Tourism Demand Overview

Principles

Definition

Tourism demand is the academic field and methodological approach focused on understanding, measuring, and forecasting the propensity and willingness of individuals and groups to travel to destinations and consume tourism products and services. This concept investigates the complex interplay of socio-economic, psychological, and external factors influencing travel decisions, expenditure patterns, and destination choices, providing critical insights for tourism planning, development, and economic analysis within a sector recognized for its significant economic contribution and sensitivity to global conditions.

Ontological type

Forecasting Models

Determinant Factors

Measurement Approaches

Key developments

Key Figures

Attribute-Based Valuation era

During 1980–1996, the attribute-based valuation paradigm in tourism demand built on Ben-Akiva and Lerman's discrete choice theory, which provided flexible logit specifications for modeling how destination attributes, prices, and travel time drive visitation. Daniel McFadden's multinomial logit and random utility framework further empowered empirical estimation of traveler elasticities and welfare effects within these models. Foundational hedonic and attribute theories from Lancaster and Rosen supplied the conceptual toolkit for valuing destination attributes, with Lancaster emphasizing goods with attributes and Rosen framing attribute-based pricing. Attitude and perceptual measurement methods, drawing on Fishbein and Ajzen's attitude theories and the later planned-behavior framework, guided survey design and interpretation of survey-based valuation and stated-preference responses.

Integrated Demand Modeling era

Reid Ewing [1] of MIT [3] and University of Maryland, College Park [4] exemplified this era's integration of diverse predictors into travel-demand models. This era's key contribution, embodied in Travel and the Built Environment: A Synthesis [7], reflects Reid Ewing [1] and colleagues' integration of urban form, accessibility, and image into travel-demand modeling. Robert Cervero [2], with appointments at University of Washington [5] and University of California, Berkeley [6], helped exemplify the era's emphasis on linking urban form and travel demand. Robert Cervero [2]'s key contribution, as reflected in Travel and the Built Environment: A Synthesis [7], emphasized how land-use patterns, accessibility, and image shape travel behavior, informing the era's multi-factor forecasting and policy-oriented scenario analysis.

Digitalized Experience Demand era

C. Michael Hall [1], associated with Richland College [3] and the University of Maryland, Baltimore [4], contributes to understanding tourism demand in the Digitalized Experience Demand era (2011-2024). His key contribution in this era centers on assessing how pandemics reshape tourism, most notably through the rapid COVID-19 assessment paper Pandemics, tourism and global change: a rapid assessment of COVID-19 [7], which provided timely, data-driven insights into how digitalized experiential demand responds to global health shocks. Daniel Scott [2], with affiliations to the Harvard–MIT Division of Health Sciences and Technology [5] and the Massachusetts Institute of Technology [6], contributes to the same era's discourse on digitally mediated tourism by integrating biomedical and tech-informed perspectives on the convergence of health, risk, and demand. His notable contribution, shared with the rapid COVID-19 assessment [7], helped shape early understanding of pandemic-driven shifts in experiential demand and underscored the value of cross-institutional collaboration in digital tourism analytics.