research framework explained

How to Use a Conceptual Framework for Better Research

A conceptual framework in research is not just a tool but a vital roadmap that guides the entire research process. It integrates various theories, assumptions, and beliefs to provide a structured approach to research. By defining a conceptual framework, researchers can focus their inquiries and clarify their hypotheses, leading to more effective and meaningful research outcomes.

What is a Conceptual Framework?

A conceptual framework is essentially an analytical tool that combines concepts and sets them within an appropriate theoretical structure. It serves as a lens through which researchers view the complexities of the real world. The importance of a conceptual framework lies in its ability to serve as a guide, helping researchers to not only visualize but also systematically approach their study.

Key Components and to be Analyzed During Research

• Theories: These are the underlying principles that guide the hypotheses and assumptions of the research.
• Assumptions: These are the accepted truths that are not tested within the scope of the research but are essential for framing the study.
• Beliefs: These often reflect the subjective viewpoints that may influence the interpretation of data.
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Together, these components help to define the conceptual framework that directs the research towards its ultimate goal. This structured approach not only improves clarity but also enhances the validity and reliability of the research outcomes. By using a conceptual framework, researchers can avoid common pitfalls and focus on essential variables and relationships.

For practical examples and to see how different frameworks can be applied in various research scenarios, you can Explore Conceptual Framework Examples .

Different Types of Conceptual Frameworks Used in Research

Understanding the various types of conceptual frameworks is crucial for researchers aiming to align their studies with the most effective structure. Conceptual frameworks in research vary primarily between theoretical and operational frameworks, each serving distinct purposes and suiting different research methodologies.

Theoretical vs Operational Frameworks

Theoretical frameworks are built upon existing theories and literature, providing a broad and abstract understanding of the research topic. They help in forming the basis of the study by linking the research to already established scholarly works. On the other hand, operational frameworks are more practical, focusing on how the study’s theories will be tested through specific procedures and variables.

• Theoretical frameworks are ideal for exploratory studies and can help in understanding complex phenomena.
• Operational frameworks suit studies requiring precise measurement and data analysis.

Choosing the Right Framework

Selecting the appropriate conceptual framework is pivotal for the success of a research project. It involves matching the research questions with the framework that best addresses the methodological needs of the study. For instance, a theoretical framework might be chosen for studies that aim to generate new theories, while an operational framework would be better suited for testing specific hypotheses.

Benefits of choosing the right framework include enhanced clarity, better alignment with research goals, and improved validity of research outcomes. Tools like Table Chart Maker can be instrumental in visually comparing the strengths and weaknesses of different frameworks, aiding in this crucial decision-making process.

Real-World Examples of Conceptual Frameworks in Research

Understanding the practical application of conceptual frameworks in research can significantly enhance the clarity and effectiveness of your studies. Here, we explore several real-world case studies that demonstrate the pivotal role of conceptual frameworks in achieving robust research conclusions.

• Healthcare Research: In a study examining the impact of lifestyle choices on chronic diseases, researchers used a conceptual framework to link dietary habits, exercise, and genetic predispositions. This framework helped in identifying key variables and their interrelations, leading to more targeted interventions.
• Educational Development: Educational theorists often employ conceptual frameworks to explore the dynamics between teaching methods and student learning outcomes. One notable study mapped out the influences of digital tools on learning engagement, providing insights that shaped educational policies.
• Environmental Policy: Conceptual frameworks have been crucial in environmental research, particularly in studies on climate change adaptation. By framing the relationships between human activity, ecological changes, and policy responses, researchers have been able to propose more effective sustainability strategies.

Adapting conceptual frameworks based on evolving research data is also critical. As new information becomes available, it’s essential to revisit and adjust the framework to maintain its relevance and accuracy, ensuring that the research remains aligned with real-world conditions.

For those looking to visualize and better comprehend their research frameworks, Graphic Organizers for Conceptual Frameworks can be an invaluable tool. These organizers help in structuring and presenting research findings clearly, enhancing both the process and the presentation of your research.

Step-by-Step Guide to Creating Your Own Conceptual Framework

Creating a conceptual framework is a critical step in structuring your research to ensure clarity and focus. This guide will walk you through the process of building a robust framework, from identifying key concepts to refining your approach as your research evolves.

Building Blocks of a Conceptual Framework

• Identify and Define Main Concepts and Variables: Start by clearly identifying the main concepts, variables, and their relationships that will form the basis of your research. This could include defining key terms and establishing the scope of your study.
• Develop a Hypothesis or Primary Research Question: Formulate a central hypothesis or question that guides the direction of your research. This will serve as the foundation upon which your conceptual framework is built.
• Link Theories and Concepts Logically: Connect your identified concepts and variables with existing theories to create a coherent structure. This logical linking helps in forming a strong theoretical base for your research.

Visualizing and Refining Your Framework

Using visual tools can significantly enhance the clarity and effectiveness of your conceptual framework. Decision Tree Templates for Conceptual Frameworks can be particularly useful in mapping out the relationships between variables and hypotheses.

Map Your Framework: Utilize tools like Creately’s visual canvas to diagram your framework. This visual representation helps in identifying gaps or overlaps in your framework and provides a clear overview of your research structure.

Analyze and Refine: As your research progresses, continuously evaluate and refine your framework. Adjustments may be necessary as new data comes to light or as initial assumptions are challenged.

By following these steps, you can ensure that your conceptual framework is not only well-defined but also adaptable to the changing dynamics of your research.

Practical Tips for Utilizing Conceptual Frameworks in Research

Effectively utilizing a conceptual framework in research not only streamlines the process but also enhances the clarity and coherence of your findings. Here are some practical tips to maximize the use of conceptual frameworks in your research endeavors.

• Setting Clear Research Goals: Begin by defining precise objectives that are aligned with your research questions. This clarity will guide your entire research process, ensuring that every step you take is purposeful and directly contributes to your overall study aims. \
• Maintaining Focus and Coherence: Throughout the research, consistently refer back to your conceptual framework to maintain focus. This will help in keeping your research aligned with the initial goals and prevent deviations that could dilute the effectiveness of your findings.
• Data Analysis and Interpretation: Use your conceptual framework as a lens through which to view and interpret data. This approach ensures that the data analysis is not only systematic but also meaningful in the context of your research objectives. For more insights, explore Research Data Analysis Methods .
• Presenting Research Findings: When it comes time to present your findings, structure your presentation around the conceptual framework . This will help your audience understand the logical flow of your research and how each part contributes to the whole.
• Avoiding Common Pitfalls: Be vigilant about common errors such as overcomplicating the framework or misaligning the research methods with the framework’s structure. Keeping it simple and aligned ensures that the framework effectively supports your research.

By adhering to these tips and utilizing tools like 7 Essential Visual Tools for Social Work Assessment , researchers can ensure that their conceptual frameworks are not only robust but also practically applicable in their studies.

How Creately Enhances the Creation and Use of Conceptual Frameworks

Creating a robust conceptual framework is pivotal for effective research, and Creately’s suite of visual tools offers unparalleled support in this endeavor. By leveraging Creately’s features, researchers can visualize, organize, and analyze their research frameworks more efficiently.

• Visual Mapping of Research Plans: Creately’s infinite visual canvas allows researchers to map out their entire research plan visually. This helps in understanding the complex relationships between different research variables and theories, enhancing the clarity and effectiveness of the research process.
• Brainstorming with Mind Maps: Using Mind Mapping Software , researchers can generate and organize ideas dynamically. Creately’s intelligent formatting helps in brainstorming sessions, making it easier to explore multiple topics or delve deeply into specific concepts.
• Centralized Data Management: Creately enables the importation of data from multiple sources, which can be integrated into the visual research framework. This centralization aids in maintaining a cohesive and comprehensive overview of all research elements, ensuring that no critical information is overlooked.
• Communication and Collaboration: The platform supports real-time collaboration, allowing teams to work together seamlessly, regardless of their physical location. This feature is crucial for research teams spread across different geographies, facilitating effective communication and iterative feedback throughout the research process.

Moreover, the ability t Explore Conceptual Framework Examples directly within Creately inspires researchers by providing practical templates and examples that can be customized to suit specific research needs. This not only saves time but also enhances the quality of the conceptual framework developed.

In conclusion, Creately’s tools for creating and managing conceptual frameworks are indispensable for researchers aiming to achieve clear, structured, and impactful research outcomes.

Join over thousands of organizations that use Creately to brainstorm, plan, analyze, and execute their projects successfully.

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Chiraag George is a communication specialist here at Creately. He is a marketing junkie that is fascinated by how brands occupy consumer mind space. A lover of all things tech, he writes a lot about the intersection of technology, branding and culture at large.

The Ultimate Guide to Qualitative Research - Part 1: The Basics

• Introduction and overview
• What is qualitative research?
• What is qualitative data?
• Examples of qualitative data
• Qualitative vs. quantitative research
• Mixed methods
• Qualitative research preparation
• Theoretical perspective
• Theoretical framework
• Literature reviews
• Research question
• Introduction

Understanding conceptual frameworks

Selecting and developing your framework, variables in a conceptual framework.

• Conceptual vs. theoretical framework
• Data collection
• Qualitative research methods
• Focus groups
• Observational research
• Case studies
• Ethnographical research
• Ethical considerations
• Confidentiality and privacy
• Power dynamics
• Reflexivity

Conceptual framework: Definition and theory

Theoretical and conceptual frameworks ultimately go hand in hand, but while there is significant overlap with theoretical perspectives and theoretical frameworks, understanding the essential differences is important when designing your research project.

Let's explore the idea of a conceptual framework, provide a few common examples, and discuss how to choose a framework for your study. Keep in mind that a conceptual framework will differ from a theoretical framework and that we will explore these differences in the next section.

In this section, we'll delve into the intricacies of conceptual frameworks and their role in qualitative research . They are essentially the scaffolding on which you hang your research questions and analysis . They define the concepts that you'll study and articulate the relationships among them.

Developing conceptual frameworks in research

At the most basic level, a conceptual framework is a visual or written product that explains, either graphically or in narrative form, the main things to be studied, the key factors, variables, or constructs, and any presumed relationships among them. It acts as a road map guiding the course of your research, directing what will be studied, and helping to organize and analyze the data.

The purpose of a conceptual framework

A conceptual framework serves multiple functions in a research project. It helps in clarifying the research problem and purpose, assists in refining the research questions, and guides the data collection and analysis process. It's the tool that ties all aspects of the study together, offering a coherent perspective for the researcher and readers to understand the research more holistically.

Relation between theoretical perspectives and conceptual frameworks

Theoretical perspectives offer overarching philosophies and assumptions that guide the research process, while conceptual frameworks are the specific devices that are derived from these perspectives to operationalize the study. If a theoretical perspective is the broad philosophical underpinning, a conceptual framework is a pragmatic approach that puts that philosophy into practice in the context of the study.

For instance, if you're working from a feminist theoretical perspective, your conceptual framework might involve specific constructs like gender roles, power dynamics , and societal norms, as well as the relationships between these constructs. The conceptual framework would be the lens through which you examine and interpret your data, guided by your theoretical perspective.

Critical theory

Critical theory is a theoretical perspective that seeks to confront social, historical, and ideological forces and structures that produce and constrain social problems. The corresponding conceptual framework might focus on constructs like power relations, historical context, and societal structures. For instance, a study on income inequality might have a conceptual framework involving constructs of socioeconomic status, institutional policies, and the distribution of resources.

Feminist theory

Feminist theory emphasizes the societal roles of gender and power relationships. A conceptual framework derived from this theory might involve constructs like gender roles, power dynamics, and societal norms. In a study about gender representation in media, a feminist conceptual framework could involve constructs such as stereotyping, representation, and societal expectations of gender.

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Choosing and developing your conceptual framework is a pivotal process in your research design. This framework will help guide your study, inform your methodology , and shape your analysis .

Factors to consider when choosing a framework

Your conceptual framework should be derived from and align with your chosen theoretical perspective , but there are other considerations as well. It should resonate with your research question , problem, or purpose and be applicable to the specific context or population you are studying. You should also consider the feasibility of operationalizing the constructs in your framework.

When selecting a conceptual framework, consider the following questions:

1. How does this framework relate to my research topic? 2. Can I use this framework to effectively address my research question(s)? 3. Does this framework resonate with the population and context I'm studying? 4. Can the constructs in this framework be feasibly operationalized in my study?

Steps in developing a conceptual framework

Developing your conceptual framework involves a few key steps:

1. Identify key constructs: Based on your theoretical perspective and research question(s) , what are the main constructs or variables that you need to explore in your study? 2. Clarify relationships among constructs: How do these constructs relate to each other? Are there presumed causal relationships, correlations, or other types of associations? 3. Define each construct: Clearly define what each construct means in the context of your study. This might also involve operationalizing each construct or defining the indicators you will use to measure or identify each construct. 4. Create a visual representation : It is often extremely helpful to create a visual representation of your conceptual framework to illustrate the constructs and their relationships. Map out the relationships among constructs to develop a holistic understanding of what you want to study.

Remember, your conceptual framework is not set in stone. You can start creating your conceptual framework based on your literature review and your own critical reflections. As you proceed with your study, you might need to refine or adapt your conceptual framework based on what you're learning from your data. Developing a robust framework is an iterative process that requires critical thinking, creativity, and flexibility.

A strong conceptual framework includes variables that refer to the constructs or characteristics that are being studied. They are the building blocks of your research study. It might be helpful to think about how the variables in your conceptual framework could be categorized as independent and dependent variables, which respectively influence and are influenced within the research study.

Independent variables and dependent variables

An independent variable is the characteristic or condition that is manipulated or selected by the researcher to determine its effect on the dependent variable. For example, in a study exploring the impact of classroom size on student engagement, classroom size would be the independent variable.

The dependent variable is the main outcome that the researcher is interested in studying or explaining. In the example given above, student engagement would be the dependent variable, as it's the outcome being observed for any changes in response to the independent variable (classroom size). In essence, defining these variables can help you identify the cause-and-effect relationships in your study. While it might be difficult to know beforehand exactly which variables will be important and how they relate to one another, this is a helpful thought exercise to flesh out potential relationships among variables you may want to study.

Relationships among variables

Within a conceptual framework, the dependent and independent variables are listed in addition to their proposed relationships to each other. The ways in which these variables influence one another form the crux of the propositions or assumptions that guide your research.

In a conceptual framework based on the theoretical perspective of constructivism, for instance, the independent variable might be a teaching method (as constructivists would argue that methods of instruction can shape learning), and the dependent variable could be the depth of student understanding. The proposed relationship between these variables might be that student-centered teaching methods lead to a deeper understanding, which would guide the data collection and analysis such that this proposition could be explored.

However, it is important to note that the terminology of independent and dependent variables is more typical of quantitative research , in which independent and dependent variables are operationalized in hypotheses that will be tested based on pre-established theory. In qualitative research , the relationships between variables are more fluid and open-ended because the focus is often more on understanding the phenomenon as a whole and building a contextualized understanding of the research problem. This can involve including new or unexpected variables and interrelationships that emerge during the study, thus extending previous theory or understanding that didn’t initially predict these relationships.

Thus, in your conceptual framework, rather than solely focusing on identifying independent and dependent variables, consider how various factors interact and influence one another within the context of your study. Your conceptual framework should provide a holistic picture of the complexity of the phenomenon you are studying.

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• What Is a Conceptual Framework? | Tips & Examples

What Is a Conceptual Framework? | Tips & Examples

Published on 4 May 2022 by Bas Swaen and Tegan George. Revised on 18 March 2024.

A conceptual framework illustrates the expected relationship between your variables. It defines the relevant objectives for your research process and maps out how they come together to draw coherent conclusions.

Keep reading for a step-by-step guide to help you construct your own conceptual framework.

Table of contents

Developing a conceptual framework in research, step 1: choose your research question, step 2: select your independent and dependent variables, step 3: visualise your cause-and-effect relationship, step 4: identify other influencing variables, frequently asked questions about conceptual models.

A conceptual framework is a representation of the relationship you expect to see between your variables, or the characteristics or properties that you want to study.

Conceptual frameworks can be written or visual and are generally developed based on a literature review of existing studies about your topic.

Your research question guides your work by determining exactly what you want to find out, giving your research process a clear focus.

However, before you start collecting your data, consider constructing a conceptual framework. This will help you map out which variables you will measure and how you expect them to relate to one another.

In order to move forward with your research question and test a cause-and-effect relationship, you must first identify at least two key variables: your independent and dependent variables .

• The expected cause, ‘hours of study’, is the independent variable (the predictor, or explanatory variable)
• The expected effect, ‘exam score’, is the dependent variable (the response, or outcome variable).

Note that causal relationships often involve several independent variables that affect the dependent variable. For the purpose of this example, we’ll work with just one independent variable (‘hours of study’).

Now that you’ve figured out your research question and variables, the first step in designing your conceptual framework is visualising your expected cause-and-effect relationship.

It’s crucial to identify other variables that can influence the relationship between your independent and dependent variables early in your research process.

Some common variables to include are moderating, mediating, and control variables.

Moderating variables

Moderating variable (or moderators) alter the effect that an independent variable has on a dependent variable. In other words, moderators change the ‘effect’ component of the cause-and-effect relationship.

Let’s add the moderator ‘IQ’. Here, a student’s IQ level can change the effect that the variable ‘hours of study’ has on the exam score. The higher the IQ, the fewer hours of study are needed to do well on the exam.

Let’s take a look at how this might work. The graph below shows how the number of hours spent studying affects exam score. As expected, the more hours you study, the better your results. Here, a student who studies for 20 hours will get a perfect score.

But the graph looks different when we add our ‘IQ’ moderator of 120. A student with this IQ will achieve a perfect score after just 15 hours of study.

Below, the value of the ‘IQ’ moderator has been increased to 150. A student with this IQ will only need to invest five hours of study in order to get a perfect score.

Here, we see that a moderating variable does indeed change the cause-and-effect relationship between two variables.

Mediating variables

Now we’ll expand the framework by adding a mediating variable . Mediating variables link the independent and dependent variables, allowing the relationship between them to be better explained.

Here’s how the conceptual framework might look if a mediator variable were involved:

In this case, the mediator helps explain why studying more hours leads to a higher exam score. The more hours a student studies, the more practice problems they will complete; the more practice problems completed, the higher the student’s exam score will be.

Moderator vs mediator

It’s important not to confuse moderating and mediating variables. To remember the difference, you can think of them in relation to the independent variable:

• A moderating variable is not affected by the independent variable, even though it affects the dependent variable. For example, no matter how many hours you study (the independent variable), your IQ will not get higher.
• A mediating variable is affected by the independent variable. In turn, it also affects the dependent variable. Therefore, it links the two variables and helps explain the relationship between them.

Control variables

Lastly,  control variables must also be taken into account. These are variables that are held constant so that they don’t interfere with the results. Even though you aren’t interested in measuring them for your study, it’s crucial to be aware of as many of them as you can be.

A mediator variable explains the process through which two variables are related, while a moderator variable affects the strength and direction of that relationship.

No. The value of a dependent variable depends on an independent variable, so a variable cannot be both independent and dependent at the same time. It must be either the cause or the effect, not both.

Yes, but including more than one of either type requires multiple research questions .

For example, if you are interested in the effect of a diet on health, you can use multiple measures of health: blood sugar, blood pressure, weight, pulse, and many more. Each of these is its own dependent variable with its own research question.

You could also choose to look at the effect of exercise levels as well as diet, or even the additional effect of the two combined. Each of these is a separate independent variable .

To ensure the internal validity of an experiment , you should only change one independent variable at a time.

A control variable is any variable that’s held constant in a research study. It’s not a variable of interest in the study, but it’s controlled because it could influence the outcomes.

A confounding variable , also called a confounder or confounding factor, is a third variable in a study examining a potential cause-and-effect relationship.

A confounding variable is related to both the supposed cause and the supposed effect of the study. It can be difficult to separate the true effect of the independent variable from the effect of the confounding variable.

In your research design , it’s important to identify potential confounding variables and plan how you will reduce their impact.

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What is a Conceptual Framework?

A conceptual framework sets forth the standards to define a research question and find appropriate, meaningful answers for the same. It connects the theories, assumptions, beliefs, and concepts behind your research and presents them in a pictorial, graphical, or narrative format.

Updated on August 28, 2023

What are frameworks in research?

Both theoretical and conceptual frameworks have a significant role in research.  Frameworks are essential to bridge the gaps in research. They aid in clearly setting the goals, priorities, relationship between variables. Frameworks in research particularly help in chalking clear process details.

Theoretical frameworks largely work at the time when a theoretical roadmap has been laid about a certain topic and the research being undertaken by the researcher, carefully analyzes it, and works on similar lines to attain successful results. 

It varies from a conceptual framework in terms of the preliminary work required to construct it. Though a conceptual framework is part of the theoretical framework in a larger sense, yet there are variations between them.

The following sections delve deeper into the characteristics of conceptual frameworks. This article will provide insight into constructing a concise, complete, and research-friendly conceptual framework for your project.

Definition of a conceptual framework

True research begins with setting empirical goals. Goals aid in presenting successful answers to the research questions at hand. It delineates a process wherein different aspects of the research are reflected upon, and coherence is established among them. 

A conceptual framework is an underrated methodological approach that should be paid attention to before embarking on a research journey in any field, be it science, finance, history, psychology, etc. 

A conceptual framework sets forth the standards to define a research question and find appropriate, meaningful answers for the same. It connects the theories, assumptions, beliefs, and concepts behind your research and presents them in a pictorial, graphical, or narrative format. Your conceptual framework establishes a link between the dependent and independent variables, factors, and other ideologies affecting the structure of your research.

A critical facet a conceptual framework unveils is the relationship the researchers have with their research. It closely highlights the factors that play an instrumental role in decision-making, variable selection, data collection, assessment of results, and formulation of new theories.

Consequently, if you, the researcher, are at the forefront of your research battlefield, your conceptual framework is the most powerful arsenal in your pocket.

What should be included in a conceptual framework?

A conceptual framework includes the key process parameters, defining variables, and cause-and-effect relationships. To add to this, the primary focus while developing a conceptual framework should remain on the quality of questions being raised and addressed through the framework. This will not only ease the process of initiation, but also enable you to draw meaningful conclusions from the same. 

A practical and advantageous approach involves selecting models and analyzing literature that is unconventional and not directly related to the topic. This helps the researcher design an illustrative framework that is multidisciplinary and simultaneously looks at a diverse range of phenomena. It also emboldens the roots of exploratory research. 

Fig. 1: Components of a conceptual framework

How to make a conceptual framework

The successful design of a conceptual framework includes:

• Selecting the appropriate research questions
• Defining the process variables (dependent, independent, and others)
• Determining the cause-and-effect relationships

This analytical tool begins with defining the most suitable set of questions that the research wishes to answer upon its conclusion. Following this, the different variety of variables is categorized. Lastly, the collected data is subjected to rigorous data analysis. Final results are compiled to establish links between the variables. 

The variables drawn inside frames impact the overall quality of the research. If the framework involves arrows, it suggests correlational linkages among the variables. Lines, on the other hand, suggest that no significant correlation exists among them. Henceforth, the utilization of lines and arrows should be done taking into cognizance the meaning they both imply.

Example of a conceptual framework

To provide an idea about a conceptual framework, let’s examine the example of drug development research. 

Say a new drug moiety A has to be launched in the market. For that, the baseline research begins with selecting the appropriate drug molecule. This is important because it:

• Provides the data for molecular docking studies to identify suitable target proteins
• Performs in vitro (a process taking place outside a living organism) and in vivo (a process taking place inside a living organism) analyzes

This assists in the screening of the molecules and a final selection leading to the most suitable target molecule. In this case, the choice of the drug molecule is an independent variable whereas, all the others, targets from molecular docking studies, and results from in vitro and in vivo analyses are dependent variables.

The outcomes revealed by the studies might be coherent or incoherent with the literature. In any case, an accurately designed conceptual framework will efficiently establish the cause-and-effect relationship and explain both perspectives satisfactorily.

If A has been chosen to be launched in the market, the conceptual framework will point towards the factors that have led to its selection. If A does not make it to the market, the key elements which did not work in its favor can be pinpointed by an accurate analysis of the conceptual framework.

Fig. 2: Concise example of a conceptual framework

Important takeaways

While conceptual frameworks are a great way of designing the research protocol, they might consist of some unforeseen loopholes. A review of the literature can sometimes provide a false impression of the collection of work done worldwide while in actuality, there might be research that is being undertaken on the same topic but is still under publication or review. Strong conceptual frameworks, therefore, are designed when all these aspects are taken into consideration and the researchers indulge in discussions with others working on similar grounds of research.

Conceptual frameworks may also sometimes lead to collecting and reviewing data that is not so relevant to the current research topic. The researchers must always be on the lookout for studies that are highly relevant to their topic of work and will be of impact if taken into consideration. 

Another common practice associated with conceptual frameworks is their classification as merely descriptive qualitative tools and not actually a concrete build-up of ideas and critically analyzed literature and data which it is, in reality. Ideal conceptual frameworks always bring out their own set of new ideas after analysis of literature rather than simply depending on facts being already reported by other research groups.

So, the next time you set out to construct your conceptual framework or improvise on your previous one, be wary that concepts for your research are ideas that need to be worked upon. They are not simply a collection of literature from the previous research.

Final thoughts

Research is witnessing a boom in the methodical approaches being applied to it nowadays. In contrast to conventional research, researchers today are always looking for better techniques and methods to improve the quality of their research. 

We strongly believe in the ideals of research that are not merely academic, but all-inclusive. We strongly encourage all our readers and researchers to do work that impacts society. Designing strong conceptual frameworks is an integral part of the process. It gives headway for systematic, empirical, and fruitful research.

Vridhi Sachdeva, MPharm

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Theories are formulated to explain, predict, and understand phenomena and, in many cases, to challenge and extend existing knowledge within the limits of critical bounded assumptions or predictions of behavior. The theoretical framework is the structure that can hold or support a theory of a research study. The theoretical framework encompasses not just the theory, but the narrative explanation about how the researcher engages in using the theory and its underlying assumptions to investigate the research problem. It is the structure of your paper that summarizes concepts, ideas, and theories derived from prior research studies and which was synthesized in order to form a conceptual basis for your analysis and interpretation of meaning found within your research.

Abend, Gabriel. "The Meaning of Theory." Sociological Theory 26 (June 2008): 173–199; Kivunja, Charles. "Distinguishing between Theory, Theoretical Framework, and Conceptual Framework: A Systematic Review of Lessons from the Field." International Journal of Higher Education 7 (December 2018): 44-53; Swanson, Richard A. Theory Building in Applied Disciplines . San Francisco, CA: Berrett-Koehler Publishers 2013; Varpio, Lara, Elise Paradis, Sebastian Uijtdehaage, and Meredith Young. "The Distinctions between Theory, Theoretical Framework, and Conceptual Framework." Academic Medicine 95 (July 2020): 989-994.

Importance of Theory and a Theoretical Framework

Theories can be unfamiliar to the beginning researcher because they are rarely applied in high school social studies curriculum and, as a result, can come across as unfamiliar and imprecise when first introduced as part of a writing assignment. However, in their most simplified form, a theory is simply a set of assumptions or predictions about something you think will happen based on existing evidence and that can be tested to see if those outcomes turn out to be true. Of course, it is slightly more deliberate than that, therefore, summarized from Kivunja (2018, p. 46), here are the essential characteristics of a theory.

• It is logical and coherent
• It has clear definitions of terms or variables, and has boundary conditions [i.e., it is not an open-ended statement]
• It has a domain where it applies
• It has clearly described relationships among variables
• It describes, explains, and makes specific predictions
• It comprises of concepts, themes, principles, and constructs
• It must have been based on empirical data [i.e., it is not a guess]
• It must have made claims that are subject to testing, been tested and verified
• It must be clear and concise
• Its assertions or predictions must be different and better than those in existing theories
• Its predictions must be general enough to be applicable to and understood within multiple contexts
• Its assertions or predictions are relevant, and if applied as predicted, will result in the predicted outcome
• The assertions and predictions are not immutable, but subject to revision and improvement as researchers use the theory to make sense of phenomena
• Its concepts and principles explain what is going on and why
• Its concepts and principles are substantive enough to enable us to predict a future

Given these characteristics, a theory can best be understood as the foundation from which you investigate assumptions or predictions derived from previous studies about the research problem, but in a way that leads to new knowledge and understanding as well as, in some cases, discovering how to improve the relevance of the theory itself or to argue that the theory is outdated and a new theory needs to be formulated based on new evidence.

A theoretical framework consists of concepts and, together with their definitions and reference to relevant scholarly literature, existing theory that is used for your particular study. The theoretical framework must demonstrate an understanding of theories and concepts that are relevant to the topic of your research paper and that relate to the broader areas of knowledge being considered.

The theoretical framework is most often not something readily found within the literature . You must review course readings and pertinent research studies for theories and analytic models that are relevant to the research problem you are investigating. The selection of a theory should depend on its appropriateness, ease of application, and explanatory power.

The theoretical framework strengthens the study in the following ways :

• An explicit statement of  theoretical assumptions permits the reader to evaluate them critically.
• The theoretical framework connects the researcher to existing knowledge. Guided by a relevant theory, you are given a basis for your hypotheses and choice of research methods.
• Articulating the theoretical assumptions of a research study forces you to address questions of why and how. It permits you to intellectually transition from simply describing a phenomenon you have observed to generalizing about various aspects of that phenomenon.
• Having a theory helps you identify the limits to those generalizations. A theoretical framework specifies which key variables influence a phenomenon of interest and highlights the need to examine how those key variables might differ and under what circumstances.
• The theoretical framework adds context around the theory itself based on how scholars had previously tested the theory in relation their overall research design [i.e., purpose of the study, methods of collecting data or information, methods of analysis, the time frame in which information is collected, study setting, and the methodological strategy used to conduct the research].

By virtue of its applicative nature, good theory in the social sciences is of value precisely because it fulfills one primary purpose: to explain the meaning, nature, and challenges associated with a phenomenon, often experienced but unexplained in the world in which we live, so that we may use that knowledge and understanding to act in more informed and effective ways.

The Conceptual Framework. College of Education. Alabama State University; Corvellec, Hervé, ed. What is Theory?: Answers from the Social and Cultural Sciences . Stockholm: Copenhagen Business School Press, 2013; Asher, Herbert B. Theory-Building and Data Analysis in the Social Sciences . Knoxville, TN: University of Tennessee Press, 1984; Drafting an Argument. Writing@CSU. Colorado State University; Kivunja, Charles. "Distinguishing between Theory, Theoretical Framework, and Conceptual Framework: A Systematic Review of Lessons from the Field." International Journal of Higher Education 7 (2018): 44-53; Omodan, Bunmi Isaiah. "A Model for Selecting Theoretical Framework through Epistemology of Research Paradigms." African Journal of Inter/Multidisciplinary Studies 4 (2022): 275-285; Ravitch, Sharon M. and Matthew Riggan. Reason and Rigor: How Conceptual Frameworks Guide Research . Second edition. Los Angeles, CA: SAGE, 2017; Trochim, William M.K. Philosophy of Research. Research Methods Knowledge Base. 2006; Jarvis, Peter. The Practitioner-Researcher. Developing Theory from Practice . San Francisco, CA: Jossey-Bass, 1999.

Strategies for Developing the Theoretical Framework

I.  Developing the Framework

Here are some strategies to develop of an effective theoretical framework:

• Examine your thesis title and research problem . The research problem anchors your entire study and forms the basis from which you construct your theoretical framework.
• Brainstorm about what you consider to be the key variables in your research . Answer the question, "What factors contribute to the presumed effect?"
• Review related literature to find how scholars have addressed your research problem. Identify the assumptions from which the author(s) addressed the problem.
• List  the constructs and variables that might be relevant to your study. Group these variables into independent and dependent categories.
• Review key social science theories that are introduced to you in your course readings and choose the theory that can best explain the relationships between the key variables in your study [note the Writing Tip on this page].
• Discuss the assumptions or propositions of this theory and point out their relevance to your research.

A theoretical framework is used to limit the scope of the relevant data by focusing on specific variables and defining the specific viewpoint [framework] that the researcher will take in analyzing and interpreting the data to be gathered. It also facilitates the understanding of concepts and variables according to given definitions and builds new knowledge by validating or challenging theoretical assumptions.

II.  Purpose

Think of theories as the conceptual basis for understanding, analyzing, and designing ways to investigate relationships within social systems. To that end, the following roles served by a theory can help guide the development of your framework.

• Means by which new research data can be interpreted and coded for future use,
• Response to new problems that have no previously identified solutions strategy,
• Means for identifying and defining research problems,
• Means for prescribing or evaluating solutions to research problems,
• Ways of discerning certain facts among the accumulated knowledge that are important and which facts are not,
• Means of giving old data new interpretations and new meaning,
• Means by which to identify important new issues and prescribe the most critical research questions that need to be answered to maximize understanding of the issue,
• Means of providing members of a professional discipline with a common language and a frame of reference for defining the boundaries of their profession, and
• Means to guide and inform research so that it can, in turn, guide research efforts and improve professional practice.

Adapted from: Torraco, R. J. “Theory-Building Research Methods.” In Swanson R. A. and E. F. Holton III , editors. Human Resource Development Handbook: Linking Research and Practice . (San Francisco, CA: Berrett-Koehler, 1997): pp. 114-137; Jacard, James and Jacob Jacoby. Theory Construction and Model-Building Skills: A Practical Guide for Social Scientists . New York: Guilford, 2010; Ravitch, Sharon M. and Matthew Riggan. Reason and Rigor: How Conceptual Frameworks Guide Research . Second edition. Los Angeles, CA: SAGE, 2017; Sutton, Robert I. and Barry M. Staw. “What Theory is Not.” Administrative Science Quarterly 40 (September 1995): 371-384.

Structure and Writing Style

The theoretical framework may be rooted in a specific theory , in which case, your work is expected to test the validity of that existing theory in relation to specific events, issues, or phenomena. Many social science research papers fit into this rubric. For example, Peripheral Realism Theory, which categorizes perceived differences among nation-states as those that give orders, those that obey, and those that rebel, could be used as a means for understanding conflicted relationships among countries in Africa. A test of this theory could be the following: Does Peripheral Realism Theory help explain intra-state actions, such as, the disputed split between southern and northern Sudan that led to the creation of two nations?

However, you may not always be asked by your professor to test a specific theory in your paper, but to develop your own framework from which your analysis of the research problem is derived . Based upon the above example, it is perhaps easiest to understand the nature and function of a theoretical framework if it is viewed as an answer to two basic questions:

• What is the research problem/question? [e.g., "How should the individual and the state relate during periods of conflict?"]
• Why is your approach a feasible solution? [i.e., justify the application of your choice of a particular theory and explain why alternative constructs were rejected. I could choose instead to test Instrumentalist or Circumstantialists models developed among ethnic conflict theorists that rely upon socio-economic-political factors to explain individual-state relations and to apply this theoretical model to periods of war between nations].

The answers to these questions come from a thorough review of the literature and your course readings [summarized and analyzed in the next section of your paper] and the gaps in the research that emerge from the review process. With this in mind, a complete theoretical framework will likely not emerge until after you have completed a thorough review of the literature .

Just as a research problem in your paper requires contextualization and background information, a theory requires a framework for understanding its application to the topic being investigated. When writing and revising this part of your research paper, keep in mind the following:

• Clearly describe the framework, concepts, models, or specific theories that underpin your study . This includes noting who the key theorists are in the field who have conducted research on the problem you are investigating and, when necessary, the historical context that supports the formulation of that theory. This latter element is particularly important if the theory is relatively unknown or it is borrowed from another discipline.
• Position your theoretical framework within a broader context of related frameworks, concepts, models, or theories . As noted in the example above, there will likely be several concepts, theories, or models that can be used to help develop a framework for understanding the research problem. Therefore, note why the theory you've chosen is the appropriate one.
• The present tense is used when writing about theory. Although the past tense can be used to describe the history of a theory or the role of key theorists, the construction of your theoretical framework is happening now.
• You should make your theoretical assumptions as explicit as possible . Later, your discussion of methodology should be linked back to this theoretical framework.
• Don’t just take what the theory says as a given! Reality is never accurately represented in such a simplistic way; if you imply that it can be, you fundamentally distort a reader's ability to understand the findings that emerge. Given this, always note the limitations of the theoretical framework you've chosen [i.e., what parts of the research problem require further investigation because the theory inadequately explains a certain phenomena].

The Conceptual Framework. College of Education. Alabama State University; Conceptual Framework: What Do You Think is Going On? College of Engineering. University of Michigan; Drafting an Argument. Writing@CSU. Colorado State University; Lynham, Susan A. “The General Method of Theory-Building Research in Applied Disciplines.” Advances in Developing Human Resources 4 (August 2002): 221-241; Tavallaei, Mehdi and Mansor Abu Talib. "A General Perspective on the Role of Theory in Qualitative Research." Journal of International Social Research 3 (Spring 2010); Ravitch, Sharon M. and Matthew Riggan. Reason and Rigor: How Conceptual Frameworks Guide Research . Second edition. Los Angeles, CA: SAGE, 2017; Reyes, Victoria. Demystifying the Journal Article. Inside Higher Education; Trochim, William M.K. Philosophy of Research. Research Methods Knowledge Base. 2006; Weick, Karl E. “The Work of Theorizing.” In Theorizing in Social Science: The Context of Discovery . Richard Swedberg, editor. (Stanford, CA: Stanford University Press, 2014), pp. 177-194.

Writing Tip

Borrowing Theoretical Constructs from Other Disciplines

An increasingly important trend in the social and behavioral sciences is to think about and attempt to understand research problems from an interdisciplinary perspective. One way to do this is to not rely exclusively on the theories developed within your particular discipline, but to think about how an issue might be informed by theories developed in other disciplines. For example, if you are a political science student studying the rhetorical strategies used by female incumbents in state legislature campaigns, theories about the use of language could be derived, not only from political science, but linguistics, communication studies, philosophy, psychology, and, in this particular case, feminist studies. Building theoretical frameworks based on the postulates and hypotheses developed in other disciplinary contexts can be both enlightening and an effective way to be more engaged in the research topic.

CohenMiller, A. S. and P. Elizabeth Pate. "A Model for Developing Interdisciplinary Research Theoretical Frameworks." The Qualitative Researcher 24 (2019): 1211-1226; Frodeman, Robert. The Oxford Handbook of Interdisciplinarity . New York: Oxford University Press, 2010.

Another Writing Tip

Don't Undertheorize!

Do not leave the theory hanging out there in the introduction never to be mentioned again. Undertheorizing weakens your paper. The theoretical framework you describe should guide your study throughout the paper. Be sure to always connect theory to the review of pertinent literature and to explain in the discussion part of your paper how the theoretical framework you chose supports analysis of the research problem or, if appropriate, how the theoretical framework was found to be inadequate in explaining the phenomenon you were investigating. In that case, don't be afraid to propose your own theory based on your findings.

Yet Another Writing Tip

What's a Theory? What's a Hypothesis?

The terms theory and hypothesis are often used interchangeably in newspapers and popular magazines and in non-academic settings. However, the difference between theory and hypothesis in scholarly research is important, particularly when using an experimental design. A theory is a well-established principle that has been developed to explain some aspect of the natural world. Theories arise from repeated observation and testing and incorporates facts, laws, predictions, and tested assumptions that are widely accepted [e.g., rational choice theory; grounded theory; critical race theory].

A hypothesis is a specific, testable prediction about what you expect to happen in your study. For example, an experiment designed to look at the relationship between study habits and test anxiety might have a hypothesis that states, "We predict that students with better study habits will suffer less test anxiety." Unless your study is exploratory in nature, your hypothesis should always explain what you expect to happen during the course of your research.

The key distinctions are:

• A theory predicts events in a broad, general context;  a hypothesis makes a specific prediction about a specified set of circumstances.
• A theory has been extensively tested and is generally accepted among a set of scholars; a hypothesis is a speculative guess that has yet to be tested.

Cherry, Kendra. Introduction to Research Methods: Theory and Hypothesis. About.com Psychology; Gezae, Michael et al. Welcome Presentation on Hypothesis. Slideshare presentation.

Still Yet Another Writing Tip

Be Prepared to Challenge the Validity of an Existing Theory

Theories are meant to be tested and their underlying assumptions challenged; they are not rigid or intransigent, but are meant to set forth general principles for explaining phenomena or predicting outcomes. Given this, testing theoretical assumptions is an important way that knowledge in any discipline develops and grows. If you're asked to apply an existing theory to a research problem, the analysis will likely include the expectation by your professor that you should offer modifications to the theory based on your research findings.

Indications that theoretical assumptions may need to be modified can include the following:

• Your findings suggest that the theory does not explain or account for current conditions or circumstances or the passage of time,
• The study reveals a finding that is incompatible with what the theory attempts to explain or predict, or
• Your analysis reveals that the theory overly generalizes behaviors or actions without taking into consideration specific factors revealed from your analysis [e.g., factors related to culture, nationality, history, gender, ethnicity, age, geographic location, legal norms or customs , religion, social class, socioeconomic status, etc.].

Philipsen, Kristian. "Theory Building: Using Abductive Search Strategies." In Collaborative Research Design: Working with Business for Meaningful Findings . Per Vagn Freytag and Louise Young, editors. (Singapore: Springer Nature, 2018), pp. 45-71; Shepherd, Dean A. and Roy Suddaby. "Theory Building: A Review and Integration." Journal of Management 43 (2017): 59-86.

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Home » Theoretical Framework – Types, Examples and Writing Guide

Theoretical Framework – Types, Examples and Writing Guide

Table of Contents

Theoretical Framework

Definition:

Theoretical framework refers to a set of concepts, theories, ideas , and assumptions that serve as a foundation for understanding a particular phenomenon or problem. It provides a conceptual framework that helps researchers to design and conduct their research, as well as to analyze and interpret their findings.

In research, a theoretical framework explains the relationship between various variables, identifies gaps in existing knowledge, and guides the development of research questions, hypotheses, and methodologies. It also helps to contextualize the research within a broader theoretical perspective, and can be used to guide the interpretation of results and the formulation of recommendations.

Types of Theoretical Framework

Types of Types of Theoretical Framework are as follows:

Conceptual Framework

This type of framework defines the key concepts and relationships between them. It helps to provide a theoretical foundation for a study or research project .

Deductive Framework

This type of framework starts with a general theory or hypothesis and then uses data to test and refine it. It is often used in quantitative research .

Inductive Framework

This type of framework starts with data and then develops a theory or hypothesis based on the patterns and themes that emerge from the data. It is often used in qualitative research .

Empirical Framework

This type of framework focuses on the collection and analysis of empirical data, such as surveys or experiments. It is often used in scientific research .

Normative Framework

This type of framework defines a set of norms or values that guide behavior or decision-making. It is often used in ethics and social sciences.

Explanatory Framework

This type of framework seeks to explain the underlying mechanisms or causes of a particular phenomenon or behavior. It is often used in psychology and social sciences.

Components of Theoretical Framework

The components of a theoretical framework include:

• Concepts : The basic building blocks of a theoretical framework. Concepts are abstract ideas or generalizations that represent objects, events, or phenomena.
• Variables : These are measurable and observable aspects of a concept. In a research context, variables can be manipulated or measured to test hypotheses.
• Assumptions : These are beliefs or statements that are taken for granted and are not tested in a study. They provide a starting point for developing hypotheses.
• Propositions : These are statements that explain the relationships between concepts and variables in a theoretical framework.
• Hypotheses : These are testable predictions that are derived from the theoretical framework. Hypotheses are used to guide data collection and analysis.
• Constructs : These are abstract concepts that cannot be directly measured but are inferred from observable variables. Constructs provide a way to understand complex phenomena.
• Models : These are simplified representations of reality that are used to explain, predict, or control a phenomenon.

How to Write Theoretical Framework

A theoretical framework is an essential part of any research study or paper, as it helps to provide a theoretical basis for the research and guide the analysis and interpretation of the data. Here are some steps to help you write a theoretical framework:

• Identify the key concepts and variables : Start by identifying the main concepts and variables that your research is exploring. These could include things like motivation, behavior, attitudes, or any other relevant concepts.
• Review relevant literature: Conduct a thorough review of the existing literature in your field to identify key theories and ideas that relate to your research. This will help you to understand the existing knowledge and theories that are relevant to your research and provide a basis for your theoretical framework.
• Develop a conceptual framework : Based on your literature review, develop a conceptual framework that outlines the key concepts and their relationships. This framework should provide a clear and concise overview of the theoretical perspective that underpins your research.
• Identify hypotheses and research questions: Based on your conceptual framework, identify the hypotheses and research questions that you want to test or explore in your research.
• Test your theoretical framework: Once you have developed your theoretical framework, test it by applying it to your research data. This will help you to identify any gaps or weaknesses in your framework and refine it as necessary.
• Write up your theoretical framework: Finally, write up your theoretical framework in a clear and concise manner, using appropriate terminology and referencing the relevant literature to support your arguments.

Theoretical Framework Examples

Here are some examples of theoretical frameworks:

• Social Learning Theory : This framework, developed by Albert Bandura, suggests that people learn from their environment, including the behaviors of others, and that behavior is influenced by both external and internal factors.
• Maslow’s Hierarchy of Needs : Abraham Maslow proposed that human needs are arranged in a hierarchy, with basic physiological needs at the bottom, followed by safety, love and belonging, esteem, and self-actualization at the top. This framework has been used in various fields, including psychology and education.
• Ecological Systems Theory : This framework, developed by Urie Bronfenbrenner, suggests that a person’s development is influenced by the interaction between the individual and the various environments in which they live, such as family, school, and community.
• Feminist Theory: This framework examines how gender and power intersect to influence social, cultural, and political issues. It emphasizes the importance of understanding and challenging systems of oppression.
• Cognitive Behavioral Theory: This framework suggests that our thoughts, beliefs, and attitudes influence our behavior, and that changing our thought patterns can lead to changes in behavior and emotional responses.
• Attachment Theory: This framework examines the ways in which early relationships with caregivers shape our later relationships and attachment styles.
• Critical Race Theory : This framework examines how race intersects with other forms of social stratification and oppression to perpetuate inequality and discrimination.

When to Have A Theoretical Framework

Following are some situations When to Have A Theoretical Framework:

• A theoretical framework should be developed when conducting research in any discipline, as it provides a foundation for understanding the research problem and guiding the research process.
• A theoretical framework is essential when conducting research on complex phenomena, as it helps to organize and structure the research questions, hypotheses, and findings.
• A theoretical framework should be developed when the research problem requires a deeper understanding of the underlying concepts and principles that govern the phenomenon being studied.
• A theoretical framework is particularly important when conducting research in social sciences, as it helps to explain the relationships between variables and provides a framework for testing hypotheses.
• A theoretical framework should be developed when conducting research in applied fields, such as engineering or medicine, as it helps to provide a theoretical basis for the development of new technologies or treatments.
• A theoretical framework should be developed when conducting research that seeks to address a specific gap in knowledge, as it helps to define the problem and identify potential solutions.
• A theoretical framework is also important when conducting research that involves the analysis of existing theories or concepts, as it helps to provide a framework for comparing and contrasting different theories and concepts.
• A theoretical framework should be developed when conducting research that seeks to make predictions or develop generalizations about a particular phenomenon, as it helps to provide a basis for evaluating the accuracy of these predictions or generalizations.
• Finally, a theoretical framework should be developed when conducting research that seeks to make a contribution to the field, as it helps to situate the research within the broader context of the discipline and identify its significance.

Purpose of Theoretical Framework

The purposes of a theoretical framework include:

• Providing a conceptual framework for the study: A theoretical framework helps researchers to define and clarify the concepts and variables of interest in their research. It enables researchers to develop a clear and concise definition of the problem, which in turn helps to guide the research process.
• Guiding the research design: A theoretical framework can guide the selection of research methods, data collection techniques, and data analysis procedures. By outlining the key concepts and assumptions underlying the research questions, the theoretical framework can help researchers to identify the most appropriate research design for their study.
• Supporting the interpretation of research findings: A theoretical framework provides a framework for interpreting the research findings by helping researchers to make connections between their findings and existing theory. It enables researchers to identify the implications of their findings for theory development and to assess the generalizability of their findings.
• Enhancing the credibility of the research: A well-developed theoretical framework can enhance the credibility of the research by providing a strong theoretical foundation for the study. It demonstrates that the research is based on a solid understanding of the relevant theory and that the research questions are grounded in a clear conceptual framework.
• Facilitating communication and collaboration: A theoretical framework provides a common language and conceptual framework for researchers, enabling them to communicate and collaborate more effectively. It helps to ensure that everyone involved in the research is working towards the same goals and is using the same concepts and definitions.

Characteristics of Theoretical Framework

Some of the characteristics of a theoretical framework include:

• Conceptual clarity: The concepts used in the theoretical framework should be clearly defined and understood by all stakeholders.
• Logical coherence : The framework should be internally consistent, with each concept and assumption logically connected to the others.
• Empirical relevance: The framework should be based on empirical evidence and research findings.
• Parsimony : The framework should be as simple as possible, without sacrificing its ability to explain the phenomenon in question.
• Flexibility : The framework should be adaptable to new findings and insights.
• Testability : The framework should be testable through research, with clear hypotheses that can be falsified or supported by data.
• Applicability : The framework should be useful for practical applications, such as designing interventions or policies.

Advantages of Theoretical Framework

Here are some of the advantages of having a theoretical framework:

• Provides a clear direction : A theoretical framework helps researchers to identify the key concepts and variables they need to study and the relationships between them. This provides a clear direction for the research and helps researchers to focus their efforts and resources.
• Increases the validity of the research: A theoretical framework helps to ensure that the research is based on sound theoretical principles and concepts. This increases the validity of the research by ensuring that it is grounded in established knowledge and is not based on arbitrary assumptions.
• Enables comparisons between studies : A theoretical framework provides a common language and set of concepts that researchers can use to compare and contrast their findings. This helps to build a cumulative body of knowledge and allows researchers to identify patterns and trends across different studies.
• Helps to generate hypotheses: A theoretical framework provides a basis for generating hypotheses about the relationships between different concepts and variables. This can help to guide the research process and identify areas that require further investigation.
• Facilitates communication: A theoretical framework provides a common language and set of concepts that researchers can use to communicate their findings to other researchers and to the wider community. This makes it easier for others to understand the research and its implications.

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Conceptual Research Framework

• First Online: 29 January 2023

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• Philipp Sylla 3  

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To build a solid theoretical foundation for the following empirical analysis, a conceptual research framework will be developed within this chapter. First of all, the objectives and theoretical foundation of the research framework will be presented in section 4.1. In addition, the structure of the framework and its representation in this chapter will be explained.

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A conceptual research framework represents a first step toward the formation of theoretical insights (cp. Kirsch et al. (2007), pp. 22–23). Its main purpose is a precise delineation of the research problem which should prevent empirical data collection without a solid conceptual basis (cp. Kaufmann (2001), p. 147).

Cp. section  4.1.3 .

Cp. Wolf (2011), p. 37.

Cp. Wiesener (2014), p. 109.

Commonly, the statements are limited to assuming functional relationships without specifying these in more detail (cp. Kirsch (1973), p. 14).

Cp. Beckmann (2009), p. 81; Dietrich (2001), p. 22.

Cp. Vollhardt (2007), p. 68.

Cp. Wolf (2011), p. 202.

Cp. Pfohl and Zöllner (1997), pp. 307–312.

Cp. Reinking (2012), pp. 251–258.

Cp. Beckmann (2009), pp. 81–82; Eder (2016), pp. 38–40; Reinking (2012), pp. 248–249; Vollhardt (2007), p. 68.

Cp. Petersen (2012), p. 51; Miroschedji (2002), p. 122; Wolf (2011), pp. 38–39.

Cp. Wolf (2011), pp. 218–230.

Cp. Beckmann (2009), p. 83; Jensen (2004), p. 15; Vollhardt (2007), p. 71; Wolf (2011), p. 218.

Schoonhoven (1981), p. 350.

Cp. Jensen (2004), pp. 15–16; Beckmann (2009), p. 84.

Cp. Beckmann (2009), p. 84; Wolf (2011), p. 223.

Cp. section  1.3 .

Source: own representation.

In scientific research, the identification of dimensions is fundamental for conceptualization, i.e. the process for making fuzzy and imprecise notions more specific and precise (cp. Babbie (2016), pp. 123–132).

Cp. Wolf (2011), pp. 38–39.

This definition is based on a general definition of system use as “[…] the degree and manner in which staff and customers utilize the capabilities of an information system” (Petter et al. (2008), p. 239).

This is evident by the central role of system use in conceptual models of IS success (cp. DeLone and McLean (1992), p. 87; Gable et al. (2008), p. 382; Soh and Markus (1995), p. 37). In addition, many empirical studies indicate that system use is relevant for IS success (cp. Petter et al. (2008), pp. 251–252).

DeLone and McLean (2003), p. 16.

A business relationship is a sequence of market transactions between a buyer and seller that is not incidental (cp. Kleinaltenkamp et al. (2011), p. 22).

Cp. Kleineicken (2004), p. 105.

Cp. Richter and Nohr (2002), p. 110.

Cp. Bächle and Lehmann (2010), p. 70.

Cp. Büyüközkan (2004), p. 140.

Cp. Hartmann (2002b), pp. 167–171.

Cp. Jetu and Riedl (2012), pp. 462–463.

Besides the organizational level, system use can also be studied at the individual or group level. Research at more aggregate levels (e.g. the level of an industry or nation) is less common (cp. Burton-Jones and Gallivan (2007), p. 659).

While users in a voluntary use setting can choose whether an IS is used or not, users do not have such a choice and must use a prescribed system in a mandatory setting (cp. Bhattacherjee et al. (2018), pp. 395–396).

In general, system use can be either studied in terms of an “intention to use” which is an attitude or as a behavior (cp. DeLone and McLean (2003), p. 23).

Cp. Jasperson et al. (2005), pp. 531–535.

Cp. Deeter-Schmelz et al. (2001), p. 10; Joo and Kim (2004), p. 95; Schoenherr and Mabert (2011), p. 831; Upadhyaya et al. (2017), p. 69.

Cp. Alsaad et al. (2018), p. 29; Gottschalk and Foss Abrahamsen (2002), p. 330; Kim and Ahn (2007), p. 131; Son and Benbasat (2007), p. 92; Quaddus and Hofmeyer (2007), p. 209.

For example, participants may have to indicate their extent of use ranging from “not at all” to “a great extent” (cp. Le et al. (2004), p. 301) or by using other similar scales (cp. Hadaya (2008), p. 267; Rao et al. (2007), p. 1040; Truong and Jitpaiboon (2008), p. 206). Another option is to ask participants to indicate the stage of their current use, for example ranging from the “exploration stage” to the “commitment stage” (cp. Son and Benbasat (2007), p. 92) or by using other stages (cp. Grewal et al. (2001), p. 24; Kang et al. (2007), pp. 108–109).

Cp. Hassan et al. (2017), p. 305; Zhu and Kraemer (2005), p. 67.

Cp. Barua et al. (2004), p. 604; Batenburg (2007), p. 186; Hassan et al. (2017), p. 322; Le et al. (2004), p. 301.

Cp. Benslimane et al. (2005), p. 224.

Cp. Garrido et al. (2008), p. 626; Hassan et al. (2017), p. 311; Quesada et al. (2010), p. 533; Rai et al. (2009), p. 275.

Cp. Giunipero et al. (2012), p. 292; Kassim and Hussin (2013), pp. 8–11; Mishra et al. (2007), p. 118; Mishra et al. (2013), p. 388; Pearcy et al. (2008), p. 26; Ranganathan et al. (2011), p. 539; Wu et al. (2007), p. 583; Yu et al. (2015), p. 1061.

One study investigates which factors affect the use of an EM for information search or transaction settlement in the context of purchasing hospital products (cp. Oppel (2003)). Another study focuses on the factors of buyer-supplier relationships which affect the choice of different EM functionalities (cp. Wang and Archer (2004)).

Cp. Jap and Haruvy (2008); Hawkins et al. (2009); Hawkins et al. (2010); Mithas et al. (2008); Schoenherr and Mabert (2008), (2011); Smeltzer and Carr (2003); Stoll (2008); Wagner and Schwab (2004).

Some studies deal with the collaborative use of electronic SCM (cp. Pu et al. (2018)), electronic information transfer (cp. Kim et al. (2006)), IOS integration (cp. Grover and Saeed (2007)) or information sharing (cp. Hadaya and Pellerin (2010)).

This distinction between discrete and relational exchanges stems from relational exchange theory (cp. Goles and Chin (2002), p. 228; Leimeister (2010), p. 26; Yaqub and Vetschera (2011), p. 215). Some authors have proposed similar polar distinctions with different terms: e.g. “adversarial” vs. “collaborative” (cp. McIvor et al. (1998), p. 96) or “transactional” vs. “collaborative” relationships (cp. Bunduchi (2005), p. 322). Besides a distinction of two polar ends of relationships, some authors also provide a more nuanced categorization for business relationships. For example, Spekman et al. (1998) distinguish between „open market negotiations“, „cooperation“, “coordination” and “collaboration” (cp. Spekman et al. (1998), p. 634).

The move to the market hypothesis states that the overall effect of the developments in IT “[…] will be to increase the economic activity coordinated by markets” (Malone et al. (1987), p. 489). This hypothesis has been challenged by the so-called move to the middle hypothesis. Their proponents believe that instead of an increase of market coordination “[…] the firm will rely on fewer suppliers than before, with whom the firm will have close and long-term relationships and with whom the firm will cooperate and coordinate closely (a move away from the market to intermediate governance structures when outsourcing)” (Clemons et al. (1993), p. 13).

Private EMs which are owned by a participant and often closed when it comes to the entry of other participants are associated with relational exchanges. In contrast, independent EMs are often associated with discrete exchanges. Consortia EMs are sometimes perceived as hybrid forms between private and independent EMs (cp. Bahinipati and Deshmukh (2012), p. 24; Chelariu and Sangtani (2009), p. 112; El Sawy (2003), p. 122; Grieger et al. (2003), p. 285).

Cp. Ivang and Sørensen (2005), p. 398; Wang and Archer (2004).

Relational exchange theory grew out of the fields of marketing and law and deals with hybrid governance forms between market and hierarchy as set outlined in transaction cost theory, e.g. strategic alliances, networks, or partnerships (cp. Goles and Chin (2002), p. 228; Yaqub and Vetschera (2011), p. 216).

In a broad definition, relational norms can be defined as “[…] a principal of right action binding upon the members of a group and serving to guide, control, or regulate proper and acceptable behavior” (cp. Macneil (1980), p. 38).

Long-term orientation denotes the degree to which the business partners expect to pursue the continuation of the business relationship (cp. Buriánek (2009), p. 105).

Macneil (1981), p. 1027.

Noordewier et al. (1990), p. 84.

Cp. Grieger (2003), p. 289; Kaplan and Sawhney (2000), p. 98.

Kaufmann and Dant (1992), p. 173.

In general, EMs can be open or closed (cp. section  3.3.1 ). However, there can also be mixed forms whereby both open and/or closed areas are provided on an EM (cp. Schönsleben (2016), p. 85). For example, reverse auctions could be conducted openly with all potential suppliers or they could be restricted to only preselected participants (cp. Stoll (2008), p. 193; Wagner (2004), p. 220).

Source: Transporeon (2016), p. 7.

Cp. Kaufmann and Stern (1988), p. 536.

Cp. Kaufmann and Dant (1992), p. 173.

Cp. Asmussen (2009), p. 137; Auer (2004), p. 97; Georgi (2000), p. 46; Hadwich (2003), p. 25.

Instant quoting provides a comparison of fixed price offers from multiple transportation service providers (cp. section  3.5.1.1.2 ). Bulletin boards mainly support the establishment of the first contact between shippers and transportation service providers (cp. section  3.5.1.1.1 ). Therefore, both functionalities are most suitable and used with no restrictions on the supplier base (i.e., all transportation service providers on the ETM are potentially involved).

Only known transportation service providers are possible for electronic transport orders because the conditions of the exchange must be agreed between the shipper and the transportation service provider beforehand.

Reverse auctions and e-tendering can be either conducted openly with all transportation service providers or in a restricted way with preselected business partners.

The reverse auction and e-tendering functionalities are positioned between these extreme points.

The phases in the development of a business relationship start with awareness and exploration and continue with expansion and commitment until the final dissolution (cp. Dwyer et al. (1987), pp. 15–19).

Cp. Saab (2007), p. 31. Trust refers to the confident belief of one party that another party can be relied upon to behave in such a manner that the own long-term interest will be served (cp. Crosby et al. (1990), p. 70). Satisfaction is a „[…] party’s affective state of feeling adequately or inadequately rewarded for the sacrifice undergone in facilitating an exchange relationship” ( Frazier et al. (1988), p. 66).

However, this does not mean that trust and satisfaction are neglected as variables for the relationship to ETMs. In particular, empirical studies which provide results for the impact of contextual variables on the trust to and satisfaction with EMs and ETMs will be considered (cp. section  4.3.3.2 ).

Cp. Keil and Tiwana (2006), pp. 239–241.

In general, companies can use multiple EMs concurrently (this is called multi-homing) or only one single EM (single-homing). Whether the buyers and sellers participating in an EM are prone to multi-homing or single-homing behavior has a considerable impact on the competition and strategies of the providers of such marketplaces (cp. Rochet and Tirole (2003), pp. 1007–1013; Koh and Fichman (2014), p. 978).

Cp. Abts and Mülder (2017), p. 530; Benlian and Hess (2011); Keil and Tiwana (2006); Schumacher and Meyer (2004), pp. 290–291; Schütte and Vering (2011), p. 81.

For a review of EM selection criteria in the literature, cp. section  4.3.3.1.3 .

Research areas where commitment is of relevance include interpersonal relationships (e.g. friendships and marriage) or the organizational commitment between employees and their employing organization (cp. Saab (2007), pp. 26–34).

Cp. Saab (2007), pp. 24–34.

Cp. Anderson and Weitz (1992); Chen et al. (2011); Gundlach et al. (1995); Huo et al. (2015); Lancastre and Lages (2006); Moore (1998); Morgan and Hunt (1994); Moorman et al. (1992); Sharma et al. (2015); Standaert et al. (2015); Zhao et al. (2011).

Dwyer et al. (1987), p. 19.

Visser and Clark (2004), p. 45. Attitudes facilitate the repetitive evaluation of objects and provide behavioral orientation in a complex environment (cp. Eggert (1999), p. 63; Visser and Clark (2004), pp. 46–47). Amongst other things, the evaluated objects can be people, tangible objects, other attitudes, institutions, behavior, or behavioral intentions (cp. Mayerl (2009), p. 23).

Behavioral intentions precede the planned behavior of people, i.e. a person forms a behavioral intention before performing a certain behavior (cp. Fishbein and Ajzen (2010), p. 39).

Cp. Kroeber-Riel and Gröppel-Klein (2013), p. 218.

Cp. Mayerl (2009), p. 24.

For example, people will have a more positive attitude toward golfing if they believe that golfing is highly associated with attributes subjectively perceived as being positive (e.g. being a beneficial form of physical activity) and less associated with negatives ones (e.g. leading to frustration) (cp. Haddock and Maio (2014), pp. 200–201).

Cp. Mayerl (2009), p. 25. For example, people often report that spiders cause feelings of anxiety. Such kinds of negative affective reactions will most likely lead to negative attitudes toward spiders (cp. Haddock and Maio (2014), pp. 201–203).

Cp. Monahan et al. (2000), p. 462.

Cp. Wolf (2011), p. 38.

This definition of the purchasing situation is based on a more general definition of the purchasing situation as “[…] all relevant forces and influences related to the acquisition of required materials, services and equipment, which have a potential impact on the way buyers and sellers work together” (Hartmann (2002a), p. 11).

Cp. Warschun (2002), p. 99.

Cp. Janker (2008), p. 25.

Cp. Hartmann (2002a), pp. 10–27.

For example, the perceived compatibility of the EM technology has a positive effect on the intention to adopt or the extent of use of EMs (cp. Li et al. (2013); White et al. (2007), pp. 90–91).

Empirical studies provide some indications that top management support (cp. Deng et al. (2019b), p. 347; Najmul Islam et al. (2020), pp. 14–16; Saprikis and Vlachopoulou (2012), pp. 630–633) and the use of related IT (cp. Chang and Wong (2010), pp. 266–268; Hadaya (2006), pp. 179–182; Truong and Jitpaiboon (2008), pp. 207–212) have a positive effect on the adoption and extent of use of EMs.

There is some empirical evidence that external pressure (e.g. pressure from business partners) has a positive effect on the adoption or extent of use of EMs(cp. Deng et al. (2019b), p. 347; Hadaya (2006), pp. 179–182; Li et al. (2013)). However, two studies could not find a statistically significant effect of external pressures (cp. Grewal et al. (2001), pp. 27–29; Quaddus and Hofmeyer (2007), pp. 208–211).

These are the dimensions of the so-called technology-organization-environment framework (cp. Coleman (2019), p. 123).

For example, the use of related IT such as e-commerce might be a factor that can predict the use of an EM from the perspective of the diffusion of innovations, but this cannot be used as justification for a managerial decision.

For an overview of different criteria which are relevant for the general selection of software, cp. Krcmar (2015), pp. 216–220. An overview of the literature on EM selection criteria will be provided in section  4.3.3.1.3 .

Besides ETM properties, other variables may affect the relationship to ETMs, e.g. trust (cp. Liu and Tang (2018), p. 679; McKnight et al. (2017), p. 132; Pavlou (2002), p. 231; Pavlou and Gefen (2004), p. 50; Verhagen et al. (2006), pp. 547–549) or satisfaction (cp. Gruen (1995), p. 457; Stenglin (2008), p. 57; Wang (2008), pp. 542–546). Therefore, insights from empirical studies which find an effect of ETM properties on trust or satisfaction will be used (cp. sections  4.3.3.2.1 to 4.3.3.2.6 ).

Cp. Hassan (2013), pp. 307–308; Gangwar et al. (2014), pp. 489–490.

Cp. Luthardt (2003), p. 79.

A transaction cost reasoning has been used to explain why improvements in IT will lead to an increased use of EMs (cp. Malone et al. (1987), pp. 485–487).

Transaction cost theory has been applied as the theoretical foundation for the identification of conditions that are relevant for using an ETM for the procurement of transportation services (cp. Goldsby and Eckert (2003), pp. 188–195).

Cp. Lillehagen and Krogstie (2008), p. 313.

Cp. Janz (2004), p. 106; Sydow (1992), p. 196.

However, both theories focus on different root causes which are relevant for the design of buyer-supplier relationships. While transaction cost theory emphasizes that the costs involved in transactions are important for designing efficient exchanges, resource dependency theory focuses on the need of firms to ensure the supply of needed resources and proposes that relationships with other firms can be used to control situations of dependency.

Several studies deal with the design of buyer-supplier relationships on the spectrum between discrete and relational exchanges. Insights from these studies can be useful to explain the relational orientation within the system use dimension of the design variables.

Empirical research is based on data. It usually involves making conjectures about certain matters related to a specific research question. Afterward, it is examined whether the empirical data support this conjecture. Conceptual research does not involve the collection and analysis of new data for advancing knowledge. Instead, conceptual contributions include developing a set of propositions, proposing a new theory or theoretical model, or providing a comprehensive review of the literature (cp. Monippally and Pawar (2010), pp. 15–439).

Conceptual insights from the literature on e-procurement and EMs will be presented in section  4.3.2.1.3 and insights from the literature on buyer-supplier relationships in section  4.3.2.1.4 .

Cp. sections  4.3.2.2.1 to 4.3.2.2.6 .

Media richness theory can be used to explain the effect of complexity (cp. section  4.3.2.2.2 ) and incomplete contracts theory can be used to explain the impact of specifiability (cp. section  4.3.2.2.6 ).

Cp. Coase (1937), pp. 386–405.

Cp. Williamson (1981), (1985), (1996).

Governance structures refer to the institutional framework within which the initiation, negotiation, monitoring, adaptation, and termination of contracts takes place (cp. Roemer (2004), p. 25).

Cp. Picot et al. (2001), p. 53.

Cp. Picot and Dietl (1990), p. 178.

Often, different types of costs for transactions are distinguished. For example, costs for initiation (e.g. research, travel expenses), agreement (e.g. negotiations), settlement (e.g. process monitoring), control (e.g. control of quality and deadlines), and adjustment (e.g. extra costs for later changes of quality, price or dates) (cp. Picot et al. (2001), p. 50; Schütt (2006), p. 80).

Cp. Williamson (1985), pp. 52–61.

Williamson (1991), p. 281.

This is an example of so-called “site specificity“ as one of several types or dimensions of asset specificity.

Opportunism denotes maximizing the own self-interest at the expense of others (cp. Picot et al. (2001), p. 52). Investments involving highly specific assets represent situations that can be opportunistically exploited by exchange parties (cp. Kiedaisch (1997), p. 48; Picot et al. (2001), p. 52; Spengel (2005), pp. 91–92).

Cp. section  4.3.2.2.1 for a more detailed discussion of the effects of asset specificity.

Cp. Rindfleisch and Heide (1997), p. 31.

Cp. Kiedaisch (1997), pp. 48–49; Picot et al. (2001), p. 52.

Source: own representation adapted from Williamson (1996), p. 108.

Cp. Picot et al. (2001), p. 53; Williamson (1996), pp. 60–61.

Cp. Janz (2004), p. 104; Werner (1997), p. 22. Resources can be defined as all means which a company needs for self-preservation (cp. Knack (2006), p. 30).

Pfeffer and Salancik (2003), p. 258.

Cp. Sydow (1992), p. 197.

Cp. Frazier (1983), p. 159.

Ratnasingam (2000), p. 56.

It is often proclaimed that dependency and power are inversely related (cp. Homburg (1998), p. 49; Janz (2004), p. 161). However, there are two parties involved in economic exchanges and each party can depend on the other. Therefore, situations of dominance or power are especially given if dependency is asymmetric, i.e. one party is more dependent on the other party (cp. Cox (2001), p. 13.).

Cp. Pfeffer and Salancik (2003), pp. 45–51. For a comprehensive review of potential determinants of dependency, cp. Freiling (1995), pp. 48–68.

Cp. Janz (2004), p. 105; Pfeffer and Salancik (2003), pp. 113–143; Sydow (1992), p. 198; Werner (1997), p. 24.

The insights of these portfolio models for the identified contextual variables will also be discussed in their corresponding chapters (cp. sections  4.3.2.2.1 to 4.3.2.2.6 ).

Freight exchange is a synonym for ETM.

Source: Andersson and Norrman (2002), p. 6.

Cp. Andersson and Norrman (2002), p. 6.

Cp. Kraljic (1983), pp. 111–112.

Cp. Caniëls and Gelderman (2007), p. 220.

Cp. Arnold and Schnabel (2007), p. 87; Bogaschewsky (2002), p. 27; Kollmann (2019), p. 189; Luczak et al. (2002), p. 161; Tassabehji (2010), p. 434.

Cp. Bogaschewsky (2002), pp. 27–28.

Designing buyers-supplier relationships is one of the tasks of strategic procurement management (cp. Large (2009), p. 150). Within marketing, the so-called relationship marketing emphasizes the importance of long-term relationships for improving sales (cp. Grönroos (1991), p. 8).

Source: Halldórsson and Skjøtt‐Larsen (2004), p. 195.

Cp. Halldórsson and Skjøtt‐Larsen (2004), pp. 194–196.

Source: Bask (2001), p. 476.

Cp. Bask (2001), pp. 474–478.

Cp. Arnolds et al. (2016), p. 33; Cox (2001), p. 13; Dyer et al. (1998), p. 72 Homburg (1995), p. 829; Olsen and Ellram (1997), p. 105.

Cp. Heide and John (1990), p. 27.

There are different types of asset specificity: physical asset specificity (e.g., specific machines which are needed for production), human asset specificity (e.g., when special knowledge is required), or site specificity (e.g., when a resource is only available in a specific location). In addition, specificity can arise in the form of temporal specificity (e.g. when inputs lose their value when not delivered on time), dedicated assets (e.g. capacities which are reserved for certain business partners), or brand capital (cp. Eistert (1996), p. 43; Söllner (2008), p. 45; Williamson (1991), p. 281).

Williamson (1985), p. 52.

Cp. Kiedaisch (1997), p. 48.

Cp. Malone et al. (1987), pp. 486–487.

Cp. Dyer et al. (1998), p. 72.

Cp. Halldórsson and Skjøtt‐Larsen (2004), p. 195.

Cp. Mahadevan (2003), pp. 94–96; Weiber et al. (2004), pp. 565–566.

A negative effect of asset specificity has been found in a Delphi study (cp. Junge et al. (2019), p. 37). In a survey study, no significant effect of asset specificity on the intention to adopt EMs but a negative effect on the extent of use has been found (cp. Son and Benbasat (2007), pp. 80–82).

It has been found that buyers bid less aggressively when they are willing to make specific investments (cp. Jap and Haruvy (2008), p. 556) and that electronic auctions are not suitable for supply involving specific requirements (cp. Stoll (2008), p. 239). Only one study did not find a significant effect of asset specificity on the use of electronic reverse auctions (cp. Mithas et al. (2008), p. 716).

Asset specificity has a positive effect on the use of supply chain management systems for exchanging information via the internet (cp. Pu et al. (2018), pp. 1701–1702) or cooperation and EDI use (cp. Son et al. (2005), pp. 338–341).

Cp. Anderson and Weitz (1992), pp. 25–26; Aral et al. (2018), p. 606; Garbe (1998), pp. 164–170; Hallén et al. (1987), pp. 28–35; Hallén et al. (1993), pp. 76–80.

Cp. Claro et al. (2003), pp. 710–713; Heide and Miner (1992), pp. 277–282; Subramani and Venkatraman (2003), pp. 54–57.

Simon (1962), p. 468.

Structural complexity refers to the number and heterogeneity of elements that make up a system. The dynamic complexity refers to the interactions between the elements of a system (cp. Bode and Wagner (2015), p. 216; Werner (1997), p. 64; Voigt et al. (2003), p. 91).

Product complexity refers to the number of parts and/or technologies that are used within a product, their heterogeneity as well as the interdependencies between these parts and/or technologies (cp. Werner (1997), p. 71). The product description complexity denotes „[…] the amount of information needed to specify the attributes of a product in enough detail to allow potential buyers (whether producers acquiring production inputs or consumers acquiring goods) to make a selection“ (Malone et al. (1987), p. 486).

Cp. Andersson and Norrman (2002), p. 4. Typically, packages or bundles of different logistics services are exchanged within contract logistics (cp. Kersten et al. (2007), pp. 37–38).

Cp. section  2.2.3 .

Williamson (1975), p. 22.

Williamson states that “[…] the distinction between deterministic complexity and uncertainty is inessential” ( Williamson (1975), p. 23).

Higher transaction costs in presence of complexity can be a result of the need for extensive information search, complicated contracts, and more possibilities for opportunistic behavior (cp. Hohberger (2001), p. 31).

Cp. Reuter (2013), p. 125. According to media richness theory, communication media vary in their capacity to process rich information (cp. Daft and Lengel (1984), pp. 191–233). For example, personal face-to-face communication provides rich communication via multiple channels like language, gestures, or facial expressions as well as direct feedback.

It has been proposed that face-to-face negotiations are preferred for complex goods while EMs are best used for goods that involve a low complexity (cp. Ihde (2004), p. 34) or that e-procurement is best used for standard goods involving a low degree of complexity (cp. Möhrstädt et al. (2001), pp. 124–125).

Cp. Homburg (1995), p. 826.

Cp. Bask (2001), p. 476.

Cp. Andersson and Norrman (2002); Ihde (2004), p. 34.

Cp. Stoll (2008), p. 236; Reuter (2013), pp. 203–204.

Cp. Choudhury et al. (1998), p. 495; Holzmüller and Schlüchter (2002), p. 9; Junge et al. (2019), p. 37.

Cp. Son and Benbasat (2007), pp. 80–85.

Cp. Upadhyaya et al. (2017), pp. 61–63.

Cp. Saprikis and Vlachopoulou (2012), pp. 630–633.

Higher levels of complexity have been found to foster IOS integration (cp. Grover and Saeed (2007), pp. 203–209) and reduce the intention to use reverse auctions (cp. Mithas et al. (2008), pp. 712–717) or the performance and success of their use (cp. Schoenherr and Mabert (2008), pp. 89–90; Wagner and Schwab (2004), pp. 19–21). However, two studies do not find indications for an effect of complexity (cp. Pu et al. (2018), pp. 1700–1702; Wang and Archer (2004)).

Two studies find a positive effect of complexity on relational orientation (cp. Cannon and Perreault Jr (1999), pp. 449–454; Kaufmann and Carter (2006), pp. 664–667), while two other studies cannot find statistically significant effects of complexity (cp. Bello et al. (2003), pp. 9–10; Janz (2004), p. 300). In another study, the complexity of the procurement object has been found to affect social bonds in a survey with participants from the USA but not from Germany (cp. Kaufmann (2001), p. 358).

Schoenherr and Mabert (2011), p. 831.

Cp. Werner (1997), p. 70.

Cp. Stoll (2008), pp. 60–61; Kollmann (2019), pp. 188–189.

Cp. Janz (2004), p. 175.

Cp. Kaufmann (2001), p. 330.

Cp. Hartmann (2002b), p. 23.

Cp. Ellis et al. (2010), p. 38; Pfeffer and Salancik (2003), p. 46.

Products may vary in their importance because they can affect subsequent processes to different degrees (cp. Kaufmann (2001), pp. 330–332; Werner (1997), pp. 135–136). The same is true for transportation services.

Cp. Pfeffer and Salancik (2003), p. 45.

Sriram et al. (1992), p. 306.

Cp. Homburg (1995), p. 825.

Cp. Werner (1997), p. 163.

Products with a low profit impact and supply risk (non-critical items) should be purchased with a focus on low process costs, for example by using desktop purchasing systems. In contrast, for products with a high profit impact but low supply risk (leverage items) the aim should be to optimize purchasing prices. Market-oriented systems are therefore more suitable (cp. Arnold and Schnabel (2007), p. 87; Bogaschewsky (2002), p. 27; Kollmann (2019), p. 189; Luczak et al. (2002), p. 159; Tassabehji (2010), p. 434).

Within ABC analysis, products are classified according to some measure of financial importance (e.g. annual purchasing volume) into products with high (A products), medium (B products), or low importance (C products) (cp. Ivanov et al. (2019), p. 365).

Cp. Stoll (2008), pp. 60–61; Kortus-Schultes and Ferfer (2005), pp. 101–103.

Cp. Holzmüller and Schlüchter (2002), p. 9.

Cp. Garrido et al. (2011), pp. 60–64.

Importance is associated with the use of EMs for integration with suppliers (cp. Oppel (2003), pp. 239–240) or the use of private EMs (cp. Truong (2016), pp. 59–63). Moreover, importance has been found to have a negative effect on the use of electronic reverse auctions (cp. Schoenherr and Mabert (2011), pp. 838–839).

Cp. Cannon and Perreault Jr (1999), 494–454; Janz (2004), p. 299; Metcalf and Frear (1993), pp. 72–79; Werner (1997), p. 161.

Cp. Ellis et al. (2010), pp. 41–43; Homburg (1995), pp. 826–828.

Cp. Metcalf et al. (1992), pp. 37–38; Spekman and Strauss (1986), pp. 36–39; Kaufmann (2001), pp. 339–355.

Cannon and Perreault Jr (1999), p. 444.

In the literature, at least 4–5 suppliers are often recommended for conducting electronic auctions (cp. Carter et al. (2004), p. 245; Held (2003), p. 143; Hausladen (2020), p. 113). This is also a good recommendation for the procurement of transportation services via e-tendering or spot market functionalities on an ETM.

Cp. section  4.3.2.1.2 .

Pfeffer and Salancik (2003), p. 50.

Cp. Papenhoff (2009), p. 93; Picot and Dietl (1990), p. 179.

Cp. Bensaou and Anderson (1999), p. 462; Ganesan (1994), p. 6.

Bensaou and Anderson (1999), p. 468.

Kraljic (1983), p. 112.

Cp. Arnold and Schnabel (2007), pp. 86–87; Bogaschewsky (2002), pp. 26–28; Kollmann (2019), pp. 185–189; Luczak et al. (2002), pp. 160–161; Tassabehji (2010), p. 434.

Cp. Reuter (2013), p. 207.

Electronic reverse auctions are preferred when there are many suppliers which can compete (cp. Schoenherr and Mabert (2011), pp. 838–839; Smeltzer and Carr (2003), pp. 485–486). In addition, more relational forms of IOS use like integration or information sharing have been found to prevail when there are only a few suppliers available (cp. Grover and Saeed (2007), pp. 203–205; Hadaya and Pellerin (2010), pp. 376–378).

The lower the availability of alternatives, the higher the rationalism in buyer-supplier relationships (cp. Bello et al. (2003), pp. 9–10; Cannon and Perreault Jr (1999), pp. 449–454; Werner (1997), p. 161), the higher the commitment to the relationship (cp. Kim (2001), pp. 94–95; Norris and McNeilly (1995), pp. 76–77), and the stronger the collaboration (cp. Sriram et al. (1992), pp. 313–314).

Cp. Premkumar et al. (2005), p. 265.

These types are derived from demand uncertainty as a relevant variable in the EM context.

(cp. Choudhury (1997), p. 13; Son and Benbasat (2007), pp. 61–62.

Cp. Walker and Weber (1984), p. 376.

Cp. Son and Benbasat (2007), pp. 61–62.

Cp. Choudhury (1997), p. 13. The authors refer to frequency uncertainty with the term “technological uncertainty of demand”. Since it captures the meaning in a better way, the term “frequency uncertainty” is used within this thesis (as also done by Son and Benbasat (2007), pp. 61–62).

Cp. Küsters and Speckenbach (2012), p. 75.

Spare parts for cars or airplanes are good examples of products with a high frequency uncertainty, because there are many different parts and it is difficult to predict when a certain part will be needed for a repair job. In contrast, a low frequency of demand is given if a certain supply is needed on a regular, ongoing basis. For example, producers of cars or airplanes face much less frequency uncertainty in the production process because they know which parts are needed for producing a planned number of finished products (cp. Choudhury (1997), p. 13).

Environmental uncertainty makes it more difficult to establish contractual protections against risks. In addition, frequent adaptations of deadlines or quantities complicate the fulfillment of contractual terms and cause adaptation efforts (cp. Kiedaisch (1997), pp. 48–49; Picot et al. (2001), p. 53).

Transaction cost theory suggests that the frequency of transactions reduces the average transaction costs because the costs for establishing certain governance structures (e.g., long-term contracts) can be distributed over many transactions. In presence of frequent transactions (low frequency uncertainty), short-term market exchanges imply high transaction costs due to frequent search and negotiation costs which could be reduced by establishing long-term contracts (cp. Wang and Archer (2004)).

Cp. Stoll (2008), p. 61.

In one study, the demand uncertainty has been found to have a negative effect on the intention to adopt and the extent of use of EMs (cp. Son and Benbasat (2007), pp. 80–82). Other studies, however, could not find significant effects of demand uncertainty on the adoption or the extent of use of EMs (cp. Najmul Islam et al. (2020), pp. 13–16; Saprikis and Vlachopoulou (2012), pp. 630–633; Upadhyaya et al. (2017), pp. 61–63).

One study finds that demand uncertainty is positively associated with the use of spot markets (cp. Choudhury et al. (1998), pp. 484–493) and another study indicates that the contract market is feasible for services involving low demand uncertainty (cp. Janssen and Verbraeck (2008), p. 480). In contrast, another study finds that collaboration-oriented EM functionalities are preferred over market-oriented functionalities when companies face high transaction uncertainty (cp. Wang and Archer (2004)). Furthermore, two studies cannot find a significant effect of demand uncertainty on the extent of use of IOS for integration or the use of electronic information transfer (cp. Grover and Saeed (2007), pp. 203–205; Kim et al. (2006), pp. 308–311).

A case study research finds that demand uncertainty is positively associated with a need for close supply chain relationships (cp. Leeuw and Fransoo (2009), pp. 727–731). But another study finds an effect of demand uncertainty in the opposite direction: demand uncertainty (in terms of a low frequency of procurement) has a negative effect on the relational orientation within procurement relationships (cp. Werner (1997), p. 161). Another study could not find an effect of the demand uncertainty in terms of transaction frequency on the relational orientation within procurement (cp. Janz (2004), pp. 299–300).

Levi et al. (2003), p. 77.

The need for responsiveness and the exchange of information represent two of six dimensions of non-contractibility which are associated with low degrees of specifiability (cp. Mithas et al. (2008), p. 709).

Bakos and Brynjolfsson (1993), p. 44.

Cp. Beall et al. (2003), p. 15.

Several studies find that electronic reverse auctions are used when specifiability is high (cp. Hawkins et al. (2009), p. 63; Hawkins et al. (2010), pp. 24–27; Kaufmann and Carter (2004), pp. 17–24). Another study also finds that companies that value non-contractible factors (i.e. low specifiability) favor the use of collaboration-oriented functionalities (cp. Wang and Archer (2004)).

One study provides qualitative evidence that recurrent transactions between suppliers and buyers are motivated by investments into non-contractible attributes with a low specifiability (cp. Radkevitch (2008), p. 93). The other study finds that negotiated contracts are preferred over market-governance when transactions are less codifiable (cp. Levi et al. (2003), pp. 7–9).

The acceptance of an IS is a state which manifests itself in the adoption or rejection of an IS by a user and which may change over time (cp. Leimeister (2015), p. 224; Wilhelm (2012), p. 17).

For example, users may work against the implementation (cp. Brown et al. (2002), p. 284). Furthermore, employees can voluntarily engage in learning new functions and expand their use over time. Such an extended use of an IS may improve outcomes for firms (cp. Hsieh et al. (2011), pp. 2027–2031). However, such a voluntary use expansion is unlikely to happen if users do not accept an IS. Moreover, being forced to use an unaccepted IS can lead to a lack of job satisfaction and further problems like absenteeism and higher employee turnover (cp. Sørebø and Eikebrokk (2008), p. 2358).

Obviously, the identified criteria within the EM selection criteria can be interpreted as contextual variables which may guide the selection of an ETM. But criteria that are relevant for beginning a relationship with an ETM may also affect the commitment toward an ETM. For example, fee levels may be a selection criterion of ETMs. These, however, may change over time and an ETM with competitive fee levels at the time of selection may over time increase the fees so that ultimately the commitment to an ETM declines.

Cp. Leimeister (2015), p. 224.

Lee et al. (2003), p. 752.

Cp. King and He (2006), p. 751; Schepers and Wetzels (2007), p. 99.

According to TRA, the central determinant of a person’s behavior is his or her behavioral intention to perform this behavior. The behavioral intention itself is determined by the person’s attitude and subjective norm, whereby the latter refers to beliefs about the expectations of others related to the behavior (cp. Ajzen et al. (1980), pp. 53–59).

Davis et al. (1989), p. 985.

Ibid., p. 985.

Source: Davis et al. (1989), p. 985.

Cp. Venkatesh and Davis (2000).

Cp. Venkatesh and Bala (2008).

Cp. Venkatesh et al. (2003).

Cp. Venkatesh et al. (2012).

For a more detailed review of models related to TAM, cp. Ginner (2018), pp. 173–176.

A meta-analysis shows that the predicted relationships by the model are generally confirmed (cp. Petter et al. (2008), p. 258). Furthermore, its first presentation in the year 1992 is the single most cited article within IS research (cp. Lowry et al. (2007), p. 171).

Cp. DeLone and McLean (1992), p. 87.

Cp. DeLone and McLean (2003), p. 10. In comparison to the first version, the updated version includes “service quality” as an additional quality dimension. Another change is the inclusion of “intention to use” in addition to the dimension “use”. Furthermore, the dimensions “individual impact” and “organizational impact” are combined in the new dimension of “net benefits” in the updated version.

Source: DeLone and McLean (2003), p. 24.

For detailed definitions and explanations of the quality dimensions, cp. sections  4.3.3.2.1 – 4.3.3.2.3 .

This is similar to the distinction between product-/software-related and vendor-related criteria which is relevant in the context of software selection (cp. Abts and Mülder (2017), p. 530; Schütte and Vering (2011), p. 81).

Cp. Bächle and Lehmann (2010), p. 70; Brenner and Breuer (2001), pp. 152–153; Büyüközkan (2004), p. 141; Darkow (2003), p. 209; Deng and Molla (2008); Deng et al. (2019a), p. 5; Held (2003), p. 222; Richter and Nohr (2002), p. 110; Stockdale and Standing (2002), pp. 229–230, (2003), p. 351; Thitimajshima et al. (2015); Wirtz (2002), p. 200.

Cp. Bächle and Lehmann (2010), p. 70; Brenner and Breuer (2001), p. 153; Büyüközkan (2004), p. 141; Darkow (2003), p. 209; Deng and Molla (2008); Deng et al. (2019a), p. 3; Held (2003), p. 224; Kleineicken (2004), p. 105; Stockdale and Standing (2002), p. 230, (2003), p. 361.

Cp. Bächle and Lehmann (2010), p. 70; Held (2003), pp. 222–225; Richter and Nohr (2002), p. 114; Stockdale and Standing (2002), p. 230, (2003), p. 361; Thitimajshima et al. (2015).

To provide a valuable offering, EMs must possess knowledge of the traded products and services, industry knowledge or market expertise, sufficient know-how for providing consulting to the participants as well as technological competencies (cp. Allweyer (2002), p. 348; Büyüközkan (2004), p. 142; Deng and Molla (2008); Deng et al. (2019a), p. 4; Wirtz (2002), p. 200).

Cp. Deng et al. (2019a), p. 4; Richter and Nohr (2002), pp. 111–112; Stockdale and Standing (2002), p. 230, (2003), p. 361; Thitimajshima et al. (2015).

The ownership deals with the question of which party owns an EM (cp. Brenner and Breuer (2001), pp. 152–153; Kleineicken (2004), p. 105; Stockdale and Standing (2002), p. 227, (2003), p. 361).

Stockdale and Standing (2002), p. 227.

Cp. Bächle and Lehmann (2010), p. 70; Darkow (2003), p. 209.

Cp. Allweyer (2002), p. 348; Bächle and Lehmann (2010), p. 70; Brenner and Breuer (2001), p. 153; Deng and Molla (2008); Held (2003), p. 223.

Cp. Allweyer (2002), p. 348; Bächle and Lehmann (2010), p. 70; Brenner and Breuer (2001), p. 152; Darkow (2003), p. 209; Held (2003), p. 224; Richter and Nohr (2002), p. 115.

Cp. Bächle and Lehmann (2010), p. 70; Darkow (2003), p. 209; Richter and Nohr (2002), p. 114; Wirtz (2002), p. 200.

Cp. Bächle and Lehmann (2010), p. 70; Brenner and Breuer (2001), p. 152; Richter and Nohr (2002), pp. 115–116.

One study reports that an evaluation procedure involving the assessment of EMs with the use of 135 criteria has helped the case company Triaton (the IT-services company of the ThyssenKrupp AG) to develop a widely accepted and suitable support for their EM strategy (cp. Klueber et al. (2001), pp. 695–703). In another study, a content analysis of over 100 practitioner articles has been conducted to identify factors of the macro-environment, internal factors of the participating companies, and factors of the EMs which should be considered during the selection of EMs (cp. Stockdale and Standing (2002), pp. 221–234).

Cp. section  4.3.3.2.1 .

Cp. Table  4.5 . The fact that the criteria are frequently mentioned by researchers shows that the criteria are not subjectively considered to be important by only a few individuals.

It should be possible to objectively evaluate the selected criteria. For example, the number of participants is often advertised by ETMs, fee levels must be made transparent before any contract with an ETM operator will be signed and it should also be possible to gather information on the security measures. In contrast, it is much more difficult to objectively evaluate criteria such as the know-how of the ETM operator or the likelihood of ETM survival.

Different dependent variables are relevant for the relationship to ETMs. These include trust (cp. Chiu et al. (2009), p. 773; Kim and Ahn (2007), pp. 125–126; Koufaris and Hampton-Sosa (2004), pp. 386–388; McKnight et al. (2017), p. 132; Pavlou (2002), pp. 229–232; Pavlou and Gefen (2004), p. 50; Zhou et al. (2009), p. 331), loyalty (cp. Agag (2019), pp. 399–404; Thitimajshima et al. (2018), pp. 137–138), success factors for ongoing use (cp. Cullen and Taylor (2009), pp. 1172–1178) or the use of specific EMs (cp. Driedonks et al. (2005), pp. 57–64; Quaddus and Hofmeyer (2007), pp. 206–211; Tao et al. (2007), pp. 1060–1065).

Acceptance encompasses all indications on dependent variables which are relevant for the use of IS by individuals. Results of studies that investigate determinants of the use of e-procurement in an organizational context (e.g. Brandon-Jones and Kauppi (2018)) or a consumer context (e.g. Jones and Kim (2010)) will be reviewed. In addition, the results from previous studies on the satisfaction with EMs or websites for procurement will be considered due to their relevance for the acceptance (cp. Devaraj et al. (2002); Jones and Kim (2010); Lee and Lin (2005); Lin (2007); Zhou et al. (2009)).

Some empirical studies provide insights that are relevant for the success of ETMs. For example, one study provides insights on the performance impacts from the use of e-procurement (cp. Boyer and Olson (2002), pp. 490–493) and another study provides insights on the impacts resulting from the use of an EM (cp. Chien et al. (2012), pp. 465–466).

Cp. DeLone and McLean (1992), p. 62.

Cp. Gorla et al. (2010), p. 212.

Cp. Petter et al. (2008), p. 238.

Cp. DeLone and McLean (2003), p. 11.

In contrast to TAM, however, the DeLone and Mclean IS success model includes more aspects within system quality than just ease of use. For example, a measurement instrument including 40 items to measure system quality has been developed (cp. Rivard et al. (1997), pp. 44–58).

Cp. Bächle and Lehmann (2010), p. 70; Darkow (2003), p. 208; Richter and Nohr (2002), pp. 113–114; Wirtz (2002), p. 200.

System quality has a positive effect on the intention to use e-procurement via its effect on perceived usefulness (cp. Brandon-Jones and Kauppi (2018), p. 34). Furthermore, system quality has a positive effect on the use of electronic reverse auctions (cp. Adomavicius et al. (2013), p. 497), the evaluation of the effectiveness of a website used for purchasing (cp. Chakraborty et al. (2002), pp. 64–68), the customer satisfaction in online shopping (cp. Lee and Lin (2005), pp. 169–171; Lin (2007), pp. 371–373), and the satisfaction with EMs (cp. Kang (2014), pp. 457–460; Kollmann (2001a); Zahedi et al. (2010), pp. 310–312).

Cp. Boyer and Olson (2002), pp. 490–493.

Cp. Chien et al. (2012), pp. 465–466.

System quality is associated with higher levels of trust in EMs (cp. Kim and Ahn (2007), pp. 125–126; McKnight et al. (2017), p. 132) or websites used for purchasing (cp. Chiu et al. (2009), p. 773; Koufaris and Hampton-Sosa (2004), pp. 386–388). In addition, empirical studies show that system quality may also lead to the ongoing use of EMs (cp. Thitimajshima et al. (2018), pp. 137–138) or e-commerce systems (cp. Cullen and Taylor (2009), pp. 1172–1178).

Cp. Gorla et al. (2010), p. 213; Petter et al. (2008), p. 239.

DeLone and McLean (2003), p. 21.

It has been found that the higher the information quality of websites used for purchasing, the higher their perceived effectiveness or usefulness (cp. Chakraborty et al. (2002), pp. 64–68; Ramkumar et al. (2019), p. 340). In addition, information quality is positively associated with the intention to use a website for online apparel shopping (cp. Jones and Kim (2010), pp. 632–633) or the use of an e-procurement system within public organizations (cp. Kassim and Hussin (2013), pp. 10–13).

Information quality is perceived to be among the most important factors for the ongoing use of an e-commerce system in the pharmaceutical supply chain (cp. Cullen and Taylor (2009), pp. 1172–1178). However, another study did not find a significant effect of information quality on the loyalty of EM participants (cp. Thitimajshima et al. (2018), pp. 137–139).

Xu et al. (2013), p. 780.

Cp. Parasuraman et al. (1988), p. 25.

DeLone and McLean (2003), p. 18.

Service quality has a positive effect on the extent to which individuals use an e-procurement system (cp. Brandon‐Jones and Carey (2011), pp. 283–286). In addition, several studies show that consumers are more satisfied with websites that they use for purchasing activities when the service quality is evaluated to be higher (cp. Lee and Lin (2005), pp. 169–171; Lin (2007), pp. 371–373; Zhou et al. (2009), p. 331. Mixed results are provided by only one study, whereby only a single dimension (assurance) of the SERVQUAL dimensions has been found to have a significant positive effect on satisfaction (cp. Devaraj et al. (2002), pp. 324–327).

Service quality has a positive effect on the trust of consumers in websites which they are using for purchasing activities (cp. Chiu et al. (2009), pp. 771–773; Zhou et al. (2009), p. 331).

Cp. Büyüközkan (2004), p. 141; Deng and Molla (2008); Deng et al. (2019a), p. 4.

Cp. Wirtz (2002), p. 200.

The term critical mass denotes the number of participants of an EM that must be reached to ensure that the EM can operate effectively (cp. Stockdale and Standing (2003), p. 351).

There are several cases where network effects can arise. A classic example is the ownership of telephones: the more people own and use telephones, the more valuable telephones become to each owner (cp. Garcia and Resende (2011), p. 323; Katz and Shapiro (1994), p. 94).

Cp. Neumann et al. (2002), p. 70.

Cp. Büyüközkan (2004), p. 143; Wirtz and Mathieu (2002), p. 224.

Two studies find that larger numbers of sellers on EMs are associated with higher numbers of buyers which represents a so-called cross-side network (cp. Chu and Manchanda (2016), pp. 883–888; Hinz et al. (2020), pp. 28–32). In addition, there are some indications that market liquidity has a positive effect on the organizational adoption of EMs. Two qualitative studies notice that reaching a critical mass of users is important for successful adoption of EMs (cp. Driedonks et al. (2005), pp. 63–65) or ETMs (cp. Sänger (2004), p. 111). Furthermore, a survey study provides indications that the number of users has a positive effect on the intention to adopt EMs (cp. Quaddus and Hofmeyer (2007), pp. 208–211).

ETMs are used for the transmission of sensitive transaction information between buyers and sellers of transportation services. In addition, transactions may be conducted with potentially unknown trading partners. In such an environment, participants face various risks which can be reduced by proper security measures which are implemented by ETM operators.

Cp. Saeed and Leitch (2003), p. 168.

A survey study of buyers using a website for purchasing supplies in the construction industry shows that higher levels of perceived security are associated with a better overall evaluation of the goodness or badness of a website (cp. Chakraborty et al. (2002), pp. 64–68).

Security measures have a positive effect on trust in EM service providers (cp. Kim and Ahn (2007), pp. 125–126; Koufaris and Hampton-Sosa (2004), pp. 386–389) or on trust in the sellers which are active on an EM (cp. Pavlou (2002), pp. 229–232; Pavlou and Gefen (2004), p. 50). Furthermore, security measures have a positive effect on the intention to use an EM (cp. Shih et al. (2013), pp. 400–402) or the corresponding repurchase intention and loyalty (cp. Agag (2019), pp. 399–404).

Cp. Büyüközkan (2004), p. 143.

Cp. section  6.3.1 .

Cp. section  4.3.3.1.3 .

Two qualitative studies show that fees can act as barriers to the adoption of EMs when they are too high (cp. Johnson (2010), pp. 163–167; Johnson (2013), pp. 346–352). Similarly, another study finds that the fees of an EM determine the perceived relative advantage, which in turn drives the use of an EM (cp. Koch (2004), p. 2449). Only one study in the steel industry in China shows that paying fees is among the factors which are considered less important for the adoption of EMs (cp. Tao et al. (2007), p. 1064).

Sometimes the term firm performance is used as a synonym for organizational performance (cp. Schryen (2013), pp. 140–142).

Van De Ven, Andrew H. (1976), p. 73.

Cp. Dehning and Richardson (2002), p. 9.

Melville et al. (2004), p. 296.

Dehning and Richardson (2002), p. 9.

Cp. Barua et al. (1995), pp. 6–7; Krcmar (2015), p. 477; Laudon and Laudon (2014), p. 55.

Studies that do not investigate the effect of IT on intermediate business processes follow a “black box” approach (cp. Barua et al. (1995), p. 6; Pfeifer (2003), p. 57; Weitzendorf (2000), p. 17).

Cp. Bakos (1987), p. 5; Chan (2000), pp. 228–229; Dehning and Richardson (2002), pp. 9–10; Dedrick et al. (2003), pp. 3–4; Kohli and Grover (2008), p. 27; Krcmar (2015), p. 477; Laudon and Laudon (2014), p. 55; Masli et al. (2011), pp. 83–85; Melville et al. (2004), pp. 287–293; Schryen (2013), p. 142.

In the business context, metrics can be defined as a set of statistics used for measuring something, in particular how well a company is doing (cp. Deuter et al. (2015), p. 977).

One of the benefits of using metrics is that they quantify effects and compress selective information. In this way, they provide crucial support for managers (cp. Gladen (2014), p. 11). The use of performance metrics has been found to have a positive effect on firm success, e.g. when it comes to improvements of the quality of leadership or the agility of firms (cp. Sandt (2004), p. 201). In addition, metrics were ranked the second most important controlling tool in a study including 28 controlling tools (cp. Niedermayr (1994), p. 233).

Cp. Werner (2017), pp. 408–409.

Cp. Schönherr (2015), p. 58; Stephan (2006), pp. 33–35.

Cp. Pellens et al. (2000), p. 22.

There are also other metrics available for value-based management. Cash-Value-Added (CVA), for example, is another famous metric (cp. Gundel (2012), p. 2). EVA has been chosen because it is well-known and accepted. In addition, EVA is well-suited for measuring and managing the value of logistics and supply chain management (cp. Lambert and Burduroglu (2000); Schönherr (2015), p. 99; Wessely (2011), p. 25).

Cp. Franz and Winkler (2006), p. 418; Gundel (2012), p. 3; Müller and Hirsch (2005), p. 83.

Cp. Holler (2009), p. 56; Schönherr (2015), pp. 78–79.

Cp. Stephan (2006), p. 81.

Cp. Gundel (2012), pp. 16–17.

The objectives in procurement also contain intangible performance aspects (i.e., supply assurance, quality, and flexibility) and costs (cp. section  2.3.1 ).

Many researchers understand the success of logistics in terms of logistics efficiency (cp. Clausen and Rotmann (2014), p. 112; Dehler (2001), p. 207; Engelbrecht (2004), p. 218; Hausladen (2020), p. 7; Hofmann and Nothardt (2009), p. 95; Muchna et al. (2018), p. 42; Pfohl (2018), pp. 42–43; Schönherr (2015), pp. 44–45; Wannenwetsch (2014), p. 10; Wiendahl (2008), p. 248). Furthermore, the supply chain performance measures developed by SCOR also reflect the dimensions of logistics efficiency: these include customer-facing elements (i.e. reliability, flexibility, and responsiveness) which cover aspects of logistics performance and internal-facing aspects (i.e. costs and assets) which cover aspects of logistics costs (cp. Ayers (2006), p. 261; Lai et al. (2002), p. 442).

Cp. Engelbrecht (2004), pp. 218–219; Kestel (1995), p. 30.

Besides the above-mentioned two positive impacts on process costs and freight rates, the use of an ETM has also a negative impact on costs because usually fees must be paid. In the conceptual research framework, fees will be considered as a contextual variable (cp. section  4.3.3.2.6 ).

Cp. Kortus-Schultes and Ferfer (2005), p. 101.

For a more detailed explanation of the phases of market transactions, cp. Grieger (2003), pp. 289–290.

It has frequently been mentioned that search costs can be reduced by EMs (cp. Bakos (1991), p. 295; Dai and Kauffman (2002), p. 459 Galbreth et al. (2005), p. 297) or ETMs (cp. Gudmundsson and Walczuck (1999), p. 102; Lin et al. (2002), p. 1).

Cp. Le (2002), p. 115; Ordanini (2005), p. 101.

For a procedure that can be applied to calculate process cost reductions, cp. section  6.3.2.1.1 .

As a result of semi-structured interviews with experts from multiple firms using an EM in the mining industry, one study concludes that the greatest benefit of using an EM stems from the improvement of e-procurement processes (cp. Ash and Burn (2006), p. 14). In addition, a Delphi study found that experts assign higher importance to the improvement of business processes than to the reduction of prices (cp. Holzmüller and Schlüchter (2002), p. 9).

Cp. Alarcón et al. (2009), pp. 217–218.

Cp. Benslimane et al. (2005), p. 220; Kang et al. (2007), p. 114.

Cp. Ballou (2004), p. 190; Bowersox et al. (2002), p. 360.

Cp. Bakos (1991), pp. 298–299; Lichtenau (2005), p. 54; Voigt et al. (2003), pp. 136–137.

Cp. Cavinato (1990), p. 65. Further terms for empty movements of vehicles exist, e.g. empty trip (cp. Scott-Sabic (2005), p. 118).

Cp. Bretzke (2014), p. 368; Crainic et al. (2009), p. 550; Davies et al. (2007), p. 17; Gudmundsson and Walczuck (1999), p. 103; Hoffmann (2001), pp. 231–232; McKinnon et al. (2015), p. 325; Nissen (2001a), p. 50; Nissen (2001b), p. 601; Polzin and Lindemann (1999), p. 529; Seeßle (2019), 372.

For example, the movement of the truck from Hamburg to Leipzig can be needed because goods must be picked up in Leipzig or because the truck must be returned to a depot.

Besides avoiding deadheads, an ETM could also be used to fill a truck that is not yet fully loaded on a certain direct run with additional LTL or PTL shipments.

For example, the ETM offers a transport order for moving goods from Hannover to Leipzig. In this case, the truck only has to be moved empty from Hamburg to Hannover and the capacity will be fully used to move the goods from Hannover to Leipzig.

The marginal costs include the increased fuel costs for moving the goods, times for loading and unloading of goods, or any costs for detours that must be taken.

The mentioned scenarios are relevant for the procurement of transportation services on the spot market. However, similar benefits may also be relevant for the contract market. For example, a shipper might have the demand to move goods regularly from Germany to Italy. An ETM can help to match this shipper with a transportation service provider that needs to move goods from Italy to Germany. In this way, the transportation service provider does not need to move trucks empty on the return from Germany to Italy and a shipper may benefit from lower freight rates.

Source: own representation. This figure has been designed using resources from flaticon.com (cp. https://www.flaticon.com ).

Cp. Scott (2018), p. 12.

Cp. Brown and Goolsbee (2002), p. 481.

Cp. Morton et al. (2001), p. 501.

Cp. Alarcón et al. (2009), p. 218; Kang et al. (2007), pp. 114–115.

Cp. Garicano and Kaplan (2005), p. 108; Lee (1998), pp. 75–77. One of the reasons for higher prices which is mentioned in both studies is that the quality of cars sold via EMs might be higher compared to that of cars sold via traditional offline markets.

Indeed, the logistics literature exhibits a variety of different views on the relevant components of logistics performance, the meaning or definition of single components as well as the relation between them (cp. Dietel (1997), p. 137).

Besides external customers receiving transportation services within distribution logistics, shippers can also purchase transportation services for internal customers. Internal customers are departments that require internal goods movements (e.g., the procurement department which requires transportation services to move goods from suppliers to manufacturing plants).

Cp. Weber (2012), pp. 146–147.

Cp. Davies et al. (2007), p. 17; Georg (2006), p. 179; Le (2002), p. 114; Nissen (2001a), p. 50; Ordanini (2005), p. 101; Ordanini and Pol (2001), p. 280; Rask and Kragh (2004), p. 272; Standing and Standing (2015), p. 725.

Cp. Bowersox et al. (2002), p. 35; Engelbrecht (2004), p. 222; Hofmann and Nothardt (2009), p. 95; Zillig (2001), p. 122.

Cp. section  2.3.1 .

Cp. Schupp (2004), p. 124.

The flexibility of transportation service supply is closely related to delivery flexibility, which is relevant within the context of logistics. Delivery flexibility denotes the ability to fulfill special and often changing requirements of customers for the delivery of goods. These requirements can cover a wide range from order modalities to the required type of packaging (cp. Blum (2006), p. 72; Disselkamp and Schüller (2004), p. 138; Engelbrecht (2004), p. 222; Pfohl (2018), p. 40; Schönherr (2015), p. 47).

Cp. Doch (2009), p. 73.

Cp. Irlinger (2012), p. 15; Janker (2008), p. 18; Kollmann (2019), p. 171.

Sometimes authors use the term “delivery reliability” to refer to a similar concept defined as “delivery quality” within this work (cp. Dietel (1997), p. 151; Schneider and Hennig (2008), p. 216; ten Hompel and Heidenblut (2011), p. 183).

Cp. Doch (2009), p. 73; Slack and Lewis (2017), p. 56.

Cp. Disselkamp and Schüller (2004), p. 136; Doch (2009), p. 73.

Cp. Dietel (1997), p. 151; Muchna et al. (2018), p. 46.

Cp. Blum (2006), p. 72; Lödding (2016), p. 27; Pfohl (2018), p. 38; Muchna et al. (2018), p. 48.

Cp. Muchna et al. (2018), p. 46; Pfohl (2018), p. 40.

Cp. Mentzer et al. (2001), p. 85.

Cp. Dewan and Hsu (2004), p. 497.

For example, shippers can use social cues (e.g., body language) during a personal meeting to assess the honesty of transportation service providers. If, however, the contact between buyers and sellers is only virtual, the information which can be used to assess seller quality is more limited (cp. Ghose (2009), p. 264).

The use of EMs may involve shorter business relationships between buyers and sellers which can cause transportation service providers to reduce their care (cp. Polzin and Lindemann (1999), p. 529).

Cp. Sänger (2004), p. 118.

Janssen and Verbraeck (2008), p. 480.

Cp. Hausladen (2020), pp. 3–4.

Cp. Böttcher (1993), p. 229; Seeck (2010), p. 10.

Cp. section  3.5.2.2 .

Cp. Lambert and Burduroglu (2000), p. 13; Schönherr (2015), pp. 99–100.

Cp. Dehler (2001), p. 241; Engelbrecht (2004), p. 254; Gil Saura et al. (2008), p. 660; Innis and La Londe (1994), p. 19; Stank et al. (2003), p. 43; Vaidyanathan and Devaraj (2008), p. 418.

Cp. Cahill (2007), pp. 12–18.

Cp. Kalwani and Narayandas (1995), p. 9.

Cp. Matzler et al. (2009), p. 12. For a more extensive discussion of the impact of customer satisfaction on organizational performance, cp. Schönherr (2015), pp. 132–135.

Source: adapted from Lambert and Burduroglu (2000), p. 13.

This holds because stocks can be used to cover up various problems and uncertainties in business processes and thereby ensure, for example, a smooth production or timely delivery (cp. Wildemann (2010), p. 23).

A decline in logistics performance represented by a higher standard deviation results in higher stock levels and thereby increases working capital (cp. Song et al. (2010), p. 72; Talluri et al. (2004), p. 68).

Cp. Benbasat and Zmud (2003), p. 187; DeLone and McLean (2003), p. 24; Gable et al. (2008), p. 382.

Cp. Garrido et al. (2008), p. 624; Giunipero et al. (2012), p. 287; Karthik and Kumar (2013), p. 223; Kassim and Hussin (2013), p. 13; Mishra et al. (2013), p. 385; Quesada et al. (2010), pp. 525–526; Rai et al. (2009), p. 284; Ranganathan et al. (2011), p. 541; Shi and Liao (2015), p. 948; Yu et al. (2015), pp. 1065–1066.

Cp. Benslimane et al. (2005), p. 220; Kang et al. (2007), pp. 114–115.

For example, one study investigates the impact of coordination application use (e.g. sharing of inventory information) and transactional application use (e.g. search for suppliers) on efficiency gains due to e-procurement (cp. Wu et al. (2007), p. 583). Another study focuses on the use of an EM for the support of five different market phases and its impact on EM benefits (cp. Najmul Islam et al. (2020), p. 8).

For example, one study finds that relationship quality has a positive effect on purchasing process improvements and a negative effect on purchasing costs (cp. Sriram and Stump (2004), p. 49).

A study in the context of the purchasing of office supplies via the internet found that the quality of the website used for purchasing (e.g. in terms of ease of use or accuracy) has a positive effect on the improvements in terms of costs for customers (cp. Boyer and Olson (2002), pp. 490–493). In addition, a study of public EMs in Taiwan found that participants perceive that EMs enhance the competitiveness and efficiency for their organization to a higher extent when the ease of use of the EM is higher (cp. Chien et al. (2012), p. 466).

Diffusion of innovations theory postulates that the relative advantage, which is “[…] the degree to which an innovation is perceived as being better than the idea it supersedes […]” (Rogers (1983), p. 213), has a positive effect on the rate of adoption of an innovation.

Cp. Hassan et al. (2017), p. 315; Yao et al. (2007), pp. 889–892).

Cp. Grewal et al. (2001), 27–29; Molla and Deng (2009), pp. 25–26; Wang et al. (2006), pp. 342–346.

Cp. Alrubaiee et al. (2012), pp. 32–33; Le et al. (2004), pp. 302–304; Li et al. (2013); Mishra and Agarwal (2010), pp. 261–262; Najmul Islam et al. (2020), pp. 13–16; Rao et al. (2007), pp. 1041–1042.

Information asymmetries, diverging objectives among buyers and sellers, and the difficulties in enforcing agreements online are some of the reasons why (potential) participants of EMs perceive risks associated with the use of an EM (cp. Clemons et al. (1993), p. 15; Mishra and Agarwal (2010), p. 255).

Cp. Le et al. (2004), p. 299.

In two qualitative studies, risk perception has been identified as a relevant barrier to EM adoption (cp. Johnson (2010), p. 168, (2012), p. 523). Furthermore, a few quantitative studies provide indications for a negative effect of the perceived risks on system use in the context of EMs (cp. Hong (2015), pp. 330–332; Le et al. (2004), pp. 302–304; Mishra and Agarwal (2010), pp. 261–262; Rao et al. (2007), pp. 1041–1042).

One study finds a statistically significant positive relationship between the perceived value of the relationship to an EM and the willingness to continue the relationship to it (cp. Zahedi et al. (2010), p. 311). Another study cannot provide evidence for an effect of post-acquisition benefits on commitment, but it found indications for a relationship between the product prices on the EM and commitment (cp. Lancastre and Lages (2006), pp. 782–783).

It has been found that the perception of problems with sellers (psychological contract violations) in the past have a negative effect on the willingness to use an EM for purchasing activities (cp. Pavlou and Gefen (2005), pp. 389–391).

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Sylla, P. (2023). Conceptual Research Framework. In: Electronic Procurement of Transportation Services. Schriftenreihe der HHL Leipzig Graduate School of Management. Springer Gabler, Wiesbaden. https://doi.org/10.1007/978-3-658-40403-1_4

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Research Frameworks: Critical Components for Reporting Qualitative Health Care Research

Qualitative health care research can provide insights into health care practices that quantitative studies cannot. However, the potential of qualitative research to improve health care is undermined by reporting that does not explain or justify the research questions and design. The vital role of research frameworks for designing and conducting quality research is widely accepted, but despite many articles and books on the topic, confusion persists about what constitutes an adequate underpinning framework, what to call it, and how to use one. This editorial clarifies some of the terminology and reinforces why research frameworks are essential for good-quality reporting of all research, especially qualitative research.

Qualitative research provides valuable insights into health care interactions and decision-making processes – for example, why and how a clinician may ignore prevailing evidence and continue making clinical decisions the way they always have. 1 The perception of qualitative health care research has improved since a 2016 article by Greenhalgh et al. highlighted the higher contributions and citation rates of qualitative research than those of contemporaneous quantitative research. 2 The Greenhalgh et al. article was subsequently supported by an open letter from 76 senior academics spanning 11 countries to the editors of the British Medical Journal . 3 Despite greater recognition and acceptance, qualitative research continues to have an “uneasy relationship with theory,” 4 which contributes to poor reporting.

As an editor for the Journal of Patient-Centered Research and Reviews , as well as Human Resources for Health , I have seen several exemplary qualitative articles with clear and coherent reporting. On the other hand, I have often been concerned by a lack of rigorous reporting, which may reflect and reinforce the outdated perception of qualitative research as the “soft option.” 5 Qualitative research is more than conducting a few semi-structured interviews, transcribing the audio recordings verbatim, coding the transcripts, and developing and reporting themes, including a few quotes. Qualitative research that benefits health care is time-consuming and labor-intensive, requires robust design, and is rooted in theory, along with comprehensive reporting. 6

What Is “Theory”?

So fundamental is theory to qualitative research that I initially toyed with titling this editorial, “ Theory: the missing link in qualitative health care research articles ,” before deeming that focus too broad. As far back as 1967, Merton 6 warned that “the word theory threatens to become meaningless.” While it cannot be overstated that “atheoretical” studies lack the underlying logic that justifies researchers’ design choices, the word theory is so overused that it is difficult to understand what constitutes an adequate theoretical foundation and what to call it.

Theory, as used in the term theoretical foundation , refers to the existing body of knowledge. 7 , 8 The existing body of knowledge consists of more than formal theories , with their explanatory and predictive characteristics, so theory implies more than just theories . Box 1 9 – 12 defines the “building blocks of formal theories.” 9 Theorizing or theory-building starts with concepts at the most concrete, experiential level, becoming progressively more abstract until a higher-level theory is developed that explains the relationships between the building blocks. 9 Grand theories are broad, representing the most abstract level of theorizing. Middle-range and explanatory theories are progressively less abstract, more specific to particular phenomena or cases (middle-range) or variables (explanatory), and testable.

The Building Blocks of Formal Theories 9

The importance of research frameworks.

Researchers may draw on several elements to frame their research. Generally, a framework is regarded as “a set of ideas that you use when you are forming your decisions and judgements” 13 or “a system of rules, ideas, or beliefs that is used to plan or decide something.” 14 Research frameworks may consist of a single formal theory or part thereof, any combination of several theories or relevant constructs from different theories, models (as simplified representations of formal theories), concepts from the literature and researchers’ experiences.

Although Merriam 15 was of the view that every study has a framework, whether explicit or not, there are advantages to using an explicit framework. Research frameworks map “the territory being investigated,” 8 thus helping researchers to be explicit about what informed their research design, from developing research questions and choosing appropriate methods to data analysis and interpretation. Using a framework makes research findings more meaningful 12 and promotes generalizability by situating the study and interpreting data in more general terms than the study itself. 16

Theoretical and Conceptual Frameworks

The variation in how the terms theoretical and conceptual frameworks are used may be confusing. Some researchers refer to only theoretical frameworks 17 , 18 or conceptual frameworks, 19 – 21 while others use the terms interchangeably. 7 Other researchers distinguish between the two. For example, Miles, Huberman & Saldana 8 see theoretical frameworks as based on formal theories and conceptual frameworks derived inductively from locally relevant concepts and variables, although they may include theoretical aspects. Conversely, some researchers believe that theoretical frameworks include formal theories and concepts. 18 Others argue that any differences between the two types of frameworks are semantic and, instead, emphasize using a research framework to provide coherence across the research questions, methods and interpretation of the results, irrespective of what that framework is called.

Like Ravitch and Riggan, 22 I regard conceptual frameworks (CFs) as the broader term. Including researchers’ perspectives and experiences in CFs provides valuable sources of originality. Novel perspectives guard against research repeating what has already been stated. 23 The term theoretical framework (TF) may be appropriate where formal published and identifiable theories or parts of such theories are used. 24 However, existing formal theories alone may not provide the current state of relevant concepts essential to understanding the motivation for and logic underlying a study. Some researchers may argue that relevant concepts may be covered in the literature review, but what is the point of literature reviews and prior findings unless authors connect them to the research questions and design? Indeed, Sutton & Straw 25 exclude literature reviews and lists of prior findings as an adequate foundation for a study, along with individual lists of variables or constructs (even when the constructs are defined), predictions or hypotheses, and diagrams that do not propose relationships. One or more of these aspects could be used in a research framework (eg, in a TF), and the literature review could (and should) focus on the theories or parts of theories (constructs), offer some critique of the theory and point out how they intend to use the theory. This would be more meaningful than merely describing the theory as the “background” to the study, without explicitly stating why and how it is being used. Similarly, a CF may include a discussion of the theories being used (basically, a TF) and a literature review of the current understanding of any relevant concepts that are not regarded as formal theory.

It may be helpful for authors to specify whether they are using a theoretical or a conceptual framework, but more importantly, authors should make explicit how they constructed and used their research framework. Some studies start with research frameworks of one type and end up with another type, 8 , 22 underscoring the need for authors to clarify the type of framework used and how it informed their research. Accepting the sheer complexity surrounding research frameworks and lamenting the difficulty of reducing the confusion around these terms, Box 2 26 – 31 and Box 3 offer examples highlighting the fundamental elements of theoretical and conceptual frameworks while acknowledging that they share a common purpose.

Examples of How Theoretical Frameworks May Be Used

Examples of how conceptual frameworks may be used, misconceptions about qualitative research.

Qualitative research’s “uneasy relationship with theory” 4 may be due to several misconceptions. One possible misconception is that qualitative research aims to build theory and thus does not need theoretical grounding. The reality is that all qualitative research methods, not just Grounded Theory studies focused on theory building, may lead to theory construction. 16 Similarly, all types of qualitative research, including Grounded Theory studies, should be guided by research frameworks. 16

Not using a research framework may also be due to misconceptions that qualitative research aims to understand people’s perspectives and experiences without examining them from a particular theoretical perspective or that theoretical foundations may influence researchers’ interpretations of participants’ meanings. In fact, in the same way that participants’ meanings vary, qualitative researchers’ interpretations (as opposed to descriptions) of participants’ meaning-making will differ. 32 , 33 Research frameworks thus provide a frame of reference for “making sense of the data.” 34

Studies informed by well-defined research frameworks can make a world of difference in alleviating misconceptions. Good qualitative reporting requires research frameworks that make explicit the combination of relevant theories, theoretical constructs and concepts that will permeate every aspect of the research. Irrespective of the term used, research frameworks are critical components of reporting not only qualitative but also all types of research.

Acknowledgments

In memory of Martie Sanders: supervisor, mentor, and colleague. My deepest gratitude for your unfailing support and guidance. I feel your loss.

Conflicts of Interest: None.

Research Writing and Analysis

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• Step 1: Seek Out Evidence
• Step 2: Explain
• Step 3: The Big Picture
• Step 4: Own It
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Defining The Conceptual Framework

What is it.

• The researcher’s understanding/hypothesis/exploration of either an existing framework/model or how existing concepts come together to inform a particular problem. Shows the reader how different elements come together to facilitate research and a clear understanding of results.
• Informs the research questions/methodology (problem statement drives framework drives RQs drives methodology)
• A tool (linked concepts) to help facilitate the understanding of the relationship among concepts or variables in relation to the real-world. Each concept is linked to frame the project in question.
• Falls inside of a larger theoretical framework (theoretical framework = explains the why and how of a particular phenomenon within a particular body of literature).
• Can be a graphic or a narrative – but should always be explained and cited
• Can be made up of theories and concepts

What does it do?

• Explains or predicts the way key concepts/variables will come together to inform the problem/phenomenon
• Gives the study direction/parameters
• Helps the researcher organize ideas and clarify concepts
• Introduces your research and how it will advance your field of practice. A conceptual framework should include concepts applicable to the field of study. These can be in the field or neighboring fields – as long as important details are captured and the framework is relevant to the problem. (alignment)

What should be in it?

• Variables, concepts, theories, and/or parts of other existing frameworks

Making a Conceptual Framework

How to make a conceptual framework.

• With a topic in mind, go to the body of literature and start identifying the key concepts used by other studies. Figure out what’s been done by other researchers, and what needs to be done (either find a specific call to action outlined in the literature or make sure your proposed problem has yet to be studied in your specific setting). Use what you find needs to be done to either support a pre-identified problem or craft a general problem for study. Only rely on scholarly sources for this part of your research.
• Begin to pull out variables, concepts, theories, and existing frameworks explained in the relevant literature.
• If you’re building a framework, start thinking about how some of those variables, concepts, theories, and facets of existing frameworks come together to shape your problem. The problem could be a situational condition that requires a scholar-practitioner approach, the result of a practical need, or an opportunity to further an applicational study, project, or research. Remember, if the answer to your specific problem exists, you don’t need to conduct the study.
• The actionable research you’d like to conduct will help shape what you include in your framework. Sketch the flow of your Applied Doctoral Project from start to finish and decide which variables are truly the best fit for your research.
• Create a graphic representation of your framework (this part is optional, but often helps readers understand the flow of your research) Even if you do a graphic, first write out how the variables could influence your Applied Doctoral Project and introduce your methodology. Remember to use APA formatting in separating the sections of your framework to create a clear understanding of the framework for your reader.
• As you move through your study, you may need to revise your framework.
• Note for qualitative/quantitative research: If doing qualitative, make sure your framework doesn’t include arrow lines, which could imply causal or correlational linkages.

Conceptual Framework for DMFT Students

• Conceptural and Theoretical Framework for DMFT Students This document is specific to DMFT students working on a conceptual or theoretical framework for their applied project.

Conceptual Framework Guide

• Conceptual Framework Guide Use this guide to determine the guiding framework for your applied dissertation research.

Example Frameworks

Let’s say I’ve just taken a job as manager of a failing restaurant. Throughout first week, I notice the few customers they have are leaving unsatisfied. I need to figure out why and turn the establishment into a thriving restaurant. I get permission from the owner to do a study to figure out exactly what we need to do to raise levels of customer satisfaction. Since I have a specific problem and want to make sure my research produces valid results, I go to the literature to find out what others are finding about customer satisfaction in the food service industry. This particular restaurant is vegan focused – and my search of the literature doesn’t say anything specific about how to increase customer service in a vegan atmosphere, so I know this research needs to be done.

I find out there are different types of satisfaction across other genres of the food service industry, and the one I’m interested in is cumulative customer satisfaction. I then decide based on what I’m seeing in the literature that my definition of customer satisfaction is the way perception, evaluation, and psychological reaction to perception and evaluation of both tangible and intangible elements of the dining experience come together to inform customer expectations. Essentially, customer expectations inform customer satisfaction.

I then find across the literature many variables could be significant in determining customer satisfaction. Because the following keep appearing, they are the ones I choose to include in my framework: price, service, branding (branched out to include physical environment and promotion), and taste. I also learn by reading the literature, satisfaction can vary between genders – so I want to make sure to also collect demographic information in my survey. Gender, age, profession, and number of children are a few demographic variables I understand would be helpful to include based on my extensive literature review.

Note: this is a quantitative study. I’m including all variables in this study, and the variables I am testing are my independent variables. Here I’m working to see how each of the independent variables influences (or not) my dependent variable, customer satisfaction. If you are interested in qualitative study, read on for an example of how to make the same framework qualitative in nature.

Also note: when you create your framework, you’ll need to cite each facet of your framework. Tell the reader where you got everything you’re including. Not only is it in compliance with APA formatting, but also it raises your credibility as a researcher. Once you’ve built the narrative around your framework, you may also want to create a visual for your reader.

See below for one example of how to illustrate your framework:

If you’re interested in a qualitative study, be sure to omit arrows and other notations inferring statistical analysis. The only time it would be inappropriate to include a framework in qualitative study is in a grounded theory study, which is not something you’ll do in an applied doctoral study.

A visual example of a qualitative framework is below:

Additional Framework Resources

Some additional helpful resources in constructing a conceptual framework for study:.

• Problem Statement, Conceptual Framework, and Research Question. McGaghie, W. C.; Bordage, G.; and J. A. Shea (2001). Problem Statement, Conceptual Framework, and Research Question. Retrieved on January 5, 2015 from http://goo.gl/qLIUFg
• Building a Conceptual Framework: Philosophy, Definitions, and Procedure
• https://www.scribbr.com/dissertation/conceptual-framework/
• https://www.projectguru.in/developing-conceptual-framework-in-a-research-paper/

Conceptual Framework Research

A conceptual framework is a synthetization of interrelated components and variables which help in solving a real-world problem. It is the final lens used for viewing the deductive resolution of an identified issue (Imenda, 2014). The development of a conceptual framework begins with a deductive assumption that a problem exists, and the application of processes, procedures, functional approach, models, or theory may be used for problem resolution (Zackoff et al., 2019). The application of theory in traditional theoretical research is to understand, explain, and predict phenomena (Swanson, 2013). In applied research the application of theory in problem solving focuses on how theory in conjunction with practice (applied action) and procedures (functional approach) frames vision, thinking, and action towards problem resolution. The inclusion of theory in a conceptual framework is not focused on validation or devaluation of applied theories. A concise way of viewing the conceptual framework is a list of understood fact-based conditions that presents the researcher’s prescribed thinking for solving the identified problem. These conditions provide a methodological rationale of interrelated ideas and approaches for beginning, executing, and defining the outcome of problem resolution efforts (Leshem & Trafford, 2007).

The term conceptual framework and theoretical framework are often and erroneously used interchangeably (Grant & Osanloo, 2014). Just as with traditional research, a theory does not or cannot be expected to explain all phenomenal conditions, a conceptual framework is not a random identification of disparate ideas meant to incase a problem. Instead it is a means of identifying and constructing for the researcher and reader alike an epistemological mindset and a functional worldview approach to the identified problem.

Grant, C., & Osanloo, A. (2014). Understanding, Selecting, and Integrating a Theoretical Framework in Dissertation Research: Creating the Blueprint for Your “House. ” Administrative Issues Journal: Connecting Education, Practice, and Research, 4(2), 12–26

Imenda, S. (2014). Is There a Conceptual Difference between Theoretical and Conceptual Frameworks? Sosyal Bilimler Dergisi/Journal of Social Sciences, 38(2), 185.

Leshem, S., & Trafford, V. (2007). Overlooking the conceptual framework. Innovations in Education & Teaching International, 44(1), 93–105. https://doi-org.proxy1.ncu.edu/10.1080/14703290601081407

Swanson, R. (2013). Theory building in applied disciplines . San Francisco: Berrett-Koehler Publishers.

Zackoff, M. W., Real, F. J., Klein, M. D., Abramson, E. L., Li, S.-T. T., & Gusic, M. E. (2019). Enhancing Educational Scholarship Through Conceptual Frameworks: A Challenge and Roadmap for Medical Educators . Academic Pediatrics, 19(2), 135–141. https://doi-org.proxy1.ncu.edu/10.1016/j.acap.2018.08.003

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Saunders’ Research Onion: Explained Simply

Peeling the onion, layer by layer (with examples).

By: David Phair (PhD) and Kerryn Warren (PhD) | January 2021

If you’re learning about research skills and methodologies, you may have heard the term “ research onion ”. Specifically, the research onion developed by Saunders et al in 2007 . But what exactly is this elusive onion? In this post, we’ll break Saunders’ research onion down into bite-sized chunks to make it a little more digestible.

Saunders’ (2007) Research Onion – What is it?

At the simplest level, Saunders’ research onion describes the different decisions you’ll need to make when developing a  research methodology   – whether that’s for your dissertation, thesis or any other formal research project. As you work from the outside of the onion inwards , you’ll face a range of choices that progress from high-level and philosophical to tactical and practical in nature. This also mimics the general structure for the methodology chapter .

While Saunders’ research onion is certainly not perfect, it’s a useful tool for thinking holistically about methodology. At a minimum, it helps you understand what decisions you need to make in terms of your research design and methodology.

The layers of Saunders’ research onion

The onion is made up of 6 layers, which you’ll need to peel back one at a time as you develop your research methodology:

• Research philosophy
• Research approach
• Research strategy
• Time horizon
• Techniques & procedures

Onion Layer 1: Research Philosophy

The very first layer of the onion is the research philosophy . But what does that mean? Well, the research philosophy is the foundation of any study as it describes the set of beliefs the research is built upon . Research philosophy can be described from either an  ontological  or  epistemological  point of view. “A what?!”, you ask?

In simple terms,  ontology  is the “what” and “how” of what we know – in other words, what is the nature of reality and what are we really able to know and understand. For example, does reality exist as a single objective thing, or is it different for each person? Think about the simulated reality in the film The Matrix.

Epistemology , on the other hand, is about “how” we can obtain knowledge and come to understand things – in other words, how can we figure out what reality is, and what the limits of this knowledge are. This is a gross oversimplification, but it’s a useful starting point (we’ll cover ontology and epistemology another post).

With that fluffy stuff out the way, let’s look at three of the main research philosophies that operate on different ontological and epistemological assumptions:

• Interpretivism

These certainly aren’t the only research philosophies, but they are very common and provide a good starting point for understanding the spectrum of philosophies.

Research Philosophy 1:  Positivism

Positivist research takes the view that knowledge exists outside of what’s being studied . In other words, what is being studied can only be done so objectively , and it cannot include opinions or personal viewpoints – the researcher doesn’t interpret, they only observe. Positivism states that there is only one reality  and that all meaning is consistent between subjects.

In the positivist’s view, knowledge can only be acquired through empirical research , which is based on measurement and observation. In other words, all knowledge is viewed as a posteriori knowledge – knowledge that is not reliant on human reasoning but instead is gained from research.

For the positivist, knowledge can only be true, false, or meaningless . Basically, if something is not found to be true or false, it no longer holds any ground and is thus dismissed.

Let’s look at an example, based on the question of whether God exists or not. Since positivism takes the stance that knowledge has to be empirically vigorous, the knowledge of whether God exists or not is irrelevant. This topic cannot be proven to be true or false, and thus this knowledge is seen as meaningless.

Kinda harsh, right? Well, that’s the one end of the spectrum – let’s look at the other end.

Research Philosophy 2: Interpretivism

On the other side of the spectrum, interpretivism emphasises the influence that social and cultural factors can have on an individual. This view focuses on  people’s thoughts and ideas , in light of the socio-cultural backdrop. With the interpretivist philosophy, the researcher plays an active role in the study, as it’s necessary to draw a holistic view of the participant and their actions, thoughts and meanings.

Let’s look at an example. If you were studying psychology, you may make use of a case study in your research which investigates an individual with a proposed diagnosis of schizophrenia. The interpretivist view would come into play here as social and cultural factors may influence the outcome of this diagnosis.

Through your research, you may find that the individual originates from India, where schizophrenic symptoms like hallucinations are viewed positively, as they are thought to indicate that the person is a spirit medium. This example illustrates an interpretivist approach since you, as a researcher, would make use of the patient’s point of view, as well as your own interpretation when assessing the case study.

Research Philosophy 3: Pragmatism

Pragmatism highlights the importance of using the best tools possible to investigate phenomena. The main aim of pragmatism is to approach research from a practical point of view , where knowledge is not fixed, but instead is constantly questioned and interpreted. For this reason, pragmatism consists of an element of researcher involvement and subjectivity, specifically when drawing conclusions based on participants’ responses and decisions. In other words, pragmatism is not committed to (or limited by) one specific philosophy.

Let’s look at an example in the form of the trolley problem, which is a set of ethical and psychological thought experiments. In these, participants have to decide on either killing one person to save multiple people or allowing multiple people to die to avoid killing one person. 

This experiment can be altered, including details such as the one person or the group of people being family members or loved ones. The fact that the experiment can be altered to suit the researcher’s needs is an example of pragmatism – in other words, the outcome of the person doing the thought experiment is more important than the philosophical ideas behind the experiment.

To recap, research philosophy is the foundation of any research project and reflects the ontological and epistemological assumptions of the researcher. So, when you’re designing your research methodology , the first thing you need to think about is which philosophy you’ll adopt, given the nature of your research.

Onion Layer 2: Research Approach

Let’s peel off another layer and take a look at the research approach . Your research approach is the broader method you’ll use for your research –  inductive  or  deductive . It’s important to clearly identify your research approach as it will inform the decisions you take in terms of data collection and analysis in your study (we’ll get to that layer soon).

Inductive approaches entail generating theories from research , rather than starting a project with a theory as a foundation.  Deductive approaches, on the other hand, begin with a theory and aim to build on it (or test it) through research.

Sounds a bit fluffy? Let’s look at two examples:

An  inductive approach  could be used in the study of an otherwise unknown isolated community. There is very little knowledge about this community, and therefore, research would have to be conducted to gain information on the community, thus leading to the formation of theories.

On the other hand, a  deductive approach  would be taken when investigating changes in the physical properties of animals over time, as this would likely be rooted in the theory of evolution. In other words, the starting point is a well-established pre-existing body of research.

Closely linked to research approaches are  qualitative and  quantitative  research. Simply put, qualitative research focuses on textual , visual or audio-based data, while quantitative research focuses on numerical data. To learn more about qualitative and quantitative research, check out our dedicated post here .

What’s the relevance of qualitative and quantitative data to research approaches? Well, inductive approaches are usually used within qualitative research, while quantitative research tends to reflect a deductive approach, usually informed by positivist philosophy. The reason for using a deductive approach here is that quantitative research typically begins with theory as a foundation, where progress is made through hypothesis testing. In other words, a wider theory is applied to a particular context, event, or observation to see whether these fit in with the theory, as with our example of evolution above.

So, to recap, the two research approaches are  inductive  and  deductive . To decide on the right approach for your study, you need to assess the type of research you aim to conduct. Ask yourself whether your research will build on something that exists, or whether you’ll be investigating something that cannot necessarily be rooted in previous research. The former suggests a deductive approach while the latter suggests an inductive approach.

Need a helping hand?

Onion Layer 3: Research Strategy

So far, we’ve looked at pretty conceptual and intangible aspects of the onion. Now, it’s time to peel another layer off that onion and get a little more practical – introducing research strategy . This layer of the research onion details how, based on the aims of the study, research can be conducted. Note that outside of the onion, these strategies are referred to as research designs.

There are several strategies  you can take, so let’s have a look at some of them.

• Experimental research
• Action research
• Case study research
• Grounded theory
• Ethnography
• Archival research

Strategy 1: Experimental research

Experimental research involves manipulating one variable (the independent variable ) to observe a change in another variable (the dependent variable ) – in other words, to assess the relationship between variables. The purpose of experimental research is to support, refute or validate a  research hypothesis . This research strategy follows the principles of the  scientific method  and is conducted within a controlled environment or setting (for example, a laboratory).

Experimental research aims to test existing theories rather than create new ones, and as such, is deductive in nature. Experimental research aligns with the positivist research philosophy, as it assumes that knowledge can only be studied objectively and in isolation from external factors such as context or culture.

Let’s look at an example of experimental research. If you had a hypothesis that a certain brand of dog food can raise a dogs’ protein levels, you could make use of experimental research to compare the effects of the specific brand to a “regular” diet. In other words, you could test your hypothesis.

In this example, you would have two groups, where one group consists of dogs with no changes to their diet (this is called  the control group) and the other group consists of dogs being fed the specific brand that you aim to investigate (this is called the experimental/treatment group). You would then test your hypothesis by comparing the protein levels in both groups.

Strategy 2: Action research

Next, we have action research . The simplest way of describing action research is by saying that it involves learning through… wait for it… action. Action research is conducted in practical settings such as a classroom, a hospital, a workspace, etc – as opposed to controlled environments like a lab. Action research helps to inform researchers of problems or weaknesses related to interactions within the real-world . With action research, there’s a strong focus on the participants (the people involved in the issue being studied, which is why it’s sometimes referred to as “participant action research” or PAR.

An example of PAR is a community intervention (for therapy, farming, education, whatever). The researcher comes with an idea and it is implemented with the help of the community (i.e. the participants). The findings are then discussed with the community to see how to better the intervention. The process is repeated until the intervention works just right for the community. In this way, a practical solution is given to a problem and it is generated by the combination of researcher and community (participant) feedback.

This kind of research is generally applied in the social sciences , specifically in professions where individuals aim to improve on themselves and the work that they are doing. Action research is most commonly adopted in qualitative studies and is rarely seen in quantitative studies. This is because, as you can see in the above examples, action research makes use of language and interactions rather than statistics and numbers.

Strategy 3: Case study research

A case study is a detailed, in-depth study of a single subject – for example, a person, a group or an institution, or an event, phenomenon or issue. In this type of research, the subject is analysed to gain an in-depth understanding of issues in a real-life setting. The objective here is to gain an in-depth understanding within the context of the study – not (necessarily) to generalise the findings.

It is vital that, when conducting case study research, you take the social context and culture into account, which means that this type of research is (more often than not) qualitative in nature and tends to be inductive. Also, since the researcher’s assumptions and understanding play a role in case study research, it is typically informed by an interpretivist philosophy.

For example, a study on political views of a specific group of people needs to take into account the current political situation within a country and factors that could contribute towards participants taking a certain view.

Strategy 4: Grounded theory

Next up, grounded theory. Grounded theory is all about “letting the data speak for itself”. In other words, in grounded theory, you let the data inform the development of a new theory, model or framework. True to the name, the theory you develop is “ grounded ” in the data. Ground theory is therefore very useful for research into issues that are completely new or under-researched.

Grounded theory research is typically qualitative (although it can also use quantitative data) and takes an inductive approach. Typically, this form of research involves identifying commonalities between sets of data, and results are then drawn from completed research without the aim of fitting the findings in with a pre-existing theory or framework.

For example, if you were to study the mythology of an unknown culture through artefacts, you’d enter your research without any hypotheses or theories, and rather work from the knowledge you gain from your study to develop these.

Strategy 5: Ethnography

Ethnography involves observing people in their natural environments and drawing meaning from their cultural interactions. The objective with ethnography is to capture the subjective experiences of participants, to see the world through their eyes. Creswell (2013) says it best: “Ethnographers study the meaning of the behaviour, the language, and the interaction among members of the culture-sharing group.”

For example, if you were interested in studying interactions on a mental health discussion board, you could use ethnography to analyse interactions and draw an understanding of the participants’ subjective experiences.

For example, if you wanted to explore the behaviour, language, and beliefs of an isolated Amazonian tribe, ethnography could allow you to develop a complex, complete description of the social behaviours of the group by immersing yourself into the community, rather than just observing from the outside.  

Given the nature of ethnography, it generally reflects an interpretivist research philosophy and involves an inductive , qualitative research approach. However, there are exceptions to this – for example, quantitative ethnography as proposed by David Shafer.

Strategy 6: Archival research

Last but not least is archival research. An archival research strategy draws from materials that already exist, and meaning is then established through a review of this existing data. This method is particularly well-suited to historical research and can make use of materials such as manuscripts and records.

For example, if you were interested in people’s beliefs about so-called supernatural phenomena in the medieval period, you could consult manuscripts and records from the time, and use those as your core data set.

Onion Layer 4: Choices

The next layer of the research onion is simply called “choices” – they could have been a little more specific, right? In any case, this layer is simply about deciding how many data types (qualitative or quantitative) you’ll use in your research. There are three options – mono , mixed , and multi-method .

Let’s take a look at them.

Choosing to use a  mono method  means that you’ll only make use of one data type – either qualitative or quantitative. For example, if you were to conduct a study investigating a community’s opinions on a specific pizza restaurant, you could make use of a qualitative approach only, so that you can analyse participants’ views and opinions of the restaurant.

If you were to make use of both quantitative and qualitative data, you’d be taking a  mixed-methods approach. Keeping with the previous example, you may also want to assess how many people in a community eat specific types of pizza. For this, you could make use of a survey to collect quantitative data and then analyse the results statistically, producing quantitative results in addition to your qualitative ones.

Lastly, there’s  multi-method . With a multi-method approach, you’d make use of a wider range of approaches, with more than just a one quantitative and one qualitative approach. For example, if you conduct a study looking at archives from a specific culture, you could make use of two qualitative methods (such as thematic analysis and content analysis ), and then additionally make use of quantitative methods to analyse numerical data.

As with all the layers of the research onion, the right choice here depends on the nature of your research, as well as your research aims and objectives . There’s also the practical consideration of viability – in other words, what kind of data will you be able to access, given your constraints.

Onion Layer 5: Time horizon

What’s that far in the distance? It’s the time horizon. But what exactly is it? Thankfully, this one’s pretty straightforward. The time horizon simply describes how many points in time you plan to collect your data at . Two options exist – the  cross-sectional  and  longitudinal  time horizon.

Imagine that you’re wasting time on social media and think, “Ooh! I want to study the language of memes and how this language evolves over time”. For this study, you’d need to collect data over multiple points in time – perhaps over a few weeks, months, or even years. Therefore, you’d make use of a  longitudinal time horizon. This option is highly beneficial when studying changes and progressions over time.

If instead, you wanted to study the language used in memes at a certain point in time (for example, in 2020), you’d make use of a  cross-sectional  time horizon. This is where data is collected at one point in time, so you wouldn’t be gathering data to see how language changes, but rather what language exists at a snapshot point in time. The type of data collected could be qualitative, quantitative or a mix of both, as the focus is on the time of collection, not the data type.

As with all the other choices, the nature of your research and your research aims and objectives are the key determining factors when deciding on the time horizon. You’ll also need to consider practical constraints , such as the amount of time you have available to complete your research (especially in the case of a dissertation or thesis).

Onion Layer 6: Techniques and Procedures

Finally, we reach the centre of the onion – this is where you get down to the real practicalities of your research to make choices regarding specific techniques and procedures .

Specifically, this is where you’ll:

• Decide on what data you’ll collect and what data collection methods you’ll use (for example, will you use a survey? Or perhaps one-on-one interviews?)
• Decide how you’ll go about sampling the population (for example, snowball sampling, random sampling, convenience sampling, etc).
• Determine the type of data analysis you’ll use to answer your research questions (such as content analysis or a statistical analysis like correlation).
• Set up the materials you’ll be using for your study (such as writing up questions for a survey or interview)

What’s important to note here is that these techniques and procedures need to align with all the other layers of the research onion – i.e., research philosophy, research approaches, research strategy, choices, and time horizon.

For example, you if you’re adopting a deductive, quantitative research approach, it’s unlikely that you’ll use interviews to collect your data, as you’ll want high-volume, numerical data (which surveys are far better suited to). So, you need to ensure that the decisions at each layer of your onion align with the rest, and most importantly, that they align with your research aims and objectives.

Let’s Recap: Research Onion 101

The research onion details the many interrelated choices you’ll need to make when you’re crafting your research methodology. These include:

• Research philosophy – the set of beliefs your research is based on (positivism, interpretivism, pragmatism)
• Research approaches – the broader method you’ll use (inductive, deductive, qualitative and quantitative)
• Research strategies – how you’ll conduct the research (e.g., experimental, action, case study, etc.)
• Choices – how many methods you’ll use (mono method, mixed-method or multi-method)
• Time horizons – the number of points in time at which you’ll collect your data (cross-sectional or longitudinal)
• Techniques and procedures (data collection methods, data analysis techniques, sampling strategies, etc.)

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60 Comments

This is good

Wow this was sooo helpful. I don’t feel so blank about my research anymore. With this information I can conquer my research. Going ‘write’ into it. Get it write not right hahahaha

I am doing research with Bolton University so i would like to empower myself.

Really thoughtful presentation and preparation. I learnt too much to teach my students in a very simple and understandable way

Very useful, thank you.

You’re most welcome. Good luck with your research!

thanks alot for your brief and brilliant notes

I am a Student at Malawi Institute of Management, pursuing a Masters’ degree in Business Administration. I find this to be very helpful

Extremely useful, well explained. Thank you so much

I would like to download this file… I can’t find the attachment file. Thanks

Thank you so much for explaining it in the most simple and precise manner!

Very thoughtful and well expained, thanks.

This is good for upgrade my research knowledge

I have enjoying your videos on YouTube, they are very educative and useful. I have learned a lot. Thanks

Thank you this has really helped me with writing my dissertation methodology !

Thanks so much for this piece. Just to be clear, which layer do interviews fit in?

well explained i found it to be very engaging. now i’m going to pass my research methods course. thank you.

Thank you so much this has really helped as I can’t get this insight from uni due to covid

well explained with more clarity!

this is an excellent piece i find it super helpful

Beautiful, thank you!

Beautiful and helpful. Thank you!

This is well done!

A complex but useful approach to research simplified! I would like to learn more from the team.

A very simplified version of a complex topic. I found it really helpful. I would like to know if this publication can be cited for academic research. Thank you

You’re welcome to cite this page, but it would be better to cite the original work of Saunders.

Thirteen odd years since my MSc in HRM & HRD at UoL. I’d like to say thank you for the effort to produce such an insightful discussion of a rather complex topic.

I am a PhD in Media Studies student. I found this enormously helpful when stringing together the methodology chapter, especially the research philosophy section.

Hello there. Thank you for summarising the work on the onion. A more recent version of the onion (Saunders et al., 2019) refers to ‘methodological choices’ rather than choices. This can be downloaded, along with the chapter dealing with research philosophies at: https://www.researchgate.net/publication/330760964_Research_Methods_for_Business_Students_Chapter_4_Understanding_research_philosophy_and_approaches_to_theory_development or https://www.academia.edu/42304065/Research_Methods_for_Business_Students_Chapter_4_Understanding_research_philosophy_and_approaches_to_theory_development_8th_edition

Thank you Mark Saunders. Your work is very insightful

Thank you for the update and additional reading Mark, very helpful indeed.

THROUGHLY AND SIMPLY BRIEFED TO MAKE SENSE AND A CLEAR INSIGHT. THANK YOU, VERY MUCH.

Thank you for the sharing the recent version of the Onion!

I want to keep it in my reference of my assignment. May I??

Great summary, thank you taking the time to put this together. I’m sure it’s been a big help to lots of people. It definitely was to me.

I love the analysis… some people do not recognize qualitative or quantitative as an approach but rather have inductive, abductive, and deductive.

This has been helpful in the understanding of research . Thank you for this valuable information.

Great summary. Well explained. Thank you, guys.

This makes my fears on methodology go away. I confidently look forward to working on my methodology now. Thank you so much I ma doing a PhD with UNIMA, School of Education

simple and clear

Simple guide to crafting a research methodology. Quite impactful. Thank you

Thank you for this, this makes things very clear. Now I’m off to conquer my research proposal. Thanks again.

Thank you for this very informative and valuable information. What would the best approach be to take if you are using secondary data to form a qualitative study and relying on industry reports and peer journals to distinguish what factors influence the use of say cryptocurrency ?

Thanks for providing the whole idea/knowledge in the simplest way with essential factors which made my entire research process more efficient as well as valuable.

what is about research design such as descriptive, causal-comparative, correlation, developmental where these fall in the research onion?

This is very helpful. Thank you for this wonderful piece. However, it would be nicer to have References to the knowledge provided here. My suggestion

This material is very important for researchers, particularly for PhD scholars to conduct further study.

This was insightful. Thank you for the knowledge.

Thank you for the wonderful knowledge !Easy to understand and grasp.

thanks very much very simple. will need a coach

Hi this is a great article giving much help to my research. I just wanted to mention here that the example where you mentioned that ” schizophrenic symptoms like hallucinations are viewed positively, as they are thought to indicate the person is a spirit medium” is completely false as those are different cases and a bit out of context here. We are medically and psychologically well versed and obviously understand the difference between the two. As much as I am grateful to this article I would like to suggest you to give proper examples.

Thank you very much, sincerely I appreciate your efforts, it is insightful information. Once again I’m grateful .

In short, a complete insight of and for writing research methodology.

This information was very helpful, I was having difficulties in writing my methodology now I can say I have the full knowledge to write a more informative research methodology.

Thank you so much for this amazing explanation. As a person who hasn’t ever done a research project, this video helped me to clear my doubts and approach my research in a clear and concise manner. Great work

very well explained , after going through this there is no need any material to study . a very concise and to the point.

I have one small query. If I choose mixed -methods (quantitative and qualitative techniques), Then, my research Philosophy will also change to both Positivists and Interpretivist. Isn’t?

well explained and thank you

Thanks for this presentation. Quite simple and easy to understand, and to teach others.

Hello! Having made a decision to use a particular research philosophy, how then do we go about justifying that choice with references? Thank you.

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What employees are saying about the future of remote work

As organizations look to the postpandemic future, many are planning a hybrid virtual model  that combines remote work with time in the office. This sensible decision follows solid productivity increases  during the pandemic.

But while productivity may have gone up, many employees report feeling anxious and burned out. Unless leaders address the sources of employee anxiety, pandemic-style productivity gains may prove unsustainable in the future. 1 Besides anxiety and burnout, longer-term productivity in a hybrid virtual model will also require addressing the organizational norms that help create a common culture, generate social cohesion, and build shared trust. See Andrea Alexander, Aaron De Smet, and Mihir Mysore, “ Reimagining the postpandemic workforce ,” McKinsey Quarterly , July 7, 2020. That’s because anxiety is known to reduce job satisfaction, negatively affect interpersonal relationships with colleagues, and decrease work performance.

A McKinsey Live event on ‘Getting hybrid work right: What employees are saying’

As organizational leaders chart the path toward the postpandemic world, they need to communicate more frequently with their employees—even if their plans have yet to solidify fully. Organizations that have articulated more specific policies and approaches for the future workplace have seen employee well-being and productivity rise.

The following charts examine our survey findings and shed light on what employees want from the future of work.

Feeling included. Even high-level communication about post-COVID-19 working arrangements boosts employee well-being and productivity. But organizations that convey more detailed, remote-relevant policies and approaches see greater increases. Employees who feel included in more detailed communication are nearly five times more likely to report increased productivity. Because communicating about the future can drive performance outcomes today, leaders should consider increasing the frequency of their employee updates—both to share what’s already decided and to communicate what is still uncertain.

Communication breakdown. Valuable as a detailed vision for postpandemic work might be to employees, 40 percent of them say they’ve yet to hear about any vision from their organizations, and another 28 percent say that what they’ve heard remains vague.

Anxiety at work. At organizations that are communicating vaguely, or not at all, about the future of postpandemic work, nearly half of employees say it’s causing them concern or anxiety. Anxiety is known to decrease work performance, reduce job satisfaction, and negatively affect interpersonal relationships with colleagues, among other ills. For the global economy, the loss of productivity because of poor mental health—including anxiety—might be as high as $1 trillion per year .

Burning out. The lack of clear communication about the future of postpandemic work also contributes to employee burnout. Nearly half of employees surveyed say they’re feeling some symptoms of being burned out at work. That may be an underestimate, since employees experiencing burnout are less likely to respond to survey requests, and the most burned-out individuals may have already left the workforce—as have many women, who’ve been disproportionately affected  by the COVID-19 crisis.

Share more. Burnout is especially pronounced for people feeling anxious due to a lack of organizational communication. These employees were almost three times more likely to report feeling burned out. The obvious recommendation for organizational leaders: share more with employees, even if you’re uncertain about the future, to help improve employee well-being now.

Employees want flexibility. So how do organizations help their anxious and burned-out employees? One way is to find out what employees want for the future. More than half of employees told us they would like their organizations to adopt more flexible hybrid virtual-working models , in which employees are sometimes on-premises and sometimes working remotely. A hybrid model can help organizations make the most of talent wherever it resides, lower costs, and strengthen organizational performance .

Talent at risk. In fact, more than a quarter of those surveyed reported that they would consider switching employers if their organization returned to fully on-site work. Of course, even employees who say they might depart could ultimately decide to remain, depending on the policies companies end up adopting, the availability of jobs at the same or better rates of pay, and the role of automation in shifting the tasks people do .

Staying home. In describing the hybrid model of the future, more than half of government and corporate workers report that they would like to work from home at least three days a week once the pandemic is over. Across geographies, US employees are the most interested in having access to remote work, with nearly a third saying they would like to work remotely full time.

What parents say. Employees with young children are the most likely to prefer flexible work locations, with only 8 percent suggesting they would like to see a fully on-site model in the future. Employees without children under 18 are nearly three times as likely to prefer on-site work, but the majority still prefer more flexible models.

Hopes and fears. Across the board, employees are eager to see organizations put a greater emphasis on flexibility, competitive compensation, and well-being once the pandemic is over—and conversely, they’re concerned that future work, regardless of whether it is on-site or remote, will negatively affect these needs. Employees also fear that on-site work will lead to a greater chance of getting sick and that remote work will reduce community and collaboration between colleagues.

Policy matters. Which working arrangements and related policies do employees say will lead to the highest levels of well-being, social cohesion, and productivity? More than a third of respondents ranked clear hours and expectations for collaboration in their top five policies; several other collaboration policies, including technologies that enable on-site employees to dial-in to remote meetings and guidelines for documentation, also received significant support. Collaboration tools, and training for those tools, also rate highly for employees, as does reimbursement for remote-work office setups. Microconnectivity policies, meanwhile—from small team events to a listening and response strategy—were top policies for more than a quarter of all respondents.

Andrea Alexander is an associate partner in McKinsey’s Houston office. Aaron De Smet is a senior partner in the New Jersey office. Meredith Langstaff is an associate partner in the Washington, DC, office, where Dan Ravid is a fellow, research and knowledge.

This article was edited by Lang Davison, an executive editor in the Seattle office.

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Reimagining the postpandemic workforce

What’s next for remote work: An analysis of 2,000 tasks, 800 jobs, and nine countries

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• Report to clients & stakeholders
• Demonstrate ESG transparency and leadership
• Engage companies and external stakeholders
• Provide transparency through client reporting
• Conduct thematic or industry research

ESG rating Key benefits

Key product features:.

We rate over 8,500 companies (14,000 issuers including subsidiaries) and more than 680,000 equity and fixed income securities globally (as of October 2020), collecting thousands of data points for each company.

MSCI ESG Research Experience and Leadership

Msci esg research experience and leadership.

• We have over 40 years 2 of experience measuring and modelling ESG performance of companies. We are recognized as a ‘Gold Standard data provider’3 and voted 'Best Firm for SRI research' and ‘Best Firm for Corporate Governance research' for the last four years 3
• We were the first ESG provider to assess companies based on industry materiality, dating back to 1999. Only dataset with live history (13+ years) demonstrating economic relevance
• Objective rules based ESG ratings, with an average 45% of data, 5 coming from alternative data sources, utilizing AI tech to extract and verify unstructured data
• First ESG ratings provider to measure and embed companies’ ESG risk exposure 4

ESG Ratings Related Content

Related content, .rel-cont-head{ font-size: 31px important; line-height: 38px important; } sustainable investing.

Companies with strong MSCI ESG Ratings profiles may be better positioned for future challenges and experience fewer instances of bribery, corruption and fraud. Learn how our sustainability solutions can provide insights into risks and opportunities.

Climate and Net-Zero Solutions

To empower investors to analyze and report on their portfolios’ exposures to transition and physical climate risk. 1 .

Sustainable Finance

ESG and climate regulation and disclosure resource center for institutional investors, managers and advisors.

ESG ratings footnotes

MSCI ESG Research LLC. is a Registered Investment Adviser under the Investment Adviser Act of 1940. The most recent SEC Form ADV filing, including Form ADV Part 2A, is available on the U.S. SEC’s website at www.adviserinfo.sec.gov  (opens in a new tab) .

MIFID2/MIFIR notice: MSCI ESG Research LLC does not distribute or act as an intermediary for financial instruments or structured deposits, nor does it deal on its own account, provide execution services for others or manage client accounts. No MSCI ESG Research product or service supports, promotes or is intended to support or promote any such activity. MSCI ESG Research is an independent provider of ESG data, reports and ratings based on published methodologies and available to clients on a subscription basis. 

ESG ADV 2A (PDF, 354 KB)  (opens in a new tab) ESG ADV 2B (brochure supplement) (PDF, 232 KB)  (opens in a new tab)

1  GICS®, the global industry classification standard jointly developed by MSCI Inc. and S&P Global.

2  Through our legacy companies KLD, Innovest, IRRC, and GMI Ratings.

3  Deep Data Delivery Standard http://www.deepdata.ai/

4  Through our legacy companies KLD, Innovest, IRRC, and GMI Ratings. Origins of MSCI ESG Ratings established in 1999. Produced time series data since 2007.

5  Source: MSCI ESG Research 2,434 constituents of the MSCI ACWI Index as of November 30, 2017.

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CVE-2024-24919: Check Point Security Gateways Zero-Day Vulnerability Explained

Huseyin Can YUCEEL & Picus Labs | June 03, 2024

The Red Report 2024

The Top 10 MITRE ATT&CK Techniques Used by Adversaries

On May 28th, 2024, Check Point disclosed an arbitrary file read vulnerability affecting Check Point Security Gateways [1]. CVE-2024-24919 has a CVSS score of 8.6 (High) and allows adversaries to read sensitive files from vulnerable products with root privileges. If the certificate authentication is not enabled, adversaries may exploit CVE-2024-24919 for unauthenticated remote code execution. 

In this blog, we explained how the Check Point CVE-2024-24919 vulnerability works and how organizations can defend against CVE-2024-24919 attacks.

Simulate Vulnerability Exploitation Attacks with 14-Day Free Trial of Picus Platform

Check Point CVE-2024-24919 Vulnerability Explained

Check Point Security Gateways are used by organizations worldwide as a security barrier against various types of threats and unauthorized access to networked systems. On May 27th, 2024, Check Point saw a significant volume of malicious traffic targeting VPN devices. CVE-2024-24919 is a high-severity zero-day vulnerability affecting Check Point Security Gateways with remote Access VPN or Mobile Access Software Blades enabled. The vulnerability has a CVSS score of 8.6 (High) and can be exploited for arbitrary file read with a possibility of unauthenticated remote code execution. Due to ease of exploitability, organizations are advised to apply hot fixes to their vulnerable Check Point Security Gateway products.

How Check Point CVE-2024-24919 Exploit Works?

Check Point CVE-2024-24919 is an arbitrary file read vulnerability ( CWE-200 ) that allows attackers to access and read sensitive files via path traversal. On its own, an arbitrary file read vulnerability would have a high severity score. However, CVE-2024-24919 allows attackers to access files with root privileges, increasing the severity. Adversaries can access critical files such as  "passwd" and "shadow" and harvest user credentials. If any multi-factor authentication is in place, attackers use harvested credentials for remote code execution.

The example HTTP POST request below exploits the CVE-2024-24919 vulnerability. 

How Picus Helps Simulate Check Point CVE-2024-24919 Attacks?

We also strongly suggest simulating the Check Point CVE-2024-24919 vulnerability to test the effectiveness of your security controls against sophisticated cyber attacks using the Picus Complete Security Validation Platform . You can also test your defenses against oth er vulnerability exploitation attacks, such as Log4Shell, Citrix Bleed, and Follina , within minutes with a 14-day free trial of the Picus Platform .

Picus Threat Library includes the following threats for Check Point CVE-2024-24919 vulnerability exploitation attacks :

Picus also provides actionable mitigation content. Picus Mitigation Library includes prevention signatures to address Check Point CVE-2024-24919 vulnerability in preventive security controls. Currently, Picus Labs validated the following signatures for Check Point CVE-2024-24919 vulnerability :

Start simulating emerging threats today and get actionable mitigation insights with a  14-day free trial   of the Picus Complete Security Validation Platform.

[1] "Preventative Hotfix for CVE-2024-24919 - Quantum Gateway Information Disclosure." Available: https://support.checkpoint.com/results/sk/sk182336

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