Skip to main content
SpringerLink
Log in

The influence of book advertising on sales in the German fiction book market

  • Original Article
  • Published:
Journal of Cultural Economics Aims and scope Submit manuscript

Abstract

Driven by the pressure to permanently release a large number of books, publishers have to allocate limited advertising budgets across the wide range of newly released books. As in many creative industries, publishers often focus their advertising activities on potential top sellers written by recent bestselling authors. Considering potential selection effects in choosing the “right” books for advertising, this paper investigates (1) whether selection effects exist and to what extent potential selection effects influence the relation between book advertising and book sales and (2) the boundary conditions under which book advertising leads to higher sales by focusing on the “star power” effects of authors. By applying propensity score matching to a dataset of 598 fiction books from the German book market, we identify substantial selection effects that lead to a serious overestimation of advertising effectiveness by up to 41 % (10,000 copies sold). Using group analyses, we find that sales of books written by recent bestselling authors are not significantly influenced by advertising activities of publishers; however, the sales of books written by lesser-known authors can be increased significantly if they are advertised. Our findings are highly relevant for publishers, indicating that a shift in the allocation of advertising budgets toward promising books by lesser-known authors is recommended to improve the overall advertising effectiveness.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Notes

  1. The relevance of the “right choice” becomes evident when considering the large number of newly released books: In the German book market, more than 80,000 new books are released each year, a high share of them (almost 19 % or 15,000 books) in the fiction category (Börsenverein 2012).

  2. Promotional activities are both independently conducted by the authors and in cooperation with publishers. In most cases, these activities do not lead to increased publisher spending (Sambeth 2008).

  3. We define a book as a bestseller if the book has entered the top 50 Spiegel bestseller list for at least 1 week. The Spiegel bestseller list is the most recognized bestseller list of the German book market (Börsenverein 2012).

  4. A nice overview of techniques that address the estimation of causal effects in comparison with propensity score matching is provided by Mithas and Krishnan (2009, Table 8, p. 309).

  5. Advertised books can be considered the experimental group exposed to the treatment “advertising” and non-advertised books as a reference group without treatment.

  6. The overlapping area should be defined before applying the matching algorithms. Different matching algorithms, such as nearest neighbor, caliper matching, or stratification matching, may be used (see Caliendo and Scheel-Kopeinig 2008 for a detailed overview of different matching algorithms).

  7. Based on expert interviews with managers of the publishing house Random House, we chose a sales volume of 1,500 as the lower limit to include bestsellers and non-bestsellers in the data so that we could control for selection effects when measuring the success factors of successful and unsuccessful books in our dataset.

  8. Please note that this study focuses on customer advertising (B2C). Moreover, many publishers use business-to-business (B2B) channels such as trade magazines (e.g., Buchreport) to communicate new book releases to market intermediaries. Typically, advertisements in trade magazines do not focus on single book titles but announce a variety of new titles from publishers’ assortments or the brand of the publisher itself.

  9. The German newspaper market is highly fragmented, with many local and regional titles and only a few national daily and weekly newspapers (AGMA 2012). With some exceptions (e.g., announcements of regional publishers), book advertising is almost exclusively conducted in national daily and weekly newspapers as well as magazines with a high proportion of readers with an affinity for books. Other media channels (e.g., radio and TV) are typically not used for book advertising but for promotional activities such as interviews and book discussions (Sambeth 2008).

  10. Detailed data on the reach and editing frequency of the selected titles are available upon request.

  11. We conducted robustness checks of our model using book groups with “high” or “low” advertising intensity based on the variable “number of announcements.” The group definition is based on a median split of the number of announcements in case of advertised books. PSM models between the non-advertised and respectively “low” and “highly” advertised books lead to consistent results to those presented in our model. In addition, no significant differences are revealed between the groups with “low” and “high” advertising intensity, indicating the adequacy of the dummy variable for capturing the advertising effect.

  12. The calculation of the mean incorporates the rater’s confidence in her or his judgment for a certain question and assigns a higher weight to raters who report having higher confidence in their ratings. We determine the value of self-confidence for each question and each book separately for all four raters (Clement et al. 2007). To avoid multicollinearity, we sum the weighted ratings of the respondents to achieve point scores for each variable.

  13. Our sample contains 11 participants rating the fame and celebrity status of 559 authors (there were 5 males and 6 females raters, with a mean of 38 and s.d. = 15 for age). Other studies also use rating measures to control for effects in case data are not available elsewhere (Eliashberg and Sawhney 1994). We double checked the data using Google and Wikipedia to learn about authors’ backgrounds and found results highly consistent with our method.

  14. Usually English; note that we focus on licensed books from abroad that enter the German market.

  15. The results of all consistency checks presented in this subsection are available upon request.

References

  • AGMA. (2012). Media-Analyse Pressemedien. Retrieved March 10, 2012 from http://www.ma-reichweiten.de.

  • Alpar, P. (1991). Knowledge-based modeling of marketing managers‘problem solving behavior. International Journal of Research in Marketing, 8(1), 5–16.

    Article  Google Scholar 

  • Ashworth, J., Heyndels, B., & Werck, K. (2010). Expert judgements and the demand for novels in flanders. Journal of Cultural Economics, 34(3), 197–218.

    Article  Google Scholar 

  • Beck, J. (2007). The sales effect of word of mouth: A model for creative goods and estimates for novels. Journal of Cultural Economics, 31(1), 5–23.

    Article  Google Scholar 

  • Berreman, J. V. (1943). Advertising and the sale of novels. Journal of Marketing, 7(3), 234–240.

    Article  Google Scholar 

  • Black, D., & Smith, J. (2004). How robust is the evidence on the effects of college quality? Evidence from matching. Journal of Econometrics, 121, 99–124.

    Article  Google Scholar 

  • Börsenverein. (2012). Buch und Buchhandel in Zahlen 2012. Frankfurt am Main: Börsenverein des Deutschen Buchhandels e.V.

  • Brown, R. (1991). Making the product portfolio a basis for action. Long Range Planning, 24(1), 102–110.

    Article  Google Scholar 

  • Caliendo, M., & Scheel-Kopeinig, S. (2008). Some practical guidance for the implementation of propensity score matching. Journal of Economic Surveys, 22(1), 31–72.

    Article  Google Scholar 

  • Caliendo, M., Clement, M., Papies, D., & Scheel-Kopeinig, S. (2012). The cost impact of spam filters: Measuring the effect of information system technologies in organizations. Information Systems Research, 23(3), 1068–1080.

    Google Scholar 

  • Caves, R. E. (2000). Creative industries. Contracts between art and commerce. Cambridge: Harvard University Press.

    Google Scholar 

  • Chevalier, J., & Goolsbee, A. (2003). Measuring prices and price competition online: Amazon.com and barnesandnoble.com. Quantitative Marketing and Economics, 1(2), 203–222.

    Article  Google Scholar 

  • Chevalier, J., & Mayzlin, D. (2006). The effect of word of mouth on sales: Online book reviews. Journal of Marketing Research, 43(August), 345–354.

    Article  Google Scholar 

  • Chintagunta, P. (2001). Endogeneity and heterogeneity in a probit demand model: Estimation using aggregate data. Marketing Science, 20(4), 442–456.

    Article  Google Scholar 

  • Chintagunta, P., Kadiyali, V., & Vilcassim, N. J. (2006). Endogeneity and simultaneity in competitive pricing and advertising: A logit demand analysis. Journal of Business, 79(6), 2761–2786.

    Article  Google Scholar 

  • Clement, M., Proppe, D., & Rott, A. (2007). Do critics make bestsellers? Opinion leaders and the success of books. Journal of Media Economics, 20(2), 77–105.

    Article  Google Scholar 

  • Danaher, P. J., Bonfrer, A., & Dhar, S. (2008). The effect of competitive advertising interference on sales for packaged goods. Journal of Marketing Research (JMR), 45(2), 211–225.

    Article  Google Scholar 

  • d’Astous, A., Colbert, F., & Mbarek, I. (2006). Factors influencing readers’ interest in new book releases: An experimental study. Poetics, 34(2), 134–147.

    Article  Google Scholar 

  • Doyle, P., & Saunders, J. (1990). Multiproduct advertising budgeting. Marketing Science, 9(2), 97–113.

    Article  Google Scholar 

  • Ebbes, P., Papies, D., & van Heerde, H. J. (2011). The sense and non-sense of holdout sample validation in the presence of endogeneity. Marketing Science, 30(6), 1115–1122.

    Article  Google Scholar 

  • Ekelund, B. G., & Börjesson, M. (2002). The shape of the literary career: An analysis of publishing trajectories. Poetics, 30(5–6), 341–364.

    Article  Google Scholar 

  • Eliashberg, J., & Sawhney, M. S. (1994). Modeling goes hollywood: Predicting individual differences in movie enjoyment. Management Science, 40(9), 1151–1173.

    Article  Google Scholar 

  • Ghose, A., Smith, M. D., & Telang, R. (2006). Internet exchanges for used books: An empirical analysis of product cannibalization and welfare impact. Information Systems Research, 17(1), 3–19.

    Article  Google Scholar 

  • Greene, W. H. (2002). Econometric analysis. New York: Prentice Hall.

    Google Scholar 

  • Heckman, J. J., Ichimura, H., & Todd, P. (1998). Matching as an econometric evaluation estimator. Review of Economic Studies, 65(2), 261–294.

    Article  Google Scholar 

  • Heckman, J. J., & Navarro-Lozano, S. (2004). Using matching, instrumental variables, and control functions to estimate economic choice models. Review of Economics and Statistics, 86, 30–57.

    Article  Google Scholar 

  • Henningsen, S., Heuke, R., & Clement, M. (2011). Determinants of advertising effectiveness: The development of an international advertising elasticity database and a meta-analysis. BuR—Business Research, 4(2), 193–239.

    Google Scholar 

  • Hirschman, E. C., & Holbrook, M. B. (1982). Hedonic consumption: Emerging concepts, methods and propositions. Journal of Marketing, 46(Summer), 92–101.

    Article  Google Scholar 

  • Hjorth-Andersen, C. (2000). A model of the danish book market. Journal of Cultural Economics, 24(1), 27–43.

    Article  Google Scholar 

  • Hjorth-Andersen, C. (2001). A model of translations. Journal of Cultural Economics, 25(2), 203–217.

    Article  Google Scholar 

  • Imbens, G. W. (2004). Nonparametric estimation of average treatment effects under exogeneity: A review. Review of Economics and Statistics, 86(1), 4–29.

    Article  Google Scholar 

  • Janssen, S., & Leemans, H. (1988). Differences in consumer behavior between buyers of literature. Poetics, 17(6), 563–575.

    Article  Google Scholar 

  • Joshi, A. M., & Hanssens, D. M. (2009). Movie advertising and the stock market valuation of studios: A case of “great expectations?” Marketing Science, 28(2), 239–250.

    Article  Google Scholar 

  • Kamphuis, J. (1991). Satisfaction with books: Some empirical findings. Poetics, 20(5–6), 471–485.

    Article  Google Scholar 

  • Kettmann, L. (2007). Expert interview, May 2007. Germany: Rowohlt Verlag.

    Google Scholar 

  • Kirmani, A., & Rao, A. R. (2000). No pain, no gain: A critical review of the literature on signaling unobservable product quality. Journal of Marketing, 64(2), 66–79.

    Article  Google Scholar 

  • Lechner, M. (2002). Program heterogeneity and propensity score matching: An application to the evaluation of active labor market policies. The Review of Economics and Statistics, 84, 205–220.

    Article  Google Scholar 

  • Lee, J., Boatwright, P., & Kamakura, W. A. (2003). A bayesian model for prelaunch sales forecasting of recorded music. Management Science, 49(2), 179–196.

    Article  Google Scholar 

  • Leemans, H., & Stokmans, M. J. W. (1991). Attributes used in choosing books. Poetics, 20(5), 487–505.

    Article  Google Scholar 

  • Leemans, H., & Stokmans, M. J. W. (1992). A descriptive model of the decision making process of buyers of books. Journal of Cultural Economics, 16(2), 25–50.

    Article  Google Scholar 

  • Leuven, E., & Sianesi, B. (2003). PSMATCH2: Stata module to perform full Mahalanobis and propensity score matching, common support graphing, and covariate imbalance testing. Statistical Software Components S432001, Boston College Department of Economics.

  • Lilien, G. L. (2011). Bridging the academic-practitioner divide in marketing decision models. Journal of Marketing, 75(4), 196–210.

    Article  Google Scholar 

  • Lohmann, C. (2007). Expert interview. Germany: Random House.

    Google Scholar 

  • Low, G. S., & Mohr, J. J. (1999). Setting advertising and promotion budgets in multi-brand companies. Journal of Advertising Research, 39(1), 67–78.

    Google Scholar 

  • Luan, Y. J., & Sudhir, K. (2010). Forecasting marketing-mix responsiveness for new products. Journal of Marketing Research (JMR), 47(3), 444–457.

    Article  Google Scholar 

  • McQuivey, J. L., & McQuivey, M. K. (1998). Is it a small publishing world after all? Media monopolization of the children’s book market, 1992–1995. Journal of Media Economics, 11(4), 35–48.

    Article  Google Scholar 

  • Mithas, S., & Krishnan, M. S. (2009). From association to causation via a potential outcomes approach. Information Systems Research, 20(2), 295–313.

    Article  Google Scholar 

  • Narayanan, S., Desiraju, R., & Chintagunta, P. K. (2004). Return on investment implications for pharmaceutical promotional expenditures: The role of marketing–mix interactions. Journal of Marketing, 68(4), 90–105.

    Article  Google Scholar 

  • Radas, S., & Shugan, S. M. (1998). Seasonal marketing and timing new product introductions. Journal of Marketing Research, 35(3), 296–315.

    Article  Google Scholar 

  • Reibstein, D. J., & Farris, P. W. (1995). Market share and distribution: A generalization, a speculation, and some implications. Marketing Science, 14(3), G190–G202.

    Article  Google Scholar 

  • Rosenbaum, P. R. (2002). Observational studies. New York: Springer.

    Book  Google Scholar 

  • Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Econometrica, 70(1), 41–55.

    Google Scholar 

  • Rosenbaum, P. R., & Rubin, D. B. (1985). Constructing a control group using multivariate matched sampling methods that incorporate the propensity score. The American Statistician, 39, 33–38.

    Google Scholar 

  • Rossiter, J. R. (2012). Advertising management principles are derived mostly from logic and very little from empirical generalizations. Marketing Theory, 12(2), 103–116.

    Article  Google Scholar 

  • Roy, A. (1951). Some thoughts on the distribution of earnings. Oxford Economic Papers, 3(2), 135–145.

    Google Scholar 

  • Rubin, D. (1974). Estimating causal effects to treatments in randomised and nonrandomised studies. Journal of Educational Psychology, 66, 688–701.

    Article  Google Scholar 

  • Rubin, D., & Thomas, N. (1966). Matching using estimated propensity scores: Relating theory to practice. Biometrics, 52(1), 249–264.

    Article  Google Scholar 

  • Sambeth, F. (2008). Expert interview. Germany: Random House.

    Google Scholar 

  • Schmidt-Stölting, C., Blömeke, E., & Clement, M. (2011). Success drivers of fiction books: An empirical analysis of hardcover and paperback editions in Germany. Journal of Media Economics, 24(1), 24–47.

    Article  Google Scholar 

  • Sethuraman, R., Tellis, G. J., & Briesch, R. A. (2011). How well does advertising work? Generalizations from meta-analysis of brand advertising elasticities. Journal of Marketing Research (JMR), 48(3), 457–471.

    Article  Google Scholar 

  • Shankar, V. (2008). Strategic allocation of marketing resources: Methods and managerial insights. Marketing Science Institute Report [08-207].

  • Sianesi, B. (2004). An evaluation of swedish system of active labour market programmes in the 1990 s. The Review of Economic and Statistics, 86(1), 133–155.

    Article  Google Scholar 

  • Silverman, B. W. (1986). Density estimation for statistics and data analysis. London: Chapman and Hall.

    Book  Google Scholar 

  • Sorensen, A. T., & Rasmussen, S. J. (2004). Is any publicity good publicity? A note on the impact of book reviews. Working Paper at Stanford University.

  • Stock, J. H., Wright, J. H., & Yogo, M. (2002). A survey of weak instruments and weak identification in generalized method of moments. Journal of Business Statistics and Economic Statistics, 20, 518–529.

    Article  Google Scholar 

  • Talukdar, D., Sudhir, K., & Ainslie, A. (2002). Investigating new product diffusion across products and countries. Marketing Science, 21(1), 97–114.

    Article  Google Scholar 

  • Tellis, G. J., Stremersch, S., & Yin, E. (2003). The international takeoff of new products: The role of economics, culture, and country innovativeness. Marketing Science, 22(2), 188–208.

    Article  Google Scholar 

  • van Bruggen, G. H., Lilien, G. L., & Kacker, M. (2002). Informants in organizational marketing research: Why use multiple informants and how to aggregate responses. Journal of Marketing Research, 39(November), 469–478.

    Article  Google Scholar 

  • Vogel, H. L. (2011). Entertainment industry economics (8th edn.). Cambridge: Cambridge University Press.

  • Wind, Y., & Mahajan, V. (1981). Designing product and business portfolios. Harvard Business Review, 59(1), 155–165.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute for Marketing and Media, Research Center for Media and Communication, University of Hamburg, Welckerstr. 8, 20354, Hamburg, Germany

    Edlira Shehu, Tim Prostka, Christina Schmidt-Stölting, Michel Clement & Eva Blömeke

Authors
  1. Edlira Shehu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tim Prostka
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Christina Schmidt-Stölting
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Michel Clement
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Eva Blömeke
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Michel Clement.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Shehu, E., Prostka, T., Schmidt-Stölting, C. et al. The influence of book advertising on sales in the German fiction book market. J Cult Econ 38, 109–130 (2014). https://doi.org/10.1007/s10824-013-9203-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10824-013-9203-0

Keywords

JEL Classification

Search

Navigation