We study search behavior in a generalized "secretary problem" environment in which consumers search sequentially for the best alternative from a known and finite set of multi-attribute alternatives. In contrast to most previous studies, we make no distributional assumptions about the quality of...

Electronic recommendation agents have the potential to be valuable e-service tools in increasing consumer decision quality. Such agents are aimed at assisting consumers in the decision-making process and have the ability to enable consumers to make better choices for themselves. The definition...

In content- and knowledge-based recommender systems often a measure of (dis)similarity between products is used. Frequently, this measure is based on the attributes of the products. However, which attributes are important for the users of the system remains an important question to answer. In...

In confidence theory, the decision maker relies on statistical regularities from the economic environment to adopt prior beliefs about the probabilities stated on a lottery. Following the confidence principle, by which the weight of the prior in Bayesian inference is proportional to the...

We conduct a lottery experiment to assess the predictive importance of simple choice process metrics (SCPMs) in forecasting risky 50/50 gambling decisions using different types of machine learning algorithms as well as traditional choice modeling approaches. The SCPMs are recorded during a fixed...

We study sequential search without priors. Our interest lies in decision rules that are close to being optimal under each prior and after each history. We call these rules robust. The search literature employs optimal rules based on cutoff strategies, and these rules are not robust. We derive...

We model fairness within the context of search. To do this, consider sequential search where the searcher is uncertain about the underlying pool of candidates. Fairness is introduced by requiring that candidates cannot be discriminated against by non-merit characteristics or by the order in...

We develop a forecasting method for the manufacturer and online seller of a product collection that changes periodically and radically. The firm, an industry leader in technology and quality, has experienced double-digit annual sales growth. In seeking to minimize supply-demand mismatch costs...

In many decisions, we are not only uncertain about the predicted outcomes of decision alternatives but also about stakeholder preferences regarding these outcomes. Further information collection may reduce uncertainties, but is costly. We present and apply a framework to identify the most...

This article examines the effects on outcome-expectancies of precise versus vague information across two contexts: prior to an action taken by the consumer (pre-action) and after the action is taken (post-action). Across three experiments, we show that with vague information individuals are more...