Bayesian Hierarchical, Semiparametric, and Nonparametric Methods for International New Product Di ffusion

Global marketing managers are keenly interested in being able to predict the salesof their new products. Understanding how a product is adopted over time allowsthe managers to optimally allocate their resources. With the world becoming evermore global, there are strong and complex interactions between the countries in theworld. My work explores how to describe the relationship between those countries anddetermines the best way to leverage that information to improve the sales predictions.In Chapter II, I describe how diffusion speed has changed over time. The mostrecent major study on this topic, by Christophe Van den Bulte, investigated newproduct di ffusions in the United States. Van den Bulte notes that a similar studyis needed in the international context, especially in developing countries. Additionally,his model contains the implicit assumption that the diffusion speed parameteris constant throughout the life of a product. I model the time component as a nonparametricfunction, allowing the speed parameter the flexibility to change over time.I find that early in the product's life, the speed parameter is higher than expected.Additionally, as the Internet has grown in popularity, the speed parameter has increased.In Chapter III, I examine whether the interactions can be described througha reference hierarchy in addition to the cross-country word-of-mouth eff ects alreadyin the literature. I also expand the word-of-mouth e ffect by relating the magnitudeof the e ffect to the distance between the two countries. The current literature only applies that e ffect equally to the n closest countries (forming a neighbor set). Thisalso leads to an analysis of how to best measure the distance between two countries. Icompare four possible distance measures: distance between the population centroids,trade ow, tourism ow, and cultural similarity. Including the reference hierarchyimproves the predictions by 30 percent over the current best model.Finally, in Chapter IV, I look more closely at the Bass Diffusion Model. It isprominently used in the marketing literature and is the base of my analysis in ChapterIII. All of the current formulations include the implicit assumption that all theregression parameters are equal for each country. One dollar increase in GDP shouldhave more of an eff ect in a poor country than in a rich country. A Dirichlet processprior enables me to cluster the countries by their regression coefficients. Incorporatingthe distance measures can improve the predictions by 35 percent in some cases.