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Published by Nicolas at March 21st, 2024 , Revised On March 12, 2024

The Ultimate Guide To Research Methodology

Research methodology is a crucial aspect of any investigative process, serving as the blueprint for the entire research journey. If you are stuck in the methodology section of your research paper , then this blog will guide you on what is a research methodology, its types and how to successfully conduct one. 

Table of Contents

What Is Research Methodology?

Research methodology can be defined as the systematic framework that guides researchers in designing, conducting, and analyzing their investigations. It encompasses a structured set of processes, techniques, and tools employed to gather and interpret data, ensuring the reliability and validity of the research findings. 

Research methodology is not confined to a singular approach; rather, it encapsulates a diverse range of methods tailored to the specific requirements of the research objectives.

Here is why Research methodology is important in academic and professional settings.

Facilitating Rigorous Inquiry

Research methodology forms the backbone of rigorous inquiry. It provides a structured approach that aids researchers in formulating precise thesis statements , selecting appropriate methodologies, and executing systematic investigations. This, in turn, enhances the quality and credibility of the research outcomes.

Ensuring Reproducibility And Reliability

In both academic and professional contexts, the ability to reproduce research outcomes is paramount. A well-defined research methodology establishes clear procedures, making it possible for others to replicate the study. This not only validates the findings but also contributes to the cumulative nature of knowledge.

Guiding Decision-Making Processes

In professional settings, decisions often hinge on reliable data and insights. Research methodology equips professionals with the tools to gather pertinent information, analyze it rigorously, and derive meaningful conclusions.

This informed decision-making is instrumental in achieving organizational goals and staying ahead in competitive environments.

Contributing To Academic Excellence

For academic researchers, adherence to robust research methodology is a hallmark of excellence. Institutions value research that adheres to high standards of methodology, fostering a culture of academic rigour and intellectual integrity. Furthermore, it prepares students with critical skills applicable beyond academia.

Enhancing Problem-Solving Abilities

Research methodology instills a problem-solving mindset by encouraging researchers to approach challenges systematically. It equips individuals with the skills to dissect complex issues, formulate hypotheses , and devise effective strategies for investigation.

Understanding Research Methodology

In the pursuit of knowledge and discovery, understanding the fundamentals of research methodology is paramount. 

Basics Of Research

Research, in its essence, is a systematic and organized process of inquiry aimed at expanding our understanding of a particular subject or phenomenon. It involves the exploration of existing knowledge, the formulation of hypotheses, and the collection and analysis of data to draw meaningful conclusions. 

Research is a dynamic and iterative process that contributes to the continuous evolution of knowledge in various disciplines.

Types of Research

Research takes on various forms, each tailored to the nature of the inquiry. Broadly classified, research can be categorized into two main types:

  • Quantitative Research: This type involves the collection and analysis of numerical data to identify patterns, relationships, and statistical significance. It is particularly useful for testing hypotheses and making predictions.
  • Qualitative Research: Qualitative research focuses on understanding the depth and details of a phenomenon through non-numerical data. It often involves methods such as interviews, focus groups, and content analysis, providing rich insights into complex issues.

Components Of Research Methodology

To conduct effective research, one must go through the different components of research methodology. These components form the scaffolding that supports the entire research process, ensuring its coherence and validity.

Research Design

Research design serves as the blueprint for the entire research project. It outlines the overall structure and strategy for conducting the study. The three primary types of research design are:

  • Exploratory Research: Aimed at gaining insights and familiarity with the topic, often used in the early stages of research.
  • Descriptive Research: Involves portraying an accurate profile of a situation or phenomenon, answering the ‘what,’ ‘who,’ ‘where,’ and ‘when’ questions.
  • Explanatory Research: Seeks to identify the causes and effects of a phenomenon, explaining the ‘why’ and ‘how.’

Data Collection Methods

Choosing the right data collection methods is crucial for obtaining reliable and relevant information. Common methods include:

  • Surveys and Questionnaires: Employed to gather information from a large number of respondents through standardized questions.
  • Interviews: In-depth conversations with participants, offering qualitative insights.
  • Observation: Systematic watching and recording of behaviour, events, or processes in their natural setting.

Data Analysis Techniques

Once data is collected, analysis becomes imperative to derive meaningful conclusions. Different methodologies exist for quantitative and qualitative data:

  • Quantitative Data Analysis: Involves statistical techniques such as descriptive statistics, inferential statistics, and regression analysis to interpret numerical data.
  • Qualitative Data Analysis: Methods like content analysis, thematic analysis, and grounded theory are employed to extract patterns, themes, and meanings from non-numerical data.

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Choosing a Research Method

Selecting an appropriate research method is a critical decision in the research process. It determines the approach, tools, and techniques that will be used to answer the research questions. 

Quantitative Research Methods

Quantitative research involves the collection and analysis of numerical data, providing a structured and objective approach to understanding and explaining phenomena.

Experimental Research

Experimental research involves manipulating variables to observe the effect on another variable under controlled conditions. It aims to establish cause-and-effect relationships.

Key Characteristics:

  • Controlled Environment: Experiments are conducted in a controlled setting to minimize external influences.
  • Random Assignment: Participants are randomly assigned to different experimental conditions.
  • Quantitative Data: Data collected is numerical, allowing for statistical analysis.

Applications: Commonly used in scientific studies and psychology to test hypotheses and identify causal relationships.

Survey Research

Survey research gathers information from a sample of individuals through standardized questionnaires or interviews. It aims to collect data on opinions, attitudes, and behaviours.

  • Structured Instruments: Surveys use structured instruments, such as questionnaires, to collect data.
  • Large Sample Size: Surveys often target a large and diverse group of participants.
  • Quantitative Data Analysis: Responses are quantified for statistical analysis.

Applications: Widely employed in social sciences, marketing, and public opinion research to understand trends and preferences.

Descriptive Research

Descriptive research seeks to portray an accurate profile of a situation or phenomenon. It focuses on answering the ‘what,’ ‘who,’ ‘where,’ and ‘when’ questions.

  • Observation and Data Collection: This involves observing and documenting without manipulating variables.
  • Objective Description: Aim to provide an unbiased and factual account of the subject.
  • Quantitative or Qualitative Data: T his can include both types of data, depending on the research focus.

Applications: Useful in situations where researchers want to understand and describe a phenomenon without altering it, common in social sciences and education.

Qualitative Research Methods

Qualitative research emphasizes exploring and understanding the depth and complexity of phenomena through non-numerical data.

A case study is an in-depth exploration of a particular person, group, event, or situation. It involves detailed, context-rich analysis.

  • Rich Data Collection: Uses various data sources, such as interviews, observations, and documents.
  • Contextual Understanding: Aims to understand the context and unique characteristics of the case.
  • Holistic Approach: Examines the case in its entirety.

Applications: Common in social sciences, psychology, and business to investigate complex and specific instances.

Ethnography

Ethnography involves immersing the researcher in the culture or community being studied to gain a deep understanding of their behaviours, beliefs, and practices.

  • Participant Observation: Researchers actively participate in the community or setting.
  • Holistic Perspective: Focuses on the interconnectedness of cultural elements.
  • Qualitative Data: In-depth narratives and descriptions are central to ethnographic studies.

Applications: Widely used in anthropology, sociology, and cultural studies to explore and document cultural practices.

Grounded Theory

Grounded theory aims to develop theories grounded in the data itself. It involves systematic data collection and analysis to construct theories from the ground up.

  • Constant Comparison: Data is continually compared and analyzed during the research process.
  • Inductive Reasoning: Theories emerge from the data rather than being imposed on it.
  • Iterative Process: The research design evolves as the study progresses.

Applications: Commonly applied in sociology, nursing, and management studies to generate theories from empirical data.

Research design is the structural framework that outlines the systematic process and plan for conducting a study. It serves as the blueprint, guiding researchers on how to collect, analyze, and interpret data.

Exploratory, Descriptive, And Explanatory Designs

Exploratory design.

Exploratory research design is employed when a researcher aims to explore a relatively unknown subject or gain insights into a complex phenomenon.

  • Flexibility: Allows for flexibility in data collection and analysis.
  • Open-Ended Questions: Uses open-ended questions to gather a broad range of information.
  • Preliminary Nature: Often used in the initial stages of research to formulate hypotheses.

Applications: Valuable in the early stages of investigation, especially when the researcher seeks a deeper understanding of a subject before formalizing research questions.

Descriptive Design

Descriptive research design focuses on portraying an accurate profile of a situation, group, or phenomenon.

  • Structured Data Collection: Involves systematic and structured data collection methods.
  • Objective Presentation: Aims to provide an unbiased and factual account of the subject.
  • Quantitative or Qualitative Data: Can incorporate both types of data, depending on the research objectives.

Applications: Widely used in social sciences, marketing, and educational research to provide detailed and objective descriptions.

Explanatory Design

Explanatory research design aims to identify the causes and effects of a phenomenon, explaining the ‘why’ and ‘how’ behind observed relationships.

  • Causal Relationships: Seeks to establish causal relationships between variables.
  • Controlled Variables : Often involves controlling certain variables to isolate causal factors.
  • Quantitative Analysis: Primarily relies on quantitative data analysis techniques.

Applications: Commonly employed in scientific studies and social sciences to delve into the underlying reasons behind observed patterns.

Cross-Sectional Vs. Longitudinal Designs

Cross-sectional design.

Cross-sectional designs collect data from participants at a single point in time.

  • Snapshot View: Provides a snapshot of a population at a specific moment.
  • Efficiency: More efficient in terms of time and resources.
  • Limited Temporal Insights: Offers limited insights into changes over time.

Applications: Suitable for studying characteristics or behaviours that are stable or not expected to change rapidly.

Longitudinal Design

Longitudinal designs involve the collection of data from the same participants over an extended period.

  • Temporal Sequence: Allows for the examination of changes over time.
  • Causality Assessment: Facilitates the assessment of cause-and-effect relationships.
  • Resource-Intensive: Requires more time and resources compared to cross-sectional designs.

Applications: Ideal for studying developmental processes, trends, or the impact of interventions over time.

Experimental Vs Non-experimental Designs

Experimental design.

Experimental designs involve manipulating variables under controlled conditions to observe the effect on another variable.

  • Causality Inference: Enables the inference of cause-and-effect relationships.
  • Quantitative Data: Primarily involves the collection and analysis of numerical data.

Applications: Commonly used in scientific studies, psychology, and medical research to establish causal relationships.

Non-Experimental Design

Non-experimental designs observe and describe phenomena without manipulating variables.

  • Natural Settings: Data is often collected in natural settings without intervention.
  • Descriptive or Correlational: Focuses on describing relationships or correlations between variables.
  • Quantitative or Qualitative Data: This can involve either type of data, depending on the research approach.

Applications: Suitable for studying complex phenomena in real-world settings where manipulation may not be ethical or feasible.

Effective data collection is fundamental to the success of any research endeavour. 

Designing Effective Surveys

Objective Design:

  • Clearly define the research objectives to guide the survey design.
  • Craft questions that align with the study’s goals and avoid ambiguity.

Structured Format:

  • Use a structured format with standardized questions for consistency.
  • Include a mix of closed-ended and open-ended questions for detailed insights.

Pilot Testing:

  • Conduct pilot tests to identify and rectify potential issues with survey design.
  • Ensure clarity, relevance, and appropriateness of questions.

Sampling Strategy:

  • Develop a robust sampling strategy to ensure a representative participant group.
  • Consider random sampling or stratified sampling based on the research goals.

Conducting Interviews

Establishing Rapport:

  • Build rapport with participants to create a comfortable and open environment.
  • Clearly communicate the purpose of the interview and the value of participants’ input.

Open-Ended Questions:

  • Frame open-ended questions to encourage detailed responses.
  • Allow participants to express their thoughts and perspectives freely.

Active Listening:

  • Practice active listening to understand areas and gather rich data.
  • Avoid interrupting and maintain a non-judgmental stance during the interview.

Ethical Considerations:

  • Obtain informed consent and assure participants of confidentiality.
  • Be transparent about the study’s purpose and potential implications.

Observation

1. participant observation.

Immersive Participation:

  • Actively immerse yourself in the setting or group being observed.
  • Develop a deep understanding of behaviours, interactions, and context.

Field Notes:

  • Maintain detailed and reflective field notes during observations.
  • Document observed patterns, unexpected events, and participant reactions.

Ethical Awareness:

  • Be conscious of ethical considerations, ensuring respect for participants.
  • Balance the role of observer and participant to minimize bias.

2. Non-participant Observation

Objective Observation:

  • Maintain a more detached and objective stance during non-participant observation.
  • Focus on recording behaviours, events, and patterns without direct involvement.

Data Reliability:

  • Enhance the reliability of data by reducing observer bias.
  • Develop clear observation protocols and guidelines.

Contextual Understanding:

  • Strive for a thorough understanding of the observed context.
  • Consider combining non-participant observation with other methods for triangulation.

Archival Research

1. using existing data.

Identifying Relevant Archives:

  • Locate and access archives relevant to the research topic.
  • Collaborate with institutions or repositories holding valuable data.

Data Verification:

  • Verify the accuracy and reliability of archived data.
  • Cross-reference with other sources to ensure data integrity.

Ethical Use:

  • Adhere to ethical guidelines when using existing data.
  • Respect copyright and intellectual property rights.

2. Challenges and Considerations

Incomplete or Inaccurate Archives:

  • Address the possibility of incomplete or inaccurate archival records.
  • Acknowledge limitations and uncertainties in the data.

Temporal Bias:

  • Recognize potential temporal biases in archived data.
  • Consider the historical context and changes that may impact interpretation.

Access Limitations:

  • Address potential limitations in accessing certain archives.
  • Seek alternative sources or collaborate with institutions to overcome barriers.

Common Challenges in Research Methodology

Conducting research is a complex and dynamic process, often accompanied by a myriad of challenges. Addressing these challenges is crucial to ensure the reliability and validity of research findings.

Sampling Issues

Sampling bias:.

  • The presence of sampling bias can lead to an unrepresentative sample, affecting the generalizability of findings.
  • Employ random sampling methods and ensure the inclusion of diverse participants to reduce bias.

Sample Size Determination:

  • Determining an appropriate sample size is a delicate balance. Too small a sample may lack statistical power, while an excessively large sample may strain resources.
  • Conduct a power analysis to determine the optimal sample size based on the research objectives and expected effect size.

Data Quality And Validity

Measurement error:.

  • Inaccuracies in measurement tools or data collection methods can introduce measurement errors, impacting the validity of results.
  • Pilot test instruments, calibrate equipment, and use standardized measures to enhance the reliability of data.

Construct Validity:

  • Ensuring that the chosen measures accurately capture the intended constructs is a persistent challenge.
  • Use established measurement instruments and employ multiple measures to assess the same construct for triangulation.

Time And Resource Constraints

Timeline pressures:.

  • Limited timeframes can compromise the depth and thoroughness of the research process.
  • Develop a realistic timeline, prioritize tasks, and communicate expectations with stakeholders to manage time constraints effectively.

Resource Availability:

  • Inadequate resources, whether financial or human, can impede the execution of research activities.
  • Seek external funding, collaborate with other researchers, and explore alternative methods that require fewer resources.

Managing Bias in Research

Selection bias:.

  • Selecting participants in a way that systematically skews the sample can introduce selection bias.
  • Employ randomization techniques, use stratified sampling, and transparently report participant recruitment methods.

Confirmation Bias:

  • Researchers may unintentionally favour information that confirms their preconceived beliefs or hypotheses.
  • Adopt a systematic and open-minded approach, use blinded study designs, and engage in peer review to mitigate confirmation bias.

Tips On How To Write A Research Methodology

Conducting successful research relies not only on the application of sound methodologies but also on strategic planning and effective collaboration. Here are some tips to enhance the success of your research methodology:

Tip 1. Clear Research Objectives

Well-defined research objectives guide the entire research process. Clearly articulate the purpose of your study, outlining specific research questions or hypotheses.

Tip 2. Comprehensive Literature Review

A thorough literature review provides a foundation for understanding existing knowledge and identifying gaps. Invest time in reviewing relevant literature to inform your research design and methodology.

Tip 3. Detailed Research Plan

A detailed plan serves as a roadmap, ensuring all aspects of the research are systematically addressed. Develop a detailed research plan outlining timelines, milestones, and tasks.

Tip 4. Ethical Considerations

Ethical practices are fundamental to maintaining the integrity of research. Address ethical considerations early, obtain necessary approvals, and ensure participant rights are safeguarded.

Tip 5. Stay Updated On Methodologies

Research methodologies evolve, and staying updated is essential for employing the most effective techniques. Engage in continuous learning by attending workshops, conferences, and reading recent publications.

Tip 6. Adaptability In Methods

Unforeseen challenges may arise during research, necessitating adaptability in methods. Be flexible and willing to modify your approach when needed, ensuring the integrity of the study.

Tip 7. Iterative Approach

Research is often an iterative process, and refining methods based on ongoing findings enhance the study’s robustness. Regularly review and refine your research design and methods as the study progresses.

Frequently Asked Questions

What is the research methodology.

Research methodology is the systematic process of planning, executing, and evaluating scientific investigation. It encompasses the techniques, tools, and procedures used to collect, analyze, and interpret data, ensuring the reliability and validity of research findings.

What are the methodologies in research?

Research methodologies include qualitative and quantitative approaches. Qualitative methods involve in-depth exploration of non-numerical data, while quantitative methods use statistical analysis to examine numerical data. Mixed methods combine both approaches for a comprehensive understanding of research questions.

How to write research methodology?

To write a research methodology, clearly outline the study’s design, data collection, and analysis procedures. Specify research tools, participants, and sampling methods. Justify choices and discuss limitations. Ensure clarity, coherence, and alignment with research objectives for a robust methodology section.

How to write the methodology section of a research paper?

In the methodology section of a research paper, describe the study’s design, data collection, and analysis methods. Detail procedures, tools, participants, and sampling. Justify choices, address ethical considerations, and explain how the methodology aligns with research objectives, ensuring clarity and rigour.

What is mixed research methodology?

Mixed research methodology combines both qualitative and quantitative research approaches within a single study. This approach aims to enhance the details and depth of research findings by providing a more comprehensive understanding of the research problem or question.

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Research Method

Home » Research Process – Steps, Examples and Tips

Research Process – Steps, Examples and Tips

Table of Contents

Research Process

Research Process

Definition:

Research Process is a systematic and structured approach that involves the collection, analysis, and interpretation of data or information to answer a specific research question or solve a particular problem.

Research Process Steps

Research Process Steps are as follows:

Identify the Research Question or Problem

This is the first step in the research process. It involves identifying a problem or question that needs to be addressed. The research question should be specific, relevant, and focused on a particular area of interest.

Conduct a Literature Review

Once the research question has been identified, the next step is to conduct a literature review. This involves reviewing existing research and literature on the topic to identify any gaps in knowledge or areas where further research is needed. A literature review helps to provide a theoretical framework for the research and also ensures that the research is not duplicating previous work.

Formulate a Hypothesis or Research Objectives

Based on the research question and literature review, the researcher can formulate a hypothesis or research objectives. A hypothesis is a statement that can be tested to determine its validity, while research objectives are specific goals that the researcher aims to achieve through the research.

Design a Research Plan and Methodology

This step involves designing a research plan and methodology that will enable the researcher to collect and analyze data to test the hypothesis or achieve the research objectives. The research plan should include details on the sample size, data collection methods, and data analysis techniques that will be used.

Collect and Analyze Data

This step involves collecting and analyzing data according to the research plan and methodology. Data can be collected through various methods, including surveys, interviews, observations, or experiments. The data analysis process involves cleaning and organizing the data, applying statistical and analytical techniques to the data, and interpreting the results.

Interpret the Findings and Draw Conclusions

After analyzing the data, the researcher must interpret the findings and draw conclusions. This involves assessing the validity and reliability of the results and determining whether the hypothesis was supported or not. The researcher must also consider any limitations of the research and discuss the implications of the findings.

Communicate the Results

Finally, the researcher must communicate the results of the research through a research report, presentation, or publication. The research report should provide a detailed account of the research process, including the research question, literature review, research methodology, data analysis, findings, and conclusions. The report should also include recommendations for further research in the area.

Review and Revise

The research process is an iterative one, and it is important to review and revise the research plan and methodology as necessary. Researchers should assess the quality of their data and methods, reflect on their findings, and consider areas for improvement.

Ethical Considerations

Throughout the research process, ethical considerations must be taken into account. This includes ensuring that the research design protects the welfare of research participants, obtaining informed consent, maintaining confidentiality and privacy, and avoiding any potential harm to participants or their communities.

Dissemination and Application

The final step in the research process is to disseminate the findings and apply the research to real-world settings. Researchers can share their findings through academic publications, presentations at conferences, or media coverage. The research can be used to inform policy decisions, develop interventions, or improve practice in the relevant field.

Research Process Example

Following is a Research Process Example:

Research Question : What are the effects of a plant-based diet on athletic performance in high school athletes?

Step 1: Background Research Conduct a literature review to gain a better understanding of the existing research on the topic. Read academic articles and research studies related to plant-based diets, athletic performance, and high school athletes.

Step 2: Develop a Hypothesis Based on the literature review, develop a hypothesis that a plant-based diet positively affects athletic performance in high school athletes.

Step 3: Design the Study Design a study to test the hypothesis. Decide on the study population, sample size, and research methods. For this study, you could use a survey to collect data on dietary habits and athletic performance from a sample of high school athletes who follow a plant-based diet and a sample of high school athletes who do not follow a plant-based diet.

Step 4: Collect Data Distribute the survey to the selected sample and collect data on dietary habits and athletic performance.

Step 5: Analyze Data Use statistical analysis to compare the data from the two samples and determine if there is a significant difference in athletic performance between those who follow a plant-based diet and those who do not.

Step 6 : Interpret Results Interpret the results of the analysis in the context of the research question and hypothesis. Discuss any limitations or potential biases in the study design.

Step 7: Draw Conclusions Based on the results, draw conclusions about whether a plant-based diet has a significant effect on athletic performance in high school athletes. If the hypothesis is supported by the data, discuss potential implications and future research directions.

Step 8: Communicate Findings Communicate the findings of the study in a clear and concise manner. Use appropriate language, visuals, and formats to ensure that the findings are understood and valued.

Applications of Research Process

The research process has numerous applications across a wide range of fields and industries. Some examples of applications of the research process include:

  • Scientific research: The research process is widely used in scientific research to investigate phenomena in the natural world and develop new theories or technologies. This includes fields such as biology, chemistry, physics, and environmental science.
  • Social sciences : The research process is commonly used in social sciences to study human behavior, social structures, and institutions. This includes fields such as sociology, psychology, anthropology, and economics.
  • Education: The research process is used in education to study learning processes, curriculum design, and teaching methodologies. This includes research on student achievement, teacher effectiveness, and educational policy.
  • Healthcare: The research process is used in healthcare to investigate medical conditions, develop new treatments, and evaluate healthcare interventions. This includes fields such as medicine, nursing, and public health.
  • Business and industry : The research process is used in business and industry to study consumer behavior, market trends, and develop new products or services. This includes market research, product development, and customer satisfaction research.
  • Government and policy : The research process is used in government and policy to evaluate the effectiveness of policies and programs, and to inform policy decisions. This includes research on social welfare, crime prevention, and environmental policy.

Purpose of Research Process

The purpose of the research process is to systematically and scientifically investigate a problem or question in order to generate new knowledge or solve a problem. The research process enables researchers to:

  • Identify gaps in existing knowledge: By conducting a thorough literature review, researchers can identify gaps in existing knowledge and develop research questions that address these gaps.
  • Collect and analyze data : The research process provides a structured approach to collecting and analyzing data. Researchers can use a variety of research methods, including surveys, experiments, and interviews, to collect data that is valid and reliable.
  • Test hypotheses : The research process allows researchers to test hypotheses and make evidence-based conclusions. Through the systematic analysis of data, researchers can draw conclusions about the relationships between variables and develop new theories or models.
  • Solve problems: The research process can be used to solve practical problems and improve real-world outcomes. For example, researchers can develop interventions to address health or social problems, evaluate the effectiveness of policies or programs, and improve organizational processes.
  • Generate new knowledge : The research process is a key way to generate new knowledge and advance understanding in a given field. By conducting rigorous and well-designed research, researchers can make significant contributions to their field and help to shape future research.

Tips for Research Process

Here are some tips for the research process:

  • Start with a clear research question : A well-defined research question is the foundation of a successful research project. It should be specific, relevant, and achievable within the given time frame and resources.
  • Conduct a thorough literature review: A comprehensive literature review will help you to identify gaps in existing knowledge, build on previous research, and avoid duplication. It will also provide a theoretical framework for your research.
  • Choose appropriate research methods: Select research methods that are appropriate for your research question, objectives, and sample size. Ensure that your methods are valid, reliable, and ethical.
  • Be organized and systematic: Keep detailed notes throughout the research process, including your research plan, methodology, data collection, and analysis. This will help you to stay organized and ensure that you don’t miss any important details.
  • Analyze data rigorously: Use appropriate statistical and analytical techniques to analyze your data. Ensure that your analysis is valid, reliable, and transparent.
  • I nterpret results carefully : Interpret your results in the context of your research question and objectives. Consider any limitations or potential biases in your research design, and be cautious in drawing conclusions.
  • Communicate effectively: Communicate your research findings clearly and effectively to your target audience. Use appropriate language, visuals, and formats to ensure that your findings are understood and valued.
  • Collaborate and seek feedback : Collaborate with other researchers, experts, or stakeholders in your field. Seek feedback on your research design, methods, and findings to ensure that they are relevant, meaningful, and impactful.

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  • What Is a Research Methodology? | Steps & Tips

What Is a Research Methodology? | Steps & Tips

Published on 25 February 2019 by Shona McCombes . Revised on 10 October 2022.

Your research methodology discusses and explains the data collection and analysis methods you used in your research. A key part of your thesis, dissertation, or research paper, the methodology chapter explains what you did and how you did it, allowing readers to evaluate the reliability and validity of your research.

It should include:

  • The type of research you conducted
  • How you collected and analysed your data
  • Any tools or materials you used in the research
  • Why you chose these methods
  • Your methodology section should generally be written in the past tense .
  • Academic style guides in your field may provide detailed guidelines on what to include for different types of studies.
  • Your citation style might provide guidelines for your methodology section (e.g., an APA Style methods section ).

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Table of contents

How to write a research methodology, why is a methods section important, step 1: explain your methodological approach, step 2: describe your data collection methods, step 3: describe your analysis method, step 4: evaluate and justify the methodological choices you made, tips for writing a strong methodology chapter, frequently asked questions about methodology.

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Your methods section is your opportunity to share how you conducted your research and why you chose the methods you chose. It’s also the place to show that your research was rigorously conducted and can be replicated .

It gives your research legitimacy and situates it within your field, and also gives your readers a place to refer to if they have any questions or critiques in other sections.

You can start by introducing your overall approach to your research. You have two options here.

Option 1: Start with your “what”

What research problem or question did you investigate?

  • Aim to describe the characteristics of something?
  • Explore an under-researched topic?
  • Establish a causal relationship?

And what type of data did you need to achieve this aim?

  • Quantitative data , qualitative data , or a mix of both?
  • Primary data collected yourself, or secondary data collected by someone else?
  • Experimental data gathered by controlling and manipulating variables, or descriptive data gathered via observations?

Option 2: Start with your “why”

Depending on your discipline, you can also start with a discussion of the rationale and assumptions underpinning your methodology. In other words, why did you choose these methods for your study?

  • Why is this the best way to answer your research question?
  • Is this a standard methodology in your field, or does it require justification?
  • Were there any ethical considerations involved in your choices?
  • What are the criteria for validity and reliability in this type of research ?

Once you have introduced your reader to your methodological approach, you should share full details about your data collection methods .

Quantitative methods

In order to be considered generalisable, you should describe quantitative research methods in enough detail for another researcher to replicate your study.

Here, explain how you operationalised your concepts and measured your variables. Discuss your sampling method or inclusion/exclusion criteria, as well as any tools, procedures, and materials you used to gather your data.

Surveys Describe where, when, and how the survey was conducted.

  • How did you design the questionnaire?
  • What form did your questions take (e.g., multiple choice, Likert scale )?
  • Were your surveys conducted in-person or virtually?
  • What sampling method did you use to select participants?
  • What was your sample size and response rate?

Experiments Share full details of the tools, techniques, and procedures you used to conduct your experiment.

  • How did you design the experiment ?
  • How did you recruit participants?
  • How did you manipulate and measure the variables ?
  • What tools did you use?

Existing data Explain how you gathered and selected the material (such as datasets or archival data) that you used in your analysis.

  • Where did you source the material?
  • How was the data originally produced?
  • What criteria did you use to select material (e.g., date range)?

The survey consisted of 5 multiple-choice questions and 10 questions measured on a 7-point Likert scale.

The goal was to collect survey responses from 350 customers visiting the fitness apparel company’s brick-and-mortar location in Boston on 4–8 July 2022, between 11:00 and 15:00.

Here, a customer was defined as a person who had purchased a product from the company on the day they took the survey. Participants were given 5 minutes to fill in the survey anonymously. In total, 408 customers responded, but not all surveys were fully completed. Due to this, 371 survey results were included in the analysis.

Qualitative methods

In qualitative research , methods are often more flexible and subjective. For this reason, it’s crucial to robustly explain the methodology choices you made.

Be sure to discuss the criteria you used to select your data, the context in which your research was conducted, and the role you played in collecting your data (e.g., were you an active participant, or a passive observer?)

Interviews or focus groups Describe where, when, and how the interviews were conducted.

  • How did you find and select participants?
  • How many participants took part?
  • What form did the interviews take ( structured , semi-structured , or unstructured )?
  • How long were the interviews?
  • How were they recorded?

Participant observation Describe where, when, and how you conducted the observation or ethnography .

  • What group or community did you observe? How long did you spend there?
  • How did you gain access to this group? What role did you play in the community?
  • How long did you spend conducting the research? Where was it located?
  • How did you record your data (e.g., audiovisual recordings, note-taking)?

Existing data Explain how you selected case study materials for your analysis.

  • What type of materials did you analyse?
  • How did you select them?

In order to gain better insight into possibilities for future improvement of the fitness shop’s product range, semi-structured interviews were conducted with 8 returning customers.

Here, a returning customer was defined as someone who usually bought products at least twice a week from the store.

Surveys were used to select participants. Interviews were conducted in a small office next to the cash register and lasted approximately 20 minutes each. Answers were recorded by note-taking, and seven interviews were also filmed with consent. One interviewee preferred not to be filmed.

Mixed methods

Mixed methods research combines quantitative and qualitative approaches. If a standalone quantitative or qualitative study is insufficient to answer your research question, mixed methods may be a good fit for you.

Mixed methods are less common than standalone analyses, largely because they require a great deal of effort to pull off successfully. If you choose to pursue mixed methods, it’s especially important to robustly justify your methods here.

Prevent plagiarism, run a free check.

Next, you should indicate how you processed and analysed your data. Avoid going into too much detail: you should not start introducing or discussing any of your results at this stage.

In quantitative research , your analysis will be based on numbers. In your methods section, you can include:

  • How you prepared the data before analysing it (e.g., checking for missing data , removing outliers , transforming variables)
  • Which software you used (e.g., SPSS, Stata or R)
  • Which statistical tests you used (e.g., two-tailed t test , simple linear regression )

In qualitative research, your analysis will be based on language, images, and observations (often involving some form of textual analysis ).

Specific methods might include:

  • Content analysis : Categorising and discussing the meaning of words, phrases and sentences
  • Thematic analysis : Coding and closely examining the data to identify broad themes and patterns
  • Discourse analysis : Studying communication and meaning in relation to their social context

Mixed methods combine the above two research methods, integrating both qualitative and quantitative approaches into one coherent analytical process.

Above all, your methodology section should clearly make the case for why you chose the methods you did. This is especially true if you did not take the most standard approach to your topic. In this case, discuss why other methods were not suitable for your objectives, and show how this approach contributes new knowledge or understanding.

In any case, it should be overwhelmingly clear to your reader that you set yourself up for success in terms of your methodology’s design. Show how your methods should lead to results that are valid and reliable, while leaving the analysis of the meaning, importance, and relevance of your results for your discussion section .

  • Quantitative: Lab-based experiments cannot always accurately simulate real-life situations and behaviours, but they are effective for testing causal relationships between variables .
  • Qualitative: Unstructured interviews usually produce results that cannot be generalised beyond the sample group , but they provide a more in-depth understanding of participants’ perceptions, motivations, and emotions.
  • Mixed methods: Despite issues systematically comparing differing types of data, a solely quantitative study would not sufficiently incorporate the lived experience of each participant, while a solely qualitative study would be insufficiently generalisable.

Remember that your aim is not just to describe your methods, but to show how and why you applied them. Again, it’s critical to demonstrate that your research was rigorously conducted and can be replicated.

1. Focus on your objectives and research questions

The methodology section should clearly show why your methods suit your objectives  and convince the reader that you chose the best possible approach to answering your problem statement and research questions .

2. Cite relevant sources

Your methodology can be strengthened by referencing existing research in your field. This can help you to:

  • Show that you followed established practice for your type of research
  • Discuss how you decided on your approach by evaluating existing research
  • Present a novel methodological approach to address a gap in the literature

3. Write for your audience

Consider how much information you need to give, and avoid getting too lengthy. If you are using methods that are standard for your discipline, you probably don’t need to give a lot of background or justification.

Regardless, your methodology should be a clear, well-structured text that makes an argument for your approach, not just a list of technical details and procedures.

Methodology refers to the overarching strategy and rationale of your research. Developing your methodology involves studying the research methods used in your field and the theories or principles that underpin them, in order to choose the approach that best matches your objectives.

Methods are the specific tools and procedures you use to collect and analyse data (e.g. interviews, experiments , surveys , statistical tests ).

In a dissertation or scientific paper, the methodology chapter or methods section comes after the introduction and before the results , discussion and conclusion .

Depending on the length and type of document, you might also include a literature review or theoretical framework before the methodology.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.

A sample is a subset of individuals from a larger population. Sampling means selecting the group that you will actually collect data from in your research.

For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

Statistical sampling allows you to test a hypothesis about the characteristics of a population. There are various sampling methods you can use to ensure that your sample is representative of the population as a whole.

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The methods section describes actions taken to investigate a research problem and the rationale for the application of specific procedures or techniques used to identify, select, process, and analyze information applied to understanding the problem, thereby, allowing the reader to critically evaluate a study’s overall validity and reliability. The methodology section of a research paper answers two main questions: How was the data collected or generated? And, how was it analyzed? The writing should be direct and precise and always written in the past tense.

Kallet, Richard H. "How to Write the Methods Section of a Research Paper." Respiratory Care 49 (October 2004): 1229-1232.

Importance of a Good Methodology Section

You must explain how you obtained and analyzed your results for the following reasons:

  • Readers need to know how the data was obtained because the method you chose affects the results and, by extension, how you interpreted their significance in the discussion section of your paper.
  • Methodology is crucial for any branch of scholarship because an unreliable method produces unreliable results and, as a consequence, undermines the value of your analysis of the findings.
  • In most cases, there are a variety of different methods you can choose to investigate a research problem. The methodology section of your paper should clearly articulate the reasons why you have chosen a particular procedure or technique.
  • The reader wants to know that the data was collected or generated in a way that is consistent with accepted practice in the field of study. For example, if you are using a multiple choice questionnaire, readers need to know that it offered your respondents a reasonable range of answers to choose from.
  • The method must be appropriate to fulfilling the overall aims of the study. For example, you need to ensure that you have a large enough sample size to be able to generalize and make recommendations based upon the findings.
  • The methodology should discuss the problems that were anticipated and the steps you took to prevent them from occurring. For any problems that do arise, you must describe the ways in which they were minimized or why these problems do not impact in any meaningful way your interpretation of the findings.
  • In the social and behavioral sciences, it is important to always provide sufficient information to allow other researchers to adopt or replicate your methodology. This information is particularly important when a new method has been developed or an innovative use of an existing method is utilized.

Bem, Daryl J. Writing the Empirical Journal Article. Psychology Writing Center. University of Washington; Denscombe, Martyn. The Good Research Guide: For Small-Scale Social Research Projects . 5th edition. Buckingham, UK: Open University Press, 2014; Lunenburg, Frederick C. Writing a Successful Thesis or Dissertation: Tips and Strategies for Students in the Social and Behavioral Sciences . Thousand Oaks, CA: Corwin Press, 2008.

Structure and Writing Style

I.  Groups of Research Methods

There are two main groups of research methods in the social sciences:

  • The e mpirical-analytical group approaches the study of social sciences in a similar manner that researchers study the natural sciences . This type of research focuses on objective knowledge, research questions that can be answered yes or no, and operational definitions of variables to be measured. The empirical-analytical group employs deductive reasoning that uses existing theory as a foundation for formulating hypotheses that need to be tested. This approach is focused on explanation.
  • The i nterpretative group of methods is focused on understanding phenomenon in a comprehensive, holistic way . Interpretive methods focus on analytically disclosing the meaning-making practices of human subjects [the why, how, or by what means people do what they do], while showing how those practices arrange so that it can be used to generate observable outcomes. Interpretive methods allow you to recognize your connection to the phenomena under investigation. However, the interpretative group requires careful examination of variables because it focuses more on subjective knowledge.

II.  Content

The introduction to your methodology section should begin by restating the research problem and underlying assumptions underpinning your study. This is followed by situating the methods you used to gather, analyze, and process information within the overall “tradition” of your field of study and within the particular research design you have chosen to study the problem. If the method you choose lies outside of the tradition of your field [i.e., your review of the literature demonstrates that the method is not commonly used], provide a justification for how your choice of methods specifically addresses the research problem in ways that have not been utilized in prior studies.

The remainder of your methodology section should describe the following:

  • Decisions made in selecting the data you have analyzed or, in the case of qualitative research, the subjects and research setting you have examined,
  • Tools and methods used to identify and collect information, and how you identified relevant variables,
  • The ways in which you processed the data and the procedures you used to analyze that data, and
  • The specific research tools or strategies that you utilized to study the underlying hypothesis and research questions.

In addition, an effectively written methodology section should:

  • Introduce the overall methodological approach for investigating your research problem . Is your study qualitative or quantitative or a combination of both (mixed method)? Are you going to take a special approach, such as action research, or a more neutral stance?
  • Indicate how the approach fits the overall research design . Your methods for gathering data should have a clear connection to your research problem. In other words, make sure that your methods will actually address the problem. One of the most common deficiencies found in research papers is that the proposed methodology is not suitable to achieving the stated objective of your paper.
  • Describe the specific methods of data collection you are going to use , such as, surveys, interviews, questionnaires, observation, archival research. If you are analyzing existing data, such as a data set or archival documents, describe how it was originally created or gathered and by whom. Also be sure to explain how older data is still relevant to investigating the current research problem.
  • Explain how you intend to analyze your results . Will you use statistical analysis? Will you use specific theoretical perspectives to help you analyze a text or explain observed behaviors? Describe how you plan to obtain an accurate assessment of relationships, patterns, trends, distributions, and possible contradictions found in the data.
  • Provide background and a rationale for methodologies that are unfamiliar for your readers . Very often in the social sciences, research problems and the methods for investigating them require more explanation/rationale than widely accepted rules governing the natural and physical sciences. Be clear and concise in your explanation.
  • Provide a justification for subject selection and sampling procedure . For instance, if you propose to conduct interviews, how do you intend to select the sample population? If you are analyzing texts, which texts have you chosen, and why? If you are using statistics, why is this set of data being used? If other data sources exist, explain why the data you chose is most appropriate to addressing the research problem.
  • Provide a justification for case study selection . A common method of analyzing research problems in the social sciences is to analyze specific cases. These can be a person, place, event, phenomenon, or other type of subject of analysis that are either examined as a singular topic of in-depth investigation or multiple topics of investigation studied for the purpose of comparing or contrasting findings. In either method, you should explain why a case or cases were chosen and how they specifically relate to the research problem.
  • Describe potential limitations . Are there any practical limitations that could affect your data collection? How will you attempt to control for potential confounding variables and errors? If your methodology may lead to problems you can anticipate, state this openly and show why pursuing this methodology outweighs the risk of these problems cropping up.

NOTE :   Once you have written all of the elements of the methods section, subsequent revisions should focus on how to present those elements as clearly and as logically as possibly. The description of how you prepared to study the research problem, how you gathered the data, and the protocol for analyzing the data should be organized chronologically. For clarity, when a large amount of detail must be presented, information should be presented in sub-sections according to topic. If necessary, consider using appendices for raw data.

ANOTHER NOTE : If you are conducting a qualitative analysis of a research problem , the methodology section generally requires a more elaborate description of the methods used as well as an explanation of the processes applied to gathering and analyzing of data than is generally required for studies using quantitative methods. Because you are the primary instrument for generating the data [e.g., through interviews or observations], the process for collecting that data has a significantly greater impact on producing the findings. Therefore, qualitative research requires a more detailed description of the methods used.

YET ANOTHER NOTE :   If your study involves interviews, observations, or other qualitative techniques involving human subjects , you may be required to obtain approval from the university's Office for the Protection of Research Subjects before beginning your research. This is not a common procedure for most undergraduate level student research assignments. However, i f your professor states you need approval, you must include a statement in your methods section that you received official endorsement and adequate informed consent from the office and that there was a clear assessment and minimization of risks to participants and to the university. This statement informs the reader that your study was conducted in an ethical and responsible manner. In some cases, the approval notice is included as an appendix to your paper.

III.  Problems to Avoid

Irrelevant Detail The methodology section of your paper should be thorough but concise. Do not provide any background information that does not directly help the reader understand why a particular method was chosen, how the data was gathered or obtained, and how the data was analyzed in relation to the research problem [note: analyzed, not interpreted! Save how you interpreted the findings for the discussion section]. With this in mind, the page length of your methods section will generally be less than any other section of your paper except the conclusion.

Unnecessary Explanation of Basic Procedures Remember that you are not writing a how-to guide about a particular method. You should make the assumption that readers possess a basic understanding of how to investigate the research problem on their own and, therefore, you do not have to go into great detail about specific methodological procedures. The focus should be on how you applied a method , not on the mechanics of doing a method. An exception to this rule is if you select an unconventional methodological approach; if this is the case, be sure to explain why this approach was chosen and how it enhances the overall process of discovery.

Problem Blindness It is almost a given that you will encounter problems when collecting or generating your data, or, gaps will exist in existing data or archival materials. Do not ignore these problems or pretend they did not occur. Often, documenting how you overcame obstacles can form an interesting part of the methodology. It demonstrates to the reader that you can provide a cogent rationale for the decisions you made to minimize the impact of any problems that arose.

Literature Review Just as the literature review section of your paper provides an overview of sources you have examined while researching a particular topic, the methodology section should cite any sources that informed your choice and application of a particular method [i.e., the choice of a survey should include any citations to the works you used to help construct the survey].

It’s More than Sources of Information! A description of a research study's method should not be confused with a description of the sources of information. Such a list of sources is useful in and of itself, especially if it is accompanied by an explanation about the selection and use of the sources. The description of the project's methodology complements a list of sources in that it sets forth the organization and interpretation of information emanating from those sources.

Azevedo, L.F. et al. "How to Write a Scientific Paper: Writing the Methods Section." Revista Portuguesa de Pneumologia 17 (2011): 232-238; Blair Lorrie. “Choosing a Methodology.” In Writing a Graduate Thesis or Dissertation , Teaching Writing Series. (Rotterdam: Sense Publishers 2016), pp. 49-72; Butin, Dan W. The Education Dissertation A Guide for Practitioner Scholars . Thousand Oaks, CA: Corwin, 2010; Carter, Susan. Structuring Your Research Thesis . New York: Palgrave Macmillan, 2012; Kallet, Richard H. “How to Write the Methods Section of a Research Paper.” Respiratory Care 49 (October 2004):1229-1232; Lunenburg, Frederick C. Writing a Successful Thesis or Dissertation: Tips and Strategies for Students in the Social and Behavioral Sciences . Thousand Oaks, CA: Corwin Press, 2008. Methods Section. The Writer’s Handbook. Writing Center. University of Wisconsin, Madison; Rudestam, Kjell Erik and Rae R. Newton. “The Method Chapter: Describing Your Research Plan.” In Surviving Your Dissertation: A Comprehensive Guide to Content and Process . (Thousand Oaks, Sage Publications, 2015), pp. 87-115; What is Interpretive Research. Institute of Public and International Affairs, University of Utah; Writing the Experimental Report: Methods, Results, and Discussion. The Writing Lab and The OWL. Purdue University; Methods and Materials. The Structure, Format, Content, and Style of a Journal-Style Scientific Paper. Department of Biology. Bates College.

Writing Tip

Statistical Designs and Tests? Do Not Fear Them!

Don't avoid using a quantitative approach to analyzing your research problem just because you fear the idea of applying statistical designs and tests. A qualitative approach, such as conducting interviews or content analysis of archival texts, can yield exciting new insights about a research problem, but it should not be undertaken simply because you have a disdain for running a simple regression. A well designed quantitative research study can often be accomplished in very clear and direct ways, whereas, a similar study of a qualitative nature usually requires considerable time to analyze large volumes of data and a tremendous burden to create new paths for analysis where previously no path associated with your research problem had existed.

To locate data and statistics, GO HERE .

Another Writing Tip

Knowing the Relationship Between Theories and Methods

There can be multiple meaning associated with the term "theories" and the term "methods" in social sciences research. A helpful way to delineate between them is to understand "theories" as representing different ways of characterizing the social world when you research it and "methods" as representing different ways of generating and analyzing data about that social world. Framed in this way, all empirical social sciences research involves theories and methods, whether they are stated explicitly or not. However, while theories and methods are often related, it is important that, as a researcher, you deliberately separate them in order to avoid your theories playing a disproportionate role in shaping what outcomes your chosen methods produce.

Introspectively engage in an ongoing dialectic between the application of theories and methods to help enable you to use the outcomes from your methods to interrogate and develop new theories, or ways of framing conceptually the research problem. This is how scholarship grows and branches out into new intellectual territory.

Reynolds, R. Larry. Ways of Knowing. Alternative Microeconomics . Part 1, Chapter 3. Boise State University; The Theory-Method Relationship. S-Cool Revision. United Kingdom.

Yet Another Writing Tip

Methods and the Methodology

Do not confuse the terms "methods" and "methodology." As Schneider notes, a method refers to the technical steps taken to do research . Descriptions of methods usually include defining and stating why you have chosen specific techniques to investigate a research problem, followed by an outline of the procedures you used to systematically select, gather, and process the data [remember to always save the interpretation of data for the discussion section of your paper].

The methodology refers to a discussion of the underlying reasoning why particular methods were used . This discussion includes describing the theoretical concepts that inform the choice of methods to be applied, placing the choice of methods within the more general nature of academic work, and reviewing its relevance to examining the research problem. The methodology section also includes a thorough review of the methods other scholars have used to study the topic.

Bryman, Alan. "Of Methods and Methodology." Qualitative Research in Organizations and Management: An International Journal 3 (2008): 159-168; Schneider, Florian. “What's in a Methodology: The Difference between Method, Methodology, and Theory…and How to Get the Balance Right?” PoliticsEastAsia.com. Chinese Department, University of Leiden, Netherlands.

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How to Write Research Methodology

Last Updated: May 21, 2023 Approved

This article was co-authored by Alexander Ruiz, M.Ed. and by wikiHow staff writer, Jennifer Mueller, JD . Alexander Ruiz is an Educational Consultant and the Educational Director of Link Educational Institute, a tutoring business based in Claremont, California that provides customizable educational plans, subject and test prep tutoring, and college application consulting. With over a decade and a half of experience in the education industry, Alexander coaches students to increase their self-awareness and emotional intelligence while achieving skills and the goal of achieving skills and higher education. He holds a BA in Psychology from Florida International University and an MA in Education from Georgia Southern University. wikiHow marks an article as reader-approved once it receives enough positive feedback. In this case, several readers have written to tell us that this article was helpful to them, earning it our reader-approved status. This article has been viewed 521,205 times.

The research methodology section of any academic research paper gives you the opportunity to convince your readers that your research is useful and will contribute to your field of study. An effective research methodology is grounded in your overall approach – whether qualitative or quantitative – and adequately describes the methods you used. Justify why you chose those methods over others, then explain how those methods will provide answers to your research questions. [1] X Research source

Describing Your Methods

Step 1 Restate your research problem.

  • In your restatement, include any underlying assumptions that you're making or conditions that you're taking for granted. These assumptions will also inform the research methods you've chosen.
  • Generally, state the variables you'll test and the other conditions you're controlling or assuming are equal.

Step 2 Establish your overall methodological approach.

  • If you want to research and document measurable social trends, or evaluate the impact of a particular policy on various variables, use a quantitative approach focused on data collection and statistical analysis.
  • If you want to evaluate people's views or understanding of a particular issue, choose a more qualitative approach.
  • You can also combine the two. For example, you might look primarily at a measurable social trend, but also interview people and get their opinions on how that trend is affecting their lives.

Step 3 Define how you collected or generated data.

  • For example, if you conducted a survey, you would describe the questions included in the survey, where and how the survey was conducted (such as in person, online, over the phone), how many surveys were distributed, and how long your respondents had to complete the survey.
  • Include enough detail that your study can be replicated by others in your field, even if they may not get the same results you did. [4] X Research source

Step 4 Provide background for uncommon methods.

  • Qualitative research methods typically require more detailed explanation than quantitative methods.
  • Basic investigative procedures don't need to be explained in detail. Generally, you can assume that your readers have a general understanding of common research methods that social scientists use, such as surveys or focus groups.

Step 5 Cite any sources that contributed to your choice of methodology.

  • For example, suppose you conducted a survey and used a couple of other research papers to help construct the questions on your survey. You would mention those as contributing sources.

Justifying Your Choice of Methods

Step 1 Explain your selection criteria for data collection.

  • Describe study participants specifically, and list any inclusion or exclusion criteria you used when forming your group of participants.
  • Justify the size of your sample, if applicable, and describe how this affects whether your study can be generalized to larger populations. For example, if you conducted a survey of 30 percent of the student population of a university, you could potentially apply those results to the student body as a whole, but maybe not to students at other universities.

Step 2 Distinguish your research from any weaknesses in your methods.

  • Reading other research papers is a good way to identify potential problems that commonly arise with various methods. State whether you actually encountered any of these common problems during your research.

Step 3 Describe how you overcame obstacles.

  • If you encountered any problems as you collected data, explain clearly the steps you took to minimize the effect that problem would have on your results.

Step 4 Evaluate other methods you could have used.

  • In some cases, this may be as simple as stating that while there were numerous studies using one method, there weren't any using your method, which caused a gap in understanding of the issue.
  • For example, there may be multiple papers providing quantitative analysis of a particular social trend. However, none of these papers looked closely at how this trend was affecting the lives of people.

Connecting Your Methods to Your Research Goals

Step 1 Describe how you analyzed your results.

  • Depending on your research questions, you may be mixing quantitative and qualitative analysis – just as you could potentially use both approaches. For example, you might do a statistical analysis, and then interpret those statistics through a particular theoretical lens.

Step 2 Explain how your analysis suits your research goals.

  • For example, suppose you're researching the effect of college education on family farms in rural America. While you could do interviews of college-educated people who grew up on a family farm, that would not give you a picture of the overall effect. A quantitative approach and statistical analysis would give you a bigger picture.

Step 3 Identify how your analysis answers your research questions.

  • If in answering your research questions, your findings have raised other questions that may require further research, state these briefly.
  • You can also include here any limitations to your methods, or questions that weren't answered through your research.

Step 4 Assess whether your findings can be transferred or generalized.

  • Generalization is more typically used in quantitative research. If you have a well-designed sample, you can statistically apply your results to the larger population your sample belongs to.

Template to Write Research Methodology

methodology in research steps

Community Q&A

AneHane

  • Organize your methodology section chronologically, starting with how you prepared to conduct your research methods, how you gathered data, and how you analyzed that data. [13] X Research source Thanks Helpful 0 Not Helpful 0
  • Write your research methodology section in past tense, unless you're submitting the methodology section before the research described has been carried out. [14] X Research source Thanks Helpful 2 Not Helpful 0
  • Discuss your plans in detail with your advisor or supervisor before committing to a particular methodology. They can help identify possible flaws in your study. [15] X Research source Thanks Helpful 0 Not Helpful 0

methodology in research steps

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  • ↑ http://expertjournals.com/how-to-write-a-research-methodology-for-your-academic-article/
  • ↑ http://libguides.usc.edu/writingguide/methodology
  • ↑ https://www.skillsyouneed.com/learn/dissertation-methodology.html
  • ↑ https://uir.unisa.ac.za/bitstream/handle/10500/4245/05Chap%204_Research%20methodology%20and%20design.pdf
  • ↑ https://elc.polyu.edu.hk/FYP/html/method.htm

About This Article

Alexander Ruiz, M.Ed.

To write a research methodology, start with a section that outlines the problems or questions you'll be studying, including your hypotheses or whatever it is you're setting out to prove. Then, briefly explain why you chose to use either a qualitative or quantitative approach for your study. Next, go over when and where you conducted your research and what parameters you used to ensure you were objective. Finally, cite any sources you used to decide on the methodology for your research. To learn how to justify your choice of methods in your research methodology, scroll down! Did this summary help you? Yes No

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What Is Research Methodology? A Plain-Language Explanation & Definition (With Examples)

By Derek Jansen (MBA)  and Kerryn Warren (PhD) | June 2020 (Last updated April 2023)

If you’re new to formal academic research, it’s quite likely that you’re feeling a little overwhelmed by all the technical lingo that gets thrown around. And who could blame you – “research methodology”, “research methods”, “sampling strategies”… it all seems never-ending!

In this post, we’ll demystify the landscape with plain-language explanations and loads of examples (including easy-to-follow videos), so that you can approach your dissertation, thesis or research project with confidence. Let’s get started.

Research Methodology 101

  • What exactly research methodology means
  • What qualitative , quantitative and mixed methods are
  • What sampling strategy is
  • What data collection methods are
  • What data analysis methods are
  • How to choose your research methodology
  • Example of a research methodology

Free Webinar: Research Methodology 101

What is research methodology?

Research methodology simply refers to the practical “how” of a research study. More specifically, it’s about how  a researcher  systematically designs a study  to ensure valid and reliable results that address the research aims, objectives and research questions . Specifically, how the researcher went about deciding:

  • What type of data to collect (e.g., qualitative or quantitative data )
  • Who  to collect it from (i.e., the sampling strategy )
  • How to  collect  it (i.e., the data collection method )
  • How to  analyse  it (i.e., the data analysis methods )

Within any formal piece of academic research (be it a dissertation, thesis or journal article), you’ll find a research methodology chapter or section which covers the aspects mentioned above. Importantly, a good methodology chapter explains not just   what methodological choices were made, but also explains  why they were made. In other words, the methodology chapter should justify  the design choices, by showing that the chosen methods and techniques are the best fit for the research aims, objectives and research questions. 

So, it’s the same as research design?

Not quite. As we mentioned, research methodology refers to the collection of practical decisions regarding what data you’ll collect, from who, how you’ll collect it and how you’ll analyse it. Research design, on the other hand, is more about the overall strategy you’ll adopt in your study. For example, whether you’ll use an experimental design in which you manipulate one variable while controlling others. You can learn more about research design and the various design types here .

Need a helping hand?

methodology in research steps

What are qualitative, quantitative and mixed-methods?

Qualitative, quantitative and mixed-methods are different types of methodological approaches, distinguished by their focus on words , numbers or both . This is a bit of an oversimplification, but its a good starting point for understanding.

Let’s take a closer look.

Qualitative research refers to research which focuses on collecting and analysing words (written or spoken) and textual or visual data, whereas quantitative research focuses on measurement and testing using numerical data . Qualitative analysis can also focus on other “softer” data points, such as body language or visual elements.

It’s quite common for a qualitative methodology to be used when the research aims and research questions are exploratory  in nature. For example, a qualitative methodology might be used to understand peoples’ perceptions about an event that took place, or a political candidate running for president. 

Contrasted to this, a quantitative methodology is typically used when the research aims and research questions are confirmatory  in nature. For example, a quantitative methodology might be used to measure the relationship between two variables (e.g. personality type and likelihood to commit a crime) or to test a set of hypotheses .

As you’ve probably guessed, the mixed-method methodology attempts to combine the best of both qualitative and quantitative methodologies to integrate perspectives and create a rich picture. If you’d like to learn more about these three methodological approaches, be sure to watch our explainer video below.

What is sampling strategy?

Simply put, sampling is about deciding who (or where) you’re going to collect your data from . Why does this matter? Well, generally it’s not possible to collect data from every single person in your group of interest (this is called the “population”), so you’ll need to engage a smaller portion of that group that’s accessible and manageable (this is called the “sample”).

How you go about selecting the sample (i.e., your sampling strategy) will have a major impact on your study.  There are many different sampling methods  you can choose from, but the two overarching categories are probability   sampling and  non-probability   sampling .

Probability sampling  involves using a completely random sample from the group of people you’re interested in. This is comparable to throwing the names all potential participants into a hat, shaking it up, and picking out the “winners”. By using a completely random sample, you’ll minimise the risk of selection bias and the results of your study will be more generalisable  to the entire population. 

Non-probability sampling , on the other hand,  doesn’t use a random sample . For example, it might involve using a convenience sample, which means you’d only interview or survey people that you have access to (perhaps your friends, family or work colleagues), rather than a truly random sample. With non-probability sampling, the results are typically not generalisable .

To learn more about sampling methods, be sure to check out the video below.

What are data collection methods?

As the name suggests, data collection methods simply refers to the way in which you go about collecting the data for your study. Some of the most common data collection methods include:

  • Interviews (which can be unstructured, semi-structured or structured)
  • Focus groups and group interviews
  • Surveys (online or physical surveys)
  • Observations (watching and recording activities)
  • Biophysical measurements (e.g., blood pressure, heart rate, etc.)
  • Documents and records (e.g., financial reports, court records, etc.)

The choice of which data collection method to use depends on your overall research aims and research questions , as well as practicalities and resource constraints. For example, if your research is exploratory in nature, qualitative methods such as interviews and focus groups would likely be a good fit. Conversely, if your research aims to measure specific variables or test hypotheses, large-scale surveys that produce large volumes of numerical data would likely be a better fit.

What are data analysis methods?

Data analysis methods refer to the methods and techniques that you’ll use to make sense of your data. These can be grouped according to whether the research is qualitative  (words-based) or quantitative (numbers-based).

Popular data analysis methods in qualitative research include:

  • Qualitative content analysis
  • Thematic analysis
  • Discourse analysis
  • Narrative analysis
  • Interpretative phenomenological analysis (IPA)
  • Visual analysis (of photographs, videos, art, etc.)

Qualitative data analysis all begins with data coding , after which an analysis method is applied. In some cases, more than one analysis method is used, depending on the research aims and research questions . In the video below, we explore some  common qualitative analysis methods, along with practical examples.  

Moving on to the quantitative side of things, popular data analysis methods in this type of research include:

  • Descriptive statistics (e.g. means, medians, modes )
  • Inferential statistics (e.g. correlation, regression, structural equation modelling)

Again, the choice of which data collection method to use depends on your overall research aims and objectives , as well as practicalities and resource constraints. In the video below, we explain some core concepts central to quantitative analysis.

How do I choose a research methodology?

As you’ve probably picked up by now, your research aims and objectives have a major influence on the research methodology . So, the starting point for developing your research methodology is to take a step back and look at the big picture of your research, before you make methodology decisions. The first question you need to ask yourself is whether your research is exploratory or confirmatory in nature.

If your research aims and objectives are primarily exploratory in nature, your research will likely be qualitative and therefore you might consider qualitative data collection methods (e.g. interviews) and analysis methods (e.g. qualitative content analysis). 

Conversely, if your research aims and objective are looking to measure or test something (i.e. they’re confirmatory), then your research will quite likely be quantitative in nature, and you might consider quantitative data collection methods (e.g. surveys) and analyses (e.g. statistical analysis).

Designing your research and working out your methodology is a large topic, which we cover extensively on the blog . For now, however, the key takeaway is that you should always start with your research aims, objectives and research questions (the golden thread). Every methodological choice you make needs align with those three components. 

Example of a research methodology chapter

In the video below, we provide a detailed walkthrough of a research methodology from an actual dissertation, as well as an overview of our free methodology template .

methodology in research steps

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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199 Comments

Leo Balanlay

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Derek Jansen

You’re most welcome, Leo. Best of luck with your research!

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Visor Likali

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Pondris Patrick

I am writing a APA Format paper . I using questionnaire with 120 STDs teacher for my participant. Can you write me mthology for this research. Send it through email sent. Just need a sample as an example please. My topic is ” impacts of overcrowding on students learning

Thanks for your comment.

We can’t write your methodology for you. If you’re looking for samples, you should be able to find some sample methodologies on Google. Alternatively, you can download some previous dissertations from a dissertation directory and have a look at the methodology chapters therein.

All the best with your research.

Anon

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Keke

Thank you. Explicit explanation

Sophy

Thank you, Derek and Kerryn, for making this simple to understand. I’m currently at the inception stage of my research.

Luyanda

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Beulah Emmanuel

excellent explanation

Gino Raz

I’m currently working on my master’s thesis, thanks for this! I’m certain that I will use Qualitative methodology.

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Yonas Tesheme

I am currently doing my dissertation proposal and I am sure that I will do quantitative research. Thank you very much it was extremely helpful.

zahid t ahmad

Very interesting and informative yet I would like to know about examples of Research Questions as well, if possible.

Maisnam loyalakla

I’m about to submit a research presentation, I have come to understand from your simplification on understanding research methodology. My research will be mixed methodology, qualitative as well as quantitative. So aim and objective of mixed method would be both exploratory and confirmatory. Thanks you very much for your guidance.

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Lika

I’m going to write synopsis which will be quantitative research method and I don’t know how to frame my topic, can I kindly get some ideas..

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Michael

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WALLACE

Well explained. Now I know my research methodology will be qualitative and exploratory. Thank you so much, keep up the good work

GEORGE REUBEN MSHEGAME

Well explained, thank you very much.

Ainembabazi Rose

This is good explanation, I have understood the different methods of research. Thanks a lot.

Kamran Saeed

Great work…very well explanation

Hyacinth Chebe Ukwuani

Thanks Derek. Kerryn was just fantastic!

Great to hear that, Hyacinth. Best of luck with your research!

Matobela Joel Marabi

Its a good templates very attractive and important to PhD students and lectuter

Thanks for the feedback, Matobela. Good luck with your research methodology.

Elie

Thank you. This is really helpful.

You’re very welcome, Elie. Good luck with your research methodology.

Sakina Dalal

Well explained thanks

Edward

This is a very helpful site especially for young researchers at college. It provides sufficient information to guide students and equip them with the necessary foundation to ask any other questions aimed at deepening their understanding.

Thanks for the kind words, Edward. Good luck with your research!

Ngwisa Marie-claire NJOTU

Thank you. I have learned a lot.

Great to hear that, Ngwisa. Good luck with your research methodology!

Claudine

Thank you for keeping your presentation simples and short and covering key information for research methodology. My key takeaway: Start with defining your research objective the other will depend on the aims of your research question.

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My name is Zanele I would like to be assisted with my research , and the topic is shortage of nursing staff globally want are the causes , effects on health, patients and community and also globally

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Thanks for making it simple and clear. It greatly helped in understanding research methodology. Regards.

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This is well simplified and straight to the point

Gabriel mugangavari

Thank you Dr

Dina Haj Ibrahim

I was given an assignment to research 2 publications and describe their research methodology? I don’t know how to start this task can someone help me?

Sure. You’re welcome to book an initial consultation with one of our Research Coaches to discuss how we can assist – https://gradcoach.com/book/new/ .

BENSON ROSEMARY

Thanks a lot I am relieved of a heavy burden.keep up with the good work

Ngaka Mokoena

I’m very much grateful Dr Derek. I’m planning to pursue one of the careers that really needs one to be very much eager to know. There’s a lot of research to do and everything, but since I’ve gotten this information I will use it to the best of my potential.

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really nice explanation thank you so much

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I’m so grateful finding this site, it’s really helpful…….every term well explained and provide accurate understanding especially to student going into an in-depth research for the very first time, even though my lecturer already explained this topic to the class, I think I got the clear and efficient explanation here, much thanks to the author.

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I would like to be assisted with my research topic : Literature Review and research methodologies. My topic is : what is the relationship between unemployment and economic growth?

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Short but sweet.Thank you

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Informative article. Thanks for your detailed information.

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I’m currently working on my Ph.D. thesis. Thanks a lot, Derek and Kerryn, Well-organized sequences, facilitate the readers’ following.

Tejal

great article for someone who does not have any background can even understand

Hasan Chowdhury

I am a bit confused about research design and methodology. Are they the same? If not, what are the differences and how are they related?

Thanks in advance.

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concise and informative.

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Thank you very much

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How can we site this article is Harvard style?

Anne

Very well written piece that afforded better understanding of the concept. Thank you!

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Am a new researcher trying to learn how best to write a research proposal. I find your article spot on and want to download the free template but finding difficulties. Can u kindly send it to my email, the free download entitled, “Free Download: Research Proposal Template (with Examples)”.

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orebotswe morokane

how do i reference this?

Roy

MLA Jansen, Derek, and Kerryn Warren. “What (Exactly) Is Research Methodology?” Grad Coach, June 2021, gradcoach.com/what-is-research-methodology/.

APA Jansen, D., & Warren, K. (2021, June). What (Exactly) Is Research Methodology? Grad Coach. https://gradcoach.com/what-is-research-methodology/

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What is Research Methodology? Definition, Types, and Examples

methodology in research steps

Research methodology 1,2 is a structured and scientific approach used to collect, analyze, and interpret quantitative or qualitative data to answer research questions or test hypotheses. A research methodology is like a plan for carrying out research and helps keep researchers on track by limiting the scope of the research. Several aspects must be considered before selecting an appropriate research methodology, such as research limitations and ethical concerns that may affect your research.

The research methodology section in a scientific paper describes the different methodological choices made, such as the data collection and analysis methods, and why these choices were selected. The reasons should explain why the methods chosen are the most appropriate to answer the research question. A good research methodology also helps ensure the reliability and validity of the research findings. There are three types of research methodology—quantitative, qualitative, and mixed-method, which can be chosen based on the research objectives.

What is research methodology ?

A research methodology describes the techniques and procedures used to identify and analyze information regarding a specific research topic. It is a process by which researchers design their study so that they can achieve their objectives using the selected research instruments. It includes all the important aspects of research, including research design, data collection methods, data analysis methods, and the overall framework within which the research is conducted. While these points can help you understand what is research methodology, you also need to know why it is important to pick the right methodology.

Why is research methodology important?

Having a good research methodology in place has the following advantages: 3

  • Helps other researchers who may want to replicate your research; the explanations will be of benefit to them.
  • You can easily answer any questions about your research if they arise at a later stage.
  • A research methodology provides a framework and guidelines for researchers to clearly define research questions, hypotheses, and objectives.
  • It helps researchers identify the most appropriate research design, sampling technique, and data collection and analysis methods.
  • A sound research methodology helps researchers ensure that their findings are valid and reliable and free from biases and errors.
  • It also helps ensure that ethical guidelines are followed while conducting research.
  • A good research methodology helps researchers in planning their research efficiently, by ensuring optimum usage of their time and resources.

Writing the methods section of a research paper? Let Paperpal help you achieve perfection

Types of research methodology.

There are three types of research methodology based on the type of research and the data required. 1

  • Quantitative research methodology focuses on measuring and testing numerical data. This approach is good for reaching a large number of people in a short amount of time. This type of research helps in testing the causal relationships between variables, making predictions, and generalizing results to wider populations.
  • Qualitative research methodology examines the opinions, behaviors, and experiences of people. It collects and analyzes words and textual data. This research methodology requires fewer participants but is still more time consuming because the time spent per participant is quite large. This method is used in exploratory research where the research problem being investigated is not clearly defined.
  • Mixed-method research methodology uses the characteristics of both quantitative and qualitative research methodologies in the same study. This method allows researchers to validate their findings, verify if the results observed using both methods are complementary, and explain any unexpected results obtained from one method by using the other method.

What are the types of sampling designs in research methodology?

Sampling 4 is an important part of a research methodology and involves selecting a representative sample of the population to conduct the study, making statistical inferences about them, and estimating the characteristics of the whole population based on these inferences. There are two types of sampling designs in research methodology—probability and nonprobability.

  • Probability sampling

In this type of sampling design, a sample is chosen from a larger population using some form of random selection, that is, every member of the population has an equal chance of being selected. The different types of probability sampling are:

  • Systematic —sample members are chosen at regular intervals. It requires selecting a starting point for the sample and sample size determination that can be repeated at regular intervals. This type of sampling method has a predefined range; hence, it is the least time consuming.
  • Stratified —researchers divide the population into smaller groups that don’t overlap but represent the entire population. While sampling, these groups can be organized, and then a sample can be drawn from each group separately.
  • Cluster —the population is divided into clusters based on demographic parameters like age, sex, location, etc.
  • Convenience —selects participants who are most easily accessible to researchers due to geographical proximity, availability at a particular time, etc.
  • Purposive —participants are selected at the researcher’s discretion. Researchers consider the purpose of the study and the understanding of the target audience.
  • Snowball —already selected participants use their social networks to refer the researcher to other potential participants.
  • Quota —while designing the study, the researchers decide how many people with which characteristics to include as participants. The characteristics help in choosing people most likely to provide insights into the subject.

What are data collection methods?

During research, data are collected using various methods depending on the research methodology being followed and the research methods being undertaken. Both qualitative and quantitative research have different data collection methods, as listed below.

Qualitative research 5

  • One-on-one interviews: Helps the interviewers understand a respondent’s subjective opinion and experience pertaining to a specific topic or event
  • Document study/literature review/record keeping: Researchers’ review of already existing written materials such as archives, annual reports, research articles, guidelines, policy documents, etc.
  • Focus groups: Constructive discussions that usually include a small sample of about 6-10 people and a moderator, to understand the participants’ opinion on a given topic.
  • Qualitative observation : Researchers collect data using their five senses (sight, smell, touch, taste, and hearing).

Quantitative research 6

  • Sampling: The most common type is probability sampling.
  • Interviews: Commonly telephonic or done in-person.
  • Observations: Structured observations are most commonly used in quantitative research. In this method, researchers make observations about specific behaviors of individuals in a structured setting.
  • Document review: Reviewing existing research or documents to collect evidence for supporting the research.
  • Surveys and questionnaires. Surveys can be administered both online and offline depending on the requirement and sample size.

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What are data analysis methods.

The data collected using the various methods for qualitative and quantitative research need to be analyzed to generate meaningful conclusions. These data analysis methods 7 also differ between quantitative and qualitative research.

Quantitative research involves a deductive method for data analysis where hypotheses are developed at the beginning of the research and precise measurement is required. The methods include statistical analysis applications to analyze numerical data and are grouped into two categories—descriptive and inferential.

Descriptive analysis is used to describe the basic features of different types of data to present it in a way that ensures the patterns become meaningful. The different types of descriptive analysis methods are:

  • Measures of frequency (count, percent, frequency)
  • Measures of central tendency (mean, median, mode)
  • Measures of dispersion or variation (range, variance, standard deviation)
  • Measure of position (percentile ranks, quartile ranks)

Inferential analysis is used to make predictions about a larger population based on the analysis of the data collected from a smaller population. This analysis is used to study the relationships between different variables. Some commonly used inferential data analysis methods are:

  • Correlation: To understand the relationship between two or more variables.
  • Cross-tabulation: Analyze the relationship between multiple variables.
  • Regression analysis: Study the impact of independent variables on the dependent variable.
  • Frequency tables: To understand the frequency of data.
  • Analysis of variance: To test the degree to which two or more variables differ in an experiment.

Qualitative research involves an inductive method for data analysis where hypotheses are developed after data collection. The methods include:

  • Content analysis: For analyzing documented information from text and images by determining the presence of certain words or concepts in texts.
  • Narrative analysis: For analyzing content obtained from sources such as interviews, field observations, and surveys. The stories and opinions shared by people are used to answer research questions.
  • Discourse analysis: For analyzing interactions with people considering the social context, that is, the lifestyle and environment, under which the interaction occurs.
  • Grounded theory: Involves hypothesis creation by data collection and analysis to explain why a phenomenon occurred.
  • Thematic analysis: To identify important themes or patterns in data and use these to address an issue.

How to choose a research methodology?

Here are some important factors to consider when choosing a research methodology: 8

  • Research objectives, aims, and questions —these would help structure the research design.
  • Review existing literature to identify any gaps in knowledge.
  • Check the statistical requirements —if data-driven or statistical results are needed then quantitative research is the best. If the research questions can be answered based on people’s opinions and perceptions, then qualitative research is most suitable.
  • Sample size —sample size can often determine the feasibility of a research methodology. For a large sample, less effort- and time-intensive methods are appropriate.
  • Constraints —constraints of time, geography, and resources can help define the appropriate methodology.

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How to write a research methodology .

A research methodology should include the following components: 3,9

  • Research design —should be selected based on the research question and the data required. Common research designs include experimental, quasi-experimental, correlational, descriptive, and exploratory.
  • Research method —this can be quantitative, qualitative, or mixed-method.
  • Reason for selecting a specific methodology —explain why this methodology is the most suitable to answer your research problem.
  • Research instruments —explain the research instruments you plan to use, mainly referring to the data collection methods such as interviews, surveys, etc. Here as well, a reason should be mentioned for selecting the particular instrument.
  • Sampling —this involves selecting a representative subset of the population being studied.
  • Data collection —involves gathering data using several data collection methods, such as surveys, interviews, etc.
  • Data analysis —describe the data analysis methods you will use once you’ve collected the data.
  • Research limitations —mention any limitations you foresee while conducting your research.
  • Validity and reliability —validity helps identify the accuracy and truthfulness of the findings; reliability refers to the consistency and stability of the results over time and across different conditions.
  • Ethical considerations —research should be conducted ethically. The considerations include obtaining consent from participants, maintaining confidentiality, and addressing conflicts of interest.

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Frequently Asked Questions

Q1. What are the key components of research methodology?

A1. A good research methodology has the following key components:

  • Research design
  • Data collection procedures
  • Data analysis methods
  • Ethical considerations

Q2. Why is ethical consideration important in research methodology?

A2. Ethical consideration is important in research methodology to ensure the readers of the reliability and validity of the study. Researchers must clearly mention the ethical norms and standards followed during the conduct of the research and also mention if the research has been cleared by any institutional board. The following 10 points are the important principles related to ethical considerations: 10

  • Participants should not be subjected to harm.
  • Respect for the dignity of participants should be prioritized.
  • Full consent should be obtained from participants before the study.
  • Participants’ privacy should be ensured.
  • Confidentiality of the research data should be ensured.
  • Anonymity of individuals and organizations participating in the research should be maintained.
  • The aims and objectives of the research should not be exaggerated.
  • Affiliations, sources of funding, and any possible conflicts of interest should be declared.
  • Communication in relation to the research should be honest and transparent.
  • Misleading information and biased representation of primary data findings should be avoided.

Q3. What is the difference between methodology and method?

A3. Research methodology is different from a research method, although both terms are often confused. Research methods are the tools used to gather data, while the research methodology provides a framework for how research is planned, conducted, and analyzed. The latter guides researchers in making decisions about the most appropriate methods for their research. Research methods refer to the specific techniques, procedures, and tools used by researchers to collect, analyze, and interpret data, for instance surveys, questionnaires, interviews, etc.

Research methodology is, thus, an integral part of a research study. It helps ensure that you stay on track to meet your research objectives and answer your research questions using the most appropriate data collection and analysis tools based on your research design.

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  • Research methodologies. Pfeiffer Library website. Accessed August 15, 2023. https://library.tiffin.edu/researchmethodologies/whatareresearchmethodologies
  • Types of research methodology. Eduvoice website. Accessed August 16, 2023. https://eduvoice.in/types-research-methodology/
  • The basics of research methodology: A key to quality research. Voxco. Accessed August 16, 2023. https://www.voxco.com/blog/what-is-research-methodology/
  • Sampling methods: Types with examples. QuestionPro website. Accessed August 16, 2023. https://www.questionpro.com/blog/types-of-sampling-for-social-research/
  • What is qualitative research? Methods, types, approaches, examples. Researcher.Life blog. Accessed August 15, 2023. https://researcher.life/blog/article/what-is-qualitative-research-methods-types-examples/
  • What is quantitative research? Definition, methods, types, and examples. Researcher.Life blog. Accessed August 15, 2023. https://researcher.life/blog/article/what-is-quantitative-research-types-and-examples/
  • Data analysis in research: Types & methods. QuestionPro website. Accessed August 16, 2023. https://www.questionpro.com/blog/data-analysis-in-research/#Data_analysis_in_qualitative_research
  • Factors to consider while choosing the right research methodology. PhD Monster website. Accessed August 17, 2023. https://www.phdmonster.com/factors-to-consider-while-choosing-the-right-research-methodology/
  • What is research methodology? Research and writing guides. Accessed August 14, 2023. https://paperpile.com/g/what-is-research-methodology/
  • Ethical considerations. Business research methodology website. Accessed August 17, 2023. https://research-methodology.net/research-methodology/ethical-considerations/

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Research Process Steps: What they are + How To Follow

There are various approaches to conducting basic and applied research. This article explains the research process steps you should know.

There are various approaches to conducting basic and applied research. This article explains the research process steps you should know. Whether you are doing basic research or applied research, there are many ways of doing it. In some ways, each research study is unique since it is conducted at a different time and place.

Conducting research might be difficult, but there are clear processes to follow. The research process starts with a broad idea for a topic. This article will assist you through the research process steps, helping you focus and develop your topic.

Research Process Steps

The research process consists of a series of systematic procedures that a researcher must go through in order to generate knowledge that will be considered valuable by the project and focus on the relevant topic.

To conduct effective research, you must understand the research process steps and follow them. Here are a few steps in the research process to make it easier for you:

10 research process steps

Step 1: Identify the Problem

Finding an issue or formulating a research question is the first step. A well-defined research problem will guide the researcher through all stages of the research process, from setting objectives to choosing a technique. There are a number of approaches to get insight into a topic and gain a better understanding of it. Such as:

  • A preliminary survey
  • Case studies
  • Interviews with a small group of people
  • Observational survey

Step 2: Evaluate the Literature

A thorough examination of the relevant studies is essential to the research process . It enables the researcher to identify the precise aspects of the problem. Once a problem has been found, the investigator or researcher needs to find out more about it.

This stage gives problem-zone background. It teaches the investigator about previous research, how they were conducted, and its conclusions. The researcher can build consistency between his work and others through a literature review. Such a review exposes the researcher to a more significant body of knowledge and helps him follow the research process efficiently.

Step 3: Create Hypotheses

Formulating an original hypothesis is the next logical step after narrowing down the research topic and defining it. A belief solves logical relationships between variables. In order to establish a hypothesis, a researcher must have a certain amount of expertise in the field. 

It is important for researchers to keep in mind while formulating a hypothesis that it must be based on the research topic. Researchers are able to concentrate their efforts and stay committed to their objectives when they develop theories to guide their work.

Step 4: The Research Design

Research design is the plan for achieving objectives and answering research questions. It outlines how to get the relevant information. Its goal is to design research to test hypotheses, address the research questions, and provide decision-making insights.

The research design aims to minimize the time, money, and effort required to acquire meaningful evidence. This plan fits into four categories:

  • Exploration and Surveys
  • Data Analysis
  • Observation

Step 5: Describe Population

Research projects usually look at a specific group of people, facilities, or how technology is used in the business. In research, the term population refers to this study group. The research topic and purpose help determine the study group.

Suppose a researcher wishes to investigate a certain group of people in the community. In that case, the research could target a specific age group, males or females, a geographic location, or an ethnic group. A final step in a study’s design is to specify its sample or population so that the results may be generalized.

Step 6: Data Collection

Data collection is important in obtaining the knowledge or information required to answer the research issue. Every research collected data, either from the literature or the people being studied. Data must be collected from the two categories of researchers. These sources may provide primary data.

  • Questionnaire

Secondary data categories are:

  • Literature survey
  • Official, unofficial reports
  • An approach based on library resources

Step 7: Data Analysis

During research design, the researcher plans data analysis. After collecting data, the researcher analyzes it. The data is examined based on the approach in this step. The research findings are reviewed and reported.

Data analysis involves a number of closely related stages, such as setting up categories, applying these categories to raw data through coding and tabulation, and then drawing statistical conclusions. The researcher can examine the acquired data using a variety of statistical methods.

Step 8: The Report-writing

After completing these steps, the researcher must prepare a report detailing his findings. The report must be carefully composed with the following in mind:

  • The Layout: On the first page, the title, date, acknowledgments, and preface should be on the report. A table of contents should be followed by a list of tables, graphs, and charts if any.
  • Introduction: It should state the research’s purpose and methods. This section should include the study’s scope and limits.
  • Summary of Findings: A non-technical summary of findings and recommendations will follow the introduction. The findings should be summarized if they’re lengthy.
  • Principal Report: The main body of the report should make sense and be broken up into sections that are easy to understand.
  • Conclusion: The researcher should restate his findings at the end of the main text. It’s the final result.

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The research process involves several steps that make it easy to complete the research successfully. The steps in the research process described above depend on each other, and the order must be kept. So, if we want to do a research project, we should follow the research process steps.

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Research Process: 8 Steps in Research Process

what is rsearch process

The research process starts with identifying a research problem and conducting a literature review to understand the context. The researcher sets research questions, objectives, and hypotheses based on the research problem.

A research study design is formed to select a sample size and collect data after processing and analyzing the collected data and the research findings presented in a research report.

What is the Research Process?

There are a variety of approaches to research in any field of investigation, irrespective of whether it is applied research or basic research. Each research study will be unique in some ways because of the particular time, setting, environment, and place it is being undertaken.

Nevertheless, all research endeavors share a common goal of furthering our understanding of the problem, and thus, all traverse through certain primary stages, forming a process called the research process.

Understanding the research process is necessary to effectively carry out research and sequence the stages inherent in the process.

How Research Process Work?

Research Process: 8 Steps in Research Process

Eight steps research process is, in essence, part and parcel of a research proposal. It is an outline of the commitment that you intend to follow in executing a research study.

A close examination of the above stages reveals that each of these stages, by and large, is dependent upon the others.

One cannot analyze data (step 7) unless he has collected data (step 6). One cannot write a report (step 8) unless he has collected and analyzed data (step 7).

Research then is a system of interdependent related stages. Violation of this sequence can cause irreparable harm to the study.

It is also true that several alternatives are available to the researcher during each stage stated above. A research process can be compared with a route map.

The map analogy is useful for the researcher because several alternatives exist at each stage of the research process.

Choosing the best alternative in terms of time constraints, money, and human resources in our research decision is our primary goal.

Before explaining the stages of the research process, we explain the term ‘iterative’ appearing within the oval-shaped diagram at the center of the schematic diagram.

The key to a successful research project ultimately lies in iteration: the process of returning again and again to the identification of the research problems, methodology, data collection, etc., which leads to new ideas, revisions, and improvements.

By discussing the research project with advisers and peers, one will often find that new research questions need to be added, variables to be omitted, added or redefined, and other changes to be made. As a proposed study is examined and reexamined from different perspectives, it may begin to transform and take a different shape.

This is expected and is an essential component of a good research study.

Besides, examining study methods and data collected from different viewpoints is important to ensure a comprehensive approach to the research question.

In conclusion, there is seldom any single strategy or formula for developing a successful research study, but it is essential to realize that the research process is cyclical and iterative.

What is the primary purpose of the research process?

The research process aims to identify a research problem, understand its context through a literature review, set research questions and objectives, design a research study, select a sample, collect data, analyze the data, and present the findings in a research report.

Why is the research design important in the research process?

The research design is the blueprint for fulfilling objectives and answering research questions. It specifies the methods and procedures for collecting, processing, and analyzing data, ensuring the study is structured and systematic.

8 Steps of Research Process

Identifying the research problem.

Identifying the Research Problem

The first and foremost task in the entire process of scientific research is to identify a research problem .

A well-identified problem will lead the researcher to accomplish all-important phases of the research process, from setting objectives to selecting the research methodology .

But the core question is: whether all problems require research.

We have countless problems around us, but all we encounter do not qualify as research problems; thus, these do not need to be researched.

Keeping this point in mind, we must draw a line between research and non-research problems.

Intuitively, researchable problems are those that have a possibility of thorough verification investigation, which can be effected through the analysis and collection of data. In contrast, the non-research problems do not need to go through these processes.

Researchers need to identify both;

Non-Research Problems

Statement of the problem, justifying the problem, analyzing the problem.

A non-research problem does not require any research to arrive at a solution. Intuitively, a non-researchable problem consists of vague details and cannot be resolved through research.

It is a managerial or built-in problem that may be solved at the administrative or management level. The answer to any question raised in a non-research setting is almost always obvious.

The cholera outbreak, for example, following a severe flood, is a common phenomenon in many communities. The reason for this is known. It is thus not a research problem.

Similarly, the reasons for the sudden rise in prices of many essential commodities following the announcement of the budget by the Finance Minister need no investigation. Hence it is not a problem that needs research.

How is a research problem different from a non-research problem?

A research problem is a perceived difficulty that requires thorough verification and investigation through data analysis and collection. In contrast, a non-research problem does not require research for a solution, as the answer is often obvious or already known.

Non-Research Problems Examples

A recent survey in town- A found that 1000 women were continuous users of contraceptive pills.

But last month’s service statistics indicate that none of these women were using contraceptive pills (Fisher et al. 1991:4).

The discrepancy is that ‘all 1000 women should have been using a pill, but none is doing so. The question is: why the discrepancy exists?

Well, the fact is, a monsoon flood has prevented all new supplies of pills from reaching town- A, and all old supplies have been exhausted. Thus, although the problem situation exists, the reason for the problem is already known.

Therefore, assuming all the facts are correct, there is no reason to research the factors associated with pill discontinuation among women. This is, thus, a non-research problem.

A pilot survey by University students revealed that in Rural Town-A, the goiter prevalence among school children is as high as 80%, while in the neighboring Rural Town-A, it is only 30%. Why is a discrepancy?

Upon inquiry, it was seen that some three years back, UNICEF launched a lipiodol injection program in the neighboring Rural Town-A.

This attempt acted as a preventive measure against the goiter. The reason for the discrepancy is known; hence, we do not consider the problem a research problem.

A hospital treated a large number of cholera cases with penicillin, but the treatment with penicillin was not found to be effective. Do we need research to know the reason?

Here again, there is one single reason that Vibrio cholera is not sensitive to penicillin; therefore, this is not the drug of choice for this disease.

In this case, too, as the reasons are known, it is unwise to undertake any study to find out why penicillin does not improve the condition of cholera patients. This is also a non-research problem.

In the tea marketing system, buying and selling tea starts with bidders. Blenders purchase open tea from the bidders. Over the years, marketing cost has been the highest for bidders and the lowest for blenders. What makes this difference?

The bidders pay exorbitantly higher transport costs, which constitute about 30% of their total cost.

Blenders have significantly fewer marketing functions involving transportation, so their marketing cost remains minimal.

Hence no research is needed to identify the factors that make this difference.

Here are some of the problems we frequently encounter, which may well be considered non-research problems:

  • Rises in the price of warm clothes during winter;
  • Preferring admission to public universities over private universities;
  • Crisis of accommodations in sea resorts during summer
  • Traffic jams in the city street after office hours;
  • High sales in department stores after an offer of a discount.

Research Problem

In contrast to a non-research problem, a research problem is of primary concern to a researcher.

A research problem is a perceived difficulty, a feeling of discomfort, or a discrepancy between a common belief and reality.

As noted by Fisher et al. (1993), a problem will qualify as a potential research problem when the following three conditions exist:

  • There should be a perceived discrepancy between “what it is” and “what it should have been.” This implies that there should be a difference between “what exists” and the “ideal or planned situation”;
  • A question about “why” the discrepancy exists. This implies that the reason(s) for this discrepancy is unclear to the researcher (so that it makes sense to develop a research question); and
  • There should be at least two possible answers or solutions to the questions or problems.

The third point is important. If there is only one possible and plausible answer to the question about the discrepancy, then a research situation does not exist.

It is a non-research problem that can be tackled at the managerial or administrative level.

Research Problem Examples

Research problem – example #1.

While visiting a rural area, the UNICEF team observed that some villages have female school attendance rates as high as 75%, while some have as low as 10%, although all villages should have a nearly equal attendance rate. What factors are associated with this discrepancy?

We may enumerate several reasons for this:

  • Villages differ in their socio-economic background.
  • In some villages, the Muslim population constitutes a large proportion of the total population. Religion might play a vital role.
  • Schools are far away from some villages. The distance thus may make this difference.

Because there is more than one answer to the problem, it is considered a research problem, and a study can be undertaken to find a solution.

Research Problem – Example #2

The Government has been making all-out efforts to ensure a regular flow of credit in rural areas at a concession rate through liberal lending policy and establishing many bank branches in rural areas.

Knowledgeable sources indicate that expected development in rural areas has not yet been achieved, mainly because of improper credit utilization.

More than one reason is suspected for such misuse or misdirection.

These include, among others:

  • Diversion of credit money to some unproductive sectors
  • Transfer of credit money to other people like money lenders, who exploit the rural people with this money
  • Lack of knowledge of proper utilization of the credit.

Here too, reasons for misuse of loans are more than one. We thus consider this problem as a researchable problem.

Research Problem – Example #3

Let’s look at a new headline: Stock Exchange observes the steepest ever fall in stock prices: several injured as retail investors clash with police, vehicles ransacked .

Investors’ demonstration, protest and clash with police pause a problem. Still, it is certainly not a research problem since there is only one known reason for the problem: Stock Exchange experiences the steepest fall in stock prices. But what causes this unprecedented fall in the share market?

Experts felt that no single reason could be attributed to the problem. It is a mix of several factors and is a research problem. The following were assumed to be some of the possible reasons:

  • The merchant banking system;
  • Liquidity shortage because of the hike in the rate of cash reserve requirement (CRR);
  • IMF’s warnings and prescriptions on the commercial banks’ exposure to the stock market;
  • Increase in supply of new shares;
  • Manipulation of share prices;
  • Lack of knowledge of the investors on the company’s fundamentals.

The choice of a research problem is not as easy as it appears. The researchers generally guide it;

  • own intellectual orientation,
  • level of training,
  • experience,
  • knowledge on the subject matter, and
  • intellectual curiosity.

Theoretical and practical considerations also play a vital role in choosing a research problem. Societal needs also guide in choosing a research problem.

Once we have chosen a research problem, a few more related steps must be followed before a decision is taken to undertake a research study.

These include, among others, the following:

  • Statement of the problem.
  • Justifying the problem.
  • Analyzing the problem.

A detailed exposition of these issues is undertaken in chapter ten while discussing the proposal development.

A clear and well-defined problem statement is considered the foundation for developing the research proposal.

It enables the researcher to systematically point out why the proposed research on the problem should be undertaken and what he hopes to achieve with the study’s findings.

A well-defined statement of the problem will lead the researcher to formulate the research objectives, understand the background of the study, and choose a proper research methodology.

Once the problem situation has been identified and clearly stated, it is important to justify the importance of the problem.

In justifying the problems, we ask such questions as why the problem of the study is important, how large and widespread the problem is, and whether others can be convinced about the importance of the problem and the like.

Answers to the above questions should be reviewed and presented in one or two paragraphs that justify the importance of the problem.

As a first step in analyzing the problem, critical attention should be given to accommodate the viewpoints of the managers, users, and researchers to the problem through threadbare discussions.

The next step is identifying the factors that may have contributed to the perceived problems.

Issues of Research Problem Identification

There are several ways to identify, define, and analyze a problem, obtain insights, and get a clearer idea about these issues. Exploratory research is one of the ways of accomplishing this.

The purpose of the exploratory research process is to progressively narrow the scope of the topic and transform the undefined problems into defined ones, incorporating specific research objectives.

The exploratory study entails a few basic strategies for gaining insights into the problem. It is accomplished through such efforts as:

Pilot Survey

A pilot survey collects proxy data from the ultimate subjects of the study to serve as a guide for the large study. A pilot study generates primary data, usually for qualitative analysis.

This characteristic distinguishes a pilot survey from secondary data analysis, which gathers background information.

Case Studies

Case studies are quite helpful in diagnosing a problem and paving the way to defining the problem. It investigates one or a few situations identical to the researcher’s problem.

Focus Group Interviews

Focus group interviews, an unstructured free-flowing interview with a small group of people, may also be conducted to understand and define a research problem .

Experience Survey

Experience survey is another strategy to deal with the problem of identifying and defining the research problem.

It is an exploratory research endeavor in which individuals knowledgeable and experienced in a particular research problem are intimately consulted to understand the problem.

These persons are sometimes known as key informants, and an interview with them is popularly known as the Key Informant Interview (KII).

Reviewing of Literature

reviewing research literature

A review of relevant literature is an integral part of the research process. It enables the researcher to formulate his problem in terms of the specific aspects of the general area of his interest that has not been researched so far.

Such a review provides exposure to a larger body of knowledge and equips him with enhanced knowledge to efficiently follow the research process.

Through a proper review of the literature, the researcher may develop the coherence between the results of his study and those of the others.

A review of previous documents on similar or related phenomena is essential even for beginning researchers.

Ignoring the existing literature may lead to wasted effort on the part of the researchers.

Why spend time merely repeating what other investigators have already done?

Suppose the researcher is aware of earlier studies of his topic or related topics . In that case, he will be in a much better position to assess his work’s significance and convince others that it is important.

A confident and expert researcher is more crucial in questioning the others’ methodology, the choice of the data, and the quality of the inferences drawn from the study results.

In sum, we enumerate the following arguments in favor of reviewing the literature:

  • It avoids duplication of the work that has been done in the recent past.
  • It helps the researcher discover what others have learned and reported on the problem.
  • It enables the researcher to become familiar with the methodology followed by others.
  • It allows the researcher to understand what concepts and theories are relevant to his area of investigation.
  • It helps the researcher to understand if there are any significant controversies, contradictions, and inconsistencies in the findings.
  • It allows the researcher to understand if there are any unanswered research questions.
  • It might help the researcher to develop an analytical framework.
  • It will help the researcher consider including variables in his research that he might not have thought about.

Why is reviewing literature crucial in the research process?

Reviewing literature helps avoid duplicating previous work, discovers what others have learned about the problem, familiarizes the researcher with relevant concepts and theories, and ensures a comprehensive approach to the research question.

What is the significance of reviewing literature in the research process?

Reviewing relevant literature helps formulate the problem, understand the background of the study, choose a proper research methodology, and develop coherence between the study’s results and previous findings.

Setting Research Questions, Objectives, and Hypotheses

Setting Research Questions, Objectives, and Hypotheses

After discovering and defining the research problem, researchers should make a formal statement of the problem leading to research objectives .

An objective will precisely say what should be researched, delineate the type of information that should be collected, and provide a framework for the scope of the study. A well-formulated, testable research hypothesis is the best expression of a research objective.

A hypothesis is an unproven statement or proposition that can be refuted or supported by empirical data. Hypothetical statements assert a possible answer to a research question.

Step #4: Choosing the Study Design

Choosing the Study Design

The research design is the blueprint or framework for fulfilling objectives and answering research questions .

It is a master plan specifying the methods and procedures for collecting, processing, and analyzing the collected data. There are four basic research designs that a researcher can use to conduct their study;

  • experiment,
  • secondary data study, and
  • observational study.

The type of research design to be chosen from among the above four methods depends primarily on four factors:

  • The type of problem
  • The objectives of the study,
  • The existing state of knowledge about the problem that is being studied, and
  • The resources are available for the study.

Deciding on the Sample Design

Deciding on the sample design

Sampling is an important and separate step in the research process. The basic idea of sampling is that it involves any procedure that uses a relatively small number of items or portions (called a sample) of a universe (called population) to conclude the whole population.

It contrasts with the process of complete enumeration, in which every member of the population is included.

Such a complete enumeration is referred to as a census.

A population is the total collection of elements we wish to make some inference or generalization.

A sample is a part of the population, carefully selected to represent that population. If certain statistical procedures are followed in selecting the sample, it should have the same characteristics as the population. These procedures are embedded in the sample design.

Sample design refers to the methods followed in selecting a sample from the population and the estimating technique vis-a-vis the formula for computing the sample statistics.

The fundamental question is, then, how to select a sample.

To answer this question, we must have acquaintance with the sampling methods.

These methods are basically of two types;

  • probability sampling , and
  • non-probability sampling .

Probability sampling ensures every unit has a known nonzero probability of selection within the target population.

If there is no feasible alternative, a non-probability sampling method may be employed.

The basis of such selection is entirely dependent on the researcher’s discretion. This approach is called judgment sampling, convenience sampling, accidental sampling, and purposive sampling.

The most widely used probability sampling methods are simple random sampling , stratified random sampling , cluster sampling , and systematic sampling . They have been classified by their representation basis and unit selection techniques.

Two other variations of the sampling methods that are in great use are multistage sampling and probability proportional to size (PPS) sampling .

Multistage sampling is most commonly used in drawing samples from very large and diverse populations.

The PPS sampling is a variation of multistage sampling in which the probability of selecting a cluster is proportional to its size, and an equal number of elements are sampled within each cluster.

Collecting Data From The Research Sample

collect data from the research sample

Data gathering may range from simple observation to a large-scale survey in any defined population. There are many ways to collect data. The approach selected depends on the objectives of the study, the research design, and the availability of time, money, and personnel.

With the variation in the type of data (qualitative or quantitative) to be collected, the method of data collection also varies .

The most common means for collecting quantitative data is the structured interview .

Studies that obtain data by interviewing respondents are called surveys. Data can also be collected by using self-administered questionnaires . Telephone interviewing is another way in which data may be collected .

Other means of data collection include secondary sources, such as the census, vital registration records, official documents, previous surveys, etc.

Qualitative data are collected mainly through in-depth interviews, focus group discussions , Key Informant Interview ( KII), and observational studies.

Process and Analyze the Collected Research Data

Processing and Analyzing the Collected Research Data

Data processing generally begins with the editing and coding of data . Data are edited to ensure consistency across respondents and to locate omissions if any.

In survey data, editing reduces errors in the recording, improves legibility, and clarifies unclear and inappropriate responses. In addition to editing, the data also need coding.

Because it is impractical to place raw data into a report, alphanumeric codes are used to reduce the responses to a more manageable form for storage and future processing.

This coding process facilitates the processing of the data. The personal computer offers an excellent opportunity for data editing and coding processes.

Data analysis usually involves reducing accumulated data to a manageable size, developing summaries, searching for patterns, and applying statistical techniques for understanding and interpreting the findings in light of the research questions.

Further, based on his analysis, the researcher determines if his findings are consistent with the formulated hypotheses and theories.

The techniques used in analyzing data may range from simple graphical techniques to very complex multivariate analyses depending on the study’s objectives, the research design employed, and the nature of the data collected.

As in the case of data collection methods, an analytical technique appropriate in one situation may not be suitable for another.

Writing Research Report – Developing Research Proposal, Writing Report, Disseminating and Utilizing Results

Writing Research Report - Developing Research Proposal, Writing Report, Disseminating and Utilizing Results

The entire task of a research study is accumulated in a document called a proposal or research proposal.

A research proposal is a work plan, prospectus, outline, offer, and a statement of intent or commitment from an individual researcher or an organization to produce a product or render a service to a potential client or sponsor .

The proposal will be prepared to keep the sequence presented in the research process. The proposal tells us what, how, where, and to whom it will be done.

It must also show the benefit of doing it. It always includes an explanation of the purpose of the study (the research objectives) or a definition of the problem.

It systematically outlines the particular research methodology and details the procedures utilized at each stage of the research process.

The end goal of a scientific study is to interpret the results and draw conclusions.

To this end, it is necessary to prepare a report and transmit the findings and recommendations to administrators, policymakers, and program managers to make a decision.

There are various research reports: term papers, dissertations, journal articles , papers for presentation at professional conferences and seminars, books, thesis, and so on. The results of a research investigation prepared in any form are of little utility if they are not communicated to others.

The primary purpose of a dissemination strategy is to identify the most effective media channels to reach different audience groups with study findings most relevant to their needs.

The dissemination may be made through a conference, a seminar, a report, or an oral or poster presentation.

The style and organization of the report will differ according to the target audience, the occasion, and the purpose of the research. Reports should be developed from the client’s perspective.

A report is an excellent means that helps to establish the researcher’s credibility. At a bare minimum, a research report should contain sections on:

  • An executive summary;
  • Background of the problem;
  • Literature review;
  • Methodology;
  • Discussion;
  • Conclusions and
  • Recommendations.

The study results can also be disseminated through peer-reviewed journals published by academic institutions and reputed publishers both at home and abroad. The report should be properly evaluated .

These journals have their format and editorial policies. The contributors can submit their manuscripts adhering to the policies and format for possible publication of their papers.

There are now ample opportunities for researchers to publish their work online.

The researchers have conducted many interesting studies without affecting actual settings. Ideally, the concluding step of a scientific study is to plan for its utilization in the real world.

Although researchers are often not in a position to implement a plan for utilizing research findings, they can contribute by including in their research reports a few recommendations regarding how the study results could be utilized for policy formulation and program intervention.

Why is the dissemination of research findings important?

Dissemination of research findings is crucial because the results of a research investigation have little utility if not communicated to others. Dissemination ensures that the findings reach relevant stakeholders, policymakers, and program managers to inform decisions.

How should a research report be structured?

A research report should contain sections on an executive summary, background of the problem, literature review, methodology, findings, discussion, conclusions, and recommendations.

Why is it essential to consider the target audience when preparing a research report?

The style and organization of a research report should differ based on the target audience, occasion, and research purpose. Tailoring the report to the audience ensures that the findings are communicated effectively and are relevant to their needs.

30 Accounting Research Paper Topics and Ideas for Writing

  • Open access
  • Published: 13 May 2024

Patient medication management, understanding and adherence during the transition from hospital to outpatient care - a qualitative longitudinal study in polymorbid patients with type 2 diabetes

  • Léa Solh Dost   ORCID: orcid.org/0000-0001-5767-1305 1 , 2 ,
  • Giacomo Gastaldi   ORCID: orcid.org/0000-0001-6327-7451 3 &
  • Marie P. Schneider   ORCID: orcid.org/0000-0002-7557-9278 1 , 2  

BMC Health Services Research volume  24 , Article number:  620 ( 2024 ) Cite this article

Metrics details

Continuity of care is under great pressure during the transition from hospital to outpatient care. Medication changes during hospitalization may be poorly communicated and understood, compromising patient safety during the transition from hospital to home. The main aims of this study were to investigate the perspectives of patients with type 2 diabetes and multimorbidities on their medications from hospital discharge to outpatient care, and their healthcare journey through the outpatient healthcare system. In this article, we present the results focusing on patients’ perspectives of their medications from hospital to two months after discharge.

Patients with type 2 diabetes, with at least two comorbidities and who returned home after discharge, were recruited during their hospitalization. A descriptive qualitative longitudinal research approach was adopted, with four in-depth semi-structured interviews per participant over a period of two months after discharge. Interviews were based on semi-structured guides, transcribed verbatim, and a thematic analysis was conducted.

Twenty-one participants were included from October 2020 to July 2021. Seventy-five interviews were conducted. Three main themes were identified: (A) Medication management, (B) Medication understanding, and (C) Medication adherence, during three periods: (1) Hospitalization, (2) Care transition, and (3) Outpatient care. Participants had varying levels of need for medication information and involvement in medication management during hospitalization and in outpatient care. The transition from hospital to autonomous medication management was difficult for most participants, who quickly returned to their routines with some participants experiencing difficulties in medication adherence.

Conclusions

The transition from hospital to outpatient care is a challenging process during which discharged patients are vulnerable and are willing to take steps to better manage, understand, and adhere to their medications. The resulting tension between patients’ difficulties with their medications and lack of standardized healthcare support calls for interprofessional guidelines to better address patients’ needs, increase their safety, and standardize physicians’, pharmacists’, and nurses’ roles and responsibilities.

Peer Review reports

Introduction

Continuity of patient care is characterized as the collaborative engagement between the patient and their physician-led care team in the ongoing management of healthcare, with the mutual objective of delivering high-quality and cost-effective medical care [ 1 ]. Continuity of care is under great pressure during the transition of care from hospital to outpatient care, with a risk of compromising patients’ safety [ 2 , 3 ]. The early post-discharge period is a high-risk and fragile transition: once discharged, one in five patients experience at least one adverse event during the first three weeks following discharge, and more than half of these adverse events are drug-related [ 4 , 5 ]. A retrospective study examining all discharged patients showed that adverse drug events (ADEs) account for up to 20% of 30-day hospital emergency readmissions [ 6 ]. During hospitalization, patients’ medications are generally modified, with an average of nearly four medication changes per patient [ 7 ]. Information regarding medications such as medication changes, the expected effect, side effects, and instructions for use are frequently poorly communicated to patients during hospitalization and at discharge [ 8 , 9 , 10 , 11 ]. Between 20 and 60% of discharged patients lack knowledge of their medications [ 12 , 13 ]. Consideration of patients’ needs and their active engagement in decision-making during hospitalization regarding their medications are often lacking [ 11 , 14 , 15 ]. This can lead to unsafe discharge and contribute to medication adherence difficulties, such as non-implementation of newly prescribed medications [ 16 , 17 ].

Patients with multiple comorbidities and polypharmacy are at higher risk of ADE [ 18 ]. Type 2 diabetes is one of the chronic health conditions most frequently associated with comorbidities and patients with type 2 diabetes often lack care continuum [ 19 , 20 , 21 ]. The prevalence of patients hospitalized with type 2 diabetes can exceed 40% [ 22 ] and these patients are at higher risk for readmission due to their comorbidities and their medications, such as insulin and oral hypoglycemic agents [ 23 , 24 , 25 ].

Interventions and strategies to improve patient care and safety at transition have shown mixed results worldwide in reducing cost, rehospitalization, ADE, and non-adherence [ 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 ]. However, interventions that are patient-centered, with a patient follow-up and led by interprofessional healthcare teams showed promising results [ 34 , 35 , 36 ]. Most of these interventions have not been implemented routinely due to the extensive time to translate research into practice and the lack of hybrid implementation studies [ 37 , 38 , 39 , 40 , 41 ]. In addition, patient-reported outcomes and perspectives have rarely been considered, yet patients’ involvement is essential for seamless and integrated care [ 42 , 43 ]. Interprofessional collaboration in which patients are full members of the interprofessional team, is still in its infancy in outpatient care [ 44 ]. Barriers and facilitators regarding medications at the transition of care have been explored in multiple qualitative studies at one given time in a given setting (e.g., at discharge, one-month post-discharge) [ 8 , 45 , 46 , 47 , 48 ]. However, few studies have adopted a holistic methodology from the hospital to the outpatient setting to explore changes in patients’ perspectives over time [ 49 , 50 , 51 ]. Finally, little is known about whether, how, and when patients return to their daily routine following hospitalization and the impact of hospitalization weeks after discharge.

In Switzerland, continuity of care after hospital discharge is still poorly documented, both in terms of contextual analysis and interventional studies, and is mainly conducted in the hospital setting [ 31 , 35 , 52 , 53 , 54 , 55 , 56 ]. The first step of an implementation science approach is to perform a contextual analysis to set up effective interventions adapted to patients’ needs and aligned to healthcare professionals’ activities in a specific context [ 41 , 57 ]. Therefore, the main aims of this study were to investigate the perspectives of patients with type 2 diabetes and multimorbidities on their medications from hospital discharge to outpatient care, and on their healthcare journey through the outpatient healthcare system. In this article, we present the results focusing on patients’ perspectives of their medications from hospital to two months after discharge.

Study design

This qualitative longitudinal study, conducted from October 2020 to July 2021, used a qualitative descriptive methodology through four consecutive in-depth semi-structured interviews per participant at three, 10-, 30- and 60-days post-discharge, as illustrated in Fig.  1 . Longitudinal qualitative research is characterized by qualitative data collection at different points in time and focuses on temporality, such as time and change [ 58 , 59 ]. Qualitative descriptive studies aim to explore and describe the depth and complexity of human experiences or phenomena [ 60 , 61 , 62 ]. We focused our qualitative study on the 60 first days after discharge as this period is considered highly vulnerable and because studies often use 30- or 60-days readmission as an outcome measure [ 5 , 63 ].

This qualitative study follows the Consolidated Criteria for Reporting Qualitative Research (COREQ). Ethics committee approval was sought and granted by the Cantonal Research Ethics Commission, Geneva (CCER) (2020 − 01779).

Recruitment took place during participants’ hospitalization in the general internal medicine divisions at the Geneva University Hospitals in the canton of Geneva (500 000 inhabitants), Switzerland. Interviews took place at participants’ homes, in a private office at the University of Geneva, by telephone or by secure video call, according to participants’ preference. Informal caregivers could also participate alongside the participants.

figure 1

Study flowchart

Researcher characteristics

All the researchers were trained in qualitative studies. The diabetologist and researcher (GG) who enrolled the patients in the study was involved directly or indirectly (advice asked to the Geneva University Hospital diabetes team of which he was a part) for most participants’ care during hospitalization. LS (Ph.D. student and community pharmacist) was unknown to participants and presented herself during hospitalization as a “researcher” and not as a healthcare professional to avoid any risk of influencing participants’ answers. This study was not interventional, and the interviewer (LS) invited participants to contact a healthcare professional for any questions related to their medication or medical issues.

Population and sampling strategy

Patients with type 2 diabetes were chosen as an example population to describe polypharmacy patients as these patients usually have several health issues and polypharmacy [ 20 , 22 , 25 ]. Inclusions criteria for the study were: adult patients with type 2 diabetes, with at least two other comorbidities, hospitalized for at least three days in a general internal medicine ward, with a minimum of one medication change during hospital stay, and who self-managed their medications once discharged home. Exclusion criteria were patients not reachable by telephone following discharge, unable to give consent (patients with schizophrenia, dementia, brain damage, or drug/alcohol misuse), and who could not communicate in French. A purposive sampling methodology was applied aiming to include participants with different ages, genders, types, and numbers of health conditions by listing participants’ characteristics in a double-entry table, available in Supplementary Material 1 , until thematic saturation was reached. Thematic saturation was considered achieved when no new code or theme emerged and new data repeated previously coded information [ 64 ]. The participants were identified if they were hospitalized in the ward dedicated to diabetes care or when the diabetes team was contacted for advice. The senior ward physician (GG) screened eligible patients and the interviewer (LS) obtained written consent before hospital discharge.

Data collection and instruments

Sociodemographic (age, gender, educational level, living arrangement) and clinical characteristics (reason for hospitalization, date of admission, health conditions, diabetes diagnosis, medications before and during hospitalization) were collected by interviewing participants before their discharge and by extracting participants’ data from electronic hospital files by GG and LS. Participants’ pharmacies were contacted with the participant’s consent to obtain medication records from the last three months if information regarding medications before hospitalization was missing in the hospital files.

Semi-structured interview guides for each interview (at three, 10-, 30- and 60-days post-discharge) were developed based on different theories and components of health behavior and medication adherence: the World Health Organization’s (WHO) five dimensions for adherence, the Information-Motivation-Behavioral skills model and the Social Cognitive Theory [ 65 , 66 , 67 ]. Each interview explored participants’ itinerary in the healthcare system and their perspectives on their medications. Regarding medications, the following themes were mentioned at each interview: changes in medications, patients’ understanding and implication; information on their medications, self-management of their medications, and patients’ medication adherence. Other aspects were mentioned in specific interviews: patients’ hospitalization and experience on their return home (interview 1), motivation (interviews 2 and 4), and patient’s feedback on the past two months (interview 4). Interview guides translated from French are available in Supplementary Material 2 . The participants completed self-reported and self-administrated questionnaires at different interviews to obtain descriptive information on different factors that may affect medication management and adherence: self-report questionnaires on quality of life (EQ-5D-5 L) [ 68 ], literacy (Schooling-Opinion-Support questionnaire) [ 69 ], medication adherence (Adherence Visual Analogue Scale, A-VAS) [ 70 ] and Belief in Medication Questionnaire (BMQ) [ 71 ] were administered to each participant at the end of selected interviews to address the different factors that may affect medication management and adherence as well as to determine a trend of determinants over time. The BMQ contains two subscores: Specific-Necessity and Specific-Concerns, addressing respectively their perceived needs for their medications, and their concerns about adverse consequences associated with taking their medication [ 72 ].

Data management

Informed consent forms, including consent to obtain health data, were securely stored in a private office at the University of Geneva. The participants’ identification key was protected by a password known only by MS and LS. Confidentiality was guaranteed by pseudonymization of participants’ information and audio-recordings were destroyed once analyzed. Sociodemographic and clinical characteristics, medication changes, and answers to questionnaires were securely collected by electronic case report forms (eCRFs) on RedCap®. Interviews were double audio-recorded and field notes were taken during interviews. Recorded interviews were manually transcribed verbatim in MAXQDA® (2018.2) by research assistants and LS and transcripts were validated for accuracy by LS. A random sample of 20% of questionnaires was checked for accuracy for the transcription from the paper questionnaires to the eCRFs. Recorded sequences with no link to the discussed topics were not transcribed and this was noted in the transcripts.

Data analysis

A descriptive statistical analysis of sociodemographic, clinical characteristics and self-reported questionnaire data was carried out. A thematic analysis of transcripts was performed, as described by Braun and Clarke [ 73 ], by following six steps: raw data was read, text segments related to the study objectives were identified, text segments to create new categories were identified, similar or redundant categories were reduced and a model that integrated all significant categories was created. The analysis was conducted in parallel with patient enrolment to ensure data saturation. To ensure the validity of the coding method, transcripts were double coded independently and discussed by the research team until similar themes were obtained. The research group developed and validated an analysis grid, with which LS coded systematically the transcriptions and met regularly with the research team to discuss questions on data analysis and to ensure the quality of coding. The analysis was carried out in French, and the verbatims of interest cited in the manuscript were translated and validated by a native English-speaking researcher to preserve the meaning.

In this analysis, we used the term “healthcare professionals” when more than one profession could be involved in participants’ medication management. Otherwise, when a specific healthcare professional was involved, we used the designated profession (e.g. physicians, pharmacists).

Patient and public involvement

During the development phase of the study, interview guides and questionnaires were reviewed for clarity and validity and adapted by two patient partners, with multiple health conditions and who experienced previously a hospital discharge. They are part of the HUG Patients Partners + 3P platform for research and patient and public involvement.

Interviews and participants’ descriptions

A total of 75 interviews were conducted with 21 participants. In total, 31 patients were contacted, seven refused to participate (four at the project presentation and three at consent), two did not enter the selection criteria at discharge and one was unreachable after discharge. Among the 21 participants, 15 participated in all interviews, four in three interviews, one in two interviews, and one in one interview, due to scheduling constraints. Details regarding interviews and participants characteristics are presented in Tables  1 and 2 .

The median length of time between hospital discharge and interviews 1,2,3 and 4 was 5 (IQR: 4–7), 14 (13-20), 35 (22-38), and 63 days (61-68), respectively. On average, by comparing medications at hospital admission and discharge, a median of 7 medication changes (IQR: 6–9, range:2;17) occurred per participant during hospitalization and a median of 7 changes (5–12) during the two months following discharge. Details regarding participants’ medications are described in Table  3 .

Patient self-reported adherence over the past week for their three most challenging medications are available in Supplementary Material 3 .

Qualitative analysis

We defined care transition as the period from discharge until the first medical appointment post-discharge, and outpatient care as the period starting after the first medical appointment. Data was organized into three key themes (A. Medication management, B. Medication understanding, and C. Medication adherence) divided into subthemes at three time points (1. Hospitalization, 2. Care transition and 3. Outpatient care). Figure  2 summarizes and illustrates the themes and subthemes with their influencing factors as bullet points.

figure 2

Participants’ medication management, understanding and adherence during hospitalization, care transition and outpatient care

A. Medication management

A.1 medication management during hospitalization: medication management by hospital staff.

Medications during hospitalization were mainly managed by hospital healthcare professionals (i.e. nurses and physicians) with varying degrees of patient involvement: “At the hospital, they prepared the medications for me. […] I didn’t even know what the packages looked like.” Participant 22; interview 1 (P22.1) Some participants reported having therapeutic education sessions with specialized nurses and physicians, such as the explanation and demonstration of insulin injection and glucose monitoring. A patient reported that he was given the choice of several treatments and was involved in shared decision-making. Other participants had an active role in managing and optimizing dosages, such as rapid insulin, due to prior knowledge and use of medications before hospitalization.

A.2 Medication management at transition: obtaining the medication and initiating self-management

Once discharged, some participants had difficulties obtaining their medications at the pharmacy because some medications were not stored and had to be ordered, delaying medication initiation. To counter this problem upstream, a few participants were provided a 24-to-48-hour supply of medications at discharge. It was sometimes requested by the patient or suggested by the healthcare professionals but was not systematic. The transition from medication management by hospital staff to self-management was exhausting for most participants who were faced with a large amount of new information and changes in their medications: “ When I was in the hospital, I didn’t even realize all the changes. When I came back home, I took away the old medication packages and got out the new ones. And then I thought : « my God, all this…I didn’t know I had all these changes » ” P2.1 Written documentation, such as the discharge prescription or dosage labels on medication packages, was helpful in managing their medication at home. Most participants used weekly pill organizers to manage their medications, which were either already used before hospitalization or were introduced post-discharge. The help of a family caregiver in managing and obtaining medications was reported as a facilitator.

A.3 Medication management in outpatient care: daily self-management and medication burden

A couple of days or weeks after discharge, most participants had acquired a routine so that medication management was less demanding, but the medication burden varied depending on the participants. For some, medication management became a simple action well implemented in their routine (“It has become automatic” , P23.4), while for others, the number of medications and the fact that the medications reminded them of the disease was a heavy burden to bear on a daily basis (“ During the first few days after getting out of the hospital, I thought I was going to do everything right. In the end, well [laughs] it’s complicated. I ended up not always taking the medication, not monitoring the blood sugar” P12.2) To support medication self-management, some participants had written documentation such as treatment plans, medication lists, and pictures of their medication packages on their phones. Some participants had difficulties obtaining medications weeks after discharge as discharge prescriptions were not renewable and participants did not see their physician in time. Others had to visit multiple physicians to have their prescriptions updated. A few participants were faced with prescription or dispensing errors, such as prescribing or dispensing the wrong dosage, which affected medication management and decreased trust in healthcare professionals. In most cases, according to participants, the pharmacy staff worked in an interprofessional collaboration with physicians to provide new and updated prescriptions.

B. Medication understanding

B.1 medication understanding during hospitalization: new information and instructions.

The amount of information received during hospitalization varied considerably among participants with some reporting having received too much, while others saying they received too little information regarding medication changes, the reason for changes, or for introducing new medications: “They told me I had to take this medication all my life, but they didn’t tell me what the effects were or why I was taking it.” P5.3

Hospitalization was seen by some participants as a vulnerable and tiring period during which they were less receptive to information. Information and explanations were generally given verbally, making it complicated for most participants to recall it. Some participants reported that hospital staff was attentive to their needs for information and used communication techniques such as teach-back (a way of checking understanding by asking participants to say in their own words what they need to know or do about their health or medications). Some participants were willing to be proactive in the understanding of their medications while others were more passive, had no specific needs for information, and did not see how they could be engaged more.

B.2 Medication understanding at transition: facing medication changes

At hospital discharge, the most challenging difficulty for participants was to understand the changes made regarding their medications. For newly diagnosed participants, the addition of new medications was more difficult to understand, whereas, for experienced participants, changes in known medications such as dosage modification, changes within a therapeutic class, and generic substitutions were the most difficult to understand. Not having been informed about changes caused confusion and misunderstanding. Therefore, medication reconciliation done by the patient was time-consuming, especially for participants with multiple medications: “ They didn’t tell me at all that they had changed my treatment completely. They just told me : « We’ve changed a few things. But it was the whole treatment ». ” P2.3 Written information, such as the discharge prescription, the discharge report (brief letter summarizing information about the hospitalization, given to the patient at discharge), or the label on the medication box (written by the pharmacist with instructions on dosage) helped them find or recall information about their medications and diagnoses. However, technical terms were used in hospital documentations and were not always understandable. For example, this participant said: “ On the prescription of valsartan, they wrote: ‘resume in the morning once profile…’[once hypertension profile allows]… I don’t know what that means.” P8.1 In addition, some documents were incomplete, as mentioned by a patient who did not have the insulin dosage mentioned on the hospital prescription. Some participants sought help from healthcare professionals, such as pharmacists, hospital physicians, or general practitioners a few days after discharge to review medications, answer questions, or obtain additional information.

B.3 Medication understanding in the outpatient care: concerns and knowledge

Weeks after discharge, most participants had concerns about the long-term use of their medications, their usefulness, and the possible risk of interactions or side effects. Some participants also reported having some lack of knowledge regarding indications, names, or how the medication worked: “I don’t even know what Brilique® [ticagrelor, antiplatelet agent] is for. It’s for blood pressure, isn’t it?. I don’t know.” P11.4 According to participants, the main reasons for the lack of understanding were the lack of information at the time of prescribing and the large number of medications, making it difficult to search for information and remember it. Participants sought information from different healthcare professionals or by themselves, on package inserts, through the internet, or from family and friends. Others reported having had all the information needed or were not interested in having more information. In addition, participants with low medication literacy, such as non-native speakers or elderly people, struggled more with medication understanding and sought help from family caregivers or healthcare professionals, even weeks after discharge: “ I don’t understand French very well […] [The doctor] explained it very quickly…[…] I didn’t understand everything he was saying” P16.2

C. Medication adherence

C.2 medication adherence at transition: adopting new behaviors.

Medication adherence was not mentioned as a concern during hospitalization and a few participants reported difficulties in medication initiation once back home: “I have an injection of Lantus® [insulin] in the morning, but obviously, the first day [after discharge], I forgot to do it because I was not used to it.” P23.1 Participants had to quickly adopt new behaviors in the first few days after discharge, especially for participants with few medications pre-hospitalization. The use of weekly pill organizers, alarms and specific storage space were reported as facilitators to support adherence. One patient did not initiate one of his medications because he did not understand the medication indication, and another patient took her old medications because she was used to them. Moreover, most participants experienced their hospitalization as a turning point, a time when they focused on their health, thought about the importance of their medications, and discussed any new lifestyle or dietary measures that might be implemented.

C.3 Medication adherence in outpatient care: ongoing medication adherence

More medication adherence difficulties appeared a few weeks after hospital discharge when most participants reported nonadherence behaviors, such as difficulties implementing the dosage regimen, or intentionally discontinuing the medication and modifying the medication regimen on their initiative. Determinants positively influencing medication adherence were the establishment of a routine; organizing medications in weekly pill-organizers; organizing pocket doses (medications for a short period that participants take with them when away from home); seeking support from family caregivers; using alarm clocks; and using specific storage places. Reasons for nonadherence were changes in daily routine; intake times that were not convenient for the patient; the large number of medications; and poor knowledge of the medication or side effects. Healthcare professionals’ assistance for medication management, such as the help of home nurses or pharmacists for the preparation of weekly pill-organizers, was requested by participants or offered by healthcare professionals to support medication adherence: “ I needed [a home nurse] to put my pills in the pillbox. […] I felt really weak […] and I was making mistakes. So, I’m very happy [the doctor] offered me [home care]. […] I have so many medications.” P22.3 Some participants who experienced prehospitalization non-adherence were more aware of their non-adherence and implemented strategies, such as modifying the timing of intake: “I said to my doctor : « I forget one time out of two […], can I take them in the morning? » We looked it up and yes, I can take it in the morning.” P11.2 In contrast, some participants were still struggling with adherence difficulties that they had before hospitalization. Motivations for taking medications two months after discharge were to improve health, avoid complications, reduce symptoms, reduce the number of medications in the future or out of obligation: “ I force myself to take them because I want to get to the end of my diabetes, I want to reduce the number of pills as much as possible.” P14.2 After a few weeks post-hospitalization, for some participants, health and illness were no longer the priority because of other life imperatives (e.g., family or financial situation).

This longitudinal study provided a multi-faceted representation of how patients manage, understand, and adhere to their medications from hospital discharge to two months after discharge. Our findings highlighted the varying degree of participants’ involvement in managing their medications during their hospitalization, the individualized needs for information during and after hospitalization, the complicated transition from hospital to autonomous medication management, the adaptation of daily routines around medication once back home, and the adherence difficulties that surfaced in the outpatient care, with nonadherence prior to hospitalization being an indicator of the behavior after discharge. Finally, our results confirmed the lack of continuity in care and showed the lack of patient care standardization experienced by the participants during the transition from hospital to outpatient care.

This in-depth analysis of patients’ experiences reinforces common challenges identified in the existing literature such as the lack of personalized information [ 9 , 10 , 11 ], loss of autonomy during hospitalization [ 14 , 74 , 75 ], difficulties in obtaining medication at discharge [ 11 , 45 , 76 ] and challenges in understanding treatment modifications and generics substitution [ 11 , 32 , 77 , 78 ]. Some of these studies were conducted during patients’ hospitalization [ 10 , 75 , 79 ] or up to 12 months after discharge [ 80 , 81 ], but most studies focused on the few days following hospital discharge [ 9 , 11 , 14 , 82 ]. Qualitative studies on medications at transition often focused on a specific topic, such as medication information, or a specific moment in time, and often included healthcare professionals, which muted patients’ voices [ 9 , 10 , 11 , 47 , 49 ]. Our qualitative longitudinal methodology was interested in capturing the temporal dynamics, in-depth narratives, and contextual nuances of patients’ medication experiences during transitions of care [ 59 , 83 ]. This approach provided a comprehensive understanding of how patients’ perspectives and behaviors evolved over time, offering insights into the complex interactions of medication management, understanding and adherence, and turning points within their medication journeys. A qualitative longitudinal design was used by Fylan et al. to underline patients’ resilience in medication management during and after discharge, by Brandberg et al. to show the dynamic process of self-management during the 4 weeks post-discharge and by Lawton et al. to examine how patients with type 2 diabetes perceived their care after discharge over a period of four years [ 49 , 50 , 51 ]. Our study focused on the first two months following hospitalization and future studies should focus on following discharged and at-risk patients over a longer period, as “transitions of care do not comprise linear trajectories of patients’ movements, with a starting and finishing point. Instead, they are endless loops of movements” [ 47 ].

Our results provide a particularly thorough description of how participants move from a state of total dependency during hospitalization regarding their medication management to a sudden and complete autonomy after hospital discharge impacting medication management, understanding, and adherence in the first days after discharge for some participants. Several qualitative studies have described the lack of shared decision-making and the loss of patient autonomy during hospitalization, which had an impact on self-management and created conflicts with healthcare professionals [ 75 , 81 , 84 ]. Our study also highlights nuanced patient experiences, including varying levels of patient needs, involvement, and proactivity during hospitalization and outpatient care, and our results contribute to capturing different perspectives that contrast with some literature that often portrays patients as more passive recipients of care [ 14 , 15 , 74 , 75 ]. Shared decision-making and proactive medication are key elements as they contribute to a smoother transition and better outcomes for patients post-discharge [ 85 , 86 , 87 ].

Consistent with the literature, the study identifies some challenges in medication initiation post-discharge [ 16 , 17 , 88 ] but our results also describe how daily routine rapidly takes over, either solidifying adherence behavior or generating barriers to medication adherence. Participants’ nonadherence prior to hospitalization was a factor influencing participants’ adherence post-hospitalization and this association should be further investigated, as literature showed that hospitalized patients have high scores of non-adherence [ 89 ]. Mortel et al. showed that more than 20% of discharged patients stopped their medications earlier than agreed with the physician and 25% adapted their medication intake [ 90 ]. Furthermore, patients who self-managed their medications had a lower perception of the necessity of their medication than patients who received help, which could negatively impact medication adherence [ 91 ]. Although participants in our study had high BMQ scores for necessity and lower scores for concerns, some participants expressed doubts about the need for their medications and a lack of motivation a few weeks after discharge. Targeted pharmacy interventions for newly prescribed medications have been shown to improve medication adherence, and hospital discharge is an opportune moment to implement this service [ 92 , 93 ].

Many medication changes were made during the transition of care (a median number of 7 changes during hospitalization and 7 changes during the two months after discharge), especially medication additions during hospitalization and interruptions after hospitalization. While medication changes during hospitalization are well described, the many changes following discharge are less discussed [ 7 , 94 ]. A Danish study showed that approximately 65% of changes made during hospitalization were accepted by primary healthcare professionals but only 43% of new medications initiated during hospitalization were continued after discharge [ 95 ]. The numerous changes after discharge may be caused by unnecessary intensification of medications during hospitalization, delayed discharge letters, lack of standardized procedures, miscommunication, patient self-management difficulties, or in response to an acute situation [ 96 , 97 , 98 ]. During the transition of care, in our study, both new and experienced participants were faced with difficulties in managing and understanding medication changes, either for newly prescribed medication or changes in previous medications. Such difficulties corroborate the findings of the literature [ 9 , 10 , 47 ] and our results showed that the lack of understanding during hospitalization led to participants having questions about their medications, even weeks after discharge. Particular attention should be given to patients’ understanding of medication changes jointly by physicians, nurses and pharmacists during the transition of care and in the months that follow as medications are likely to undergo as many changes as during hospitalization.

Implication for practice and future research

The patients’ perspectives in this study showed, at a system level, that there was a lack of standardization in healthcare professional practices regarding medication dispensing and follow-up. For now, in Switzerland, there are no official guidelines on medication prescription and dispensation during the transition of care although some international guidelines have been developed for outpatient healthcare professionals [ 3 , 99 , 100 , 101 , 102 ]. Here are some suggestions for improvement arising from our results. Patients should be included as partners and healthcare professionals should systematically assess (i) previous medication adherence, (ii) patients’ desired level of involvement and (iii) their needs for information during hospitalization. Hospital discharge processes should be routinely implemented to standardize hospital discharge preparation, medication prescribing, and dispensing. Discharge from the hospital should be planned with community pharmacies to ensure that all medications are available and, if necessary, doses of medications should be supplied by the hospital to bridge the gap. A partnership with outpatient healthcare professionals, such as general practitioners, community pharmacists, and homecare nurses, should be set up for effective asynchronous interprofessional collaboration to consolidate patients’ medication management, knowledge, and adherence, as well as to monitor signs of deterioration or adverse drug events.

Future research should consolidate our first attempt to develop a framework to better characterize medication at the transition of care, using Fig. 2   as a starting point. Contextualized interventions, co-designed by health professionals, patients and stakeholders, should be tested in a hybrid implementation study to test the implementation and effectiveness of the intervention for the health system [ 103 ].

Limitations

This study has some limitations. First, the transcripts were validated for accuracy by the interviewer but not by a third party, which could have increased the robustness of the transcription. Nevertheless, the interviewer followed all methodological recommendations for transcription. Second, patient inclusion took place during the COVID-19 pandemic, which may have had an impact on patient care and the availability of healthcare professionals. Third, we cannot guarantee the accuracy of some participants’ medication history before hospitalization, even though we contacted the participants’ main pharmacy, as participants could have gone to different pharmacies to obtain their medications. Fourth, our findings may not be generalizable to other populations and other healthcare systems because some issues may be specific to multimorbid patients with type 2 diabetes or to the Swiss healthcare setting. Nevertheless, issues encountered by our participants regarding their medications correlate with findings in the literature. Fifth, only 15 out of 21 participants took part in all the interviews, but most participants took part in at least three interviews and data saturation was reached. Lastly, by its qualitative and longitudinal design, it is possible that the discussion during interviews and participants’ reflections between interviews influenced participants’ management, knowledge, and adherence, even though this study was observational, and no advice or recommendations were given by the interviewer during interviews.

Discharged patients are willing to take steps to better manage, understand, and adhere to their medications, yet they are also faced with difficulties in the hospital and outpatient care. Furthermore, extensive changes in medications not only occur during hospitalization but also during the two months following hospital discharge, for which healthcare professionals should give particular attention. The different degrees of patients’ involvement, needs and resources should be carefully considered to enable them to better manage, understand and adhere to their medications. At a system level, patients’ experiences revealed a lack of standardization of medication practices during the transition of care. The healthcare system should provide the ecosystem needed for healthcare professionals responsible for or involved in the management of patients’ medications during the hospital stay, discharge, and outpatient care to standardize their practices while considering the patient as an active partner.

Data availability

The anonymized quantitative survey datasets and the qualitative codes are available in French from the corresponding author on reasonable request.

Abbreviations

adverse drug events

Adherence Visual Analogue Scale

Belief in Medication Questionnaire

Consolidated Criteria for Reporting Qualitative Research

case report form

standard deviation

World Health Organization

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Acknowledgements

The authors would like to thank all the patients who took part in this study. We would also like to thank the Geneva University Hospitals Patients Partners + 3P platform as well as Mrs. Tourane Corbière and Mr. Joël Mermoud, patient partners, who reviewed interview guides for clarity and significance. We would like to thank Samuel Fabbi, Vitcoryavarman Koh, and Pierre Repiton for the transcriptions of the audio recordings.

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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LS, GG, and MS conceptualized and designed the study. LS and GG screened and recruited participants. LS conducted the interviews. LS, GG, and MS performed data analysis and interpretation. LS drafted the manuscript and LS and MS worked on the different versions. MS and GG approved the final manuscript.

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Solh Dost, L., Gastaldi, G. & Schneider, M. Patient medication management, understanding and adherence during the transition from hospital to outpatient care - a qualitative longitudinal study in polymorbid patients with type 2 diabetes. BMC Health Serv Res 24 , 620 (2024). https://doi.org/10.1186/s12913-024-10784-9

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methodology in research steps

Green PLM: business goals-oriented algorithm assessing the greenness of a product in the new product development phase for the automotive industry

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methodology in research steps

  • Maria Rosienkiewicz   ORCID: orcid.org/0000-0002-6976-352X 1 , 2 ,
  • Joanna Helman   ORCID: orcid.org/0000-0002-4239-674X 1 , 2 ,
  • Mariusz Cholewa   ORCID: orcid.org/0000-0002-7263-4454 1 , 2 ,
  • Mateusz Molasy   ORCID: orcid.org/0000-0001-6390-9711 1 , 2 ,
  • Sylwester Oleszek   ORCID: orcid.org/0000-0001-8920-6715 3 &
  • Giovanni Berselli   ORCID: orcid.org/0000-0003-0093-3006 4 , 5  

Sustainability-oriented new product development process is becoming of key importance in many sectors of the industry. Especially in the automotive industry, it plays a major role as this sector is historically associated with resource-intensive production and fossil fuel consumption, and thus has to implement solutions that will contribute to restraint of climate change. Manufacturing companies are currently faced with the challenge of adapting their business models to changing market expectations and requirements resulting from the sustainable development path. Moreover, the development of the new digital factories and pressure from the legislators require adjustment of existing Product Lifecycle Management systems. To enhance the concept of the Green Product Lifecycle Management which is still under development, in this work we propose a new three-step methodology composed of three main steps: (1) assessing indicators’ importance for sustainable business goals and business models, (2) assessing indicators and their importance in the automotive industry, (3) assessing “greenness” of the product. This complex approach is innovative as it is based on the business-oriented perspective. Selecting suitable business goals and corresponding business models leads to the selection of the appropriate subset of green indicators. Several more aspects are taken into account in this holistic analysis: the indicator's features, relevance for the company, importance to sustainable business goals, importance in terms of subsectors of the automotive industry as well as environmental, economic, and social impact. This approach enables the company to compute the value of the greenness of the product in reference to the key green indicators.

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1 Introduction

Sustainability-oriented new product development (NPD) process is becoming of key importance in many sectors of the industry. Especially in the automotive industry, it plays a major role as this sector is historically associated with resource-intensive production and fossil fuel consumption, and thus has to implement solutions that will contribute to restraint of climate change. Embracing sustainability in the new product development process is in fact a strategic necessity for the automotive industry's long-term viability. Practices based on green economy, circular economy, and sustainability not only lead to reducing the net greenhouse gas emissions but also enhancing overall corporate responsibility. When designing a new product, a company is faced with the choice of hundreds, if not thousands, of possible variants ranging from the use of eco-friendly materials to the integration of energy-efficient manufacturing technologies. Selection of the optimal variant of the final product is extremely tough nowadays—it is often a compromise between manufacturing cost, time, and environmental footprint. Therefore, from the scientific point of view, it is very important to support industrial companies with solutions enabling the proper choice in this context. What is more, sustainability-oriented new product development process is in line with the growing consumer demand for environmentally conscious choices, thus fostering brand loyalty and market competitiveness. As the world struggles with the urgent need to transition towards greener economies, the automotive industry's commitment to sustainability not only mitigates environmental, economic, and social impacts but also positions it as a proactive contributor to global efforts in achieving a more sustainable future. Without a doubt, companies operating in the automotive sector are and will be—both directly and indirectly—forced to change their manufacturing processes in order to meet regulations concerning environmental protection. In Europe, a number of documents indicate a direction in which manufacturing companies should be oriented—e.g.:

European green deal which is trying “to make the EU's climate, energy, transport and taxation policies fit for reducing net greenhouse gas emissions by at least 55% by 2030, compared to 1990 levels” (“The European Green Deal” 2021 );

Fit for 55 package which “is a set of proposals to revise and update EU legislation and to put in place new initiatives with the aim of ensuring that EU policies are in line with the climate goals agreed by the Council and the European Parliament” (“Fit for 55” 2023 );

Circular economy action plan which provides “provides a future-oriented agenda for achieving a cleaner and more competitive Europe in co-creation with economic actors, consumers, citizens and civil society organisations. It aims at accelerating the transformational change required by the European Green Deal, while building on circular economy actions” (Commission and Communication 2020 );

Ecodesign directive that successfully regulates energy efficiency and some circularity features of energy-related products ( Directive 2009 /125/EC of the European Parliament and of the Council of 21 October 2009 establishing a framework for the setting of ecodesign requirements for energy-related products (recast) (Text with EEA relevance) 2009 );

EU ecolabel “ helps consumers, retailers and business make truly sustainable choices. The EU Ecolabel logo has become a byword for quality while meeting the highest environmental standards. It means products (goods and services) displaying the iconic "EU flower" symbol meet all the criteria and have earned the right to join the growing EU Ecolabel Community” ( Regulation (EC) No 66/2010 of the European Parliament and of the Council of 25 November 2009 on the EU Ecolabel (Text with EEA relevance) 2009 );

EU green public procurement (GPP) is defined as "a process whereby public authorities seek to procure goods, services and works with a reduced environmental impact throughout their lifecycle when compared to goods, services and works with the same primary function that would otherwise be procured"(“Green Public Procurement” n.d.).

Carbon border adjustment mechanism (CBAM) regulation it is “one of the key elements of the European Union’s ‘Fit for 55’ package.(…) CBAM targets imports of carbon-intensive products, in full compliance with international trade rules, to prevent offsetting the EU’s greenhouse gas emissions reduction efforts through imports of products manufactured in non-EU countries, where climate change policies are less ambitious than in the European Union. It will also help prevent the relocation of the production or the import of carbon-intensive products. The products of the following sectors will be covered by CBAM: cement, aluminium, fertilisers, electric energy production, iron and steel”(“Council agrees on the Carbon Border Adjustment Mechanism (CBAM)” n.d.).

Bearing in mind the above-listed issues, it can be stated that the development of solutions enhancing companies from the automotive industry in the new product development process is of high importance. Therefore, the research presented in this paper focus on this particular topic. On the contrary to well-known methods used widely in the industry (like e.g. Lifecycle Assesment LCA) the authors of this paper propose a new approach in assessing greeness of a product—it is based on a business goals-oriented algorithm applied to the new product development phase for the automotive industry. The presented paper is divided into 5 main chapters. At first literature review is presented and discussed. Literature analysis covers topics related to (1) sustainability-oriented business models, (2) Green Product Lifecycle Management (PLM) and (3) automotive industry. Based on obtained results, the aim of research is defined. Subsequently, a three-step research methodology is described and explained. Finally, results and conclusions are presented. The research—based on which the paper was created—was carried out within the GreenPLM project commissioned by Transition Technologies PSC S.A. This paper is a follow-up of a paper entitled “Towards GreenPLM—Key Sustainable Indicators Selection and Assessment Method Development” (Helman et al., 2023 ). In the mentioned paper the primary scientific goal was to offer a methodical way to choose and assess sustainability indicators for use in the various stages of the automotive lifecycle management. By determining which sustainability indicators are pertinent to each stage of the product lifecycle, the application's principal objective is to assist the industry in its pursuit of more environmentally friendly development. As a result, the important green indicators for the automotive sector in line with the GreenPLM concept are highlighted, together with their classification into the early stages of the car's lifecycle and prospective data sources. The paper written by Helman et al. introduces the idea of GreenPLM and the potential uses for it in the future (Helman et al., 2023 ). In the present paper, further analysis is carried out, which focuses on the development of a new—based on sustainability- oriented business goals—approach enabling assessing greenness of a product in the automotive industry.

2 Literature analysis

2.1 sustainability-oriented business models.

Nowadays, a highly developed economy and strong market competitiveness force companies not only to continuously increase the effectiveness in every area, but also—like never before—to take into consideration environmental aspects (Kochańska, 2024 ). Manufacturing companies are currently faced with the challenge of adapting their business models to changing market expectations and requirements resulting from the sustainable development path. Business model can be defined as “a conceptual tool containing a set of objects, concepts and their relationships with the objective to express the business logic of a specific firm” (Osterwalder et al., 2005 ). It helps to understand how a company does a business and it can be used for analysis, comparison and performance assessment, management, communication, and innovation (Bocken et al., 2014 ). It answers a series of questions essential to any business, i.e. who are the customers, what do they value, how that value can be delivered to the customer at an appropriate cost and how the business deploys its assets. Business model includes a description of the key assets and are concerned with how the firm defines its competitive strategy through the design of the product or service it offers to its market, how it charges for it, what it costs to produce, how it differentiates itself from other firms by the value proposition, and how the firm integrates its own value chain with those of other firm’s in a value network (Rasmussen, 2007 ). Business models cover two main spheres: the first sphere is operations and related resources, the second sphere is about created and captured value (Rudnicka, 2016 ). The central point of every business model is value proposition (“BS8001:, 2017 BSI Knowledge” 2017 ). As presented in the Introduction, changing business models into those supporting green economy, circular economy and sustainability is no longer a need, but rather necessity. Business models (innovations) for sustainability can be defined as “innovations that create significant positive and/or significantly reduced negative impacts for the environment and/or society, through changes in the way the organization and its value-network create, deliver value and capture value (i.e. create economic value) or change their value propositions” (Bocken et al., 2014 ). Also, the transition to a circular economy requires significant changes in the way organizations operate. The transition to the circular economy often entails holistic adaptations in firms' business models or even the creation of new ones. The implementation of circular economy principles often requires new visions and strategies and a fundamental redesign of product concepts, service offerings, and channels towards long-life solutions. CE principles also affect how companies can make money, with the ownership structure perhaps shifting, boosting demand for services along the product lifecycle (Ferasso et al., 2020 ). Early developments of sustainable business models link the concept of sustainability with innovation. Namely, the sustained success of an organization depends on innovation. Rules determining the functioning of a sustainable business model need to be based on creating technological innovations that can create new markets after being commercialized (Boons & Lüdeke-Freund, 2013 ). Schaltegger et al. define a business model for sustainability as one which helps in describing, analyzing, managing, and communicating as follows (Schaltegger et al., 2016 ):

a company’s sustainable value proposition to its customers, and all other stakeholders,

how it creates and delivers this value,

how it captures economic value while maintaining or regenerating natural, social, and economic capital beyond its organizational boundaries.

Wells states that “a sustainable product cannot be produced by an unsustainable industry” (Wells, 2013 ). The author considers defining a sustainable automotive industry that is “one that creates life-enhancing employment for communities over a long period of time. It has zero net consumption of physical resources in production. It is consistently profitable while being able to withstand short-term fluctuations in economic circumstances. And it produces products that themselves do not pollute or otherwise degrade the environment, are fit for purpose, and are designed for longevity” (Wells, 2013 ). This definition suggests that, over time, manufacturing as such (of new, complete products) is only a small part of the business model, that concepts such as product-service systems are more appropriate. It is recognised that profitability is absolutely vital for sustainability. However, profitability is a necessary but insufficient condition for sustainability: the environmental and social dimensions must also be included.

Jonker and O’Riordan define four criteria that a sustainable business model must meet. They are: sharing knowledge, making connections (sustainability is between companies), awareness and multiple value creation (Jonker & O’Riordan, 2016 ). As the traditional business model elements are insufficient for showing the full relationships and values into the direction of sustainable development in business context, Rudnicka presented elements of business models including sustainability issues in (Rudnicka, 2016 ). Bocken et al. identified eight sustainable business model archetypes on the basis of analysis of practice and literature business model examples. The archetypes are classified in higher order groupings that describe main types of business models innovations: technological, social, and organizational oriented innovations. They are as follows (Bocken et al., 2014 ):

maximizing material and energy efficiency,

creating value from ‘waste’,

substitute with renewables and natural processes,

delivering functionality rather than ownership,

adopting a stewardship role,

encouraging sufficiency,

re-purposing the business for society/environment,

developing scale-up solutions.

Clinton and Whisnart presented 20 business model innovations for sustainability. They have been categorized into 5 categories, however authors admit that some business models fit into multiple categories. They are as follows (Clinton & Whisnant, 2019 ):

category of environmental impact

Closed Loop Production,

Physical to Virtual,

Produce on Demand,

Rematerialization,

category of social impact

Buy One, Give One,

Cooperative Ownership,

Inclusive Sourcing,

category of financial impact

Crowdfunding,

Differential Pricing,

Innovative product financing,

Pay for Success,

category of social innovation focused on “the base of the pyramid”

Building a Marketplace,

Microfinance,

Micro-Franchise,

Subscription Model,

category of diverse impact

Alternative Marketplaces,

Behavior Change,

Product as a Service,

Shared Resource.

The value proposition seems central to any business model, because it defines the products/services that create value for the organization’s existing and/or new customer base. It also relates to the viability of the business model, because it identifies how the organization makes money. For organizations transitioning to more circular and sustainable operations, the value proposition might not be solely financial in nature and instead reflect delivery of wider social and/or environmental benefits (“BS8001:, 2017 BSI Knowledge” 2017 ). Referring to the circular economy, Mentink ( 2014 ) identified the changes of business model components needed for developing a more circular service model. They are as follows:

“value propositions (what?)—products should become fully reused or recycled, which requires reverse logistics systems, or firms should turn towards product-service system (PSS) and sell performance related to serviced products‚

activities, processes, resources and capabilities (how?)—products have to be made in specific processes, with recycled materials and specific resources, which may require not only specific capabilities but also creating reverse logistics systems and maintaining relationships with other companies and customers to assure closing of material loops,

revenue models (why?)—selling product-based services charged according to their use‚

customers or customer interfaces (who?)—selling circular products or services may require prior changes of customer habits or, if this is not possible, even changes of customers” (Lewandowski, 2016 ).

Laubscher and Marinelli (Laubscher & Marinelli, 2014 ) identified six key areas for integration of the circular economy principles with the business model. They are as follows: sales mode, product design/material composition, IT/data management, supply loops, strategic sourcing for own operations, HR/incentives (Lewandowski, 2016 ).

In order to provide a framework for and guidance on implementing the principles of the circular economy within organizations, the British norm BS 8001:2017 has been developed (“BS8001:, 2017 BSI Knowledge” 2017 ). The guidance is intended to apply to any organization, regardless of location, size, sector and type. In the norm six general business model groupings have been introduced that have the potential to be compatible with a circular economic system. They are as follows and they include following specific business models (“BS8001:, 2017 BSI Knowledge” 2017 ):

business model “produce on demand/made to order”,

Dematerialization

business model “digitalization”,

Product lifecycle extension/reuse

business model “product life‑extension”,

business model “facilitated reuse”,

business model “product modular design”,

business model “refurbish, repair, remanufacture and recondition”.

Recovery of secondary raw materials/by‑products

business model “recovery of secondary materials/by‑products (including recycling)”,

business model “incentivized return/extended producer responsibility”.

product as a service/product–service system (PSS)

business model “lease agreement”,

business model “performance based (pay for success)”,

sharing economy and collaborative consumption

business model “sharing economy”,

business model “sharing platforms/resources (collaborative consumption)”.

It has been assumed that these business models are not mutually exclusive. In order to realize its value proposition an organization might need to adopt a business model which includes elements of each of them. Moreover, complex organizations might concurrently have different business models operating across their divisions/units and for different product/markets (“BS8001:, 2017 BSI Knowledge” 2017 ).Popular circular economy business models collected by Lewandowski are as follows (Lewandowski, 2016 ):

classification criteria: renegade

Energy recover—the conversion of non-recyclable waste materials into useable heat, electricity, or fuel,

Circular supplies—using renewable energy,

Efficient buildings—locating business activities in efficient buildings,

Sustainable product locations—locating business in eco-industrial parks,

Chemical leasing—the producer mainly sells the functions performed by the chemical, so the environmental impacts and use of hazardous chemical are reduced,

classification criteria: share

Maintenance and Repair—product lifecycle is extended through maintenance and repair,

Collaborative Consumption, Sharing Platforms, PSS Footnote 1 : Product renting, sharing or pooling—enable sharing use, access, or ownership of product between members of the public or between businesses,

PSS: Product lease—exclusive use of a product without being the owner,

PSS: Availability based—the product or service is available for the customer for a specific period of time,

PSS: Performance based—the revenue is generated according to delivered solution, effect or demand-fulfillment,

Incentivized return and reuse or Next Life Sales—customers return used products for an agreed value. Collected products are resold or refurbished and sold,

Upgrading—replacing modules or components with better quality ones,

Product Attachment and Trust—creating products that will be loved, liked or trusted longer,

Bring your own device—users bring their own devices to get the access to services,

Hybrid model—a durable product contains short-lived consumables,

Gap-exploiter model—exploits “lifetime value gaps” or leftover value in product systems. (e.g., shoes lasting longer than their soles),

classification criteria: optimize

Asset management—internal collection, reuse, refurbishing and resale of used products,

Produce on demand—producing when demand is present and products were ordered,

Waste reduction, Good housekeeping, Lean thinking, Fit thinking—waste reduction in the production process and before,

PSS: Activity management/outsourcing—more efficient use of capital goods, materials, human resources through outsourcing,

classification criteria: loop

Remanufacture, Product Transformation—restoring a product or its components to “as new” quality,

Recycling, Recycling 2.0, Resource Recovery—recovering resources out of disposed products or by-products,

Upcycling—materials are reused and their value is upgraded,

Circular Supplies—using supplies from material loops, bio based- or fully recyclable,

classification criteria: virtualize

Dematerialized services—shifting physical products, services or processes to virtual,

classification criteria: exchange

New technology—new technology of production.

On the basis of analysis of fore mentioned business models Lewandowski ( 2016 ) proposes a circular business model canvas, that is extended and adjusted to the circular economy version of the business model canvas developed by Osterwalder and Pigneur ( 2010 ). The building blocks allow for designing of a business model according to the principles of circular economy, and consists of value propositions, customer segments, channels, customer relationships, revenue streams, key resources, key activities, key partnerships, cost structure, take-back system, adoption factors (Lewandowski, 2016 ). Another nineteen circular business models grouped into 6 groups have been proposed by IMSA, an independent think tank and consultancy & research firm committed to the environment, sustainability and innovation, headquartered in Amsterdam. They can be found in (“Circular Future—Public Affairs and consultancy about Circular Economy” 2022 ). Four main business models that circulate products and materials in the economy, and have the potential to decouple revenue streams from production and resource use, have been presented by Ellen MacArthur Foundation. They are: “Resale” business model, “Rental” business model, “Repair” business model, “Remaking” business model (Ellen MacArthur Foundation, 2021 ). The business model approach seems useful for analyzing and improving sustainability, because business models can be viewed as activity systems that cover internal and external activities in which companies are engaged. When activities represent sustainable issues, they are best represented by the practical descriptions, communication, and expression of activities of companies (Ritala et al., 2018 ). Analysis of Green Supply Chain Management operations used by Ford, BMW, Toyota, and BYD has been performed by Sanghavi et. al and is presented in (Sanghavi et al., 2015 ).

Literature review focused on sustainability-oriented business models shows that a lot of studies have been dedicated to this topic. Numerous classifications have been developed and described. Companies, depending on their business goals, can suitably choose a proper business model to start their transition process towards sustainability and green economy.

2.2 Green product lifecycle management

Product Lifecycle Management is facing a major change. New phenomena are emerging in new product development—including crowdsourcing, crowdfunding, and gamification (Molasy et al., 2023 ). Development of the new digital factories and pressure from the legislators require adjustment of existing PLM systems. They need to support the companies in terms of collaborative processes and workflows to enhance sustainable information sharing.

According to Belkadi et al., the key challenge in this context is not only the definition of information flow between all involved entities in the sustainability process but also the mapping of information between different production lifecycle phases (Belkadi et al., 2015 ). In the investigated area a number of definitions have been developed to better precise the emerging area, including sustainable products (Bangsa & Schlegelmilch, 2020 ), Closed Loop Lifecycle Management (CL2M), Green Information Systems, Sustainable PLM, and Intelligent Products (Främling et al., 2013 ). In terms of sustainable products a number of indicators can be considered in order to provide the customers with the appropriate assurance and information about their sustainability performance (Bangsa & Schlegelmilch, 2020 ). According to Främling et al. Sustainable PLM can be defined as a type of Closed Loop Lifecycle Management (CL2M). The key feature is the possibility to connect Intelligent Products with each other and at the same time with other information systems. The systems that are called Green Information Systems (Green IS) aim at reducing environmental impacts (Främling et al., 2013 ). Their focus is to reduce”the production of CO 2 and other greenhouse gases through new combinations of people, processes, and technologies that enable the processing of digitized information” (Främling et al., 2013 ). Främling et al. underline that the main purpose of CL2M is to constantly improve design, manufacturing, use and end-of-life handling of products, in order to obtain "improved quality, less breakdowns, reduced need for spare parts and ensuring an operation that is continuously maintained at the most energy- and resource-efficient level” (Främling et al., 2013 ). According to Främling et al. Sustainable PLM should be understood as CL2M for the purpose of improving environmental sustainability during all phases of the lifecycle. A key issue in terms of Sustainable PLM or so called Green PLM is related to measurement of environmental sustainability and ways to improve it. Therefore, it is crucial to measure, gather, and analyse data and corresponding indicators which can be a firm basis and a trigger for companies in their shift towards green production. A helpful approach in this process is LCA, which stands for Lifecycle Assessment or Lifecycle Analysis defined a methodological framework for estimating and assessing the environmental impacts attributable to the lifecycle of a product (Främling et al., 2013 ). According to Främling et al., it is hard to extend and/or adapt existing ERP systems to the requirements of Sustainable PLM. Främling et al. state that “it is likely that an easier, safer, and more scalable approach is to develop and increase the use of Intelligent Product-based information systems separately and communicate with stock-based information systems using their own external interfaces. The multi-organizational, multi-manufacturer, etc., reality and requirements of Sustainable PLM can only be met in a scalable way if ad hoc, loosely coupled interoperability between devices and other information systems is technically easy and economically feasible enough. Failing to recognize the importance of loosely coupled integration can delay the speed of evolution and adoption of Sustainable PLM” (Främling et al., 2013 ). According to Vila et al. ( 2015 ) a Green PLM strategy should be composed of mission, vision and objective. They propose an approach to product lifecycle with green competencies as well as Green Product Lifecycle Framework. Green Product Lifecycle Framework should be composed of 3 main phases (Vila et al., 2015 ):

Design-Development phase, focused on Eco Design and Green Development, composed of: Strategic Planning, Conceptual Design, Embodiment Design, Detail Design, Manufacturing Plan;

Manufacturing phase focused on Green Manufacturing and Sustainable Production, composed of: Storage Package, Assembly, Production, Production Control, Resource Management;

Service phase, focused on Sustainable Logistics, Product Special Response and Responsible Use and Maintenance, composed of: Logistics, Sales, Delivery, Client Service, Reduce/Reuse/Retire/Recycle;

For each of the 3 above-mentioned phases, Vila et al. propose an approach based on dedicated methods, tools and knowledge, as follows (Vila et al., 2015 ):

Design-Development phase:

Methods : Design for environment (Eco Design), Eco-standards application

Tools : Eco CAD/CAE/CAM tools, Lifecycle management tools (PLM)

Knowledge : Product lifecycle assessment, Materials and process selection

Manufacturing phase:

Methods : Design for sustainable manufacturing, Green Supply chain management

Tools : Green manufacturing, Intelligent/smart sensors/controls, Green energies

Knowledge : New materials, New manufacturing technologies

Service phase:

Methods : Design for Sustainable Maintenance, Sustainable service system

Tools : Product Usefulness Time Control, Sustainable Use Scorecard

Knowledge : Energy consumption (CO2 impact), Maintenance and care.

Marcon et al. propose another framework for a green product. They divided green product attributes' groups into 3 main product lifecycle phases, namely—(1) Production, (2) Use and (3) End-of-life (Marcon et al., 2022 ). Recently, the Brazilian automotive industry has been pressured by stricter environmental laws and regulations focusing on adopting more green production processes, whereas consumers have increased demand for green products. In this context, De Medeiros et al. investigated behavioural motivation for green product consumption. They focused their research on the decision-making process regarding the purchase of cars and furniture (de Medeiros et al., 2016 ). According to the obtained results de Medeiros et al. prove that “if the prices of products with and without ecological appeal were the same, 95% of the respondents would prefer to buy the green product”. This key finding from this research provides the manufacturers with very important information.

2.3 Automotive industry insight

The automotive industry comprises of a wide range of companies and organizations involved in the design, development, manufacturing, marketing, and selling of motor vehicles. It can be divided into sectors in many different aspects. For the purpose of this research the four classifications were taken into account—namely: (1) Global Industry Classification Standard, (2) Industry classification taxonomy, (3) Refinitiv Business Classification and (4) Automotive supply chain actors.

The Global Industry Classification Standard, developed by S&P Dow Jones Indices, was designed in response to the global financial community’s need for accurate, complete and standard industry definitions (“Global Industry Classification Standard” 2018 ). The GICS structure consists of 11 Sectors, 24 Industry groups, 69 Industries and 158 sub-industries. Under the sector of Consumer Discretionary, the Automobiles & Components industry group can be found. It is divided into two industries with two sub-industries (each) are indicated. They are as follows:

Auto Components

Auto Parts and Equipment

Tires and Rubber

Automobiles

Automobile Manufacturers

Motorcycle Manufacturers

Industry classification taxonomy developed for the Industrial Classification Benchmark (ICB) is a widely used standard of detailed and comprehensive structure for sector and industry analysis, facilitating the comparison of companies across four levels of classification and national boundaries. Its taxonomy covers a robust system of 11 Industries with 20 Supersectors and 45 Sectors detailed into 173 Subsectors (“Industry Classification Benchmark” 2022 ). Under the industry of Consumer Discretionary, the supersector of Automobiles and Part can be found. It is divided into 4 subsectors (“Industry Classification Benchmark” 2022 ):

Auto Services—Companies that provide assistance to individual vehicle owners.

Tires—Manufacturers, distributors and retreaders of automobile, truck and motorcycle tires

Automobiles—Makers of passenger vehicles, including cars, sport utility vehicles (SUVs) and light trucks. Excludes makers of heavy trucks and makers of recreational vehicles (RVs and ATVs).

Auto Parts—Manufacturers and distributors of new and replacement parts for motorcycles and automobiles, such as engines, carburettors and batteries. Excludes producers of tires, which are classified under Tires Subsector.

A similar division is presented by Refinitiv Business Classification (previously called Reuters Business Sector Scheme as well as Thomson Reuters Business Classification, developed by the Reuters Group. It is a market-based classification scheme, similar to the GICS and ICB systems. The automotive industry is represented by Consumer Cyclicals economic sectors in Automobiles & Auto Parts business sector. The industry group of Automobiles & Auto Parts covers 3 types of industries that are divided into the following activities (“TRBC Sector Classification” n.d.):

Auto and Truck Manufacturers

Motorcycles and Scooters

Automobiles and Multi Utility Vehicles

Light Trucks

Electric (Alternative) Vehicles

Luxury Vehicles

Auto & Truck Wholesale

Auto, Truck & Motorcycle Parts

Automotive Body Parts

Engine & Powertrain Systems

Automotive Batteries

Automotive Systems

Automotive Accessories

Motorcycle Parts & Accessories

Auto & Truck Parts Wholesale

Tires & Rubber Products

Tire & Tube Manufacturers

Tire Retreading

Industrial Rubber Products

Rubber Plantations

Tires & Rubber Products Wholesale

The other type of the classification of the automotive industry is its division into supply chain actors, where at least 4 levels can be distinguished (“Driving Innovation for Automotive Manufacturing Tier 1 Suppliers” n.d.):

Tier 3—suppliers of raw and semi-raw materials,

Tier 2—non-automotive grade parts,

Tier 1—automotive parts and systems,

OEM—Original Equipment Manufacturer.

Above-presented classifications prove that the automotive industry is complex and is divided into many subsectors. Its influence from the global perspective is huge. Thus, the car sector is regarded as one of the primary causes of the environmental problem on the planet. Additionally, it has been demonstrated that the social and environmental aspects are negatively impacted by existing methods in the automotive industry. On the other hand, any nation's economic development depends heavily on the automotive industry. As a result, the sector needs to drastically alter its current operational procedures (Helman et al., 2023 ). Currently, according to Golinska-Dawson ( 2019 ) the Automotive Parts Remanufacturers Association (APRA) “identifies over 50 different components which are currently remanufactured”. Although the material flow in remanufacturing process can be assessed as much more complex than in the primary manufacturing process (Golinska-Dawson & Pawlewski, 2015 ), Kosacka-Olejnik et al. ( 2020 ) emphasise that remanufacturing is set to become an increasingly important player in the future manufacturing industry with an EU market potential of €90 billion by 2030 according to the European Remanufacturing Network. Certain publications mention that sustainability-oriented goals are still not seen as being as significant in the manufacturing sector as traditional productivity targets, yet this is slowly changing (Kochańska & Burduk, 2023 ). Sliż and Wycinka underline that in order to decrease the negative influence on the economy and environment, attempts are made to design vehicles in a way which reduces both CO 2 emissions, and fuel consumption as well as replaces internal combustion engines with electric units (Sliż & Wycinka, 2021 ). To reduce negative environmental impact, engine emission standards are getting stricter – i.a. ambitious goals to reduce the concentrations of hazardous compounds in the exhaust gases were supplemented by strict requirements for the reduction of the concentration and volume of solid particles (Žvirblis et al., 2023 ). It is crucial to develop methods that allow to perform the same processes but with the more ecologically-oriented solutions—i.e. by the reduction of pollutant emissions (Łapczyńska, 2023 ) or by optimizing transportation processes, as they are one of the most important sources of waste, no matter how necessary transport is. (Kochańska et al. Early Access). All the mentioned requirements and trends cause the automotive industry to make the new product development process greener. Therefore, in the automotive sector, sustainability metrics, particularly those pertaining to the environmental aspect, have gained substantial attention.

2.4 Significance and aim

The literature review presented in the previous chapters leads to certain important conclusions. First of all, many business models for sustainability have been developed so far. Companies, depending on their business goals, can suitably choose a proper business model to start their transition process towards sustainability and a green economy. Moreover, the transition towards digital manufacturing and legislative pressure cause a need to modify the current PLM systems. They must assist the businesses with their collaborative workflows and processes in order to improve sustainability- and green-oriented processes. The concept of the Green Product Lifecycle Management is still under development. It can also be noted that the new product development (NPD) phase is crucial from the perspective of further environmental impact. In general, there are certain methods—the majority of them based on Lifecycle Assessment (LCA) approach, yet a dedicated solution based on sustainability-oriented business models is missing. Last, but not least, it should be emphasized that especially the automotive industry—due to its huge impact on the environment—requires a radical shift in the way it performs usual business practices Based on these conclusions, the main aim of the paper was derived. Bearing in mind a number of existing sustainability-oriented business models, and a need of development PLM systems towards greenness (especially in the NPD process) and major shift within the automotive industry, the main aim of this paper is to develop a new approach to assessing greenness of a product which would be based on a business goals-oriented algorithm and applied to the new product development phase for the automotive industry. This algorithm will be applied to the 20 indicators identified within the first stage of the research described in the paper “Towards GreenPLM—Key Sustainable Indicators Selection and Assessment Method Development” (Helman et al., 2023 ).

3 Research methodology

In order to reach the above-mentioned aim, the three-step research methodology was proposed. It is composed of 3 main steps:

Step 1 : assessing indicators’ importance for sustainable business goals and business models.

Step 2 : assessing indicators and their importance in the automotive industry.

Step 3 : assessing “greenness” of the product.

To assess the 20 indicators (selected in (Helman et al., 2023 )) in terms of their importance for sustainable business goals and business models, the step 1 of the research methodology—presented in Fig.  1 —has been developed. In the first stage, business goals need to be analyzed with respect to sustainability issues. Parallelly, business models focused on sustainability aspects should be analyzed. Next, to each of the defined business goals, corresponding business models must be identified, and their impacts on sustainability should be indicated (selecting from: environmental, economic and/or social). The final step of the methodology is to assign indicators that can be used to achieve defined business goals and corresponding business models.

figure 1

Step 1: Methodology of assessing indicators’ importance for sustainable business goals and business models; own elaboration

Once the 20 indicators will be assessed in terms of their importance for sustainable business goals and business models according to the step 1, the methodology for assessing indicators and their importance in the automotive industry will be applied (step 2). The scheme of the proposed methodology is presented in the figure below. At first five overarching assessment criteria are defined, namely:

Indicator's features,

Relevance for the company,

Importance to sustainable business goals,

Importance in terms of subsectors,

Environmental, Economic, Social impact.

Some of the overarching criteria have been detailed to more precisely assess the indicators:

Indicator's features:

availability of data,

durability (low variability over time),

need of monitor—cost of collecting,

preciseness/quality/confidence level,

ease of indicator-related data processing,

standardized indicator,

Importance in terms of subsectors:

Auto Services,

Automobiles,

Auto Parts,

Environmental, Economic, Social impact:

Environmental impact:

Raw material extraction,

Modification of natural area,

Economic impact:

Material cost of product,

Maintenance cost of product,

Manufacturing cost of product,

End-of-life cost of product,

Social impact:

Health and safety,

Socio-economic repercussion,

Governance by customers,

Human rights.

According to the step 2 of the research methodology presented in Fig.  2 , each assessment criterion has to be analyzed and rated. The ratings for particular criteria are presented in the figure above. Once the points are assigned, an overall criterion assessment has to computed—for each overarching criterion separately. Subsequently, all calculated values have to be normalized to enable mutual comparison and further analysis. Thus mean of the overall normalized assessment for all five criteria can be estimated. Finally, the indicators can be sorted from the most relevant to the least relevant and the key sustainability-oriented indicators for Green PLM can be identified.

figure 2

Step 2: Methodology for assessing importance of indicators for the Green PLM project

Once the key indicators are selected according to the step 2 of the methodology of assessing indicators and their importance in the automotive industry, they can be further analyzed in order to indicate how to use them in terms of the “greenness” of the product. The algorithm presented in Fig.  3 can serve as a tool helping a company to assess to what extent their product can be defined as “green”.

figure 3

Step 3: Algorithm assessing the “greenness” of a product

A scheme presenting the step 3 of the research methodology, which is an algorithm assessing the “greenness” of a product, is in the figure below. It is composed of 10 steps.

In order to initiate the algorithm assessing the “greenness” of a product, a company has to first determine its business goals. Next, based on that, relevant indicators should be selected. In the following step, values of the indicators should be defined and (if needed) results aggregated. Next, the corresponding values of the final product and the critical value of the indicators in terms of the greenness of the product need to be defined. Subsequently, results for all analyzed indicators should be calculated. If the results meet the criterion 1 point for each indicator is assigned. Within another step, the weight of each of the criteria has to be defined and then summed up (value X). Next, for each indicator, the point value has to be multiplied by the criterion's weight and then summed up (value Y). Finally, Y by X should be divided. The obtained value defines the level of greenness of the product in percentage terms.

4.1 Step 1: assessing indicators’ importance for sustainable business goals

In the following chapters, the results obtained from the described three-step research methodology will be presented. At first, the procedure of assessing green indicators’ importance for sustainable business goals will be applied.

According to the step 1 of the research methodology, business goals and business goals have to be identified at first. The review of numerous sustainability-oriented business models is presented in chapter 2.1, enabled to define the final list of the business models used in the further analysis. The most suitable business models that are reflecting sustainable business goals were identified by:

British norm BS 8001:2025 (“BS8001:, 2017 BSI Knowledge” 2017 ),

Lewandowski ( 2016 ),

IMSA (“Circular Future—Public Affairs and consultancy about Circular Economy” 2022 ),

Clinton & Whisnart ( 2019 ),

Ellen MacArthur Foundation ( 2021 ).

They are as follows:

Produce on demand/made to order,

Produce on demand,

Remanufacture, Product Transformation,

Recycling, Recycling 2.0, Resource Recovery,

Closed loop production,

Upcycle/upcycling,

Digitalization,

Dematerialized services,

Physical to virtual,

Product life‑extension,

Product as a service,

Circular supplies,

Facilitated reuse,

Product modular design,

Next life sales,

Refurbish and resell,

Refurbish, repair, remanufacture and recondition,

Recovery of secondary materials/by‑products (including recycling),

Recycling (waste handling and repurpose),

Incentivized return/extended producer responsibility,

Take back management,

Asset management,

Incentivized return and reuse or next life sales,

Lease agreement,

Pss: product lease,

Sharing Economy,

Collaborative Consumption, sharing platforms, pss: product renting, sharing or pooling,

Collaborative production,

Shared resource,

Sharing platforms/resources (collaborative consumption),

Sharing platforms,

Pay per use,

Buy one, give one,

Inclusive sourcing,

Maintenance and repair,

Behavior change,

Energy recover,

Waste reduction, good housekeeping, lean thinking, fit thinking,

Chemical leasing.

The business goals focused on implementing the principles of green economy are defined as follows:

to minimize raw material and/or energy demand,

to avoid overstocking,

to replace physical infrastructure and assets with digital/virtual services,

to design new products to be durable for a long lifetime (durability),

to reuse parts/components with or without repair/upgrade,

to encourage cost effective product repairs and reduce need for replacement of integrated components, thereby reducing resource consumption,

to put the product back into the market to earn a second or subsequent income,

to create products from secondary raw materials/by products and recycling,

to recover used/unwanted products and sell it again,

to increase overall profitability during the lease period,

to strengthen community relationships,

to reduce costs over directly sourcing the products/services,

to increase utilization rate of products and services,

to create an entirely new product from the source material (waste),

to attract consumers to the cause (to donate a portion of the profits to those in need),

to create more ‘ethical’ products by setting supplier standards or conducting audits (toward sustainable sourcing),

to extend product lifecycle,

to increase “stickiness” with the customer, making them less likely to buy from another good/service provider,

to convert non-recyclable waste materials into useable heat, electricity, or fuel,

to reduce waste in the production process and before,

to cooperate in the production value chain leading to closing material loops,

to reduce environmental impacts and use of hazardous chemical.

Below, for the three selected business goals, the examples of the explanatory results are presented.

Business goal: to minimize raw material and/or energy demand (Table  1 ).

Corresponding indicators:

lightweight material

sustainable material

number of renewable parts

number of reused parts assembled

energy usage

water usage

amount of waste

product size (partly)

product weight (partly)

amount of scrap (partly)

Business goal: to reuse parts/components with or without repair/upgrade (Table  2 ).

energy usage water usage

waste recycled/reused

Business goal: to extend product lifecycle (Table  3 ).

number of reused parts assembled (partly)

Analogous analysis was performed for all the identified business goals. In the next step all indicators were analyzed under the aspect of their suitability to reach sustainable business goals. Indicators were assigned as corresponding (blue color in Table  4 ) or partly corresponding (light blue color in Table  4 ) to defined business goals (Table  4 ).

4.2 Step 2: Assessment of indicators and their importance in the automotive industry—presentation of results

According to the step 2 of the research methodology, the assessment of the 20 indicators has been performed by the Authors of this paper. Each of the five overarching assessment criteria (Indicator's features, Relevance for the company, Importance to sustainable business goals, Importance in terms of subsectors, Environmental, Economic, and Social impact) were assessed and presented in a separate table (namely Tables  5 , 6 , 7 , 8 , 9 ).

Based on the above-presented analysis, the last steps of step 2 of the research methodology were applied. The obtained results summarize the assessment in the five overarching criteria:

Criterion 1: Indicator's features—mean value of all assigned points per indicator,

Criterion 2: Relevance for the company—binary value per indicator,

Criterion 3: Importance to sustainable business goals—sum of all assigned points per indicator,

Criterion 4: Importance in terms of subsectors—sum of all assigned points per indicator,

Criterion 5: Environmental, Economic, Social impact—sum of all assigned points per indicator.

They were normalized and the mean value was calculated for each indicator (I.1–I.20). The results can be found in Table  10 .

Based on the above-presented computations, the key indicators for Green PLM were ranked in terms of their importance for the automotive industry from the sustainability-oriented perspective (see Fig.  4 ).

figure 4

Final ranking of key sustainability-related indicators for Green PLM

Implementation of the two steps of the three-step methodology enabled selection of the key indicators in terms of their importance in the automotive industry and at the same time the indicators that can be used as key sustainability-related indicators for Green PLM development. The five key indicators are:

number of reused parts assembled,

sustainable material,

number of renewable parts,

hazardous material,

non-polluting material.

They have been indicated as the most important and versatile due to the reason that they simultaneously:

match the highest number of sustainability-related business goals,

are relevant for the highest number of environmental, economic, and social impacts,

correspond to the highest number of the automotive subsectors,

achieved the highest scores in terms of desired indicator’s features,

are relevant for the company.

4.3 Step 3: algorithm assessing “greenness” of the product

According to the step 3 of the research methodology, the algorithm assessing “greenness” of the product was applied. It should be noted that the application of the proposed algorithm can differ depending on the need (e.g. promotion/communication aspects), yet it seems that it should be used in the first place as a tool enabling its user to compare a product in its path towards “greenness”. A hypothetical situation can be assumed that a company is developing a product “A” and assigns a number of indicators and corresponding values to assess its “greenness”. Next, after some time, another product is developed—product “B” (e.g. it can be the next generation of product “A”). The company again assigns a number of indicators with corresponding values to assess the level of “greenness” of product “B”. Thus, products “A” and “B” can be compared in terms of their “greenness”. If the level of “greenness” has increased, it can be stated that the company is properly addressing the aim of sustainability and is successfully reaching its business goals. The algorithm presented below has been developed for the five selected indicators in the previous part of the analysis. Nevertheless, it has to be underlined that the algorithm can be easily adjusted for another set of indicators. To demonstrate the application of the proposed algorithm, the following tables have been developed as an example (Tables 11 and 12 ).

According to the above-presented example, once the business goals are listed, the appropriate indicators can be selected (according to the step 2 of the methodology). Next, it can be verified whether an indicator is related to the single part (and thus can be directly assessed whether a part is “green” or not) or is it related to the assembly. So—for example—in indicator I.1 non-polluting material it can be stated that if a part is built of a non-polluting material it can be assessed as 100% green. In case of indicator I.2 hazardous material if material is hazardous it is negative situation. Thus, to assess a part as 100% green it is expected that the value of the indicator I.2 is “no”—meaning that the part is built of non- hazardous material. On the other hand, if we consider the indicator I.8 number of reused parts assembled which does not refer to a part (but to an assembly) the status is n/a. This type of indicator can be considered and analyzed only on the product level (meaning assembly). In order to assess whether a final product is green or not, or how much green it is, certain aggregation and calculations have to be conducted. So initially, following the example of indicator I.1 non-polluting material , all parts in the final product built of non-polluting materials have to be identified. Next, their weights have to be summed up. Subsequently, the total weight of the final product has to be defined. Having the weight of all non-polluting materials in the product and the weight of the final product the proportion of these two can be calculated. In that case, a real percentage value is obtained (e.g. 95.87% for I.1). This value should be compared with the “greenness” threshold which a company should define. If the real percentage value calculated for the given indicator is greater than the “greenness” threshold (so the criterion is met) 1 point can be assigned. For each indicator, a company should set the weights for every criterion (constant values) so that it is clear how important a given indicator for the “greenness” of the whole product is. So for example, the company may assume that indicator I. 2 non-hazardous material (criterion = 1,5) is more important than indicator I.4 sustainable material (criterion = 1,2). Following the algorithm defining the “greenness” of a product, once all the weights of the criteria are set, they can be summed up. Next, for each indicator, a point value resulting from either meeting the “greenness” threshold (1 point) or not (0 points) should be multiplied by the criterion’s weight. The values of these products should be summed. In the final step, the “greenness” status of the product can be calculated by simply dividing these two values. As a result, a percentage value will be defined. Here again, the company should define the critical value—when a product can be considered green (e.g. when the “greenness” status of the product exceeds 75%).

5 Conclusions

Within the literature review three main aspects were analyzed. At first, an analysis focused on the identification of business models corresponding to sustainability was performed. Next, current trends and needs were described in terms of the green PLM. Finally, an introduction describing the automotive industry definition and its subsectors was presented together with defining current challenges. Based on the literature analysis and drawn conclusions, the aim of the research was defined. Thus, the main aim of this paper was to develop a new approach to assessing greenness of a product which would be based on a business goals-oriented algorithm and applied to the new product development phase for the automotive industry. This aim was achieved. Three-step research methodology enabled to assess indicators’ importance for sustainable business goals and business models (step 1), assess indicators and their importance in the automotive industry (step 2) and finally assess “greenness” of the product (3). This complex approach is innovative as it is based on the business-oriented perspective. Selecting suitable business goals and corresponding business models leads to the selection of the appropriate subset of indicators. Several more aspects are taken into account in this holistic analysis, namely indicator's features, relevance for the company, importance to sustainable business goals, importance in terms of subsectors of the automotive industry as well as environmental, economic, and social impact. In the paper the example of analysis was presented. Obtained results led to the selection of five key sustainability-oriented green Product Lifecycle Management indicators the most important in the automotive industry: number of reused parts assembled, sustainable material, number of renewable parts, hazardous material, non-polluting material. According to the third step of the research methodology, the algorithm assessing “greenness” of the product was applied. It enables the company to compute the value of the “greenness” of the product in reference to the key green PLM indicators (selected according to the step 1 and step 2 of the methodology). “Greenness” threshold should be defined by a company according to its internal policy and be in line with the company’s goals and current needs. The exact values of these thresholds may result for example from the expectations of their customers. They can also be imposed by critical values set by the headquarters. Moreover, when setting the “greenness” thresholds, the company should monitor the current corresponding laws and regulations—both national and international. Therefore it is advisable to track regulations based on those mentioned in the Introduction: the European Green Deal, the Fit for 55 package, Circular Economy Action Plan, the Ecodesign Directive, the EU Ecolabel or the EU green public procurement (GPP) and/or join corresponding initiatives, eg.: https://sciencebasedtargets.org/ , https://pacecircular.org/ , https://www.unglobalcompact.org/ ).

5.1 Limitations

The authors would like to acknowledge that the presented analysis has several limitations. The first limitation—the assessment of the indicators was limited to the 20 green PLM indicators described within the paper “Towards GreenPLM—Key Sustainable Indicators Selection and Assessment Method Development” (Helman et al., 2023 ). The points granted in particular parts of the analysis were assigned by the authors of this paper. In the future application of the proposed algorithms, the team assigning the points can be more versatile. The analysis, by definition, was limited to the automotive industry. However, the proposed three-step methodology can be easily adjusted and transferred to another type of industry if needed.

5.2 Further research

Further work will concern issues related to the practical implementation of the methodology developed above. The possibility of building a community of its users in order to maintain and expand the database of green indicators, green products and their components will also be investigated. An interesting issue to research will be the concept of supporting the process of knowledge sharing and cooperation and competition in such a community.

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Acknowledgements

The research leading to these results was carried out within the GreenPLM project funded by transition Technologies PSC S.A.

The research leading to these results received funding from Transition Technologies PSC S.A.

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Department of Laser Technologies, Automation and Production Management, Wroclaw University of Science and Technology, Lukasiewicza 5, 50-370, Wroclaw, Poland

Maria Rosienkiewicz, Joanna Helman, Mariusz Cholewa & Mateusz Molasy

Instytut Transferu Technologii Sp. z o.o, Na Grobli 15, 50-421, Wrocław, Poland

Transition Technologies PSC S.A, Piotrkowska 276, 90-361, Lodz, Poland

Sylwester Oleszek

Department of Mechanical Engineering, Energetics, Management and Transportation, University of Genoa, Via all’Opera Pia 15/A, 16145, Genoa, Italy

Giovanni Berselli

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Contributions

All authors contributed to the study in the following way: Conceptualization: M. Rosienkiewicz, M. Cholewa, J. Helman, G. Berselli, Literature review: M. Rosienkiewicz, M. Molasy, J. Helman, Methodology—step 1: M. Rosienkiewicz, J. Helman, M. Cholewa, M. Molasy, Methodology—step 2: M. Rosienkiewicz, J. Helman, M. Cholewa, Methodology—step 3: M. Rosienkiewicz, Formal analysis and investigation: M. Rosienkiewicz, J. Helman, M. Cholewa, Visualization: M. Rosienkiewicz, J. Helman, Writing—original draft preparation: M. Rosienkiewicz, Writing—review and editing: J. Helman, M. Cholewa, M. Molasy, S. Oleszek, G. Berselli, Project proposal development: M. Cholewa,

Scientific advisory: G. Berselli, Funding acquisition: M. Cholewa, S. Oleszek, Project administration: S. Oleszek, Supervision: M. Cholewa, S. Oleszek. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Maria Rosienkiewicz .

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Rosienkiewicz, M., Helman, J., Cholewa, M. et al. Green PLM: business goals-oriented algorithm assessing the greenness of a product in the new product development phase for the automotive industry. Ann Oper Res (2024). https://doi.org/10.1007/s10479-024-06014-4

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