TY - GEN
T1 - Developing a Web-based collaborative forecasting platform to support tourism supply chain management
AU - Zhang, Xinyan
AU - Song, Haiyan
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
KW - Collaborative forecasting
KW - tourism supply chain
UR - https://www.scopus.com/pages/publications/84903847056
U2 - 10.1109/IEEM.2012.6837979
DO - 10.1109/IEEM.2012.6837979
M3 - Conference contribution
AN - SCOPUS:84903847056
SN - 9781467329453
T3 - IEEE International Conference on Industrial Engineering and Engineering Management
SP - 1414
EP - 1418
BT - 2012 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2012
PB - IEEE Computer Society
T2 - 2012 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2012
Y2 - 10 December 2012 through 13 December 2012
ER -