Knowledge that Transforms

Kim, Fong, and DeSarbo (2012) recently introduced a finite mixture Bayesian regression model to simultaneously identify market segments of consumers (heterogeneity) and determine how such segments differ with respect to active regression coefficients (variable selection). The current manuscript introduces three extensions of their model to incorporate managerial restrictions (constraints). We demonstrate with synthetic data that the new constrained finite mixture Bayesian regression models can be gainfully employed to identify and represent several constrained heterogeneous response patterns commonly encountered in practice. In addition, we illustrate that the proposed models are more robust against multicollinearity than traditional methods. Finally, to illustrate their usefulness, we apply the proposed constrained models in the context of a service quality (SERVPERF) survey of the National Insurance Company’s customers.

“Hard-discounters” have become a considerable force within grocery retailing. With rock-bottom prices and minimal assortments, they strongly differ from “large-discounters” like Wal-Mart, and constitute complements rather than substitutes for more traditional supermarkets. Hence, we propose that their impact-of-entry on local incumbents is very different as well. Using a store choice and spending model that explicitly accounts for inter-store synergies and “multiple-store shopping” behavior, we study consumer responses to 194 hard-discounter openings. While we find that hard-discounters, like large-discounters, especially appeal to private label-prone shoppers and lead to sizable incumbent losses, the results confirm that the nature of these losses is strikingly different. First, hard-discounters do not make incumbent chains lose their best customers but, rather, shoppers who already visited other chains alongside the incumbent. Second, we find that chains located in close proximity of new hard-discounters do not suffer more from their entry. Third, losses are lower for upscale chains and incumbents that strongly complement the hard-discounter. Implications for proper response to hard-discounter entry are discussed.

The authors propose that static visuals can evoke a perception of movement (i.e., dynamic imagery) and thereby affect consumer engagement and attitudes. Focusing on brand logos as the static visual element, the authors measure the perceived movement evoked by the logo and demonstrate that the evoked dynamic imagery affects the level of consumer engagement with the brand logo. They measure consumer engagement through both self-report measures and eye-tracking technology and find that engagement affects consumer attitudes toward the brand. The authors also show that the perceived movement–engagement–attitude effect is moderated by the congruence between perceived movement and brand characteristics. These findings suggest that dynamic imagery is an important aspect of logo design, and if used carefully, it can enhance brand attitudes.