Hotel daily occupancy forecasting with competitive sets: a recursive algorithm

Purpose – This paper aims to improve the accuracy of hotel daily occupancy forecasts – an essential element in the revenue management cycle – by proposing and testing a novel approach. The authors add the hotel competitive-set’s predicted occupancy as an input of the individual property forecast and...

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Vydáno v:International journal of contemporary hospitality management Ročník 28; číslo 2; s. 267 - 285
Hlavní autoři: Schwartz, Zvi, Uysal, Muzaffer, Webb, Timothy, Altin, Mehmet
Médium: Journal Article
Jazyk:angličtina
Vydáno: Bradford Emerald Group Publishing Limited 08.02.2016
Témata:
Accuracy
Algorithms
Brand image in tourism
Competition
Confidentiality
Customer services
Forecasting
Hospitality industry
Hotels & motels
Information sharing
Inventory
Management decisions
Market segments
Occupancy rates
Optimization
Pricing policies
Revenue management
Time series
Tourism & hospitality
Tourism & hospitality management/marketing
Travel
Trends
Vacations
Hotels
Accuracy
Revenue management
Competitive sets
Forecasting
ISSN:0959-6119, 1757-1049
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Abstract Purpose – This paper aims to improve the accuracy of hotel daily occupancy forecasts – an essential element in the revenue management cycle – by proposing and testing a novel approach. The authors add the hotel competitive-set’s predicted occupancy as an input of the individual property forecast and, using a recursive approach, demonstrate that there is a potential for significant reduction in the forecasting error. Design/methodology/approach – The paper outlines the theoretical justification and the mechanism for this new approach. It applies a simulation for exploring the potential to improve the accuracy of the hotel’s daily occupancy forecasts, as well as analysis of data from a field study of two hotel clusters’ daily forecasts to provide empirical support to the procedure’s viability. Findings – The results provide strong support to the notion that the accuracy could be enhanced. Incorporating the competitive set prediction by using either a genetic algorithm or the simple linear regression model improves the accuracy of the forecast using either the absolute or the absolute percentage as the error measure. Research limitations/implications – The proliferation of data sharing practices in the hotel industry reveals that the timely data sharing-aggregation-dissemination mechanism required for implementing this forecasting paradigm is feasible. Originality/value – Given the crucial role of accurate forecasts in revenue management and recent changes in the hotels’ operating environment which made it harder to achieve or maintain high levels of accuracy, this study’s proposed novel approach has the potential to make a unique contribution in the realm of forecasting daily occupancies.
AbstractList Purpose - This paper aims to improve the accuracy of hotel daily occupancy forecasts - an essential element in the revenue management cycle - by proposing and testing a novel approach. The authors add the hotel competitive-set's predicted occupancy as an input of the individual property forecast and, using a recursive approach, demonstrate that there is a potential for significant reduction in the forecasting error. Design/methodology/approach - The paper outlines the theoretical justification and the mechanism for this new approach. It applies a simulation for exploring the potential to improve the accuracy of the hotel's daily occupancy forecasts, as well as analysis of data from a field study of two hotel clusters' daily forecasts to provide empirical support to the procedure's viability. Findings - The results provide strong support to the notion that the accuracy could be enhanced. Incorporating the competitive set prediction by using either a genetic algorithm or the simple linear regression model improves the accuracy of the forecast using either the absolute or the absolute percentage as the error measure. Research limitations/implications - The proliferation of data sharing practices in the hotel industry reveals that the timely data sharing-aggregation-dissemination mechanism required for implementing this forecasting paradigm is feasible. Originality/value - Given the crucial role of accurate forecasts in revenue management and recent changes in the hotels' operating environment which made it harder to achieve or maintain high levels of accuracy, this study's proposed novel approach has the potential to make a unique contribution in the realm of forecasting daily occupancies.
Purpose – This paper aims to improve the accuracy of hotel daily occupancy forecasts – an essential element in the revenue management cycle – by proposing and testing a novel approach. The authors add the hotel competitive-set’s predicted occupancy as an input of the individual property forecast and, using a recursive approach, demonstrate that there is a potential for significant reduction in the forecasting error. Design/methodology/approach – The paper outlines the theoretical justification and the mechanism for this new approach. It applies a simulation for exploring the potential to improve the accuracy of the hotel’s daily occupancy forecasts, as well as analysis of data from a field study of two hotel clusters’ daily forecasts to provide empirical support to the procedure’s viability. Findings – The results provide strong support to the notion that the accuracy could be enhanced. Incorporating the competitive set prediction by using either a genetic algorithm or the simple linear regression model improves the accuracy of the forecast using either the absolute or the absolute percentage as the error measure. Research limitations/implications – The proliferation of data sharing practices in the hotel industry reveals that the timely data sharing-aggregation-dissemination mechanism required for implementing this forecasting paradigm is feasible. Originality/value – Given the crucial role of accurate forecasts in revenue management and recent changes in the hotels’ operating environment which made it harder to achieve or maintain high levels of accuracy, this study’s proposed novel approach has the potential to make a unique contribution in the realm of forecasting daily occupancies.
Author Webb, Timothy
Altin, Mehmet
Uysal, Muzaffer
Schwartz, Zvi
Author_xml – sequence: 1
  givenname: Zvi
  surname: Schwartz
  fullname: Schwartz, Zvi
  organization: Department of Hotel Restaurant and Institutional Management, Alfred Lerner College of Business and Economics, University of Delaware, Newark, Delaware, USA
– sequence: 2
  givenname: Muzaffer
  surname: Uysal
  fullname: Uysal, Muzaffer
  organization: Department of Hospitality and Tourism Management, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA
– sequence: 3
  givenname: Timothy
  surname: Webb
  fullname: Webb, Timothy
  organization: Department of Hospitality and Tourism Management, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA
– sequence: 4
  givenname: Mehmet
  surname: Altin
  fullname: Altin, Mehmet
  organization: Department of Hospitality and Tourism Management, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA
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Keywords Hotels
Accuracy
Revenue management
Competitive sets
Forecasting
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  doi: 10.1016/j.mcm.2007.03.008
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  doi: 10.1016/j.tourman.2006.08.003
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Snippet Purpose – This paper aims to improve the accuracy of hotel daily occupancy forecasts – an essential element in the revenue management cycle – by proposing and...
Purpose - This paper aims to improve the accuracy of hotel daily occupancy forecasts - an essential element in the revenue management cycle - by proposing and...
Purpose – This paper aims to improve the accuracy of hotel daily occupancy forecasts – an essential element in the revenue management cycle – by proposing and...
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StartPage 267
SubjectTerms Accuracy
Algorithms
Brand image in tourism
Competition
Confidentiality
Customer services
Forecasting
Hospitality industry
Hotels & motels
Information sharing
Inventory
Management decisions
Market segments
Occupancy rates
Optimization
Pricing policies
Revenue management
Time series
Tourism & hospitality
Tourism & hospitality management/marketing
Travel
Trends
Vacations
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Title Hotel daily occupancy forecasting with competitive sets: a recursive algorithm
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