A theory of motivation and satisfaction with application to decision support

The paper deals with optimization of allocation of human resources among different activities. It is assumed that an individual is characterized by a ‘risk averse’ and ‘constant return to scale’ utility function of two variables: motivation to perform and reward following the performance. The individual is trying to maximize the utility by the best allocation of this time resources among the activities and by selecting the best portfolio of activities. Motivations are regarded, generally, as the product of the individual’s preferences (i.e. subjective choice probabilities), productivities of time, output prices, performance and access probabilities, etc., while the rewards are profits or salaries connected with each activity. Satisfaction is defined as the maximum of utility attained for the optimum allocation and selection strategies. It is shown that for the given ‘equitable reward rate’, the optimum allocation and portfolio selection strategies can be derived explicitly and the derivation does not require the explicit knowledge of the individual’s utility function.