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Compreender a satisfação dos hóspedes em hotéis de estâncias de esqui éimportante, no entanto pouco estudada.Este estudo analisa como a satisfação varia de acordo com a época do ano, do rating, danacionalidade, do tipo de viagem e do ano da estadia. Assim, com base em 8.433 reviewsdo TripAdvisor do Top 10 de hotéis dos Alpes Suíços, aplicámos técnicas de text mining(nomeadamente análise de sentimentos e topic modeling). Foram aplicados testesestatísticos, através do SPSS, para testar as hipóteses criadas.A época baixa, contrariamente ao esperado é quando os hóspedes ficam mais satisfeitos;os hóspedes suíços são os menos satisfeitos, comparativamente aos norte-americanos;as famílias superam todos os grupos na satisfação e a pandemia COVID-19, foi onde houveum maior marco temporal negativo.Ao analisar o topic modeling, o staff, o pequeno almoço e a localização Alpina (Matterhorne Zermatt) são os atributos que mais marcam a experiência dos hóspedes.Os resultados devem orientar decisões estratégicas, para os gestores de hotéis adaptaremos seus serviços em função da época e do perfil do hóspede, de modo a melhorar a satisfação.
Understanding guest satisfaction at ski resort hotels is important, yet it has beenlittle studied.This study analyzes how satisfaction varies according to the time of year, hotel rating,nationality, type of trip, and year of stay. Thus, based on 8,433 TripAdvisor reviews of thetop 10 hotels in the Swiss Alps, we applied text mining techniques (namely sentimentanalysis and topic modeling). Statistical tests were conducted using SPSS to test thehypotheses formulated.Contrary to expectations, the low season is when guests are most satisfied; Swiss guestsare the least satisfied compared to North Americans; families outperform all other groupsin satisfaction, and the COVID-19 pandemic was the period with the most significantnegative impact.Upon analyzing the topic modeling, the staff, breakfast, and the Alpine location(Matterhorn and Zermatt) are the attributes that most significantly shape the guestexperience.The results should guide strategic decisions, enabling hotel managers to adapt theirservices according to the season and guest profile in order to improve satisfaction.
Understanding guest satisfaction at ski resort hotels is important, yet it has beenlittle studied.This study analyzes how satisfaction varies according to the time of year, hotel rating,nationality, type of trip, and year of stay. Thus, based on 8,433 TripAdvisor reviews of thetop 10 hotels in the Swiss Alps, we applied text mining techniques (namely sentimentanalysis and topic modeling). Statistical tests were conducted using SPSS to test thehypotheses formulated.Contrary to expectations, the low season is when guests are most satisfied; Swiss guestsare the least satisfied compared to North Americans; families outperform all other groupsin satisfaction, and the COVID-19 pandemic was the period with the most significantnegative impact.Upon analyzing the topic modeling, the staff, breakfast, and the Alpine location(Matterhorn and Zermatt) are the attributes that most significantly shape the guestexperience.The results should guide strategic decisions, enabling hotel managers to adapt theirservices according to the season and guest profile in order to improve satisfaction.
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Palavras-chave
Satisfação dos hóspedes hóteis de estâncias de esqui text mining Alpes Suíços experiência do cliente