Factors Determining UK Album Success

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Factors Determining UK Album Success This article was downloaded by: [Lancaster University Library] On: 23 January 2013, At: 07:37 Publisher: Routledge Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK Applied Economics Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/raec20 Factors determining UK album success Caroline Elliott a & Rob Simmons a a Department of Economics, Lancaster University Management School, Lancaster University, Lancaster LA1 4YX, UK Version of record first published: 31 Jan 2011. To cite this article: Caroline Elliott & Rob Simmons (2011): Factors determining UK album success, Applied Economics, 43:30, 4699-4705 To link to this article: http://dx.doi.org/10.1080/00036846.2010.498349 PLEASE SCROLL DOWN FOR ARTICLE Full terms and conditions of use: http://www.tandfonline.com/page/terms-and-conditions This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae, and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand, or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material. Applied Economics, 2011, 43, 4699–4705 Factors determining UK album success Caroline Elliott* and Rob Simmons Department of Economics, Lancaster University Management School, Lancaster University, Lancaster LA1 4YX, UK This article uses a recently compiled dataset on the UK album sales to determine which factors contribute to best-selling album sales success. We control for factors including length of time since release, nationality of artist, artist type and album type, testing the increasing returns to information hypothesis. Information on general public online review scores for the albums in the dataset allows for a strong test of the accuracy of online reviews in predicting music sales, as online reviews are a relatively recent phenomenon, while the release of many of the albums predates the widespread use of Internet. I. Introduction the literature on the factors contributing to music sales is more limited (see Strobl and Tucker (2000); Despite the challenges faced by the music industry in Connolly and Krueger (2006); Fox and Kochanowski recent years, the industry remains important to the (2007) for recent detailed summaries of developments UK economy, with the total UK recorded music in the music industry as well as discussion of the income reaching £928.8 million in 2009 according to limited existing literature that explores the determi- the British Phonographic Industry (2010).1 Music nants of album success). albums, along with other entertainment goods such In the statistical analysis, we test whether factors as films, can broadly be considered to be experience such as length of time since release, nationality of goods, which have to be ‘consumed’ for consumers to artist, type of artist and type of album impact on discover whether the product matches their prefer- best-selling album success. We are also able to test the ences, although some characteristics of the product increasing returns to information hypothesis, which Downloaded by [Lancaster University Library] at 07:37 23 January 2013 can be ascertained, via search, prior to purchasing suggests that past success of an album gives rise to a (Nelson, 1970; Shapiro and Varian, 1999). Individual greater amount of album information in the public music tracks can be heard on television music domain, contributing to further album success and channels, online or on the radio, but full information sales. Increasing returns to information have previ- on the album may be difficult to obtain prior to ously been identified for a number of experience purchase. This article uses a recently compiled dataset goods in the entertainment industry, including the US on the UK best-selling album sales over the past 50 hit singles market in popular music (Giles, 2007); years to determine which factors contribute to the films (Walls (1997) for the US and Hand (2001) for album sales success. While there is an established the UK); and Broadway theatre productions literature examining the factors contributing to the (Maddison, 2004). This article extends this literature sales of films, for example, Elberse and Eliashberg by confirming the increasing returns to information (2003), Moul (2007) and Elliott and Simmons (2008), result for the UK music album sales. The result is *Corresponding author. E-mail: [email protected] 1 www.bpi.co.uk. Applied Economics ISSN 0003–6846 print/ISSN 1466–4283 online ß 2011 Taylor & Francis 4699 http://www.informaworld.com DOI: 10.1080/00036846.2010.498349 4700 C. Elliott and R. Simmons particularly strong as it is not only identified for the De Vany and Walls (1996). For example, this may be UK best-selling albums, but replicated using a second due to the greater propensity for word-of-mouth dataset of recently released albums. recommendations, which may be particularly valu- Potential consumers have an increasing number of able for experience good purchases. This has led a sources of information available to them when number of researchers, including Walls (1997), Hand considering the purchase of experience goods such (2001), Maddison (2004) and Giles (2007), to test for as music, films and books. Online reviews are a relationship between size and rank for entertain- increasingly common, and those provided by the ment goods that departs from the simple Pareto law, general public are an alternative to expert reviews with the model estimated typically taking the follow- that continue to be published in newspapers and ing form: magazines, as well as online. Hence, data were 2 collected on general public online review scores. lnðSÞ¼lnðAÞþ lnðRÞþ lnðRÞ ð3Þ This allows for a strong test of the accuracy of Of crucial importance is the sign associated with online reviews in predicting music sales, as online the coefficient on the squared rank variable. reviews are a relatively recent phenomenon, while the A negative, significantly different from zero coeffi- release of many of the albums in the dataset predates cient, indicates a departure from Pareto’s Law, with the widespread use of Internet. There is a growing autocorrelated growth and increasing returns to empirical literature investigating the impact of third- information. party reviews in diverse settings such as Broadway Initial Ordinary Least Squares (OLS) regression shows (Reddy et al., 1998) cinema (Eliashberg and results suffered from heteroscedasticity. Hence, Shugan, 1997; Holbrook, 2005; Reinstein and Snyder, Huber’s robust regression method was adopted in 2005; Elliott and Simmons, 2008); books (Chevalier our sales regressions. Robust regression is an estima- and Mayzlin, 2006). Consequently, reviews, whether tor designed to eliminate gross outliers. The proce- offered by ‘experts’ or increasingly online by mem- dure is to perform an initial screening of the data bers of the public, may be influential in determining based on Cook’s distance41. Once any gross outliers the sales. However, we are unaware of any other are removed, iterations are performed, using Huber research into the impact of online reviews in the weights and biweights sequentially, until convergence music industry to date. is achieved. The resulting SEs are then robust to The structure of the remainder of the article is as heteroscedasticity. This procedure can be applied follows: in the following section, the methodology where a distribution exhibits excess kurtosis due to and dataset adopted are discussed. Results are the presence of outliers, for example, for film reve- reported in Section III, with conclusions suggested nues where a big blockbuster massively outperforms in Section IV. ordinary films. In our case, there are a few albums with extremely high sales that may appear as outliers. II. Methodology and Data Data collection In November 2006, the UK Chart Company pub- Empirical methodology lished the total sales of the 100 best-selling albums in Downloaded by [Lancaster University Library] at 07:37 23 January 2013 Pareto’s law suggests the following relationship the UK for the first time, with data collated from the between size and rank: 1950s onwards. The data includes vinyl as well as CD sales, and includes greatest hits, live albums and SR ¼ A ð1Þ soundtracks. This allows researchers the opportunity or, in a natural logarithmic form to estimate the factors impacting on album success for the most popular albums. The analysis below lnðSÞ¼lnðAÞ lnðRÞð2Þ focuses on the number of albums sold (sales)asa where S is the size, R the rank and A, the measure of size, with Maddison (2004) similarly using coefficients. a count of number of Broadway performances. The relationship has been applied in a number of However, note that revenue has been used in Walls settings, including investigations into the relationship (1997) and Hand (2001), while Giles uses the number between firm size and rank (see, e.g. Steindl, 1965). of weeks in the top position
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