Utilize este identificador para referenciar este registo: http://hdl.handle.net/10362/79662
Título: Comparing two scale lengths in the context of a customer satisfaction survey
Autor: Raupp, Adriana Pereira
Orientador: Coelho, Pedro Miguel Pereira Simões
Palavras-chave: Rating scales
Customer satisfaction
ECSI
PLS SEM
Data de Defesa: 12-Jul-2019
Resumo: In addition to tangible assets, nowadays, companies are being measured by their orientation towards customers. Thereby, organizations are making efforts to survey and understand their customers’ needs, which would result in customer satisfaction and ultimately bring competitive gains. Customer satisfaction surveys can be done in several ways, within the various methodologies used across the world, since the 1990s. To this end, there are a couple industry standards in customer satisfaction measurement, such as the American and the European Customer Satisfaction indexes. Customers were surveyed in several attributes, which estimated other attributes that could culminate in the estimation of the satisfaction index. Indeed, this is done by using partial least squares structured equation modeling. In this study, the methodology for the European Customer Satisfaction Index, ECSI, was applied to the customers of an online company in Brazil called Singu. Although, the ECSI methodology uses a scale length of ten points, in this work a five-point scale was used simultaneously, aiming at comparing the results obtained with both surveys and evaluating which one estimates best in this context. In the conclusion, results show why the longer scale is the best option in the end, in spite of having significant fewer respondents.
Descrição: Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Marketing Research e CRM
URI: http://hdl.handle.net/10362/79662
Designação: Mestrado em Estatística e Gestão de Informação, especialização em Estudos de Mercado e Gestão do Relacionamento com o Cliente
Aparece nas colecções:NIMS - Dissertações de Mestrado em Estatística e Gestão da Informação (Statistics and Information Management)

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