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Title: An integrative framework for collaborative forecasting in tourism supply chains
Authors: Zhang, XY 
Song, HY 
Keywords: Collaborative forecasting
Forecasting support system
Tourism demand
Tourism supply chain
Issue Date: 2018
Publisher: John Wiley & Sons
Source: International journal of tourism research, Mar.-Apr. 2018, v. 20, no. 2, p. 158-171 How to cite?
Journal: International journal of tourism research 
Abstract: Tourism practitioners must often rely on each other in a tourism supply chain (TSC). Demand forecasting plays a key role in shaping the activities of TSC practitioners. In the past 4decades, researchers have developed many techniques for advanced tourism demand forecasting, but practitioners have had little interest in them. To bridge this gap, we examine the nature of the forecasting tasks of TSC practitioners in Hong Kong and propose a collaborative TSC forecasting framework that not only integrates tourism demand forecasting methods with practitioners' knowledge, but also facilitates information sharing between TSC practitioners to increase industry collaboration and improve forecasting performance.
ISSN: 1099-2340
EISSN: 1522-1970
DOI: 10.1002/jtr.2168
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