Doctoral Thesis Marketing Modeling for New Products

Defended on Tuesday, 29 June 2010

Abstract

This thesis addresses the analysis of new or very recent marketing data and the introduction of new marketing models. We present a collection of models that are useful to analyze (1) the optimal launch time of new and dominant technologies, (2) the triggers, speed and timing of new products’ price landings, (3) the consumer heterogeneity that drives substitution patterns present in aggregate data, and  (4) the influential locations that drive the diffusion of new technologies. The econometric approaches that we apply are diverse but they are predominantly Bayesian methods. We use Bayesian mixture modelling, Bayesian variable selection techniques, Bayesian spatial models and we put forward a new Bayesian approach for the random coefficient logit model. The data that we analyze consist of unique and large datasets of video-game prices, video-game consoles’ sales, aggregate sales data for consumer products and Google’s online search data.

Keywords

marketing modeling, new products, bayesian methodology

Time frame

2006 - 2009

Preferred reference

C. Hernández-Mireles, Marketing Modeling for New Products, Promotor:Prof. dr. Philip Hans Franses, http://hdl.handle.net/1765/19878

Author

Carlos Hernandez Mireles
Carlos Hernandez Mireles

Supervisory Team

Philip Hans Franses
Professor of Applied Econometrics and Professor of Marketing Research
  • Promotor
Dennis Fok
Professor of Applied Econometrics
  • Copromotor
Richard Paap
Professor of Econometrics
  • Copromotor

Committee Members