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Herding in the consumption and purchase of digital goods and moderators of the herding bias

  • Original Empirical Research
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Abstract

Digital goods are increasingly produced by average individuals in a serialized fashion. However, it is unclear whether users engage in herding in the consumption and purchase of such digital goods and what the moderators of the herding effect are. Thus, we propose a simultaneous equations model based on herding theory to theoretically examine users’ potential herding behavior through two competing effects: the private signal effect and the sequential actions effect, which refer to the impact of the private signals and observed sequential actions of others on user quality inference and herding, respectively. The model is implemented in a hierarchical Bayes framework, and it is estimated using data from the top Chinese literature site. The empirical results suggest that users engage in rational herding in both digital book consumption and purchase on the focal site and that the herding bias is surprisingly stronger for purchasing. Product features significantly mitigate the herding bias, while the reputation of the producer and competition exacerbate the herding effect. The impact of this rational herding is also quantified. This study offers new insights and important theoretical and managerial implications for marketing researchers, amateur producers, marketing managers, and publishers.

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Notes

  1. Social influence or contagion refers to the spread of ideas, attitudes, or behavior patterns in a group through imitation and conformity (Colman 2014). Imitation is an advanced behavior whereby an individual observes and replicates another’s behavior. Therefore, herding is one specific type of informational social influence or imitation where the two conditions (the uncertainty condition and the sequential action condition) must be satisfied. Social contagion and imitation do not necessarily lead to herding.

  2. We used two popular text analyzers for Chinese characters on some book chapters from the site—the Chinese parser developed by the Stanford Natural Language Processing Group (http://nlp.stanford.edu/software/lex-parser.html) and yoshikoder software developed by Will Lowe at Harvard’s Weatherhead Center for International Affairs (http://yoshikoder.sourceforge.net/). Unfortunately, we found that the accuracy of these text analysis tools is low and unreliable, and this textual analysis was overwhelmingly time-consuming.

References

  • Akerlof, G. A. (1970). The market for ‘lemons’: quality uncertainty and the market mechanism. Quarterly Journal of Economics, 84(3), 488–500.

    Article  Google Scholar 

  • Anthony, J. (2012). The challenge of e-book growth in international markets. Publishing Research Quarterly, 28(October), 273–284.

    Article  Google Scholar 

  • Banerjee, A. (1992). A simple model of herd behavior. Quarterly Journal of Economics, 107(3), 797–817.

    Article  Google Scholar 

  • Bikhchandani, S., & Sharma, S. (2000). Herd behavior in financial markets? IMF Staff Papers, 47(3), 279–310.

    Google Scholar 

  • Bikhchandani, S., Hirshlleifer, D., & Welch, I. (1992). Theory of fads, fashion, custom, and cultural change as information cascades. Journal of Political Economy, 100(5), 992–1026.

    Article  Google Scholar 

  • Chen, Y. (2008). Herd behavior in purchasing books online. Computers in Human Behavior, 24, 1977–1992.

    Article  Google Scholar 

  • Chen, Y., Wang, Q., & Xie, J. (2011). Online social interactions: a natural experiment on word of mouth versus observational learning. Journal of Marketing Research, (April), 238–254.

  • Cipriani, M., & Guarino, A. (2005). Herd behavior in a laboratory financial market. American Economic Review, 95(5), 1427–1443.

    Article  Google Scholar 

  • Cipriani, M., & Guarino, A. (2014). Estimating a structural model of herd behavior in financial markets. American Economic Review, 104(1), 224–251.

    Article  Google Scholar 

  • Colman, A. M. (2014). A dictionary of psychology. Oxford University Press. http://www.oxfordreference.com/view/10.1093/acref/9780199534067.001.0001/acref-9780199534067-e-7741.

  • Conley, T. G., Hansen, C. B., & Rossi, P. E. (2012). Plausibly exogenous. The Review of Economics and Statistics, 94(1), 260–272.

    Article  Google Scholar 

  • Dawar, N., & Parker, P. (1994). Marketing universals: consumers’ use of brand name, price, physical appearance, and retailer reputation as signals of product quality. Journal of Marketing, 58(2), 81–95.

    Google Scholar 

  • Desai, P. (2000). Multiple messages to retain retailers: signaling new product demand. Marketing Science, 19(4), 381–389.

    Article  Google Scholar 

  • Devenow, A., & Welch, I. (1996). Rational herding in financial economics. European Economic Review, 40, 603–615.

    Article  Google Scholar 

  • Dhar, T., Sun, G., & Weinberg, C. B. (2012). The long-term box office performance of sequel movies. Marketing Letters, 23(1), 13–29.

    Article  Google Scholar 

  • Dholakia, U. M., & Soltysinski, K. (2001). Coveted or overlooked? The psychology of bidding for comparable listings in digital auctions. Marketing Letters, 12(3), 225–237.

    Article  Google Scholar 

  • Dholakia, U. M., Basuroy, S., & Soltysinski, K. (2002). Auction or agent (or both)? A study of moderators of the herding bias in digital auctions. International Journal of Research in Marketing, 19, 115–130.

    Article  Google Scholar 

  • Drehmann, M., Oechssler, J., & Roider, A. (2005). Herding and contrarian behavior in financial markets: an internet experiment. American Economic Review, 95(5), 1403–1426.

    Article  Google Scholar 

  • Duan, W., Gu, B., & Whinston, A. B. (2009). Informational cascades vs. network externalities: an empirical investigation of herding on software downloading. MIS Quarterly, 33(1), 23–48.

    Article  Google Scholar 

  • Easydigitaldownloads. (2018). The 12 most popular digital products you can sell online. Available at https://easydigitaldownloads.com/blog/the-12-most-popular-digital-products-you-can-sell-online/.

  • Engel, J. F., Kollat, D. T., & Blackwell, R. D. (1968). Consumer behavior (1st ed.). New York: Holt, Rinehart and Winston.

    Google Scholar 

  • Graham, J. R. (1999). Herding among investment newsletters: theory and evidence. Journal of Finance, LIV(1), 237–268.

    Article  Google Scholar 

  • Hagedorn, R. (1995). Doubtless to be continued: A brief history of serial narrative: Chapter of to be continued: Soap operas around the world, Routledge, 27–48. Available at http://readinglists.le.ac.uk/items/BA6299BE-F0F0-76FF-CD79-0C7408AFDB38.html.

  • Hamilton, W. D. (1971). Geometry for the selfish herd. Journal of Theoretical Biology, 31, 295–311.

    Article  Google Scholar 

  • Herzenstein, M., Dholakia, U. M., & Andrews, R. L. (2011). Strategic herding behavior in peer-to-peer loan auctions. Journal of Interactive Marketing, 25, 27–36.

    Article  Google Scholar 

  • Ho, E., Kowatsch, T., & Llic, A. (2014). The sales velocity effect on retailing. Journal of Interactive Marketing, 28(4), 237–256.

    Article  Google Scholar 

  • Huang, J. H., & Chen, Y. F. (2006). Herding in online product choice. Psychology & Marketing, 23(5), 413–428.

    Article  Google Scholar 

  • Kalra, A., & Li, S. (2008). Signaling quality through specialization. Marketing Science, 27(2), 168–184.

    Article  Google Scholar 

  • Keynes, J. M. (1930). A treatise on money. London: Macmillan.

    Google Scholar 

  • Khanna, N., & Mathews, R. D. (2011). Can herding improve investment decisions? RAND Journal of Economics, 42(1), 150–174.

    Article  Google Scholar 

  • Krastel, Z. (2015). Investigating the influence of the herding effect on consumption experience: the case of online music. Available at https://spectrum.library.concordia.ca/979897/.

  • Langley, D. J., Hoeve, M. C., Ortt, J. R., Pals, N., & van der Vecht, B. (2014). Patterns of herding and their occurrence in an online setting. Journal of Interactive Marketing, 28, 16–25.

    Article  Google Scholar 

  • Lee, Y. J., Hosanagar, K., & Tan, Y. (2015). Do I follow my friends or the crowd? Information cascades in online movie ratings. Management Science, 61(9), 2241–2258.

    Article  Google Scholar 

  • Li, Y. (2016). Online fiction becomes Chinese cultural force. The Wall Street Journal, July 20.

  • Li, S., Srinivasan, K., & Sun, B. (2009). Internet auction features as quality signals. Journal of Marketing, 73(January), 75–92.

    Article  Google Scholar 

  • Li, S., Liechty, J. C. & Montgomery, A. L. (2017). Modeling category viewership of web users with multivariate count models. Working paper, Kelley School of Business, Indiana University.

  • Liu, T., & Schiraldi, P. (2012). New product launch: herd seeking or herd preventing? Economic Theory, 51, 627–648.

    Article  Google Scholar 

  • Liu, C. Z., Au, Y. A., & Choi, H. S. (2014). Effect of freemium strategy in the mobile app market: an empirical study of Google play. Journal of Management Information Systems, 31(3), 326–354.

    Article  Google Scholar 

  • Manchanda, P., Rossi, P., & Chintagunta, P. (2004). Response modeling with nonrandom marketing mix variables. Journal of Marketing Research, 41(4), 467–478.

    Article  Google Scholar 

  • Melissas, N. (2005). Herd behavior as an incentive scheme. Economic Theory, 26, 517–536.

    Article  Google Scholar 

  • PWC US. (2017). PwC’s entertainment & media outlook forecasts U.S. industry spending to reach $759 billion by 2021. Available at https://www.prnewswire.com/news-releases/pwcs-entertainment%2D%2Dmedia-outlook-forecasts-us-industry-spending-to-reach-759-billion-by-2021-300469724.html.

  • Raafat, R. M., Chater, N., & Frith, C. (2009). Herding in humans. Trends in Cognitive Sciences, 13(10), 420–428.

    Article  Google Scholar 

  • Rizzelo, S. (2004). Knowledge as a path-dependence process. Journal of Bioeconomics, 6, 255–274.

    Article  Google Scholar 

  • Schmittlein, D. C., Morrison, D. G., & Colombo, R. (1987). Counting your customers: who are they and what will they do next? Management Science, 33(1), 1–24.

    Article  Google Scholar 

  • Sgroi, D. (2003). The right choice at the right time: a herding experiment in endogenous time. Experimental Economics, 6, 159–180.

    Article  Google Scholar 

  • Simonsohn, U., & Ariely, D. (2008). When rational sellers face nonrational buyers: evidence from herding on eBay. Management Science, 54(9), 1624–1637.

    Article  Google Scholar 

  • Spyrou, S. (2013). Herding in financial markets: a review of the literature. Review of Behavioral Finance, 5(2), 175–194.

    Article  Google Scholar 

  • Streitfeld, D. (2014). Web fiction, serialized and social. The New York Times, March 23, 2014.

  • Tucker, C., & Zhang, J. (2011). How does popularity information affect choices? A field experiment. Management Science, 57(5), 828–842.

    Article  Google Scholar 

  • Villas-Boas, J. M., & Winer, R. S. (1999). Endogeneity in brand choice models. Marketing Science, 45(10), 1324–1338.

    Google Scholar 

  • www.china.com.cn. (2012). Qidian.com accounts for 43.8% market share in the online literary market, May 8, 2012.

  • Zalmanson, L., & Oestreicher-Singer, G. (2016). Turning content viewers into subscribers. MIT Sloan Management Review, 57(3), 10–13.

    Google Scholar 

  • Zhang, J. (2010). The sound of silence: observational learning in the U.S. kidney market. Marketing Science, 29(2), 315–335.

    Article  Google Scholar 

  • Zhang, J., & Liu, P. (2012). Rational herding in microloan markets. Management Science, 58(5), 892–912.

    Article  Google Scholar 

  • Zhang, J., Liu, Y., & Chen, Y. (2018). Social learning in networks of friends versus strangers. Marketing Science, 34(4), 573–589.

    Article  Google Scholar 

Download references

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Authors and Affiliations

  1. Kelley School of Business, Indiana University, 1309 E. 10th Street, Bloomington, IN, 47405, USA

    Amy Wenxuan Ding & Shibo Li

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  1. Amy Wenxuan Ding
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  2. Shibo Li
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Correspondence to Amy Wenxuan Ding.

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Ding, A.W., Li, S. Herding in the consumption and purchase of digital goods and moderators of the herding bias. J. of the Acad. Mark. Sci. 47, 460–478 (2019). https://doi.org/10.1007/s11747-018-0619-0

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