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Drivers of demand for management literature

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Abstract

This study investigates the successful creation of specialized books in management literature, by focusing on consumer demand for expert knowledge in business topics. Applying a sales-ranks conversion model based on a sample of 60,000 books from Amazon.de, I test hypotheses on the effects of (1) author characteristics (professional background, reputation, experience, demographics), (2) book characteristics (publisher, price, page count, reading excerpts, cover), and (3) promotional activities (recommendations, reviews, discussions) on book sales for a sample of 1,435 management books. Data were collected from the Amazon website using Perl-based scripts. The regression results demonstrate that demand for management knowledge depends on a mix of these factors; yet, success is largely determined by author characteristics. In fact, the market’s perception of the author alters consumers’ price sensitivity and renders observable book characteristics insignificant; promotional activities amplify this effect. The paper shows how to target demand for management knowledge more effectively.

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Notes

  1. This causal linkage must have inspired management scholars Michael Treacy and Fred Wiersema in 1995, when they decided to order 50,000 copies of the business strategy book ‘The Discipline of Market Leaders’ from US stores—secretly, as the book was their own work. Admittedly, these stores were the ones whose sales counted for the bestseller list of the New York Times. As a result, their book found its way onto the bestseller list notwithstanding the mediocre reviews it had received before. After this promotional act, the book became a bestseller even ‘without further demand intervention by the authors’ (Bikhchandani et al. 1998).

  2. Butler et al. (2005) presented evidence that books recommended by Oprah Winfrey’s US TV show received a boost in popularity and sales. I used a dummy indicating whether a book appeared in one of the three leading German literature TV shows in the month before data collection, and another dummy indicating whether an author had received a literary prize in the last 2 years (Noble Prize, Pulitzer Prize, Georg Büchner Prize, Ingeborg Bachmann Prize, Peace Prize of the German Book Trade using data from the broadcasting and organizations’ websites and press releases). However, management books almost never won anything, and the results are inconclusive.

  3. A simple way to gain a better sense of the relative utility of the log-linear and the log–log models involves a comparison of the R2 values (Hiscox 2002; see Tables 5 and 8). For both models the pattern of results is the same, yet the log-linear model performs much better than the log–log model (adj. R2 of 0.512 vs. 0.406). To further discriminate between the two models, Davidson and MacKinnon’s (1981, 1993) ‘J test’ is used to assess H0 (the log–log model is appropriate) against H1 (the log-linear model is appropriate) by an indirect linear combination of the two models. The test is conducted by estimating a combination of the log–log model and the predicted values from the log-linear model, where αi is the weight on the log-linear model; if H0 is true, then the true value of αi is zero, and the procedure is simply reversed to test for whether H1 can be rejected (Gujarati 2003; Hiscox 2002). Here, the weight on the log-linear model αi is strongly significant (p < 0.01), whereas the log–log weight is not (p = 0.114), so clearly the log-linear model dominates the log–log model in terms of specification quality and explains more of the variation in book sales.

  4. Possibly, the insignificance of some variables partly comes from the fact that e.g., ‘being German’ or ‘being male’ is very prevalent in the data set, so this is rather a ‘standard’ category than a mark of distinction. These issues could be explored in other settings.

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  1. Westfälische Wilhelms-Universität Münster, Institute of Strategic Management, Leonardo-Campus 18, 48149, Münster, Germany

    Brinja Meiseberg

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Correspondence to Brinja Meiseberg.

Appendix

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Table 8 Robustness checks: results
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Meiseberg, B. Drivers of demand for management literature. J Bus Econ 84, 1051–1085 (2014). https://doi.org/10.1007/s11573-014-0712-x

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