Applications of Business Analytics in Marketing: Joint Modeling of Correlated Multivariate Outcomes

In this dissertation I develop a general regression methodology for mixed multivariate outcomes. This methodology extends the generalized linear mixed model paradigm (glmm) to allow for correlated multivariate normal random effects across regression equations for differing outcomes. This methodology, referred to as joint modeling, is particularly useful in business and marketing applications where multiple outcomes of varying data type must be analyzed simultaneously with regression.

I apply joint models to binary and continuous measures of customer loyalty in a large multinational survey of car owners. Survey respondents’ word-of-mouth and desire to switch brands were used as proxies for attitudinal loyalty and behavioral loyalty and were modeled as a function of product-related attributes, service-related attributes, marketing activities, and overall satisfaction of both their current car and alternatives together. My findings provide insights into customer loyalty in the context of both experience based loyalty and image based loyalty as well as cross-cultural consumer behavior and confirm the mediating role of satisfaction. Furthermore, I find that brand evaluation based on experience with the current brand, and alternative brand evaluations based on image both significantly affect customers’ overall satisfaction levels with varying degrees of impact. The study also identifies a significant moderating effect of culture between product-related attribute performance, service-related attributes performance, marketing activities, and satisfaction. The association between functional attribute performance and satisfaction is found to be stronger in collectivistic cultures than more individualistic cultures.

A second study focuses on gaining a better understanding of the interplay between price promotion and consumption of both hedonic and utilitarian retail grocery items. A joint model relating three key outcomes, loyalty, cross-buy, and trip revenue was fit with price promotion, consumption type, and consumer demographic characteristics as explanatory variables. The findings indicate that in-store deal use is associated with significant store loyalty, variety-seeking behavior, and trip revenue for both hedonic and utilitarian goods. More interestingly, we find that coupon use for utilitarian goods is negatively associated with store-loyalty, cross-buy (variety- seeking), and trip revenue.