IngentaConnect New Frontiers in Tourist Behavior Research: Steps toward Causal I...

Author: Mazanec, Josef A.¹

Source: Asia Pacific Journal of Tourism Research, Volume 12, Number 3, September 2007 , pp. 223-235(13)

Publisher: Routledge, part of the Taylor & Francis Group

Abstract:

Over the last two decades the range of methods for analyzing causal relationships has been significantly extended. New approaches to the theory of causality rely on the concept of "intervention" instead of "association". Under an axiomatic framework they elaborate the conditions for safe causal inference from non-experimental data. Inferred Causation (IC) Theory combines elements of graph theory, statistics, logic and artificial intelligence research in computer science. It is not limited to parametric models in need of quantitative (ratio or interval scaled) data, but also operates much more generally on the observed conditional independence relationships among a set of qualitative (categorical) observations. Causal inferences do not appear to be restricted to experimental data. This is particularly promising for research domains such as consumer or tourist behavior where data from controlled experiments on real markets are rare. A case example highlights the potential use of Inferred Causation methodology in tourism research. It aims at measuring the direct and indirect influences of destination loyalty, perceived service quality and satisfaction on the tourist's intention to repeat visit.

Keywords: tourist behavior research; causal inference

Document Type: Research article

DOI: 10.1080/10941660701416796

Affiliations: 1: Institute for Tourism and Leisure Studies, Vienna University of Economics and Business Administration, Austria

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New Frontiers in Tourist Behavior Research: Steps toward Causal Inference from Non-experimental Data