International Journal of Research in Marketing | June 2017
(a) Applies readily to non-metric (discrete choice) data and (b) incorporates the ‘outside option’ or ‘none chosen’ alternative.
We develop an extension of the Bayesian semiparametric Dirichlet process method, called the Mixture of Dirichlet process (MDP) to achieve the objectives of the paper. We demonstrate our model on a set of 5 different CBC datasets having different respondent numbers, product profiles and attributes evaluated. We find the proposed model consistently outperforms the best available benchmarks in fit and predictive validity.
Sudhir Voleti is an Associate Professor of Marketing at the Indian School of Business (ISB), where he is also a distinguished faculty member in Business Analytics. A renowned researcher in the fields of marketing research and business analytics, he has previously served as Associate Dean of Faculty Alignment and the Registrar's Office (FARO) at ISB.
Professor Voleti holds a PhD in Marketing and an MS in Applied Statistics from the University of Rochester, a PGDM from Indian Institute of Management (IIM) Calcutta, and a BE from the Birla Institute of Technology, Ranchi, along with years of industry experience.
Professor Voleti is recognised as one of India's leading data science academicians. His research focuses on combining data with econometric and statistical methods to explain phenomena of marketing interest such as evolution in the equity of brands across time, valuation of brands using secondary sales data, the sales impact of geographic and abstract distances between products and markets, and the performance, productivity, and benchmarking of salesforce organisations.
Professor Voleti has published numerous research articles in leading academic journals such as Management Science, Journal of Marketing, Journal of the Royal Statistical Society, the International Journal of Research in Marketing, and the Journal of Retailing, as well as book chapters and articles in the popular media. He also serves on the editorial review boards of numerous journals. Some of his significant works include "Impact of Reference Prices on Product Positioning and Profits", "The role of big data and predictive analytics in retailing", "Why the Dynamics of Competition Matter for Category Profitability", "A Bayesian non-parametric model of residual brand equity in hierarchical branding structures", and "An Approach to Improve the Predictive power of Choice - Based Conjoint Analysis".
