The Development of Rental Car Efficiency using Two-Phase Technique

Abstract

The objective of this research is to develop two phase technique for evaluating the efficiency of rental car usage; this technique consists of data envelopment analysis (DEA) when undesirable factors exist, and hierarchical clustering analysis (HCA). The used data were taken from the information systems of 104 government agencies and car rental companies. It consists of the cost of car rentals, the entire active distance and the cost of maintenance as a desirable factor, and the cost of car repairing after accident as an undesirable factor. When undesirable factor exists, all mentioned data were firstly evaluated by DEA with additive inverse method (ADD) and the evaluated data were further grouped by hierarchical clustering analysis. It is considerate that data grouping by using characteristics of evaluated data criterion is more effective than those using the judgment by the assessor. The results indicated that two phase technique for the efficient evaluation is able to calculate and cluster the efficiency scores on the use of rental vehicle in government agencies into three levels. These three levels include low performance scores group (0.0000-0.4447) moderate performance scores group (0.4608-0.7993) and high performance scores group (0.9475-1.0000). This efficiency data could be used for decision-making in the policy development to allocate the rental car usage for decision making unit (DMU) efficiently and worthwhile.