A Dynamic Structural Model of User Learning in Mobile Media Content
Consumer adoption and usage of mobile communication and multimedia content services has been growing steadily over the past few years in many countries around the world. In this paper, we develop and estimate a structural model of user behavior and learning with regard to content generation and usage activities in mobile digital media environments. Users learn about two different categories of content: content from regular Internet social networking and community (SNC) sites and that from mobile portal sites. Then they can choose to engage in the creation (uploading) and consumption (downloading) of multi-media content from these two categories of websites. In our context, users have two sources of learning about content quality: (i) direct experience through their own content creation and usage behavior and (ii) indirect experience through word-of-mouth such as the content creation and usage behavior of their social network neighbors. Our model seeks to explicitly explain how direct and indirect experiences from social interactions influence the content creation and usage behavior of users over time. We estimate this model using a unique dataset of consumers mobile media content creation and usage behavior over a 3-month time period. Our estimates suggest that when it comes to user learning from direct experience, the content that is downloaded from mobile portals has the highest level of quality. In contrast, content that is downloaded by users from SNC websites has the lowest level of quality. Besides, the order of magnitude of signal accuracy for each content type from the direct experience is consistent with the order of true quality level. This finding implies that in the context of mobile media users make content choices based on their perception of differences in both content quality level and content quality variation. Further we find that signals about the quality of content from direct experience are more accurate than signals from indirect experiences. Potential implications for mobile phone operators and advertisers are discussed.
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- Aguirregabiria, Victor & Mira, Pedro, 2010.
"Dynamic discrete choice structural models: A survey,"
Journal of Econometrics,
Elsevier, vol. 156(1), pages 38-67, May.
- Pedro Mira & Victor Aguirregabiria, 2007. "Dynamic Discrete Choice Structural Models: A Survey," Working Papers wp2007_0711, CEMFI.
- Victor Aguirregabiria & Pedro mira, 2007. "Dynamic Discrete Choice Structural Models: A Survey," Working Papers tecipa-297, University of Toronto, Department of Economics.
- Nair, Harikesh S. & Manchanda, Puneet & Bhatia, Tulikaa, 2006. "Asymmetric Peer Effects in Physician Prescription Behavior: The Role of Opinion Leaders," Research Papers 1970, Stanford University, Graduate School of Business.
- Tülin Erdem & Michael P. Keane, 1996. "Decision-Making Under Uncertainty: Capturing Dynamic Brand Choice Processes in Turbulent Consumer Goods Markets," Marketing Science, INFORMS, vol. 15(1), pages 1-20.
- Mark Israel, 2005. "Services as Experience Goods: An Empirical Examination of Consumer Learning in Automobile Insurance," American Economic Review, American Economic Association, vol. 95(5), pages 1444-1463, December.
- Keane, Michael P & Wolpin, Kenneth I, 1994.
"The Solution and Estimation of Discrete Choice Dynamic Programming Models by Simulation and Interpolation: Monte Carlo Evidence,"
The Review of Economics and Statistics,
MIT Press, vol. 76(4), pages 648-72, November.
- Michael P. Keane & Kenneth I. Wolpin, 1994. "The solution and estimation of discrete choice dynamic programming models by simulation and interpolation: Monte Carlo evidence," Staff Report 181, Federal Reserve Bank of Minneapolis.
- Ernst R. Berndt & Bronwyn H. Hall & Robert E. Hall & Jerry A. Hausman, 1974. "Estimation and Inference in Nonlinear Structural Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 4, pages 653-665 National Bureau of Economic Research, Inc.
- Tülin Erdem & Michael Keane & T. Öncü & Judi Strebel, 2005. "Learning About Computers: An Analysis of Information Search and Technology Choice," Quantitative Marketing and Economics, Springer, vol. 3(3), pages 207-247, September.
- Nitin Mehta & Xinlei (Jack) Chen & Om Narasimhan, 2008. "Informing, Transforming, and Persuading: Disentangling the Multiple Effects of Advertising on Brand Choice Decisions," Marketing Science, INFORMS, vol. 27(3), pages 334-355, 05-06.
- Tülin Erdem & Michael P. Keane & Baohong Sun, 2008. "A Dynamic Model of Brand Choice When Price and Advertising Signal Product Quality," Marketing Science, INFORMS, vol. 27(6), pages 1111-1125, 11-12.
- Ackerberg, Daniel A, 2001. "Empirically Distinguishing Informative and Prestige Effects of Advertising," RAND Journal of Economics, The RAND Corporation, vol. 32(2), pages 316-33, Summer.
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