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Prioritization of Service Quality Parameters Based on Ordinal Responses

By: CHATTERJEE, Sudipta.
Contributor(s): CHATTERJEE, Aditya.
Material type: materialTypeLabelArticlePublisher: UK : Routledge, June 2005Subject(s): Service priority | SERVQUAL model | Ordered categorical data | RIDIT analysis | Pareto analysis | Multivariate regression | Rank correlationTotal Quality Management & Business Excellence 16, 4, p. 477 - 489 Abstract: The importance attributed to service sector industries has become more pronounced in the post-globalization era and the trend continues unabated even today. In such industries, direct assessment of the service quality is often not possible and the measurement has to be made in terms of suitable surrogates through various parameters related to delivery, support, cost, billing, access, speed, response to queries, complaint redressal and so on. The SERVQUAL models and their extensions (Parasuraman et al., 1985, 1988, 1994a, 1994b; Zeithamal et al., 1993) have delved into the various facets of measuring service quality and the factors that influence the customer expectations and their perceptions. However, a concrete quantification of the ‘service gaps’ used in such models, is seldom found in the literature. As such, it is very much necessary to quantify the ‘service gaps’ and also to quantify the expectation of the service parameters as perceived by the customers. In the present paper, a prioritization methodology of the service quality parameters has been proposed for a service sector industry based on surveys carried out on both the internal, as well as, external consumers. The responses of the surveys are Ordered Categorical in nature. As such, the conventional statistical techniques based on continuous responses are not suitable or justified. Moreover, it appears that the use of ‘difference scores’ in SERVQUAL or similar instruments, contributes to problems with the reliability, discriminant validity, convergent validity and predictive validity of the measure (Van Dyke et al., 1999). The idea of a gap without constructing difference scores may be conceived by the RIDIT scores, which is a well known technique in Categorical Data Analysis (Bross, 1958; Fleiss, 1973, 1999; Agresti, 1984). The proposed methodology is expected to encompass any service sector industry with well-defined service quality parameters and can be used as an alternative approach to the SERVQUAL instrument.
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The importance attributed to service sector industries has become more pronounced in the post-globalization era and the trend continues unabated even today. In such industries, direct assessment of the service quality is often not possible and the measurement has to be made in terms of suitable surrogates through various parameters related to delivery, support, cost, billing, access, speed, response to queries, complaint redressal and so on. The SERVQUAL models and their extensions (Parasuraman et al., 1985, 1988, 1994a, 1994b; Zeithamal et al., 1993) have delved into the various facets of measuring service quality and the factors that influence the customer expectations and their perceptions. However, a concrete quantification of the ‘service gaps’ used in such models, is seldom found in the literature. As such, it is very much necessary to quantify the ‘service gaps’ and also to quantify the expectation of the service parameters as perceived by the customers. In the present paper, a prioritization methodology of the service quality parameters has been proposed for a service sector industry based on surveys carried out on both the internal, as well as, external consumers. The responses of the surveys are Ordered Categorical in nature. As such, the conventional statistical techniques based on continuous responses are not suitable or justified. Moreover, it appears that the use of ‘difference scores’ in SERVQUAL or similar instruments, contributes to problems with the reliability, discriminant validity, convergent validity and predictive validity of the measure (Van Dyke et al., 1999). The idea of a gap without constructing difference scores may be conceived by the RIDIT scores, which is a well known technique in Categorical Data Analysis (Bross, 1958; Fleiss, 1973, 1999; Agresti, 1984). The proposed methodology is expected to encompass any service sector industry with well-defined service quality parameters and can be used as an alternative approach to the SERVQUAL instrument.

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