Predicting Customer Satisfaction Using a Two-level Service Expectation Framework: Empirical Evidence from Star Rated Hotels in Malawi
Hospitality is the fastest-growing, experience-intensive service industry and becoming the biggest export service sector worldwide. Several countries including Malawi, have several star-rated hotels which possess some anticipated degree of comfort and service quality in those hotels. It is anticipated that customers evaluate the service performance of a hotel against their expectations and experiences, eventually deriving satisfaction. The purpose of this study was to establish whether service expectations can measure or predict customer satisfaction. Using an explanatory and descriptive design, this study focused on eleven hotels of star ratings situated in Lilongwe and Blantyre cities in Malawi. Two hundred and three hotel guests took part in the study. Data collection was done with the aid of survey questionnaire; the SPSS version 23.0 software and AMOS software version 22.0 were used for data analysis. Initially, paired samples t-test was used to compare mean scores for desired service expectations across fourteen pairs of hotel services with mean scores for adequate service expectations. The paired samples t-test results indicated that the Zone of Tolerance (ZoT), measured as the difference between the desired and adequate service mean scores, were positive and significantly different in all the 14 pairs. The study engaged the Structural Equation Modelling (SEM) to ascertain the relationships between service expectations and customer contentment as latent variables of the hypothesised model. Both the unidimensionality test and confirmatory factor analysis (CFA) were used to establish the factor structure of the measurement variables in the model. The hypothesis that service expectations do not significantly predict customer satisfaction was rejected (β= 0.793; t=7.969; p<0.05). The study concluded that there were high customer perceptions of services consistent with their expectations; which in turn, significantly predict customer satisfaction in star-rated hotels. The study recommends that managers of star-rated hotel ought to closely monitor and constantly improve hotel service attributes that raise customers’ expectations to enhance customer satisfaction among current hotel guests and possibly aid more customer recruitment.
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