Studying the effectiveness of investments in hotel services using customer sentiment analysis

Author:

Kozłowski MaciejORCID,Korzeniewski JerzyORCID

Abstract

AbstractThe main aim of the article is to assess investments in hotel services in Poland in 2018–2020. The assessment was carried out by examining the correlation between financial outlays in the hotel industry in powiats (counties) and voivodeships of Poland and customer opinions expressed in internet entries on the websites of individual tourist facilities. The methodology for testing the sentiment of text documents is an unsupervised classification algorithm applied to the Polish language. The classification task consists of the unsupervised assignment of a text document to one of three sentiment classes: positive, neutral, or negative. The research is based on opinions collected from 906 hotels and the amount of financial investment in individual hotel segments (categories) in the surveyed years on a powiat basis. Financial investment data were gathered from the official statistical yearbook websites and internet entries were scraped from the websites of individual tourist facilities. The analysis shows a positive relationship between the size of investment in hotel services and the sentiment of customers' opinions. The scientific contribution of the research is threefold. Firstly, an attempt is made to assess the efficiency of investments in hotel services in Poland in recent years. Secondly, the approach applied omits the downsides of other popular models of assessing the quality of services. Thirdly, the algorithm used quite precisely finds the categories required for a different kind or broader analysis of the quality of hotel services.

Publisher

Springer Science and Business Media LLC

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Customer Feedback and Sentiment Analysis for Hotel Services;2024 International Conference on Distributed Computing and Optimization Techniques (ICDCOT);2024-03-15

2. Sentiment Analysis of User Reactions to Meta's Threads Launch and Twitter's X Renaming;Advances in Business Information Systems and Analytics;2024-02-23

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