Marketing Modeling for New Products Defended on Tuesday, 29 June 2010
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.
marketing modeling, new products, bayesian methodology
Hernández-Mireles, C. (2010, June 29). Marketing Modeling for New Products (No. EPS-2010-202-MKT). ERIM Ph.D. Series Research in Management. Erasmus Research Institute of Management. Retrieved from hdl.handle.net/1765/19878