Qualitative vs. quantitative research techniques in tourism

Molho E.

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Qualitative vs. quantitative research techniques in tourism

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Lecture
Résumé
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Résumé du document

Research in the field of tourism has not been very important until the early nineteen seventies; it has begun to spread only since that time. Marketing research is a broad concept including various techniques, but a main distinction should be done between quantitative and qualitative research methods. Quantitative techniques describe variables by assigning a number – representing an attitude, opinion or motivation- which can be statistically analyzed. In contrast, qualitative research focuses on attitudes, opinions and motivations in the words of each respondent, but without quantifying it. Quantitative methods have always dominated in tourism, as it often appears as more reliable, since it is based on facts that can be observed, and then analysed. However, qualitative techniques have become to be more and more used for the last decade. Each technique has obviously specific advantages and drawbacks; that is why it is necessary to examine both in different contexts, especially in tourism research. As Alf H. Walle reported in his report called “Quantitative versus Qualitative Research in Tourism”, “plurality of equally valid research strategies exist within tourism. Choice must be thus determined according to the situation in which the research takes place.”

Sommaire

Introduction.
Quantitative methods.
1. Domination of quantitative methods in tourism.
2. Factors to be considered.
3. The kind of marketing research required.
4. Importance of differentiating primary data and secondary data.
5. Quantification of the data.
Quantitative techniques.
1. Hypothesis testing.
2. Correlation and regression analysis.
3. The discriminant analysis.
4. Factor analysis and cluster analysis.
Explanation of a quantitative research.
Drawbacks of quantitative methods.
Qualitative techniques.
1. Focus on the typology of motivations in tourism.
2. Direct methods.
Usefulness of Indirect qualitative methods.
Examples of qualitative research.
Evaluation of qualitative methods and the impact.
Conclusion.
Bibliography.

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Extraits

[...] This usually takes a long time, but a large sample can be used easily. Finally, causal research establishes a cause-effect link between variables. The principal method of collection of data is experiments, such as table tests; this method is however time-consuming and expensive. Whatever the choice may be, the final decision should always be made according to the nature of the problem, time constraints, the secrecy and degree of precision required. Equally important is the difference to make between secondary and primary data. [...]

[...] Another example of quantitative research in tourism is the report called Evaluation of Models of Human Decision Making for predicting Leisure Choice Behaviour” which has been written by BL Driver USDA, Edwin E. Krumpe and Wej Paradice. The purpose here was to increase predictability about leisure choices, by focusing on six generics models of decision making, which are the followings: the basic-multiple-attribute model, the Fishbein- Ajzen model, the conjoint model, the discrete choice model, the Lens model and finally the lexicographic model. [...]

[...] As we have seen, both quantitative and qualitative research methods have advantages and drawbacks. To solve this problem and overcome the limitations, the principal solution appears to be the use of both methods in the same time, according to the situation. As Miller and Crabtree pointed out, different levels of “intensity” can be reached in tourism research, this “intensity” being defined as the “degree to which qualitative methods are associated with quantitative methods”. They distinguished four possible designs; first of all the concurrent level uses quantitative and qualitative tools simultaneously on the same question. [...]

[...] The “science versus art dichotomy” can therefore be used in the field of tourism; science indeed involves exactness and quantification but without looking for insights or intuitions and eliminates some difficult aspects of situations that appear not very clear or exact; the risk is also to oversimplify reality. Moreover, a “scientific approach” may take a far too long time to be implemented. Yet, despite these disadvantages, the reasons why quantitative methods have always been used more frequently than qualitative techniques are quite obvious. [...]

[...] Factor loadings, scores and variance thus explain percentages. However, subjectivity is a problem when it comes to interpret the number of factors. To face this limitation, cluster analysis can be a good research tool: it consists in grouping objects or people into clusters, with an eventual additional information such as the distance of each object to the centre of its cluster, or to the centre of the next closest cluster. An example of cluster analysis is the research that has been carried out by Becken and Gnoth in 2004, whose report is called “Tourism Management: Tourist Consumption System among Overseas Visitors: Reporting on American, German and Australian Visitors to New Zealand” They used a cluster analysis to define segments that behave similarly in relation to their travel decisions. [...]

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