DocumentCode
690902
Title
Developing a Web-based collaborative forecasting platform to support tourism supply chain management
Author
Xinyan Zhang ; Haiyan Song
Author_Institution
Sch. of Prof. Educ. & Executive Dev., Hong Kong Polytech. Univ., Hong Kong, China
fYear
2012
fDate
10-13 Dec. 2012
Firstpage
1414
Lastpage
1418
Abstract
Tourism is a networked industry where clusters of organizations coordinate, cooperate, or compete in a dynamic environment. Therefore tourism industry is well suited to the concept of the supply chain. It is believed that applying supply chain management strategy to the tourism industry provides a new research opportunity to generate insights into how a tourism supply chain (TSC) develops a sustainable competitive advantage, especially when the demand uncertainty is high. Along this line, this paper is aimed at developing a Web-based platform for TSC members to conduct collaborative forecasting. Unlike the traditional stand-alone forecasting process in which individual tourism practitioners produce demand predictions based on their private or partial information, collaborative forecasting breaks down the “island of analysis” and involves reliance on TSC partners to provide specific and timely information on important derivers of future demand. Specific designs of the collaborative forecasting platform are proposed in this paper, and this includes the user classification, forecasting method selection, and platform structure design.
Keywords
Internet; supply chain management; travel industry; TSC; Web-based collaborative forecasting platform; demand predictions; demand uncertainty; forecasting method selection; island of analysis; networked industry; platform structure design; stand-alone forecasting process; tourism industry; tourism supply chain management strategy; user classification; Biological system modeling; Collaboration; Forecasting; Industries; Predictive models; Supply chains; Collaborative forecasting; tourism supply chain;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Engineering and Engineering Management (IEEM), 2012 IEEE International Conference on
Conference_Location
Hong Kong
Type
conf
DOI
10.1109/IEEM.2012.6837979
Filename
6837979
Link To Document