Skip to main content
main-content
Top

Hint

Swipe to navigate through the articles of this issue

Published in: Customer Needs and Solutions 1-2/2022

04-03-2022 | Research Article

Optimal Inter-release Timing for Sequentially Released Products

Authors: Jackie Y. Luan, K. Sudhir

Published in: Customer Needs and Solutions | Issue 1-2/2022

Login to get access
share
SHARE

Abstract

Marketers routinely use timing as a segmentation device through sequential product releases. While there has been much theoretical research on the optimal introduction strategy of sequential releases, there is little empirical research on this problem. This paper develops an econometric model to empirically solve the inter-release timing problem: it involves (1) developing and estimating a structural model of consumers’ choice for sequentially released products and (2) using the estimates of the structural model to solve for the optimal inter-release time. The empirical application focuses on the movie industry, where we specifically address the issue of the inter-release time between a theatrical movie and its DVD version. We find that consumers are indeed forward looking; a shrinking movie-DVD release window does negatively impact box-office revenues, but there is a tradeoff in that there is greater residual buzz from the movie marketing that supports the sales of DVD due to the shorter time window. This leads to an inverted U-shaped relationship between movie-DVD release window and revenues, and the theater-DVD window that maximizes industry revenue for the average movie during the data period is 2.5 months.
Footnotes
1
The pandemic has upended this sequential model with many studios going straight to streaming or simultaneously releasing in theater and streaming services.
 
2
The applicability of the model may well go beyond the theater and DVD stages and extend to other stages of a typical Hollywood movie’s sequential release scheme, such as pay-per-view (PPV), video-on-demand (VOD), premium channel premiere, and network TV showing. We focus on the issue of theater-DVD window to simplify the conceptual underpinnings of the econometric approach. Currently, the theatrical and DVD markets combined account for over 90% of the movie-related revenue.
 
3
While many executives including the President of Universal Studios Rick Finkelstein perceive that this trend of shortening DVD releases has “gone too far,” others such as Disney have proposed shortening the movie-DVD window to a 4-month standard. At the extreme, Mark Cuban of 29/29 Entertainment has advocated a simultaneous release of movies and DVDs. In fact, Mark Cuban’s studio recently released Steven Soderbergh’s “Bubble” in theaters only 4 days before it became available on DVD, but the movie proved to be a small-scale experiment since it was boycotted by major theater chains.
 
4
Note that we do not assume, that buzz will decay or inter-release window negatively affects DVD sales. The sign and magnitude of these effects are empirically estimated in the model.
 
5
It took only 5 years for 30 million DVD players to be sold, compared to about 8 years for CD players, and 10 years for PCs to reach the same volume mark.
 
6
DVD rentals totaled $5.7 billion, up from $4.5 billion in 2003. Couple that with DVD sales of $15.5 billion, the DVD market over twice as large as the theatrical exhibition market. With DVD penetration spiraling, VHS market has been dwindling: VHS sales dropped 42% to 240.4 million from 2002, while VHS rentals fell 23% to 53.2 million (MPAA 2004). Therefore, the empirical study does not consider the VHS market.
 
7
The study does not consider previously viewed DVDs for the following two reasons: first, the sales of previously owned DVDs was approximately $2 billion in 2004; only 7–8% of the $26 billion DVD market. Second, previously viewed DVDs usually contribute revenues to video retailers (or “rentailers”) but not to the studios, so they would have a negligible impact on the studios’ marketing-mix decisions. Nevertheless, some consumers may strategically wait to purchase previously viewed DVDs, and, as a result, the pricing and timing decisions of the new DVD release might have an effect on the incentive to do so. However, modeling such effect requires a different approach that resembles previous models on secondhand markets such as used automobile or textbook markets. And we do not consider catalog DVDs (i.e., DVD release for movies more than 2 years old) for three reasons. First, new-release DVDs account for a large majority of revenues while catalog DVDs represent a small proportion of total pre-recorded DVD sales. Second, since catalog DVDs are released long after their theatrical release dates, the timing decisions are affected by different factors than what is considered in our model; for instance, the DVD of “Assault on Precinct 13” (1976) was released when the remake of the movie was about to open in theaters.
 
8
We focus on movies whose box-office gross was above five million dollars because extremely small-budget movies are usually marketed differently (for instance, such movies are targeted at a small niche market and are usually supported by no advertising; they may simply go directly to videos, bypassing the theater channel altogether).
 
9
TV is the major channel for DVD advertising, representing 60–70% of the industry spending because of TV’s ability to show DVD trailers.
 
10
Such characteristics of movies may include news coverage of the movie and/or tabloid fame of its stars.
 
11
Orbach and Einav [34] examine the uniform pricing scheme in the theatrical movie market and argue that this regime is inferior to alternative pricing strategies.
 
12
We believe it to be an innocuous assumption; we also estimated a specification without this single-viewing constraint, and the estimation and policy analysis results remain virtually unchanged.
 
13
The US Copyright Act of 1976 stipulates that the owner of a legally owned copy of a copyrighted product is entitled to “first use” (commonly known as the First Sale Doctrine), which invokes copyright jurisdiction only upon the first sale of videos so that subsequent usage (such as rental) no longer generates revenue to the copyright holder. This effectively prevents movie studios to discriminate between institutional buyers (i.e., video rental stores) and individual buyers. See [24] for a detailed discussion of its implication on studios’ pricing strategies and the difference between the US market and the E.U. market.
 
14
We do not model the case in which the household first rents the video and then buys, or the reverse. We do not think such a simplification severely compromises the validity of the model implications.
 
15
Video rental stores typically set a uniform price for all new releases. Therefore, we let \({p}_m^R={p}^R\).
 
16
Another way to model such difference is to view the buying utility as a discounted sum of per-period utilities and explicitly specify the discounting patterns [23].
 
17
Assuming rational expectations (i.e., the agent’s expectations are objectively correct) is a prevailing practice in dynamic choice economic models. However, such maintained assumptions may be questionable, given that the multiple forms of expectations can all lead to the observed choice behavior (e.g., [38]). It would be ideal if we had data on stated expectations (e.g., how soon consumers expect a particular DVD to be released); however, such questions are not asked in our consumer survey data.
 
18
The 2SLS estimates are computed in the first stage by using A = (ZZ)−1, then the resulting parameter estimates are used to compute the optimal weighting matrix, \(A={\left({Z}^{\prime}\xi \left({\hat{\theta}}_{2 SLS}\right)\xi {\left({\hat{\theta}}_{2 SLS}\right)}^{\prime }Z\right)}^{-1}\).
 
19
Some industry insiders claimed that the trend towards a faster DVD release is caused by an ever-shortening movie leg at the box-office. Our results indicate that the claim is untrue. First, even controlling for the movie leg, the trend variable has a significantly negative coefficient. Second, we also performed a simple regression of the movie leg against a time trend, and the trend variable is not significant, i.e., there is no evidence that movies’ legs have been shortening during our sample period.
 
20
Leaving the hardware adoption decision out of the current framework might be problematic if the trend towards a shorter theater-to-DVD window induces consumers to adopt the DVD player earlier than they otherwise would, which subsequently increases the demand for DVD software titles. However, this effect is not identifiable with our current data.
 
Literature
1.
go back to reference Lehmann DR, Weinberg CB (2000) Sales through sequential distribution channels: an application to movies and videos. J Mark 64(3):18–33 CrossRef Lehmann DR, Weinberg CB (2000) Sales through sequential distribution channels: an application to movies and videos. J Mark 64(3):18–33 CrossRef
2.
go back to reference Moorthy KS, Png IPL (1992) Market-segmentation, cannibalization, and the timing of product introductions. Manag Sci 38(3):345–359 CrossRef Moorthy KS, Png IPL (1992) Market-segmentation, cannibalization, and the timing of product introductions. Manag Sci 38(3):345–359 CrossRef
3.
go back to reference Weiss AM (1994) The effects of expectations on technology adoption: some empirical evidence. J Ind Econ 42(4):341–360 CrossRef Weiss AM (1994) The effects of expectations on technology adoption: some empirical evidence. J Ind Econ 42(4):341–360 CrossRef
4.
go back to reference Boone DS, Lemon KN, Staelin R (2001) The impact of firm introductory strategies on consumers’ perceptions of future product introductions and purchase decisions. J Prod Innov Manag 18(2):96–109 CrossRef Boone DS, Lemon KN, Staelin R (2001) The impact of firm introductory strategies on consumers’ perceptions of future product introductions and purchase decisions. J Prod Innov Manag 18(2):96–109 CrossRef
5.
go back to reference Gowrisankaran G, Rysman M (2005) "Determinants of price declines for new durable consumer goods," Working Paper, Washington University in St. Louis Gowrisankaran G, Rysman M (2005) "Determinants of price declines for new durable consumer goods," Working Paper, Washington University in St. Louis
6.
go back to reference Melnikov O (2000) "Demand for differentiated durable products: the case of the U. S. computer printer market," Working Paper, Department of Economics, Yale University Melnikov O (2000) "Demand for differentiated durable products: the case of the U. S. computer printer market," Working Paper, Department of Economics, Yale University
7.
go back to reference Song I, Chintagunta PK (2003) A micromodel of new product adoption with heterogeneous and forward-looking consumers: application to the digital camera category. Quant Mark Econ 1(4):371–407 CrossRef Song I, Chintagunta PK (2003) A micromodel of new product adoption with heterogeneous and forward-looking consumers: application to the digital camera category. Quant Mark Econ 1(4):371–407 CrossRef
8.
go back to reference Gentzkow M (2004) "Valuing new goods in a model with complementarity: online newspapers," Working paper, Harvard University. Gentzkow M (2004) "Valuing new goods in a model with complementarity: online newspapers," Working paper, Harvard University.
9.
go back to reference Song I, Chintagunta PK (2005) "Measuring cross-category price effects with aggregate store data," Working Paper, Hong Kong University of Science and Technology. Song I, Chintagunta PK (2005) "Measuring cross-category price effects with aggregate store data," Working Paper, Hong Kong University of Science and Technology.
10.
go back to reference Prasad A, Bronnenberg B, Mahajan V (2004) "Product entry timing in dual distribution channels: the case of the movie industry," Review of Marketing Science, 2, Article 4. Prasad A, Bronnenberg B, Mahajan V (2004) "Product entry timing in dual distribution channels: the case of the movie industry," Review of Marketing Science, 2, Article 4.
11.
go back to reference Norton JA, Bass FM (1987) A diffusion theory model of adoption and substitution for successive generations of high-technology products. Manag Sci 33(9):1069–1086 CrossRef Norton JA, Bass FM (1987) A diffusion theory model of adoption and substitution for successive generations of high-technology products. Manag Sci 33(9):1069–1086 CrossRef
12.
go back to reference Padmananbhan V, Bass FM (1993) Optimal pricing of successive generations of product advances. Int J Res Mark 10(2):185–207 CrossRef Padmananbhan V, Bass FM (1993) Optimal pricing of successive generations of product advances. Int J Res Mark 10(2):185–207 CrossRef
13.
go back to reference Wilson LO, Norton JA (1989) Optimal entry timing for a product line extension. Mark Sci 8(1):1–17 CrossRef Wilson LO, Norton JA (1989) Optimal entry timing for a product line extension. Mark Sci 8(1):1–17 CrossRef
14.
go back to reference Ainslie A, Dreze X, Zufryden F (2004) "Modeling movie lifecycles and market share," Marketing Science, Forthcoming. Ainslie A, Dreze X, Zufryden F (2004) "Modeling movie lifecycles and market share," Marketing Science, Forthcoming.
15.
go back to reference De Vany A, Lee C (2001) Quality signals in information cascades and the dynamics of the distribution of motion picture box office revenues. J Econ Dyn Control 25(3-4):593–614 CrossRef De Vany A, Lee C (2001) Quality signals in information cascades and the dynamics of the distribution of motion picture box office revenues. J Econ Dyn Control 25(3-4):593–614 CrossRef
16.
go back to reference Neelamegham R, Chintagunta P (1999) A Bayesian model to forecast new product performance in domestic and international markets. Mark Sci 18(2):115–136 CrossRef Neelamegham R, Chintagunta P (1999) A Bayesian model to forecast new product performance in domestic and international markets. Mark Sci 18(2):115–136 CrossRef
17.
go back to reference Sawhney MS, Eliashberg J (1996) A parsimonious model for forecasting gross box-office revenues of motion pictures. Mark Sci 15(2):113–131 CrossRef Sawhney MS, Eliashberg J (1996) A parsimonious model for forecasting gross box-office revenues of motion pictures. Mark Sci 15(2):113–131 CrossRef
18.
go back to reference Zufryden FS (1996) Linking advertising to box office performance of new film releases - a marketing planning model. J Advert Res 36(4):29–41 Zufryden FS (1996) Linking advertising to box office performance of new film releases - a marketing planning model. J Advert Res 36(4):29–41
19.
go back to reference Einav L (2003), "Not all rivals look alike: estimating an equilibrium model of the release date timing game," Working Paper, Stanford University. Einav L (2003), "Not all rivals look alike: estimating an equilibrium model of the release date timing game," Working Paper, Stanford University.
20.
go back to reference Foutz NZ, Kadiyali V (2003) "Competitive dynamics in optimal release timing of motion pictures," Working Paper, Cornell University. Foutz NZ, Kadiyali V (2003) "Competitive dynamics in optimal release timing of motion pictures," Working Paper, Cornell University.
21.
go back to reference Krider RE, Weinberg CB (1998) Competitive dynamics and the introduction of new products: the motion picture timing game. J Mark Res 35(1):1–15 CrossRef Krider RE, Weinberg CB (1998) Competitive dynamics and the introduction of new products: the motion picture timing game. J Mark Res 35(1):1–15 CrossRef
22.
go back to reference Radas S, Shugan SM (1998) Seasonal marketing and timing new product introductions. J Mark Res 35(3):296–315 CrossRef Radas S, Shugan SM (1998) Seasonal marketing and timing new product introductions. J Mark Res 35(3):296–315 CrossRef
23.
go back to reference Knox G, Eliashberg J (2004) "Consumers rent vs. buy decision: the case of home video," Working Paper, University of Pennsylvania Knox G, Eliashberg J (2004) "Consumers rent vs. buy decision: the case of home video," Working Paper, University of Pennsylvania
24.
go back to reference Mortimer JH (2004) "Price discrimination and copyright law: evidence from the introduction of DVDs," Working paper, Harvard University. Mortimer JH (2004) "Price discrimination and copyright law: evidence from the introduction of DVDs," Working paper, Harvard University.
25.
go back to reference Chellappa RK, Shivendu S (2003) Economic implications of variable technology standards for movie piracy in a global context. J Manag Inf Syst 20(2):137–168 CrossRef Chellappa RK, Shivendu S (2003) Economic implications of variable technology standards for movie piracy in a global context. J Manag Inf Syst 20(2):137–168 CrossRef
26.
go back to reference Rao A (2015) Online content pricing: purchase and rental markets. Mark Sci 34(3):430–451 CrossRef Rao A (2015) Online content pricing: purchase and rental markets. Mark Sci 34(3):430–451 CrossRef
27.
go back to reference Hartmann WR (2004) "Intertemporal effects of consumption and their implication for demand elasticity estimates," Working paper, Stanford University. Hartmann WR (2004) "Intertemporal effects of consumption and their implication for demand elasticity estimates," Working paper, Stanford University.
28.
go back to reference Israel M (2005) "Who can see the future? Information and consumer reactions to future price discounts," Working Paper, Northwestern University. Israel M (2005) "Who can see the future? Information and consumer reactions to future price discounts," Working Paper, Northwestern University.
29.
go back to reference Hendel I, Nevo A (2002) "Sales and consumer inventory," NBER Working Paper No. 9048 Hendel I, Nevo A (2002) "Sales and consumer inventory," NBER Working Paper No. 9048
31.
go back to reference McBride S (2004) "‘Noel,’ in theaters and self-erasing discs," The Wall Street Journal, 18 October, 2004. McBride S (2004) "‘Noel,’ in theaters and self-erasing discs," The Wall Street Journal, 18 October, 2004.
32.
go back to reference Gilbert-Rolfe J, Merchant U, Moroian V (2003) "Drivers of marketing spending in motion pictures," The Anderson School of Business, UCLA. Gilbert-Rolfe J, Merchant U, Moroian V (2003) "Drivers of marketing spending in motion pictures," The Anderson School of Business, UCLA.
33.
go back to reference Einav L (2004), "Gross seasonality and underlying seasonality: evidence from the U.S. motion picture industry," Working Paper, Stanford University. Einav L (2004), "Gross seasonality and underlying seasonality: evidence from the U.S. motion picture industry," Working Paper, Stanford University.
34.
go back to reference Orbach BY, Einav L (2002) "Uniform prices for differentiated goods: the case of the movie-theater industry," Harvard Law and Economics Discussion Paper. Orbach BY, Einav L (2002) "Uniform prices for differentiated goods: the case of the movie-theater industry," Harvard Law and Economics Discussion Paper.
35.
go back to reference Keane MP (1997) Modeling heterogeneity and state dependence in consumer choice behavior. J Bus Econ Stat 15(3):310–327 Keane MP (1997) Modeling heterogeneity and state dependence in consumer choice behavior. J Bus Econ Stat 15(3):310–327
36.
go back to reference Seetharaman PB (2003) Probabilistic versus random-utility models of state dependence: an empirical comparison. Int J Res Mark 20(1):87–96 CrossRef Seetharaman PB (2003) Probabilistic versus random-utility models of state dependence: an empirical comparison. Int J Res Mark 20(1):87–96 CrossRef
37.
go back to reference Rust J (1987) Optimal replacement of Gmc bus engines - an empirical model of Harold Zurcher. Econometrica 55(5):999–1033 CrossRef Rust J (1987) Optimal replacement of Gmc bus engines - an empirical model of Harold Zurcher. Econometrica 55(5):999–1033 CrossRef
38.
go back to reference Erdem T, Keane MP, Strebel J (2004) "Learning about computers: an analysis of information search and technology choice," Working Paper, UC Berkeley. Erdem T, Keane MP, Strebel J (2004) "Learning about computers: an analysis of information search and technology choice," Working Paper, UC Berkeley.
39.
go back to reference Eliashberg J, Elberse A, Leenders MAAM (2005) "The motion picture industry: critical issues in practice, current research and new research directions," Working Paper. Eliashberg J, Elberse A, Leenders MAAM (2005) "The motion picture industry: critical issues in practice, current research and new research directions," Working Paper.
40.
go back to reference Gelman A, Carlin JB, Stern HS, Rubin DB (2003) Bayesian data analysis, (2nd ed.). Boca Raton, FL: Chapman & Hall/CRC Gelman A, Carlin JB, Stern HS, Rubin DB (2003) Bayesian data analysis, (2nd ed.). Boca Raton, FL: Chapman & Hall/CRC
41.
go back to reference Berry S, Levinsohn J, Pakes A (1995) Automobile prices in market equilibrium. Econometrica 63(4):841–890 CrossRef Berry S, Levinsohn J, Pakes A (1995) Automobile prices in market equilibrium. Econometrica 63(4):841–890 CrossRef
42.
go back to reference Nevo A (2001) Measuring market power in the ready-to-eat cereal industry. Econometrica 69(2):307–342 CrossRef Nevo A (2001) Measuring market power in the ready-to-eat cereal industry. Econometrica 69(2):307–342 CrossRef
43.
go back to reference Sudhir K (2001) Competitive pricing behavior in the auto market: a structural analysis. Mark Sci 20(1):42–60 CrossRef Sudhir K (2001) Competitive pricing behavior in the auto market: a structural analysis. Mark Sci 20(1):42–60 CrossRef
44.
go back to reference Harris KM, Keane MP (1999) A model of health plan choice: inferring preferences and perceptions from a combination of revealed preference and attitudinal data. J Econ 89(1-2):131–157 CrossRef Harris KM, Keane MP (1999) A model of health plan choice: inferring preferences and perceptions from a combination of revealed preference and attitudinal data. J Econ 89(1-2):131–157 CrossRef
45.
go back to reference Drasgow F (ed) (1986) Polychoric and polyserial correlations: Wiley. Drasgow F (ed) (1986) Polychoric and polyserial correlations: Wiley.
46.
go back to reference Olsson U (1979) Maximum likelihood estimation of the polychoric correlation coefficient. Psychometrika 44:443–460 CrossRef Olsson U (1979) Maximum likelihood estimation of the polychoric correlation coefficient. Psychometrika 44:443–460 CrossRef
47.
go back to reference Berry S (1994) Estimating discrete-choice models of product differentiation. RAND J Econ 25(2):242–262 CrossRef Berry S (1994) Estimating discrete-choice models of product differentiation. RAND J Econ 25(2):242–262 CrossRef
48.
go back to reference Karace-Mandic P (2004) "Network effects in technology adoption: the case of DVD players," Working Paper, University of California at Berkeley Karace-Mandic P (2004) "Network effects in technology adoption: the case of DVD players," Working Paper, University of California at Berkeley
49.
go back to reference Inceoglu F Park M (2003) "Diffusion of a new product under network effects: the case of U.S. DVD player market," Working Paper, Boston University Inceoglu F Park M (2003) "Diffusion of a new product under network effects: the case of U.S. DVD player market," Working Paper, Boston University
50.
go back to reference Luan JY, Sudhir K (2006) "Forecasting advertising responsiveness for short life-cycle products," Working Paper, Yale University. Luan JY, Sudhir K (2006) "Forecasting advertising responsiveness for short life-cycle products," Working Paper, Yale University.
51.
go back to reference Kurt I (2004) Video industry on the way to another record year. Video Store Magazine 26(30):8 Kurt I (2004) Video industry on the way to another record year. Video Store Magazine 26(30):8
Metadata
Title
Optimal Inter-release Timing for Sequentially Released Products
Authors
Jackie Y. Luan
K. Sudhir
Publication date
04-03-2022
Publisher
Springer US
Published in
Customer Needs and Solutions / Issue 1-2/2022
Print ISSN: 2196-291X
Electronic ISSN: 2196-2928
DOI
https://doi.org/10.1007/s40547-022-00124-5