The Hong Kong Polytechnic University
The Hong Kong Polytechnic University
Hong Kong Tourism Demand Forecasting System
Public Policy Research Institute
School of Hotel and Tourism Management

The System Won the Silver Award in the 6th International Invention Exhibition

Thursday, November 20, 2008

The 6th International Invention Exhibition (Oct 16 - 19, Suzhou, China) has been successfully concluded. The web-based tourism demand forecasting system has received the Silver Award.

The exhibition was sponsored by International Federation of Inventors' Associations (IFIA),China Association of Inventions (CAI), Science and technology bureau of Jiangsu Province and Government of Suzhou city, with exhibitors coming from 39 countries in Asia, Europe, North America and Africa. The Web-based Tourism Demand System participated and was awarded with a Silver medal.

Jointly developed by PolyU's Public Policy Research Institute and SHTM, this System is maintained by an expert panel led by Prof. Haiyan Song. The sophisticated system forecasts tourism-related demands in terms of tourist arrival, expenditure by sectors and hotel room nights. The forecast figures are available for 10 major source countries and regions, including Australia, Japan, Korea, Macao, the Chinese mainland, the Philippines, Singapore, Taiwan, UK and US. Not only does the System measures incoming tourists, it also predicts the number of outgoing Hong Kong residents and their preference of tourist destinations in the next decade, providing useful figures for industry practitioners to project future demand. More importantly, using this system, industry personnel can generate different scenario analysis based on their own estimation of economic growth rate and fluctuation in currency exchange rates. This built-in scenario analysis tool can be very useful for policy evaluation and decision making.

Like other Web-based systems, the System has four significant features -- wide accessibility, flexibility, reusability, and user friendliness. Through the Web technology, the transfer of knowledge from experts in tourism forecasting to tourism-related decision makers is improved considerably. Forecasting accuracy and reliability are therefore enhanced.