Estimating Demand Heterogeneity Using Aggregated Data: An Application to the Frozen Pizza Category

References

• ACNielsen Consumer insight: New product introductions. (2001) . Consumer and Market Trends Report, ACNielsen, ChicagoGoogle Scholar
• Berry S. T., Levinsohn J., Pakes A. Automobile prices in market equilibrium. Econometrica (1995) 63(4):841–890Crossref, Google Scholar
• Berry S. T., Levinsohn J., Pakes A. Differentiated products demand systems from a combination of micro and macro data: The new car market. J. Political Econom. (2004) 112(1):68–105Crossref, Google Scholar
• Blattberg R., Wisniewski K. Priced-induced patterns of competition. Marketing Sci. (1989) 8(4):291–309Link, Google Scholar
• Bodapati A., Gupta S. The recoverability of segmentation structure from store-level aggregate data. J. Marketing Res. (2004) 41(3):351–364Crossref, Google Scholar
• Bronnenberg B. J., Mela C. F. Market roll-out and retailer adoption for new brands. Marketing Sci. (2004) 23(4):500–518Link, Google Scholar
• Carpenter G. S., Cooper L., Hanssens D. M., Midgley D. Modeling asymmetric competition. Marketing Sci. (1988) 7(4):393–412Link, Google Scholar
• Chintagunta P. K. Endogeneity and heterogeneity in a probit demand model: Estimation using aggregate data. Marketing Sci. (2001) 20(4):442–56Link, Google Scholar
• Chintagunta P. K., Dubé J.-P., Singh V. Market structure across stores: An application of a random coefficients logit model with store level data. Econom. Models Marketing (2002) 16:191–221Google Scholar
• Elrod T. Choice map: Inferring a product market map from panel data. Marketing Sci. (1988) 7(1):21–40Link, Google Scholar
• Elrod T., Keane M. P. A factor-analytic probit model for representing the market structure in panel data. J. Marketing Res. (1995) 32(1):1–16Crossref, Google Scholar
• Erdem T. A dynamic analysis of market structure based on panel data. Marketing Sci. (1996) 15(4):359–378Link, Google Scholar
• Hansen L. P. Large sample properties of generalized method of moments estimators. Econometrica (1982) 50(4):1029–1054Crossref, Google Scholar
• Hauser J. R., Tellis G. J., Griffin A. Research on innovation: A review and agenda for Marketing Science. Marketing Sci. (2006) 25(6):740–759Link, Google Scholar
• Holcomb R. Food industry overview: Frozen Pizza. (2000) . Report FAPC-103, Food and Agricultural Products Center, Oklahoma State University, StillwaterGoogle Scholar
• Imbens G. W., Lancaster T. Combining micro and macro data in microeconometric models. Rev. Econom. Studies (1994) 61(4):655–680Crossref, Google Scholar
• Kayande U., Roberts J. H., Lilien G. L., Fong D. K. H. Mapping the bounds of incoherence: How far can you go and how does it affect your brand? Marketing Sci. (2007) 26(4):504–513Link, Google Scholar
• Keller K. L., Lehman D. Brands and branding: Research findings and future priorities. Marketing Sci. (2006) 25(6):740–759Link, Google Scholar
• Luo L., Kannan P. K., Ratchford B. T. New product development under channel acceptance. Marketing Sci. (2007) 26(2):149–163Link, Google Scholar
• Musalem A., Bradlow E. T., Raju J. S. Who's got the coupon? Estimating consumer preferences and coupon usage from aggregate information. J. Marketing Res. (2008) 45(6):715–730Crossref, Google Scholar
• Nelson P., Siegfried J. J., Howell J. A simultaneous equations model of coffee brand pricing and advertising. Rev. Econom. Statist. (1992) 74(1):54–63Crossref, Google Scholar
• Nevo A. A practitioner's guide to estimation of random-coefficients logit models of demand. J. Econom. Management Strategy (2000) 9(4):513–548Crossref, Google Scholar
• Nevo A. Measuring market power in the ready-to-eat cereal industry. Econometrica (2001) 69(2):307–342Crossref, Google Scholar
• Petrin A. Quantifying the benefits of new products: The case of the Minivan. J. Political Econom. (2002) 110(4):705–729Crossref, Google Scholar
• Pizza Marketing Quarterly Rising crust pizza: Should you worry? (2000) Winter):16–18 http://www.pmq.com/digiorno.shtmlGoogle Scholar
• Shugan S. M. Estimating brand positioning maps using supermarket scanning data. J. Marketing Res. (1987) 24(1):1–18Crossref, Google Scholar
• Sriram S., Chintagunta P. K., Neelamegham R. Effects of brand preference, product attributes, and marketing mix variables in technology product markets. Marketing Sci. (2006) 25(5):440–456Link, Google Scholar
• van Heerde H., Gupta S., Wittink D. R. Is 75% of the sales promotion bump due to brand switching? No, only 33% is. J. Marketing Res. (2003) 40(4):481–491Crossref, Google Scholar
• van Heerde H., Mela C. F., Manchanda P. The dynamic effect of innovation on market structure. J. Marketing Res. (2004) 41(2):166–183Crossref, Google Scholar
• Van Oest R., Franses P. H. Which brands gain share from which brands? Inference from store-level scanner data. Quant. Marketing Econom. (2005) 3(3):281–304Crossref, Google Scholar
• Villas-Boas J. M., Winer R. Endogeneity in brand choice models. Management Sci. (1999) 45(10):1324–1338Link, Google Scholar