Eric T. Bradlow

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Many online retailers monitor visitor traffic as a measure of their stores’ success. However, summary measures such as the number of hits per month provide little insight into individual consumers’ behavior. Additionally, behavior may evolve over time, especially in a changing environment like the Internet. Understanding the nature of this evolution(More)
This research examines the ability of six popular Web search engines, individually and collectively, to locate Web pages containing common marketing/management phrases. We propose and validate a model for search engine performance that is able to represent key patterns of coverage and overlap among the engines. The model enables us to estimate the typical(More)
We predict the popularity of short messages called tweets created in the micro-blogging site known as Twitter. We measure the popularity of a tweet by the time-series path of its retweets, which is when people forward the tweet to others. We develop a probabilistic model for the evolution of the retweets using a Bayesian approach, and form predictions using(More)
Recent trends in marketing have demonstrated an increased focus on in-store expenditures with the hope of “grabbing consumers” at the point of purchase, but does this make sense? To help answer this question, the authors examine the interplay between in-store and out-of-store factors on consumer attention to and evaluation of brands displayed on supermarket(More)
This paper compares the behavior of individuals playing a classic two-person deterministic prisoner’s dilemma (PD) game with choice data obtained from repeated interdependent security prisoner’s dilemma games with varying probabilities of loss and the ability to learn (or not learn) about the actions of one’s counterpart, an area of recent interest in(More)
P methods for choice-based conjoint analysis provide a means to adapt choice-based questions at the individual-respondent level and provide an alternative means to estimate partworths when there are relatively few questions per respondent, as in a Web-based questionnaire. However, these methods are deterministic and are susceptible to the propagation of(More)
This article discusses the use of Bayesian methods for estimating logit demand models using aggregate data. We analyze two different demand systems: independent samples and consumer panel. Under the first system, there is a different and independent random sample of N consumers in each period and each consumer makes only a single purchase decision. Under(More)
We examine three sets of established behavioral hypotheses about consumers’ in-store shopping behavior (the effect of perceived time pressure, licensing, and the social presence of other shoppers) using field data on shopping paths and linked purchases obtained from an actual grocery store. We incorporate these behavioral hypotheses within an(More)
The Centers for Medicare and Medicaid Services publicly reports so-called process performance at all U.S. hospitals, such as whether certain recommended treatments are given to specific types of patients. We examined whether hospital performance on key process indicators improved during the three years since this reporting began. We also studied whether or(More)