Sample Masters Project Management Dissertation Chapter 3

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Dissertation Chapter Research Methodology

How does the adoption of a particular methodology affect the researcher’s choice of data collection methods and analysis?

As per the literature, different methodologies can be used to perform research (Creswell & Clark, 2011). However, other methods allow researchers to select additional data collection methods and data analysis methods. This methodology must be chosen, enabling the researcher to select an appropriate or desired data collection and analysis method.

Three research methodologies can be used based on three different epistemological stances: positivism, interpretivism, and realism (Bryman & Bell, 2011). Each of these methodologies allows researchers to use different data collection and analysis methods.

The epistemological stance of positivism is based on objectivity, a logical approach, and rationality to seek generalized conclusions by developing a hypothesis and statistically testing them (Cohen, Manion, & Morrison).

Using statistical techniques in positivism enables researchers to separate their own beliefs from affecting the research’s objectivity. Statistical and quantitative research approaches such as surveys (closed-ended questionnaires) are used in positivism. These methods are based on objective results and prevent researchers from using their interpretations to analyze the data (Bryman & Bell, 2011).

Positivism methodology enables researchers to use statistical techniques to separate their beliefs from affecting the research’s objectivity. The quantitative research method, such as a survey (closed-ended questionnaires), is used in positivism to collect data (Cohen, Manion, & Morrison, 2013).

The quantitative data collection methods are based on the number of repeated observations and normally involve data sampling. The data analysis method depends upon the type of data that is collected in the research.

Therefore, when a quantitative data collection method like a closed-ended questionnaire is used, the quantitative and statistical data analysis method is used, such as; descriptive statistics, frequency distribution analysis, regression analysis, correlation analysis. (Bryman & Bell, 2011)

On the other hand, the interpretivism methodology is based on perceived knowledge. It seeks to find conclusions by specific context to understand a particular situation or context (Cohen, Manion, & Morrison, 2013). In interpretivism, the researchers tend to interpret the world according to their understanding and interpretations.

The qualitative research method, such as open-ended interviews, is used in interpretivism to collect qualitative data and interpretative methods to analyze the qualitative data (Bryman & Bell, 2011).

Qualitative research methods help obtain in-depth perceptions, opinions, views, beliefs, motivations, and attitudes (Cohen, Manion, & Morrison, 2013). Therefore, qualitative research methods focus on qualitative aspects rather than the number of observations.

However, the realism methodology is based on a mixed research method where positivism and interpretivism are collectively used (Saunders, Lewis & Thornhill, 2012). Mixed research enables the researcher to use quantitative and qualitative research together (Creswell & Clark, 2011).

Therefore, the quantitative research method (closed-ended questionnaire) and qualitative research method (open-ended interviews) are used together in realism. This methodology allows the researchers to use quantitative and qualitative data collection and analysis methods together in research.

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Which methods might you choose, bearing in mind your chosen methodology and epistemological stance?

The chosen methodology and epistemological stance which was selected for conducting this research is realism. As per Saunders, Lewis, and Thornhill (2012), research in the management field often employs positivists and interpretivist collectively, indicating a realism stance.

Given this, as this research is related to management, it was appropriate to select this method to perform this study. As realism enabled the use of positivism and interpretivism collectively, a mixed research method is used in this research.

By using mixed research methods, it was possible to use quantitative and qualitative research methods. So two different types of data collection methods (closed-ended questionnaires and open-ended interviews) and data analysis methods were used to perform the research.

The closed-ended questionnaire was used to collect quantitative data from a relatively large number of respondents sample. The quantitative data will be analyzed using statistical analysis, namely, frequency distribution analysis and regression analysis.

Using the frequency distribution analysis, it would be possible to identify the respondents’ least favoured and most favoured answers. However, regression analysis could be employed to statically test the hypothesis and determine the impact of one variable on another variable.

However, open-ended interviews were used to collect qualitative data from a limited number of respondents to find their in-depth and exclusive opinion and views regarding the research topic.

The qualitative data will be analysed by interpreting and inferring meanings from the interviewees’ answers. This highlights how realism’s selected methodology and epistemological stance allow researchers to choose the mixed research method (quantitative and qualitative data collection and analysis methods).


Bryman, A., & Bell, E. (2011). Business Research Methods. London, Oxford: Oxford University Press.

Creswell, J. W., & Clark, V. L. (2011). Designing and Conducting Mixed Methods Research. London, SAGE.

Cohen, L., Manion, L., & Morrison, K. (2013). Research Methods in Education. Routledge.

Saunders, M., Lewis, P., & Thornhill, A. (2012). Research Methods for Business Students. London: Pearson.

Frequently Asked Questions

To write the methodology chapter of a dissertation:

  1. Describe research design & approach.
  2. Explain data collection methods.
  3. Justify chosen methods.
  4. Address limitations.
  5. Analyse data.
  6. Ensure replicability.