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Decoding hotel reviewers: Insights from a decision tree analysis Cover

Decoding hotel reviewers: Insights from a decision tree analysis

Open Access
|Jun 2025

Figures & Tables

Figure 1

Conceptual model framework.
Conceptual model framework.

Figure 2

DT (test sample) of triggers for eWOM hotel reviews.
DT (test sample) of triggers for eWOM hotel reviews.

Description of variables of questionnaire_

Q1: Do you use or have you ever used the Internet (on computers, tablets, cell phones) to search for hotel information?
Yes/No (end of survey)
Q2: Please check the sites or platforms where you usually look for information about hotels, indicating the ones you use the most.
Q2 is subdivided into 14 variables, each one of them specifying a platform/site. Respondents need to evaluate all of them individually in a 4-point Likert scale: 1 never, 2 little, 3 quite a lot, 4 the most
Q2_OTA1; Q2_RS1; Q2_RS2; Q2_OTA3; Q2_OTA2; Q2_OTA4; Q2_OTA5; Q2_OTA6; Q2_SMP1; Q2_SMP2; Q2_SMP4; Q2_SMP3
Q2_OTA7; Q2_OTA8
Q3: How likely are you to write an opinion after staying in a hotel (approximately how many times do you do it)?
5-point Likert scale: never, rarely, about half of the time, often, and always
Gender: male/female
Age: 18–21, 22–30, 31–45, 46–65, 66–80, over 80
Household status: I live:
Alone; with my partner; with friends; with my partner and children; with my family (parents, siblings, etc.)
Work status:
Not currently employed (studying, unemployed, retired); self-employed; work as a salaried employee in a small company; work as a salaried employee in a large company; manager in a small company; manager in a large company
Educational level:
School graduate; intermediate vocational training; higher vocational training; university degree/graduated; higher studies (Master’s degree, doctorate, etc.)
Net monthly income (in euros)
Less than 1,000; 1,001–2,000; 2,001–3,000; 3,001–4,000; 4,001–5,000; 5,001–6,000; over 6,000

Classification table of DT model_

Classification
SampleObservedPredicted
Training Never/rarelyHalf/often/alwaysPercent Correct (%)
Never/rarely15015149.8
Half/often/always7514265.4
Overall percentage 56.4
TestNever/rarely745955.6
Half/often/always305865.9
Overall percentage 59.7

Classification table of logistic regression model_

Classification
ObservedPredicted
Never/rarelyHalf/often/alwaysPercent correct (%)
Never/rarely3805487.6
Half/often/always22085 27.9
Overall percentage 62.9
DOI: https://doi.org/10.2478/mmcks-2025-0010 | Journal eISSN: 2069-8887 | Journal ISSN: 1842-0206
Language: English
Page range: 81 - 92
Submitted on: Feb 19, 2025
Accepted on: Jun 24, 2025
Published on: Jun 26, 2025
Published by: Society for Business Excellence
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2025 Miguel Llorens-Marin, Adolfo Hernandez, Maria Puelles-Gallo, published by Society for Business Excellence
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.