Using logistic regression for persona segmentation in tourism: A case study

2020 ◽  
Vol 48 (4) ◽  
pp. 1-16
Author(s):  
Rui Kang
Keyword(s):  
Logistic Regression ◽  
Regression Models ◽  
Tourism Industry ◽  
Opinion Leaders ◽  
Service Users ◽  
User Characteristics ◽  
Logistic Regression Models ◽  
Integrated Method ◽  
Tourism Motivation

I introduced a method for persona segmentation in the tourism industry to identify representative subgroups with different motivations or goals. Data from 496 key opinion leaders of groups representing 7,965 travel service users were analyzed with a logistic regression model of user characteristics and tourism motivation. I found that logistic regression is an integrated method of persona segmentation that balances precision and accuracy, and yields replicable and valid results. Three subgroups for persona segmentation based on logistic regression models are proposed.

Statistical simulation of ocean current patterns using autoregressive logistic regression models: A case study in the Gulf of Mexico

2019 ◽  
Vol 136 ◽  
pp. 1-12 ◽  
Author(s):  
Helios Chiri ◽  
Ana Julia Abascal ◽  
Sonia Castanedo ◽  
José Antonio A. Antolínez ◽  
Yonggang Liu ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Gulf Of Mexico ◽  
Regression Models ◽  
Statistical Simulation ◽  
Ocean Current ◽  
Logistic Regression Models

Procrastination of Travel: The Effect of Crowdedness

2018 ◽  
Vol 43 (3) ◽  
pp. 447-460 ◽  
Author(s):  
Yuan Wang ◽  
Xiang (Robert) Li
Keyword(s):  
Logistic Regression ◽  
Regression Models ◽  
Travel Cost ◽  
Tourism Industry ◽  
Theme Park ◽  
Logistic Regression Models ◽  
Travel And Tourism ◽  
Binomial Logistic Regression ◽  
Specific Timing

The tendency to postpone an action, otherwise known as procrastination, is related to the discounting of future costs. In a tourism context, despite having the best intentions to travel, people may procrastinate their trips. Considering crowding as a type of travel cost, this study examined the effects of crowdedness on travelers’ intentions to visit a theme park and their intended timing of the visit. The results of binomial logistic regression models reveal that crowdedness is negatively related to tourists’ theme park visit intention. More important, crowding is associated with people’s procrastination on their specific timing of visiting the theme park. By focusing on the effect of travel cost (i.e., crowding) on procrastination, this paper calls for more attention to procrastination in the travel and tourism industry and proposes procrastination as a different angle to look at the nontravel phenomenon.

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