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Advisor(s)
Abstract(s)
Due to the perishable nature of tourist products, which impacts supply and demand, the
possibility of analysing the relationship between customers’ satisfaction and service quality can
contribute to increased revenues. Machine learning techniques allow the analysis of how these services
can be improved or developed and how to reach new markets, and look for the emergence of ideas to
innovate and improve interaction with the customer. This paper presents a decision-support system
for analysing consumer satisfaction, based on consumer feedback from the customer’s experience
when transported by a transfer company, in the present case working in the Algarve region, Portugal.
The results show how tourists perceive the service and which factors influence their level of satisfaction
and sentiment. One of the results revealed that the first impression associated with good news is what
creates the most value in the experience, i.e., “first impressions matter”..
Description
Keywords
Customer satisfaction Sentiment analysis Tourism transport Machine learning techniques OLAP Data mining Business analytics
Citation
Multimodal Technologies and Interaction 7 (1): 5 (2023)
Publisher
MDPI