A note on research methodology: for MBA students
Regarding the subject of Research Methods in MBA study, what topics should be considered key topics and what topics considered as minor topics on describing a research methodology (as a theoretical blueprint)? Here are the topics I can think of for this discussion purpose: research objectives, research questions, research philosophy, research approach (methods) types (i.e. qualitative, quantitative, mixed methods), research approach (reasoning) types (i.e. inductive, deductive, abductive), researcher positionality, primary research methods, secondary research methods, research methods design criteria, research ethics consideration, research constraint.
Overall classification
For an MBA dissertation, a research methodology should be presented as a logical theoretical blueprint showing how the study will move from the research problem to credible conclusions. The key principle is alignment: research questions should drive the research design, data requirements, collection methods and analysis—not the reverse.
Your proposed topics are all relevant, but they do not have equal importance. Some are core methodological decisions, whereas others are supporting or contextual issues. A useful structure is to classify them into three levels:
1. Key topics: essential decisions that define the methodology.
2. Supporting topics: necessary to demonstrate rigour and feasibility.
3. Minor or conditional topics: included only when relevant to the chosen design.
The topics can be organised using an adapted version of the research-onion logic: philosophy, theoretical reasoning, methodological choice, strategy, time horizon, and specific techniques and procedures.
Key topics
1. Research objectives and research questions
These should normally be the starting point and the most important topic.
The methodology must show how each research question will be answered. For example:
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Students should demonstrate:
- The connection between the research problem, objectives and questions.
- Whether the questions are descriptive, exploratory, explanatory, evaluative or predictive.
- The type of evidence needed to answer each question.
- How each question will be addressed by specific data and analysis.
This topic is essential because a methodology cannot be justified independently of the research questions.
2. Research philosophy and philosophical assumptions
Research philosophy explains what the researcher believes about reality, knowledge and values. It usually includes:
- Ontology: assumptions about the nature of reality.
- Epistemology: assumptions about what can count as knowledge.
- Axiology: the role of values and ethics in research.
For an MBA dissertation, students do not need an excessively abstract philosophical discussion. They should explain the practical implications of their chosen position. Common positions include:
- Positivism: useful for testing relationships through structured, measurable data.
- Interpretivism: useful for understanding meanings, experiences and organisational contexts.
- Pragmatism: useful when the research question requires both quantitative and qualitative evidence.
- Critical realism: useful when observable events are explained through underlying structures, mechanisms or contextual conditions.
The important question is not simply “Which philosophy has been selected?” but:
Why is this philosophical position appropriate for the research questions and the type of knowledge sought?
Research philosophy is therefore a key topic, although the depth required should be proportionate to MBA-level work.
3. Approach to theory development
Your proposed distinction between different types of research approach is important, but the terminology should be clarified. There are two different meanings of “research approach”:
Approach to reasoning
This concerns the relationship between theory and data:
- Deduction: theory → hypotheses or propositions → data collection → testing.
- Induction: data → patterns → concepts or theory development.
- Abduction: movement between existing theory and surprising empirical findings to develop the best explanation.
This is a key topic because it explains the logic of the investigation. For example, a study based on agency theory may use deduction to test whether performance-based incentives are associated with management control outcomes.
Methodological approach
This concerns the broad form of evidence used:
- Quantitative.
- Qualitative.
- Mixed methods.
These two classifications should not be conflated. For example:
- A study can be quantitative and deductive.
- A study can be qualitative and inductive.
- A study can be mixed methods and abductive.
A strong methodology explicitly states both dimensions.
4. Methodological choice
This is the decision to use:
- Mono-method quantitative research.
- Mono-method qualitative research.
- Multi-method research within one broad methodological tradition.
- Mixed-methods research combining qualitative and quantitative components.
A mixed-methods study should not be justified merely by saying that “using two methods is better.” The researcher should explain the purpose of integration, such as:
- Triangulation: comparing findings from different forms of evidence.
- Complementarity: using one method to provide depth or explanation for another.
- Development: using findings from one phase to construct the next phase.
- Expansion: examining different aspects of a complex research problem.
Mixed methods requires a plan for the sequence, priority and integration of the qualitative and quantitative strands.
This is a key topic when relevant, but not every MBA dissertation needs mixed methods.
5. Research strategy or research design
This is one of the most important areas missing from your proposed list. It explains the overall design through which the study will be conducted.
Possible strategies include:
- Survey research.
- Case study.
- Comparative case study.
- Interviews.
- Ethnography.
- Action research.
- Experimental or quasi-experimental research.
- Archival or documentary research.
- Systematic or structured literature review.
The choice should be linked to the research questions. For example:
- “How many?” or “What relationship?” may support a survey design.
- “How?” and “Why?” may support a case study or interview design.
- “What changed after an intervention?” may support action research or quasi-experimental research.
- “What patterns exist across firms?” may support archival or secondary-data research.
Research strategy is a core topic, not a minor one. It provides the bridge between philosophical assumptions and practical methods.
6. Sampling and case selection
Sampling is another essential topic that is absent from your initial list. A methodology should explain:
- The target population.
- The sampling frame, if available.
- The unit of analysis.
- Inclusion and exclusion criteria.
- Sampling technique.
- Proposed sample size or number of cases.
- The rationale for the selection.
Examples include:
- Probability sampling for a survey of accounting professionals.
- Purposive sampling for interviews with managers who have implemented a new accounting system.
- Convenience or snowball sampling where access is restricted, accompanied by an explicit limitation.
- Single-case or multiple-case selection for organisational research.
Sampling decisions directly affect the credibility, transferability and generalisability of findings, so they should be treated as a key topic.
7. Data collection methods
Your distinction between primary and secondary research is useful, but it should be supplemented by the specific collection procedures.
Primary data
Possible methods include:
- Questionnaires.
- Semi-structured interviews.
- Focus groups.
- Observation.
- Diaries.
- Experiments.
- Workshops or action-research activities.
Secondary data
Possible sources include:
- Company annual reports.
- Government statistics.
- Public databases.
- Internal organisational records.
- Policy documents.
- Industry reports.
- Existing datasets.
- Academic and professional publications.
Students should explain not merely what data they intend to use, but:
- Why the data are appropriate.
- How participants or documents will be accessed.
- When and where data will be collected.
- How the instrument or protocol will be developed.
- Whether the data are sufficiently current, complete and credible.
Data collection is a key topic.
8. Data analysis methods
This is another major topic that should be added to your framework. A methodology is incomplete if it explains how data will be collected but not how they will be analysed.
Quantitative analysis
Depending on the research question, this may include:
- Descriptive statistics.
- Reliability analysis.
- Correlation analysis.
- Regression analysis.
- Analysis of variance.
- Factor analysis.
- Structural equation modelling.
The choice should depend on the variables, measurement levels, sample size and assumptions of the analysis.
Qualitative analysis
This may include:
- Thematic analysis.
- Content analysis.
- Template analysis.
- Grounded-theory coding.
- Narrative analysis.
- Framework analysis.
- Cross-case analysis.
Students should explain the coding process, theme development and use of quotations or documentary evidence.
Mixed-methods analysis
The researcher should explain:
- How each dataset will be analysed separately.
- When the datasets will be integrated.
- How convergence, divergence or complementarity will be assessed.
- How integrated conclusions will be developed.
Data analysis is a key topic because it determines how raw evidence becomes research findings.
Supporting topics
9. Research quality and design criteria
Your phrase “research methods design criteria” is important but should be made more precise. It should cover the standards by which the study will be judged.
For quantitative research, relevant criteria include:
- Reliability.
- Measurement validity.
- Internal validity.
- External validity.
- Objectivity.
- Statistical conclusion validity.
For qualitative research, relevant criteria include:
- Credibility.
- Transferability.
- Dependability.
- Confirmability.
- Reflexivity.
- Transparency.
For mixed methods, relevant criteria include:
- Quality of the qualitative component.
- Quality of the quantitative component.
- Quality of integration.
- The coherence of the overall interpretation.
A methodology should also consider whether the instruments are:
- Clearly operationalised.
- Consistent with the constructs.
- Pilot-tested where appropriate.
- Suitable for the target participants.
This is a supporting but essential quality topic.
10. Operationalisation and measurement
This topic is particularly important in management accounting and business research. Students should show how abstract concepts will be translated into observable indicators.
For example, “management accounting sophistication” might be operationalised through indicators such as:
- Use of strategic costing techniques.
- Frequency of non-financial performance measurement.
- Use of budgeting and forecasting systems.
- Extent of decision-support information.
- Perceived integration of accounting with strategic planning.
For qualitative studies, operationalisation may involve defining the central concepts and constructing an interview framework rather than using numerical measures.
Operationalisation is essential in quantitative work and strongly useful in qualitative work, so it should be treated as a major supporting topic.
11. Research ethics
Research ethics should be included in every methodology, but its length should reflect the risks of the project. Relevant issues include:
- Informed consent.
- Voluntary participation.
- Right to withdraw.
- Confidentiality and anonymity.
- Data security and retention.
- Avoidance of harm.
- Deception.
- Conflicts of interest.
- Researcher integrity.
- Use of organisationally sensitive information.
- Data protection and privacy requirements.
In mixed-methods research, ethical decisions arise separately in relation to participant selection, data collection, analysis, relationships with stakeholders and reporting.
Ethics is therefore a key topic, although a low-risk questionnaire may require a shorter discussion than research involving employees, vulnerable groups or commercially sensitive data.
12. Researcher positionality and reflexivity
Positionality is increasingly important, especially in qualitative, case-study, participatory and action research. It concerns how the researcher’s identity, experience, organisational position, assumptions and values may influence the research process. Reflexivity involves critically examining those influences throughout the project.
For example, a lecturer researching students’ attitudes may possess institutional authority that affects participants’ willingness to speak openly. An accounting professional studying management controls may have insider knowledge but also professional assumptions that shape interpretation.
For a conventional anonymous survey using publicly available data, positionality may receive only a brief statement. For interviews, ethnography or action research, it should be discussed more fully.
Thus, positionality is a conditional key topic:
- Major for qualitative, participatory, insider and action research.
- Important but shorter for most other designs.
- Less prominent, though not necessarily irrelevant, in highly structured secondary-data research.
13. Research constraints and delimitations
Your proposed topic is relevant, but it is useful to distinguish:
- Delimitations: boundaries deliberately set by the researcher.
- Limitations: weaknesses or constraints that may affect the study.
- Risks: possible problems that may arise during the research.
- Mitigation: actions to reduce those problems.
Examples include:
- Limited access to organisations.
- Small or non-probability samples.
- Low questionnaire response rates.
- Self-report bias.
- Recall bias.
- Common-method bias.
- Restricted time and budget.
- Confidentiality restrictions.
- Limited generalisability.
- Incomplete secondary data.
Constraints should not be presented as an apologetic list. The researcher should explain how the design responds to them—for example, through triangulation, pilot testing, transparent sampling, sensitivity analysis or cautious claims.
This is a supporting topic, normally placed near the end of the methodology.
14. Time horizon and research procedures
Time horizon is often overlooked in MBA dissertations. It refers mainly to whether the study is:
- Cross-sectional: data collected at one point or within a short period.
- Longitudinal: changes observed over time.
The methodology should also provide a basic sequence of procedures:
1. Obtain ethical approval and organisational access.
2. Develop or select the research instrument.
3. Pilot-test the questionnaire or interview guide.
4. Recruit participants or obtain documents.
5. Collect data.
6. Clean, code and analyse data.
7. Integrate and interpret findings.
8. Store and dispose of data appropriately.
Time horizon is a supporting topic, but it becomes a key topic for studies examining change, implementation or performance over time.
Minor or conditional topics
The following are not unimportant, but they should not normally dominate a short MBA methodology chapter.
15. Detailed philosophical debates
Students sometimes spend too many pages comparing positivism, interpretivism, realism and pragmatism without showing how the selected philosophy affects the actual study. A concise, justified explanation is usually more valuable than an extensive history of epistemology.
16. The research onion as a theory
The research onion is useful as an organising framework, but it is not itself the methodology. Students should use it to structure decisions, not describe every layer mechanically. It should not replace justification of the actual research design.
17. Extensive classification of methods
A methodology does not need a long catalogue of every possible interview, survey or case-study type. Students should discuss only the methods relevant to their study and explain why alternatives were rejected.
18. Researcher biography
A positionality statement should discuss relevant influences on the research, not provide a detailed personal biography. The issue is methodological relevance rather than personal description.
19. Project management detail
A detailed Gantt chart, budget or week-by-week work plan may be useful in a proposal, but it is usually a minor part of the methodology chapter unless specifically required by the programme.
20. General background on primary and secondary research
Definitions of primary and secondary data should be brief. The important issue is the suitability, quality, accessibility and analysis of the actual data sources.
Recommended hierarchy
A practical MBA methodology blueprint could use the following hierarchy:
Level | Topics |
Key | Research objectives and questions |
Key | Research philosophy and assumptions |
Key | Approach to theory: deduction, induction or abduction |
Key | Methodological choice: quantitative, qualitative or mixed methods |
Key | Research strategy or design |
Key | Sampling and case selection |
Key | Data collection methods |
Key | Data analysis methods |
Key | Research ethics |
Supporting | Operationalisation and measurement |
Supporting | Quality criteria: validity, reliability, credibility and dependability |
Supporting | Time horizon |
Supporting | Research constraints and limitations |
Supporting or conditional | Positionality and reflexivity |
Minor or conditional | Detailed philosophical debates, project management and broad method catalogues |
Suggested methodology structure
For an MBA dissertation, the following chapter structure is usually coherent:
1. Introduction to the methodology
Briefly restate the research problem, objectives and questions, and explain that the methodology is designed to answer them.
2. Research philosophy
Explain the chosen philosophy and its implications for reality, knowledge, values and evidence.
3. Research approach
State both:
- The methodological approach: qualitative, quantitative or mixed methods.
- The reasoning approach: deductive, inductive or abductive.
4. Research design and strategy
Explain the survey, case study, interview, archival, action-research or other design, including the time horizon.
5. Population, sampling and access
Define the unit of analysis, target population, sample, sampling method and access arrangements.
6. Data collection
Describe primary or secondary data sources, instruments, procedures and pilot testing.
7. Data analysis
Explain the quantitative, qualitative or mixed-methods analysis procedures and the link between analysis and each research question.
8. Quality and rigour
Discuss validity, reliability, credibility, reflexivity, triangulation and the limitations of the design as appropriate.
9. Ethics and data management
Explain consent, confidentiality, data protection, participant risks and storage arrangements.
10. Constraints and conclusion
Discuss limitations, mitigation measures and the overall coherence of the methodological blueprint.
The most important teaching message for MBA students is that methodology is not a collection of independent headings. It is a chain of justified decisions:
Research problem→ Objectives and questions→ Philosophy→ Reasoning approach→ Research design→ Sampling and data→ Analysis→ Conclusions
If a student can explain and defend that chain, the methodology is likely to be coherent. If the student merely lists philosophy, methods and ethics without showing their connections, the chapter is descriptive rather than methodological.
Provide 3 academic references on the topic discussed here in Harvard reference format.
Harvard references
These three academic textbooks are particularly suitable for the methodology topics discussed:
1. Creswell, J.W. and Creswell, J.D. (2023) Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. 6th edn. Thousand Oaks, CA: SAGE Publications.
2. Saunders, M.N.K., Lewis, P. and Thornhill, A. (2023) Research Methods for Business Students. 9th edn. Harlow: Pearson.
3. Easterby-Smith, M., Jaspersen, L.J., Thorpe, R. and Valizade, D. (2021) Management and Business Research. 7th edn. London: SAGE Publications.
Possible in-text citations
· Research methodology should be aligned with the research questions and the overall research design (Saunders, Lewis and Thornhill, 2023).
· Qualitative, quantitative and mixed-methods approaches involve different assumptions, procedures and standards of quality (Creswell and Creswell, 2023).
· Management research requires systematic consideration of research philosophy, design, data collection, analysis and research quality (Easterby-Smith et al., 2021).
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