Exploring travel agencies customers’ loyalty motives throught machine learning analysis

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Technická Univerzita v Liberci
Technical university of Liberec, Czech Republic
This article focuses on identifying the directions of changes in the decision-making process of purchasing package travels and the motives determining this purchase, as well as the impact of these motives on the affective, behavioral and global loyalty of travel agency customers during the COVID-19 pandemic. To achieve the research goal, a literature review and field research were conducted. In the case of secondary sources, the content analysis method was used to examine them, while data from primary sources (N = 1,508) were collected using an indirect survey technique (CAWI). The data analysis was carried out using machine learning – the variable importance method and the random forest algorithm. The obtained results allowed us to conclude that during the period of threat of the COVID-19 virus pandemic, tourist packages had been purchased less frequently, and buyers either had limited their trips to domestic trips or had adapted their travel destinations to the changing pandemic situation. The most important motivators that determined the choice of a travel agency during the COVID-19 pandemic were an attractive offer, a wide selection of package travels, previous positive experiences and trust in the organiser. It was also confirmed that in the face of the pandemic threat, buyers of package travels had been loyal to travel agencies. The use of machine learning allowed for more in-depth analyses and identification of motives that had a key impact on the development of buyer loyalty during the pandemic. The factors identified in the study encouraging buyers of package travels to maintain long-term relationships with their suppliers are belief in the value of the travel agency’s offer, trust in the travel agency, individual approach travel agency employees, efficient service in the travel agency, and a wide selection of package travels.
Tourist package, travel agency, customer behavior, random forest, COVID-19 pandemic