Variation within service categories and customer satisfaction: A segment-based approach using the tetra-class model

Abstract

Do client ' s age, gender or income affect how they may benefi t from certain services? Is the classifi cation of a service into one of the four categories of the tetra-class model, fi xed or, for example, linked to the length of time a customer has been a client or their geographical proximity? This study examines how the contribution of certain services to customer satisfaction changes in reference to his age, gender and income. Without questioning the suitability of the tetra-class model for classifying services, the authors have studied the nature of the changes in categories of services for three client-based variables and two variables linked to the service relationship. The results indicate that there are degrees of variability that alter in importance from one client segment to another and also with respect to the particular service under consideration.

An investigation of the influence of consumer value on service elements’ contributions to satisfaction

“…The Phi coeffi cient, whereby the closer to one the index is the stronger the association is, and the adjusted deviation statistic also completed the analysis of transfer signifi cance. As Poubanne et al 7 noted, superior absolute values of two standard deviations show a signifi cant change.…”

“…The more that service attributes are positioned on the extremity of this satisfaction axis, the more they contribute either positively or negatively to overall satisfaction; a folding of the axis then allows the categorisation of the service attributes into the four categories of key, secondary, basic and plus by the positioning of their points on the map. 5,22,24 Such studies as those by Bartikowski and Llosa, 22 Bodet, 25 Clerfeuille and Poubanne, 26 Lichtl é et al , 27 Poubanne et al , 7 Ray and Gotteland 19 and Sabadie et al 28 have used this method and confi rmed the existence of its four types of service-attribute contributions in such different sectors as catering services, medical and veterinary services, insurance services, energyprovision services, bank services, sport services and food retail stores.…”

“…The signifi cance of the categorical changes was then estimated using the indicators developed by Poubanne et al 7 From the crossed tables representing the repartition of each service attribute according to the type of categorisation, the 2 independence test showed the degree of association between the different consumer value segments. Indeed, as Poubanne et al 7 noted, if the tetra-class categorisation is so unstable as to validate the independence of the segments, the use of the model can no longer be justifi ed.…”

“…Indeed, as Poubanne et al 7 noted, if the tetra-class categorisation is so unstable as to validate the independence of the segments, the use of the model can no longer be justifi ed. The Phi coeffi cient, whereby the closer to one the index is the stronger the association is, and the adjusted deviation statistic also completed the analysis of transfer signifi cance.…”

“…However, according to Moutte 6 and Poubanne et al , 7 service-element categorisation based on the elements ' contributions to consumer satisfaction presents limited outcomes when an overall population is investigated. Therefore, because managerial concerns are often complex as a result of the heterogeneity of service consumers, it appears necessary to categorise the elements ' contributions to satisfaction in regard to different consumer-market segments.…”