# Using a market basket analysis in tourism studies

**Authors:** Damjan Vavpotič, Karmen Knavs, Ljubica Knežević Cvelbar  
**arXiv:** [2110.10679](https://arxiv.org/abs/2110.10679)  
**Date:** 2021-10-20  
**Summary page:** https://www.summarizepaper.com/en/paper/2110.10679v1/

## Key points

- Understanding tourist visitation patterns is crucial for decision makers in the tourism industry
- Geo-location data plays a significant role in understanding tourism demand
- The study proposes a new approach based on market basket analysis using geo-location data shared by tourists
- The approach bundles available services and identifies commonly consumed experiences
- The researchers applied this approach to analyze tourist behavior in Vienna, Austria
- The proposed method has potential for use at the destination level
- Findings from the study provide valuable information on tourism demand patterns
- Decision makers can optimize offerings and create tailored packages or recommendations based on frequently combined experiences
- Geo-location data and market basket analysis are effective tools for analyzing tourism demand patterns.

## Summary

In the study titled "Using a Market Basket Analysis in Tourism Studies," authors Damjan Vavpotič, Karmen Knavs, and Ljubica Knežević Cvelbar emphasize the importance of understanding tourist visitation patterns for decision makers in order to create a smart tourism industry. They highlight that geo-location data plays a crucial role in better understanding tourism demand. To contribute to this field of research, the authors propose a new approach based on market basket analysis. This approach utilizes geo-location data shared by tourists on various tourism platforms to bundle the range of available services and identify which experiences are commonly consumed together. The researchers applied this approach to analyze tourist behavior in Vienna, Austria. Through their analyses, they argue that their proposed method has significant potential for use at the destination level. The findings from this study provide relevant information on tourism demand patterns that can be valuable for smart tourism decision-making. By identifying which experiences are frequently combined by tourists, decision makers can optimize their offerings and create tailored packages or recommendations to enhance visitor experiences. Overall, this research contributes to the growing body of knowledge on using geo-location data for understanding tourist behavior and highlights the potential of market basket analysis as an effective tool in analyzing tourism demand patterns.