CPN Based Modeling of Tourism Demand Forecasting

  •  Hua Bai    
  •  Haoyuan Zhang    


The tourism demand has become more and more diversified and sensitive to traveling environment, resulting in the high volatility of tourism market. Travel agencies, scenic spots, hotels and other tourism businesses in the tourism supply chain (TSC) need a tight collaboration in order to minimize cost and improve responsiveness and service level. The existence of the bullwhip effect will cause the waste of resources and low efficiency, thus collaborative demand forecasting becomes a good practice to enhance sharing of information and resources, and as a result improving the efficiency and effectiveness of tourism demand forecasting. This paper proposes a collaborative tourism demand forecasting framework based on Colored Petri Net (CPN), which can simulate and examine the effectiveness of tourism supply chain collaboration.

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