مقاله سال ۲۰۱۶

 مجله امگا – Omega

Bus transit systems play an important role in the regional development of a country. Hence, the issue of bus transit performance is of widespread concern. Traditionally, partial indicators are used to measure the operational performance (e.g., average vehicle-miles per vehicle). However, partial indicators only focus on single or parts of operational factors.

They may lead to misleading results in the bus transit industry, because bus transit operations are characterized by multiple inputs and multi-product capability (Odeck, 2006). Performance measurement based on the conventional data envelopment analysis (DEA) model, which aggregates multiple inputs and multiple outputs, can overcome the weakness of partial indicators. The extant literature on performance measurement for bus transit firms has evaluated efficiency by using the conventional DEA model (e.g., Chang and Kao, 1992; Nolan, 1996; Viton, 1997, 1998; Cowie and Asenova, 1999; Nolan et al., 2001; Odeck, 2006).

In Taiwan, a bus transit firm primarily operates two activities: highway bus (HB) service and urban bus (UB) service. Services provided by bus transit firms are unstorable and must be consumed immediately. If they are not consumed, they will disappear (Tomazinis, 1975). The quantities of consumed service may be a proportion of the quantities of produced service. Hence, the operation of a bus transit firm further involves two processes: production process and consumption process. When bus transit performance is estimated, these unique characteristics of bus transit services should be reflected in the difference between the concepts of efficiency and effectiveness (Hatry, 1980). Efficiency represents “do things right” and is measured by production efficiency (PE), which describes the ratio of actual outputs produced to inputs, while effectiveness represents “do the right things” and is measured by service effectiveness (SEV), which describes the ratio of consumed outputs to produced outputs, and operational effectiveness (OEV), which is the combination of PE and SEV (Yu and Fan, 2009). Since a bus transit firm includes multiple activities and multiple processes, parts of its resources belong to the specific activity or process, while others are shared among different activities and/or processes (e.g., management staff). Furthermore, when bus transit operators plan operationally, they will consider the inter-relationship between consecutive terms, and reserve a proportion of outputs or revenue to the next period (e.g., network length). Hence, in order to understand the operational performance for a bus transit firm, the allocation of shared inputs and the effect of carry-over items between two consecutive terms also need to be taken into account.