Fuzzy linguistic approach to quality assessment model for electricity network infrastructure

Abstract In the modern service economy, the consumer satisfaction is one of primary objectives that a company aims at achieving. Successful companies offer high quality of products or services in order to meet the consumers’ expectation, and, at the same time, they safeguard their own profits and increase market competitiveness. The consumer satisfaction is an indicator to estimate how likely a customer will make a purchase in the future and it is used as a metric very useful in managing and monitoring the company businesses. To address this issue, we present QuAM (Quality Assessment Model), a model for evaluating the overall quality and value of services supplied by a company, through the analysis of the consumer satisfaction. The quality is measured indeed, by the definition of some subjective criteria that are collected through a question form filled in by the consumers. The consumers’ judgments about the supplied items/services allow evaluating the reputation as well as the success of a company. In this work, QuAM has been applied in the electricity network domain, in order to assess an electricity company. In this domain, the overall evaluation of the organization is based on measuring service quality in terms of response times and cost. The quality of service often comes at a cost, with a concern that the pursuit of profit incentives by utilities may have a negative effect on the quality of service. The role of customers is crucial to estimate a market demand curve for service quality, and maximize the customers satisfaction means increasing profitability, productivity and the corporate image. QuAM has been designed by exploiting a fuzzy linguistic approach along with the Computing with Words (CWW) paradigm: the customers feedbacks are modeled through linguistic labels, which naturally fit to describe human judgments; then a linguistic operator LOWA (Linguistic Ordered Weighted Averaging) allows aggregating all the collected judgments into a synthetic linguistic expression. Finally, heuristic measures enable a comprehensive company evaluation