Predicting Thalasso Tourist Delight: A Hybrid SEM—Artificial Intelligence Analysis

Joint Authors

Sánchez-Medina, Agustín J.
Naranjo-Barrera, Ylenia I.
Alonso, Jesús B.
Rufo Torres, Julio Francisco

Source

Complexity

Issue

Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-14, 14 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2018-10-16

Country of Publication

Egypt

No. of Pages

14

Main Subjects

Philosophy

Abstract EN

This study focuses on the influence of the quality of services received by thalassotherapy customers on their global satisfaction and the relationship between this and the word of mouth.

This study uses a hybrid SEM—classification tree analysis.

The empirical findings reveal a significant relationship between the quality of each offered service and global satisfaction.

This study contributes to identify tourist’s satisfaction or delight on received thalasso services through a proposed methodology.

The main contribution of this work consists of the proposal of a methodology to identify objectively through the opinion of tourists if they were satisfied or had reached delight.

This work demonstrates, confirming what has been found in previous literature, that global satisfaction is related to the different experiences provided by the service.

Thus, all hypotheses are accepted, supporting the hypotheses that relate the pool, the staff, the treatments, and the environment to satisfaction.

In addition, the hypotheses that link satisfaction with the word of mouth are also supported.

This theoretical implication has important practical implications for managers of the type of facilities such as those studied in this paper, since it shows that it is not enough to do well in one of the services provided if the environment or the interaction with the staff is not right.

American Psychological Association (APA)

Sánchez-Medina, Agustín J.& Naranjo-Barrera, Ylenia I.& Alonso, Jesús B.& Rufo Torres, Julio Francisco. 2018. Predicting Thalasso Tourist Delight: A Hybrid SEM—Artificial Intelligence Analysis. Complexity،Vol. 2018, no. 2018, pp.1-14.
https://search.emarefa.net/detail/BIM-1134097

Modern Language Association (MLA)

Sánchez-Medina, Agustín J.…[et al.]. Predicting Thalasso Tourist Delight: A Hybrid SEM—Artificial Intelligence Analysis. Complexity No. 2018 (2018), pp.1-14.
https://search.emarefa.net/detail/BIM-1134097

American Medical Association (AMA)

Sánchez-Medina, Agustín J.& Naranjo-Barrera, Ylenia I.& Alonso, Jesús B.& Rufo Torres, Julio Francisco. Predicting Thalasso Tourist Delight: A Hybrid SEM—Artificial Intelligence Analysis. Complexity. 2018. Vol. 2018, no. 2018, pp.1-14.
https://search.emarefa.net/detail/BIM-1134097

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1134097