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Article . 2024
License: CC BY
Data sources: Datacite
ZENODO
Article . 2024
License: CC BY
Data sources: Datacite
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BIG DATA ANALYTICS IN HOTEL REVENUE MANAGEMENT

Authors: Sivakumar R D, Assistant Professor, Department of Computer Science; Brindha S, Former Assistant Professor of Business Administration;

BIG DATA ANALYTICS IN HOTEL REVENUE MANAGEMENT

Abstract

The abstract of "Big Data Analytics in Hotel Revenue Management" analyzes how big data analytics are combined with revenue management to create opportunities for the hospitality sector. With a data-driven hospitality sector emerging, the hoteliers have been seen to use sophisticated analytics data to ensure that they can generate revenue from their operations as well as enhance their performance. This report is going to examine the position of big data analytics in hotel revenue management, and it will emphasize on the areas where it brings about the most benefits, and where it presents the world with the most challenges. It is a detailed account of the various components of revenue management including price optimization, demand forecasting, inventory management and also customer segmentation alongside demonstrating how big data analytics can be used to improve decision making for every aspect. Also dealt with is the issue regarding the different types of data sets that are available for access by the hoteliers. These include transactional data, customer demographics, social media activity and online reviews. The last part of the paper aims at discussing how these wide range of data sets and information can be incorporated, analyzed and a derived actionable outcome. These techniques included the application of machine learning, predictive analysis, and data visualization which is somehow a way to distinguish the patterns, trends and the correlation between data of great sizes and complexity. The paper looks to the challenges that arise with big data analytics deployment in hotel revenue management; including data quality, privacy, and organizational resistance, giving practical ways to work through these. Moreover, the article also focuses on the novel trends and possible directions in this field which include but not restricted to the artificial intelligence and internet of the things (IoT) to broaden the practice of revenue management capability. All in all, this paper informs about the possibility for how big data analytics can trigger a revolution among the revenue management practices in the hotel industry, giving hotel operators the tools to make better-informed decisions, perfect their pricing strategies, and obtain better profitability in the long run.

Keywords

Data Integration, Pricing Optimization, Demand Forecasting, Hospitality Industry, Predictive Modeling, Machine Learning, Data Sources, Revenue Optimization, Business Intelligence, Customer Segmentation, Big Data Analytics, Hotel Revenue Management, Data-driven Strategies, Inventory Management, Decision-making

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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