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Tourism Forecasting and Environment

Ann Smith, Markus Dablander, Constantin Octavian Puiu, Brady Metherall, William Lee, Ruzanna Ab Razak, Noriszura Ismail

Research output: Working paperDiscussion paper

Abstract

Congestion in Edinburgh is a major issue, especially during peak visitor periods. The primary aim of this study was to develop a practical forecasting tool providing visitor volume, and visitor segmentation projections, to assist the travel and hospitality sectors in their planning. To address this a predictive model has been established based on Edinburgh Castle visitor records in conjunction with the Google Trends popularity index for Edinburgh Castle. Popularity of attractions was found to increase around major events with on-line search trends offering an indication of expected volume. Preliminary findings indicate predictions are feasible and could be improved should data relevant to other attractions and sectors be available.
Original languageEnglish
PublisherCambridge University Press
Number of pages24
DOIs
Publication statusPublished - 21 Mar 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 8 - Decent Work and Economic Growth
    SDG 8 Decent Work and Economic Growth
  2. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

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