An integrative framework for collaborative forecasting in tourism supply chains

Xinyan Zhang, Haiyan Song

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

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 4 decades, 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.

Original languageEnglish
Pages (from-to)158-171
Number of pages14
JournalInternational Journal of Tourism Research
Volume20
Issue number2
DOIs
Publication statusPublished - 1 Mar 2018

Keywords

  • collaborative forecasting
  • forecasting
  • forecasting support system
  • tourism demand
  • tourism supply chain

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