This paper presents a case study of an expert system combining a knowledge-based system and regression analysis to support decision making involved in improving the productivity of an organization. A pharmaceutical distributor in Taiwan is used as an example to illustrate the development and application of an expert system to tackle the daily decision problem of handling uncertainty in carrying out delivery tasks. Regression analysis is used as a method to predict the working time of drivers undertaking the delivery tasks. The application of a knowledge-based system coupled with the use of regression analysis is proposed to balance the workload, increase capabilities of handling more orders, improve productivity, ensure decision consistency, and reduce relevant costs. To determine whether or not the proposed expert system will be technically feasible and cost-effective, a systematic way of predicting the success or failure of the system is implemented. It is found that the project would be worth much more than what it would cost. Thus, the proposed expert system is economically justified.
Relation:
International Journal of Management 20(3), pp.360-376
