Theories, models or frameworks

There are some researchers who like to play with concepts and ideas and formulate new ones.  Other researchers like to do things in the field.  Myself, I sit in the middle.  I like to know some concepts before going into the field.  I like to see what happens when I use them to ask questions or to interpret the data that I collect.

Whatever type of researcher you consider yourself, it is important to have some sort of theory, framework or model in mind.  It helps you to make sense of the data; it also helps you to understand what could be going on in the field where you are working.  And most importantly it can help you explain to other people what you see.  

For me a theory involves some statements about the world and how phenomena occur. A framework shows how these statements work in practice.  And a model encapsulates measures and in some cases hypotheses about these aspects to enable you to collect data about them.  

As is usually the case, you need to read in order to understand these elements.  It is also good to read how other people have used them in practice. Many students skip the first thing (read the raw theory, framework or model) because they like to see their practical application.  They miss on the building blocks of what they are about to use.  So you need to go back to the original sources.  

Life is hard...  

But of course no theory, model or framework is perfect.  They try to be generic enough to be applicable to a range of situations.  So it is part of your job as a researcher to understand and test them, and find out how and if their work as initially stated by whoever defined them.  This is your chance to contribute to knowledge in your own particular areas of interest.  

As you can see from the above figure,  theories, frameworks and models are powerful elements in research.  They give you a preliminary view of what you are going to study.  They give you some sort of guidance for your fieldwork. Your job as a researcher is to use, confirm, modify or challenge what these elements propose.  For your own particular research, you will need to adapt theories, frameworks or models.  When you use some sort of guidance you are more into the deductive style of research.   

You can also decide to be totally 'open' and say that your mind is like a blank canvas, so you are not biased by any of these elements when you are going to observe something in your fieldwork.  That is fine, only that this is also a particular view that you adopt.  Those using grounded theory or first principles would like this. They decide to build theories, models or frameworks from what they observe in the field or what they conceptualise.  This is more an inductive process rather than a deductive one.   

At the end of your research it is expected that you advance knowledge on your particular areas of interest but also on these elements.  This is part of your contribution to knowledge.  When you analyse your findings do not forget to reflect on how theories, frameworks or models have helped you interpret what you observe.  If you are going to produce a new element of this, think carefully of who is to benefit and what are the implications for action of the new knowledge.  These implications will affect the work of managers, users and other researchers. 

Remember, do not claim too much when analising your findings. But whatever you claim should be relevant and well constructed so that other people can use it in their own research or their working life.  

So what? Analysing your research findings

After the joys and bumps of your data collection then comes the final hurdle for many of you.  How to write the whole thing up, how to say what you want to say.

Another mountain to climb, or just a final sprint ? 

It may well be neither of these I think.  

Analysing your findings is about showing people what happened in a sort of story.  Try to be as comprehensive as possible, but make sure the story is readable, and that your findings are clear. 

This will definitely require different iterations.  So be prepared to have different versions of your story and also think of different audiences, for instance those who are technical and those who are non-technical.

When iterating your story, It is important to go back to your research questions and see how the findings are answering them.  It is good to think how the findings answer the questions, and if they don't do so, then you can explain why.

Try to be open in your interpretation of the findings.  Tell the reader what you found, but tell them as if you were just a reporter.  It helps not to be too personal, at least in the initial sections.  It also helps the reader to know where you stand, in other words how you agree/disagree with the findings.  Remember that you have a set of values as a researcher.   Your views about how the world is/should be might or might not fit with the findings.  

Some people divide their findings narrative into several parts.  First, a very descriptive part, where they fill in some general gaps of knowledge.  They present some descriptive statistics.  They also talk about the research context.  They prepare the reader with some basic details.  

The second part is now the juicy bit.  They produce some strong statements, and then they show the evidence to support them. You can still be descriptive but then you start introducing your own analysis, questions and answers, your doubts, insights.  

The third part is my favourite, and some times I ask my students after they tell me all the wonders they have discovered.  I ask them: so what? Yes, the findings sound interesting, but...

The so what question aims to elicit the contributions that your findings and your research make. Do the findings confirm or contradict what has been said before in the literature? What are the implications for managers, for researchers and/or the public in general? Is it that the day after tomorrow people who read your findings will think differently? If so, how differently? How could the theories or frameworks in the literature change as a result of your research ? What could be the limitations of your research? What new questions can you leave for future research? 

Because we are human beings we tend to overestimate what we know or what we have learned.  We need to put our findings in perspective.  For a start, we should not claim too much. There are many people out there doing research who do a much better job than us.  For sure tomorrow there will be new and better insights being published in the areas of knowledge that interest us.  Our findings are just a drop in the ocean of social sciences research. 

Better to be humble than arrogant I think.

Not claiming too much also means advancing in small steps.  That will give us the chance to have something to do after we finish.  Remember that research is a continuous activity.  So we had better save some of ideas for later, whilst they get more mature and ready to be used.

So once you have your findings, keep revising them a few times (remember iteration?), then put them in writing; whilst you do that please think of who can benefit from reading your findings.  After you summarise, analyse and discuss the findings, think of one or two key contributions from your research.  

Finally, it makes no harm to anyone to acknowledge a need to continue researching in the near future.  

Collecting data

This is at glance one of the most attractive activities of research for newcomers and for most of the Phd students I have come across, including myself.  

When I was given the go ahead to travel to my home country and collect data for my Phd I felt relieved.  Finally I was going to be able to test my ideas and models in practice.  I was also going home for a few months to spend time with my family.  

Nothing could be better.

As it turned out, things had changed in my country.  Or at least I thought so.  In retrospect, what had happened was that I had changed as an individual. My perspective of the world was different and I could not fit well in what used to be my natural environment.  

There were also unexpected things.  I had to spend time attending some family affairs.  In addition, my initial data collection plan had to be modified.  Access to certain people was not as easy as thought.  I had to fit within their agenda rather than the other way round.  

I was lucky because I had a good friend who introduced me to the research setting (a university), and I could also take part in some meetings with technology experts to gain an idea of what was going on in my home country.  I was also invited to teach in this university.  It was a nice experience, but it took time.  Anyway I could do it because I was an action researcher and my methodology design allowed for this to happen.  

Whenever I shared some of my findings with my Phd supervisor he left me with some very interesting but difficult questions to think about.  Was this a reflection of what was really going on? Why was not I more inquisitive and curious? How was I making sure I was using my theory/framework appropriately? What role was I to play in the research setting (just observing or taking the initiative to do something about a situation)?

This questioning as well as my own reflections led me to adjust my initial plan and facilitate additional activities in my research setting.  I could carry some of these activities, and I was not allowed to carry out others, and this also gave me more food for thought.  

As it turned out, the data collection was not only about collecting, but also reflecting and acting on a situation.  

So if you have an opportunity to collect data, just make sure you make the most of it.  These are my tips to do so:

-Do not waste time asking questions for which answers are already known from other sources (reports, literature review).  

-Make sure you validate the data you collect.  

-Follow your methodology whenever possible.  

-Do not jump into conclusions too fast about what the data is telling you.  

-Be prepared for contingencies.  Always have a plan B

-Try to gather different perspectives.  

The power of a methodology

We all have a view of things we need to do in life to be happy and achieve what we want.

This can involve for instance to study, get a degree, then get a job, then get married, have children, buy a house, etc.  

We have some sort of sequence for these things to happen, but sometimes we have to change it, or we also have to do several of these things at the same time.

The good news is that we all have a methodology set in our lives.  A methodology is a process at shows how we want to achieve certain things in life (be happy). 

The methodology is also guided by certain values that we hold as true and essential to ensure that we do good research.  So for instance we want to achieve happiness in life by being honest.  Some researchers would call this having a set of principles. I personally prefer values, because they seem to be more linked to the person (researcher).  Values should also reflect the motivation to carry out research.  

One of my favourite values in research is that of inclusion.  To me it means to ensure that I include people and their views when doing research.  It also means sharing with them the outputs of the research, or the information that I will aim to publish from working with them.  

In a methodology there are stages or phases that you propose in order to provide answers to your research questions.  These stages could be organised in a logical sequence.  So that you know what you achieve when you complete one stage before or when starting another stage.  

This is not to say that a methodology should be an algorithm.  We do not live our lives according to algorithms.  Because many things can happen.  

A methodology gives guidance about what to do but also what to do in case of...it offers a way out of potential problems.  This guidance is also about how methods or techniques (I see them as activities in      the daily life of a researcher) are to be used. 

A methodology should also show that you are going to produce good data.  There are principles to ensure this.  Trustworthiness, rigour, good quality and ways to avoid bias are used in qualitative research.  In quantitative research these criteria can be validity and reliability. A good researcher knows what type of research suits his/her project, and is able to evaluate it according to relevant criteria.  

To sum up, a good methodology is a clear description that aims to ensure that other people can trust the results of your research.   Your research design should be robust so that other people can follow it if they need to.  Your findings should reflect as much as possible what people think or say and should 

be presented in a way that they can be understood and used by others. 

The not good news for some of you is that a methodology should be unique.  This does not mean that you cannot reuse some of the activities that you or other searchers have carried out in other projects.  But it is unique in the sense that is designed to specifically answer your research questions.  So you need to show that you know about methodology design, and that you have taken the time to design one particular for your project.  

Having a research question to live for

Do not get me wrong with the title of this post.  I honestly believe that good research in social sciences requires having and pursuing a burning research question, something to live (and maybe) to die for.

A research question is something that keeps you interested in your research.  It is a question that is relevant to you, but also interesting to other researchers in your area and to people who have a problem at work or in their daily life and want to solve it.

There could be many questions: how to cure cancer, how to reduce risk of suicide in youngsters, what impacts is social media having in the marketing of companies, how do ethnic minorities coexist in socially deprived areas; why are we having more floods in cities; or when is the best time for a company to enter into a new market.  Questions can be answered from the perspective of different areas of knowledge.  

I normally ask my students who do their dissertations or theses to start with a few questions.  These questions should be interesting for them first of all.  We rephrase some of the questions and then I ask them to go away and READ.  I suggest they read literature from at least two areas of knowledge.  This will ensure that students can see differences in perspective.  

Reading has the powerful effect to give you answers to your questions, but also to open up new questions.  If you read the literature of a subject you can identify what questions have driven researchers to pursue their research.  You can also identify other questions that they have not answered or that they are formulated to be pursued in the future.  Reading is a powerful source of questions.  

The more reading we do the more questions we have, but also the more information we can exchange in conversation.  So we can meet again, look at questions and go again and read.  

Of course you can (and should) review and modify your questions as you progress.  Some questions need to be divided into sub questions.  Others might become less relevant or interesting for you. And others are answered by other researchers when they publish their work.  

What is important for you as a researcher is to keep a research question alive.  By doing this you will also keep your motivation alive.  

And also make sure that you are able to provide some reasonable answers to the questions that you set within the time frame of your research project (dissertation, thesis). Maybe you have a big research question that will take a lifetime to answer.  So please do not forget that question.  But for now, we should focus on how to start answering it in the time that is set for your project.    

Reviewing the literature

Many of my students come to ask me the meaning of a literature review. 

They think that it is a requisite in a dissertation or thesis to write something from books or journals, before they can do what they would like to do in their  projects. 

The first thing I tell my students to do is to read.  And continue reading. And write about what you read. 

You might have a clear idea of you want to do.  But you need to acknowledge that there have been others before you.  And that there are others like you who do research, and do it better.  

A literature review is a process of positioning you and your research within a larger community of research.  It is about finding out what has been done and said, and finding out where you fit.  

The literature review is a public good, because it draws on public knowledge.  So you are producing something public, and by doing it you also show your competence to propose something innovative.  

So it is a balancing act.  Reviewing the current state of things about your topic, and bringing someone new to it.  This new could be a different perspective, something that other people have not done (maybe they want to do it as further research) plus something new like a rethinking of established knowledge, a different type of analysis on the subject, the use of alternative theories or methodologies, or their application in an untried context or setting, etc.  

There should be a guiding question or set of questions that should guide your reading.  These can be formulated before you start your review, and they can also change as you read.  Because your mindset keeps changing and should keep changing.  And because every day there are new articles and books on the topics of your interest.

Your review should cover two or three areas.  Otherwise you run the risk of talking about everything and nothing at the same time.  If you think that your research questions can be answered from the perspective of many disciplines, you need reformulate your questions. And I order to do this you need to read a bit more.  It might be that researchers are already tackling the questions that you are interested in, only that they use a different terminology.  For instance, if you want to know why is it that organisations invest too much in information technology and do not seem to get immediate benefits, you might like to look at research related to the information technology productivity paradox.  Alternatively you might like to look at the literature on information technology evaluation. 

Here is another example: if you want to understand how organisations become more competitive, you can tackle this issue from a marketing perspective or from an innovation perspective.  The literature in both of these areas will suggest ways in which competitiveness can be enhanced.  You might find similarities and differences on what they define as a problem of competitiveness as well as on how they go about solving it.

Longer research efforts (PhD) could take you to explore more than two areas of the literature.  This is because inevitably you will come across philosophical theories, sociological theories, learning theories, etc.  Even within one particular area or topic (learning), you are required to present several perspectives.  

Two more aspects characterise a literature review.  The first one is that is should be critical. This means that you not only describe the work of others but you also analyse it in terms of its suitability for your own research question or set of questions.  Again, your analysis is not only opinionated or descriptive, you also need to find literature that would support your views.  

The second aspect is that you declare explicitly in which area or areas your own research contributions are going to be.  You might not know this by the time that you do your literature review.  However, if you narrow the review appropriately, you will be able to show that in one or two particular areas there are research gaps that your work has the potential to fill.  

A good literature review is like a good scaffolding.  It is well structured.  It allows you to build on.  And it is pleasant to read, so that the reader gets on board your own research project.

  

Do you have what it takes to be a social science researcher ?

Many of us come to know about social science research in an expected way.

My own story is that of being a graduate of computer science and systems engineering.  I had worked in the private sector as a project manager and analyst for projects which involved  some information technologies (hardware, software).

I was also interested in systems thinking, a body of knowledge that provides a different view on complex societal problems.

I always wanted to understand how to make life easier and more fulfilling for me and other people.  Half way through my computer science degree, I realized that I could not fit life into technology.  Neither should I continue looking for a silver bullet, a methodology or a management fashion that could provide human fulfilment. Wanting to make life better is still a motivation to carry out research.  

So when you start the activity of research, ask yourself what your main motivation is.  Is it to obtain a degree (Msc, PhD), or is it to understand things in a better way?  Or is it to look for some knowledge that will enable you to control the life of other human beings? 

Social science research is about understanding.  Of course it has practical implications.  But in order to solve problems in a better way than it is currently the case, we need to understand. This requires us to change our mentality.  From being problem solvers to facilitators, from knowing what we think we know to accept that we do not know much.  

The ability to ask questions, and pursue some temporary answers, is key to research.  This does not mean we should all the time be worried about not having the right questions to ask.  They will come with reading, reflection and writing.  They will also come in our conversations with others.

So if you want to control other people's lives, maybe research is not for you and should better become something else.  Social life cannot be controlled.  You need to have humility as a researcher in order to accept this. 


Curiosity, humility, creativity and courage to pursue your own motivation, these are key ingredients for a social science researcher.