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How to... conduct empirical research

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The theoretical framework

Empirical research is not divorced from theoretical considerations; and a consideration of theory should form one of the starting points of your research. This applies particularly in the case of management research which by its very nature is practical and applied to the real world. The link between research and theory is symbiotic: theory should inform research, and the findings of research should inform theory.

There are a number of different theoretical perspectives; if you are unfamiliar with them, we suggest that you look at any good research methods textbook for a full account (see Further information), but this page will contain notes on the following:

Positivism

This is the approach of the natural sciences, emphasizing total objectivity and independence on the part of the researcher, a highly scientific methodology, with data being collected in a value-free manner and using quantitative techniques with some statistical measures of analysis. Assumes that there are 'independent facts' in the social world as in the natural world. The object is to generalize from what has been observed and hence add to the body of theory.

Empiricism

Very similar to positivism in that it has a strong reliance on objectivity and quantitative methods of data collection, but with less of a reliance on theory. There is emphasis on data and facts in their own right; they do not need to be linked to theory.

Interpretivism

This view criticizes positivism as being inappropriate for the social world of business and management which is dominated by people rather than the laws of nature and hence has an inevitable subjective element as people will have different interpretations of situations and events. The business world can only be understood through people's interpretation. This view is more likely to emphasize qualitative methods such as participant observation, focus groups and semi-structured interviewing.

Quantitative methods: Qualitative methods: 
typically use numbers. typically use words.
are deductive. are inductive.
involve the researcher as ideally an objective, impartial observer. require more participation and involvement on the part of the researcher.
may focus on cause and effect. focuses on understanding of phenomena in their social, institutional, political and economic context.
require a hypothesis. do not require a hypothesis.
have the drawback that they may force people into categories, also it cannot go into much depth about subjects and issues. have the drawback that they focus on a few individuals, and may therefore be difficult to generalize.

Realism

While reality exists independently of human experience, people are not like objects in the natural world but are subject to social influences and processes. Like empiricism and positivism, this emphasizes the importance of explanation, but is also concerned with the social world and with its underlying structures.

Inductive and deductive approaches

At what point in your research you bring in a theoretical perspective will depend on whether you choose an:

  • Inductive approach – collect the data, then develop the theory.
  • Deductive approach – assume a theoretical position then test it against the data.
The inductive approach: The deductive approach:
is more usually linked with an interpretive approach. is more usually linked with the positivist approach.
is more likely to use qualitative methods, such as interviewing, observation etc., with a more flexible structure. is more likely to use quantitative methods, such as experiments, questionnaires etc., and a highly structured methodology with controls.
does not simply look at cause and effect, but at people's perceptions of events, and at the context of the research. is the more scientific method, concerned with cause and effect, and the relationship between variables.
builds theory after collection of the data. starts from a theoretical perspective, and develops a hypothesis which is tested against the data.
is more likely to use an in-depth study of a smaller sample. is more likely to use a larger sample.
is less likely to be concerned with generalization (a danger is that no patterns emerge). is concerned with generalization.
tresses the researcher involvement. stresses the independence of the researcher.

It should be emphasized that none of the above approaches are mutually exclusive and can be used in combination.

Sampling techniques

Sampling may be done either:

  • On a probability basis – that is, each member of a given population has an equal chance of being selected, as when your population is the workforce of an organization, and you select members from it:

    • On a random basis – a given number is selected completely at random.
    • On a systematic basis – every nth element of the population is selected.
    • On a stratified random basis – the population is divided into segments, for example, in a University, you could divide the population into academic, administrators, and academic related. A random number of each group is then selected.
    • On a cluster basis – a particular subgroup is chosen at random.

  • On a non-probability basis – the population does not have an equal chance of being selected; instead, selection happens according to some factor such as:

    • Convenience – being present at a particular time e.g. at lunch in the canteen.
    • Purposive – people can be selected deliberately because their views are relevant to the issue concerned.
    • Quota – the assumption is made that there are subgroups in the population, and a quota of respondents is chosen to reflect this diversity.

Useful articles

Richard Laughlin in provides an interesting general overview of the different perspectives on theory and methodology as applied to accounting. (Accounting, Auditing & Accountability Journal, Volume 8 Number 1).

D. Tranfield and K. Starkey in look at the relationship between theory and practice in management research, and develop a number of analytical frameworks, including looking at Becher's conceptual schema for disciplines and Gibbons et al.'s taxonomy of knowledge production systems. (British Journal of Management, vol. 9, no. 4 – abstract only).