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• How to Write a Literature Review | Guide, Examples, & Templates

How to Write a Literature Review | Guide, Examples, & Templates

Published on January 2, 2023 by Shona McCombes . Revised on September 11, 2023.

What is a literature review? A literature review is a survey of scholarly sources on a specific topic. It provides an overview of current knowledge, allowing you to identify relevant theories, methods, and gaps in the existing research that you can later apply to your paper, thesis, or dissertation topic .

There are five key steps to writing a literature review:

• Search for relevant literature
• Evaluate sources
• Identify themes, debates, and gaps
• Outline the structure
• Write your literature review

A good literature review doesn’t just summarize sources—it analyzes, synthesizes , and critically evaluates to give a clear picture of the state of knowledge on the subject.

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Table of contents

What is the purpose of a literature review, examples of literature reviews, step 1 – search for relevant literature, step 2 – evaluate and select sources, step 3 – identify themes, debates, and gaps, step 4 – outline your literature review’s structure, step 5 – write your literature review, free lecture slides, other interesting articles, frequently asked questions, introduction.

• Quick Run-through
• Step 1 & 2

When you write a thesis , dissertation , or research paper , you will likely have to conduct a literature review to situate your research within existing knowledge. The literature review gives you a chance to:

• Demonstrate your familiarity with the topic and its scholarly context
• Develop a theoretical framework and methodology for your research
• Position your work in relation to other researchers and theorists
• Show how your research addresses a gap or contributes to a debate
• Evaluate the current state of research and demonstrate your knowledge of the scholarly debates around your topic.

Writing literature reviews is a particularly important skill if you want to apply for graduate school or pursue a career in research. We’ve written a step-by-step guide that you can follow below.

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Writing literature reviews can be quite challenging! A good starting point could be to look at some examples, depending on what kind of literature review you’d like to write.

• Example literature review #1: “Why Do People Migrate? A Review of the Theoretical Literature” ( Theoretical literature review about the development of economic migration theory from the 1950s to today.)
• Example literature review #2: “Literature review as a research methodology: An overview and guidelines” ( Methodological literature review about interdisciplinary knowledge acquisition and production.)
• Example literature review #3: “The Use of Technology in English Language Learning: A Literature Review” ( Thematic literature review about the effects of technology on language acquisition.)
• Example literature review #4: “Learners’ Listening Comprehension Difficulties in English Language Learning: A Literature Review” ( Chronological literature review about how the concept of listening skills has changed over time.)

You can also check out our templates with literature review examples and sample outlines at the links below.

Download Word doc Download Google doc

Before you begin searching for literature, you need a clearly defined topic .

If you are writing the literature review section of a dissertation or research paper, you will search for literature related to your research problem and questions .

Make a list of keywords

Start by creating a list of keywords related to your research question. Include each of the key concepts or variables you’re interested in, and list any synonyms and related terms. You can add to this list as you discover new keywords in the process of your literature search.

• Social media, Facebook, Instagram, Twitter, Snapchat, TikTok
• Body image, self-perception, self-esteem, mental health
• Generation Z, teenagers, adolescents, youth

Search for relevant sources

Use your keywords to begin searching for sources. Some useful databases to search for journals and articles include:

• Your university’s library catalogue
• Google Scholar
• Project Muse (humanities and social sciences)
• Medline (life sciences and biomedicine)
• EconLit (economics)
• Inspec (physics, engineering and computer science)

You can also use boolean operators to help narrow down your search.

Make sure to read the abstract to find out whether an article is relevant to your question. When you find a useful book or article, you can check the bibliography to find other relevant sources.

You likely won’t be able to read absolutely everything that has been written on your topic, so it will be necessary to evaluate which sources are most relevant to your research question.

For each publication, ask yourself:

• What question or problem is the author addressing?
• What are the key concepts and how are they defined?
• What are the key theories, models, and methods?
• Does the research use established frameworks or take an innovative approach?
• What are the results and conclusions of the study?
• How does the publication relate to other literature in the field? Does it confirm, add to, or challenge established knowledge?
• What are the strengths and weaknesses of the research?

Make sure the sources you use are credible , and make sure you read any landmark studies and major theories in your field of research.

You can use our template to summarize and evaluate sources you’re thinking about using. Click on either button below to download.

Take notes and cite your sources

As you read, you should also begin the writing process. Take notes that you can later incorporate into the text of your literature review.

It is important to keep track of your sources with citations to avoid plagiarism . It can be helpful to make an annotated bibliography , where you compile full citation information and write a paragraph of summary and analysis for each source. This helps you remember what you read and saves time later in the process.

To begin organizing your literature review’s argument and structure, be sure you understand the connections and relationships between the sources you’ve read. Based on your reading and notes, you can look for:

• Trends and patterns (in theory, method or results): do certain approaches become more or less popular over time?
• Themes: what questions or concepts recur across the literature?
• Debates, conflicts and contradictions: where do sources disagree?
• Pivotal publications: are there any influential theories or studies that changed the direction of the field?
• Gaps: what is missing from the literature? Are there weaknesses that need to be addressed?

This step will help you work out the structure of your literature review and (if applicable) show how your own research will contribute to existing knowledge.

• Most research has focused on young women.
• There is an increasing interest in the visual aspects of social media.
• But there is still a lack of robust research on highly visual platforms like Instagram and Snapchat—this is a gap that you could address in your own research.

There are various approaches to organizing the body of a literature review. Depending on the length of your literature review, you can combine several of these strategies (for example, your overall structure might be thematic, but each theme is discussed chronologically).

Chronological

The simplest approach is to trace the development of the topic over time. However, if you choose this strategy, be careful to avoid simply listing and summarizing sources in order.

Try to analyze patterns, turning points and key debates that have shaped the direction of the field. Give your interpretation of how and why certain developments occurred.

If you have found some recurring central themes, you can organize your literature review into subsections that address different aspects of the topic.

For example, if you are reviewing literature about inequalities in migrant health outcomes, key themes might include healthcare policy, language barriers, cultural attitudes, legal status, and economic access.

Methodological

If you draw your sources from different disciplines or fields that use a variety of research methods , you might want to compare the results and conclusions that emerge from different approaches. For example:

• Look at what results have emerged in qualitative versus quantitative research
• Discuss how the topic has been approached by empirical versus theoretical scholarship
• Divide the literature into sociological, historical, and cultural sources

Theoretical

A literature review is often the foundation for a theoretical framework . You can use it to discuss various theories, models, and definitions of key concepts.

You might argue for the relevance of a specific theoretical approach, or combine various theoretical concepts to create a framework for your research.

Like any other academic text , your literature review should have an introduction , a main body, and a conclusion . What you include in each depends on the objective of your literature review.

The introduction should clearly establish the focus and purpose of the literature review.

Depending on the length of your literature review, you might want to divide the body into subsections. You can use a subheading for each theme, time period, or methodological approach.

As you write, you can follow these tips:

• Summarize and synthesize: give an overview of the main points of each source and combine them into a coherent whole
• Analyze and interpret: don’t just paraphrase other researchers — add your own interpretations where possible, discussing the significance of findings in relation to the literature as a whole
• Critically evaluate: mention the strengths and weaknesses of your sources
• Write in well-structured paragraphs: use transition words and topic sentences to draw connections, comparisons and contrasts

In the conclusion, you should summarize the key findings you have taken from the literature and emphasize their significance.

When you’ve finished writing and revising your literature review, don’t forget to proofread thoroughly before submitting. Not a language expert? Check out Scribbr’s professional proofreading services !

This article has been adapted into lecture slides that you can use to teach your students about writing a literature review.

Scribbr slides are free to use, customize, and distribute for educational purposes.

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If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

A literature review is a survey of scholarly sources (such as books, journal articles, and theses) related to a specific topic or research question .

It is often written as part of a thesis, dissertation , or research paper , in order to situate your work in relation to existing knowledge.

There are several reasons to conduct a literature review at the beginning of a research project:

• To familiarize yourself with the current state of knowledge on your topic
• To ensure that you’re not just repeating what others have already done
• To identify gaps in knowledge and unresolved problems that your research can address
• To develop your theoretical framework and methodology
• To provide an overview of the key findings and debates on the topic

Writing the literature review shows your reader how your work relates to existing research and what new insights it will contribute.

The literature review usually comes near the beginning of your thesis or dissertation . After the introduction , it grounds your research in a scholarly field and leads directly to your theoretical framework or methodology .

A literature review is a survey of credible sources on a topic, often used in dissertations , theses, and research papers . Literature reviews give an overview of knowledge on a subject, helping you identify relevant theories and methods, as well as gaps in existing research. Literature reviews are set up similarly to other  academic texts , with an introduction , a main body, and a conclusion .

An  annotated bibliography is a list of  source references that has a short description (called an annotation ) for each of the sources. It is often assigned as part of the research process for a  paper .  

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McCombes, S. (2023, September 11). How to Write a Literature Review | Guide, Examples, & Templates. Scribbr. Retrieved August 21, 2024, from https://www.scribbr.com/dissertation/literature-review/

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• What is a Literature Review? | Guide, Template, & Examples

What is a Literature Review? | Guide, Template, & Examples

Published on 22 February 2022 by Shona McCombes . Revised on 7 June 2022.

What is a literature review? A literature review is a survey of scholarly sources on a specific topic. It provides an overview of current knowledge, allowing you to identify relevant theories, methods, and gaps in the existing research.

There are five key steps to writing a literature review:

• Search for relevant literature
• Evaluate sources
• Identify themes, debates and gaps
• Outline the structure
• Write your literature review

A good literature review doesn’t just summarise sources – it analyses, synthesises, and critically evaluates to give a clear picture of the state of knowledge on the subject.

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Table of contents

Why write a literature review, examples of literature reviews, step 1: search for relevant literature, step 2: evaluate and select sources, step 3: identify themes, debates and gaps, step 4: outline your literature review’s structure, step 5: write your literature review, frequently asked questions about literature reviews, introduction.

• Quick Run-through
• Step 1 & 2

When you write a dissertation or thesis, you will have to conduct a literature review to situate your research within existing knowledge. The literature review gives you a chance to:

• Demonstrate your familiarity with the topic and scholarly context
• Develop a theoretical framework and methodology for your research
• Position yourself in relation to other researchers and theorists
• Show how your dissertation addresses a gap or contributes to a debate

You might also have to write a literature review as a stand-alone assignment. In this case, the purpose is to evaluate the current state of research and demonstrate your knowledge of scholarly debates around a topic.

The content will look slightly different in each case, but the process of conducting a literature review follows the same steps. We’ve written a step-by-step guide that you can follow below.

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Writing literature reviews can be quite challenging! A good starting point could be to look at some examples, depending on what kind of literature review you’d like to write.

• Example literature review #1: “Why Do People Migrate? A Review of the Theoretical Literature” ( Theoretical literature review about the development of economic migration theory from the 1950s to today.)
• Example literature review #2: “Literature review as a research methodology: An overview and guidelines” ( Methodological literature review about interdisciplinary knowledge acquisition and production.)
• Example literature review #3: “The Use of Technology in English Language Learning: A Literature Review” ( Thematic literature review about the effects of technology on language acquisition.)
• Example literature review #4: “Learners’ Listening Comprehension Difficulties in English Language Learning: A Literature Review” ( Chronological literature review about how the concept of listening skills has changed over time.)

You can also check out our templates with literature review examples and sample outlines at the links below.

Download Word doc Download Google doc

Before you begin searching for literature, you need a clearly defined topic .

If you are writing the literature review section of a dissertation or research paper, you will search for literature related to your research objectives and questions .

If you are writing a literature review as a stand-alone assignment, you will have to choose a focus and develop a central question to direct your search. Unlike a dissertation research question, this question has to be answerable without collecting original data. You should be able to answer it based only on a review of existing publications.

Make a list of keywords

Start by creating a list of keywords related to your research topic. Include each of the key concepts or variables you’re interested in, and list any synonyms and related terms. You can add to this list if you discover new keywords in the process of your literature search.

• Social media, Facebook, Instagram, Twitter, Snapchat, TikTok
• Body image, self-perception, self-esteem, mental health
• Generation Z, teenagers, adolescents, youth

Search for relevant sources

Use your keywords to begin searching for sources. Some databases to search for journals and articles include:

• Your university’s library catalogue
• Google Scholar
• Project Muse (humanities and social sciences)
• Medline (life sciences and biomedicine)
• EconLit (economics)
• Inspec (physics, engineering and computer science)

You can use boolean operators to help narrow down your search:

Read the abstract to find out whether an article is relevant to your question. When you find a useful book or article, you can check the bibliography to find other relevant sources.

To identify the most important publications on your topic, take note of recurring citations. If the same authors, books or articles keep appearing in your reading, make sure to seek them out.

You probably won’t be able to read absolutely everything that has been written on the topic – you’ll have to evaluate which sources are most relevant to your questions.

For each publication, ask yourself:

• What question or problem is the author addressing?
• What are the key concepts and how are they defined?
• What are the key theories, models and methods? Does the research use established frameworks or take an innovative approach?
• What are the results and conclusions of the study?
• How does the publication relate to other literature in the field? Does it confirm, add to, or challenge established knowledge?
• How does the publication contribute to your understanding of the topic? What are its key insights and arguments?
• What are the strengths and weaknesses of the research?

Make sure the sources you use are credible, and make sure you read any landmark studies and major theories in your field of research.

You can find out how many times an article has been cited on Google Scholar – a high citation count means the article has been influential in the field, and should certainly be included in your literature review.

The scope of your review will depend on your topic and discipline: in the sciences you usually only review recent literature, but in the humanities you might take a long historical perspective (for example, to trace how a concept has changed in meaning over time).

Remember that you can use our template to summarise and evaluate sources you’re thinking about using!

Take notes and cite your sources

As you read, you should also begin the writing process. Take notes that you can later incorporate into the text of your literature review.

It’s important to keep track of your sources with references to avoid plagiarism . It can be helpful to make an annotated bibliography, where you compile full reference information and write a paragraph of summary and analysis for each source. This helps you remember what you read and saves time later in the process.

You can use our free APA Reference Generator for quick, correct, consistent citations.

Prevent plagiarism, run a free check.

To begin organising your literature review’s argument and structure, you need to understand the connections and relationships between the sources you’ve read. Based on your reading and notes, you can look for:

• Trends and patterns (in theory, method or results): do certain approaches become more or less popular over time?
• Themes: what questions or concepts recur across the literature?
• Debates, conflicts and contradictions: where do sources disagree?
• Pivotal publications: are there any influential theories or studies that changed the direction of the field?
• Gaps: what is missing from the literature? Are there weaknesses that need to be addressed?

This step will help you work out the structure of your literature review and (if applicable) show how your own research will contribute to existing knowledge.

• Most research has focused on young women.
• There is an increasing interest in the visual aspects of social media.
• But there is still a lack of robust research on highly-visual platforms like Instagram and Snapchat – this is a gap that you could address in your own research.

There are various approaches to organising the body of a literature review. You should have a rough idea of your strategy before you start writing.

Depending on the length of your literature review, you can combine several of these strategies (for example, your overall structure might be thematic, but each theme is discussed chronologically).

Chronological

The simplest approach is to trace the development of the topic over time. However, if you choose this strategy, be careful to avoid simply listing and summarising sources in order.

Try to analyse patterns, turning points and key debates that have shaped the direction of the field. Give your interpretation of how and why certain developments occurred.

If you have found some recurring central themes, you can organise your literature review into subsections that address different aspects of the topic.

For example, if you are reviewing literature about inequalities in migrant health outcomes, key themes might include healthcare policy, language barriers, cultural attitudes, legal status, and economic access.

Methodological

If you draw your sources from different disciplines or fields that use a variety of research methods , you might want to compare the results and conclusions that emerge from different approaches. For example:

• Look at what results have emerged in qualitative versus quantitative research
• Discuss how the topic has been approached by empirical versus theoretical scholarship
• Divide the literature into sociological, historical, and cultural sources

Theoretical

A literature review is often the foundation for a theoretical framework . You can use it to discuss various theories, models, and definitions of key concepts.

You might argue for the relevance of a specific theoretical approach, or combine various theoretical concepts to create a framework for your research.

Like any other academic text, your literature review should have an introduction , a main body, and a conclusion . What you include in each depends on the objective of your literature review.

The introduction should clearly establish the focus and purpose of the literature review.

If you are writing the literature review as part of your dissertation or thesis, reiterate your central problem or research question and give a brief summary of the scholarly context. You can emphasise the timeliness of the topic (“many recent studies have focused on the problem of x”) or highlight a gap in the literature (“while there has been much research on x, few researchers have taken y into consideration”).

Depending on the length of your literature review, you might want to divide the body into subsections. You can use a subheading for each theme, time period, or methodological approach.

As you write, make sure to follow these tips:

• Summarise and synthesise: give an overview of the main points of each source and combine them into a coherent whole.
• Analyse and interpret: don’t just paraphrase other researchers – add your own interpretations, discussing the significance of findings in relation to the literature as a whole.
• Critically evaluate: mention the strengths and weaknesses of your sources.
• Write in well-structured paragraphs: use transitions and topic sentences to draw connections, comparisons and contrasts.

In the conclusion, you should summarise the key findings you have taken from the literature and emphasise their significance.

If the literature review is part of your dissertation or thesis, reiterate how your research addresses gaps and contributes new knowledge, or discuss how you have drawn on existing theories and methods to build a framework for your research. This can lead directly into your methodology section.

A literature review is a survey of scholarly sources (such as books, journal articles, and theses) related to a specific topic or research question .

It is often written as part of a dissertation , thesis, research paper , or proposal .

There are several reasons to conduct a literature review at the beginning of a research project:

• To familiarise yourself with the current state of knowledge on your topic
• To ensure that you’re not just repeating what others have already done
• To identify gaps in knowledge and unresolved problems that your research can address
• To develop your theoretical framework and methodology
• To provide an overview of the key findings and debates on the topic

Writing the literature review shows your reader how your work relates to existing research and what new insights it will contribute.

The literature review usually comes near the beginning of your  dissertation . After the introduction , it grounds your research in a scholarly field and leads directly to your theoretical framework or methodology .

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the ‘Cite this Scribbr article’ button to automatically add the citation to our free Reference Generator.

McCombes, S. (2022, June 07). What is a Literature Review? | Guide, Template, & Examples. Scribbr. Retrieved 21 August 2024, from https://www.scribbr.co.uk/thesis-dissertation/literature-review/

Is this article helpful?

Shona McCombes

Other students also liked, how to write a dissertation proposal | a step-by-step guide, what is a theoretical framework | a step-by-step guide, what is a research methodology | steps & tips.

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• CAREER FEATURE
• 04 December 2020
• Correction 09 December 2020

How to write a superb literature review

Andy Tay is a freelance writer based in Singapore.

You can also search for this author in PubMed   Google Scholar

Credit: Getty

Literature reviews are important resources for scientists. They provide historical context for a field while offering opinions on its future trajectory. Creating them can provide inspiration for one’s own research, as well as some practice in writing. But few scientists are trained in how to write a review — or in what constitutes an excellent one. Even picking the appropriate software to use can be an involved decision (see ‘Tools and techniques’). So Nature asked editors and working scientists with well-cited reviews for their tips.

WENTING ZHAO: Be focused and avoid jargon

Assistant professor of chemical and biomedical engineering, Nanyang Technological University, Singapore.

When I was a research student, review writing improved my understanding of the history of my field. I also learnt about unmet challenges in the field that triggered ideas.

For example, while writing my first review 1 as a PhD student, I was frustrated by how poorly we understood how cells actively sense, interact with and adapt to nanoparticles used in drug delivery. This experience motivated me to study how the surface properties of nanoparticles can be modified to enhance biological sensing. When I transitioned to my postdoctoral research, this question led me to discover the role of cell-membrane curvature, which led to publications and my current research focus. I wouldn’t have started in this area without writing that review.

Collection: Careers toolkit

A common problem for students writing their first reviews is being overly ambitious. When I wrote mine, I imagined producing a comprehensive summary of every single type of nanomaterial used in biological applications. It ended up becoming a colossal piece of work, with too many papers discussed and without a clear way to categorize them. We published the work in the end, but decided to limit the discussion strictly to nanoparticles for biological sensing, rather than covering how different nanomaterials are used in biology.

My advice to students is to accept that a review is unlike a textbook: it should offer a more focused discussion, and it’s OK to skip some topics so that you do not distract your readers. Students should also consider editorial deadlines, especially for invited reviews: make sure that the review’s scope is not so extensive that it delays the writing.

A good review should also avoid jargon and explain the basic concepts for someone who is new to the field. Although I trained as an engineer, I’m interested in biology, and my research is about developing nanomaterials to manipulate proteins at the cell membrane and how this can affect ageing and cancer. As an ‘outsider’, the reviews that I find most useful for these biological topics are those that speak to me in accessible scientific language.

Bozhi Tian likes to get a variety of perspectives into a review. Credit: Aleksander Prominski

BOZHI TIAN: Have a process and develop your style

Associate professor of chemistry, University of Chicago, Illinois.

In my lab, we start by asking: what is the purpose of this review? My reasons for writing one can include the chance to contribute insights to the scientific community and identify opportunities for my research. I also see review writing as a way to train early-career researchers in soft skills such as project management and leadership. This is especially true for lead authors, because they will learn to work with their co-authors to integrate the various sections into a piece with smooth transitions and no overlaps.

After we have identified the need and purpose of a review article, I will form a team from the researchers in my lab. I try to include students with different areas of expertise, because it is useful to get a variety of perspectives. For example, in the review ‘An atlas of nano-enabled neural interfaces’ 2 , we had authors with backgrounds in biophysics, neuroengineering, neurobiology and materials sciences focusing on different sections of the review.

After this, I will discuss an outline with my team. We go through multiple iterations to make sure that we have scanned the literature sufficiently and do not repeat discussions that have appeared in other reviews. It is also important that the outline is not decided by me alone: students often have fresh ideas that they can bring to the table. Once this is done, we proceed with the writing.

I often remind my students to imagine themselves as ‘artists of science’ and encourage them to develop how they write and present information. Adding more words isn’t always the best way: for example, I enjoy using tables to summarize research progress and suggest future research trajectories. I’ve also considered including short videos in our review papers to highlight key aspects of the work. I think this can increase readership and accessibility because these videos can be easily shared on social-media platforms.

ANKITA ANIRBAN: Timeliness and figures make a huge difference

Editor, Nature Reviews Physics .

One of my roles as a journal editor is to evaluate proposals for reviews. The best proposals are timely and clearly explain why readers should pay attention to the proposed topic.

It is not enough for a review to be a summary of the latest growth in the literature: the most interesting reviews instead provide a discussion about disagreements in the field.

Careers Collection: Publishing

Scientists often centre the story of their primary research papers around their figures — but when it comes to reviews, figures often take a secondary role. In my opinion, review figures are more important than most people think. One of my favourite review-style articles 3 presents a plot bringing together data from multiple research papers (many of which directly contradict each other). This is then used to identify broad trends and suggest underlying mechanisms that could explain all of the different conclusions.

An important role of a review article is to introduce researchers to a field. For this, schematic figures can be useful to illustrate the science being discussed, in much the same way as the first slide of a talk should. That is why, at Nature Reviews, we have in-house illustrators to assist authors. However, simplicity is key, and even without support from professional illustrators, researchers can still make use of many free drawing tools to enhance the value of their review figures.

Yoojin Choi recommends that researchers be open to critiques when writing reviews. Credit: Yoojin Choi

YOOJIN CHOI: Stay updated and be open to suggestions

Research assistant professor, Korea Advanced Institute of Science and Technology, Daejeon.

I started writing the review ‘Biosynthesis of inorganic nanomaterials using microbial cells and bacteriophages’ 4 as a PhD student in 2018. It took me one year to write the first draft because I was working on the review alongside my PhD research and mostly on my own, with support from my adviser. It took a further year to complete the processes of peer review, revision and publication. During this time, many new papers and even competing reviews were published. To provide the most up-to-date and original review, I had to stay abreast of the literature. In my case, I made use of Google Scholar, which I set to send me daily updates of relevant literature based on key words.

Through my review-writing process, I also learnt to be more open to critiques to enhance the value and increase the readership of my work. Initially, my review was focused only on using microbial cells such as bacteria to produce nanomaterials, which was the subject of my PhD research. Bacteria such as these are known as biofactories: that is, organisms that produce biological material which can be modified to produce useful materials, such as magnetic nanoparticles for drug-delivery purposes.

Synchronized editing: the future of collaborative writing

However, when the first peer-review report came back, all three reviewers suggested expanding the review to cover another type of biofactory: bacteriophages. These are essentially viruses that infect bacteria, and they can also produce nanomaterials.

The feedback eventually led me to include a discussion of the differences between the various biofactories (bacteriophages, bacteria, fungi and microalgae) and their advantages and disadvantages. This turned out to be a great addition because it made the review more comprehensive.

Writing the review also led me to an idea about using nanomaterial-modified microorganisms to produce chemicals, which I’m still researching now.

PAULA MARTIN-GONZALEZ: Make good use of technology

PhD student, University of Cambridge, UK.

Just before the coronavirus lockdown, my PhD adviser and I decided to write a literature review discussing the integration of medical imaging with genomics to improve ovarian cancer management.

As I was researching the review, I noticed a trend in which some papers were consistently being cited by many other papers in the field. It was clear to me that those papers must be important, but as a new member of the field of integrated cancer biology, it was difficult to immediately find and read all of these ‘seminal papers’.

That was when I decided to code a small application to make my literature research more efficient. Using my code, users can enter a query, such as ‘ovarian cancer, computer tomography, radiomics’, and the application searches for all relevant literature archived in databases such as PubMed that feature these key words.

The code then identifies the relevant papers and creates a citation graph of all the references cited in the results of the search. The software highlights papers that have many citation relationships with other papers in the search, and could therefore be called seminal papers.

My code has substantially improved how I organize papers and has informed me of key publications and discoveries in my research field: something that would have taken more time and experience in the field otherwise. After I shared my code on GitHub, I received feedback that it can be daunting for researchers who are not used to coding. Consequently, I am hoping to build a more user-friendly interface in a form of a web page, akin to PubMed or Google Scholar, where users can simply input their queries to generate citation graphs.

Tools and techniques

Most reference managers on the market offer similar capabilities when it comes to providing a Microsoft Word plug-in and producing different citation styles. But depending on your working preferences, some might be more suitable than others.

Reference managers

Here is a comparison of the more popular collaborative writing tools, but there are other options, including Fidus Writer, Manuscript.io, Authorea and Stencila.

Collaborative writing tools

*Markdown and LaTex are code-based formatting languages favoured by physicists, mathematicians and computer scientists who code on a regular basis, and less popular in other disciplines such as biology and chemistry.

doi: https://doi.org/10.1038/d41586-020-03422-x

Interviews have been edited for length and clarity.

Updates & Corrections

Correction 09 December 2020 : An earlier version of the tables in this article included some incorrect details about the programs Zotero, Endnote and Manubot. These have now been corrected.

Hsing, I.-M., Xu, Y. & Zhao, W. Electroanalysis 19 , 755–768 (2007).

Article   Google Scholar  

Ledesma, H. A. et al. Nature Nanotechnol. 14 , 645–657 (2019).

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Brahlek, M., Koirala, N., Bansal, N. & Oh, S. Solid State Commun. 215–216 , 54–62 (2015).

Choi, Y. & Lee, S. Y. Nature Rev. Chem . https://doi.org/10.1038/s41570-020-00221-w (2020).

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• Literature Review: The What, Why and How-to Guide
• Introduction

Literature Review: The What, Why and How-to Guide — Introduction

• Getting Started
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What are Literature Reviews?

So, what is a literature review? "A literature review is an account of what has been published on a topic by accredited scholars and researchers. In writing the literature review, your purpose is to convey to your reader what knowledge and ideas have been established on a topic, and what their strengths and weaknesses are. As a piece of writing, the literature review must be defined by a guiding concept (e.g., your research objective, the problem or issue you are discussing, or your argumentative thesis). It is not just a descriptive list of the material available, or a set of summaries." Taylor, D.  The literature review: A few tips on conducting it . University of Toronto Health Sciences Writing Centre.

Goals of Literature Reviews

What are the goals of creating a Literature Review?  A literature could be written to accomplish different aims:

• To develop a theory or evaluate an existing theory
• To summarize the historical or existing state of a research topic
• Identify a problem in a field of research 

Baumeister, R. F., & Leary, M. R. (1997). Writing narrative literature reviews .  Review of General Psychology , 1 (3), 311-320.

What kinds of sources require a Literature Review?

• A research paper assigned in a course
• A thesis or dissertation
• A grant proposal
• An article intended for publication in a journal

All these instances require you to collect what has been written about your research topic so that you can demonstrate how your own research sheds new light on the topic.

Types of Literature Reviews

What kinds of literature reviews are written?

Narrative review: The purpose of this type of review is to describe the current state of the research on a specific topic/research and to offer a critical analysis of the literature reviewed. Studies are grouped by research/theoretical categories, and themes and trends, strengths and weakness, and gaps are identified. The review ends with a conclusion section which summarizes the findings regarding the state of the research of the specific study, the gaps identify and if applicable, explains how the author's research will address gaps identify in the review and expand the knowledge on the topic reviewed.

• Example : Predictors and Outcomes of U.S. Quality Maternity Leave: A Review and Conceptual Framework:  10.1177/08948453211037398  

Systematic review : "The authors of a systematic review use a specific procedure to search the research literature, select the studies to include in their review, and critically evaluate the studies they find." (p. 139). Nelson, L. K. (2013). Research in Communication Sciences and Disorders . Plural Publishing.

• Example : The effect of leave policies on increasing fertility: a systematic review:  10.1057/s41599-022-01270-w

Meta-analysis : "Meta-analysis is a method of reviewing research findings in a quantitative fashion by transforming the data from individual studies into what is called an effect size and then pooling and analyzing this information. The basic goal in meta-analysis is to explain why different outcomes have occurred in different studies." (p. 197). Roberts, M. C., & Ilardi, S. S. (2003). Handbook of Research Methods in Clinical Psychology . Blackwell Publishing.

• Example : Employment Instability and Fertility in Europe: A Meta-Analysis:  10.1215/00703370-9164737

Meta-synthesis : "Qualitative meta-synthesis is a type of qualitative study that uses as data the findings from other qualitative studies linked by the same or related topic." (p.312). Zimmer, L. (2006). Qualitative meta-synthesis: A question of dialoguing with texts .  Journal of Advanced Nursing , 53 (3), 311-318.

• Example : Women’s perspectives on career successes and barriers: A qualitative meta-synthesis:  10.1177/05390184221113735

Literature Reviews in the Health Sciences

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A literature review surveys prior research published in books, scholarly articles, and any other sources relevant to a particular issue, area of research, or theory, and by so doing, provides a description, summary, and critical evaluation of these works in relation to the research problem being investigated. Literature reviews are designed to provide an overview of sources you have used in researching a particular topic and to demonstrate to your readers how your research fits within existing scholarship about the topic.

Fink, Arlene. Conducting Research Literature Reviews: From the Internet to Paper . Fourth edition. Thousand Oaks, CA: SAGE, 2014.

Importance of a Good Literature Review

A literature review may consist of simply a summary of key sources, but in the social sciences, a literature review usually has an organizational pattern and combines both summary and synthesis, often within specific conceptual categories . A summary is a recap of the important information of the source, but a synthesis is a re-organization, or a reshuffling, of that information in a way that informs how you are planning to investigate a research problem. The analytical features of a literature review might:

• Give a new interpretation of old material or combine new with old interpretations,
• Trace the intellectual progression of the field, including major debates,
• Depending on the situation, evaluate the sources and advise the reader on the most pertinent or relevant research, or
• Usually in the conclusion of a literature review, identify where gaps exist in how a problem has been researched to date.

Given this, the purpose of a literature review is to:

• Place each work in the context of its contribution to understanding the research problem being studied.
• Describe the relationship of each work to the others under consideration.
• Identify new ways to interpret prior research.
• Reveal any gaps that exist in the literature.
• Resolve conflicts amongst seemingly contradictory previous studies.
• Identify areas of prior scholarship to prevent duplication of effort.
• Point the way in fulfilling a need for additional research.
• Locate your own research within the context of existing literature [very important].

Fink, Arlene. Conducting Research Literature Reviews: From the Internet to Paper. 2nd ed. Thousand Oaks, CA: Sage, 2005; Hart, Chris. Doing a Literature Review: Releasing the Social Science Research Imagination . Thousand Oaks, CA: Sage Publications, 1998; Jesson, Jill. Doing Your Literature Review: Traditional and Systematic Techniques . Los Angeles, CA: SAGE, 2011; Knopf, Jeffrey W. "Doing a Literature Review." PS: Political Science and Politics 39 (January 2006): 127-132; Ridley, Diana. The Literature Review: A Step-by-Step Guide for Students . 2nd ed. Los Angeles, CA: SAGE, 2012.

Types of Literature Reviews

It is important to think of knowledge in a given field as consisting of three layers. First, there are the primary studies that researchers conduct and publish. Second are the reviews of those studies that summarize and offer new interpretations built from and often extending beyond the primary studies. Third, there are the perceptions, conclusions, opinion, and interpretations that are shared informally among scholars that become part of the body of epistemological traditions within the field.

In composing a literature review, it is important to note that it is often this third layer of knowledge that is cited as "true" even though it often has only a loose relationship to the primary studies and secondary literature reviews. Given this, while literature reviews are designed to provide an overview and synthesis of pertinent sources you have explored, there are a number of approaches you could adopt depending upon the type of analysis underpinning your study.

Argumentative Review This form examines literature selectively in order to support or refute an argument, deeply embedded assumption, or philosophical problem already established in the literature. The purpose is to develop a body of literature that establishes a contrarian viewpoint. Given the value-laden nature of some social science research [e.g., educational reform; immigration control], argumentative approaches to analyzing the literature can be a legitimate and important form of discourse. However, note that they can also introduce problems of bias when they are used to make summary claims of the sort found in systematic reviews [see below].

Integrative Review Considered a form of research that reviews, critiques, and synthesizes representative literature on a topic in an integrated way such that new frameworks and perspectives on the topic are generated. The body of literature includes all studies that address related or identical hypotheses or research problems. A well-done integrative review meets the same standards as primary research in regard to clarity, rigor, and replication. This is the most common form of review in the social sciences.

Historical Review Few things rest in isolation from historical precedent. Historical literature reviews focus on examining research throughout a period of time, often starting with the first time an issue, concept, theory, phenomena emerged in the literature, then tracing its evolution within the scholarship of a discipline. The purpose is to place research in a historical context to show familiarity with state-of-the-art developments and to identify the likely directions for future research.

Methodological Review A review does not always focus on what someone said [findings], but how they came about saying what they say [method of analysis]. Reviewing methods of analysis provides a framework of understanding at different levels [i.e. those of theory, substantive fields, research approaches, and data collection and analysis techniques], how researchers draw upon a wide variety of knowledge ranging from the conceptual level to practical documents for use in fieldwork in the areas of ontological and epistemological consideration, quantitative and qualitative integration, sampling, interviewing, data collection, and data analysis. This approach helps highlight ethical issues which you should be aware of and consider as you go through your own study.

Systematic Review This form consists of an overview of existing evidence pertinent to a clearly formulated research question, which uses pre-specified and standardized methods to identify and critically appraise relevant research, and to collect, report, and analyze data from the studies that are included in the review. The goal is to deliberately document, critically evaluate, and summarize scientifically all of the research about a clearly defined research problem . Typically it focuses on a very specific empirical question, often posed in a cause-and-effect form, such as "To what extent does A contribute to B?" This type of literature review is primarily applied to examining prior research studies in clinical medicine and allied health fields, but it is increasingly being used in the social sciences.

Theoretical Review The purpose of this form is to examine the corpus of theory that has accumulated in regard to an issue, concept, theory, phenomena. The theoretical literature review helps to establish what theories already exist, the relationships between them, to what degree the existing theories have been investigated, and to develop new hypotheses to be tested. Often this form is used to help establish a lack of appropriate theories or reveal that current theories are inadequate for explaining new or emerging research problems. The unit of analysis can focus on a theoretical concept or a whole theory or framework.

NOTE: Most often the literature review will incorporate some combination of types. For example, a review that examines literature supporting or refuting an argument, assumption, or philosophical problem related to the research problem will also need to include writing supported by sources that establish the history of these arguments in the literature.

Baumeister, Roy F. and Mark R. Leary. "Writing Narrative Literature Reviews."  Review of General Psychology 1 (September 1997): 311-320; Mark R. Fink, Arlene. Conducting Research Literature Reviews: From the Internet to Paper . 2nd ed. Thousand Oaks, CA: Sage, 2005; Hart, Chris. Doing a Literature Review: Releasing the Social Science Research Imagination . Thousand Oaks, CA: Sage Publications, 1998; Kennedy, Mary M. "Defining a Literature." Educational Researcher 36 (April 2007): 139-147; Petticrew, Mark and Helen Roberts. Systematic Reviews in the Social Sciences: A Practical Guide . Malden, MA: Blackwell Publishers, 2006; Torracro, Richard. "Writing Integrative Literature Reviews: Guidelines and Examples." Human Resource Development Review 4 (September 2005): 356-367; Rocco, Tonette S. and Maria S. Plakhotnik. "Literature Reviews, Conceptual Frameworks, and Theoretical Frameworks: Terms, Functions, and Distinctions." Human Ressource Development Review 8 (March 2008): 120-130; Sutton, Anthea. Systematic Approaches to a Successful Literature Review . Los Angeles, CA: Sage Publications, 2016.

Structure and Writing Style

I.  Thinking About Your Literature Review

The structure of a literature review should include the following in support of understanding the research problem :

• An overview of the subject, issue, or theory under consideration, along with the objectives of the literature review,
• Division of works under review into themes or categories [e.g. works that support a particular position, those against, and those offering alternative approaches entirely],
• An explanation of how each work is similar to and how it varies from the others,
• Conclusions as to which pieces are best considered in their argument, are most convincing of their opinions, and make the greatest contribution to the understanding and development of their area of research.

The critical evaluation of each work should consider :

• Provenance -- what are the author's credentials? Are the author's arguments supported by evidence [e.g. primary historical material, case studies, narratives, statistics, recent scientific findings]?
• Methodology -- were the techniques used to identify, gather, and analyze the data appropriate to addressing the research problem? Was the sample size appropriate? Were the results effectively interpreted and reported?
• Objectivity -- is the author's perspective even-handed or prejudicial? Is contrary data considered or is certain pertinent information ignored to prove the author's point?
• Persuasiveness -- which of the author's theses are most convincing or least convincing?
• Validity -- are the author's arguments and conclusions convincing? Does the work ultimately contribute in any significant way to an understanding of the subject?

II.  Development of the Literature Review

Four Basic Stages of Writing 1.  Problem formulation -- which topic or field is being examined and what are its component issues? 2.  Literature search -- finding materials relevant to the subject being explored. 3.  Data evaluation -- determining which literature makes a significant contribution to the understanding of the topic. 4.  Analysis and interpretation -- discussing the findings and conclusions of pertinent literature.

Consider the following issues before writing the literature review: Clarify If your assignment is not specific about what form your literature review should take, seek clarification from your professor by asking these questions: 1.  Roughly how many sources would be appropriate to include? 2.  What types of sources should I review (books, journal articles, websites; scholarly versus popular sources)? 3.  Should I summarize, synthesize, or critique sources by discussing a common theme or issue? 4.  Should I evaluate the sources in any way beyond evaluating how they relate to understanding the research problem? 5.  Should I provide subheadings and other background information, such as definitions and/or a history? Find Models Use the exercise of reviewing the literature to examine how authors in your discipline or area of interest have composed their literature review sections. Read them to get a sense of the types of themes you might want to look for in your own research or to identify ways to organize your final review. The bibliography or reference section of sources you've already read, such as required readings in the course syllabus, are also excellent entry points into your own research. Narrow the Topic The narrower your topic, the easier it will be to limit the number of sources you need to read in order to obtain a good survey of relevant resources. Your professor will probably not expect you to read everything that's available about the topic, but you'll make the act of reviewing easier if you first limit scope of the research problem. A good strategy is to begin by searching the USC Libraries Catalog for recent books about the topic and review the table of contents for chapters that focuses on specific issues. You can also review the indexes of books to find references to specific issues that can serve as the focus of your research. For example, a book surveying the history of the Israeli-Palestinian conflict may include a chapter on the role Egypt has played in mediating the conflict, or look in the index for the pages where Egypt is mentioned in the text. Consider Whether Your Sources are Current Some disciplines require that you use information that is as current as possible. This is particularly true in disciplines in medicine and the sciences where research conducted becomes obsolete very quickly as new discoveries are made. However, when writing a review in the social sciences, a survey of the history of the literature may be required. In other words, a complete understanding the research problem requires you to deliberately examine how knowledge and perspectives have changed over time. Sort through other current bibliographies or literature reviews in the field to get a sense of what your discipline expects. You can also use this method to explore what is considered by scholars to be a "hot topic" and what is not.

III.  Ways to Organize Your Literature Review

Chronology of Events If your review follows the chronological method, you could write about the materials according to when they were published. This approach should only be followed if a clear path of research building on previous research can be identified and that these trends follow a clear chronological order of development. For example, a literature review that focuses on continuing research about the emergence of German economic power after the fall of the Soviet Union. By Publication Order your sources by publication chronology, then, only if the order demonstrates a more important trend. For instance, you could order a review of literature on environmental studies of brown fields if the progression revealed, for example, a change in the soil collection practices of the researchers who wrote and/or conducted the studies. Thematic [“conceptual categories”] A thematic literature review is the most common approach to summarizing prior research in the social and behavioral sciences. Thematic reviews are organized around a topic or issue, rather than the progression of time, although the progression of time may still be incorporated into a thematic review. For example, a review of the Internet’s impact on American presidential politics could focus on the development of online political satire. While the study focuses on one topic, the Internet’s impact on American presidential politics, it would still be organized chronologically reflecting technological developments in media. The difference in this example between a "chronological" and a "thematic" approach is what is emphasized the most: themes related to the role of the Internet in presidential politics. Note that more authentic thematic reviews tend to break away from chronological order. A review organized in this manner would shift between time periods within each section according to the point being made. Methodological A methodological approach focuses on the methods utilized by the researcher. For the Internet in American presidential politics project, one methodological approach would be to look at cultural differences between the portrayal of American presidents on American, British, and French websites. Or the review might focus on the fundraising impact of the Internet on a particular political party. A methodological scope will influence either the types of documents in the review or the way in which these documents are discussed.

Other Sections of Your Literature Review Once you've decided on the organizational method for your literature review, the sections you need to include in the paper should be easy to figure out because they arise from your organizational strategy. In other words, a chronological review would have subsections for each vital time period; a thematic review would have subtopics based upon factors that relate to the theme or issue. However, sometimes you may need to add additional sections that are necessary for your study, but do not fit in the organizational strategy of the body. What other sections you include in the body is up to you. However, only include what is necessary for the reader to locate your study within the larger scholarship about the research problem.

Here are examples of other sections, usually in the form of a single paragraph, you may need to include depending on the type of review you write:

• Current Situation : Information necessary to understand the current topic or focus of the literature review.
• Sources Used : Describes the methods and resources [e.g., databases] you used to identify the literature you reviewed.
• History : The chronological progression of the field, the research literature, or an idea that is necessary to understand the literature review, if the body of the literature review is not already a chronology.
• Selection Methods : Criteria you used to select (and perhaps exclude) sources in your literature review. For instance, you might explain that your review includes only peer-reviewed [i.e., scholarly] sources.
• Standards : Description of the way in which you present your information.
• Questions for Further Research : What questions about the field has the review sparked? How will you further your research as a result of the review?

IV.  Writing Your Literature Review

Once you've settled on how to organize your literature review, you're ready to write each section. When writing your review, keep in mind these issues.

Use Evidence A literature review section is, in this sense, just like any other academic research paper. Your interpretation of the available sources must be backed up with evidence [citations] that demonstrates that what you are saying is valid. Be Selective Select only the most important points in each source to highlight in the review. The type of information you choose to mention should relate directly to the research problem, whether it is thematic, methodological, or chronological. Related items that provide additional information, but that are not key to understanding the research problem, can be included in a list of further readings . Use Quotes Sparingly Some short quotes are appropriate if you want to emphasize a point, or if what an author stated cannot be easily paraphrased. Sometimes you may need to quote certain terminology that was coined by the author, is not common knowledge, or taken directly from the study. Do not use extensive quotes as a substitute for using your own words in reviewing the literature. Summarize and Synthesize Remember to summarize and synthesize your sources within each thematic paragraph as well as throughout the review. Recapitulate important features of a research study, but then synthesize it by rephrasing the study's significance and relating it to your own work and the work of others. Keep Your Own Voice While the literature review presents others' ideas, your voice [the writer's] should remain front and center. For example, weave references to other sources into what you are writing but maintain your own voice by starting and ending the paragraph with your own ideas and wording. Use Caution When Paraphrasing When paraphrasing a source that is not your own, be sure to represent the author's information or opinions accurately and in your own words. Even when paraphrasing an author’s work, you still must provide a citation to that work.

V.  Common Mistakes to Avoid

These are the most common mistakes made in reviewing social science research literature.

• Sources in your literature review do not clearly relate to the research problem;
• You do not take sufficient time to define and identify the most relevant sources to use in the literature review related to the research problem;
• Relies exclusively on secondary analytical sources rather than including relevant primary research studies or data;
• Uncritically accepts another researcher's findings and interpretations as valid, rather than examining critically all aspects of the research design and analysis;
• Does not describe the search procedures that were used in identifying the literature to review;
• Reports isolated statistical results rather than synthesizing them in chi-squared or meta-analytic methods; and,
• Only includes research that validates assumptions and does not consider contrary findings and alternative interpretations found in the literature.

Cook, Kathleen E. and Elise Murowchick. “Do Literature Review Skills Transfer from One Course to Another?” Psychology Learning and Teaching 13 (March 2014): 3-11; Fink, Arlene. Conducting Research Literature Reviews: From the Internet to Paper . 2nd ed. Thousand Oaks, CA: Sage, 2005; Hart, Chris. Doing a Literature Review: Releasing the Social Science Research Imagination . Thousand Oaks, CA: Sage Publications, 1998; Jesson, Jill. Doing Your Literature Review: Traditional and Systematic Techniques . London: SAGE, 2011; Literature Review Handout. Online Writing Center. Liberty University; Literature Reviews. The Writing Center. University of North Carolina; Onwuegbuzie, Anthony J. and Rebecca Frels. Seven Steps to a Comprehensive Literature Review: A Multimodal and Cultural Approach . Los Angeles, CA: SAGE, 2016; Ridley, Diana. The Literature Review: A Step-by-Step Guide for Students . 2nd ed. Los Angeles, CA: SAGE, 2012; Randolph, Justus J. “A Guide to Writing the Dissertation Literature Review." Practical Assessment, Research, and Evaluation. vol. 14, June 2009; Sutton, Anthea. Systematic Approaches to a Successful Literature Review . Los Angeles, CA: Sage Publications, 2016; Taylor, Dena. The Literature Review: A Few Tips On Conducting It. University College Writing Centre. University of Toronto; Writing a Literature Review. Academic Skills Centre. University of Canberra.

Writing Tip

Break Out of Your Disciplinary Box!

Thinking interdisciplinarily about a research problem can be a rewarding exercise in applying new ideas, theories, or concepts to an old problem. For example, what might cultural anthropologists say about the continuing conflict in the Middle East? In what ways might geographers view the need for better distribution of social service agencies in large cities than how social workers might study the issue? You don’t want to substitute a thorough review of core research literature in your discipline for studies conducted in other fields of study. However, particularly in the social sciences, thinking about research problems from multiple vectors is a key strategy for finding new solutions to a problem or gaining a new perspective. Consult with a librarian about identifying research databases in other disciplines; almost every field of study has at least one comprehensive database devoted to indexing its research literature.

Frodeman, Robert. The Oxford Handbook of Interdisciplinarity . New York: Oxford University Press, 2010.

Another Writing Tip

Don't Just Review for Content!

While conducting a review of the literature, maximize the time you devote to writing this part of your paper by thinking broadly about what you should be looking for and evaluating. Review not just what scholars are saying, but how are they saying it. Some questions to ask:

• How are they organizing their ideas?
• What methods have they used to study the problem?
• What theories have been used to explain, predict, or understand their research problem?
• What sources have they cited to support their conclusions?
• How have they used non-textual elements [e.g., charts, graphs, figures, etc.] to illustrate key points?

When you begin to write your literature review section, you'll be glad you dug deeper into how the research was designed and constructed because it establishes a means for developing more substantial analysis and interpretation of the research problem.

Hart, Chris. Doing a Literature Review: Releasing the Social Science Research Imagination . Thousand Oaks, CA: Sage Publications, 1 998.

Yet Another Writing Tip

When Do I Know I Can Stop Looking and Move On?

Here are several strategies you can utilize to assess whether you've thoroughly reviewed the literature:

• Look for repeating patterns in the research findings . If the same thing is being said, just by different people, then this likely demonstrates that the research problem has hit a conceptual dead end. At this point consider: Does your study extend current research?  Does it forge a new path? Or, does is merely add more of the same thing being said?
• Look at sources the authors cite to in their work . If you begin to see the same researchers cited again and again, then this is often an indication that no new ideas have been generated to address the research problem.
• Search Google Scholar to identify who has subsequently cited leading scholars already identified in your literature review [see next sub-tab]. This is called citation tracking and there are a number of sources that can help you identify who has cited whom, particularly scholars from outside of your discipline. Here again, if the same authors are being cited again and again, this may indicate no new literature has been written on the topic.

Onwuegbuzie, Anthony J. and Rebecca Frels. Seven Steps to a Comprehensive Literature Review: A Multimodal and Cultural Approach . Los Angeles, CA: Sage, 2016; Sutton, Anthea. Systematic Approaches to a Successful Literature Review . Los Angeles, CA: Sage Publications, 2016.

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Research Methods

• Getting Started
• Literature Review Research
• Research Design
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Literature Review

• What is a Literature Review?
• What is NOT a Literature Review?
• Purposes of a Literature Review
• Types of Literature Reviews
• Literature Reviews vs. Systematic Reviews
• Systematic vs. Meta-Analysis

Literature Review  is a comprehensive survey of the works published in a particular field of study or line of research, usually over a specific period of time, in the form of an in-depth, critical bibliographic essay or annotated list in which attention is drawn to the most significant works.

Also, we can define a literature review as the collected body of scholarly works related to a topic:

• Summarizes and analyzes previous research relevant to a topic
• Includes scholarly books and articles published in academic journals
• Can be an specific scholarly paper or a section in a research paper

The objective of a Literature Review is to find previous published scholarly works relevant to an specific topic

• Help gather ideas or information
• Keep up to date in current trends and findings
• Help develop new questions

A literature review is important because it:

• Explains the background of research on a topic.
• Demonstrates why a topic is significant to a subject area.
• Helps focus your own research questions or problems
• Discovers relationships between research studies/ideas.
• Suggests unexplored ideas or populations
• Identifies major themes, concepts, and researchers on a topic.
• Tests assumptions; may help counter preconceived ideas and remove unconscious bias.
• Identifies critical gaps, points of disagreement, or potentially flawed methodology or theoretical approaches.
• Indicates potential directions for future research.

All content in this section is from Literature Review Research from Old Dominion University 

Keep in mind the following, a literature review is NOT:

Not an essay 

Not an annotated bibliography  in which you summarize each article that you have reviewed.  A literature review goes beyond basic summarizing to focus on the critical analysis of the reviewed works and their relationship to your research question.

Not a research paper   where you select resources to support one side of an issue versus another.  A lit review should explain and consider all sides of an argument in order to avoid bias, and areas of agreement and disagreement should be highlighted.

A literature review serves several purposes. For example, it

• provides thorough knowledge of previous studies; introduces seminal works.
• helps focus one’s own research topic.
• identifies a conceptual framework for one’s own research questions or problems; indicates potential directions for future research.
• suggests previously unused or underused methodologies, designs, quantitative and qualitative strategies.
• identifies gaps in previous studies; identifies flawed methodologies and/or theoretical approaches; avoids replication of mistakes.
• helps the researcher avoid repetition of earlier research.
• suggests unexplored populations.
• determines whether past studies agree or disagree; identifies controversy in the literature.
• tests assumptions; may help counter preconceived ideas and remove unconscious bias.

As Kennedy (2007) notes*, it is important to think of knowledge in a given field as consisting of three layers. First, there are the primary studies that researchers conduct and publish. Second are the reviews of those studies that summarize and offer new interpretations built from and often extending beyond the original studies. Third, there are the perceptions, conclusions, opinion, and interpretations that are shared informally that become part of the lore of field. In composing a literature review, it is important to note that it is often this third layer of knowledge that is cited as "true" even though it often has only a loose relationship to the primary studies and secondary literature reviews.

Given this, while literature reviews are designed to provide an overview and synthesis of pertinent sources you have explored, there are several approaches to how they can be done, depending upon the type of analysis underpinning your study. Listed below are definitions of types of literature reviews:

Argumentative Review      This form examines literature selectively in order to support or refute an argument, deeply imbedded assumption, or philosophical problem already established in the literature. The purpose is to develop a body of literature that establishes a contrarian viewpoint. Given the value-laden nature of some social science research [e.g., educational reform; immigration control], argumentative approaches to analyzing the literature can be a legitimate and important form of discourse. However, note that they can also introduce problems of bias when they are used to to make summary claims of the sort found in systematic reviews.

Integrative Review      Considered a form of research that reviews, critiques, and synthesizes representative literature on a topic in an integrated way such that new frameworks and perspectives on the topic are generated. The body of literature includes all studies that address related or identical hypotheses. A well-done integrative review meets the same standards as primary research in regard to clarity, rigor, and replication.

Historical Review      Few things rest in isolation from historical precedent. Historical reviews are focused on examining research throughout a period of time, often starting with the first time an issue, concept, theory, phenomena emerged in the literature, then tracing its evolution within the scholarship of a discipline. The purpose is to place research in a historical context to show familiarity with state-of-the-art developments and to identify the likely directions for future research.

Methodological Review      A review does not always focus on what someone said [content], but how they said it [method of analysis]. This approach provides a framework of understanding at different levels (i.e. those of theory, substantive fields, research approaches and data collection and analysis techniques), enables researchers to draw on a wide variety of knowledge ranging from the conceptual level to practical documents for use in fieldwork in the areas of ontological and epistemological consideration, quantitative and qualitative integration, sampling, interviewing, data collection and data analysis, and helps highlight many ethical issues which we should be aware of and consider as we go through our study.

Systematic Review      This form consists of an overview of existing evidence pertinent to a clearly formulated research question, which uses pre-specified and standardized methods to identify and critically appraise relevant research, and to collect, report, and analyse data from the studies that are included in the review. Typically it focuses on a very specific empirical question, often posed in a cause-and-effect form, such as "To what extent does A contribute to B?"

Theoretical Review      The purpose of this form is to concretely examine the corpus of theory that has accumulated in regard to an issue, concept, theory, phenomena. The theoretical literature review help establish what theories already exist, the relationships between them, to what degree the existing theories have been investigated, and to develop new hypotheses to be tested. Often this form is used to help establish a lack of appropriate theories or reveal that current theories are inadequate for explaining new or emerging research problems. The unit of analysis can focus on a theoretical concept or a whole theory or framework.

* Kennedy, Mary M. "Defining a Literature."  Educational Researcher  36 (April 2007): 139-147.

All content in this section is from The Literature Review created by Dr. Robert Larabee USC

Robinson, P. and Lowe, J. (2015),  Literature reviews vs systematic reviews.  Australian and New Zealand Journal of Public Health, 39: 103-103. doi: 10.1111/1753-6405.12393

What's in the name? The difference between a Systematic Review and a Literature Review, and why it matters . By Lynn Kysh from University of Southern California

Systematic review or meta-analysis?

A  systematic review  answers a defined research question by collecting and summarizing all empirical evidence that fits pre-specified eligibility criteria.

A  meta-analysis  is the use of statistical methods to summarize the results of these studies.

Systematic reviews, just like other research articles, can be of varying quality. They are a significant piece of work (the Centre for Reviews and Dissemination at York estimates that a team will take 9-24 months), and to be useful to other researchers and practitioners they should have:

• clearly stated objectives with pre-defined eligibility criteria for studies
• explicit, reproducible methodology
• a systematic search that attempts to identify all studies
• assessment of the validity of the findings of the included studies (e.g. risk of bias)
• systematic presentation, and synthesis, of the characteristics and findings of the included studies

Not all systematic reviews contain meta-analysis. 

Meta-analysis is the use of statistical methods to summarize the results of independent studies. By combining information from all relevant studies, meta-analysis can provide more precise estimates of the effects of health care than those derived from the individual studies included within a review.  More information on meta-analyses can be found in  Cochrane Handbook, Chapter 9 .

A meta-analysis goes beyond critique and integration and conducts secondary statistical analysis on the outcomes of similar studies.  It is a systematic review that uses quantitative methods to synthesize and summarize the results.

An advantage of a meta-analysis is the ability to be completely objective in evaluating research findings.  Not all topics, however, have sufficient research evidence to allow a meta-analysis to be conducted.  In that case, an integrative review is an appropriate strategy. 

Some of the content in this section is from Systematic reviews and meta-analyses: step by step guide created by Kate McAllister.

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What is a literature review?

A literature review is an integrated analysis -- not just a summary-- of scholarly writings and other relevant evidence related directly to your research question.  That is, it represents a synthesis of the evidence that provides background information on your topic and shows a association between the evidence and your research question.

A literature review may be a stand alone work or the introduction to a larger research paper, depending on the assignment.  Rely heavily on the guidelines your instructor has given you.

Why is it important?

A literature review is important because it:

• Explains the background of research on a topic.
• Demonstrates why a topic is significant to a subject area.
• Discovers relationships between research studies/ideas.
• Identifies major themes, concepts, and researchers on a topic.
• Identifies critical gaps and points of disagreement.
• Discusses further research questions that logically come out of the previous studies.

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1. Choose a topic. Define your research question.

Your literature review should be guided by your central research question.  The literature represents background and research developments related to a specific research question, interpreted and analyzed by you in a synthesized way.

• Make sure your research question is not too broad or too narrow.  Is it manageable?
• Begin writing down terms that are related to your question. These will be useful for searches later.
• If you have the opportunity, discuss your topic with your professor and your class mates.

2. Decide on the scope of your review

How many studies do you need to look at? How comprehensive should it be? How many years should it cover? 

• This may depend on your assignment.  How many sources does the assignment require?

3. Select the databases you will use to conduct your searches.

Make a list of the databases you will search. 

Where to find databases:

• use the tabs on this guide
• Find other databases in the Nursing Information Resources web page
• More on the Medical Library web page
• ... and more on the Yale University Library web page

4. Conduct your searches to find the evidence. Keep track of your searches.

• Use the key words in your question, as well as synonyms for those words, as terms in your search. Use the database tutorials for help.
• Save the searches in the databases. This saves time when you want to redo, or modify, the searches. It is also helpful to use as a guide is the searches are not finding any useful results.
• Review the abstracts of research studies carefully. This will save you time.
• Use the bibliographies and references of research studies you find to locate others.
• Check with your professor, or a subject expert in the field, if you are missing any key works in the field.
• Ask your librarian for help at any time.
• Use a citation manager, such as EndNote as the repository for your citations. See the EndNote tutorials for help.

Review the literature

Some questions to help you analyze the research:

• What was the research question of the study you are reviewing? What were the authors trying to discover?
• Was the research funded by a source that could influence the findings?
• What were the research methodologies? Analyze its literature review, the samples and variables used, the results, and the conclusions.
• Does the research seem to be complete? Could it have been conducted more soundly? What further questions does it raise?
• If there are conflicting studies, why do you think that is?
• How are the authors viewed in the field? Has this study been cited? If so, how has it been analyzed?

Tips: 

• Review the abstracts carefully.  
• Keep careful notes so that you may track your thought processes during the research process.
• Create a matrix of the studies for easy analysis, and synthesis, across all of the studies.
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Writing a Literature Review

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A literature review is a document or section of a document that collects key sources on a topic and discusses those sources in conversation with each other (also called synthesis ). The lit review is an important genre in many disciplines, not just literature (i.e., the study of works of literature such as novels and plays). When we say “literature review” or refer to “the literature,” we are talking about the research ( scholarship ) in a given field. You will often see the terms “the research,” “the scholarship,” and “the literature” used mostly interchangeably.

Where, when, and why would I write a lit review?

There are a number of different situations where you might write a literature review, each with slightly different expectations; different disciplines, too, have field-specific expectations for what a literature review is and does. For instance, in the humanities, authors might include more overt argumentation and interpretation of source material in their literature reviews, whereas in the sciences, authors are more likely to report study designs and results in their literature reviews; these differences reflect these disciplines’ purposes and conventions in scholarship. You should always look at examples from your own discipline and talk to professors or mentors in your field to be sure you understand your discipline’s conventions, for literature reviews as well as for any other genre.

A literature review can be a part of a research paper or scholarly article, usually falling after the introduction and before the research methods sections. In these cases, the lit review just needs to cover scholarship that is important to the issue you are writing about; sometimes it will also cover key sources that informed your research methodology.

Lit reviews can also be standalone pieces, either as assignments in a class or as publications. In a class, a lit review may be assigned to help students familiarize themselves with a topic and with scholarship in their field, get an idea of the other researchers working on the topic they’re interested in, find gaps in existing research in order to propose new projects, and/or develop a theoretical framework and methodology for later research. As a publication, a lit review usually is meant to help make other scholars’ lives easier by collecting and summarizing, synthesizing, and analyzing existing research on a topic. This can be especially helpful for students or scholars getting into a new research area, or for directing an entire community of scholars toward questions that have not yet been answered.

What are the parts of a lit review?

Most lit reviews use a basic introduction-body-conclusion structure; if your lit review is part of a larger paper, the introduction and conclusion pieces may be just a few sentences while you focus most of your attention on the body. If your lit review is a standalone piece, the introduction and conclusion take up more space and give you a place to discuss your goals, research methods, and conclusions separately from where you discuss the literature itself.

Introduction:

• An introductory paragraph that explains what your working topic and thesis is
• A forecast of key topics or texts that will appear in the review
• Potentially, a description of how you found sources and how you analyzed them for inclusion and discussion in the review (more often found in published, standalone literature reviews than in lit review sections in an article or research paper)
• Summarize and synthesize: Give an overview of the main points of each source and combine them into a coherent whole
• Analyze and interpret: Don’t just paraphrase other researchers – add your own interpretations where possible, discussing the significance of findings in relation to the literature as a whole
• Critically Evaluate: Mention the strengths and weaknesses of your sources
• Write in well-structured paragraphs: Use transition words and topic sentence to draw connections, comparisons, and contrasts.

Conclusion:

• Summarize the key findings you have taken from the literature and emphasize their significance
• Connect it back to your primary research question

How should I organize my lit review?

Lit reviews can take many different organizational patterns depending on what you are trying to accomplish with the review. Here are some examples:

• Chronological : The simplest approach is to trace the development of the topic over time, which helps familiarize the audience with the topic (for instance if you are introducing something that is not commonly known in your field). If you choose this strategy, be careful to avoid simply listing and summarizing sources in order. Try to analyze the patterns, turning points, and key debates that have shaped the direction of the field. Give your interpretation of how and why certain developments occurred (as mentioned previously, this may not be appropriate in your discipline — check with a teacher or mentor if you’re unsure).
• Thematic : If you have found some recurring central themes that you will continue working with throughout your piece, you can organize your literature review into subsections that address different aspects of the topic. For example, if you are reviewing literature about women and religion, key themes can include the role of women in churches and the religious attitude towards women.
• Qualitative versus quantitative research
• Empirical versus theoretical scholarship
• Divide the research by sociological, historical, or cultural sources
• Theoretical : In many humanities articles, the literature review is the foundation for the theoretical framework. You can use it to discuss various theories, models, and definitions of key concepts. You can argue for the relevance of a specific theoretical approach or combine various theorical concepts to create a framework for your research.

What are some strategies or tips I can use while writing my lit review?

Any lit review is only as good as the research it discusses; make sure your sources are well-chosen and your research is thorough. Don’t be afraid to do more research if you discover a new thread as you’re writing. More info on the research process is available in our "Conducting Research" resources .

As you’re doing your research, create an annotated bibliography ( see our page on the this type of document ). Much of the information used in an annotated bibliography can be used also in a literature review, so you’ll be not only partially drafting your lit review as you research, but also developing your sense of the larger conversation going on among scholars, professionals, and any other stakeholders in your topic.

Usually you will need to synthesize research rather than just summarizing it. This means drawing connections between sources to create a picture of the scholarly conversation on a topic over time. Many student writers struggle to synthesize because they feel they don’t have anything to add to the scholars they are citing; here are some strategies to help you:

• It often helps to remember that the point of these kinds of syntheses is to show your readers how you understand your research, to help them read the rest of your paper.
• Writing teachers often say synthesis is like hosting a dinner party: imagine all your sources are together in a room, discussing your topic. What are they saying to each other?
• Look at the in-text citations in each paragraph. Are you citing just one source for each paragraph? This usually indicates summary only. When you have multiple sources cited in a paragraph, you are more likely to be synthesizing them (not always, but often
• Read more about synthesis here.

The most interesting literature reviews are often written as arguments (again, as mentioned at the beginning of the page, this is discipline-specific and doesn’t work for all situations). Often, the literature review is where you can establish your research as filling a particular gap or as relevant in a particular way. You have some chance to do this in your introduction in an article, but the literature review section gives a more extended opportunity to establish the conversation in the way you would like your readers to see it. You can choose the intellectual lineage you would like to be part of and whose definitions matter most to your thinking (mostly humanities-specific, but this goes for sciences as well). In addressing these points, you argue for your place in the conversation, which tends to make the lit review more compelling than a simple reporting of other sources.

What is a Literature Review? How to Write It (with Examples)

A literature review is a critical analysis and synthesis of existing research on a particular topic. It provides an overview of the current state of knowledge, identifies gaps, and highlights key findings in the literature. 1 The purpose of a literature review is to situate your own research within the context of existing scholarship, demonstrating your understanding of the topic and showing how your work contributes to the ongoing conversation in the field. Learning how to write a literature review is a critical tool for successful research. Your ability to summarize and synthesize prior research pertaining to a certain topic demonstrates your grasp on the topic of study, and assists in the learning process. 

Table of Contents

• What is the purpose of literature review? 
• a. Habitat Loss and Species Extinction: 
• b. Range Shifts and Phenological Changes: 
• c. Ocean Acidification and Coral Reefs: 
• d. Adaptive Strategies and Conservation Efforts: 

How to write a good literature review 

• Choose a Topic and Define the Research Question: 
• Decide on the Scope of Your Review: 
• Select Databases for Searches: 
• Conduct Searches and Keep Track: 
• Review the Literature: 
• Organize and Write Your Literature Review: 
• How to write a literature review faster with Paperpal? 
• Frequently asked questions 

What is a literature review?

A well-conducted literature review demonstrates the researcher’s familiarity with the existing literature, establishes the context for their own research, and contributes to scholarly conversations on the topic. One of the purposes of a literature review is also to help researchers avoid duplicating previous work and ensure that their research is informed by and builds upon the existing body of knowledge.

What is the purpose of literature review?

A literature review serves several important purposes within academic and research contexts. Here are some key objectives and functions of a literature review: 2  

1. Contextualizing the Research Problem: The literature review provides a background and context for the research problem under investigation. It helps to situate the study within the existing body of knowledge. 

2. Identifying Gaps in Knowledge: By identifying gaps, contradictions, or areas requiring further research, the researcher can shape the research question and justify the significance of the study. This is crucial for ensuring that the new research contributes something novel to the field. 

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3. Understanding Theoretical and Conceptual Frameworks: Literature reviews help researchers gain an understanding of the theoretical and conceptual frameworks used in previous studies. This aids in the development of a theoretical framework for the current research. 

4. Providing Methodological Insights: Another purpose of literature reviews is that it allows researchers to learn about the methodologies employed in previous studies. This can help in choosing appropriate research methods for the current study and avoiding pitfalls that others may have encountered. 

5. Establishing Credibility: A well-conducted literature review demonstrates the researcher’s familiarity with existing scholarship, establishing their credibility and expertise in the field. It also helps in building a solid foundation for the new research. 

6. Informing Hypotheses or Research Questions: The literature review guides the formulation of hypotheses or research questions by highlighting relevant findings and areas of uncertainty in existing literature. 

Literature review example

Let’s delve deeper with a literature review example: Let’s say your literature review is about the impact of climate change on biodiversity. You might format your literature review into sections such as the effects of climate change on habitat loss and species extinction, phenological changes, and marine biodiversity. Each section would then summarize and analyze relevant studies in those areas, highlighting key findings and identifying gaps in the research. The review would conclude by emphasizing the need for further research on specific aspects of the relationship between climate change and biodiversity. The following literature review template provides a glimpse into the recommended literature review structure and content, demonstrating how research findings are organized around specific themes within a broader topic. 

Literature Review on Climate Change Impacts on Biodiversity:

Climate change is a global phenomenon with far-reaching consequences, including significant impacts on biodiversity. This literature review synthesizes key findings from various studies: 

a. Habitat Loss and Species Extinction:

Climate change-induced alterations in temperature and precipitation patterns contribute to habitat loss, affecting numerous species (Thomas et al., 2004). The review discusses how these changes increase the risk of extinction, particularly for species with specific habitat requirements. 

b. Range Shifts and Phenological Changes:

Observations of range shifts and changes in the timing of biological events (phenology) are documented in response to changing climatic conditions (Parmesan & Yohe, 2003). These shifts affect ecosystems and may lead to mismatches between species and their resources. 

c. Ocean Acidification and Coral Reefs:

The review explores the impact of climate change on marine biodiversity, emphasizing ocean acidification’s threat to coral reefs (Hoegh-Guldberg et al., 2007). Changes in pH levels negatively affect coral calcification, disrupting the delicate balance of marine ecosystems. 

d. Adaptive Strategies and Conservation Efforts:

Recognizing the urgency of the situation, the literature review discusses various adaptive strategies adopted by species and conservation efforts aimed at mitigating the impacts of climate change on biodiversity (Hannah et al., 2007). It emphasizes the importance of interdisciplinary approaches for effective conservation planning. 

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Writing a literature review involves summarizing and synthesizing existing research on a particular topic. A good literature review format should include the following elements. 

Introduction: The introduction sets the stage for your literature review, providing context and introducing the main focus of your review. 

• Opening Statement: Begin with a general statement about the broader topic and its significance in the field. 
• Scope and Purpose: Clearly define the scope of your literature review. Explain the specific research question or objective you aim to address. 
• Organizational Framework: Briefly outline the structure of your literature review, indicating how you will categorize and discuss the existing research. 
• Significance of the Study: Highlight why your literature review is important and how it contributes to the understanding of the chosen topic. 
• Thesis Statement: Conclude the introduction with a concise thesis statement that outlines the main argument or perspective you will develop in the body of the literature review. 

Body: The body of the literature review is where you provide a comprehensive analysis of existing literature, grouping studies based on themes, methodologies, or other relevant criteria. 

• Organize by Theme or Concept: Group studies that share common themes, concepts, or methodologies. Discuss each theme or concept in detail, summarizing key findings and identifying gaps or areas of disagreement. 
• Critical Analysis: Evaluate the strengths and weaknesses of each study. Discuss the methodologies used, the quality of evidence, and the overall contribution of each work to the understanding of the topic. 
• Synthesis of Findings: Synthesize the information from different studies to highlight trends, patterns, or areas of consensus in the literature. 
• Identification of Gaps: Discuss any gaps or limitations in the existing research and explain how your review contributes to filling these gaps. 
• Transition between Sections: Provide smooth transitions between different themes or concepts to maintain the flow of your literature review. 

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Conclusion: The conclusion of your literature review should summarize the main findings, highlight the contributions of the review, and suggest avenues for future research. 

• Summary of Key Findings: Recap the main findings from the literature and restate how they contribute to your research question or objective. 
• Contributions to the Field: Discuss the overall contribution of your literature review to the existing knowledge in the field. 
• Implications and Applications: Explore the practical implications of the findings and suggest how they might impact future research or practice. 
• Recommendations for Future Research: Identify areas that require further investigation and propose potential directions for future research in the field. 
• Final Thoughts: Conclude with a final reflection on the importance of your literature review and its relevance to the broader academic community. 

Conducting a literature review

Conducting a literature review is an essential step in research that involves reviewing and analyzing existing literature on a specific topic. It’s important to know how to do a literature review effectively, so here are the steps to follow: 1  

Choose a Topic and Define the Research Question:

• Select a topic that is relevant to your field of study. 
• Clearly define your research question or objective. Determine what specific aspect of the topic do you want to explore? 

Decide on the Scope of Your Review:

• Determine the timeframe for your literature review. Are you focusing on recent developments, or do you want a historical overview? 
• Consider the geographical scope. Is your review global, or are you focusing on a specific region? 
• Define the inclusion and exclusion criteria. What types of sources will you include? Are there specific types of studies or publications you will exclude? 

Select Databases for Searches:

• Identify relevant databases for your field. Examples include PubMed, IEEE Xplore, Scopus, Web of Science, and Google Scholar. 
• Consider searching in library catalogs, institutional repositories, and specialized databases related to your topic. 

Conduct Searches and Keep Track:

• Develop a systematic search strategy using keywords, Boolean operators (AND, OR, NOT), and other search techniques. 
• Record and document your search strategy for transparency and replicability. 
• Keep track of the articles, including publication details, abstracts, and links. Use citation management tools like EndNote, Zotero, or Mendeley to organize your references. 

Review the Literature:

• Evaluate the relevance and quality of each source. Consider the methodology, sample size, and results of studies. 
• Organize the literature by themes or key concepts. Identify patterns, trends, and gaps in the existing research. 
• Summarize key findings and arguments from each source. Compare and contrast different perspectives. 
• Identify areas where there is a consensus in the literature and where there are conflicting opinions. 
• Provide critical analysis and synthesis of the literature. What are the strengths and weaknesses of existing research? 

Organize and Write Your Literature Review:

• Literature review outline should be based on themes, chronological order, or methodological approaches. 
• Write a clear and coherent narrative that synthesizes the information gathered. 
• Use proper citations for each source and ensure consistency in your citation style (APA, MLA, Chicago, etc.). 
• Conclude your literature review by summarizing key findings, identifying gaps, and suggesting areas for future research. 

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How to write a literature review faster with Paperpal?

Paperpal, an AI writing assistant, integrates powerful academic search capabilities within its writing platform. With the Research feature, you get 100% factual insights, with citations backed by 250M+ verified research articles, directly within your writing interface with the option to save relevant references in your Citation Library. By eliminating the need to switch tabs to find answers to all your research questions, Paperpal saves time and helps you stay focused on your writing.   

Here’s how to use the Research feature:  

• Ask a question: Get started with a new document on paperpal.com. Click on the “Research” feature and type your question in plain English. Paperpal will scour over 250 million research articles, including conference papers and preprints, to provide you with accurate insights and citations. 
• Review and Save: Paperpal summarizes the information, while citing sources and listing relevant reads. You can quickly scan the results to identify relevant references and save these directly to your built-in citations library for later access. 
• Cite with Confidence: Paperpal makes it easy to incorporate relevant citations and references into your writing, ensuring your arguments are well-supported by credible sources. This translates to a polished, well-researched literature review. 

The literature review sample and detailed advice on writing and conducting a review will help you produce a well-structured report. But remember that a good literature review is an ongoing process, and it may be necessary to revisit and update it as your research progresses. By combining effortless research with an easy citation process, Paperpal Research streamlines the literature review process and empowers you to write faster and with more confidence. Try Paperpal Research now and see for yourself.  

Frequently asked questions

A literature review is a critical and comprehensive analysis of existing literature (published and unpublished works) on a specific topic or research question and provides a synthesis of the current state of knowledge in a particular field. A well-conducted literature review is crucial for researchers to build upon existing knowledge, avoid duplication of efforts, and contribute to the advancement of their field. It also helps researchers situate their work within a broader context and facilitates the development of a sound theoretical and conceptual framework for their studies.

Literature review is a crucial component of research writing, providing a solid background for a research paper’s investigation. The aim is to keep professionals up to date by providing an understanding of ongoing developments within a specific field, including research methods, and experimental techniques used in that field, and present that knowledge in the form of a written report. Also, the depth and breadth of the literature review emphasizes the credibility of the scholar in his or her field.  

Before writing a literature review, it’s essential to undertake several preparatory steps to ensure that your review is well-researched, organized, and focused. This includes choosing a topic of general interest to you and doing exploratory research on that topic, writing an annotated bibliography, and noting major points, especially those that relate to the position you have taken on the topic. 

Literature reviews and academic research papers are essential components of scholarly work but serve different purposes within the academic realm. 3 A literature review aims to provide a foundation for understanding the current state of research on a particular topic, identify gaps or controversies, and lay the groundwork for future research. Therefore, it draws heavily from existing academic sources, including books, journal articles, and other scholarly publications. In contrast, an academic research paper aims to present new knowledge, contribute to the academic discourse, and advance the understanding of a specific research question. Therefore, it involves a mix of existing literature (in the introduction and literature review sections) and original data or findings obtained through research methods. 

Literature reviews are essential components of academic and research papers, and various strategies can be employed to conduct them effectively. If you want to know how to write a literature review for a research paper, here are four common approaches that are often used by researchers.  Chronological Review: This strategy involves organizing the literature based on the chronological order of publication. It helps to trace the development of a topic over time, showing how ideas, theories, and research have evolved.  Thematic Review: Thematic reviews focus on identifying and analyzing themes or topics that cut across different studies. Instead of organizing the literature chronologically, it is grouped by key themes or concepts, allowing for a comprehensive exploration of various aspects of the topic.  Methodological Review: This strategy involves organizing the literature based on the research methods employed in different studies. It helps to highlight the strengths and weaknesses of various methodologies and allows the reader to evaluate the reliability and validity of the research findings.  Theoretical Review: A theoretical review examines the literature based on the theoretical frameworks used in different studies. This approach helps to identify the key theories that have been applied to the topic and assess their contributions to the understanding of the subject.  It’s important to note that these strategies are not mutually exclusive, and a literature review may combine elements of more than one approach. The choice of strategy depends on the research question, the nature of the literature available, and the goals of the review. Additionally, other strategies, such as integrative reviews or systematic reviews, may be employed depending on the specific requirements of the research.

The literature review format can vary depending on the specific publication guidelines. However, there are some common elements and structures that are often followed. Here is a general guideline for the format of a literature review:  Introduction:   Provide an overview of the topic.  Define the scope and purpose of the literature review.  State the research question or objective.  Body:   Organize the literature by themes, concepts, or chronology.  Critically analyze and evaluate each source.  Discuss the strengths and weaknesses of the studies.  Highlight any methodological limitations or biases.  Identify patterns, connections, or contradictions in the existing research.  Conclusion:   Summarize the key points discussed in the literature review.  Highlight the research gap.  Address the research question or objective stated in the introduction.  Highlight the contributions of the review and suggest directions for future research.

Both annotated bibliographies and literature reviews involve the examination of scholarly sources. While annotated bibliographies focus on individual sources with brief annotations, literature reviews provide a more in-depth, integrated, and comprehensive analysis of existing literature on a specific topic. The key differences are as follows: 

References 

• Denney, A. S., & Tewksbury, R. (2013). How to write a literature review.  Journal of criminal justice education ,  24 (2), 218-234. 
• Pan, M. L. (2016).  Preparing literature reviews: Qualitative and quantitative approaches . Taylor & Francis. 
• Cantero, C. (2019). How to write a literature review.  San José State University Writing Center . 

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What Is A Literature Review?

A plain-language explainer (with examples).

By:  Derek Jansen (MBA) & Kerryn Warren (PhD) | June 2020 (Updated May 2023)

If you’re faced with writing a dissertation or thesis, chances are you’ve encountered the term “literature review” . If you’re on this page, you’re probably not 100% what the literature review is all about. The good news is that you’ve come to the right place.

Literature Review 101

• What (exactly) is a literature review
• What’s the purpose of the literature review chapter
• How to find high-quality resources
• How to structure your literature review chapter
• Example of an actual literature review

What is a literature review?

The word “literature review” can refer to two related things that are part of the broader literature review process. The first is the task of  reviewing the literature  – i.e. sourcing and reading through the existing research relating to your research topic. The second is the  actual chapter  that you write up in your dissertation, thesis or research project. Let’s look at each of them:

Reviewing the literature

The first step of any literature review is to hunt down and  read through the existing research  that’s relevant to your research topic. To do this, you’ll use a combination of tools (we’ll discuss some of these later) to find journal articles, books, ebooks, research reports, dissertations, theses and any other credible sources of information that relate to your topic. You’ll then  summarise and catalogue these  for easy reference when you write up your literature review chapter. 

The literature review chapter

The second step of the literature review is to write the actual literature review chapter (this is usually the second chapter in a typical dissertation or thesis structure ). At the simplest level, the literature review chapter is an  overview of the key literature  that’s relevant to your research topic. This chapter should provide a smooth-flowing discussion of what research has already been done, what is known, what is unknown and what is contested in relation to your research topic. So, you can think of it as an  integrated review of the state of knowledge  around your research topic. 

What’s the purpose of a literature review?

The literature review chapter has a few important functions within your dissertation, thesis or research project. Let’s take a look at these:

Purpose #1 – Demonstrate your topic knowledge

The first function of the literature review chapter is, quite simply, to show the reader (or marker) that you  know what you’re talking about . In other words, a good literature review chapter demonstrates that you’ve read the relevant existing research and understand what’s going on – who’s said what, what’s agreed upon, disagreed upon and so on. This needs to be  more than just a summary  of who said what – it needs to integrate the existing research to  show how it all fits together  and what’s missing (which leads us to purpose #2, next). 

Purpose #2 – Reveal the research gap that you’ll fill

The second function of the literature review chapter is to  show what’s currently missing  from the existing research, to lay the foundation for your own research topic. In other words, your literature review chapter needs to show that there are currently “missing pieces” in terms of the bigger puzzle, and that  your study will fill one of those research gaps . By doing this, you are showing that your research topic is original and will help contribute to the body of knowledge. In other words, the literature review helps justify your research topic.  

Purpose #3 – Lay the foundation for your conceptual framework

The third function of the literature review is to form the  basis for a conceptual framework . Not every research topic will necessarily have a conceptual framework, but if your topic does require one, it needs to be rooted in your literature review. 

For example, let’s say your research aims to identify the drivers of a certain outcome – the factors which contribute to burnout in office workers. In this case, you’d likely develop a conceptual framework which details the potential factors (e.g. long hours, excessive stress, etc), as well as the outcome (burnout). Those factors would need to emerge from the literature review chapter – they can’t just come from your gut! 

So, in this case, the literature review chapter would uncover each of the potential factors (based on previous studies about burnout), which would then be modelled into a framework. 

Purpose #4 – To inform your methodology

The fourth function of the literature review is to  inform the choice of methodology  for your own research. As we’ve  discussed on the Grad Coach blog , your choice of methodology will be heavily influenced by your research aims, objectives and questions . Given that you’ll be reviewing studies covering a topic close to yours, it makes sense that you could learn a lot from their (well-considered) methodologies.

So, when you’re reviewing the literature, you’ll need to  pay close attention to the research design , methodology and methods used in similar studies, and use these to inform your methodology. Quite often, you’ll be able to  “borrow” from previous studies . This is especially true for quantitative studies , as you can use previously tried and tested measures and scales. 

How do I find articles for my literature review?

Finding quality journal articles is essential to crafting a rock-solid literature review. As you probably already know, not all research is created equally, and so you need to make sure that your literature review is  built on credible research . 

We could write an entire post on how to find quality literature (actually, we have ), but a good starting point is Google Scholar . Google Scholar is essentially the academic equivalent of Google, using Google’s powerful search capabilities to find relevant journal articles and reports. It certainly doesn’t cover every possible resource, but it’s a very useful way to get started on your literature review journey, as it will very quickly give you a good indication of what the  most popular pieces of research  are in your field.

One downside of Google Scholar is that it’s merely a search engine – that is, it lists the articles, but oftentimes  it doesn’t host the articles . So you’ll often hit a paywall when clicking through to journal websites. 

Thankfully, your university should provide you with access to their library, so you can find the article titles using Google Scholar and then search for them by name in your university’s online library. Your university may also provide you with access to  ResearchGate , which is another great source for existing research. 

Remember, the correct search keywords will be super important to get the right information from the start. So, pay close attention to the keywords used in the journal articles you read and use those keywords to search for more articles. If you can’t find a spoon in the kitchen, you haven’t looked in the right drawer. 

Need a helping hand?

How should I structure my literature review?

Unfortunately, there’s no generic universal answer for this one. The structure of your literature review will depend largely on your topic area and your research aims and objectives.

You could potentially structure your literature review chapter according to theme, group, variables , chronologically or per concepts in your field of research. We explain the main approaches to structuring your literature review here . You can also download a copy of our free literature review template to help you establish an initial structure.

In general, it’s also a good idea to start wide (i.e. the big-picture-level) and then narrow down, ending your literature review close to your research questions . However, there’s no universal one “right way” to structure your literature review. The most important thing is not to discuss your sources one after the other like a list – as we touched on earlier, your literature review needs to synthesise the research , not summarise it .

Ultimately, you need to craft your literature review so that it conveys the most important information effectively – it needs to tell a logical story in a digestible way. It’s no use starting off with highly technical terms and then only explaining what these terms mean later. Always assume your reader is not a subject matter expert and hold their hand through a journe y of the literature while keeping the functions of the literature review chapter (which we discussed earlier) front of mind.

Example of a literature review

In the video below, we walk you through a high-quality literature review from a dissertation that earned full distinction. This will give you a clearer view of what a strong literature review looks like in practice and hopefully provide some inspiration for your own. 

Wrapping Up

In this post, we’ve (hopefully) answered the question, “ what is a literature review? “. We’ve also considered the purpose and functions of the literature review, as well as how to find literature and how to structure the literature review chapter. If you’re keen to learn more, check out the literature review section of the Grad Coach blog , as well as our detailed video post covering how to write a literature review . 

Psst… there’s more!

This post is an extract from our bestselling short course, Literature Review Bootcamp . If you want to work smart, you don't want to miss this .

16 Comments

Thanks for this review. It narrates what’s not been taught as tutors are always in a early to finish their classes.

Thanks for the kind words, Becky. Good luck with your literature review 🙂

This website is amazing, it really helps break everything down. Thank you, I would have been lost without it.

This is review is amazing. I benefited from it a lot and hope others visiting this website will benefit too.

Timothy T. Chol [email protected]

Thank you very much for the guiding in literature review I learn and benefited a lot this make my journey smooth I’ll recommend this site to my friends

This was so useful. Thank you so much.

Hi, Concept was explained nicely by both of you. Thanks a lot for sharing it. It will surely help research scholars to start their Research Journey.

The review is really helpful to me especially during this period of covid-19 pandemic when most universities in my country only offer online classes. Great stuff

Great Brief Explanation, thanks

So helpful to me as a student

GradCoach is a fantastic site with brilliant and modern minds behind it.. I spent weeks decoding the substantial academic Jargon and grounding my initial steps on the research process, which could be shortened to a couple of days through the Gradcoach. Thanks again!

This is an amazing talk. I paved way for myself as a researcher. Thank you GradCoach!

Well-presented overview of the literature!

This was brilliant. So clear. Thank you

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Literature review.

• What is a Literature Review?
• What is Its Purpose?
• 1. Select a Topic
• 2. Set the Topic in Context
• 3. Types of Information Sources
• 4. Use Information Sources
• 5. Get the Information
• 6. Organize / Manage the Information
• 7. Position the Literature Review
• 8. Write the Literature Review

A literature review is a comprehensive summary of previous research on a topic. The literature review surveys scholarly articles, books, and other sources relevant to a particular area of research.  The review should enumerate, describe, summarize, objectively evaluate and clarify this previous research.  It should give a theoretical base for the research and help you (the author) determine the nature of your research.  The literature review acknowledges the work of previous researchers, and in so doing, assures the reader that your work has been well conceived.  It is assumed that by mentioning a previous work in the field of study, that the author has read, evaluated, and assimiliated that work into the work at hand.

A literature review creates a "landscape" for the reader, giving her or him a full understanding of the developments in the field.  This landscape informs the reader that the author has indeed assimilated all (or the vast majority of) previous, significant works in the field into her or his research. 

 "In writing the literature review, the purpose is to convey to the reader what knowledge and ideas have been established on a topic, and what their strengths and weaknesses are. The literature review must be defined by a guiding concept (eg. your research objective, the problem or issue you are discussing, or your argumentative thesis). It is not just a descriptive list of the material available, or a set of summaries.( http://www.writing.utoronto.ca/advice/specific-types-of-writing/literature-review )

Recommended Reading

• Next: What is Its Purpose? >>
• Last Updated: Oct 2, 2023 12:34 PM

• University of Texas Libraries

Literature Reviews

Steps in the literature review process.

• What is a literature review?
• Define your research question
• Determine inclusion and exclusion criteria
• Choose databases and search
• Review Results
• Synthesize Results
• Analyze Results
• Librarian Support
• Artificial Intelligence (AI) Tools
• You may need to some exploratory searching of the literature to get a sense of scope, to determine whether you need to narrow or broaden your focus
• Identify databases that provide the most relevant sources, and identify relevant terms (controlled vocabularies) to add to your search strategy
• Finalize your research question
• Think about relevant dates, geographies (and languages), methods, and conflicting points of view
• Conduct searches in the published literature via the identified databases
• Check to see if this topic has been covered in other discipline's databases
• Examine the citations of on-point articles for keywords, authors, and previous research (via references) and cited reference searching.
• Save your search results in a citation management tool (such as Zotero, Mendeley or EndNote)
• De-duplicate your search results
• Make sure that you've found the seminal pieces -- they have been cited many times, and their work is considered foundational 
• Check with your professor or a librarian to make sure your search has been comprehensive
• Evaluate the strengths and weaknesses of individual sources and evaluate for bias, methodologies, and thoroughness
• Group your results in to an organizational structure that will support why your research needs to be done, or that provides the answer to your research question  
• Develop your conclusions
• Are there gaps in the literature?
• Where has significant research taken place, and who has done it?
• Is there consensus or debate on this topic?
• Which methodological approaches work best?
• For example: Background, Current Practices, Critics and Proponents, Where/How this study will fit in 
• Organize your citations and focus on your research question and pertinent studies
• Compile your bibliography

Note: The first four steps are the best points at which to contact a librarian. Your librarian can help you determine the best databases to use for your topic, assess scope, and formulate a search strategy.

Videos Tutorials about Literature Reviews

This 4.5 minute video from Academic Education Materials has a Creative Commons License and a British narrator.

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• Last Updated: Aug 22, 2024 9:12 AM
• URL: https://guides.lib.utexas.edu/literaturereviews

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Ten Simple Rules for Writing a Literature Review

Marco pautasso.

1 Centre for Functional and Evolutionary Ecology (CEFE), CNRS, Montpellier, France

2 Centre for Biodiversity Synthesis and Analysis (CESAB), FRB, Aix-en-Provence, France

Literature reviews are in great demand in most scientific fields. Their need stems from the ever-increasing output of scientific publications [1] . For example, compared to 1991, in 2008 three, eight, and forty times more papers were indexed in Web of Science on malaria, obesity, and biodiversity, respectively [2] . Given such mountains of papers, scientists cannot be expected to examine in detail every single new paper relevant to their interests [3] . Thus, it is both advantageous and necessary to rely on regular summaries of the recent literature. Although recognition for scientists mainly comes from primary research, timely literature reviews can lead to new synthetic insights and are often widely read [4] . For such summaries to be useful, however, they need to be compiled in a professional way [5] .

When starting from scratch, reviewing the literature can require a titanic amount of work. That is why researchers who have spent their career working on a certain research issue are in a perfect position to review that literature. Some graduate schools are now offering courses in reviewing the literature, given that most research students start their project by producing an overview of what has already been done on their research issue [6] . However, it is likely that most scientists have not thought in detail about how to approach and carry out a literature review.

Reviewing the literature requires the ability to juggle multiple tasks, from finding and evaluating relevant material to synthesising information from various sources, from critical thinking to paraphrasing, evaluating, and citation skills [7] . In this contribution, I share ten simple rules I learned working on about 25 literature reviews as a PhD and postdoctoral student. Ideas and insights also come from discussions with coauthors and colleagues, as well as feedback from reviewers and editors.

Rule 1: Define a Topic and Audience

How to choose which topic to review? There are so many issues in contemporary science that you could spend a lifetime of attending conferences and reading the literature just pondering what to review. On the one hand, if you take several years to choose, several other people may have had the same idea in the meantime. On the other hand, only a well-considered topic is likely to lead to a brilliant literature review [8] . The topic must at least be:

• interesting to you (ideally, you should have come across a series of recent papers related to your line of work that call for a critical summary),
• an important aspect of the field (so that many readers will be interested in the review and there will be enough material to write it), and
• a well-defined issue (otherwise you could potentially include thousands of publications, which would make the review unhelpful).

Ideas for potential reviews may come from papers providing lists of key research questions to be answered [9] , but also from serendipitous moments during desultory reading and discussions. In addition to choosing your topic, you should also select a target audience. In many cases, the topic (e.g., web services in computational biology) will automatically define an audience (e.g., computational biologists), but that same topic may also be of interest to neighbouring fields (e.g., computer science, biology, etc.).

Rule 2: Search and Re-search the Literature

After having chosen your topic and audience, start by checking the literature and downloading relevant papers. Five pieces of advice here:

• keep track of the search items you use (so that your search can be replicated [10] ),
• keep a list of papers whose pdfs you cannot access immediately (so as to retrieve them later with alternative strategies),
• use a paper management system (e.g., Mendeley, Papers, Qiqqa, Sente),
• define early in the process some criteria for exclusion of irrelevant papers (these criteria can then be described in the review to help define its scope), and
• do not just look for research papers in the area you wish to review, but also seek previous reviews.

The chances are high that someone will already have published a literature review ( Figure 1 ), if not exactly on the issue you are planning to tackle, at least on a related topic. If there are already a few or several reviews of the literature on your issue, my advice is not to give up, but to carry on with your own literature review,

The bottom-right situation (many literature reviews but few research papers) is not just a theoretical situation; it applies, for example, to the study of the impacts of climate change on plant diseases, where there appear to be more literature reviews than research studies [33] .

• discussing in your review the approaches, limitations, and conclusions of past reviews,
• trying to find a new angle that has not been covered adequately in the previous reviews, and
• incorporating new material that has inevitably accumulated since their appearance.

When searching the literature for pertinent papers and reviews, the usual rules apply:

• be thorough,
• use different keywords and database sources (e.g., DBLP, Google Scholar, ISI Proceedings, JSTOR Search, Medline, Scopus, Web of Science), and
• look at who has cited past relevant papers and book chapters.

Rule 3: Take Notes While Reading

If you read the papers first, and only afterwards start writing the review, you will need a very good memory to remember who wrote what, and what your impressions and associations were while reading each single paper. My advice is, while reading, to start writing down interesting pieces of information, insights about how to organize the review, and thoughts on what to write. This way, by the time you have read the literature you selected, you will already have a rough draft of the review.

Of course, this draft will still need much rewriting, restructuring, and rethinking to obtain a text with a coherent argument [11] , but you will have avoided the danger posed by staring at a blank document. Be careful when taking notes to use quotation marks if you are provisionally copying verbatim from the literature. It is advisable then to reformulate such quotes with your own words in the final draft. It is important to be careful in noting the references already at this stage, so as to avoid misattributions. Using referencing software from the very beginning of your endeavour will save you time.

Rule 4: Choose the Type of Review You Wish to Write

After having taken notes while reading the literature, you will have a rough idea of the amount of material available for the review. This is probably a good time to decide whether to go for a mini- or a full review. Some journals are now favouring the publication of rather short reviews focusing on the last few years, with a limit on the number of words and citations. A mini-review is not necessarily a minor review: it may well attract more attention from busy readers, although it will inevitably simplify some issues and leave out some relevant material due to space limitations. A full review will have the advantage of more freedom to cover in detail the complexities of a particular scientific development, but may then be left in the pile of the very important papers “to be read” by readers with little time to spare for major monographs.

There is probably a continuum between mini- and full reviews. The same point applies to the dichotomy of descriptive vs. integrative reviews. While descriptive reviews focus on the methodology, findings, and interpretation of each reviewed study, integrative reviews attempt to find common ideas and concepts from the reviewed material [12] . A similar distinction exists between narrative and systematic reviews: while narrative reviews are qualitative, systematic reviews attempt to test a hypothesis based on the published evidence, which is gathered using a predefined protocol to reduce bias [13] , [14] . When systematic reviews analyse quantitative results in a quantitative way, they become meta-analyses. The choice between different review types will have to be made on a case-by-case basis, depending not just on the nature of the material found and the preferences of the target journal(s), but also on the time available to write the review and the number of coauthors [15] .

Rule 5: Keep the Review Focused, but Make It of Broad Interest

Whether your plan is to write a mini- or a full review, it is good advice to keep it focused 16 , 17 . Including material just for the sake of it can easily lead to reviews that are trying to do too many things at once. The need to keep a review focused can be problematic for interdisciplinary reviews, where the aim is to bridge the gap between fields [18] . If you are writing a review on, for example, how epidemiological approaches are used in modelling the spread of ideas, you may be inclined to include material from both parent fields, epidemiology and the study of cultural diffusion. This may be necessary to some extent, but in this case a focused review would only deal in detail with those studies at the interface between epidemiology and the spread of ideas.

While focus is an important feature of a successful review, this requirement has to be balanced with the need to make the review relevant to a broad audience. This square may be circled by discussing the wider implications of the reviewed topic for other disciplines.

Rule 6: Be Critical and Consistent

Reviewing the literature is not stamp collecting. A good review does not just summarize the literature, but discusses it critically, identifies methodological problems, and points out research gaps [19] . After having read a review of the literature, a reader should have a rough idea of:

• the major achievements in the reviewed field,
• the main areas of debate, and
• the outstanding research questions.

It is challenging to achieve a successful review on all these fronts. A solution can be to involve a set of complementary coauthors: some people are excellent at mapping what has been achieved, some others are very good at identifying dark clouds on the horizon, and some have instead a knack at predicting where solutions are going to come from. If your journal club has exactly this sort of team, then you should definitely write a review of the literature! In addition to critical thinking, a literature review needs consistency, for example in the choice of passive vs. active voice and present vs. past tense.

Rule 7: Find a Logical Structure

Like a well-baked cake, a good review has a number of telling features: it is worth the reader's time, timely, systematic, well written, focused, and critical. It also needs a good structure. With reviews, the usual subdivision of research papers into introduction, methods, results, and discussion does not work or is rarely used. However, a general introduction of the context and, toward the end, a recapitulation of the main points covered and take-home messages make sense also in the case of reviews. For systematic reviews, there is a trend towards including information about how the literature was searched (database, keywords, time limits) [20] .

How can you organize the flow of the main body of the review so that the reader will be drawn into and guided through it? It is generally helpful to draw a conceptual scheme of the review, e.g., with mind-mapping techniques. Such diagrams can help recognize a logical way to order and link the various sections of a review [21] . This is the case not just at the writing stage, but also for readers if the diagram is included in the review as a figure. A careful selection of diagrams and figures relevant to the reviewed topic can be very helpful to structure the text too [22] .

Rule 8: Make Use of Feedback

Reviews of the literature are normally peer-reviewed in the same way as research papers, and rightly so [23] . As a rule, incorporating feedback from reviewers greatly helps improve a review draft. Having read the review with a fresh mind, reviewers may spot inaccuracies, inconsistencies, and ambiguities that had not been noticed by the writers due to rereading the typescript too many times. It is however advisable to reread the draft one more time before submission, as a last-minute correction of typos, leaps, and muddled sentences may enable the reviewers to focus on providing advice on the content rather than the form.

Feedback is vital to writing a good review, and should be sought from a variety of colleagues, so as to obtain a diversity of views on the draft. This may lead in some cases to conflicting views on the merits of the paper, and on how to improve it, but such a situation is better than the absence of feedback. A diversity of feedback perspectives on a literature review can help identify where the consensus view stands in the landscape of the current scientific understanding of an issue [24] .

Rule 9: Include Your Own Relevant Research, but Be Objective

In many cases, reviewers of the literature will have published studies relevant to the review they are writing. This could create a conflict of interest: how can reviewers report objectively on their own work [25] ? Some scientists may be overly enthusiastic about what they have published, and thus risk giving too much importance to their own findings in the review. However, bias could also occur in the other direction: some scientists may be unduly dismissive of their own achievements, so that they will tend to downplay their contribution (if any) to a field when reviewing it.

In general, a review of the literature should neither be a public relations brochure nor an exercise in competitive self-denial. If a reviewer is up to the job of producing a well-organized and methodical review, which flows well and provides a service to the readership, then it should be possible to be objective in reviewing one's own relevant findings. In reviews written by multiple authors, this may be achieved by assigning the review of the results of a coauthor to different coauthors.

Rule 10: Be Up-to-Date, but Do Not Forget Older Studies

Given the progressive acceleration in the publication of scientific papers, today's reviews of the literature need awareness not just of the overall direction and achievements of a field of inquiry, but also of the latest studies, so as not to become out-of-date before they have been published. Ideally, a literature review should not identify as a major research gap an issue that has just been addressed in a series of papers in press (the same applies, of course, to older, overlooked studies (“sleeping beauties” [26] )). This implies that literature reviewers would do well to keep an eye on electronic lists of papers in press, given that it can take months before these appear in scientific databases. Some reviews declare that they have scanned the literature up to a certain point in time, but given that peer review can be a rather lengthy process, a full search for newly appeared literature at the revision stage may be worthwhile. Assessing the contribution of papers that have just appeared is particularly challenging, because there is little perspective with which to gauge their significance and impact on further research and society.

Inevitably, new papers on the reviewed topic (including independently written literature reviews) will appear from all quarters after the review has been published, so that there may soon be the need for an updated review. But this is the nature of science [27] – [32] . I wish everybody good luck with writing a review of the literature.

Acknowledgments

Many thanks to M. Barbosa, K. Dehnen-Schmutz, T. Döring, D. Fontaneto, M. Garbelotto, O. Holdenrieder, M. Jeger, D. Lonsdale, A. MacLeod, P. Mills, M. Moslonka-Lefebvre, G. Stancanelli, P. Weisberg, and X. Xu for insights and discussions, and to P. Bourne, T. Matoni, and D. Smith for helpful comments on a previous draft.

Funding Statement

This work was funded by the French Foundation for Research on Biodiversity (FRB) through its Centre for Synthesis and Analysis of Biodiversity data (CESAB), as part of the NETSEED research project. The funders had no role in the preparation of the manuscript.

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Literature Review for Grad Students in Education

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Introduction to Literature Review

If you cannot access the above video, you can watch it here

What is a Literature Review

  The purpose of an academic research paper is to express and document an original idea. Literature Review is one part of that process of writing a research paper. In a research paper, you use the literature as a starting point, a building block and as evidence of a new insight. The goal of the literature review is only to summarize and synthesize the arguments and ideas of others. You should not present your original idea.

The reading that you do as part of a literature review will answer one of two questions:

“What do we know about the subject of our study?” “Based on what we know, what conclusions can we draw about the research question?”

Notice that the conclusions to be drawn are about the research question , as opposed to a novel theory. 

The types of conclusions about your research question that you want to discover are: ❖ gaps in the knowledge on a subject area ❖ questions about your topic that remain unanswered ❖ areas of disagreement in your subject area that need to be settled.

Purpose of Literature Review?

There are a number of differing descriptions of the purpose of a literature review. Primarily it is a tool for

❖ researching the history of scholarly publication on a topic

❖ becoming aware of the scholarly debate within a topic

❖  a summary or restatement of conclusions from research which has been published

❖ synthesis or recombining, comparing and contrasting, the ideas of others.

❖ evaluate sources

❖ search for gaps

A literature review provides a comprehensive overview of a topic , supporting the fundamental purpose of a research paper, which is to present a new point of view or insight on a topic. The literature review supports the new insight. It does not present or argue for it.

Structure of Literature Review

• Choose a topic
• Find research
• Organize sources/notetaking
• Evaluate Sources
• Synthesize: think of this phase as a narrative . 

There are various ways of organizing the literature review process- if one of these seems closer to your purpose, try it out.

Different Types of Literature Sources

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Conduct a literature review

What is a literature review.

A literature review is a summary of the published work in a field of study. This can be a section of a larger paper or article, or can be the focus of an entire paper. Literature reviews show that you have examined the breadth of knowledge and can justify your thesis or research questions. They are also valuable tools for other researchers who need to find a summary of that field of knowledge.

Unlike an annotated bibliography, which is a list of sources with short descriptions, a literature review synthesizes sources into a summary that has a thesis or statement of purpose—stated or implied—at its core.

How do I write a literature review?

Step 1: define your research scope.

• What is the specific research question that your literature review helps to define?
• Are there a maximum or minimum number of sources that your review should include?

Ask us if you have questions about refining your topic, search methods, writing tips, or citation management.

Step 2: Identify the literature

Start by searching broadly. Literature for your review will typically be acquired through scholarly books, journal articles, and/or dissertations. Develop an understanding of what is out there, what terms are accurate and helpful, etc., and keep track of all of it with citation management tools . If you need help figuring out key terms and where to search, ask us .

Use citation searching to track how scholars interact with, and build upon, previous research:

• Mine the references cited section of each relevant source for additional key sources
• Use Google Scholar or Scopus to find other sources that have cited a particular work

Step 3: Critically analyze the literature

Key to your literature review is a critical analysis of the literature collected around your topic. The analysis will explore relationships, major themes, and any critical gaps in the research expressed in the work. Read and summarize each source with an eye toward analyzing authority, currency, coverage, methodology, and relationship to other works. The University of Toronto's Writing Center provides a comprehensive list of questions you can use to analyze your sources.

Step 4: Categorize your resources

Divide the available resources that pertain to your research into categories reflecting their roles in addressing your research question. Possible ways to categorize resources include organization by:

• methodology
• theoretical/philosophical approach

Regardless of the division, each category should be accompanied by thorough discussions and explanations of strengths and weaknesses, value to the overall survey, and comparisons with similar sources. You may have enough resources when:

• You've used multiple databases and other resources (web portals, repositories, etc.) to get a variety of perspectives on the research topic.
• The same citations are showing up in a variety of databases.

Additional resources

Undergraduate student resources.

• Literature Review Handout (University of North Carolina at Chapel Hill)
• Learn how to write a review of literature (University of Wisconsin-Madison)

Graduate student and faculty resources

• Information Research Strategies (University of Arizona)
• Literature Reviews: An Overview for Graduate Students (NC State University)
• Oliver, P. (2012). Succeeding with Your Literature Review: A Handbook for Students [ebook]
• Machi, L. A. & McEvoy, B. T. (2016). The Literature Review: Six Steps to Success [ebook]
• Graustein, J. S. (2012). How to Write an Exceptional Thesis or Dissertation: A Step-by-Step Guide from Proposal to Successful Defense [ebook]
• Thomas, R. M. & Brubaker, D. L. (2008). Theses and Dissertations: A Guide to Planning, Research, and Writing

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Literature Review versus Literature Survey. What is the difference?

I have read several articles about literature reviews. At the same time I found some guides about literature surveys . I am confused... how is a literature survey different from a literature review? What is the standard procedure to conduct a literature survey without making it a literature review?

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• 2 Welcome to Academia.SE. You have a couple of different questions in your post. We encourage multiple posts for multiple questions. See our tour and help center pages. Your questions about literature surveys and reviews are closely related and match the title. You should make a second post about how to pursue research given your background, since that it unrelated. –  Ben Norris Commented Dec 26, 2013 at 14:11

2 Answers 2

Reviewing the literature relevant to a given field is a standard part of doing research, as this serves to put your work into the context of the larger discipline in which you are working.

If there is an actual difference between the "literature survey" and the "literature review," it's that the latter can serve as a paper in and of itself, and is much more extensive than a literature survey, which is typically a major part of the introduction of a research paper.

The literature review as a standalone article could be compared to a "curated" overview of the literature in the field—who has done what, how do papers relate to one another, and what are the most important present and (possibly) future directions of work in such a field. Such papers can also be considerably longer than a traditional research paper, and some reviews might cite as many as a thousand references!

In comparison, the literature survey of a standard research article is usually much shorter (1-2 journal pages), and will not cite nearly as many papers (anywhere from 10 to 100, depending on the topic and the amount of relevant literature available).

• 2 Hi thanks for your comment. But I m still confused. I have seen survey papers are published and I have seen literature review sections in thesis. I mean aren't survey papers related to computer science are literature reviews ? –  Npn Commented Jan 1, 2014 at 14:51
• 3 In general, "review paper" is much more commonly used than "survey paper." Maybe CS prefers "survey paper," but essentially, there's no substantial difference between them. But every paper includes some sort of synopsis of existing literature; in a review or survey paper, it's the entire paper. –  aeismail Commented Jan 1, 2014 at 15:12
• Thanks ,I understood that review papers should be read to do a research. –  Npn Commented Jan 1, 2014 at 15:30

Well, I have written couple of survery/review articles published in prestigious journals here , here , and here and hence I think I can give you some hint on this question.

First View: One of the most important things to consider is that, these terms have been used differently in varied academic disciplines and even in some cases they are used interchangeably with negligible differences. Even in CS (my field), the way image processing scholars look at these terms may be different from networking researchers (I once experienced the comments I received from experts in image processing and realize how different they look at the works). So it might not be wrong if consider insignificant differences between these two terms.

What I describe here may be more applicable to CS. There are two different views at these terms that I describe here

Technically a feasible description around these two terms is that in survey works you should review the published papers and analyze, summarize, organize, and present findings in a novel way that can generate an original view to a certain aspect of the domain. For example, if researchers review the available research findings and conclude that electrical cars are emission-free vehicles, another researcher can review the same results and present an argument that building batteries themselves produce huge emission. The second contribution opens door for new research around emission-free production of car batteries. If we consider that survey paper is the result of literature survey, we can use the following definitions from CS journals.

• According to the definition of survey paper provided by IEEE Communications Surveys & Tutorials journal (one of the best CS journals), " The term survey, as applied here, is defined to mean a survey of the literature. A survey article should provide a comprehensive review of developments in a selected area ".
• In ACM Computing Survey (another prestigious CS journal), survey paper is described as “A paper that summarizes and organizes recent research results in a novel way that integrates and adds understanding to work in the field. A survey article emphasizes the classification of the existing literature, developing a perspective on the area, and evaluating trends.”
• In Elsevier journal of Computer Science Review, you will see here 4 that “Critical review of the relevant literature“ is required a component of every typical survey paper.

To summarize, these two terms can be distinguished using following notes (or maybe definitions)

Literature Survey: Is the process of analyzing, summarizing, organizing, and presenting novel conclusions from the results of technical review of large number of recently published scholarly articles. The results of the literature survey can contribute to the body of knowledge when peer-reviewed and published as survey articles

Literature Review: Is the process of technically and critically reviewing published papers to extract technical and scientific metadata from the presented contents. The metadata are usually used during literature survey to technically compare different but relevant works and draw conclusions on weaknesses and strengths of the works.

Second View: The second view over literature survey and review is that in survey, researchers usually utilize the author-provided contents available in the published works to qualitatively analyze and compare them with other related works. While in the former, you should not perform qualitative analysis. Rather it should be quantitative meaning that every research work under study should be implemented and benchmarked under certain criteria. The results of this benchmarking study can be used to compare them together and criticize or appreciate the works.

So basically you can look at current literature and find which approach is dominating in your field. Hope it helps. I try to revise it if I came a cross other points or useful comments here.

• 3 Up vote for Comprehensive answer. –  user3135645 Commented Dec 28, 2013 at 5:57
• 3 Nice answer (+1). I agree with you that the difference between the two terms is non-essential and preference in terminology depends mostly on the research discipline (field) and journal editors' preferences. Having said that, your distinction between the terms seems artificial, meaning that I don't see core logic that prevents applying both definitions to the opposite terms (unless I've missed some points). Also, I wanted to add that more accurate definitions should mention that literature survey or literature review is each both a process and an artifact , resulting from that process. –  Aleksandr Blekh Commented May 8, 2015 at 3:50

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LITERATURE REVIEW SOFTWARE FOR BETTER RESEARCH

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“It's nice to get a quick overview of related literature. Really easy to use, and it helps getting on top of the often complicated structures of referencing”

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“This has helped me so much in researching the literature. Currently, I am beginning to investigate new fields and this has helped me hugely”

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Canterbury University, NZ

“I can’t live without you anymore! I also recommend you to my students.”

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As a person who is an early researcher and identifies as dyslexic, I can say that having research articles laid out in the date vs cite graph format is much more approachable than looking at a standard database interface. I feel that the maps Litmaps offers lower the barrier of entry for researchers by giving them the connections between articles spaced out visually. This helps me orientate where a paper is in the history of a field. Thus, new researchers can look at one of Litmap's "seed maps" and have the same information as hours of digging through a database.

Baylor Fain

Postdoctoral Associate – University of Florida

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A Narrative Review of Literature Examining Studies Researching the Impact of Law on Health and Economic Outcomes

Affiliation.

• 1 Office of Policy, Performance, and Evaluation, Centers for Disease Control and Prevention, Atlanta, Georgia (Drs Pepin, St. Clair Sims, Khushalani, Kelly, Arifkhanova, Puddy, and Kaminski); Office of Public Health Law Services, National Center for State, Tribal, Local, and Territorial Public Health Infrastructure and Workforce, Centers for Disease Control and Prevention, Atlanta, Georgia (Dr Hulkower); and Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, Tennessee (Drs Tonti, Song, and Calhoun).
• PMID: 37797335
• PMCID: PMC10841287 (available on 2025-01-01 )
• DOI: 10.1097/PHH.0000000000001833

Context: Public health policy can play an important role in improving public health outcomes. Accordingly, there has been an increasing emphasis by policy makers on identifying and implementing evidence-informed public health policy interventions.

Program or policy: Growth and refinement of the field of research assessing the impact of legal interventions on health outcomes, known as legal epidemiology, prompted this review of studies on the relationship between laws and health or economic outcomes.

Implementation: Authors systematically searched 8 major literature databases for all English language journal articles that assessed the effect of a law on health and economic outcomes published between January 1, 2009, and September 18, 2019. This search generated 12 570 unique articles 177 of which met inclusion criteria. The team conducting the systematic review was a multidisciplinary team that included health economists and public health policy researchers, as well as public health lawyers with expertise in legal epidemiological research methods. The authors identified and assessed the types of methods used to measure the laws' health impact.

Evaluation: In this review, the authors examine how legal epidemiological research methods have been described in the literature as well as trends among the studies. Overall, 3 major themes emerged from this study: (1) limited variability in the sources of the health data across the studies, (2) limited differences in the methodological approaches used to connect law to health outcomes, and (3) lack of transparency surrounding the source and quality of the legal data relied upon.

Discussion: Through highlighting public health law research methodologies, this systematic review may inform researchers, practitioners, and lawmakers on how to better examine and understand the impacts of legal interventions on health and economic outcomes. Findings may serve as a source of suggested practices in conducting legal epidemiological outcomes research and identifying conceptual and method-related gaps in the literature.

Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.

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Conflict of interest statement

The authors have indicated that they have no potential conflicts of interest to disclose.

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Pediatric head injury guideline use in Sweden: a cross-sectional survey on determinants for successful implementation of a clinical practice guideline

• Fredrik Wickbom 1 , 2 ,
• William Berghog 1 ,
• Susanne Bernhardsson 3 , 4 , 5 ,
• Linda Persson 6 ,
• Stefan Kunkel 7 &
• Johan Undén 1 , 2  

BMC Health Services Research volume  24 , Article number:  965 ( 2024 ) Cite this article

27 Accesses

Metrics details

The Scandinavian Neurotrauma Committee guideline (SNC-16) was developed and published in 2016, to aid clinicians in management of pediatric head injuries in Scandinavian emergency departments (ED). The objective of this study was to explore determinants for use of the SNC-16 guideline by Swedish ED physicians.

This is a nationwide, cross-sectional, web-based survey in Sweden. Using modified snowball sampling, physicians managing children in the ED were invited via e-mail to complete the validated Clinician Guideline Determinants Questionnaire between February and May, 2023. Baseline data, data on enablers and barriers for use of the SNC-16 guideline, and preferred routes for implementation and access of guidelines in general were collected and analyzed descriptively and exploratory with Chi-square and Fisher's tests.

Of 595 invitations, 198 emergency physicians completed the survey (effective response rate 33.3%). There was a high reported use of the SNC-16 guideline (149/195; 76.4%) and a strong belief in its benefits for the patients (188/197; 95.4% agreement). Respondents generally agreed with the guideline's content (187/197; 94.9%) and found it easy to use and navigate (188/197; 95.4%). Some respondents (53/197; 26.9%) perceived a lack of organizational support needed to use the guideline. Implementation tools may be improved as only 58.9% (116/197) agreed that the guideline includes such. Only 37.6% (74/197) of the respondents agreed that the guideline clearly describes the underlying evidence supporting the recommendation. Most respondents prefer to consult colleagues (178/198; 89.9%) and guidelines (149/198; 75.3%) to gain knowledge to guide clinical decision making. Four types of enablers for guideline use emerged from free-text answers: ease of use and implementation, alignment with local guidelines and practice, advantages for stakeholders, and practicality and accessibility. Barriers for guideline use were manifested as: organizational challenges, medical concerns , and practical concerns.

Conclusions

The findings suggest high self-reported use of the SNC-16 guideline among Swedish ED physicians. In updated versions of the guideline, focus on improving implementation tools and descriptions of the underlying evidence may further facilitate adoption and adherence. Measures to improve organizational support for guideline use and involvement of patient representatives should also be considered.

Peer Review reports

Contributions to the literature

The pediatric Scandinavian Neurotrauma Committee head injury guideline from 2016 seems well known and well used by Swedish emergency department physicians, despite lack of formal implementation.

The study identified guideline implementation determinants that need to be addressed in both future guideline versions and in implementation strategies.

This study contributes reference data for the Clinician Guideline Determinants Questionnaire; a novel, validated tool for assessment of determinants for guideline use, with different results compared to previous reports utilizing the questionnaire.

Head trauma is a common cause to seek emergency department (ED) care among children in Sweden. In 2022, over 33,000 cases of head injury were registered in Sweden in children 0–17 years of age, according to the Swedish National Board of Health and Welfare [ 1 ]. Of these, 22.3% were diagnosed with an intracranial injury of varying severity (including concussion), yielding an overall incidence of 1521/100 000 patients with head injuries and an incidence of 340/100 000 patients with intracranial injury. Mild traumatic brain injury (mTBI) constitutes more than 80% of pediatric TBI cases globally [ 2 ]. Most of these injured children will recover without the need for acute intervention, e.g., neurosurgery or intensive care admission [ 2 , 3 , 4 , 5 ].

Cranial computed tomography (CT) utilizes ionizing radiation for imaging of the brain and is a valuable tool for excluding significant intracranial injuries, ordered in 4% of children with isolated head trauma in southern Sweden [ 6 ]. Radiation exposure in early life entails a risk of malignancy development later in life, and the selection of patients with mTBI for neuroimaging poses a clinical challenge [ 5 , 7 , 8 , 9 ]. Structured in-hospital observation is considered equally effective, although this is associated with higher resource use [ 10 , 11 ]. In Sweden (and similar to other countries), it is often junior physicians who initially manage these children, following a diverse range of local guidelines (or no guideline), resulting in an unstandardized approach to pediatric TBI on a national level [ 12 , 13 ].

The Scandinavian Neurotrauma Committee has recently developed a clinical practice guideline addressing the initial management of mTBI in children (SNC-16 guideline) in Scandinavia [ 14 ]. It was published in 2016 and has since then been passively disseminated into more than 50% of the Swedish emergency hospitals’ management routines [ 13 ]. Although validated in other settings, the SNC-16 guideline has not been validated in the Scandinavian population [ 15 , 16 ]. The SNC-16 guideline for managing patients with mTBI has been developed to help healthcare providers make informed management decisions. To assess the risk of intracranial injury, various factors such as clinical signs and symptoms (e.g., loss of consciousness, amnesia, neurological deficits) and current state of consciousness are considered in the guideline. If a patient's clinical status falls within the low-risk criteria, a CT scan or prolonged structured observation may be deemed unnecessary [ 14 ].

The process of clinically adapting research-based knowledge is widely acknowledged as intricate and non-self-regulating [ 17 , 18 , 19 ]. Clinical practice guidelines are considered valuable tools for integrating the latest medical evidence into clinical practice [ 20 , 21 ]. By identifying existing barriers and facilitators that influence the use of specific guidelines, it may be possible to tailor an implementation process and facilitate the uptake of a guideline into clinical settings and ensure adequate compliance [ 19 , 22 , 23 ].

In 2019, the Clinician Guideline Determinants Questionnaire (CGDQ) was developed and published by Gagliardi et al. [ 24 ]. This tool serves the purpose of providing a comprehensive and validated instrument for addressing factors relevant for the use or non-use of a specific guideline from a clinician's perspective. Knowledge about determinants for use and non-use specific for the SNC-16 guideline may support an implementation process and increase adherence to evidence-based practices in managing pediatric head trauma in Sweden. It may also give important information in future updates of the guideline.

The primary objective of this study was to identify barriers and enablers affecting use of the SNC-16 guideline by physicians in Sweden. Knowledge about these determinants is important as it allows development of tailored interventions in forthcoming implementation processes with the intention to promote uptake of research findings in routine care [ 24 ]. This study is part of a series of studies which embraces validation, development, and implementation of the SNC-16 guideline in Scandinavia.

Study design

This is a cross-sectional observational study in Sweden. Collection of data was performed using a validated questionnaire for implementation research [ 24 ]. Respondents were asked to assess the SNC-16 guideline based on the structured questions in the questionnaire. Reporting follows STROBE guidelines for cross-sectional studies (Additional file 1) [ 25 ]. An ethical advisory opinion was granted by the Swedish Ethical Review Authority (Dnr 2020 – 02 693).

The survey was sent to physicians in Swedish EDs of varying sizes nationwide, in which head trauma in pediatric patients is managed. Data were collected during February 23 to May 8, 2023.

Participants

Physicians from various medical specialties who regularly, at their own discretion, work in the ED of a Swedish hospital and assess pediatric acute head trauma, were included. Respondents not fulfilling the above criteria were excluded.

Potential participants were invited by an e-mail containing an information text and a link to the questionnaire. The initial e-mail recipient list of potential respondents was based on three different e-mail collection strategies: 1) a list of suggested respondents from a previous study, investigating management of pediatric TBI in Sweden at an organizational level [ 13 ]; 2) new e-mails to ED managers with a request to send us e-mail addresses to ED physicians working with pediatric mTBI in their ED (as the list from 2022 may contain irrelevant recipients or old e-mail addresses); and 3) screening of e-mail recipient lists accessible for our research team (identifying physicians in the department of general surgery in the Region of Halland, physicians in the department of emergency medicine in the Region of Halland and interns employed in the Region of Halland, Sweden). Only potential e-mail recipients suggested from a hospital that managed children with pediatric head trauma were included when extracting the e-mail list, drawn from the 66 hospitals included in the 2022 paper (370 e-mail addresses).

In summary, the final e-mail recipient list in the first block contained 502 unique e-mail addresses to potential respondents (Fig.  1 ). Non-responders were sent a total of five reminders during the time for data collection.

Flowchart describing structure for collection of the final data set

Before completing the survey, participants were asked to contribute with e-mail addresses to additional colleagues in their hospital or neighboring hospitals who they believed fulfilled the above inclusion criteria. Respondents not fulfilling the inclusion criteria were given the option to decline participation but still contribute with e-mail addresses to suitable colleagues. New e-mail addresses were added in blocks and generated in total five consecutive groups with new e-mail addresses to whom the survey was distributed. With this modified snowball sampling method, it was possible to control response rates. The study size was reached when no more new e-mail addresses were added by respondents with the snowball method, and no more non-respondents answered the survey despite multiple reminders. Respondents were pseudonymized at analysis and no patient data was recorded.

Respondents are by definition fluent in both Swedish and English as this is a criterion for admission to medical training in Swedish universities and hospitals. The medical literature in Sweden is also predominately in English.

The Clinician Guideline Determinants Questionnaire (CGDQ) was used for data collection [ 24 ]. It is a validated instrument for preparing and evaluating implementation of clinical practice guidelines. The CGDQ includes four sections exploring: 1) clinician demographic and background information; 2) attitudes to known determinants of guideline use; 3) open-ended items on additional determinants; and 4) a section examining preferred ways of distribution, access, and character of a guideline. The CGDQ was transcripted unchanged from the original version and presented in English in a digital questionnaire in the web-based survey system EsMaker (Entergate AB). As respondents have a high knowledge of the English language, we judged the risks associated with a translation of the questionnaire to Swedish greater than the risk that respondents would not understand the questions. Three questions exploring what size and type of hospital the respondent worked in, type of patients (children/adults/both) they managed, and their familiarity with assessing children with head injury were added to the background information section by the authors. The SNC-16 flow chart, a link to the original publication, and a link to an article in the Swedish medical journal Läkartidningen were presented at the beginning of the questionnaire [ 14 , 26 ]. The text “SNC-16 guideline” was inserted in the questionnaire where stated, “name guideline”. Some items have been truncated to improve readability in the results section of this paper, with a reference to the full questionnaire and complete items in Additional file 2.

To minimize the risk for introducing selection bias, purposive sampling was used to include respondents from varying parts of Sweden and from varying hospital sizes, and including both junior and senior physicians, when compiling the initial respondent mailing list.

Data analysis

Reported data are categorical nominal/dichotomous or categorical ordinal (on a 7-step Likert scale, including response option “not sure”), or in free text. Responses to categorical nominal items are summarized and presented as frequencies and percentages. Variables that are reported on an ordinal 7-step Likert scale were dichotomized into “disagree” if Likert response 1–4 or unsure, and into “agree” if Likert response 5–7. The unmerged response distribution is shown in Additional file 3. Results are presented for the four sections in the applied implementation tool (CGDQ). Merging of categories was performed if there were few responses in a response category.

Background data on respondents are presented descriptively for a) gender, b) career stage (as found most appropriate by the respondent), c) medical specialty, d) hospital category (local hospital, regional hospital, university hospital or children’s hospital – with local and regional merged as small hospitals and university and children’s as large), e) region in Sweden, f) managing only children or both children and adults, g) familiarity with assessing children with head injury (categorized as “daily” + “several times a week” = regularly; “1–3 times/month” = seldom; “5–10 times/year” + “1–4 times/year” + “less than once a year” = rarely), h) have participated in the development of one or more guidelines, i) belief in clinical benefit of guidelines, and j) actual use of SNC-16 guideline.

Frequencies and percentages for "agree” and “disagree” for determinants in Sect. 2 of the survey were calculated. The authors decided to perform further analysis on a subset of factors from the clinician and guideline specific determinants in Sect. 2, aiming to explore possible associations between determinants and background factors. The subset comprised six variables selected by the authors after reviewing initial results and considered most salient to grasp the respondent’s thoughts on the guideline and their knowledge about the relevant clinical condition, with the most clinically relevant imprint. Authors decided to not test all items as it would entail an unjustified risk for significant results by chance. Chi-square test, or Fisher’s exact test when appropriate, was used to assess associations.

The free-text responses obtained from questions 3.1 to 3.4 (additional file 2) were independently categorized into types of barriers and enablers by two of the authors (FW, WB) and then compiled in consensus.

The first invitation e-mail was sent on February 23, 2023. The final reminder was sent on April 20, 2023. Respondents suggested 93 additional unique potential respondents, resulting in invitations also sent to these individuals. In this group, 43 participants opened the e-mail and participated in the survey, yielding a response rate in the snowball sample group of 46.2%. The total response rate was 43.4% (258/595; opens and responds to request) with an effective response rate for analysable respondents of 33.3% (198/595) (Fig.  1 ).

Background information

The 198 responding physicians from 42 unique EDs had varying clinical experience, in a span from early career interns (14.1%; 28/198), mid-career residents (48.5%; 96/198), to late career consultants (37.4%; 74/198). The most common specialties represented were general surgery (52.0%; 103/198) and emergency medicine (31.8%; 63/198). A majority (82.3%; 163/198) of the respondents worked in small (local or regional hospitals) compared to 17.7% ( n  = 35) in large (university or children’s) hospitals. There was a high degree of familiarity with the SNC-16 guideline, as 84.3% (166/197) had “read all or some of the guideline on multiple occasions” and only 8.1% (16/197) were unaware of the guideline or “aware of the guideline but have not read it”. A high proportion (76.4%; 149/195) of respondents reported regular use of the SNC-16 guideline in their respective clinical settings, and almost all (95.4%; 188/197) believed that guideline use in general optimized healthcare delivery and outcomes (Table  1 ).

Determinants of guideline use

It was common among respondents to think that colleagues (77.8%; 154/198) expected them to use the SNC-16 guideline. Fewer believed that patients (12.1%; 24/198), managers/executives in their own organization (37.9%; 75/198), a monitoring agency (Swedish National Board of Health and Welfare: 15.7%; 31/198), the government (4.0%; 8/198), and/or the professional society (23.7%; 47/198) expected them to use the guideline.

The attitude towards use of the SNC-16 guideline was generally positive as 94.9% (187/197) agreed with the content of the guideline. Approximately one of four (26.9%; 53/197) disagreed to the statement “My organization provides support (leadership, resources, assistance, etc.) needed to use this guideline”. In statement Q2.25 and Q2.27, the respondents’ perceptions of the guideline’s consistency with available evidence and how clearly the guideline describes this underlying evidence as foundation for the recommendations was explored, and the uncertainty was relatively high for both statements (“Not sure”: 37.2%; 73/196, and 47.2%; 93/197 respectively) (Table  2 ).

Enablers and barriers

Four types of enablers for guideline use emerged from the compilation of the free-text responses: ease of use and implementation, alignment with local guidelines and practice, advantages for stakeholders, and practicality and accessibility. Barriers for guideline use were manifested as: organizational challenges, medical concerns , and practical concerns (Table  3 ).

This section provided participants an opportunity to share thoughts on other determinants that could enable or challenge their use of the guideline. Noteworthy examples of "Enablers" were suggestions to extend the formal implementation among nurses, aiming to achieve a widespread adherence and acceptance of the SNC-16 guideline within all categories of healthcare professionals managing these conditions. Regarding practical concerns, ease of accessibility, e.g. laminated plastic cards in the ED, online versions, simple and unambiguous instructions, were described as enabling use of the guideline. Additionally, the importance of including disseminated guidelines, such as the SNC-16 guideline, into official local guidelines and practices was highlighted. In a broader perspective, a suggestion to gather all relevant guidelines in a bundle of nationally endorsed clinical decision-making tools was also noted.

In contrast, the absence of official organizational endorsement, both on a local and national level, emerged as a potential barrier. A specific concern raised was the fact that many Swedish physicians use the Reaction Level Scale-85 (RLS-85) [ 27 ], as opposed to the Glasgow Coma Scale (GCS) [ 28 ] recommended in the SNC-16 guideline, for assessment of level of consciousness. This discord was suggested as a barrier to adopting the SNC-16 guideline rising from inexperience in using the GCS. Challenges related to organizational practices, such as the absence of observational units and ED overcrowding, were identified as barriers affecting guideline adherence, possibly instead increasing the use of CT scanning. Within the category of medical concerns , participants expressed concern about the risk of over-investigation, encompassing both excessive observation and CT scans, and that the guideline might result in decisions that contradict the clinical judgement of experienced physicians. Concerns about the lack of clinical validation and available evidence were also raised by the respondents. The "practical concerns" category was composed around issues of complexity of guideline, time constraints, and limited availability.

In summary, the free-text responses confirmed already reported key enablers and barriers. They also provided new suggestions regarding the value of interdisciplinary collaboration among healthcare professionals and the importance of organizational structures for guideline adherence.

Learning style

Most of the respondents reported a preference for consulting colleagues (89.9%; 178/198), guidelines (75.3%; 149/198), and the internet (65.2%; 129/198) to gain knowledge to guide their clinical decisions (Fig.  2 ). Educational meetings/conferences were the most popular way to learn about guidelines (78.3%; 155/198) (Fig.  3 ). No clear preference was apparent regarding the optimal format for distribution of guideline material (Fig.  4 ).

Key sources to guide clinical decision making. 198 respondents provided answers to the multiple-choice question (4.1 in additional file 2) about the usefulness of different sources when seeking support to guide clinical decision-making. *Other = Foamed (free open access medical education) and local guidelines ( n  = 2)

Preferred ways to learn about guidelines. A total of 198 respondents provided answers to this multiple-choice question (4.2 in additional file 2). *Other = Suggested national Swedish collection of guidelines, podcasts, official medical guideline database (“Internetmedicin”), educational lunch sessions, colleagues ( n  = 6)

Preferred formats for guidelines, guideline summaries, or guideline tools ( n  = 198, multiple choice)

Associations to demographic variables

Associations between background variables and a subset of determinants were explored in Table  4 . There were significant differences between respondents that managed pediatric head injuries regularly, seldom, or rarely in their view of whether following the SNC-16 guideline would improve care delivery (91%; 79/87 versus 94%; 90/96 versus 73%; 11/15) and their view on the support provided from their organization to enable them to use the guideline (73%; 63/86 versus 52%; 50/96 versus 47%; 7/15). Those respondents that believed that guidelines (in general) optimize healthcare delivery and outcomes also had a significantly higher belief in that following the SNC-16 guideline would improve delivered care. There were no significant differences regarding gender, career stage, specialty, size of hospital, location of the respondent’s hospital in Sweden, types of patients managed, or whether the respondent had experience in guideline development for the selected determinants.

This cross-sectional survey showed that reported regular use of the passively disseminated SNC-16 guideline for pediatric mTBI was high. The respondents also held a high belief in patient benefit if applying the guideline. Improvements in the reporting of the underlying evidence and appurtenant implementation tools were requested. Barriers, such as lack of organizational support and resources, emerged both in the qualitative and quantitative data. The conveyed perception of determinants for use of the SNC-16 guideline was generally homogenous among the respondents, and independent of varying grouping variables.

The high proportion of regular guideline use (76%) reported in this study is in contrast to other reports, with only 35% adhering to guidelines in a systematic review by Mickan et al. [ 29 ] and 43% of prenatal care physicians regularly using a hepatitis C virus screening guideline in a survey by Moore et al. [ 30 ]. In a recent report on management routines at an organizational level, 55% of Swedish hospitals based their local recommendation in part or fully on the SNC-16 guideline [ 13 ]. The reason for this seemingly successful non-facilitated dissemination of the SNC-16 guideline in Sweden is unclear, although some plausible causes can be hypothesized. There is a lack of alternative, validated guidelines in Scandinavia. Also, the guidelines were published in the most common national journal and on the most commonly used web tool for doctors [ 26 , 31 ]. Additionally, a recent, non-intervention multi-center study, validated a set of pediatric mTBI guidelines in the Scandinavian healthcare system [ 32 ].

Pathman et al. [ 33 ] developed a four-step model for “leakage” of guideline evidence, from awareness to final adherence, outlining the concept of progressive loss of research evidence from guideline publication to clinical practice. The drop-off, or “leakage”, in each step of the Pathman model was estimated to be 15% in the systematic review by Mickan et al. [ 29 ]. The first step, awareness of the SNC-16 guideline, is not explicitly measured in the CGDQ. The second step is agreement with the content. If assuming that “regular use” corresponds to adoption or adherence in the Pathman framework, the leakage in this study would be between 9.25% ( agreement to adoption to adherence ) and 18.5% ( agreement to adoption ). This may raise attention to a possible, although not ascertained, discrepancy worth some effort to address in future updates of the guideline, also when considering the design of an implementation strategy. There was, for example, an uncertainty among our respondents concerning the guideline’s consistency with available evidence, which may act as a barrier for adoption and adherence. The guideline format and layout were acknowledged as easy to navigate, with clear and unambiguous wording, which may on the other hand facilitate adoption and adherence and efforts to preserve it may be beneficial [ 17 ].

In pediatric guidelines for mTBI, there has been a successive development from dichotomous prediction models based on single assessments [ 34 , 35 ], to risk group stratification at several levels (three to five) at one single time-point [ 5 , 14 ], and more recently to multiple risk groups and assessments at several time-points under observation in ED [ 36 ]. Whether the ambition to increase diagnostic accuracy via increasingly complicated flow chart structures will, at some point, limit the accessibility, final adoption and adherence to a guideline remains to be investigated, even though there have been dedicated efforts to investigate optimal implementation pathways and implementation outcome for newer mTBI guidelines both in Australia/New Zealand [ 36 , 37 ] and the US [ 38 , 39 , 40 , 41 , 42 ]. Among the Swedish respondents, a high belief in the benefit for the patients of using the SNC-16 guideline was reported in this study, which may imply that the basic flowchart structure of the clinical decision rule that is central to the guideline is feasible for the Scandinavian setting. A recent systematic review of trends in guideline implementation showed that even if more studies investigate and tailor interventions to facilitate implementation of a guideline, with most studies reporting effect, studies that did not plan specific implementation measures also achieved impact [ 20 ]. Causes for a seemingly successful dissemination of the SNC-16 guideline could therefore be numerous.

Potential barriers for implementation of the SNC-16 guideline could be identified within different types of determinants. Over one quarter of our respondents stated a lack of organizational support needed to use the guideline. Organizational barriers affect uptake of recommendations and a top-down drive of change from medical managers is likely important for adoption of a guideline, identifying team and organization leaders as a target for interventions in future implementation planning [ 39 , 43 ]. Lack of resources (e.g., observational units, CT accessibility) also seems to pose an organizational challenge in Swedish health care.

Another relevant issue are the implementation tools accompanying the SNC-16 guideline. Respondents were unsure about which tools are included in the guideline and the helpfulness of these tools. This uncertainty was also expressed as a barrier in the free-text answers. Many respondents seem to prefer electronic tools and further improvements may include development of electronic educational tools/websites and integration with electronic health record-based systems, an aspect that has been identified in other populations [ 37 , 38 , 39 , 41 ]. The need for developing more concise implementation tools, both digital and in print, was identified in an interview study investigating experience and use of the CDC pediatric mTBI guidelines in rural areas in US [ 38 ]. Recently, an evaluation of a generic model to integrate decision aids for shared decision making into electronic evidence summaries with adjacent guidelines showed promising results and may be applicable also for pediatric TBI in the future [ 44 ]. Another area amenable to improvements is the description of the underlying evidence supporting the recommendations, where only 37.6% agreed that the description was clear. This finding is in contrast to a survey by Sawka et al. [ 45 ], also using the CGDQ, which showed that 92.3% agreed that the evidence underlying the evaluated US thyroid guideline was clearly described.

More than half of the respondents sought guidance for their clinical decision-making from colleagues (90%), guidelines (75%), or the internet (65%) and preferred to learn about guidelines via educational meetings and conferences (78%). Sawka et al. [ 45 ], reported somewhat different results regarding the thyroid guideline, where the most common sources for knowledge were medical literature (88.1%), guidelines (87.2%), and colleagues (65.6%). The reported need for discussion with colleagues and learning via meetings/conferences may underscore the need for understanding stakeholders’ views of how to manage mTBI in children. Many respondents were unsure about practice in other settings, and educational meetings may fill an important knowledge gap in this respect. Daugherty et al. [ 38 ], who evaluated the implementation of the CDC pediatric mTBI guideline in a rural area in the US, identified a perceived lack of access to mTBI specialists and discussed the telemonitoring ECHO model as an example where health care providers could meet in a virtual community and discuss cases. There are reports on the application of this model in pediatric emergency care and pediatric mTBI [ 46 , 47 ]. In a recent systematic review, education of professionals was a commonly utilized intervention in guideline implementation planning [ 20 ]. Another review by Chan et al. [ 48 ] reported a positive impact through specific interventions, namely educational outreach, audit, and feedback. There was a significant association between familiarity with assessing pediatric mTBI and the perceived benefit of adherence to the recommendations. This association might be explained by senior physicians managing this condition more seldom, and when doing so relying on their clinical judgement and solid experience rather than a clinical practice guideline [ 37 ].

There are several limitations to consider when interpreting the results from this survey. The low total response rate of 43.4% (analyzable response rate 33.3%) implies a potential responder bias. The high reported use of the guideline could be an effect of sampling bias due to the modified snowball sampling method, for example if the respondents more commonly recommended colleagues with similar education, value base, or within the same organization. Nevertheless, our sampling strategy and different e-mail address collection strategies offered a good opportunity to maximize and optimize respondent relevance by drawing on snowball sampling, the ED physician community, and the ongoing guideline implementation. The background information does not, however, indicate a widespread bias among respondents as the distribution of gender, career stage, category of hospital, part of Sweden, and types of patients managed is reasonable from a Swedish healthcare perspective. Another risk worth mentioning is that of contamination, in the form of an observer effect. There has been an intense focus in Sweden on pediatric mTBI management as an effect of the ongoing guideline validation efforts. The validation study [ 32 ] is strictly observational but has inevitably set focus on the SNC-16 guidelines and the investigators behind these. However, the use of an e-mail recipient list from the 2022 study [ 13 ] is unlikely to have contaminated the responses as there was only one respondent from each of the 66 hospitals in that study. Another limitation is the cross-sectional design, addressing the physicians’ perceptions of their own actions, leaving room for deviation from the reported views in actual patient management decisions.

This cross-sectional survey on determinants for use of the Scandinavian guideline for management of mild and moderate head injury in children suggests that use of the guideline is high in our sample of ED providers in Sweden. In updated versions of the guideline, focus on improving implementation tools and descriptions of the underlying evidence may further facilitate adoption and adherence. Measures to improve organizational support for guideline use and involvement of patient representatives should also be considered.

Availability of data and materials

Pseudonymized datasets used and analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Scandinavian Neurotrauma Committee

Computed tomography

Emergency department

Clinical Guideline Determinants Questionnaire

Mild traumatic brain injury

Glasgow Coma Scale

Reaction Level Scale -85

Centers for Disease Control

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Acknowledgements

We would like to thank the respondents in this survey for their valuable contribution and Region Halland for ongoing support with research efforts, especially the FoUU department.

Open access funding provided by Lund University. This study was non-commercially funded by the research and development department at Halland Hospital (FoUU Halland), Sweden.

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FW, LP, SB and JU conceived and planned the study. FW, LP and WB developed the electronic questionnaire. FW and WB compiled the respondent list. WB collected the data, with supervision by FW. FW and WB analyzed the data, summarized the results, and wrote the first draft. SK contributed with statistical supervision throughout the process. SB and JU contributed with critical review of the manuscript. All authors have read and approved the final manuscript.

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None of the authors have any financial competing interests. SB participated in the development of the Clinician Guideline Determinants Questionnaire. JU is a member of the SNC committee, a non-profit organization independent from financial company support, who are responsible for the SNC-16 guidelines.

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Wickbom, F., Berghog, W., Bernhardsson, S. et al. Pediatric head injury guideline use in Sweden: a cross-sectional survey on determinants for successful implementation of a clinical practice guideline. BMC Health Serv Res 24 , 965 (2024). https://doi.org/10.1186/s12913-024-11423-z

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DOI : https://doi.org/10.1186/s12913-024-11423-z

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Analysing near-miss incidents in construction: a systematic literature review.

1. Introduction

• Q 1 —Are near-miss events in construction industry the subject of scientific research?
• Q 2 —What methods have been employed thus far to obtain information on near misses and systems for recording incidents in construction companies?
• Q 3 —What methods have been used to analyse the information and figures obtained?
• Q 4 —What are the key aspects of near misses in the construction industry that have been of interest to the researchers?

2. Definition of Near-Miss Events

3. research methodology, 4.1. a statistical analysis of publications, 4.2. methods used to obtain information about near misses, 4.2.1. traditional methods.

• Traditional registration forms
• Computerized systems for the recording of events
• Surveys and interviews

4.2.2. Real-Time Monitoring Systems

• Employee-tracking systems
• Video surveillance systems
• Wearable technology
• Motion sensors

4.3. Methods Used to Analyse the Information and Figures That Have Been Obtained

4.3.1. quantitative and qualitative statistical methods, 4.3.2. analysis using artificial intelligence (ai), 4.3.3. building information modelling, 4.4. key aspects of near-miss investigations in the construction industry, 4.4.1. occupational risk assessment, 4.4.2. causes of hazards in construction, 4.4.3. time series of near misses, 4.4.4. material factors of construction processes, 4.5. a comprehensive overview of the research questions and references on near misses in the construction industry, 5. discussion, 5.1. interest of researchers in near misses in construction (question 1), 5.2. methods used to obtain near-miss information (question 2), 5.3. methods used to analyse the information and data sets (question 3), 5.4. key aspects of near-miss investigations in the construction industry (question 4), 6. conclusions.

• A quantitative analysis of the Q 1 question has revealed a positive trend, namely that there is a growing interest among researchers in studying near misses in construction. The greatest interest in NM topics is observed in the United States of America, China, the United Kingdom, Australia, Hong Kong, and Germany. Additionally, there has been a recent emergence of interest in Poland. The majority of articles are mainly published in journals such as Safety Science (10), Journal of Construction Engineering and Management (8), and Automation in Construction (5);
• The analysis of question Q 2 illustrates that traditional paper-based event registration systems are currently being superseded by advanced IT systems. However, both traditional and advanced systems are subject to the disadvantage of relying on employee-reported data, which introduces a significant degree of uncertainty regarding in the quality of the information provided. A substantial proportion of the data and findings presented in the studies was obtained through surveys and interviews. The implementation of real-time monitoring systems is becoming increasingly prevalent in construction sites. The objective of such systems is to provide immediate alerts in the event of potential hazards, thereby preventing a significant number of near misses. Real-time monitoring systems employ a range of technologies, including ultrasonic technology, radio frequency identification (RFID), inertial measurement units (IMUs), real-time location systems (RTLSs), industrial cameras, wearable technology, motion sensors, and advanced IT technologies, among others;
• The analysis of acquired near-miss data is primarily conducted through the utilisation of quantitative and qualitative statistical methods, as evidenced by the examination of the Q 3 question. In recent years, research utilising artificial intelligence (AI) has made significant advances. The most commonly employed artificial intelligence techniques include text mining, machine learning, and artificial neural networks. The growing deployment of Building Information Modelling (BIM) technology has precipitated a profound transformation in the safety management of construction sites, with the advent of sophisticated tools for the identification and management of hazardous occurrences;
• In response to question Q 4 , the study of near misses in the construction industry has identified several key aspects that have attracted the attention of researchers. These include the utilisation of both quantitative and qualitative methodologies for risk assessment, the analysis of the causes of hazards, the identification of accident precursors through the creation of time series, and the examination of material factors pertaining to construction processes. Researchers are focusing on the utilisation of both databases and advanced technologies, such as real-time location tracking, for the assessment and analysis of occupational risks. Techniques such as Analytic Hierarchy Process (AHP) and clustering facilitate a comprehensive assessment and categorisation of incidents, thereby enabling the identification of patterns and susceptibility to specific types of accidents. Moreover, the impact of a company’s safety climate and organisational culture on the frequency and characteristics of near misses represents a pivotal area of investigation. The findings of this research indicate that effective safety management requires a holistic approach that integrates technology, risk management and safety culture, with the objective of reducing accidents and enhancing overall working conditions on construction sites.

7. Gaps and Future Research Directions, Limitations

• Given the diversity and variability of construction sites and the changing conditions and circumstances of work, it is essential to create homogeneous clusters of near misses and to analyse the phenomena within these clusters. The formation of such clusters may be contingent upon the direct causes of the events in question;
• Given the inherently dynamic nature of construction, it is essential to analyse time series of events that indicate trends in development and safety levels. The numerical characteristics of these trends may be used to construct predictive models for future accidents and near misses;
• The authors have identified potential avenues for future research, which could involve the development of mathematical models using techniques such as linear regression, artificial intelligence, and machine learning. The objective of these models is to predict the probable timing of occupational accidents within defined incident categories, utilising data from near misses. Moreover, efforts are being made to gain access to the hazardous incident recording systems of different construction companies, with a view to facilitating comparison of the resulting data;
• One significant limitation of near-miss research is the lack of an integrated database that encompasses a diverse range of construction sites and construction work. A data resource of this nature would be of immense value for the purpose of conducting comprehensive analyses and formulating effective risk management strategies. This issue can be attributed to two factors: firstly, the reluctance of company managers to share their databases with researchers specialising in risk assessment, and secondly, the reluctance of employees to report near-miss incidents. Such actions may result in adverse consequences for employees, including disciplinary action or negative perceptions from managers. This consequently results in the recording of only a subset of incidents, thereby distorting the true picture of safety on the site.

Author Contributions

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Woźniak, Z.; Hoła, B. Analysing Near-Miss Incidents in Construction: A Systematic Literature Review. Appl. Sci. 2024 , 14 , 7260. https://doi.org/10.3390/app14167260

Woźniak Z, Hoła B. Analysing Near-Miss Incidents in Construction: A Systematic Literature Review. Applied Sciences . 2024; 14(16):7260. https://doi.org/10.3390/app14167260

Woźniak, Zuzanna, and Bożena Hoła. 2024. "Analysing Near-Miss Incidents in Construction: A Systematic Literature Review" Applied Sciences 14, no. 16: 7260. https://doi.org/10.3390/app14167260

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Exploring the factors driving AI adoption in production: a systematic literature review and future research agenda

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• Published: 23 August 2024

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• Heidi Heimberger   ORCID: orcid.org/0000-0003-3390-0219 1 , 2 ,
• Djerdj Horvat   ORCID: orcid.org/0000-0003-3747-3402 1 &
• Frank Schultmann   ORCID: orcid.org/0000-0001-6405-9763 1  

Our paper analyzes the current state of research on artificial intelligence (AI) adoption from a production perspective. We represent a holistic view on the topic which is necessary to get a first understanding of AI in a production-context and to build a comprehensive view on the different dimensions as well as factors influencing its adoption. We review the scientific literature published between 2010 and May 2024 to analyze the current state of research on AI in production. Following a systematic approach to select relevant studies, our literature review is based on a sample of articles that contribute to production-specific AI adoption. Our results reveal that the topic has been emerging within the last years and that AI adoption research in production is to date still in an early stage. We are able to systematize and explain 35 factors with a significant role for AI adoption in production and classify the results in a framework. Based on the factor analysis, we establish a future research agenda that serves as a basis for future research and addresses open questions. Our paper provides an overview of the current state of the research on the adoption of AI in a production-specific context, which forms a basis for further studies as well as a starting point for a better understanding of the implementation of AI in practice.

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1 Introduction

The technological change resulting from deep digitisation and the increasing use of digital technologies has reached and transformed many sectors [ 1 ]. In manufacturing, the development of a new industrial age, characterized by extensive automation and digitisation of processes [ 2 ], is changing the sector’s ‘technological reality’ [ 3 ] by integrating a wide range of information and communication technologies (such as Industry 4.0-related technologies) into production processes [ 4 ].

Although the evolution of AI traces back to the year 1956 (as part of the Dartmouth Conference) [ 5 ], its development has progressed rapidly, especially since the 2010s [ 6 ]. Driven by improvements, such as the fast and low-cost development of smart hardware, the enhancement of algorithms as well as the capability to manage big data [ 7 ], there is an increasing number of AI applications available for implementation today [ 8 ]. The integration of AI into production processes promises to boost the productivity, efficiency as well as automation of processes [ 9 ], but is currently still in its infancy [ 10 ] and manufacturing firms seem to still be hesitant to adopt AI in a production-context. This appears to be driven by the high complexity of AI combined with the lack of practical knowledge about its implementation in production and several other influencing factors [ 11 , 12 ].

In the literature, many contributions analyze AI from a technological perspective, mainly addressing underlying models, algorithms, and developments of AI tools. Various authors characterise both machine learning and deep learning as key technologies of AI [ 8 , 13 ], which are often applied in combination with other AI technologies, such as natural language recognition. While promising areas for AI application already exist in various domains such as marketing [ 14 ], procurement [ 15 ], supply chain management [ 16 ] or innovation management [ 17 ], the integration of AI into production processes also provides significant performance potentials, particularly in the areas of maintenance [ 18 ], quality control [ 19 ] and production planning and management [ 20 ]. However, AI adoption requires important technological foundations, such as the provision of data and the necessary infrastructure, which must be ensured [ 11 , 12 , 21 ]. Although the state of the art literature provides important insights into possible fields of application of AI in production, the question remains: To what extent are these versatile applications already in use and what is required for their successful adoption?

Besides the technology perspective of AI, a more human-oriented field of discussion is debated in scientific literature [ 22 ]. While new technologies play an essential role in driving business growth in the digital transformation of the production industry, the increasing interaction between humans and intelligent machines (also referred to as ‘augmentation’) creates stress challenges [ 23 ] and impacts work [ 24 ], which thus creates managerial challenges in organizations [ 25 , 26 ]. One of the widely discussed topics in this context is the fear of AI threatening jobs (including production jobs), which was triggered by e.g. a study of Frey, Osborne [ 27 ]. Another issue associated to the fear of machines replacing humans is the lack of acceptance resulting from the mistrust of technologies [ 28 , 29 ]. This can also be linked to the various ethical challenges involved in working with AI [ 22 ]. This perspective, which focuses on the interplay between AI and humans [ 30 ], reveals the tension triggered by AI. Although this is discussed from different angles, the question remains how these aspects influence the adoption of AI in production.

Another thematic stream of current literature can be observed in a series of contributions on the organizational aspects of the technology. In comparison to the two research areas discussed above, the number of publications in this area seems to be smaller. This perspective focuses on issues to implement AI, such as the importance of a profound management structure [ 31 , 32 ], leadership [ 33 ], implications on the organizational culture [ 34 ] as well as the need for digital capabilities and special organizational skills [ 33 ]. Although some studies on the general adoption of AI without a sectoral focus have already been conducted (such as by Chen, Tajdini [ 35 ] or Kinkel, Baumgartner, Cherubini [ 36 ]) and hence, some initial factors influencing the adoption of AI can be derived, the contributions from this perspective are still scarce, are usually not specifically analyzed in the context of production or lack a comprehensive view on the organization in AI adoption.

While non-industry specific AI issues have been researched in recent years, the current literature misses a production-specific analysis of AI adoption, providing an understanding of the possibilities and issues related to integrating AI into the production context. Moreover, the existing literature tells us little about relevant mechanisms and factors underlying the adoption of AI in production processes, which include both technical, human-centered as well as organizational issues. As organizational understanding of AI in a business context is currently still in its early stages, it is difficult to find an aggregate view on the factors that can support companies in implementing AI initiatives in production [ 37 , 38 ]. Addressing this gap, we aim to systematise the current scientific knowledge on AI adoption, with a focus on production. By drawing on a systematic literature review (SLR), we examine existing studies on AI adoption in production and explore the main issues regarding adoption that are covered in the analyzed articles. Building on these findings, we conduct a comprehensive analysis of the existing studies with the aim of systematically investigating the key factors influencing the adoption of AI in production. This systematic approach paves the way for the formulation of a future research agenda.

Our SLR addresses three research questions (RQs). RQ1: What are the statistical characteristics of existing research on AI adoption in production? To answer this RQ, we conduct descriptive statistics of the analyzed studies and provide information on time trends, methods used in the research, and country specifications. RQ2: What factors influence the adoption of AI in production? RQ2 specifies the adoption factors and forms the core component of our analysis. By adoption factors, we mean the factors that influence the use of AI in production (both positively and negatively) and that must therefore be analyzed and taken into account. RQ3: What research topics are of importance to advance the research field of AI adoption in production? We address this RQ by using the analyzed literature as well as the key factors of AI adoption as a starting point to derive RQs that are not addressed and thus provide an outlook on the topic.

2 Methodology

In order to create a sound information base for both policy makers and practitioners on the topic of AI adoption in production, this paper follows the systematic approach of a SLR. For many fields, including management research, a SLR is an important tool to capture the diversity of existing knowledge on a specific topic for a scientific investigation [ 39 ]. The investigator often pursues multiple goals, such as capturing and assessing the existing environment and advancing the existing body of knowledge with a proprietary RQ [ 39 ] or identifying key research topics [ 40 ].

Our SLR aims to select, analyze, and synthesize findings from the existing literature on AI adoption in production over the past 24 years. In order to identify relevant data for our literature synthesis, we follow the systematic approach of the Preferred Reporting Items for Systematic reviews (PRISMA) [ 41 ]. In evaluating the findings, we draw on a mixed-methods approach, combining some quantitative analyses, especially on the descriptive aspects of the selected publications, as well as qualitative analyses aimed at evaluating and comparing the contents of the papers. Figure  1 graphically summarizes the methodological approach that guides the content of the following sub-chapters.

Methodical procedure of our SLR following PRISMA [ 41 ]

2.1 Data identification

Following the development of the specific RQs, we searched for suitable publications. To locate relevant studies, we chose to conduct a publication analysis in the databases Scopus, Web of Science and ScienceDirect as these databases primarily contain international scientific articles and provide a broad overview of the interdisciplinary research field and its findings. To align the search with the RQs [ 42 ], we applied predefined key words to search the titles, abstracts, and keywords of Scopus, Web of Science and ScienceDirect articles. Our research team conducted several pre-tests to determine the final search commands for which the test results were on target and increased the efficiency of the search [ 42 ]. Using the combination of Boolean operators, we covered the three topics of AI, production, and adoption by searching combinations of ‘Artificial Intelligence’ AND ‘production or manufacturing’ AND ‘adopt*’ in the three scientific databases. Although ‘manufacturing’ tends to stand for the whole sector and ‘production’ refers to the process, the two terms are often used to describe the same context. We also follow the view of Burbidge, Falster, Riis, Svendsen [ 43 ] and use the terms synonymously in this paper and therefore also include both terms as keywords in the study location as well as in the analysis.

AI research has been credited with a resurgence since 2010 [ 6 ], which is the reason for our choice of time horizon. Due to the increase in publications within the last years, we selected articles published online from 2010 to May 8, 2024 for our analysis. As document types, we included conference papers, articles, reviews, book chapters, conference reviews as well as books, focusing exclusively on contributions in English in the final publication stage. The result of the study location is a list of 3,833 documents whose titles, abstracts, and keywords meet the search criteria and are therefore included in the next step of the analysis.

2.2 Data analysis

For these 3,833 documents, we then conducted an abstract analysis, ‘us[ing] a set of explicit selection criteria to assess the relevance of each study found to see if it actually does address the research question’ [ 42 ]. For this step, we again conducted double-blind screenings (including a minimum of two reviewers) as pilot searches so that all reviewers have the same understanding of the decision rules and make equal decisions regarding their inclusion for further analysis.

To ensure the paper’s focus on all three topics regarded in our research (AI, production, and adoption), we followed clearly defined rules of inclusion and exclusion that all reviewers had to follow in the review process. As a first requirement for inclusion, AI must be the technology in focus that is analysed in the publication. If AI was only mentioned and not further specified, we excluded the publication. With a second requirement, we checked the papers for the context of analysis, which in our case must be production. If the core focus is beyond production, the publication was also excluded from further analysis. The third prerequisite for further consideration of the publication is the analysis of the adoption of a technology in the paper. If technology adoption is not addressed or adoption factors are not considered, we excluded the paper. An article was only selected for full-text analysis if, after analyzing the titles, abstracts, and keywords, a clear focus on all three research areas was visible and the inclusion criteria were met for all three contexts.

By using this tripartite inclusion analysis, we were able to analyse the publications in a structured way and to reduce the 3,833 selected documents in our double-blind approach to 300 articles that were chosen for the full-text analysis. In the process of finding full versions of these publications, we had to exclude three papers as we could not access them. For the rest of the 297 articles we obtained full access and thus included them for further analysis. After a thorough examination of the full texts, we again had to exclude 249 publications because they did not meet our content-related inclusion criteria mentioned above, although the abstract analysis gave indications that they did. As a result, we finally obtained 47 selected papers on which we base the literature analysis and synthesis (see Fig.  1 ).

2.3 Descriptive analysis

Figure  2 summarises the results of the descriptive analysis on the selected literature regarding AI adoption in production that we analyse in our SLR. From Fig.  2 a), which illustrates annual publication trends (2010–2024), the increase in publications on AI adoption in production over the past 5 years is evident, yet slightly declining after a peak in 2022. After a steady increase until 2022, in which 11 articles are included in the final analysis, 2023 features ten articles, followed by three articles for 2024 until the cut-off date in May 2024. Of the 47 papers identified through our search, the majority (n = 33) are peer-reviewed journal articles and the remaining thirteen contributions conference proceedings and one book chapter (see Fig.  2 b)).

Descriptive analyses of the selected articles addressing AI adoption in production

The identified contributions reveal some additional characteristics in terms of the authors country base (Fig.  2 c)) and research methods used (Fig.  2 d)). Almost four out of ten of the publications were written in collaboration with authors from several countries (n = 19). Six of the papers were published by authors from the United States, five from Germany and four from India. In terms of the applied research methods used by the researchers, a wide range of methods is used (see Fig.  2 c), with qualitative methods (n = 22) being the most frequently used.

2.4 Factor analysis

In order to derive a comprehensive list of factors that influence the use of AI in production at different levels, we follow a qualitative content analysis. It is based on inductive category development, avoiding prefabricated categories in order to allow new categories to emerge based on the content at hand [ 44 , 45 ]. To do this, we first read the entire text to gain an understanding of the content and then derive codes [ 46 ] that seem to capture key ideas [ 45 ]. The codes are subsequently sorted into distinct categories, each of which is clearly defined and establishes meaningful connections between different codes. Based on an iterative process with feedback loops, the assigned categories are continuously reviewed and updated as revisions are made [ 44 ].

Various factors at different levels are of significance to AI and influence technology adoption [ 47 , 48 ]. To identify the specific factors that are of importance for AI adoption in production, we analyze the selected contributions in terms of the factors considered, compare them with each other and consequently obtain a list of factors through a bottom-up approach. While some of the factors are based on empirical findings, others are expected factors that result from the research findings of the respective studies. Through our analysis, a list of 35 factors emerges that influence AI adoption in production which occur with varying frequency in the studies analyzed by our SLR. Table 1 visualizes each factor in the respective contributions sorted by the frequency of occurrence.

The presence of skills is considered a particularly important factor in AI adoption in the studies analyzed (n = 35). The availability of data (n = 25) as well as the need for ethical guidelines (n = 24) are also seen as key drivers of AI adoption, as data is seen as the basis for the implementation of AI and ethical issues must be addressed in handling such an advanced technology. As such, these three factors make up the accelerants of AI adoption in production that are most frequently cited in the studies analyzed.

Also of importance are issues of managerial support (n = 22), as well as performance measures and IT infrastructure (n = 20). Some factors were also mentioned, but only addressed by one study at a time: government support, industrial sector, product complexity, batch size, and R&D Intensity. These factors are often used as quantitatively measurable adoption factors, especially in empirical surveys, such the study by Kinkel, Baumgartner, Cherubini [ 36 ].

3 Factors influencing AI adoption

The 35 factors presented characteristically in Sect.  2.4 serve as the basis for our in-depth analysis and for developing a framework of influences on AI adoption in production which are grouped into supercategories. A supercategory describes a cluster of topics to which various factors of AI adoption in production can be assigned. We were able to define seven categories that influence AI adoption in production: the internal influences of ‘business and structure’, ‘organizational effectiveness’, ‘technology and system’, ‘data management’ as well as the external influences of the ‘regulatory environment’, ‘business environment’ and ‘economic environment’ (see Fig.  3 ). The factors that were mentioned most frequently (occurrence in at least half of the papers analyzed) are marked accordingly (*) in Fig.  3 .

Framework of factors influencing AI adoption in production

3.1 Internal Environment

The internal influences on AI adoption in production refer to factors that an organization carries internally and that thus also influence adoption from within. Such factors can usually be influenced and clearly controlled by the organization itself.

3.1.1 Business and structure

The supercategory ‘business and structure’ includes the various factors and characteristics that impact a company’s performance, operations, and strategic decision-making. By considering and analyzing these business variables when implementing AI in production processes, companies can develop effective strategies to optimize their performance, increase their competitiveness, and adapt to changes in the business environment.

To understand and grasp the benefits in the use of AI, quantitative performance measures for the current and potential use of AI in industrial production systems help to clarify the value and potential benefits of AI use [ 49 , 54 , 74 , 79 , 91 ]. Assessing possible risks [ 77 ] as well as the monetary expected benefits for AI (e.g. Return on Investment (ROI)) in production plays an important role for adoption decisions in market-oriented companies [ 57 , 58 , 63 , 65 , 78 ]. Due to financial constraints, managers behave cautiously in their investments [ 78 ], so they need to evaluate AI adoption as financially viable to want to make the investment [ 61 , 63 , 93 ] and also drive acceptance [ 60 ]. AI systems can significantly improve cost–benefit structures in manufacturing, thereby increasing the profitability of production systems [ 73 ] and making companies more resilient [ 75 ]. However, in most cases, the adoption of AI requires high investments and the allocation of resources (s.a. personnel or financial) for this purpose [ 50 , 51 , 57 , 80 , 94 ]. Consequently, a lack of budgets and high expected transition costs often hinder the implementation of smart concepts [ 56 , 62 , 67 , 82 , 84 , 92 ]. It is up to management to provide necessary funding for AI adoption [ 53 , 59 , 79 ], which is required, for example, for skill development of employees [ 59 , 61 , 63 ], IT adaptation [ 62 , 66 ], AI development [ 74 ] or hardware deployment [ 68 ]. In their empirical study, Kinkel, Baumgartner, Cherubini [ 36 ] confirm a positive correlation between company size and the intensity in the use of AI technologies. Large companies generally stand out with a higher propensity to adopt [ 53 ] as they have less difficulties in comparison to small firms regarding the availability of resources [ 69 ], such as know-how, budget [ 68 , 84 ] and general data organization [ 68 ]. Others argue that small companies tend to be more open to change and are characterized by faster decision-making processes [ 68 , 93 ]. Product complexity also influences a company’s propensity for AI. Companies that produce rather simple products are more likely to digitize, which in turn offers good starting points for AI adoption. On the other hand, complex product manufacturers (often characterized by small batch sizes) are often less able to standardize and automate [ 36 ]. The company’s produced batch size has a similar influence on AI adoption. Small and medium batch sizes in particular hinder the integration of intelligent technologies, as less automation often prevails here as well. Nevertheless, even small and medium lot sizes can benefit economically from AI [ 36 ]. Since a high R&D intensity indicates a high innovation capability of a company, it is assumed to have a positive influence on AI adoption, as companies with a high R&D intensity already invest heavily in and use new innovations. This in turn speaks for existing competencies, know how and structures [ 36 ].

3.1.2 Organizational effectiveness

This supercategory focuses on the broader aspects that contribute to the effectiveness, development, and success of an organization when implementing AI in a production context. As the factors are interconnected and influence each other, decision makers should consider them carefully.

Users´ trust in AI is an essential factor to enable successful AI adoption and use in production [ 52 , 68 , 78 , 79 , 88 , 90 ]. From the users´ perspective, AI often exhibits the characteristics of a black box because its inherent processes are not fully understood [ 50 , 90 ] which can lead individuals to develop a fear towards the unknown [ 71 ]. Because of this lack of understanding, successful interaction between humans and AI is not guaranteed [ 90 ], as trust is a foundation for decisions that machines are intended to make autonomously [ 52 , 91 ]. To strengthen faith in AI systems [ 76 , 80 ], AI users can be involved in AI design processes in order to understand appropriate tools [ 54 , 90 ]. In this context, trust is also discussed in close connection with transparency and regulation [ 79 ]. User resistance is considered a barrier to implementing new information technologies, as adoption requires change [ 53 , 62 , 92 ]. Ignorance, as a kind of resistance to change, is a main obstacle to successful digital transformation [ 51 , 56 , 65 ]. Some employees may resist the change brought about by AI because they fear losing their jobs [ 52 ] or have other concerns [ 78 ]. Overcoming resistance to technology adoption requires organizational change and is critical for the success of adoption [ 50 , 51 , 62 , 67 , 71 , 80 ]. Therefore, change management is important to create awareness of the importance of AI adoption and increase acceptance of the workforce [ 66 , 68 , 74 , 83 ]. Management commitment is seen as a significant driver of technology adoption [ 53 , 59 , 81 , 82 , 86 ] and a lack of commitment can negatively impact user adoption and workforce trust and lead to skepticism towards technology [ 86 ]. The top management’s understanding and support for the benefits of the adopted technology [ 53 , 56 , 67 , 78 , 93 , 94 ] enhances AI adoption, can prioritize its implementation and also affects the performance of the AI-enabled application [ 55 , 60 , 83 ]. Preparing, enabling, and thus empowering the workforce, are considered the management’s responsibility in the adoption of digital technologies [ 59 , 75 ]. This requires intelligent leadership [ 52 ] as decision makers need to integrate their workforce into decision-making processes [ 75 ]. Guidelines can support managers by providing access to best practices that help in the adoption of AI [ 50 ]. Critical measures to manage organizational change include the empowerment of visionaries or appointed AI champions leading the change and the collaborative development of digital roadmaps [ 54 , 62 ]. To demonstrate management commitment, managers can create such a dedicated role, consisting of an individual or a small group that is actively and enthusiastically committed to AI adoption in production. This body is considered the adoption manager, point of contact and internal driver of adoption [ 62 , 74 , 80 ]. AI initiatives in production do not necessarily have to be initiated by management. Although management support is essential for successful AI adoption, employees can also actively drive integration initially and thus realize pilot projects or initial trials [ 66 , 80 ]. The development of strategies as well as roadmaps is considered another enabling and necessary factor for the adoption of AI in production [ 50 , 53 , 54 , 62 , 71 , 93 ]. While many major AI strategies already exist at country level to further promote research and development of AI [ 87 ], strategy development is also important at the firm level [ 76 , 77 , 81 ]. In this context, strategies should not be delegated top-down, but be developed in a collaborative manner, i.e. by engaging the workforce [ 75 ] and be in alignment with clear visions [ 91 , 94 ]. Roadmaps are used to improve planning, support implementation, facilitate the adoption of smart technologies in manufacturing [ 93 ] and should be integrated into both business and IT strategy [ 62 , 66 ]. In practice, clear adoption roadmaps that provide approaches on how to effectively integrate AI into existing strategies and businesses are often lacking [ 56 , 87 ]. The need for AI-related skills in organizations is a widely discussed topic in AI adoption analyses [ 79 ]. In this context, the literature points both at the need for specific skills in the development and design of AI applications [ 57 , 71 , 72 , 73 , 76 , 93 ] as well as the skills in using the technology [ 53 , 65 , 73 , 74 , 75 , 84 , 93 ] which availability in the firm is not always given [ 49 ]. AI requires new digital skills [ 36 , 50 , 52 , 55 , 56 , 59 , 61 , 63 , 66 , 78 , 80 ], where e.g. advanced analytics [ 64 , 75 , 81 ], programming skills [ 68 ] and cybersecurity skills [ 78 , 93 ] gain importance. The lack of skills required for AI is seen as a major challenge of digital transformation, as a skilled workforce is considered a key resource for companies [ 51 , 54 , 56 , 60 , 62 , 67 , 69 , 70 , 82 , 93 ]. This lack of a necessary skillset hinders the adoption of AI tools in production systems [ 58 , 77 ]. Closely related to skills is the need for new training concepts, which organizations need to consider when integrating digital technologies [ 49 , 50 , 51 , 56 , 59 , 63 , 71 , 74 , 75 ]. Firms must invest in qualification in order to create necessary competences [ 73 , 78 , 80 , 81 , 92 ]. Additionally, education must target and further develop the skills required for effectively integrating intelligent technologies into manufacturing processes [ 54 , 61 , 62 , 83 ]. Regarding this issue, academic institutions must develop fitting curricula for data driven manufacturing engineering [ 64 ]. Another driving factor of AI adoption is the innovation culture of an organization, which is influenced by various drivers. For example, companies that operate in an environment with high innovation rates, facing intense competitive pressures are considered more likely to see smart technologies as a tool for strategic change [ 83 , 91 , 93 ]. These firms often invest in more expensive and advanced smart technologies as the pressure and resulting competition forces them to innovate [ 93 ]. Another way of approach this is that innovation capability can also be supported and complemented by AI, for example by intelligent systems supporting humans in innovation or even innovating on their own [ 52 ].The entrepreneurial orientation of a firm is characterized in particular by innovativeness [ 66 ], productivity [ 63 ], risk-taking [ 86 ] as well as continuous improvement [ 50 ]. Such characteristics of an innovating culture are considered essential for companies to recognise dynamic changes in the market and make adoption decisions [ 51 , 71 , 81 , 84 , 86 , 94 ]. The prevalence of a digital mindset in companies is important for technology adoption, as digital transformation affects the entire organizational culture and behavior [ 59 , 80 , 92 ] and a lack of a digital culture [ 50 , 65 ] as well as a ‘passive mindset’ [ 78 ] can hinder the digital transformation of firms. Organizations need to develop a corresponding culture [ 66 , 67 , 71 ], also referred to as ‘AI-ready-culture’ [ 54 ], that promotes development and encourages people and data through the incorporation of technology [ 71 , 75 ]. With the increasing adoption of smart technologies, a ‘new digital normal’ is emerging, characterized by hybrid work models, more human–machine interactions and an increased use of digital technologies [ 75 , 83 ].

3.1.3 Technology and System

The ‘technology and system’ supercategory focuses on the broader issues related to the technology and infrastructure that support organizational operations and provide the technical foundation for AI deployment.

By IT infrastructure we refer to issues regarding the foundational systems and IT needed for AI adoption in production. Industrial firms and their IT systems must achieve a mature technological readiness in order to enable successful AI adoption [ 51 , 60 , 67 , 69 , 83 ]. A lack of appropriate IT infrastructure [ 68 , 71 , 78 , 91 ] or small maturity of Internet of Things (IoT) technologies [ 70 ]) hinders the efficient use of data in production firms [ 56 ] which is why firms must update their foundational information systems for successful AI adoption [ 53 , 54 , 62 , 66 , 72 , 75 ]. IT and data security are fundamental for AI adoption and must be provided [ 50 , 51 , 68 , 82 ]. This requires necessary developments that can ensure security during AI implementation while complying with legal requirements [ 52 , 72 , 78 ]. Generally, security concerns are common when implementing AI innovations [ 72 , 79 , 91 , 94 ]. This fear of a lack of security can also prevent the release of (e.g. customer) data in a production environment [ 56 ]. Additionally, as industrial production systems are vulnerable to failures as well as cyberattacks, companies need to address security and cybersecurity measures [ 49 , 76 , 88 , 89 ]. Developing user-friendly AI solutions can facilitate the adoption of smart solutions by increasing user understanding and making systems easy to use by employees as well as quick to integrate [ 50 , 72 , 84 ]. When developing user-friendly solutions which satisfy user needs [ 76 ], it is particularly important to understand and integrate the user perspective in the development process [ 90 ]. If employees find technical solutions easy to use, they are more confident in its use and perceived usefulness increases [ 53 , 67 , 68 ]. The compatibility of AI with a firm and its existing systems, i.e., the extent to which AI matches existing processes, structures, and infrastructures [ 53 , 54 , 56 , 60 , 78 , 80 , 82 , 83 , 93 , 94 ], is considered an important requirement for the adoption of AI in IT systems [ 91 ]. Along with compatibility also comes connectivity, which is intended to ensure the links within the overall network and avoid silo thinking [ 59 ]. Connectivity and interoperability of AI-based processes within the company’s IT manufacturing systems must be ensured at different system levels and are considered key factors in the development of AI applications for production [ 50 , 72 , 89 ]. The design of modular AI solutions can increase system compatibility [ 84 ]. Firms deciding for AI adoption must address safety issues [ 51 , 54 , 59 , 72 , 73 , 78 ]. This includes both safety in the use and operation of AI [ 60 , 69 ]. In order to address safety concerns of integrating AI solutions in industrial systems [ 49 ], systems must secure high reliability [ 71 ]. AI can also be integrated as a safety enabler, for example, by providing technologies to monitor health and safety in the workplace to prevent fatigue and injury [ 75 ].

3.1.4 Data management

Since AI adoption in the organization is strongly data-driven, the ‘data management’ supercategory is dedicated to the comprehensive aspects related to the effective and responsible management of data within the organization.

Data privacy must be guaranteed when creating AI applications based on industrial production data [ 49 , 58 , 59 , 60 , 72 , 76 , 78 , 79 , 82 , 88 , 89 , 91 , 94 ] as ‘[M]anufacturing industries generate large volumes of unstructured and sensitive data during their daily operations’ [ 89 ]. Closely related to this is the need for anonymization and confidentiality of data [ 61 , 69 , 70 , 78 ]. The availability of large, heterogeneous data sets is essential for the digital transformation of organizations [ 52 , 59 , 78 , 80 , 88 , 89 ] and is considered one of the key drivers of AI innovation [ 62 , 68 , 72 , 86 ]. In production systems, lack of data availability is often a barrier to AI adoption [ 58 , 70 , 77 ]. In order to enable AI to establish relationships between data, the availability of large input data that is critical [ 62 , 76 , 81 ]. New AI models are trained with this data and can adapt as well as improve as they receive new data [ 59 , 62 ]. Big data can thus significantly improve the quality of AI applications [ 59 , 71 ]. As more and more data is generated in manufacturing [ 85 ], AI opens up new opportunities for companies to make use of it [ 62 ]. However, operational data are often unstructured, as they come from different sources and exist in diverse formats [ 85 , 87 ]. This challenges data processing, as data quality and origin are key factors in the management of data [ 78 , 79 , 80 , 88 , 89 , 91 ]. To make production data valuable and usable for AI, consistency of data and thus data integrity is required across manufacturing systems [ 50 , 62 , 77 , 84 ]. Another key prerequisites for AI adoption is data governance [ 56 , 59 , 67 , 68 , 71 , 78 , 88 ] which is an important asset to make use of data in production [ 50 ] and ensure the complex management of heterogenous data sets [ 89 ]. The interoperability of data and thus the foundation for the compatibility of AI with existing systems, i.e., the extent to which AI matches existing processes, structures, and infrastructures [ 53 , 56 , 84 , 93 ], is considered another important requirement for the adoption of AI in IT systems. Data interoperability in production systems can be hindered by missing data standards as different machines use different formats [ 87 ]. Data processing refers to techniques used to preparing data for analysis which is essential to obtain consistent results from data analytics in production [ 58 , 72 , 80 , 81 , 84 ]. In this process, the numerous, heterogeneous data from different sensors are processed in such a way that they can be used for further analyses [ 87 ]. The capability of production firms to process data and information is thus important to enable AI adoption [ 77 , 86 , 93 ]. With the increasing data generation in the smart and connected factory, the strategic relevance of data analytics is gaining importance [ 55 , 69 , 78 ], as it is essential for AI systems in performing advanced data analyses [ 49 , 67 , 72 , 86 , 88 ]. Using analytics, valuable insights can be gained from the production data obtained using AI systems [ 58 , 77 , 87 ]. In order to enable the processing of big data, a profound data infrastructure is necessary [ 65 , 75 , 87 ]. Facilities must be equipped with sensors, that collect data and model information, which requires investments from firms [ 72 ]. In addition, production firms must build the necessary skills, culture and capabilities for data analytics [ 54 , 75 , 87 , 93 ]. Data storage, one of the foundations and prerequisites for smart manufacturing [ 54 , 68 , 71 , 74 ], must be ensured in order to manage the larg amounts of data and thus realize the adoption of intelligent technologies in production [ 50 , 59 , 72 , 78 , 84 , 87 , 88 , 89 ].

3.2 External environment

The external drivers of AI adoption in production influence the organization through conditions and events from outside the firm and are therefore difficult to control by the organization itself.

3.2.1 Regulatory environment

This supercategory captures the broader concept of establishing rules, standards, and frameworks that guide the behavior, actions, and operations of individuals, organizations, and societies when implementing AI.

AI adoption in production faces many ethical challenges [ 70 , 72 , 79 ]. AI applications must be compliant with the requirements of organizational ethical standards and laws [ 49 , 50 , 59 , 60 , 62 , 75 ] which is why certain issues must be examined in AI adoption and AI design [ 62 , 73 , 82 , 91 ] so that fairness and justice are guaranteed [ 78 , 79 , 92 ]. Social rights, cultural values and norms must not be violated in the process [ 49 , 52 , 53 , 81 ]. In this context, the explainability and transparency of AI decisions also plays an important role [ 50 , 54 , 58 , 70 , 78 , 89 ] and can address the characteristic of AI of a black box [ 90 ]. In addition, AI applications must be compliant with legal and regulatory requirements [ 51 , 52 , 59 , 77 , 81 , 82 , 91 ] and be developed accordingly [ 49 , 76 ] in order to make organization processes using AI clear and effective [ 65 ]. At present, policies and regulation of AI are still in its infancy [ 49 ] and missing federal regulatory guidelines, standards as well as incentives hinder the adoption of AI [ 67 ] which should be expanded simultaneously to the expansion of AI technology [ 60 ]. This also includes regulations on the handling of data (e.g. anonymization of data) [ 61 , 72 ].

3.2.2 Business environment

The factors in the ‘business environment’ supercategory refer to the external conditions and influences that affect the operations, decision making, and performance of the company seeking to implement AI in a production context.

Cooperation and collaboration can influence the success of digital technology adoption [ 52 , 53 , 59 , 72 ], which is why partnerships are important for adoption [ 53 , 59 ] and can positively influence its future success [ 52 , 67 ]. Both intraorganizational and interorganizational knowledge sharing can positively influence AI adoption [ 49 ]. In collaborations, companies can use a shared knowledge base where data and process sharing [ 51 , 59 , 94 ] as well as social support systems strengthen feedback loops between departments [ 79 , 80 ]. With regard to AI adoption in firms, vendors as well as service providers need to collaborate closely to improve the compatibility and operational capability of smart technologies across different industries [ 82 , 93 ]. Without external IT support, companies can rarely integrate AI into their production processes [ 66 ], which is why thorough support from vendors can significantly facilitate the integration of AI into existing manufacturing processes [ 80 , 91 ]. Public–private collaborations can also add value and governments can target AI dissemination [ 60 , 74 ]. The support of the government also positively influences AI adoption. This includes investing in research projects and policies, building a regulatory setting as well as creating a collaborative environment [ 60 ]. Production companies are constantly exposed to changing conditions, which is why the dynamics of the environment is another factor influencing the adoption of AI [ 52 , 63 , 72 , 86 ]. Environmental dynamics influence the operational performance of firms and can favor an entrepreneurial orientation of firms [ 86 ]. In order to respond to dynamics, companies need to develop certain capabilities and resources (i.e. dynamic capabilities) [ 86 ]. This requires the development of transparency, agility, as well as resilience to unpredictable changes, which was important in the case of the COVID-19 pandemic, for example, where companies had to adapt quickly to changing environments [ 75 ]. A firm’s environment (e.g. governments, partners or customers) can also pressure companies to adopt digital technologies [ 53 , 67 , 82 , 91 ]. Companies facing intense competition are considered more likely to invest in smart technologies, as rivalry pushes them to innovate and they hope to gain competitive advantages from adoption [ 36 , 66 , 82 , 93 ].

3.2.3 Economic environment

By considering both the industrial sector and country within the subcategory ‘economic environment’, production firms can analyze the interplay between the two and understand how drivers can influence the AI adoption process in their industrial sector’s performance within a particular country.

The industrial sector of a firm influences AI adoption in production from a structural perspective, as it indicates variations in product characteristics, governmental support, the general digitalization status, the production environment as well as the use of AI technologies within the sector [ 36 ]. Another factor that influences AI adoption is the country in which a company is located. This influences not only cultural aspects, the availability of know-how and technology orientation, but also regulations, laws, standards and subsidies [ 36 ]. From another perspective, AI can also contribute to the wider socio-economic growth of economies by making new opportunities easily available and thus equipping e.g. more rural areas with advanced capabilities [ 78 ].

3.3 Future research directions

The analysis of AI adoption in production requires a comprehensive analysis of the various factors that influence the introduction of the innovation. As discussed by Kinkel, Baumgartner, Cherubini [ 36 ], our research also concludes that organizational factors have a particularly important role to play. After evaluating the individual drivers of AI adoption in production in detail in this qualitative synthesis, we draw a conclusion from the results and derive a research agenda from the analysis to serve as a basis for future research. The RQs emerged from the analyzed factors and are presented in Table  2 . We developed the questions based on the literature review and identified research gaps for every factor that was most frequently mentioned. From the factors analyzed and RQs developed, the internal environment has a strong influence on AI adoption in production, and organizational factors play a major role here.

Looking at the supercategory ‘business and environment’, performance indicators and investments are considered drivers of AI adoption in production. Indicators to measure the performance of AI innovations are necessary here so that managers can perform cost–benefit analyses and make the right decision for their company. There is a need for research here to support possible calculations and show managers a comprehensive view of the costs and benefits of technology in production. In terms of budget, it should be noted that AI adoption involves a considerable financial outlay that must be carefully weighed and some capital must be available to carry out the necessary implementation efforts (e.g., staffing costs, machine retrofits, change management, and external IT service costs). Since AI adoption is a complex process and turnkey solutions can seldom be implemented easily and quickly, but require many changes (not only technologically but also on an organizational level), it is currently difficult to estimate the necessary budgets and thus make them available. Especially the factors of the supercategory ‘organizational effectiveness’ drive AI adoption in production. Trust of the workforce is considered an important driver, which must be created in order to successfully implement AI. This requires measures that can support management in building trust. Closely related to this are the necessary change management processes that must be initiated to accompany the changes in a targeted manner. Management itself must also play a clear role in the introduction of AI and communicate its support, as this also influences the adoption. The development of clear processes and measures can help here. Developing roadmaps for AI adoption can facilitate the adoption process and promote strategic integration with existing IT and business strategy. Here, best practice roadmaps and necessary action steps can be helpful for companies. Skills are considered the most important driver for AI adoption in manufacturing. Here, there is a lack of clear approaches that support companies in identifying the range of necessary skills and, associated with this, also opportunities to further develop these skills in the existing workforce. Also, building a culture of innovation requires closer research that can help companies foster a conducive environment for AI adoption and the integration of other smart technologies. Steps for developing a positive mindset require further research that can provide approaches for necessary action steps and measures in creating a positive digital culture. With regard to ‘technology and system’, the factors of IT infrastructure and security in particular are driving AI adoption in production. Existing IT systems must reach a certain maturity to enable AI adoption on a technical level. This calls for clear requirements that visualize for companies which systems and standards are in place and where developments are needed. Security must be continuously ensured, for which certain standards and action catalogs must be developed. With regard to the supercategory ‘data management’, the availability of data is considered the basis for successful AI adoption, as no AI can be successfully deployed without data. In the production context in particular, this requires developments that support companies in the provision of data, which usually arises from very heterogeneous sources and forms. Data analytics must also be closely examined, and production companies usually need external support in doing so. The multitude of data also requires big data storage capabilities. Here, groundwork is needed to show companies options about the possibilities of different storage options (e.g., on premis vs. cloud-based).

In the ‘regulatory environment’, ethics in particular is considered a driver of AI adoption in production. Here, fundamental ethical factors and frameworks need to be developed that companies can use as a guideline to ensure ethical standards throughout the process. Cooperations and environmental dynamism drive the supercategory ‘business environment’. Collaborations are necessary to successfully implement AI adoption and action is needed to create the necessary contact facilitation bodies. In a competitive environment, companies have to make quick decisions under strong pressure, which also affects AI adoption. Here, guidelines and also best practice approaches can help to simplify decisions and quickly demonstrate the advantage of the solutions. There is a need for research in this context.

4 Conclusions

The use of AI technologies in production continues to gain momentum as managers hope to increase efficiency, productivity and reduce costs [ 9 , 13 , 20 ]. Although the benefits of AI adoption speak for themselves, implementing AI is a complex decision that requires a lot of knowledge, capital and change [ 95 ] and is influenced by various internal and external factors. Therefore, managers are still cautious about implementing the technology in a production context. Our SLR seeks to examine the emergent phenomenon of AI in production with the precise aim of understanding the factors influencing AI adoption and the key topics discussed in the literature when analyzing AI in a production context. For this purpose, we use the current state of research and examine the existing studies based on the methodology of a systematic literature analysis and respond to three RQs.

We answer RQ1 by closely analyzing the literature selected in our SLR to identify trends in current research on AI adoption in production. In this process, it becomes clear that the topic is gaining importance and that research has increased over the last few years. In the field of production, AI is being examined from various angles and current research addresses aspects from a business, human and technical perspective. In our response to RQ2 we synthesized the existing literature to derive 35 factors that influence AI adoption in production at different levels from inside or outside the organization. In doing so, we find that AI adoption in production poses particularly significant challenges to organizational effectiveness compared to other digital technologies and that the relevance of data management takes on a new dimension. Production companies often operate more traditionally and are sometimes rigid when it comes to change [ 96 , 97 ], which can pose organizational challenges when adopting AI. In addition, the existing machines and systems are typically rather heterogeneous and are subject to different digitalization standards, which in turn can hinder the availability of the necessary data for AI implementation [ 98 , 99 ]. We address RQ3 by deriving a research agenda, which lays a foundation for further scientific research and deepening the understanding of AI adoption in production. The results of our analysis can further help managers to better understand AI adoption and to pay attention to the different factors that influence the adoption of this complex technology.

4.1 Contributions

Our paper takes the first step towards analysing the current state of the research on AI adoption from a production perspective. We represent a holistic view on the topic, which is necessary to get a better understanding of AI in a production-context and build a comprehensive view on the different dimensions as well as factors influencing its adoption. To the best of our knowledge, this is the first contribution that systematises research about the adoption of AI in production. As such, it makes an important contribution to current AI and production research, which is threefold:

First, we highlight the characteristics of studies conducted in recent years on the topic of AI adoption in production, from which several features and developments can be deduced. Our results confirm the topicality of the issue and the increasing relevance of research in the field.

Having laid the foundations for understanding AI in production, we focused our research on the identification and systematization of the most relevant factors influencing AI adoption in production at different levels. This brings us to the second contribution, our comprehensive factor analysis of AI adoption in production provides a framework for further research as well as a potential basis for managers to draw upon when adopting AI. By systematizing the relevant factors influencing AI adoption in production, we derived a set of 35 researched factors associated with AI adoption in production. These factors can be clustered in two areas of analysis and seven respective supercategories. The internal environment area includes four levels of analysis: ‘business and structure’ (focusing on financial aspects and firm characteristics), ‘organizational effectiveness’ (focusing on human-centred factors), ‘technology and system’ (based on the IT infrastructure and systems) as well as ‘data management’ (including all data related factors). Three categories are assigned to the external environment: the ‘regulatory environment’ (such as ethics and the regulatory forms), the ‘business environment’ (focused on cooperation activities and dynamics in the firm environment) and the ‘economic environment’ (related to sectoral and country specifics).

Third, the developed research plan as outlined in Table  2 serves as an additional outcome of the SLR, identifying key RQs in the analyzed areas that can serve as a foundation for researchers to expand the research area of AI adoption in production. These RQs are related to the mostly cited factors analyzed in our SLR and aim to broaden the understanding on the emerging topic.

The resulting insights can serve as the basis for strategic decisions by production companies looking to integrate AI into their processes. Our findings on the factors influencing AI adoption as well as the developed research agenda enhance the practical understanding of a production-specific adoption. Hence, they can serve as the basis for strategic decisions for companies on the path to an effective AI adoption. Managers can, for example, analyse the individual factors in light of their company as well as take necessary steps to develop further aspects in a targeted manner. Researchers, on the other hand, can use the future research agenda in order to assess open RQs and can expand the state of research on AI adoption in production.

4.2 Limitations

Since a literature review must be restricted in its scope in order to make the analyses feasible, our study provides a starting point for further research. Hence, there is a need for further qualitative and quantitative empirical research on the heterogeneous nature of how firms configure their AI adoption process. Along these lines, the following aspects would be of particular interest for future research to improve and further validate the analytical power of the proposed framework.

First, the lack of research on AI adoption in production leads to a limited number of papers included in this SLR. As visualized in Fig.  2 , the number of publications related to the adoption of AI in production has been increasing since 2018 but is, to date, still at an early stage. For this reason, only 47 papers published until May 2024 addressing the production-specific adoption of AI were identified and therefore included in our analysis for in-depth investigation. This rather small number of papers included in the full-text analysis gives a limited view on AI adoption in production but allows a more detailed analysis. As the number of publications in this research field increases, there seems to be a lot of research happening in this field which is why new findings might be constantly added and developed as relevant in the future [ 39 ]. Moreover, in order to research AI adoption from a more practical perspective and thus to build up a broader, continuously updated view on AI adoption in production, future literature analyses could include other publication formats, e.g. study reports of research institutions and companies, as well discussion papers.

Second, the scope of the application areas of AI in production has been increasing rapidly. Even though our overview of the three main areas covered in the recent literature serves as a good basis for identifying the most dominant fields for AI adoption in production, a more detailed analysis could provide a better overview of possibilities for manufacturing companies. Hence, a further systematisation as well as evaluation of application areas for AI in production can provide managers with the information needed to decide where AI applications might be of interest for the specific company needs.

Third, the systematisation of the 35 factors influencing AI adoption in production serve as a good ground for identifying relevant areas influenced by and in turn influencing the adoption of AI. Further analyses should be conducted in order to extend this view and extend the framework. For example, our review could be combined with explorative research methods (such as case studies in production firms) in order to add the practical insights from firms adopting AI. This integration of practical experiences can also help exploit and monitor more AI-specific factors by observing AI adoption processes. In enriching the factors through in-depth analyses, the results of the identified AI adoption factors could also be examined in light of theoretical contributions like the technology-organization-environment (TOE) framework [ 47 ] and other adoption theories.

Fourth, in order to examine the special relevance of identified factors for AI adoption process and thus to distinguish it from the common factors influencing the adoption of more general digital technologies, there is a further need for more in-depth (ethnographic) research into their impacts on the adoption processes, particularly in the production context. Similarly, further research could use the framework introduced in this paper as a basis to develop new indicators and measurement concepts as well as to examine their impacts on production performance using quantitative methods.

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Heimberger, H., Horvat, D. & Schultmann, F. Exploring the factors driving AI adoption in production: a systematic literature review and future research agenda. Inf Technol Manag (2024). https://doi.org/10.1007/s10799-024-00436-z

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Background: Type 2 diabetes mellitus and cardiovascular illnesses are two metabolic conditions that are greatly influenced by insulin resistance (IR). Identifying genetic markers associated with IR can offer insights into its mechanisms and potential therapeutic targets. Objective: This study investigated the association between four single nucleotide polymorphisms (SNPs) and insulin resistance among 191 individuals in the Indian population. Methods: A literature review identified four SNPs linked to IR. Participants were divided into groups based on insulin resistance and sensitivity, determined by the Homeostasis Model Assessment for Insulin Resistance (HOMA2-IR). DNA was extracted for genotyping using Illumina Infinium Global Screening Array (GSA) V3. Case-control analysis assessed SNP-genotype associations with insulin resistance and other clinical parameters. Results: Among 191 participants, 57 were insulin-resistant and 134 were insulin-sensitive. Significant associations (P < 0.05) were found between selected SNPs and IR. SNP rs920590 showed the strongest association, with the T allele associated with increased IR risk (odds ratio = 4.01, 95% CI 1.55-10.34; p < 0.0014). Additionally, serum LDL cholesterol, serum triglycerides, HbA1c, Insulin fasting and fat mass show significant differences in cases and controls. Conclusion: This study validates genetic markers linked to insulin resistance (IR) in the Indian population and elucidates their roles in IR pathogenesis. Understanding these markers can inform personalised therapeutic strategies for metabolic disorders.

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This study was funded by Answer Genomics Pvt Limited.

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The study protocol received approval from the Answer Genomics Ethical Review Committee. REF.NO.:10/NRT/23-24 AERC Number:10001/AERC/24 I am pleased to inform you that the aforementioned study has been approved by the Answergenomics Ethical Review Committee (AERC) in accordance with the compliance of the Section 4, National Ethical Guidelines for Biomedical and Health Research Involving Human Participants, ICMR (2017). All research activities must be conducted in accordance with the approved submission. It is your responsibility to fulfil the following requirements of approval: 1. Changes, amendments and addenda to the protocol, informed consent, or other study materials must be submitted to AERC for re-review and approval prior to implementation. 2. Any unanticipated problems, adverse events, protocol violations, social harm, or any new information becoming available which could change the risk/benefit ratio must be reported to the AERC. The AERC concluded that the Principal Investigator has taken sufficient safeguards to carry out the study. Therefore, the AERC approves the proposal for conducting the survey submitted in the protocol. This approval is based on your submission of study protocol (refer email [email protected] dated 29/12/2024) Any deviation from this protocol will require further approval of the AERC. This is valid for one year from the date of approval, mentioned geographical location and presented sample. After the completion of the study, please submit the study report to the AERC.

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