Multidimensional Analysis of Booking Data in Hospitality Industry Using Data Warehousing Techniques
Understanding customer behaviors is essential for optimizing pricing strategies, enhancing guest experiences, and effectively meeting demand in the hospitality industry. This study presents the development of a data warehouse system designed to analyze hotel booking behaviors. Using ETL processes...
| Main Authors: | , |
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| Format: | Article |
| Language: | English English |
| Published: |
INTI International University
2024
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| Subjects: | |
| Online Access: | http://eprints.intimal.edu.my/2119/ http://eprints.intimal.edu.my/2119/2/660 http://eprints.intimal.edu.my/2119/3/ij2024_54r.pdf |
| _version_ | 1848766925392314368 |
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| author | Lam, Mai Nguyen, Duc-Hien |
| author_facet | Lam, Mai Nguyen, Duc-Hien |
| author_sort | Lam, Mai |
| building | INTI Institutional Repository |
| collection | Online Access |
| description | Understanding customer behaviors is essential for optimizing pricing strategies, enhancing guest
experiences, and effectively meeting demand in the hospitality industry. This study presents the
development of a data warehouse system designed to analyze hotel booking behaviors. Using ETL
processes, reservation data from diverse sources is consolidated and standardized to enable
comprehensive analysis. Then, multidimensional analyses of booking frequency and transaction
value reveal key customer preferences and behavioral patterns. A real-world dataset comprising
119,390 records spanning from July 1, 2015, to August 31, 2017, was utilized to validate the
system. Multidimensional analyses revealed that 70% of bookings occurred during peak seasons,
with transaction values averaging 25% higher compared to off-peak periods. Additionally,
customers who booked via direct channels displayed a 20% higher retention rate. The results
validate the proposed system's capability to provide actionable intelligence, driving effective
business strategies and supporting predictive modeling in the hospitality industry. |
| first_indexed | 2025-11-14T11:58:53Z |
| format | Article |
| id | intimal-2119 |
| institution | INTI International University |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T11:58:53Z |
| publishDate | 2024 |
| publisher | INTI International University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | intimal-21192025-07-12T07:51:23Z http://eprints.intimal.edu.my/2119/ Multidimensional Analysis of Booking Data in Hospitality Industry Using Data Warehousing Techniques Lam, Mai Nguyen, Duc-Hien H Social Sciences (General) HD Industries. Land use. Labor HD28 Management. Industrial Management Understanding customer behaviors is essential for optimizing pricing strategies, enhancing guest experiences, and effectively meeting demand in the hospitality industry. This study presents the development of a data warehouse system designed to analyze hotel booking behaviors. Using ETL processes, reservation data from diverse sources is consolidated and standardized to enable comprehensive analysis. Then, multidimensional analyses of booking frequency and transaction value reveal key customer preferences and behavioral patterns. A real-world dataset comprising 119,390 records spanning from July 1, 2015, to August 31, 2017, was utilized to validate the system. Multidimensional analyses revealed that 70% of bookings occurred during peak seasons, with transaction values averaging 25% higher compared to off-peak periods. Additionally, customers who booked via direct channels displayed a 20% higher retention rate. The results validate the proposed system's capability to provide actionable intelligence, driving effective business strategies and supporting predictive modeling in the hospitality industry. INTI International University 2024-12 Article PeerReviewed text en cc_by_4 http://eprints.intimal.edu.my/2119/2/660 text en cc_by_4 http://eprints.intimal.edu.my/2119/3/ij2024_54r.pdf Lam, Mai and Nguyen, Duc-Hien (2024) Multidimensional Analysis of Booking Data in Hospitality Industry Using Data Warehousing Techniques. INTI JOURNAL, 2024 (54). pp. 1-10. ISSN e2600-7320 https://intijournal.intimal.edu.my |
| spellingShingle | H Social Sciences (General) HD Industries. Land use. Labor HD28 Management. Industrial Management Lam, Mai Nguyen, Duc-Hien Multidimensional Analysis of Booking Data in Hospitality Industry Using Data Warehousing Techniques |
| title | Multidimensional Analysis of Booking Data in Hospitality Industry Using Data Warehousing Techniques |
| title_full | Multidimensional Analysis of Booking Data in Hospitality Industry Using Data Warehousing Techniques |
| title_fullStr | Multidimensional Analysis of Booking Data in Hospitality Industry Using Data Warehousing Techniques |
| title_full_unstemmed | Multidimensional Analysis of Booking Data in Hospitality Industry Using Data Warehousing Techniques |
| title_short | Multidimensional Analysis of Booking Data in Hospitality Industry Using Data Warehousing Techniques |
| title_sort | multidimensional analysis of booking data in hospitality industry using data warehousing techniques |
| topic | H Social Sciences (General) HD Industries. Land use. Labor HD28 Management. Industrial Management |
| url | http://eprints.intimal.edu.my/2119/ http://eprints.intimal.edu.my/2119/ http://eprints.intimal.edu.my/2119/2/660 http://eprints.intimal.edu.my/2119/3/ij2024_54r.pdf |