Article: Neural networks to analyse the incidence of customer satisfaction in their loyalty in a tourist destination Journal: International Journal of Services, Economics and Management (IJSEM) 2018 Vol.9 No.2 pp.95 - 110 Abstract: The relationship between levels of satisfaction experienced and its expression in future projected behaviour is widely addressed in the literature, however in the context of tourism in general and tourist destinations in particular acquires distinctive features that demand further research and deepening in this relationship. This research seeks to deepen this relationship, using techniques such as the analysis of neural networks since it allows identifying hidden relationships among multiple variables when working with large databases. The study was carried out in a tourist destination of sun and beach, allowing first verify the latent variables present in the construct of customer satisfaction and then, through the analysis of neural networks, corroborate that there is a high relationship between levels of satisfaction experienced by tourists and their willingness to return and recommend the destination or willingness to discredit the destination whenever dissatisfactions are generated, noting that this last relationship was more significant. Likewise, it is identified which attributes of the service have the most influence on each of these decisions, observing that in each of the previous decisions, the attributes influence differently. Inderscience Publishers - linking academia, business and industry through research

Title: Neural networks to analyse the incidence of customer satisfaction in their loyalty in a tourist destination

Authors: Reyner Pérez-Campdesuñer; Alexander Sánchez-Rodríguez; Gelmar García-Vidal; Rodobaldo Martínez-Vivar

Addresses: Faculty of Administrative Sciences, Universidad UTE, Vía Chone, km 4 1/2, 230103, Santo Domingo, Ecuador ' Faculty of Administrative Sciences, Universidad UTE, Vía Chone, km 4 1/2, 230103, Santo Domingo, Ecuador ' Faculty of Administrative Sciences, Universidad UTE, Vía Chone, km 4 1/2, 230103, Santo Domingo, Ecuador ' Faculty of Administrative Sciences, Universidad UTE, Vía Chone, km 4 1/2, 230103, Santo Domingo, Ecuador

Abstract: The relationship between levels of satisfaction experienced and its expression in future projected behaviour is widely addressed in the literature, however in the context of tourism in general and tourist destinations in particular acquires distinctive features that demand further research and deepening in this relationship. This research seeks to deepen this relationship, using techniques such as the analysis of neural networks since it allows identifying hidden relationships among multiple variables when working with large databases. The study was carried out in a tourist destination of sun and beach, allowing first verify the latent variables present in the construct of customer satisfaction and then, through the analysis of neural networks, corroborate that there is a high relationship between levels of satisfaction experienced by tourists and their willingness to return and recommend the destination or willingness to discredit the destination whenever dissatisfactions are generated, noting that this last relationship was more significant. Likewise, it is identified which attributes of the service have the most influence on each of these decisions, observing that in each of the previous decisions, the attributes influence differently.

Keywords: neural networks; customer satisfaction; loyalty; tourist destination.

DOI: 10.1504/IJSEM.2018.096065

International Journal of Services, Economics and Management, 2018 Vol.9 No.2, pp.95 - 110

Received: 28 Nov 2017
Accepted: 13 Jul 2018
Published online: 09 Nov 2018 *

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Title: Neural networks to analyse the incidence of customer satisfaction in their loyalty in a tourist destination

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