp. 451-461. https://doi.org/10.1016/S0031-3203(02)00060-2
  33. Liu, Y., "Word of mouth for movies: Its dynamics and impact on box office revenue", Journal of Marketing, Vol.70, No.3, 2006, pp. 74-89. https://doi.org/10.1509/jmkg.70.3.074
  34. Meiseberg, B., "The effectiveness of e-tailers' communication practices in stimulating sales of niche versus popular products", Journal of Retailing, Vol.92, No.3, 2016, pp. 319-332. https://doi.org/10.1016/j.jretai.2016.02.002
  35. Noe, T. and G. Parker, "Winner take all: Competition, strategy, and the structure of returns in the internet economy", Journal of Economics & Management Strategy, Vol.14 No.1, 2005, pp. 141-164. https://doi.org/10.1111/j.1430-9134.2005.00037.x
  36. Oestreicher-Singer, G. and A., "Sundararajan, Recommendation networks and the long tail of electronic commerce", Mis Quarterly, Vol.36, No.1, 2012, pp. 65-83. https://doi.org/10.2307/41410406
  37. Ottosson, M. and D. Kindstrom, "Exploring proactive niche market strategies in the steel industry: Activities and implications", Industrial Marketing Management, Vol.55, 2016, pp. 119-130. https://doi.org/10.1016/j.indmarman.2015.08.003
  38. Pareto, V., Cours d'economie politique, Librairie Droz, 1964.
  39. Park, S. and S. Gupta, "Handling endogenous regressors by joint estimation using copulas", Marketing Science, Vol.31, No.4, 2012, pp. 567-586. https://doi.org/10.1287/mksc.1120.0718
  40. Parrish, E. D., N. L. Cassill, and W. Oxenham, "Niche market strategy for a mature marketplace", Marketing Intelligence & Planning, Vol.24, No.7, 2006, pp. 694-707. https://doi.org/10.1108/02634500610711860
  41. Prasad, A., B. Bronnenberg, and V. Mahajan, "Product entry timing in dual distribution channels: The case of the movie industry", Review of Marketing Science, Vol.2, No.2, 2004, pp. 83-102. https://doi.org/10.2202/1546-5616.1008
  42. Rosen, S., "The economics of superstars", The American Economic Review, Vol.71, No.5, 1981, pp. 845-858.
  43. Roth, M. S., "Depth versus breadth strategies for global brand image management", Journal of Advertising, Vol.21, No.2, 1992, pp. 25-36. https://doi.org/10.1080/00913367.1992.10673365
  44. Shani, D. and S. Chalasani, "Exploiting niches using relationship marketing", Journal of Consumer Marketing, Vol.9, No.3, 1993, pp. 33-42. https://doi.org/10.1108/07363769210035215
  45. Song, R., S. Moon, H. A. Chen, and M. B. Houston, "When marketing strategy meets culture: The role of culture in product evaluations", Journal of the Academy of Marketing Science, Vol.46, No.3, 2018, pp. 384-402. https://doi.org/10.1007/s11747-017-0525-x
  46. Srinivasan, S., O. J. Rutz, and K. Pauwels, K., "Paths to and off purchase: Quantifying the impact of traditional marketing and online consumer activity", Journal of the Academy of Marketing Science, Vol.44, No.4, 2016, pp. 440-453. https://doi.org/10.1007/s11747-015-0431-z
  47. Stephen, A. T., and J. Galak, "The effects of traditional and social earned media on sales: A study of a microlending marketplace", Journal of Marketing Research, Vol.49, No.5, 2012, pp. 624-639. https://doi.org/10.1509/jmr.09.0401
  48. Stephen, A. T., and O. Toubia, "Deriving value from social commerce networks", Journal of Marketing Research, Vol.47, No.2, 2012, pp. 215-228. https://doi.org/10.1509/jmkr.47.2.215
  49. Tan, T. F., S. Netessine, and L. Hitt, "Is tom cruise threatened? An empirical study of the impact of product variety on demand concentration", Information Systems Research, Vol.28, No.3, 2017, pp. 643-660. https://doi.org/10.1287/isre.2017.0712
  50. Toften, K. and T. Hammervoll, "Niche marketing research: Status and challenges", Marketing Intelligence & Planning, Vol.31, No.3, 2013, pp. 272-285. https://doi.org/10.1108/02634501311324618
  51. Trusov, M., R. E. Bucklin, and K. Pauwels, "Effects of word-of-mouth versus traditional marketing: Findings from an internet social networking site", Journal of Marketing, Vol.73, No.5, 2009, pp. 90-102. https://doi.org/10.1509/jmkg.73.5.90
  52. Tucker, C. and J. Zhang, "How does popularity information affect choices? A field experiment", Management Science, Vol.57, No.5, 2011, pp. 828-842. https://doi.org/10.1287/mnsc.1110.1312
  53. Vinokurova, N., "Reshaping demand landscapes: How firms change customer preferences to better fit their products", Strategic Management Journal, Vol.40, No.13, 2019, pp. 2107-2137. https://doi.org/10.1002/smj.3074
  54. Wallace, E., I. Buil, L. de Chernatony, and M. Hogan, "Who "likes" you... and why? A typology of Facebook fans: From "fan"-atics and self-expressives to utilitarians and authentics", Journal of Advertising Research, Vol.54, No.1, 2014, pp. 92-109. https://doi.org/10.2501/JAR-54-1-092-109
  55. Yang, J., Kim, W., Amblee, N. and J. Jeong, "The heterogeneous effect of WOM on product sales: Why the effect of WOM valence is mixed?", European Journal of Marketing, Vol.46, No.11/12, 2012, pp. 1523-1538. https://doi.org/10.1108/03090561211259961
  56. Zachary, M. A., P. T. Gianiodis, G. T. Payne, and G. D. Markman, "Entry timing: Enduring lessons and future directions", Journal of Management, Vol.41, No.5, 2015, pp. 1388-1415. https://doi.org/10.1177/0149206314563982
  57. Zentner, A., M. Smith, and C. Kaya, "How video rental patterns change as consumers move online", Management Science, Vol.59, No.11, 2013, pp. 2622-2634. https://doi.org/10.1287/mnsc.2013.1731
  58. Zhou, W. and W. Duan, "Online user reviews, product variety, and the long tail: An empirical investigation on online software downloads", Electronic Commerce Research and Applications, Vol.11, No.3, 2012, pp. 275-289. https://doi.org/10.1016/j.elerap.2011.12.002