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2014 | Vol. 5, No 2 | 5--16
Tytuł artykułu

Classifying Variables with Cluster Analysis when Measuring Quality of Services in Contact Centers

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The goal of the paper was to discover, whether using one of multidimensional exploratory techniques - cluster analysis in quantifying quality of services in contact centers brings logical classification of variables and if this classification can be used and measure quality of these services. On a basis of literature studies important attributes of services delivered by contact centers were identified. They were examined as observable variables with the use of a computer assisted telephone interview method on a sample of 1000 contact center customers. Then, variables were classified using cluster analysis. Clusters link observed data into meaningful structures, that is, develop taxonomies. Using factor analysis to quantify and measure quality of contact centers allowed to distinguish the following clusters: "answer", "empathy", "availability" and "time". The profile of contact center services quality obtained from cluster analysis shows that the highest quality assessment is for the cluster "answer", then for "availability". The quality concerning cluster "empathy" is visibly lower, while the cluster "time" is of decidedly the lowest quality assessment. Proposition of classifying variables into clusters creates a theoretical model which quantify quality of services delivered by contact centers and make its structure more comprehensible. In practice, a proposed classification allows to identify quality gaps and design contact centers services with a special attention paid to the matters of quality to meet customers' expectations. The paper's contribution is a novel way of quantifying and measuring quality of services in contact centers.(original abstract)
Opis fizyczny
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