Robert MacIntosh is Head of the School of Management and Languages at Heriot-Watt University. He trained as an engineer and has researched strategy development and strategic change for twenty years in a range of public, private, family and charitable organizations. He has published extensively in top rank journals including Strategic Management Journal. He sits on the Council of the British Academy of Management, is a board member for the charity Turning Point Scotland and for Heriot-Watt University Malaysia as well as being a Fellow of the Institution of Engineering and Technology. His latest books include “Strategic Management: strategists at work” published by Palgrave and “Research Methods” (2nd Ed) published by Goodfellow. His status as a shareholder in Aberdeen Football Club demonstrates his sense of optimism.

Kevin O’Gorman is Professor of Management and Business History and Head of Business Management in the School of Languages and Management in Heriot-Watt University, Edinburgh. He trained in Glasgow, Salamanca and Rome as a philosopher, theologian and historian. His research interests have a dual focus: Origins, history and cultural practices of hospitality, and philosophical, ethical and cultural underpinnings of contemporary management practices. Using a wide range of methodological approaches he has published over 80 journal articles, books, chapters, and conference papers in business and management.

Know what is expected in your discipline

Not all requirements are the same in every academic discipline or field of study.  Just because your friend studying philosophy did not need to worry about an extended methodology does not mean you can avoid it too… You might expect a detailed discussion of method and techniques in the scientific disciplines but not the social sciences, however, they are now very popular in business and management.

Understand and define the terms

The vocabulary used in research mythology, in particular terms surrounding research philosophy, for example, ontology and epistemology are not phrases you are likely to use in everyday conversation.  However, when you understand and define the terms the rest of it becomes much more manageable – it is not that complicated it just needs a little initial investment of time.

Avoid inconsistencies

Don’t present yourself as a meat-eating vegetarian; that makes no sense in the culinary world, and if you were invited for dinner, would confuse your host no end. Similarly in methodological parlance presenting yourself as a positivist who adopts social construction or an Interprevisit who conducts a large scale, closed question survey who plans to use grounded theory to analyse their results would have the same sense of social awkwardness. Surprisingly such inconsistencies do occur and they and go a long way to highlighting the fact that you don’t really understand what you are talking about.

Avoid vagueness

If you don’t understand the terms, probably because you have not taken the time to learn them, do not try to gloss over this and just use the terms vaguely. Your examiners are sure to notice and will mark you down in and undergraduate or postgraduate dissertations. Much worse, in a PhD viva you could find yourself in a good 20 minute round of questioning whilst you want the floor to open up and swallow you.

Specify Your Research Philosophy

This will normally consist of clearly articulating ontology and epistemology. Ontology is how you view the reality within which your research project is undertaken.  At its most basic level, ontology can be thought of as whether we see the world as objective or subjective.  Research involves the development of new knowledge. Epistemology concerns our view of how we might obtain valid knowledge. The Methods Map illustrates four epistemological positions: positivist, critical realist, action research, and interpretivist.

Define how you will collect your data

The Method Map suggests three broad categories of methodology which are quantitative, qualitative and case study. Quantitative methods sit comfortably within an objective ontology and a positivist epistemology. The case study approach is one of the most common ways for students to conduct their research project. Case studies often involve detailed exploration of some phenomena, often using multiple data sources collected over time.  Qualitative methodologies can yield valuable, revelatory, and rich data. This methodology can be used on its own, or in conjunction with other research tools depending on the nature of the research project. For example, interviews, focus groups or observations can be used to explain and interpret the results of quantitative research, or conversely, to provide exploratory data that are later developed by quantitative research.  Regardless of what you adopt: quantitative, qualitative or case study approach you must also clearly articulate your data collection techniques.

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Select appropriate data analysis tool(s)

The data gathered using particular research techniques should be subject to some analysis which we categorize as subscribing to one of two broad approaches: deductive or inductive. There are other approaches to analysis but these two capture the majority of research projects. The Deductive approach to analysis typically involves the use of quantitative data to explore relationships between variables, constructs and outcomes. Inductive analysis attempts to build an understanding of the relationships within a data set by engaging with the data itself and looking for patterns, themes, etc. Don’t forget that if you have gathered more than one type of data you may need more than one type of analytical approach.  Multiple types of analysis can be helpful; however, multiple philosophies of knowledge within the same project tend not to help at all.

Give a detailed account of how you actually analysed your data

Again, don’t be vague, don’t hide behind big words you have only just learned the meaning of, and don’t gloss over this section in the hope that no one will notice – they will! So, instead give a clear, explicit and concise explanation and description of how you actually analysed your data.  Don’t hesitate to illustrate your answer with examples!

Revisit and Rewrite

Typically, we develop a first draft of our methodology before we conduct the research.  Resist the temptation to assume that this will be okay for your final submission.  Once you have collected and analysed your data you should revisit the entire chapter and check the description in the chapter reflected the specifics of what you did, what worked and what you had to adapt.  More than likely things will have changed from the planning to execution stage.  This is perfectly normal, plans evolve and you were there to see them evolve.  The reader, however, wasn’t there and will expect the methodology as described to be an accurate reflection of what has been carried out.

Ensure the reader in not surprised when they get to you data in the next

You are writing a thesis, dissertation or academic paper, you are not writing a short story.  Whilst your findings should be interesting and revealing, there is no need for a late plot twist.    Nor for that matter should there be surprises when you move from chapter to chapter, your presentation of data and analysis chapter should follow clearly and explicitly from the Methodology Chapter.

Mimic your heroes!

There is no need to reinvent the wheel… you are reporting the results of an academic study, something that has been done many times before.  During your literature review, you will have identified your academic superheroes.  Their papers will likely appear in the most prestigious outlets and be amongst the most heavily cited in your field.  Further, some of these papers will give a world-class account of empirical research with a clear articulation of methods, forms of analysis which can be followed, leading to conclusions and insights that genuinely convince the reader that a major contribution is being made.  Shamelessly mimic their presentational style.  Go further, read everything else you can find from these talented individuals. You may even find that their earlier works weren’t quite so spectacular, which should give you some cause for optimism. Also use the Methods Map which will help you select and articulate your ontology, epistemology, methodology, data collection techniques and data analysis tools.

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