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22 flow conditions and measured the driver's satisfaction A Handbook for Measuring with the road. The test area was a 9.3-km, 4-lane, rural basic Customer Satisfaction motorway section between an on-ramp and an off-ramp. Twenty-four participants drove subject vehicles in both Morpace [30] presents a methodology for measuring cus- directions in the study segment for a total of 105 test runs. tomer satisfaction on an ongoing basis and the development Videocameras were mounted on the test vehicle to record of transit agency performance measures in response research travel time, number of lane changes, time of a car-following findings. situation by lane, and elapsed travel time by lane. The factor The authors point out that the results of a customer satis- that most influenced driver satisfaction was traffic flow rate. faction measurement program cannot be expected to drive The number of lane changes, the elapsed time of a car- agency decisions. Agency personnel must choose between following situation, and the driver's experience also affected improvements to address customer expectations and better the driver's evaluation of traffic conditions. education of customers about service parameters. They state the premise that, "Customers must always be first, [but] cus- tomers may not always be right". They identify 10 Determinants of Service Quality, which 3.2 Transit Passenger Perceptions are applicable to most service industries. The contention is of LOS that consumers use basically similar criteria in evaluating Recent transit LOS research has focused on developing service quality. The 10 criteria are as follows: methods that incorporate more than just the characteristics of the available transit service, but measures of the environ- 1. Reliability (consistent and dependable); ment in which that service operates. Fu et al. [26] developed 2. Responsiveness (timeliness of service, helpfulness of a Transit Service Indicator (TSI) that recognizes that quality employees); of service results from the interaction of supply and demand. 3. Competence (able to perform service); The proposed index uses multiple performance measures 4. Accessibility; (e.g., service frequency, hours of service, route coverage, and 5. Courtesy; various travel-time components as well as spatial and tempo- 6. Communication; ral variations in travel demand). Tumlin et al. [27] developed 7. Credibility; a method that assesses transit performance in the context of 8. Security; different transportation environments. Quality of service cri- 9. Understanding the Customer; and teria and scores reflect system performance in each area as 10. Tangibles. well as provide for an aggregate measure of transit quality of service. They identify four transit market segments: Other transit LOS research efforts have focused on devel- oping or refining measures that can be easily calculated 1. Secure customers very satisfied, definitely would repeat, using existing transit agency data sources. Xin et al. [28] definitely would recommend; applied the recent edition of the TCQSM to evaluate the 2. Favorable customers; quality of transit service on several travel corridors in an 3. Vulnerable customers; and urbanized area. Findings indicate that TCQSM measures 4. At-risk customers. (e.g., service frequency, hours of service, service coverage, and transit-auto travel time) are sensitive to planning/ They recommend that telephone benchmark surveys be design variables (e.g., service headway, route structure, and used to establish baseline customer satisfaction with the tran- service span) and, therefore, can be easily calculated by tran- sit service. These surveys are fairly expensive, so they also rec- sit agencies using readily available data. Furth and Muller ommend a simpler survey approach, based on "impact [29] noted that traditional transit service quality measures scores," be used for tracking progress regularly. analyze waiting time and service reliability separately, under- The "impact score survey" is administered on-board and estimating the total costs of service unreliability which distributed to transit riders annually or biennially. The goal cause patrons to budget extra time waiting for transit to is to identify those attributes that have the greatest negative account for unreliability. Using AVL data, actual plus bud- effect on overall customer satisfaction and also affect the geted waiting time were measured and converted to costs. greatest number of customers. Findings indicate that service reliability improvements can They suggest the use of an "Impact Score Technique" to reduce waiting cost as much as large reductions in service identify the effect on customer satisfaction of "Things Gone headways. Wrong" with the service. The score weights the effect of a