Application of Monte Carlo AHP in ranking dental quality attributes

Previous studies on the healthcare service quality have either ignored the multi-dimensional nature of healthcare services or naively generalized their research findings to dental services. This study reports the development of a comprehensive model that measures dental service quality in a hierarchical method. Examining the quality structure of dental services by using an analytic hierarchy process (AHP), we then add Monte Carlo simulation to precisely identify the priorities of the leading attributes. The empirical testing with a dental clinic group is then presented and demonstrates its usefulness in identifying real orders of quality attributes. Results from this model provide stronger confidence for the management of dental clinics than traditional AHP, and have significant cost-saving and revenue-increasing contributions. This model extends the applications of both AHP and the Monte Carlo simulation in service industry management, and proves its ability in clearly prioritizing critical attributes, in that it greatly sharpens the effectiveness of the decision-making process.