Abstract:A mathematical model to measure the level of service at airport passenger terminals is presented. The model relates passengers’ ratings of services at terminals and the time spent waiting for those services. The fuzzy concept is used to deal with the vagueness of service ratings such as “satisfied” and “unsatisfied.” Furthermore, two instruments are used to obtain the amount of time spent in service processes: perceived time reported by passengers and objective quantities measured by researchers. Empirical dat… Show more
“…For example see,Mu¨ller and Gosling (1991),Lemer (1992),Davis and Braaksma (1987),Yen (1995),Yen et al (2001),Omer and Khan (1988),Ashford (1988),Ndoh and Ashford (1993),Seneviratne and Martel (1994),Caves and Pickard (2001), andPark (1999).…”
“…For example see,Mu¨ller and Gosling (1991),Lemer (1992),Davis and Braaksma (1987),Yen (1995),Yen et al (2001),Omer and Khan (1988),Ashford (1988),Ndoh and Ashford (1993),Seneviratne and Martel (1994),Caves and Pickard (2001), andPark (1999).…”
“…Many researchers have pointed out that customers' perceived service levels differ significantly from actual service levels (Mishalani et al 2006;Yen, Teng, and Chen 2001). Mishalani et al (2006) found perceived waiting time at bus stops to be greater than the actual waiting time in the range of 3-15 minutes due to the absence of accurate real-time bus arrival information.…”
The need to assess service quality of existing transportation systems based on users'perceptions has received increased attention in recent years. In this context, researchers have identified level of service (LOS) as an effective tool to measure users' perceptions of service quality on a linguistic scale ranging from LOS A to LOS F which denote 'best' to 'worst' levels of service according to users' perceptions. However, contrary to the definition of LOS that requires it to be measured based on user perception, the existing LOS benchmarks available for public transportation are based on expert judgment. This research attempts to develop LOS benchmarks for bus transit services based on user perception using the 'Law of Successive Interval Scaling' which converts an ordered categorical scale into an interval scale. The results obtained through this analysis for the city of Kolkata, India, highlight the difference in LOS scale values between developed and developing nations and between expert opinion and user perception.
“…Nevertheless, Ashford (1988) suggested that a strong interaction exists between space provision and time; however, that interaction cannot be obtained by the P-R concept as it has been presented. 1 In addition to that deficiency, recent LOS studies of airport passenger terminal processing components have shown that perceived and actual times have enormous discrepancies (Park, 1994(Park, , 1999Yen et al, 2001). Those discrepancies indicate that obtaining data by the stated preference technique must be used with caution.…”
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