Managing Tourist Behavioral Patterns After Travel Based on Big Data Analysis (Case Study: Ferdowsi's Tomb)

Document Type : Original Article

Authors

1 Assistant Professor, Department of Tourism Management, Faculty of Literature and Humanities, Shahrekord University, Shahrekord ,Iran

2 Ph.d of Tourism Management, Tourism Faculty, University of Science & Culture, Tehran, Iran

Abstract

Context and Purpose: The main objective of this research is to manage tourists' behavioral patterns with the help of big data analysis and artificial intelligence, with the aim of improving the tourism experience in attractions.
Design/methodology/approach: This research is an applied type in terms of purpose and a mixed qualitative-quantitative exploratory research in terms of approach. In this research, the big data generated in the travel process is extracted and analyzed using Python. The study population consists of all tourists in the Ferdowsi Mausoleum in Mashhad.
Findings: Based on the modeling of tourists' behavioral patterns and with the help of big data analysis and artificial intelligence in order to improve the tourism experience, big data was extracted in the post-trip stage of tourists. The findings of each stage of the trip show that big data can be useful in examining the current situation after the trip and, in addition, play an effective role in improving the experience.
Conclusion: The results obtained in the studied attraction of Ferdowsi's Tomb show that tourism managers can improve the tourist experience at every stage of the trip by using big data of destination tourist attractions and achieve a comprehensive model in this regard, and use it in all attractions and tourist destinations in the country.
Originality/value: This research uses the latest technologies related to artificial intelligence in the post-trip experience of tourists.

Keywords

References

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Tourism and hospitality marketing research
Volume 3, Issue 1 - Serial Number 4
Spring and Summer
March 2025
Pages 81-100

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