Adjusting Service Performance Criteria Based on Generalized Information from Previous Reports

This paper uses Least Square Method to develop the stochastic models to fit the categorized historical data which are commonly used in evaluating service performances. This paper then provides formulas to determine the targets for revenue maximization and downside risk under control. The paper further demonstrates that when setting a single criterion, if the benefit of achieving the criterion and the loss of missing the criterion do not vary according to the criterion, people will not have motivation to set a high criterion and will choose to set the criterion at the lowest point. On the other hand, if the potential gain increasing rate of setting a higher criterion overgrows the probability decreasing rate of achieving such a criterion, the risk-neutral agents will have the potential to take the high risk to pursue an impractically high criterion.