Predictive models of hotel booking cancellation: a semi-automated analysis of the literature
This study sought to combine data science tools and capabilities with human judgement and interpretation in order to demonstrate how semiautomatic analysis of the literature can contribute to identifying and synthesising research findings and topics about booking cancellation forecasting. The st...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
University of Algarve, ESGHT/CINTURS
2019-01-01
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| Series: | Tourism & Management Studies |
| Subjects: | |
| Online Access: | https://www.tmstudies.net/index.php/ectms/article/view/1107/pdf_117 |
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| Summary: | This study sought to combine data science tools and capabilities
with human judgement and interpretation in order to demonstrate
how semiautomatic analysis of the literature can contribute to
identifying and synthesising research findings and topics about
booking cancellation forecasting. The study also focused on
recording in detail the analysis’s full experimental procedure to
encourage other researchers to conduct automated literature
reviews in order to understand more fully the current tendencies in
their field of study. The data were obtained through a keyword
search in Scopus and Web of Science databases. The methodology
presented not only diminishes human bias but also enhances data
visualisation and text mining techniques’ ability to facilitate
abstraction, expedite analysis and improve literature reviews. The
results show that, despite the importance of forecasting booking
cancellations to understanding net demand and improving
cancellation and overbooking policies, further research on this
subject is needed. |
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| ISSN: | 2182-8466 |