README for Supplementary Data Files

This folder contains the supplementary data files prepared for editorial assessment and confidential peer review of the manuscript entitled:

"Deconstructing the formation of ski tourism destination experience quality: a configurational framework based on online reviews"

The files included in this package are described as follows:

1. Data 1. Ski-related POIs and geographic coordinates.xlsx
Contains the initial pool of ski-related points of interest collected for sample screening, together with their geographic coordinate information and related screening fields.

2. Data 2. Final sample of 91 ski tourism destinations.xlsx
Contains the final screened sample of 91 ski tourism destinations retained for destination-level analysis.

3. Data 3. Online_reviews_of_91_ski_tourism_destinations.zip
Contains the effective review corpus retained for analysis after excluding platform-generated default positive comments and other low-information entries. This dataset was used as the textual basis for preprocessing, BERTopic modeling, sentiment scoring, and the construction of destination-level analytical variables. If needed, the package may include cleaned review files, segmented review files, and a brief codebook or readme describing the file structure and processing procedures.

4. Data 4. Analytical_dataset_before_calibration.xlsx
Contains the destination-level analytical dataset before fuzzy-set calibration, including the outcome variable and all antecedent condition variables used in the NCA and fsQCA analyses. It also includes variable mapping, notes, and descriptive statistics.

5. Data 5. Calibrated_analytical_dataset.xlsx
Contains the calibrated fuzzy-set dataset used as the direct analytical input for the configurational analyses.

6. Data 6. NCA_and_fsQCA_results.xlsx
Contains the main analytical outputs, including variable mapping, calibration anchors, NCA results, fsQCA necessity analysis, truth tables, high-EQ and low-EQ solution summaries, low-EQ intermediate and parsimonious solution sheets used for Table 6 coding, case-membership information, and robustness checks for both high EQ and low EQ.

7. Code 1. BERTopic_topic_modeling_pipeline.py
Provides the BERTopic-based topic modeling pipeline used to generate topic assignments, topic information, representative documents, and keyword outputs.

8. Code 2. Review_preprocessing_and_sentence_segmentation.py
Provides the review cleaning and rule-based sentence segmentation procedure used to remove low-information reviews and prepare the textual corpus for analysis.

9. Code 3. Topic_sentiment_scoring.py
Provides the script used to merge topic assignments with segmented reviews and generate sentiment scores for subsequent analysis.

10. Code 4. Destination_level_variable_construction.py
Provides the script used to aggregate topic-level sentiment information to the destination level and construct the outcome and antecedent variables.

11. Code 5. Fuzzy_set_calibration.py
Provides the script used to calculate calibration anchors and convert continuous variables into fuzzy-set membership scores.

12. Code 6. NCA_analysis.py
Provides the script used to conduct the Necessary Condition Analysis and generate ceiling-line plots and bottleneck results.

13. Code 7. fsQCA_analysis_and_robustness.R
Provides the script used to conduct fsQCA analyses and robustness checks, including the low-EQ solution coding logic used for the final Table 6.

14. README_for_Supplementary_Data_Files.txt
Describes the contents and purpose of each supplementary file.

15. Data_Availability_Statement.txt
Provides the data availability statement for the manuscript and the submission system.

