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Meta-analyses using information reweighting: An application to online advertising

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  • Pengyuan Wang
  • Eric Bradlow
  • Edward George

Abstract

Because technology-enabled marketing research has led to information arriving at a rapid pace, methods in marketing that allow for coherent, sequential and fast information integration are needed. We propose in this research a new approach to information integration: Information Reweighted Priors (IRPs). It is a sample reweighting approach which utilizes the output from a Bayesian model fit using Markov Chain Monte Carlo, with no restrictions on the likelihood, prior distributions, or data structure; hence a general purpose tool. We demonstrate the approach with simulated datasets and an online advertising dataset with external information obtained from i) previous advertising studies in the industry from a major online advertising portal, ii) past academic studies of online adverting and iii) out-of-sample summaries of the dataset. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Pengyuan Wang & Eric Bradlow & Edward George, 2014. "Meta-analyses using information reweighting: An application to online advertising," Quantitative Marketing and Economics (QME), Springer, vol. 12(2), pages 209-233, June.
    • Handle: RePEc:kap:qmktec:v:12:y:2014:i:2:p:209-233
    DOI: 10.1007/s11129-014-9145-7
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    1. Wendy W. Moe & Peter S. Fader, 2004. "Dynamic Conversion Behavior at E-Commerce Sites," Management Science, INFORMS, vol. 50(3), pages 326-335, March.
    2. Marshall P. & Bradlow E.T., 2002. "A Unified Approach to Conjoint Analysis Models," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 674-682, September.
    3. O'Donnell, Christopher J. & Coelli, Timothy J., 2005. "A Bayesian approach to imposing curvature on distance functions," Journal of Econometrics, Elsevier, vol. 126(2), pages 493-523, June.
    4. Dubas, Justin M. & Lee, Byung-Joo & Mark, Nelson C., 2010. "A multinomial logit approach to exchange rate policy classification with an application to growth," Journal of International Money and Finance, Elsevier, vol. 29(7), pages 1438-1462, November.
    5. Michel Wedel & Rik Pieters, 2000. "Eye Fixations on Advertisements and Memory for Brands: A Model and Findings," Marketing Science, INFORMS, vol. 19(4), pages 297-312, October.
    6. Buckley, Patrick G., 1988. "Nested multinomial logit analysis of scanner data for a hierarchical choice model," Journal of Business Research, Elsevier, vol. 17(2), pages 133-154, September.
    7. Greg M. Allenby & Peter E. Rossi, 1991. "Quality Perceptions and Asymmetric Switching Between Brands," Marketing Science, INFORMS, vol. 10(3), pages 185-204.
    8. Gulgun Yildiz Tiryaki & Cuma Akbay, 2010. "Consumers’ fluid milk consumption behaviors in TURKEY: an application of multinomial logit model," Quality & Quantity: International Journal of Methodology, Springer, vol. 44(1), pages 87-98, January.
    9. Eugene D. Hahn, 2006. "Re‐examining informative prior elicitation through the lens of Markov chain Monte Carlo methods," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(1), pages 37-48, January.
    10. Dan Horsky & Sanjog Misra & Paul Nelson, 2006. "Observed and Unobserved Preference Heterogeneity in Brand-Choice Models," Marketing Science, INFORMS, vol. 25(4), pages 322-335, 07-08.
    11. Garrett Sonnier & Andrew Ainslie & Thomas Otter, 2007. "Heterogeneity distributions of willingness-to-pay in choice models," Quantitative Marketing and Economics (QME), Springer, vol. 5(3), pages 313-331, September.
    12. Andrés Musalem & Eric T. Bradlow & Jagmohan S. Raju, 2009. "Bayesian estimation of random‐coefficients choice models using aggregate data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(3), pages 490-516, April.
    13. Peter J. Lenk & Wayne S. DeSarbo & Paul E. Green & Martin R. Young, 1996. "Hierarchical Bayes Conjoint Analysis: Recovery of Partworth Heterogeneity from Reduced Experimental Designs," Marketing Science, INFORMS, vol. 15(2), pages 173-191.
    14. Peter J. Lenk & Ambar G. Rao, 1990. "New Models from Old: Forecasting Product Adoption by Hierarchical Bayes Procedures," Marketing Science, INFORMS, vol. 9(1), pages 42-53.
    15. Lybbert, Travis J. & Barrett, Christopher B. & McPeak, John G. & Luseno, Winnie K., 2007. "Bayesian Herders: Updating of Rainfall Beliefs in Response to External Forecasts," World Development, Elsevier, vol. 35(3), pages 480-497, March.
    16. Winkler R. L. & Smith J. E. & Fryback D. G., 2002. "The Role of Informative Priors in Zero-Numerator Problems: Being Conservative Versus Being Candid," The American Statistician, American Statistical Association, vol. 56, pages 1-4, February.
    17. MacEachern, Steven N. & Peruggia, Mario, 2000. "Subsampling the Gibbs sampler: variance reduction," Statistics & Probability Letters, Elsevier, vol. 47(1), pages 91-98, March.
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    More about this item

    Keywords

    Information integration; Prior reweighting; Advertising; Informative priors; Statistical computing; C11 - Bayesian Analysis: General; M31 - Marketing; M37 - Advertising;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • M37 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Advertising

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