Selecting and promoting service encounter elements in passenger rail transportation

Tripp, Carolyn; Drea, John T.

doi:10.1108/08876040210436902

Cited by 41 publications

(21 citation statements)

References 15 publications

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“…They are similar to most of the attributes used in other rail passenger studies, e.g. Hanna and Drea (1998), Drea and Hanna (2000), and Tripp and Drea (2002) that used literature searches and focus groups. Their Cronbach alpha values are similar to those in this study.…”

Section: Conclusion and Recommendationsmentioning

confidence: 91%

“…In the later paper cost, convenience getting to the station, parking availability, Amtrak comfort, seat comfort, ride, seating area cleanliness, and courtesy of on-board staff were the service quality attributes tested. Tripp and Drea (2002) also used a survey of Amtrak passengers to assess the "direct and indirect relationship between pre-core/peripheral and core service performance components and their impact on the likelihood of repeat purchase" (p. 433). They found that the core experiences on-board that determined the customer's attitude to the service provider an subsequently their intention to use the train again.…”

Section: Introductionmentioning

confidence: 99%

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Developing zones of tolerance for managing passenger rail service quality

Cavana

Corbett

2007

International Journal of Quality &Amp; Reliability Management

136

101

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Purpose -The purpose of this article is to develop and empirically test an extension to the three-column format SERVQUAL instrument to evaluate passenger rail service quality. Design/methodology/approach -This article combines the literatures of service quality and rail transport quality to develop the conceptual framework. Three new transport dimensions (comfort, connection, and convenience) are added to the original five SERVQUAL dimensions (assurance, empathy, reliability, responsiveness, and tangibles). The instrument was tested on a passenger line in Wellington, New Zealand. Valid responses to 340 questionnaires were statistically analyzed. Findings -High Cronbach alpha values supported the reliability of the instrument. Content and construct validity are demonstrated also. Regression analysis identified assurance, responsiveness and empathy as the quality factors that had significant effects on overall service quality. In addition, customers indicated that reliability and convenience were also very important factors. Service quality "zones of tolerance" were identified for each dimension and attribute. Research limitations/implications -There are not many published studies to confirm or compare the results of the three-column SERVQUAL instrument, either in the general service literature or in the rail passenger literature. Although the five original SERVQUAL dimensions have been tested quite extensively, the three new rail transport dimensions require further development and testing, particularly since the sample was drawn from a single passenger line in New Zealand. More development and empirical testing are required to refine this measure. Practical implications -Based on the eight dimensions, the practical use of the "zones of tolerance" for identifying areas of quality shortfall and managing quality are illustrated in this paper. Originality/value -This paper provides one of the few empirical applications of the three-column SERVQUAL instrument and extends it to make it more suitable for evaluating rail passenger service quality.

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Section: Conclusion and Recommendationsmentioning

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Developing zones of tolerance for managing passenger rail service quality

Cavana

Corbett

2007

International Journal of Quality &Amp; Reliability Management

136

101

View full text Add to dashboard Cite

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“…Existing research on service quality analyses In recent years, the management of service quality has attracted considerable attention from academics who have investigated the characteristics of service quality (e.g., Golder et al 2012;Harvey 1998), the effect of service quality on behavioral intentions (e.g., Tripp and Drea 2002;Sánchez Pérez et al 2007), and the impact of service quality on operational and business performance (e.g., Adam 1994). Consequently, public transport operators as well as other service providers have begun to use quality measures for various quality management purposes.…”

Section: Measurement and Analyses Of Service Qualitymentioning

confidence: 99%

“…In recent years, the management of public transport quality has attracted considerable attention from academics investigating the measurement of service quality (Prioni and Hensher 2000;, the effect of service quality on behavioral intentions (e.g., Tripp and Drea 2002;Sánchez Pérez et al 2007), or the design of performance-based quality contracts (Hensher and Stanley 2003;Hensher and Houghton 2004). Likewise, public transport operators are increasingly focusing on improving service quality, assuming that this has an impact on their performance.…”

Section: Introductionmentioning

confidence: 99%

The limits of analyzing service quality data in public transport

Becker

Albers

2015

Transportation

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In recent years, management and academics have increasingly focused on quality management in public transport. In particular, many public transport operators regularly monitor their service quality over time and use these data to assess quality performance (e.g., for performance-based quality contracts) and to determine managerial decisions (e.g., budget allocations for service improvements). However, despite the widespread applications of service quality data in practice, it is unclear whether crosssectional analyses and cross-temporal comparisons of service quality data provide valid insights for quality management purposes. In this study, we investigate the usability of cross-sectional analyses and cross-temporal comparisons of service quality data by conducting an empirical study that tracked a panel's perceptions of the service quality of public transport and its choice over the course of three consecutive years. The results demonstrate that cross-sectional analyses provide valid insights for quality management. However, cross-temporal comparisons should be interpreted carefully because the results of these comparisons are surprisingly unreliable. In fact, we find that service quality data do not provide reliable results over time and therefore conclude that cross-temporal comparisons of service quality data must be interpreted with caution for quality management in public transport.

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“…However, when customers evaluate the quality of a service as a whole, some service attributes are considered more important than others (Mokonyama and Venter, 2013), being their influence implicitly taken into account with their global evaluation. Therefore, there are several categories of attributes having a greater or lesser impact on service quality (de Oña et al, 2013;Eboli and Mazzulla, 2012;TRB, 2004;Tripp and Drea, 2002); their influence should be considered when an indicator of the level of quality is calculated.…”

Section: Introductionmentioning

confidence: 99%