Variability can be an important strategic variable in a contest. We study optimal strategies involving choice of variability in contests with fixed and probabilistic targets, one-round and multiround contests, contests with and without handicaps, and situations where one contestant can modify...

In this article, we extend recent work on the inferential impact of errors in data to a decision-making setting. In the context of a simple quality-control example, we illustrate how errors can cause substantial reductions in the value of information from a sample and how uncertainty about error...

Data from surveys often include errors, and such errors can have a serious effect on inferences about behavior or perceptions. In this paper a model is developed for making inferences based on dichotomous survey data with possible errors. A likelihood analysis reveals an identification problem,...

Inferences about a proportion p are often based on data generated from dichotomous processes, which are generally modeled as processes that are Bernoulli in p. In reality, the assumption that a data-generating process is Bernoulli in p is often violated due to the presence of noise. The level of...

Forecasts are crucial for practically all economic and business decisions. However, there is a mounting body of empirical evidence showing that accurate forecasting in the economic and business world is usually not possible. In addition, there is huge uncertainty, as practically all economic and...

Much of the salesforce compensation literature has focused on developing incentive schemes to maximize effort levels on the part of the salesforce. The amount of effort to expend in the selling task is considered to be the sole decision variable for a sales representative. In this paper, we...