Decision makers in dynamic environments such as air traffic control, firefighting, and call center operations adapt in real-time using outcome feedback. Understanding this adaptation is important for influencing and improving the decisions made. Recently, stimulus-response (S-R) learning models...

We introduce a diffusion of innovation model based on a network threshold approach. Realistic network and threshold data were gathered regarding the diffusion of new software tools within part of a large organization. Novel model features are a second threshold for innovation rejection and a...

Choice-based conjoint analysis has increased in popularity in recent years among marketing practitioners. The typical practice is to estimate choice-based conjoint models at the aggregate level, given insufficient data for individual-level estimation of part-worths. We discuss a method for...

A criticism of purchase-based brand loyalty measures is that they are confounded by the marketing mix variables that affect brand choice. This paper investigates the magnitude and direction of the associations for share of category requirements (SCR), defined as each brand's share among the...

We propose an approach for deriving joint space maps of bundle compositions and market segments from three-way (e.g., consumers x product options/benefits/features x usage situations/scenarios/time periods) pick-any/J data. The proposed latent structure multidimensional scaling procedure...

We consider M transmitting stations sending packets to a single receiver over a slotted time-multiplexed link. For each phase consisting of T consecutive slots, the receiver dynamically allocates these slots among the M transmitters. Our objective is to characterize policies that minimize the...

In many Internet commerce applications buyers can easily achieve anonymity, limiting what a seller can learn about any buyer individually. However, because sellers need to keep a fixed web address, buyers can probe them repeatedly or pool their information about sellers with the information...

This paper discusses the issues in estimating the effects of marketing variables with linear models. When the variables are not directly observable, it is well known that direct regression yields biased estimates. Several researchers have recently suggested reverse regression as an alternative...

This paper presents a multidimensional scaling (MDS) methodology (vector model) for the spatial analysis of preference data that explicitly models the effects of unfamiliarity on evoked preferences. Our objective is to derive a joint space map of brand locations and consumer preference vectors...