Crowding Types and Price Dynamics in Tourism Destinations Choice

Emiliano Alvarez, Juan Gabriel Brida, Nicolas Garrido

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

This article analyzes how the preferences of tourists for types of resorts, crowding types of tourists, and the pricing strategies of the resorts interact to determine the occupancy rate, price, and distribution of welfare in the market of resorts. The model captures the process of acquisition of information of the consumers for making the choice of resorts and a dynamic strategy adopted by the resorts to manage their revenue. After describing the difficulties to introduce an analytical description of the model, an agent-based model (ABM) is presented to explore the properties of the market. The study shows that crowding types of tourists in destinations together with a very simple revenue management heuristic can produce counterintuitive results affecting the distribution of surplus in the markets. When all the managers in a market overreact by raising prices as consequence of a high occupancy rate, they appropriate a larger portion of the surplus of the market. When managers are risk-averse and rapidly reduce prices when occupancy is low, they deliver more welfare to tourists.

Original languageEnglish
Pages (from-to)1-10
Number of pages10
JournalIEEE Transactions on Computational Social Systems
DOIs
Publication statusAccepted/In press - 2022

Keywords

  • Adaptation models
  • Agent-based models (ABMs)
  • Analytical models
  • Behavioral sciences
  • Complex systems
  • complex systems
  • Costs
  • crowding types
  • Games
  • price dynamics
  • Pricing
  • tourism destinations

ASJC Scopus subject areas

  • Modelling and Simulation
  • Social Sciences (miscellaneous)
  • Human-Computer Interaction

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