A Decision Support System For Audit Staff Scheduling Of Multiple And Large-Scaled Engagements

Abstract

As raising cost of audit and shrinking audit market, the management of accounting firms have put into more efforts on increasing productivity by improving audit planning, upgrade audit technology and cost control. One avenue to accomplish cost savings while maintaining high audit quality is to refine staff scheduling. This study proposes a different approach to resolving audit staff scheduling for multiple and large engagements. The major advantage of the proposed method is to solve staff resource allocation problems by alleviating the limitations of both linear and integer programming. In addition, the objectives and constraints of models proposed in this study can be modified easily to adjust for firm-specific situations.