On tourism and hospitality management research: A critical realist proposal

Abstract

There is a growing literature discussing the role of different research methods in Tourism and Hospitality Research and, in particular, arguing that some re-evaluation of their use is necessary if Tourism and Hospitality is to become a progressive research programme. This paper argues that the literature does not address the philosophical consistency of the use of different methods. It either falls back onto a false dual of advocating quantitative or qualitative research methods, or fails to fully explore the justification for triangulating methods. This paper argues that, based in a philosophical position known as Critical Realism, a consistent research programme involving the triangulation of quantitative and qualitative methods can be established.

Notes

For a discussion of the changing conception of positivism in sociology, see Halfpenny (1982). For a discussion in economics, see Walters and Young (2001).

The dualistic distinction of theory/fact is echoed by the distinctions between fact/value and science/non-science, which imply knowledge/non-knowledge.

However, Popper's philosophical arguments differ from the common practice of ‘rejecting’ null hypotheses in statistical inference. Statistical significance levels are ‘arbitrary’ and not consonant with crucial observations per se.

This is as opposed to an approach that purely emphasizes internal logic as the criterion for assessment. In this respect a purely deductive argument contains its conclusions within the premises of the argument. The validity or otherwise of the conclusions rests only in the consistent application of appropriate rules of reasoning.

These conjunctions can be expressed either deterministically or stochastically.

This is despite the fact that the analysis of the experiment shows such a flat ontology to be inconsistent with the experiment itself (Bhaskar, 1978).

As Trigg (1989) notes, this subject/object duality has had a number of manifestations. The language/sensory experience, conceptual/real and mind/world dualities are other manifestations. In the current context, subjectivity/objectivity or the epistemic/aleatory nature of reality are examples.

It is important to recognize here that what is at stake is the ‘logic’ of inference employed by the researcher; in other words, the consistency of the components of the argument. All research claims are contingent on such suppositions, but these are often left implicit. It follows that by exploring them explicitly progress can be made.

Critical realism has, since Bhaskar (1979), argued that reasons can be causal (thereby rejecting a common distinction). Therefore, it is consistent to ask people about their reasons for their actions. However, critical realism is ‘critical’ about such responses, because all views expressed are held to be corrigible. However, this ‘hermeneutic moment’ is essential in the absence of reliable experiments.

In terms of a distinction between them, the most that could be argued is that qualitative methods might involve less closure than quantitative, and that, in many circumstances, they are more powerful (Mearman, 2003).

Not every question need refer to causal relations or natural laws.

The traditional meaning of triangulation is to take a number of perspectives on the same phenomenon in question and to combine them in some way in order to capture the complexity of the phenomenon. The complexity of the world is clearly recognized by critical realism. However, triangulation as proposed here encompasses and extends the conventional notion. A number of perspectives can be considered; the key to our approach is that different methods are used for the same phenomenon.

This is consistent with Keynes’ view that probabilities are essentially ordinal and non-quantitative. Keynes emphasized the importance of rational belief rather than knowledge as a basis of argument (Keynes, VIII, p. 10). Rational belief resides in logical justification. There is a relative/absolute dimension to this. Probabilities, which are not necessarily numerically defined, are, on the one hand, relative to given evidence. However, once given a body of evidence or initial proposition, probabilities concerning subsequent propositions are absolute or objective. Crucially for Keynes, relevant evidence is ascertained through a process of negative analogy. To avoid the problem of induction, Keynes argued that one should examine a particular phenomenon in different contexts. If a phenomenon appears to be common across various contexts then this indicates its relevance. In turn, this relevance adds weight to a particular account of that phenomenon. If the different contexts reveal non-common elements, then the weight of an argument will decrease, revealing our ignorance.

It should be clear that ontological differences are essentially ones of presumption. Various research methods of more or less quantitative emphasis in themselves do not necessitate a particular ontological perspective. All inferences will be conditional upon ontological presuppositions. The important thing in research is to be clear about this presumption.