Choices

In focusing on different modes of enquiry, the researcher makes an important decision on different frameworks for the collection and analysis of data (Bryman and Bell 2007). Overall there are three choices (qualitative, quantitative or multi-method) into the research design where, as can be seen from Table 3:2, each employs a different approach in many ways.

3.3.5.1 Qualitative Methods

The qualitative research approach is usually associated with the phenomenological (interpretative) school of thought (Kumar 2005). Principle aim of pure qualitative research is to establish the meaning of the phenomenon from individual’s opinions, views, qualities and experiences. A number of authors outline the main features of qualitative methods, in particular Fellows and Liu (2008) noted that qualitative research is concerned with collecting and analysing information using multiple methods, mainly in non-numeric forms. Moreover, Blaxter et al. (2006) explained that the aim of qualitative approach is to achieve ‘depth’ rather than ‘breadth’, hence it tends to be rich in context and scope.

The inherent weakness of qualitative research methods is discussed by Bryman and Bell (2007) who emphasized four main disadvantages of adapting a qualitative approach. Firstly, findings from a qualitative research are often derived from subjective values of the researcher and discourses of views that are seen significant and important to the researcher (or participants). Secondly, it is difficult to replicate the study due to subjectivity and unstructured nature of the qualitative data. Thirdly, because data is generally collected from a small number of participants, it is difficult to generalise the research findings to a larger setting. Finally, due to lack of transparency and deficiencies in data collection and analysis phase, it is very hard to establish how the researcher has arrived to the conclusion. Moreover, several authors (Bryman and Bell 2007; Easterby-Smith et al. 1991; Fellows and Liu 2008; Naoum 2007) stress the difficulty of collection, filtering and organisation of data, which can be a very lengthy process (time and resource consuming).

3.3.5.2 Quantitative Methods

Quantitative approach reflects the positivist research paradigm, which is ‘value-free’, objective in nature (Bryman and Bell 2007). Naoum (2007 p. 38) defined the quantitative methods as “testing a hypothesis or a theory composed of variables, measured with numbers, and analysed with statistical procedures”. Quantitative approaches involve gathering of relatively large-scale numerical data, which is analysed (using statistical procedures) and interpreted in order to come to conclusions to test or verify a theory (Bryman and Bell 2007).

One of the advantages of quantitative approach is that it yields precise, reliable, quantified results and findings (Bryman and Bell 2007). In addition to this, quantitative approach leads to generalisation and replication of the study (Fellows and Liu 2008). Concerns on validity and reliability are often termed with qualitative research approaches, as it is difficult to apply conventional standards of validity and reliability to qualitative research data (Bryman and Bell 2007). However, in quantitative research different techniques can be adopted to check the validity, reliability and accuracy of the findings (Fellows and Liu 2008).

Despite the above-mentioned strengths, the quantitative research approach is often criticised for failing to account for researcher’s opinions, views, intentions, attitudes and

experiences. In other words, quantitative research fails to distinguish social world from natural world and tends to ignore how people interpret the world around them. Furthermore, Bryman and Bell (2007) argued that this can lead to bias as scientific approach cannot be totally objective, since subjectivity is involved in data input, collection and analysis. Bryman and Bell (2007) further explained that measurement may be flawed, for example it may not be precise and accurate due to parallax (researchers seeing things differently) as well as instrument error and so on.

3.3.5.3 Triangulation (multi-method)

Flick (2007) described the triangulation as the reflection of the research issue from at least two points. Easterby-Smith et al. (1991) distinguished four variants of triangulation. The most used one is data triangulation, which is the use of multiple methods to ‘compensate’ for the weakness of a research method by counterbalancing with strengths of another. Another method is triangulation of theories which involve the use of models from one discipline to look at the issue from a different perspective and explain situations from a multiple perspective. Thirdly, triangulation by researcher is another method which involves a different person to collect data on the same research problem. Finally, the methodological triangulation method involves using both quantitative and qualitative methods for data collection to where, for example ‘objectivity’

Table 3:2 A comparison of the qualitative and quantitative modes of enquiry.

Qualitative Quantitative

Paradigm  Interpretivist  Positivist

Aim  To establish the meaning of the phenomenon

from individual’s opinions, views, qualities and experiences

 To test or verify a hypothesis or a theory by gathering of relatively large-scale numerical data which is analysed (using statistical procedures) and interpreted in order to come to reach to a conclusion

Features  Unstructured/semi-structured or open

methodology  Descriptive  Gives ‘depth’

 Structured and predetermined methodology  Factual and quantifiable

 Gives ‘breadth’

Strength  Rich in context and scope  Yields precise, reliable, quantified results and findings

 Leads to generalisation and replication of the study  Different techniques can be adopted to check the

validity, reliability and accuracy of the findings

Weaknesses  Findings are often derived from subjective

values of the researcher and discourses of views that are seen significant and important to the researcher

 Difficult to replicate due to subjectivity and unstructured nature of the research

 Difficult to generalise the research findings to a larger setting

 Can be hard to establish how the researcher has arrived at the conclusion

 Can take a lot of time to collect, filter and organise data

 Fails to distinguish the social world from natural world and ignores how people interpret the world around them

 Measurement may be flawed, for example, it may not be precise and accurate due to parallax (researchers seeing things differently) or wrong instrument may be chosen to collect data.

 Problems with the meaning of the questions can render the validity/reliability of data, for example, a

respondent may not share the same knowledge and imply something completely different

Main Data Collection Techniques

 Open question surveys  Semi-structured interviews  Participant/process observations,  Focus groups

 Data that can be quantified, numbers, statistics etc.  Factual questions

 ‘Closed’ questions  Structured Interviews

of the quantitative approach can be balanced with ‘subjectivity’ of qualitative approach to produce a neutral viewpoint. Or alternatively “quantitative methods can be used to study both ‘hard facts’ and human perceptions; likewise qualitative methods can be used and analysed in either objectivist or constructionist way” (Easterby-Smith et al. 1991 p. 134). Fellows and Liu (2008); Bryman and Bell (2007) and; Flick (2007) outlined the following benefits of triangulation.

• Triangulation is generally implemented to limit the bias, increase the consistency and validate the findings by confirming with more confident and accurate data. This means results could either converge, complement each other or diverge.

• While quantitative research gathers hard facts and figures (such as through closed questions in a questionnaire), qualitative research instruments such as semi- structured/unstructured interview can be utilised to collect ‘human’ issues related to the research.

• Possible instruments for triangulation include diaries, archives of a project; and databanks which can save on research time and cost.