Handbook of Research Methods in Tourism

Handbook of Research Methods in Tourism

Quantitative and Qualitative Approaches

Elgar original reference

Edited by Larry Dwyer, Alison Gill and Neelu Seetaram

This insightful book explores the most important established and emerging qualitative and quantitative research methods in tourism. The authors provide a detailed overview of the nature of the research method, its use in tourism, the advantages and limitations, and future directions for research.

Chapter 2: Regression Analysis

Jaume Rosselló

Subjects: development studies, tourism, environment, environmental sociology, tourism, geography, tourism, research methods, qualitative research methods, quantitative research methods


Jaume Rosselló INTRODUCTION Qualitative and quantitative research methods have often both been classed as useful and legitimate by social researchers. However, during recent decades, quantitative methods have come to prevail in the social sciences, and tourism research is not an exception. The main role of quantitative research has typically been reduced to helping generate and pose hypotheses that can then be tested using mathematical research methods. Nowadays, many tourism journals reflect this bias in favor of quantitative methods, and it can be seen that the purpose of qualitative research is usually to provide information for developing further quantitative research (Lewis et al., 1995). Within the social sciences and some natural sciences, statistics are the most widely used branch of mathematics in quantitative research when hypotheses have to be tested. Statistical methods are extensively used in fields such as economics, social sciences, and biology. Quantitative research using statistical methods starts with the collection of data, based on a certain hypothesis or theory. For instance, quantitative opinion surveys are widely used in tourism, where statistics are commonly reported, such as the proportion of respondents agreeing with a certain stance. In these opinion surveys, the respondents are asked a set of structured questions and their responses are then tabulated. On other occasions, researchers compile and compare different statistics in order to identify some kind of correlation. In this case, when a causal relationship between a “dependent variable” and one or more “independent variables” is hypothesized (and must be tested), regression analysis comes to...

You are not authenticated to view the full text of this chapter or article.

Elgaronline requires a subscription or purchase to access the full text of books or journals. Please login through your library system or with your personal username and password on the homepage.

Non-subscribers can freely search the site, view abstracts/ extracts and download selected front matter and introductory chapters for personal use.

Your library may not have purchased all subject areas. If you are authenticated and think you should have access to this title, please contact your librarian.

Further information