Econometric models in marketing
著者
書誌事項
Econometric models in marketing
（Advances in econometrics : a research annual / editors, R.L. Basmann, George F. Rhodes, Jr, v. 16）
JAI Press, 2002
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注記
Includes bibliographical references
内容説明・目次
内容説明
In the 16th Edition of "Advances in Econometrics", we present twelve papers discussing the current interface between Marketing and Econometrics. The authors are leading scholars in the fields and introduce the latest models for analysing marketing data. The papers are representative of the types of problems and methods that are used within the field of marketing. Marketing focuses on the interaction between the firm and the consumer. Economics encompasses this interaction as well as many others. Economics, along with psychology and sociology, provides a theoretical foundation for marketing. Given the applied nature of marketing research, measurement and quantitative issues arise frequently. Quantitative marketing tends to rely heavily upon statistics and econometrics. However, quantitative marketing can place a different emphasis upon the problem than econometrics, even when using the same techniques. A basic difference between quantitative marketing research and econometrics tends to be the pragmatism that is found in many marketing studies. Another important motivating factor in marketing research is the type of data that is available. Applied econometrics tends to rely heavily on data collected by governmental organizations. In contrast, marketing often uses data collected by private firms or marketing research firms. Observational and survey data are quite similar to those used in econometrics. However, the remaining types of data, panel and transactional, can look quite different from what may be familiar to econometricians. The automation and computerization of much of the sales transaction process leaves an audit trail that results in huge quantities of data. A popular area of study is the use of scanner data collected at the checkout stand using bar code readers. Methods that work for small data sets may not work well in these larger data sets. In addition, new sources of data, such as clickstream data from a web site, will offer new challenges. This volume addresses these and related issues.
目次
Introduction (P.H. Franses, A.L. Montgomery). The role of stated intentions in new product purchase forecasting (C. Hsiao, B. Sun, V.G. Morwitz). Discrete choice models incorporating revealed preferences and psychometric data (S. Chib, P.B. Seetharaman, A. Strijnev). Advances in Optimum experimental design for conjoint analysis and discrete choice models (H. Grosmann, H. Holling, R. Schwabe). A decision theoretic framework for profit maximization in direct marketing (L. Muus, H. van der Scheer, T. Wansbeek). New and improved direct marketing: a non-parametric approach (J.S. Racine). Estimating market level multiplicative models of promotion effects with linearly aggregated data: a parametric approach. (A.C. Bemmaor, U. Wagner). Market structure across stores: an application of a random coefficients logit model with store level data (P. Chintagunta, J.P. Dube, V. Singh). Econometric analysis of the market share attraction model (D. Fok, P.H. Franses, R. Paap). Reflecting uncertainty about econometric theory when estimating consumer demand (A. Montgomery). A study of spurious regression and model discrimination in the generalized bass model (F.M. Bass, S. Srinivasan). Using stochastic frontier analysis for performance measurement and benchmarking (L.J. Parsons).
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