The theoretical framework is one of the more infamous components of a dissertation. A good theoretical framework gives you a strong scientific research base and provides support for the rest of your dissertation. But what exactly is a theoretical framework? And how do you write one?
The goal of a theoretical framework
After you have identified your problem statement and research question(s), it is important to determine what theories and ideas exist in relation to your chosen subject.
By presenting this information, you ‘frame’ your research and show that you are knowledgeable about the key concepts, theories, and models that relate to your topic.
The definitions and models you select also give your research direction, as you will continue to build on these choices in different stages of your project.
The theoretical framework also provides scientific justification for your investigation: it shows that your research is not just coming “out of the blue,” but that it is both grounded in and based on scientific theory.
How to determine the contents of a theoretical framework
As noted above, it is important that you cite existing theories and ideas that are relevant to your chosen topic within the theoretical framework. This includes defining key terms from your problem statement and research questions/hypotheses. An important first step is therefore to identify these concepts.
1. Select key concepts
Sample problem statement and research questions: Company X is struggling with the problem that many online customers do not return to make subsequent purchases. Management wants to increase customer loyalty and believes that improved customer satisfaction will play a major role in achieving this goal. To investigate this problem, you have identified and plan to focus on the following problem statement, objective, and research questions:
Problem: Many online customers do not return to make subsequent purchases.
Objective: To increase customer loyalty and thereby generate more revenue.
Research question: ‘How can the satisfaction of company X’s online customers be improved in order to increase customer loyalty?’
- ‘What is the relationship between customer loyalty and costumer satisfaction?’
- ‘How satisfied and loyal are company X’s online costumers currently?’
- ‘What factors affect the satisfaction and loyalty of company X’s online costumers?’
The concepts of “customer loyalty” and “customer satisfaction” are critical to this study and will be measured as part of the research. As such they are key concepts to define within the theoretical framework.
2. Define and evaluate relevant concepts, theories, and models
A literature review is first used to determine how other researchers have defined these key concepts. You should then critically compare the definitions that different authors have proposed. The last step is to choose the definition that best fits your research and justify why this is the case.
It is also important to indicate if there are any notable links between these concepts.
Apart from that, you should describe any relevant theories and models that relate to your key concepts and argue why you are or are not applying them to your own research.
3. Consider adding other elements to your theoretical framework
Depending on your topic or discipline, a comprehensive review of the state of affairs in relation to your research topic may also be helpful to include in your theoretical framework.
Here it’s important to understand the expectations of your supervisor or program in advance. Theoretical problems are more likely to require a “state of affairs” overview than more practical problems.
Analyzing the research field will give you an idea of what similar studies have looked at and found regarding the problem. This will clarify the position of your research in relation to existing knowledge in the field.
Following these steps will help to ensure that you are presenting a solid overview:
- Describe what discussions on the subject exist within the literature.
- Explain what methods, theories, and models other authors have applied. In doing so, always argue why a particular theory or model is or is not appropriate for your own research.
- Analyze the similarities and differences between your own research and earlier studies.
- Explain how your study adds to knowledge that already exists on the subject.
What kinds of research questions can you answer within a theoretical framework?
The theoretical framework can be used to answer descriptive research questions that only require literature (or desk) research. For example, theory alone is sufficient to answer the research question: ‘What is the relationship between customer loyalty and customer satisfaction?’.
In contrast, sub-questions such as ‘How satisfied are company X’s online customers currently?’ cannot be answered in the theoretical framework, given that field research is needed.
The theoretical framework (and the literature review that serves as its backbone) can also be used to further analyze existing findings and hypotheses. It may also be used to formulate and evaluate hypotheses of your own, which you can later test during the qualitative or quantitative research of your study.
The structure of the theoretical framework
There are no fixed rules for structuring a theoretical framework. The important thing is to create a structure that is logical. One way to do this is to draw on your research questions/hypotheses and some of your key terms.
For example, you could create a section or paragraph that looks at each question, hypothesis, or key concept. Within that text, you could then explore the theories and models that are relevant to that particular item.
How long should the theoretical framework be?
The rules about length are not clear either, but a theoretical framework is on average three to five pages long.
To makes things clearer, you might find it useful to include models or other graphics within the theoretical framework. However, if you are concerned about space, you can place these illustrations in an appendix (which you can then refer to in the main text).
Sample theoretical framework
We have prepared a sample theoretical framework that will give you a sense of what this important part of a dissertation may look like.
Sample theoretical framework
Elements of Research
A theoretical framework is a collection of interrelated concepts, like a theory but not necessarily so well worked-out. A theoretical framework guides your research, determining what things you will measure, and what statistical relationships you will look for.
Theoretical frameworks are obviously critical in deductive, theory-testing sorts of studies (see Kinds of Research for more information). In those kinds of studies, the theoretical framework must be very specific and well-thought out.
Surprisingly, theoretical frameworks are also important in exploratory studies, where you really don't know much about what is going on, and are trying to learn more. There are two reasons why theoretical frameworks are important here. First, no matter how little you think you know about a topic, and how unbiased you think you are, it is impossible for a human being not to have preconceived notions, even if they are of a very general nature. For example, some people fundamentally believe that people are basically lazy and untrustworthy, and you have keep your wits about you to avoid being conned. These fundamental beliefs about human nature affect how you look things when doing personnel research. In this sense, you are always being guided by a theoretical framework, but you don't know it. Not knowing what your real framework is can be a problem. The framework tends to guide what you notice in an organization, and what you don't notice. In other words, you don't even notice things that don't fit your framework! We can never completely get around this problem, but we can reduce the problem considerably by simply making our implicit framework explicit. Once it is explicit, we can deliberately consider other frameworks, and try to see the organizational situation through different lenses.
Cases and Variables
Cases are objects whose behavior or characteristics we study. Usually, the cases are persons. But they can also be groups, departments, organizations, etc. They can also be more esoteric things like events (e.g., meetings), utterances, pairs of people, etc.
Variables are characteristics of cases. They are attributes. Qualities of the cases that we measure or record. For example, if the cases are persons, the variables could be sex, age, height, weight, feeling of empowerment, math ability, etc. Variables are called what they are because it is assumed that the cases will vary in their scores on these attributes. For example, if the variable is age, we obviously recognize that people can be different ages. Of course, sometimes, for a given sample of people, there might not be any variation on some attribute. For example, the variable 'number of children' might be zero for all members of this class. It's still a variable, though, because in principle it could have variation.
In any particular study, variables can play different roles. Two key roles are independent variables and dependent variables. Usually there is only one dependent variable, and it is the outcome variable, the one you are trying to predict. Variation in the dependent variable is what you are trying to explain. For example, if we do a study to determine why some people are more satisfied in their jobs than others, job satisfaction is the dependent variable.
The independent variables, also known as the predictor or explanatory variables, are the factors that you think explain variation in the dependent variable. In other words, these are the causes. For example, you may think that people are more satisfied with their jobs if they are given a lot of freedom to do what they want, and if they are well-paid. So 'job freedom' and 'salary' are the independent variables, and 'job satisfaction' is the dependent variable. This is diagrammed as follows:
(yes, I know. It looks like the Enterprise)
There are actually two other kinds of variables, which are basically independent variables, but work a little differently. These are moderator and intervening variables. A moderator variable is one that modifies the relationship between two other variables.
For example, suppose that the cases are whole organizations, and you believe that diversity in the organization can help make them more profitable (because diversity leads to fresh outlooks on old problems), but only if managers are specially trained in diversity management (otherwise all that diversity causes conflicts and miscommunication). Here, diversity is clearly an independent variable, and profitability is clearly a dependent variable. But what is diversity training? Its main function seems to be adjust the strength of relation between diversity and profitability
For example, suppose you are studying job applications to various departments within a large organization. You believe that in overall, women applicants are more likely to get the job than men applicants, but that this varies by the number of women already in the department the person applied to. Specifically, departments that already have a lot of women will favor female applicants, while departments with few women will favor male applicants. We can diagram this as follows:
Actually, if that model is true, then this one is as well, though it's harder to think about:
Whether sex of applicant is the independent and % women in dept is the moderator, or the other around, is not something we can ever decide. Another way to talk about moderating and independent variables is in terms of interaction. Interacting variables affect the dependent variable only when both are acting in concert. We could diagram that this way:
An intervening or intermediary variable is one that is affected by the independent variable and in turn affects the dependent variable. For example, we said that diversity is good for profitability because diversity leads to innovation (fresh looks) which in turn leads to profitability. Here, innovation is an intervening variable. We diagram it this way:
Note that in the diagram, there is no arrow from diversity directly to profitability. This means that if we control for innovativeness, diversity is unrelated to profitability. To control for a variable means to hold its values constant. For example, suppose we measure the diversity, innovativeness and profitability of a several thousand companies. If we look at the relationship between diversity and profitability, we might find that the more diverse companies have, on average, higher profitability than the less diverse companies. But suppose we divide the sample into two groups: innovative companies and non-innovative. Now, within just the innovative group, we again look at the relationship between diversity and profitability. We might find that there is no relationship. Similarly, if we just look at the non-innovative group, we might find no relationship between diversity and profitability there either. That's because the only reason diversity affects profitability is because diversity tends to affect a company's innovativeness, and that in turn affects profitability.
Here's another example. Consider the relationship between education and health. In general, the more a educated a person is, the healthier they are. Do diplomas have magic powers? Do the cells in educated people's bodies know how to fight cancer? I doubt it. It might be because educated people are more likely to eat nutritionally sensible food and this in turn contributes to their health. But of course, there are many reasons why you might eat nutritionally sensible food, even if you are not educated. So if we were to look at the relationship between education and health among only people who eat nutritionally sensible food, we might find no relationship. That would support the idea that nutrition is an intervening variable.
It should be noted, however, if you control for a variable, and the relationship between two variables disappears, that doesn't necessarily mean that the variable you controlled for was an intervening variable. Here is an example. Look at the relationship between the amount of ice cream sold on a given day, and the number of drownings on those days. This is not hypothetical: this is real. There is a strong correlation: the more you sell, the more people drown. What's going on? Are people forgetting the 'no swimming within an hour of eating' rule? Ice cream screws up your coordination? No. There is a third variable that is causing both ice cream sales and drownings. The variable is temperature. On hot days, people are more likely to buy ice cream. They are also more likely to go to the beach, where a certain proportion will drown. If we control for temperature (i.e., we only consider days that are cold, or days that are warm), we find that there is no relationship between ice cream sales and drownings. But temperature is not an intervening variable, since it ice cream sales do not cause temperature changes. Nor is ice cream sales an intervening variable, since ice cream sales do not cause drownings.
|Copyright ©1996-8 Stephen P. Borgatti||Revised: September 07, 1999||Home Page|