Abstract
In this chapter on entertainment product decisions, we take a deep dive into just what “quality” means in an entertainment context and the taste-dependency of the concept. We then study what makes an entertainment product a “high quality” one, and how such quality ultimately relates to product success. Because many entertainment products rely on a storyline, we also take a look at what makes a narrative “great”—including an examination of whether storyline development can (ever) be automated in the age of big data.
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Notes
- 1.
Those other success drivers in our study included measures of advertising and distribution.
- 2.
Of course, one could always argue that, drawing on Mr. Milchan, if a great entertainment product has not returned its investments, “it’s not the end” yet… The problem with this logic is that even if quality finds its way in the long term in some cases, investors usually don’t want to wait to get their money back. In addition, ad hoc evidence for our finding that quality is only loosely linked to success is abundant. It comes from those who have produced great works and lost a lot of money (like Citizen Kane and Once Upon a Time in America, which generate revenues today, but ruined their makers when they came out). It is also true for less well-known films: The Iron Giant—IMDb: 8.0 (out of 10), global box office: $23 million at $70 million budget; Children of Men—IMDb: 7.9, global box office: $70 million at $76 million budget; The Insider—IMDb: 7.9, global box office: $60 million at $90 million budget). And evidence also comes from what consumers believe are bad products, but generated a fortune (e.g., Alvin and the Chipmunks: Chipwrecked —IMDb: 4.4, global box office: $343 million at $75 million budget; Couples Retreat—IMDb: 5.5, global box office: $172 million at $70 million budget; Transformers: Age of Extinction—IMDb: 5.7, global box office: $1.1 billion at $210 million budget).
- 3.
See our earlier section on the dominance of experience qualities for entertainment. We will discuss the role of technological attributes as entertainment search qualities in the next chapter.
- 4.
Holbrook (1999) also finds other discrepancies between the tastes of HBO audiences and his “experts.” Experts’ judgments are negatively influenced by recency (older films are rated systematically higher by them!), whereas a foreign language soundtrack and a non-U.S. origin are associated with more positive quality perceptions. In another study of expert quality criteria for movies, Wallentin (2016) explains professional critics’ judgments of almost 2,000 movies shown in Sweden from 1999 to 2011 using regression analysis. Like Holbrook, he finds that experts see a higher quality in non-U.S. films. Focusing on genre effects for experts, he finds a positive effect for dramas and documentaries, whereas action, family, comedy, romance, and horror have negative effects on the experts’ quality perceptions.
- 5.
We discuss international differences in genre preferences in more detail in the following chapter.
- 6.
We assume that, as a result of this high variation, the reported differences in downloads are probably not significant (the authors do not report any statistical tests).
- 7.
Specifically, these script aspects encompass: a clear premise, a familiar setting, an early exposition, the avoidance of coincidences, interconnectedness, surprises, anticipation of what happens next, no flashbacks, a linear timeline, clear motivation of characters, a multidimensional hero, a strong nemesis, a sympathetic hero, believable characters, hero character growth, important conflict, multidimensional conflict, conflict build-up, conflict lock-in, an unambiguous resolution, a logical ending, and a surprising ending. Let us note that Eliashberg et al. also include some other interesting language characteristics, such as the use of passive sentences and the average word length of sentences. Because they use fan-created texts instead of original treatments in this study, the results for these variables are probably of limited generalizability though.
- 8.
An aspect that is tied closely to the concept of familiarity, by the way.
- 9.
Please refer back to our discussion of the fundamental role of creativity in entertainment and the sensations-familiarity framework in prior chapters.
- 10.
For a broad review of the state of algorithmic music composition, see the articles in McLean and Dean (2018).
- 11.
You can find Cope’s website and his musical compositions at https://goo.gl/1W3pnm.
- 12.
We discuss the concept of innovativeness as part of our innovation management chapter.
- 13.
This finding, along with the fact that Cope has never released the algorithms underlying his creations in full, has led some to question the credibility of his work; for example, Collins and Laney (2017) name him a “somewhat controversial figure,” something that does not necessarily conflict with his role as a pioneer in the field of computer-generated music and entertainment.
- 14.
Let us note that one might question the low-innovativeness character of reconfigurations—think of the first iPhone as a reconfiguration of existing products (Steve Jobs, in his original announcement speech in 2007, referred to it as a combination of an iPod, a mobile phone, and an Internet device; quoted in Wright 2015). But whereas high innovativeness products might build on existing technology and offers, they take large liberties at integrating them—which again would require high levels of creativity.
- 15.
See also the reactions from a small sample of student listeners who Simoni (2018) repeatedly exposed to different pieces of algorithmic music.
- 16.
See also our analysis of the state of the industry as part of the integrated entertainment marketing chapter for a discussion of the prospects of familiarity-dominated entertainment offers.
References
Barnes, B. (2013). Solving equation of a hit film script, with data. The New York Times, May 5, https://goo.gl/S5RvQt.
Collins, T., & Laney, R. (2017). Computer-generated stylistic compositions with long term repetitive and phrasal structure. Journal of Creative Music Systems, 1.
Cope, D. (1996). Experiments in musical intelligence. Madison: A-R Editions.
Cope, D. (2005). Computer models of musical creativity. Cambridge, MA: MIT Press.
Cutting, J. E. (2016). Narrative theory and the dynamics of popular movies. Psychonomic Bulletin & Review, 23, 1713–1743.
Eck, D. (2016). Welcome to Magenta! Magenta, June 1, https://goo.gl/gWNt8B.
Elberse, A., & Eliashberg, J. (2003). Demand and supply dynamics for sequentially released products in international markets: The case of motion pictures. Marketing Science, 22, 329–354.
Eliashberg, J., Hui, S. K., & Zhang, J. Z. (2007). From story line to box office: A new approach for green-lighting movie scripts. Management Science, 53, 881–893.
Eliashberg, J., Hui, S. K., & John Zhang, Z. (2014). Assessing box office performance using movie scripts: A Kernel-based approach. IEEE Transactions on Knowledge and Data Engineering, 26, 2639–2648.
Freitag, C. (2016). Listen to ‘Daddy’s Car,’ a track composed by artificial intelligence. Pigeons & Planes, September 22, https://goo.gl/9vvqJ2.
Garcia, R., & Calantone, R. (2002). A critical look at technological innovation typology and innovativeness terminology: A literature review. Journal of Product Innovation Management, 19, 110–132.
Hennig-Thurau, T., Houston, M. B., & Sridhar, S. (2006). Can good marketing carry a bad product? Evidence from the motion picture industry. Marketing Letters, 17, 205–219.
Hennig-Thurau, T., Walsh, G., & Wruck, O. (2001). An investigation into the factors determining the success of service innovations: The case of motion pictures. Academy of Marketing Science Review, 1, 1–23.
Holbrook, M. B. (1999). Popular appeal versus expert judgments of motion pictures. Journal of Consumer Research, 26, 144–155.
Jordanous, A. (2016). Has computational creativity successfully made it ‘Beyond the Fence’ in musical theatre?, Conference Paper, University of Kent.
Langfitt, F. (2015). How China’s censors influence Hollywood. NPR, May 18, https://goo.gl/fNtSM9.
Lewis, J. (2003). Following the money in America’s sunniest company town: Some notes on the political economy of the Hollywood blockbuster. In J. Stringer (Ed.), Movie blockbusters (pp. 61–71). London: Routledge.
McCarthy, E. J. (1960). Basic marketing: A managerial approach. Homewood, IL: Richard D. Irwin.
McKee, R. (2016). The Aristotle of our time. https://goo.gl/ApH3B9.
McLean, A., & Dean, R. T. (Eds.). (2018). The Oxford handbook of algorithmic music. New York, NY: Oxford University Press.
Moon, S., Bergey, P. K., & Iacobucci, D. (2010). Dynamic effects among movie ratings, movie revenues, and viewer satisfaction. Journal of Marketing, 74, 108–121.
Pähler vor der Holte, N., & Hennig-Thurau, T. (2016). Das Phänomen Neue Drama-Serien. Working Paper, Department of Marketing and Media Research, Münster University.
Reagan, A. J., Mitchell, L., Kiley, D., Danforth, C. M., & Dodds, P. S. (2016). The emotional arcs of stories are dominated by six basic shapes. EPJ Data Science, 5, 1–12.
Shanken, M. R. (2008). An interview with Arnon Milchan. Cigar Aficionado, September/October, https://goo.gl/7xuGwM.
Simoni, M. (2018). The audience reception of algorithmic music. In A. McLean & R. T. Dean (Eds.), The Oxford handbook of algorithmic music (pp. 531–556). New York, NY: Oxford University Press.
The Economist (2015). The force is strong in this firm, December 19, https://goo.gl/E7vbr4.
The R-gument(or) (2016). Why Hollywood might want to scale back (a little): A rant against modern tentpole filmmaking, August 26, https://goo.gl/vGeiys.
Thompson, K. (1999). Storytelling in the new Hollywood. Cambridge, MA: Harvard University Press.
Vogel, H. L. (2015). Entertainment industry economics: A guide for financial analysis (9th ed.). Cambridge: Cambridge University Press.
Wallentin, E. (2016). Demand for cinema and diverging tastes of critics and audiences. Journal of Retailing and Consumer Services, 33, 72–81.
Wright, M. (2015). The original iPhone announcement annotated: Steve Jobs’ genius meets genius. TNW, September 9, https://goo.gl/fxpx5t.
Wu, S. (2015). An empirical observation of Chinese film performance drivers. Empirical Studies of the Arts, 33, 192–206.
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Hennig-Thurau, T., Houston, M.B. (2019). Entertainment Product Decisions, Episode 1: The Quality of the Entertainment Experience. In: Entertainment Science. Springer, Cham. https://doi.org/10.1007/978-3-319-89292-4_7
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