Browsing by Subject "Industrial and Systems Engineering"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    The impact of computer decision support on military team decision making.
    (2010-08) Larson, Adam Donavon
    This dissertation work highlights extremely valuable results regarding significant costs and benefits of using a computer decision aid by analyzing the impact of such a decision support tool on military team decision making. Decision support systems (DSS) are becoming increasingly popular as an approach to aid decision makers in making better decisions in a more efficient and effective manner. However, DSSs have both costs and benefits in their utilization, and there is no guarantee that a DSS will actually improve decision making or problem solving performance. This work shows that although a DSS has many advantages and can facilitate user problem solving, brittle DSS behavior can significantly degrade user decision making. The primary goals of this work are to improve scientific understanding of situations in which DSSs may improve decision making performance and those where the use of a DSS may actually degrade performance. Specifically, the heart of this work focuses on understanding and measuring the performance benefits and costs of a solution generating DSS on individuals versus teams, and on situations in which the DSS produces "brittle," or questionable solutions. Understanding the impact of brittle behavior is especially important given the domains in which DSSs are often utilized, including military, medical, and business operations. The results of decisions in these areas greatly impact dollars and most importantly, human lives, that may be saved or lost. The decisions teams make in military situations play a vital role in determining the success or failure of operations. Decision support in this study was provided by a component of a DSS tool called Weasel. A previous study in 2004 analyzed Weasel with respect to individual decision makers' performance and behavior [9]. This study analyzed team behavior and performance in a military context with military personnel working together in three person teams. The primary questions addressed by this work are: What is Weasel's overall impact on team versus individual performance and what is the effect on user performance when Weasel exhibits brittle behavior? Brittle behavior refers to the automated decision tool offering questionable, low quality courses of action for a given situation. As all DSSs will at sometime or another exhibit some degree of brittle behavior, the impact of such behavior on user decision making is vitally important. The results showed brittle behavior does indeed negatively impact user decision making behavior, and that individuals and teams demonstrated the same levels of performance with the use of the automated decision tool. The results of this experiment will help researchers and military personnel to better understand when it is appropriate to use decision support and to better understand both the benefits and the costs in team decision making by assessing when the DSS tool facilitated improved decision making and when performance was hindered by the tool. Additionally, information may be gained regarding situations where computer support and automation use may degrade performance.
  • Thumbnail Image
    Item
    On the use of some misspecified models of customer choice in revenue management.
    (2010-08) Li, Le
    Much of the recent revenue management literature takes customer behavior into account. A number of parametric models that incorporate customer choice have been developed. In some cases, these models closely approximate reality and provide high quality solutions. Nevertheless, most studies of revenue management models do not consider the possibility that the model used to generate decisions is different from reality. Such analyses also typically do not address effects of forecasting or how forecasts evolve when the model being used is misspecified. (A model for which there is no parameter setting that makes the model a correct description of reality is called a misspecified model). In this dissertation, we study some models of customer choice in revenue management and test their performance when implemented in settings where their assumptions are violated; i.e., when they are misspecified. First, we study a model based on the notion of "buy-up" that considers the dependency of the customers who are willing to purchase low-fare tickets and those who prefer high-fare tickets. To implement this parametric model, a decision maker (revenue manager) needs to observe some data to estimate its parameters (buy-up rate and demand distributions), and make decisions (booking limits) using the model. Meanwhile, the choices of booking limits will affect customers' behavior and thus affect the following observed data. We study the above dynamics and show the convergence of booking limits when the buy-up model is misspecified and customer arrivals are actually deterministic. Numerical studies are also provided to show the performance of the model. Second, we continue the study of the "buy-up" model and consider more complicated actual customers' behavior in which the numbers of different types of customers are stochastic. We present a general necessary condition for the convergence of booking limits and buy-up rate estimates. We provide sufficient conditions for convergence using two different approaches. Comparisons among the optimal revenue, the revenue associated with convergence in the "buy-up" model, and the revenue obtained from the Littlewood rule are presented in the end. Third, we study the performance of the Littlewood rule when it is used to manage bookings for substitutable fights. We show the convergence of booking limits under some assumptions, and make some conjectures about the limiting behavior of booking limits in other settings. Some numerical studies are performed to enlighten future work.