Application of the european customer satisfaction index to postal services. Structural equation models versus partial least squars

Customer satisfaction and retention are key issues for organizations in today’s competitive market place. As such, much research and revenue has been invested in developing accurate ways of assessing consumer satisfaction at both the macro (national) and micro (organizational) level, facilitating comparisons in performance both within and between industries. Since the instigation of the national customer satisfaction indices (CSI), partial least squares (PLS) has been used to estimate the CSI models in preference to structural equation models (SEM) because they do not rely on strict assumptions about the data. However, this choice was based upon some misconceptions about the use of SEM’s and does not take into consideration more recent advances in SEM, including estimation methods that are robust to non-normality and missing data. In this paper, both SEM and PLS approaches were compared by evaluating perceptions of the Isle of Man Post Office Products and Customer service using a CSI format. The new robust SEM procedures were found to be advantageous over PLS. Product quality was found to be the only driver of customer satisfaction, while image and satisfaction were the only predictors of loyalty, thus arguing for the specificity of postal services

Informed recommender: basing recommendations on consumer product reviews

Recommender systems attempt to predict items in which a user might be interested, given some information about the user's and items' profiles. Most existing recommender systems use content-based or collaborative filtering methods or hybrid methods that combine both techniques (see the sidebar for more details). We created Informed Recommender to address the problem of using consumer opinion about products, expressed online in free-form text, to generate product recommendations. Informed recommender uses prioritized consumer product reviews to make recommendations. Using text-mining techniques, it maps each piece of each review comment automatically into an ontology

Recommender System Based on Consumer Product Reviews

Consumer reviews, opinions and shared experiences in the use of a product is a powerful source of information about consumer preferences that can be used in recommender systems. Despite the importance and value of such information, there is no comprehensive mechanism that formalizes the opinions selection and retrieval process and the utilization of retrieved opinions due to the difficulty of extracting information from text data. In this paper, a new recommender system that is built on consumer product reviews is proposed. A prioritizing mechanism is developed for the system. The proposed approach is illustrated using the case study of a recommender system for digital cameras

Customer satisfaction in the banking industry: a comparative study of Ghana and Spain

La satisfacció és una preocupació crucial pels clients i per les organitzacions, incloent els bancs. L'estudi examina la satisfacció global dels clients dels bancs a Ghana i Espanya. Així s'analitzen aspectes com la relació entre satisfacció global i les dimensions de qualitat dels serveis bancari, així com les pròpies dimensions principals de la qualitat d'aquests serveis. Finalment, les percepcions sobre aquestes dimensions son comparades entre els bancs de Ghana i Espanya. S'han analitzat els clients de 819 bancs de Ghana i Espanya, els resultats van mostrar que els clients espanyols estaven més descontents respecte les dimensions tangibles i empatia metre que els clients de Ghana puntuaven pitjar la dimensió conveniència. En general, els clients de Ghana estaven força més descontents amb els serveis bancaris que els d'Espanya. La fiabilitat, l'empatia i la conveniència son els predictors de satisfacció global en Ghana, mentres que la fiabilitat és la única dimensió que explica la satisfacció global a Espanya.