| This dissertation focuses on decision making and decision support systems, and consists of four related studies. In the first study, a web version of the Aspiration-level Interactive Method (AIM), WebAIM, is developed and made available at http://mgt2.buffalo.edu/webaimU . We demonstrate the usage of the program and introduce the features of WebAIM through a house selection problem. In the second study, we explore certain properties of AIM and extend the concept of robustness of solutions in AIM. We map well-diversified aspiration levels to their corresponding most preferred alternatives, and find that a majority of aspiration levels are mapped to relatively few alternatives. Next, we apply the techniques developed in Multiple Criteria Decision Making to a negotiation problem. We consider a one-to-many negotiation problem such as a house-purchasing process in which there is one buyer and many sellers. Using the Best Alternative to a Negotiated Agreement (BATNA) as a dynamic measure of negotiating strength, we develop a systematic quantitative iterative approach to assist in the negotiation process. Finally, we consider generating random uniformly-distributed weights for the simulation of additive p-criteria decision models. The study reviews and validates several approaches for generating random weights with and without linear constraints. Some obvious approaches do not work well at all. |
