Abstract
Firms often make decisions with limited information. Sometimes the decisions are made under conditions of known probabilities—that is, they are made under risk; at other times the results or events of the future are completely unknown. Under such circumstances, one uses probabilistic and Bayesian models in the decision-making process. Probability is the chance that a given event will occur. Thus, when one tosses a coin, there is a 50% chance that the coin will turn up heads. This chapter discusses certain models that make use of probability information. One category of decision making under conditions of chance is the theory of games. The tactics suggested by such theories are not unlike those employed, for example, in chess where each player analyzes several possible moves—based on the anticipated moves of the opponent, before he or she actually makes a move. Maximax policy is decision making under conditions of optimism. If a firm follows a maximax strategy, it is out to get all it can regardless of the outcome.
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