In order to provide more efficient services and quality and improve its e-government features, the Polytechnic University of Bari enriched its usual request of evaluation by their users (students) with an online survey focused on satisfaction about the quality of website services. In this paper we chosen to measure the customer satisfaction by building three synthetic indices. The first index is simply represented by the raw judgement of the respondents about their opinion on the whole website’s quality. The second one was built as weighted average of all item scores of the survey’s questionnaire, divided in conceptual sections, by using, as weight, the correlation index between each section’s mean and the item of the final overall judgment. The third index was calculated similarly to the previous one, but considering the importance of each single item in the overall correlation matrix, by using as weight their communalities in a Principal Component Analysis. Then, a comparison between the three indices was done, by using various tools of multivariate analysis, and the index which appeared more suitable to differentiate the users by their “customer satisfaction” was used to define the user profiles
Relationships between User Characteristics and Customer Satisfaction about University Websites
Crocetta, C.;D'OVIDIO, Francesco Domenico;MANCARELLA, ROSSANA;TOMA, Ernesto
2016-01-01
Abstract
In order to provide more efficient services and quality and improve its e-government features, the Polytechnic University of Bari enriched its usual request of evaluation by their users (students) with an online survey focused on satisfaction about the quality of website services. In this paper we chosen to measure the customer satisfaction by building three synthetic indices. The first index is simply represented by the raw judgement of the respondents about their opinion on the whole website’s quality. The second one was built as weighted average of all item scores of the survey’s questionnaire, divided in conceptual sections, by using, as weight, the correlation index between each section’s mean and the item of the final overall judgment. The third index was calculated similarly to the previous one, but considering the importance of each single item in the overall correlation matrix, by using as weight their communalities in a Principal Component Analysis. Then, a comparison between the three indices was done, by using various tools of multivariate analysis, and the index which appeared more suitable to differentiate the users by their “customer satisfaction” was used to define the user profilesFile | Dimensione | Formato | |
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