Sample Undergraduate Project Management Dissertation Chapter

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Research Methodology


Behind every successful research lies a carefully and meticulously crafted methodology. The selection of an appropriate and rigorous methodology is perhaps the most integral part of any management research (Sackett and Larson, 1990). Methodology varies from research to research, depending on the nature of the study to be conducted.

The literature is rife with opposing views regarding the selection of a suitable methodology for any research. According to Easterby-Smith et al. (2012), a philosophical issue must be present when pursuing particular research.

However, Denzin and Lincoln (2005) argue that any research strategy is heavily driven by the researcher’s personal beliefs, experiences, and knowledge.

Previously, researches were conducted using standard approaches such as primary and secondary research methods. However, today the spectrum of research methodology has broadened considerably.

Approaches are now based primarily on the three theories of Ontology, Epistemology, and Axiology. This paper explores the primary and secondary approaches and the epistemological perspectives used in management research.

Primary and Secondary Approach

A primary research method involves direct and unmediated observation and investigation of the phenomenon to be studied. The researcher personally collects the data instead of the secondary research approach, where the data used is extracted from the previously conducted research.

Each of the aforementioned methodologies has its advantages in addition to a few limitations. A primary research approach allows generalising trends for a larger population which is not possible in a secondary research approach.

However, primary research is rather time-consuming and often leads to an over-reliance on statistical analysis. On the other hand, secondary research is cheaper and less time-consuming. Still, it may be challenging to filter out the biases and inaccuracies from the previous studies used.

Selection between the two is a critical task. Hence, due diligence should be attached to it. It is better to adopt a direct approach if the research deals with a specific problem as the secondary data often presents conflicting perspectives. However, when data collection is complex (e.g., information regarding the public sector), it is more sensible and convenient to employ the secondary research approach to get a generalised impression of the prevalent trends.

Social Constructivist Approach

Social constructivism is based upon the belief that knowledge is socially constructed rather than created or discovered. Thus, social constructivism is not concerned with the nature of knowledge and can be classified as an epistemological perspective (Andrews, 2012).

It is often expressed how observations are an exact image of the world (Murphy et al., 1998). This view emphasises the importance of everyday communication between people and their language to attach meaning to this interaction and construct their reality. The constructivist approach helps researchers understand the underlying values, beliefs, and perceptions that influence and shape people’s behaviour.

Social constructivism falls under the paradigm of qualitative research. This approach employs the information conveyed through verbal and emotional behaviour (Lincoln and Guba, 1985).

This paradigm helps explore and understand the complexity of situations/problems that are not well-defined. It also helps create a more accurate picture regarding the study. Thus, adding depth to the surveys/questionnaires or the interviews that are conducted.

The researcher in this study is not merely an observer rather an active part of the data collection. However, truly understanding the population’s perceptions and translating them into meaningful research is difficult and complex.

A researcher needs to ensure that their personal beliefs do not influence the interpretations of conducted interviews in any form to mitigate the risk of biases.

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Positivist Approach

The positivism approach is steeped in the belief that knowledge is created through research. It emphasizes that the researcher is an objective observer and collects facts about the social situation. They then arrange these facts in a “chain of causality” to explain social interactions (Morgan and Smircich, 1980).

Thus, the positivism approach is closely intertwined with the quantitative research paradigm. In a positivist approach, the emphasis is on measuring the situation rather than understanding the underlying beliefs driving the particular behaviour.

Rigorous mathematical/scientific experiments are performed to test the validity of the hypothesis coined at the research’s inception stage. In this approach, the research design is “highly structured” and often develops before the study begins.

A positivist approach is very logical and objectively documents the results as opposed to the social constructivist approach, where business tends to bleed into the analysis and the documentation of the results. Hence, the researcher must ensure that while the study is objective, it is not rigid.

Methodology Used

Previously, the positivist approach was the dominant research paradigm in the Information Systems field (Chen and Hirschheim, 2004); however, social constructivism quickly emerged as the new norm. While positivist researches test the designed hypotheses using objective evidence, the constructivist approach tries to understand the underlying meaning behind people’s interactions, behaviours, and experiences.

A combination of the two approaches mentioned above will be used in this study to quantify the data objectively while at the same time making sense of people’s experiences in a social context.

As enterprise cloud implementation is still in progress, it cannot be classified as a mature field. Hence, a qualitative approach is the most suitable for the course of this research. The aim is to conduct “open-ended rich and detailed” interviews/surveys to generate data that will help develop sound hypotheses (Edmondson and McManus, 2007) about enterprise cloud implementation.

In this scenario, in-depth interviews with the appropriate personnel such as IT managers, senior executives, and enterprise architects who are directly involved in the planning and implementation process of the enterprise cloud will help collect accurate and objective data. It is hoped that this research will prove beneficial in understanding the process of enterprise cloud implementation and help establish relevant hypotheses in this field.


Sackett, P. R., & Larson, J. R., Jr. 1990. Research strategies and tactics in industrial and organizational psychology. In M. D. Dunnette & L. M. Hough (Eds.), Handbook of industrial and organizational psychology: 419-489. Palo Alto, GA: Consulting Psychologists Press.

Easterby-Smith, M., Thorpe, R. & Jackson, P., (2012) Management Research, 4th ed. London: SAGE Publications.

Denzin, N., & Lincoln, Y., (2005) Introduction: the discipline and practice of qualitative research: Handbook of Qualitative Research, Thousand Oaks, CA: SAGE Publications, pp.1-17.

Lincoln YS, Guba EG. Naturalistic Inquiry. Beverly Hills, Calif: Sage Publications; 1985.

Morgan, G., and L. Smircich, 1980. The case for Qualitative research. Acad. Manag. Rev., 5(4): 491-500.
[online] Available at: [Accessed 9 Apr. 2017].

Murphy, E., Dingwall, R., Greatbatch, & Parker, P., (1998) ‘Qualitative research methods in health technology assessment: a literature review,’ Health Technology Assessment, 2(16).

Edmondson, A., and McManus, S. 2007. “Methodological fit in management field research,” Academy of management review (32:4), pp 1246-1264. Chen, W., and Hirschheim, R. 2004. “A paradigmatic and methodological examination of information systems research from 1991 to 2001,” Information Systems Journal (14:3), pp 197-235.

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.