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Developing a Web-based tourism demand forecasting system

delete2008-09-01
delete19
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OA
AI
H
Haiyan Song *
S
Stephen F. Witt
X
Xinyan Zhang
DOI:10.5367/000000008785633578delete
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摘要

摘要

En 中文
Tourism demand is the foundation on which all tourism-related business decisions ultimately rest and so accurate forecasts of tourism demand are crucial for tourism industry practitioners. From the functional point of view, a tourism demand forecasting system (TDFS) is a forecasting support system capable of providing quantitative tourism demand forecasts and allowing users to make their own 'what-if' scenario forecasts. From the technical point of view, a TDFS is an information system consisting of a set of computer-based modules or components that support tourism demand forecasting and scenario analysis. This paper establishes a widely accessible Web-based TDFS which not only takes advantage of advanced econometric tourism demand forecasting techniques but also incorporates the real-time judgemental contribution of experts in the field. Furthermore, scenario forecasts are permitted within the system. Built on Web-based technology, the system provides advanced information sharing and communication and brings considerable convenience to various stakeholders engaged in tourism demand forecasting at different locations. In attempting to generate more accurate tourism demand forecasts, the system is designed to incorporate a two-stage forecasting methodology, which integrates judgemental adjustments with statistically based forecasts. The software architecture, detailed components and development environment of the Web-based TDFS are described in detail. A three-tiered client-server architecture is employed, which offers great flexibility, reusability and reliability. The prototype system has been developed and screen shots of interaction with the system are presented using Hong Kong tourism as an example.
Keyword:
tourism demand forecasts
econometric models
forecasting systems
judgemental forecasts
Web/Internet
Hong Kong

期刊

Tourism Economics 封面图
Tourism Economics
IF:
3.2
论文数:
1.7K
被引数:
4.2K

机构

H
hong kong polytechnic university
学者数:
3.0W
论文数: 4.1W
被引数: 921
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