Machine Learning in Tourism Revenue Management

Maria Enache

Economics and Applied Informatics, 2019, issue 1, 132-136

Abstract: Machine learning algorithms increase the efficiency of revenue management systems. Real-time data processing, customization, and automation are the key features that make it possible to overcome the performance of old systems in determining the price and time for a satisfactory offer and maximize revenue. Good practice is hiring external scientists to build segmentation and forecasting features. Such solutions require the collection of user information, which is hard to do without custom-built behavior and a market tracking engine.

Keywords: Business; IT; Models (search for similar items in EconPapers)
Date: 2019
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.eia.feaa.ugal.ro/images/eia/2019_1/Enache%201.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ddj:fseeai:y:2019:i:1:p:132-136

DOI: 10.35219/eai1584040915

Access Statistics for this article

More articles in Economics and Applied Informatics from "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration Contact information at EDIRC.
Bibliographic data for series maintained by Gianina Mihai ().