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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.

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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 !

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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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Literature Reviews

• What is a literature review?
• Steps in the Literature Review Process
• Define your research question
• Determine inclusion and exclusion criteria
• Choose databases and search
• Review Results
• Synthesize Results
• Analyze Results
• Librarian Support

What is a Literature Review?

A literature or narrative review is a comprehensive review and analysis of the published literature on a specific topic or research question. The literature that is reviewed contains: books, articles, academic articles, conference proceedings, association papers, and dissertations. It contains the most pertinent studies and points to important past and current research and practices. It provides background and context, and shows how your research will contribute to the field. 

A literature review should: 

• Provide a comprehensive and updated review of the literature;
• Explain why this review has taken place;
• Articulate a position or hypothesis;
• Acknowledge and account for conflicting and corroborating points of view

From  S age Research Methods

Purpose of a Literature Review

A literature review can be written as an introduction to a study to:

• Demonstrate how a study fills a gap in research
• Compare a study with other research that's been done

Or it can be a separate work (a research article on its own) which:

• Organizes or describes a topic
• Describes variables within a particular issue/problem

Limitations of a Literature Review

Some of the limitations of a literature review are:

• It's a snapshot in time. Unlike other reviews, this one has beginning, a middle and an end. There may be future developments that could make your work less relevant.
• It may be too focused. Some niche studies may miss the bigger picture.
• It can be difficult to be comprehensive. There is no way to make sure all the literature on a topic was considered.
• It is easy to be biased if you stick to top tier journals. There may be other places where people are publishing exemplary research. Look to open access publications and conferences to reflect a more inclusive collection. Also, make sure to include opposing views (and not just supporting evidence).

Source: Grant, Maria J., and Andrew Booth. “A Typology of Reviews: An Analysis of 14 Review Types and Associated Methodologies.” Health Information & Libraries Journal, vol. 26, no. 2, June 2009, pp. 91–108. Wiley Online Library, doi:10.1111/j.1471-1842.2009.00848.x.

Meryl Brodsky : Communication and Information Studies

Hannah Chapman Tripp : Biology, Neuroscience

Carolyn Cunningham : Human Development & Family Sciences, Psychology, Sociology

Larayne Dallas : Engineering

Janelle Hedstrom : Special Education, Curriculum & Instruction, Ed Leadership & Policy ​

Susan Macicak : Linguistics

Imelda Vetter : Dell Medical School

For help in other subject areas, please see the guide to library specialists by subject .

Periodically, UT Libraries runs a workshop covering the basics and library support for literature reviews. While we try to offer these once per academic year, we find providing the recording to be helpful to community members who have missed the session. Following is the most recent recording of the workshop, Conducting a Literature Review. To view the recording, a UT login is required.

• October 26, 2022 recording
• Last Updated: Oct 26, 2022 2:49 PM
• URL: https://guides.lib.utexas.edu/literaturereviews

Libraries | Research Guides

Literature reviews, what is a literature review, learning more about how to do a literature review.

• Planning the Review
• The Research Question
• Choosing Where to Search
• Organizing the Review
• Writing the Review

A literature review is a review and synthesis of existing research on a topic or research question. A literature review is meant to analyze the scholarly literature, make connections across writings and identify strengths, weaknesses, trends, and missing conversations. A literature review should address different aspects of a topic as it relates to your research question. A literature review goes beyond a description or summary of the literature you have read. 

• Sage Research Methods Core Collection This link opens in a new window SAGE Research Methods supports research at all levels by providing material to guide users through every step of the research process. SAGE Research Methods is the ultimate methods library with more than 1000 books, reference works, journal articles, and instructional videos by world-leading academics from across the social sciences, including the largest collection of qualitative methods books available online from any scholarly publisher. – Publisher

• Next: Planning the Review >>
• Last Updated: Jan 17, 2024 10:05 AM
• URL: https://libguides.northwestern.edu/literaturereviews

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

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

• Getting Started
• How to Pick a Topic
• Strategies to Find Sources
• Evaluating Sources & Lit. Reviews
• Tips for Writing Literature Reviews
• Writing Literature Review: Useful Sites
• Citation Resources
• Other Academic Writings

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

• UConn Health subject guide on systematic reviews Explanation of the different review types used in health sciences literature as well as tools to help you find the right review type
• << Previous: Getting Started
• Next: How to Pick a Topic >>
• Last Updated: Sep 21, 2022 2:16 PM
• URL: https://guides.lib.uconn.edu/literaturereview

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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.

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 .

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Undertaking a literature review in marketing

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T1 - Undertaking a literature review in marketing

AU - Gabbott, Mark

N2 - Writing a literature review is often considered to be one of the most difficult tasks a student will undertake and is often the most significant part of the academic contribution of essays and theses. Academia is a broad and inclusive community and all research takes place within the context of others work. It is therefore imperative that we review current knowledge before we can advance. This article provides guidelines for the construction of a literature review in marketing and focuses upon three key tasks. The first is the identification and sourcing of literature. The second is the interpretation and critical understanding of what has been collected and the third is the preparation and writing of the final document. Within these three tasks a number of suggestions and examples are given to aid anyone starting to prepare a marketing literature review.

AB - Writing a literature review is often considered to be one of the most difficult tasks a student will undertake and is often the most significant part of the academic contribution of essays and theses. Academia is a broad and inclusive community and all research takes place within the context of others work. It is therefore imperative that we review current knowledge before we can advance. This article provides guidelines for the construction of a literature review in marketing and focuses upon three key tasks. The first is the identification and sourcing of literature. The second is the interpretation and critical understanding of what has been collected and the third is the preparation and writing of the final document. Within these three tasks a number of suggestions and examples are given to aid anyone starting to prepare a marketing literature review.

KW - literature

KW - retrieval

KW - critical review

KW - writing-up

M3 - Article

SN - 1469-347X

JO - The Marketing review

JF - The Marketing review

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What is a literature review

“A literature review is a description of the literature relevant to a particular field or topic. It gives an overview of what has been said, who the key writers are, what are the prevailing theories and hypotheses, what questions are being asked, and what methods and methodologies are appropriate and useful" (Emerald Insight).

A literature review  is not  just a summary of everything you have read on the topic.  It is a critical analysis of the existing research relevant to your topic, and you should show how the literature relates to your topic and identify any gaps in the area of research. Our Learning Hub has lots of useful guidance for carrying out a  Literature Review .

How is it different?

It's on a much larger scale from your research for previous modules.

You may need to devise new ways of searching and managing your results.

Think about:

• Using RefWorks to manage your references
• Setting up alerts to retrieve new results for your searches

How to carry out a review

• Devise a search strategy
• Search systematically
• Read critically – i.e. deconstruct the material
• Put it all back together – reconstruct

1. Devise a search strategy

Think about the sort of research that would help your project.

1. What subject areas does you topic fall into?

2. What possible sources could you use? Think broadly, for example:

• Company reports
• Industry profiles
• Market research
• Financial reports
• Newspaper articles
• Journal articles

3. What don't you want?  What are the limits? For example, geographical restrictions or time periods.

2. Search systematically

• Plan your search first, thinking about your keywords
• Use the pages on this LibGuide to identify quality resources
• Use the tutorials and advice on those pages to improve your searches
• Use the  Inter Library Loans service  to borrow books or to obtain copies of papers which aren't in the library
• Speak to the Business Librarians for help with your searches, or to recommend new items for library stock
• Look at the programme of  Succeed @ Tees workshops , and attend any which are relevant.

3. Read critically - i.e. deconstruct your results

Read critically, argument: .

• What is the main argument?
• Is the main argument clear and logical?
• What is the evidence?
• Is the evidence valid?
• Does the evidence support the conclusions?

4. Put it all back together – reconstruct

• Group your topic areas – develop themes
• Briefly summarise key findings

- See Phrasebank for suggestions of how to phrase your sentences.

• Use the academic papers as examples of the style of academic writing as well as for their content
• Check your referencing

Succeed@Tees Workshops: Writing a Literature Review

The following workshop will help you to develop your skills in writing a literature review :

Writing a literature review

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Literature Reviews

• Getting started

What is a literature review?

Why conduct a literature review, stages of a literature review, lit reviews: an overview (video), check out these books.

• Types of reviews
• 1. Define your research question
• 2. Plan your search
• 3. Search the literature
• 4. Organize your results
• 5. Synthesize your findings
• 6. Write the review
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• Need to write a systematic review? This link opens in a new window

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Definition: A literature review is a systematic examination and synthesis of existing scholarly research on a specific topic or subject.

Purpose: It serves to provide a comprehensive overview of the current state of knowledge within a particular field.

Analysis: Involves critically evaluating and summarizing key findings, methodologies, and debates found in academic literature.

Identifying Gaps: Aims to pinpoint areas where there is a lack of research or unresolved questions, highlighting opportunities for further investigation.

Contextualization: Enables researchers to understand how their work fits into the broader academic conversation and contributes to the existing body of knowledge.

tl;dr  A literature review critically examines and synthesizes existing scholarly research and publications on a specific topic to provide a comprehensive understanding of the current state of knowledge in the field.

What is a literature review NOT?

❌ An annotated bibliography

❌ Original research

❌ A summary

❌ Something to be conducted at the end of your research

❌ An opinion piece

❌ A chronological compilation of studies

The reason for conducting a literature review is to:

Literature Reviews: An Overview for Graduate Students

While this 9-minute video from NCSU is geared toward graduate students, it is useful for anyone conducting a literature review.

Writing the literature review: A practical guide

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Writing literature reviews: A guide for students of the social and behavioral sciences

Available online!

So, you have to write a literature review: A guided workbook for engineers

Telling a research story: Writing a literature review

The literature review: Six steps to success

Systematic approaches to a successful literature review

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Doing a systematic review: A student's guide

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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: 
• 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  

• 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. 
• 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. 
• 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. 
• 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. 
• 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. 
• 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. 

How to write a good literature review

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. 

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. 

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 literature review is an ongoing process, and it may be necessary to revisit and update it as your research progresses. 

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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A Step-by-Step Guide to Writing a Stellar Literature Review (with Help from AI)

Table of contents

Aren’t all of us mini versions of Sherlock Holmes when browsing data and archives for a research piece? As we go through the process, a comprehensive literature review is an essential toolkit to make your research shine.

A literature review consists of scholarly sources that validate the content. Its primary objective is to offer a concise summary of the research and to let you explore relevant theories and methodologies. Through this review, you can identify gaps in the existing research and bridge them with your contribution. 

The real challenge is how to write an excellent literature review. Let’s learn.

What is the purpose of a literature review?

A literature review is an introduction to your research. It helps you put your perspective to the table, along with a summary of the theme.

What does my literature review communicate?

• Explanation of your research: how the information was collected, the research method, the justification of the chosen data sources, and an overview of the data analysis.
• Framework: the journey from where the concept began and how it is presented.
• Connects the previous and current research: 

It presents the broader scope of your research by connecting it to the existing data and debates and underlining how your content fits the prevailing studies. 

In an era of information overload, a literature review must be well-structured. 

Let’s learn all about the structure and style of a literature review that’ll help you strengthen your research.

Literature review– structure and style

Begin with a question and end it with the solution– the key to structuring a literature review. It resembles an essay’s format, with the first paragraph introducing the readers to the topic and the following explaining the research in-depth.

The conclusion reiterates the question and summarizes the overall insights of your research. There’s no word count restriction. —it depends on the type of research. For example, a dissertation demands lengthy work, whereas a short paper needs a few pages. 

In a literature review, maintaining high quality is vital, with a focus on academic writing style. Informal language should be avoided in favor of a more formal tone. 

The content avoids contractions, clearly differentiating between previous and current research through the use of past and present tense. Wordtune assists in establishing a formal tone, enhancing your work with pertinent suggestions. This AI-powered tool ensures your writing remains genuine, lucid, and engaging. 

The option of refining the tonality offers multiple possibilities for rephrasing a single sentence. Thus, pick the best and keep writing.

Get Wordtune for free > Get Wordtune for free >

Your friendly step-by-step guide to writing a literary review (with help from AI)

Do you find it challenging to begin the literature review? Don’t worry! We’re here to get you started with our step-by-step guide.

1. Narrow down the research scope

Simply begin with the question: What am I answering through my research?

Whether it’s cooking or painting, the real challenge is the prep-up for it rather than performing the task. Once you’re done, it smoothly progresses. Similarly, for your literature review, prepare the groundwork by narrowing down the research scope.

Browse and scoop out relevant data inclining well with your research. While you can’t cover every aspect of your research, pick a topic that isn’t too narrow nor too broad to keep your literature review well-balanced. 

2. Hunt relevant literature

The next question: Does this data align with the issue I’m trying to address?

As you review sources of information, hunt out the best ones. Determine which findings help in offering a focused insight on your topic. The best way to pick primary sources is to opt for the ones featured in reliable publications. You can also choose secondary sources from other researchers from a reasonable time frame and a relevant background.

For example, if your research focuses on the Historical Architecture of 18th-century Europe, the first-hand accounts and surveys from the past would hold more weight than the new-age publications. 

3. Observe the themes and patterns in sources

Next comes: What is the core viewpoint in most of the research? Has it stayed constant over time, or have the authors differed in their points of view?

Ensure to scoop out the essential aspects of what each source represents. Once you have collected all this information, combine it and add your interpretations at the end. This process is known as synthesis.

Synthesize ideas by combining arguments, findings and forming your new version.

4. Generate an outline

The next question: How can I organize my review effectively? When navigating multiple data sources, you must have noticed a structure throughout the research. Develop an outline to make the process easier. An outline is a skeletal format of the review, helping you connect the information more strategically.

Here are the three different ways to organize an outline– Chronologically, Thematically, or by Methodology.You can develop the outline chronologically, starting from the older sources and leading to the latest pieces. Another way of organizing is to thematically divide the sections and discuss each under the designated sub-heading.

You can even organize it per the research methods used by the respective authors. The choice of outline depends on the subject. For example, in the case of a science paper, you can divide the information into sections like introduction, types of equipment, method, procedure, findings, etc. In contrast, it’s best to present it in divisions based on timelines like Ancient, Middle Ages, Industrial revolutions, etc., for a history paper.

If you’re confused about how to structure the data, work with Wordtune. 

With the Generate with AI feature, you can mention your research topic and let Wordtune curate a comprehensive outline for your study.

Having a precise prompt is the key to getting the best results.

5. Start filling!

Your next question must be: Am I ready to compose all the parts of the literature review?

Once you’re ready with the basic outline and relevant sources, start filling in the data. Go for an introductory paragraph first to ensure your readers understand the topic and how you will present it. Ensure you clearly explain the section in the first sentence.

However, if beginning from the first paragraph seems intimidating, don’t worry! Add the main body content to the sub-headings, then jump to the introduction. 

Add headings wherever possible to make it more straightforward and guide your readers logically through different sources. Lastly, conclude your study by presenting a key takeaway and summarizing your findings. To make your task easier, work with Wordtune. It helps align your content with the desired tone and refine the structure.

6. Give attention to detail and edit

The last question: Am I satisfied with the language and content written in the literature review? Is it easy to understand?

Once you’re done writing the first draft of a literature review, it’s time to refine it. Take time between writing and reading the draft to ensure a fresh perspective. It makes it easier to spot errors when you disconnect from the content for some time. Start by looking at the document from a bird's eye to ensure the formatting and structure are in order. 

After reviewing the content format, you must thoroughly check your work for grammar, spelling, and punctuation. One of the best approaches to editing and proofreading is to use Wordtune . It helps simplify complex sentences, enhance the content quality, and gain prowess over the tonality.

The dos and don’ts of writing a literature review

Writing a stellar literature review requires following a few dos and don'ts. Just like Sherlock Holmes would never overlook a hint, you must pay attention to every minute detail while writing a perfect narrative. To help you write, below are some dos and don'ts to remember.

Composing a literature review demands a holistic research summary, each part exhibiting your understanding and approach. As you write the content, make sure to cover the following points:

• Keep a historical background of the field of research. Highlight the relevant relation between the old studies and your new research.
• Discuss the core issue, question, and debate of your topic.
• Theories lay the foundation of research. While you’re writing a literature review, make sure to add relevant concepts and ideas to support your statements.
• Another critical thing to keep in mind is to define complex terminologies. It helps the readers understand the content with better clarity. 

Examples of comprehensive literature reviews

Aren’t good examples the best way to understand a subject? Let’s look into a few examples of literature reviews and analyze what makes them well-written.

1. Critical Thinking and Transferability: A Review of the Literature (Gwendolyn Reece)

An overview of scholarly sources is included in the literature review, which explores critical thinking in American education. The introduction stating the subject’s importance makes it a winning literature review. Following the introduction is a well-defined purpose that highlights the importance of research.

As one keeps reading, there is more clarity on the pros and cons of the research. By dividing information into parts with relevant subheadings, the author breaks a lengthy literature review into manageable chunks, defining the overall structure.

Along with other studies and presented perspectives, the author also expresses her opinion. It is presented with minimal usage of ‘I,’ keeping it person-poised yet general. Toward the conclusion, the author again offers an overview of the study. A summary is further strengthened by presenting suggestions for future research as well. 

2. The Use of Technology in English Language Learning: A Literature Review

This literature review is thematically organized on how technology affects language acquisition. The study begins with an introduction to the topic with well-cited sources. It presents the views of different studies to help readers get a sense of different perspectives. After giving these perspectives, the author offers a personalized opinion.

One of the critical aspects that makes this a good literature review is a dedicated paragraph for definitions. It helps readers proceed further with a clear understanding of the crucial terminologies. There’s a comparison of the modern and previous studies and approaches to give an overall picture of the research.

Once the main body is composed, the author integrates recommendations for action-based tips. Thus, the literature review isn’t just summarizing the sources but offering actions relevant to the topics. Finally, the concluding paragraph has a brief overview with key takeaways.

Wordtune: your writing buddy!

A literature review demands the right balance of language and clarity. You must refine the content to achieve a formal tone and clear structure. Do you know what will help you the most? Wordtune !. 

The real-time grammar checker leaves no scope for errors and lets you retain precision in writing. This writing companion is all you need for stress-free working and comprehensive literature review development.

Let the narrative begin

A literary review isn't just about summarizing sources; it's about seamlessly bringing your perspective to the table. Always remember to set a narrative for added interest and a brilliant composition. With structure and style being the pillars of a stellar literature review, work with Wordtune to ensure zero compromises on the quality.

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Scaling customer experiences with data and AI

Integrating data and AI solutions throughout the customer experience journey can enable enterprises to become predictive and proactive, says vice president of product marketing at NICE, Andy Traba.

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In partnership with NICE

Today, interactions matter more than ever. According to data compiled by NICE, once a consumer makes a buying decision for a product or service, 80% of their decision to keep doing business with that brand hinges on the quality of their customer service experience, according to NICE research. Enter AI.

"I think AI is becoming a really integral part of every business today because it is finding that sweet spot in allowing businesses to grow while finding key efficiencies to manage that bottom line and really do that at scale," says vice president of product marketing at NICE, Andy Traba.

When many think of AI and customer experiences, chatbots that give customers more headaches than help often come to mind. However, emerging AI use cases are enabling greater efficiencies than ever. From sentiment analysis to co-pilots to integration throughout the entire customer journey, the evolving era of AI is reducing friction and building better relationships between enterprises and both their employees and customers.

"When we think about bolstering AI capabilities, it's really about getting the right data to train my models on so that they have those best outcomes."

Deploying any technology requires a delicate balance between delivering quality solutions without compromising the bottom line. AI integration offers investment returns by scaling customer and employee capabilities, automating tedious and redundant tasks, and offering consistent experiences based on collected and specialized data.

"I think as you're hopefully venturing into leveraging AI more to improve your business, the key recommendation I would provide is just to focus on those crystal clear high-probability use cases and get those early wins and then reinvest back into the business," says Traba.

While artificial intelligence has increasingly grabbed headlines in recent years, augmented intelligence—where AI tools are used to enhance human capabilities rather than automate them—is worthy of similar buzz for its potential in the customer experience space, says Traba.

Currently, the customer experience landscape is highly reactive. Looking ahead, Traba foresees a shift to proactive and predictive customer experiences that blend both AI and augmented intelligence. Say a customer’s device is reaching its end-of-life state. Rather than the customer reaching out to a chatbot or contact center, AI tools would flag the device’s issue early and direct the customer to a live chat with a representative, offering both the efficiency of automation and personalized help from a human representative.

"Where I see the future evolving in terms of customer experiences, is being much more proactive with the convergence of data, these advancements of technology, and certainly generative AI," says Traba.

This episode of Business Lab is produced in partnership with NICE.

Full Transcript

Laurel Ruma: From MIT Technology Review, I'm Laurel Ruma and this is Business Lab, the show that helps business leaders make sense of new technologies coming out of the lab and into the marketplace. Our topic is building better customer and employee experiences with artificial intelligence. Integrating data and AI solutions into everyday business can help provide insights, create efficiencies, and free up time for employees to work on more complicated issues. And all of this builds a better experience for customers. Two words for you: augmented intelligence. My guest is Andy Traba, vice president of product marketing at NICE. This podcast is produced in partnership with NICE. Welcome Andy.

Andy Traba: Hi Laurel. Thanks for having me.

Laurel : Well, thanks for being here. So to set some context, could you describe the current state of AI within customer experience? Common use cases that come to mind are chatbots, but what are some other applications for AI in this space?

Andy : Thank you. I think it's a great question to get started, and I think first and foremost, the use of AI is growing everywhere. Certainly, we had this big boom last year where everybody started talking about AI thanks to ChatGPT and a lot of the advancements with generative AI, and we're certainly seeing a lot more doing now, moving beyond just talking. So just growing a use case of trying to apply AI everywhere to improve experiences. One of the more popular ones, and this technology has been around for some time, is sentiment analysis. So instead of just proactively surveying customers to ask how are they doing, what was their experience like, using AI models to analyze the conversations they're having with brands and automatically determine that. And it's also a good use case, I think, to emphasize the importance of data that goes into the training of AI models.

As you think about sentiment analysis, you want to train those models based on the actual customer experience conversations, maybe past records or even surveys. What you want to avoid is training a sentiment model maybe based on movie reviews or Amazon reviews, something that's not really well connected. So certainly sentiment analysis is a very popular use case that goes beyond just chatbots.

Two other ones I'll bring up are co-pilots. We've seen, certainly, a lot of recent news with the launch of Microsoft Copilot and other forms for copilots within the contact center and certainly helping customer service agents. It's a very popular use case that we see. The reason driving that demand is the types of conversations that are getting to agents today are much more complex. AI has done a good job of taking away the easy stuff. We no longer have to call into a contact center to reset our passwords, so what's left over for the agents is much more difficult types of interactions.So being able to assist them in real time with prompts and guidance and recommending knowledge articles to make their job easier and more effective is really popular.

And then the third and final one just on this question is the really kind of rise of AI-driven journeys. Many, many years ago, you and I would call into a contact center, and the only channel we could use was voice. Today, those channels have exploded. There's social media, there's messaging, there's voice, there's AI assistance that we can chat with. So being able to orchestrate or navigate a customer effectively through that journey and recommend the next best action or the next best channel for them to reduce that complexity is really in demand as well. And how can I even get to a point where I can proactively engage with them on the channel of their choice at the time of day that we're likely to get a response is certainly an area that we see AI playing an important role today, but even more so in the future those three really sentiment analysis, the rise of co-pilots and then using AI across the entire customer journey.

Laurel: So as AI becomes more popular across enterprises and across industries, why is integrating AI and customer experience then so crucial for today's business landscape?

Andy: I think it's so crucial today because it's finding this sweet spot in terms of business decision-making. When we think of business decision-making, we are often challenged with, am I going to focus on revenue or cost cutting? Am I going to focus on building new products or perfecting my existing products? And rarely has there been a technology that has allowed a business to achieve all of those at once. But we're seeing that today with AI finding a sweet spot where I can improve revenue and keep customers happy and renewing or even gain new ones without having to spend additional money. I could even do that in a more efficient way with AI. Within AI, I can take a very innovative approach and produce new products that my customers demand and save time and money through efficiencies in making my current products better. I think AI is becoming a really integral part of every business today because it is finding that sweet spot in allowing businesses to grow while finding key efficiencies to manage that bottom line and really do that at scale.

Laurel: And speaking of those efficiencies, employee experience lays that foundation for the customer. But based on your time at NICE and within business operations, how does employee experience affect the overall experience then for customers?

Andy: I think what we've seen at NICE is really that customer experience and employee experience are hand in glove. They're one and the same. They have tremendous correlation between each other. Some examples, just to give some anecdotes, and this is customer experience really happening everywhere. If you go into a car dealership for a Tesla or a BMW, a high-end product, but you are interacting with a salesperson who's a little pushy or maybe just having a bad day, it's going to deteriorate the overall customer experience, so that bad employee experience causes a negative effect. Same thing if you go to your favorite local restaurant, but you maybe have a new server who's not really well-trained or is still figuring out the menu and the logistics that's going to have a negative spillover effect. And then even on the flip side of that, you can see employee experience having a positive effect on their overall customer experience.

If employees are engaged and they have the right information and the right tools, they can turn a negative into a positive. Think of airlines, a very commoditized industry right now, but if you have a problem with your flight and it got canceled and you have a critical moment of need, that employee from that airline could really turn that experience around by finding a new flight, booking you, making sure that you are on your trip and meeting your destination on time or without very little delay. So I think when we think about experiences at large and the employee and the customer outcomes are very much tied together, we've done research here at NICE on this exact topic, and what we found was once a consumer makes a buying decision for a particular product or service, after that point, 80% of that consumer's decision to continue doing business with that brand is based on the quality of their interactions.

So how those conversations play out, plays a very, very important part of whether or not they will continue doing business with that brand. Today, interactions matter more than ever. To conclude on this question, one of my favorite quotes, customer experience today isn't just part of the business, it is the business. And I think employees play a really important front role in achieving that.

Laurel: That certainly makes sense. 80% is a huge number, and I think of that in my own experiences, but could you explain the difference between artificial intelligence and augmented intelligence and also how they overlap?

Andy: Yeah, it's a great question. I think today artificial intelligence is certainly capturing all of the buzz, but what I think is just as buzzworthy is augmented intelligence. So let's start by defining the two. So artificial intelligence refers to machines mimicking human cognition. And when we think about customer experience, there's really no better example of that than chatbots or virtual assistants. Technology that allows you to interact with the brand 365 24/7 at any time that you need, and it's mimicking the conversations that you would normally have with a live human customer service representative. Augmented intelligence on the other hand, is really about AI enhancing human capabilities, increasing the cognitive load of an individual, allowing them to do more with less, saving them time. I think in the domain of customer experience, co-pilots are becoming a very popular example here. How can co-pilots make recommendations, generate responses, automate a lot of the mundane tasks that humans just don't like to do and frankly aren't good at?

So I think there's a clear distinction then between artificial intelligence, really those machines taking on the human capabilities 100% versus augmented, not replacing humans, but lifting them up, allowing them to do more. And where there's overlap, and I think we're going to see this trend really start accelerating in the years to come in customer experiences is the blend between those two as we're interacting with a brand. And what I mean by that is maybe starting out by having a conversation with an intelligent virtual agent, a chatbot, and then seamlessly blending into a human live customer representative to play a specialized role. So maybe as I'm researching a new product to buy such as a cell phone online, I can be able to ask the chatbot some questions and it's referring to its knowledge base and its past interactions to answer those. But when it's time to ask a very specific question, I might be elevated to a customer service representative for that brand, just might choose to say, "Hey, when it's time to buy, I want to ensure you're speaking to a live individual." So I think there's going to be a blend or a continuum, if you will, of these types of interactions you have. And I think we're going to get to a point where very soon we might not even know is it a human on the other end of that digital interaction or just a machine chatting back and forth? But I think those two concepts, artificial intelligence and augmented intelligence are certainly here to stay and driving improvements in customer experience at scale with brands.

Laurel: Well, there's the customer journey, but then there's also the AI journey, and most of those journeys start with data. So internally, what is the process of bolstering AI capabilities in terms of data, and how does data play a role in enhancing both employee and customer experiences?

Andy: I think in today's age, it's common understanding really that AI is only as good as the data it's trained on. Quick anecdote, if I'm an AI engineer and I'm trying to predict what movies people will watch, so I can drive engagement into my movie app, I'm going to want data. What movies have people watched in the past and what did they like? Similarly in customer experience, if I'm trying to predict the best outcome of that interaction, I want CX data. I want to know what's gone well in the past on these interactions, what's gone poorly or wrong? I don't want data that's just available on the public internet. I need specialized CX data for my AI models. When we think about bolstering AI capabilities, it's really about getting the right data to train my models on so that they have those best outcomes.

And going back to the example I brought in around sentiment, I think that reinforces the need to ensure that when we're training AI models for customer experience, it's done off of rich CX datasets and not just publicly available information like some of the more popular large language models are using.

And I think about how data plays a role in enhancing employee and customer experiences. There's a strategy that's important to derive new information or derive new data from those unstructured data sets that often these contact centers and experience centers have. So when we think about a conversation, it's very open-ended, right? It could go many ways. It is not often predictable and it's very hard to understand it at the surface where AI and advanced machine learning techniques can help though is deriving new information from those conversations such as what was the consumer's sentiment level at the beginning of the conversation versus the end. What actions did the agent take that either drove positive trends in that sentiment or negative trends? How did all of these elements play out? And very quickly you can go from taking large unstructured data sets that might not have a lot of information or signals in them to very large data sets that are rich and contain a lot of signals and deriving that new information or understanding, how I like to think of it, the chemistry of that conversation is playing a very critical role I think in AI powering customer experiences today to ensure that those experiences are trusted, they're done right, and they're built on consumer data that can be trusted, not public information that doesn't really help drive a positive customer experience.

Laurel: Getting back to your idea of customer experience is the business. One of the major questions that most organizations face with technology deployment is how to deliver quality customer experiences without compromising the bottom line. So how can AI move the needle in this way in that positive territory?

Andy: Yeah, I think if there's one word to think about when it comes to AI moving the bottom line, it's scale. I think how we think of things is really all about scale, allowing humans or employees to do more, whether that's by increasing their cognitive load, saving them time, allowing things to be more efficient. Again, that's referring back to that augmented intelligence. And then when we go through artificial intelligence thinking all about automation. So how can we offer customer experience 365 24/7? How can allowing consumers to reach out to a brand at any time that's convenient boost that customer experience? So doing both of those tactics in a way that moves the bottom line and drives results is important. I think there's a third one though that isn't receiving enough attention, and that's consistency. So we can allow employees to do more. We can automate their tasks to provide more capacity, but we also have to provide consistent, positive experiences.

And where AI and machine learning really help here is finding areas of variability, finding not only the areas of variability but then also the root cause or the driver of those variabilities to close those gaps. And a brand I'll give a shout out to who I think does this incredibly well is Starbucks. I can go to a Starbucks in any location around the world and order an iced caramel macchiato, and I'm going to get that same drink experience regardless of the thousands of Starbucks locations. And I think that consistency plays a really powerful role in the overall customer experience of Starbucks' brand. And when you think about the logistics of doing that at scale, it's incredibly complex and challenging. If you have the data and you have the right tools and the AI, finding those gaps and offering more consistent experiences is incredibly powerful.

Laurel: So could you share some practical strategies and best practices for organizations to leverage AI to empower employees, foster positive and productive work environments, and then also all of this would ultimately improve customer interactions?

Andy: Yeah, I think the overall positive, going back to earlier in our conversation is there are many use cases. AI has a tremendous opportunity in this space. The recommendation I would provide is to focus first on a crystal clear, high-probability use case for your business. Auto summary or the automated note-taking of agents after call work is becoming an increasingly popular one that we're seeing in the space. And I think the reasons for it are really clear. It's a win-win-win for the employee, the customer, and the business. It's a win for the employee because AI is going to automate something that is mundane for them or very procedural. If you think of a customer service representative, they're taking 40, 50 maybe in upwards of 60 conversations a day during their job, taking notes of what was talked about. What are action items? Very complicated, mundane, tiresome even. They don't like doing it.

So AI can offload that activity from them, which is a win for the employee. It's a win for the customer as a lot of times the agents are great at note-taking, especially when they're doing that so often, which can lead to that unfortunate experience where you have to call back as a consumer and repeat yourself because the agent you're now talking to can't understand or doesn't have good information about what you called or interacted with previously. So from a consumer experience, it helps them because they have to repeat themselves less often. The agent that they're currently speaking with can offer a more personalized service because they have better notes or history of past interactions.

And then finally, the third win, it's really good for the business because you're saving time and money that the agents no longer have to manually do something. We see that 30 to 60 seconds of note-taking at a business with 1,000 employees adds up to be millions of dollars every year. So there's a clear-cut business case for the business to achieve results, improve customer experience, and improve employee experience at the same time. I think as you're hopefully venturing into leveraging AI more to improve your business, the key recommendation I would provide is just to focus on those crystal clear high-probability use cases and get those early wins and then reinvest back into the business.

Laurel: Yeah, I think those are the positive aspects of that, but concerns about job loss due to automation tend to crop up with AI deployment. So what are the opportunities that AI integration can provide for organizations and their employees so it's a win-win for everybody?

Andy: And certainly empathetic to this topic. As with all new technologies, whenever there's excitement around them, there's also this uncertainty of what will those long-term outcomes be? But I think when we historically look back, all transformative technologies have boosted GDP and they've created more jobs. And so I see no reason to believe this time around will be different. Now those jobs might be different and new roles will emerge. When it comes to customer experience and the employee experience one interesting theory I'm following is, if you think about Apple, they had a really revolutionary model where they branded their employees geniuses. So you'd go into an Apple store and you would speak to a genius, and that model carried through all of their physical flagship stores. A very positive model. Back in the day, people would actually pay money to go speak to a genius or get a priority customer service slot but a model that's really hard to scale and a model that hasn't been successful in a virtual environment.

I think when we see AI and a lot of these new technology advancements though, that's a prime example of maybe a new job that does emerge where if AI is offloading a lot of the interactions to chatbots, what do customer service agents do? Maybe they become geniuses where they're playing a more proactive, high-value add back to consumers and overall improving the service and the experience there. So I do think that AI will have job shifts, but overall there'll be a net positive just like there has been with all past transformative technologies.

Laurel: Continuing that look ahead, how do you see the era of AI evolving in terms of customer and employee experience? What excites you about the future in this space?

Andy: This is actually what I'm most excited about is when we think about customer experience today, it's highly reactive. As a consumer, if I have a problem, I search your website, I interact with your chatbot, I end up talking to a live customer service representative. The consumer is the driving force of everything and the business or the brand is having to be reactive to them. Where I see the future evolving in terms of customer experiences, is being much more proactive with the convergence of data, these advancements of technology, and certainly generative AI. I do see AI becoming smarter and being more predictive and proactive to alert that there is going to be a problem before the consumer actually is experiencing it and to take action on that proactively before that problem manifests itself.

And just a quick example of maybe there's a media or a cable company where a device is reaching its end-of-life state, so rather than it have it go on the fritz the day of the Super Bowl, reach out, be proactive, contact that individual, give them specific instructions to follow. And I think that's really where we see the advancements of not only big data, AI, but just the abundance of the ability to reach out in preferred channels, whether that's a simple SMS or a high-touch service representative reaching out really where the future of customer experience moves to a much more proactive state from its reactive state today.

Laurel: Well, thank you so much, Andy. I appreciate your time, and thank you for joining us on the Business Lab today.

Andy: Thanks. This was an excellent conversation, Laurel, and thanks again for having me.

Laurel: That was Andy Traba, who is the vice president of product marketing at NICE, who I spoke with from Cambridge Massachusetts, the home of MIT and MIT Technology Review. That's it for this episode of Business Lab. I'm your host, Laurel Ruma. I'm the global director of Insights, the custom publishing division of MIT Technology Review. We were founded in 1899 at the Massachusetts Institute of Technology, and you can find us in print on the web and at events each year around the world. For more information about us and the show, please check out our website at technologyreview.com. This show is available wherever you get your podcasts. If you enjoyed this episode, we hope you'll take a moment to rate and review us. Business Lab is a production of MIT Technology Review. This episode was produced by Giro Studios. Thanks for listening.

This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff.

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• Published: 21 March 2024

Expert review of the science underlying nature-based climate solutions

• B. Buma   ORCID: orcid.org/0000-0003-2402-7737 1 , 2   na1 ,
• D. R. Gordon   ORCID: orcid.org/0000-0001-6398-2345 1 , 3   na1 ,
• K. M. Kleisner 1 ,
• A. Bartuska 1 , 4 ,
• A. Bidlack 5 ,
• R. DeFries   ORCID: orcid.org/0000-0002-3332-4621 6 ,
• P. Ellis   ORCID: orcid.org/0000-0001-7933-8298 7 ,
• P. Friedlingstein   ORCID: orcid.org/0000-0003-3309-4739 8 , 9 ,
• S. Metzger 10   nAff15   nAff16 ,
• G. Morgan 11 ,
• K. Novick   ORCID: orcid.org/0000-0002-8431-0879 12 ,
• J. N. Sanchirico 13 ,
• J. R. Collins   ORCID: orcid.org/0000-0002-5705-9682 1 , 14 ,
• A. J. Eagle   ORCID: orcid.org/0000-0003-0841-2379 1 ,
• R. Fujita 1 ,
• E. Holst 1 ,
• J. M. Lavallee   ORCID: orcid.org/0000-0002-3028-7087 1 ,
• R. N. Lubowski 1   nAff17 ,
• C. Melikov 1   nAff18 ,
• L. A. Moore   ORCID: orcid.org/0000-0003-0239-6080 1   nAff19 ,
• E. E. Oldfield   ORCID: orcid.org/0000-0002-6181-1267 1 ,
• J. Paltseva 1   nAff20 ,
• A. M. Raffeld   ORCID: orcid.org/0000-0002-5036-6460 1 ,
• N. A. Randazzo 1   nAff21   nAff22 ,
• C. Schneider 1 ,
• N. Uludere Aragon 1   nAff23 &
• S. P. Hamburg 1  

Nature Climate Change ( 2024 ) Cite this article

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• Climate-change ecology
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Viable nature-based climate solutions (NbCS) are needed to achieve climate goals expressed in international agreements like the Paris Accord. Many NbCS pathways have strong scientific foundations and can deliver meaningful climate benefits but effective mitigation is undermined by pathways with less scientific certainty. Here we couple an extensive literature review with an expert elicitation on 43 pathways and find that at present the most used pathways, such as tropical forest conservation, have a solid scientific basis for mitigation. However, the experts suggested that some pathways, many with carbon credit eligibility and market activity, remain uncertain in terms of their climate mitigation efficacy. Sources of uncertainty include incomplete GHG measurement and accounting. We recommend focusing on resolving those uncertainties before broadly scaling implementation of those pathways in quantitative emission or sequestration mitigation plans. If appropriate, those pathways should be supported for their cobenefits, such as biodiversity and food security.

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Nature-based climate solutions (NbCS) are conservation, restoration and improved management strategies (pathways) in natural and working ecosystems with the primary motivation to mitigate GHG emissions and remove CO 2 from the atmosphere 1 (similar to ecosystem-based mitigation 2 ). GHG mitigation through ecosystem stewardship is integral to meeting global climate goals, with the greatest benefit coming from near-term maximization of emission reductions, followed by CO 2 removal 3 . Many countries (for example, Indonesia, China and Colombia) use NbCS to demonstrate progress toward national climate commitments.

The scope of NbCS is narrower than that of nature-based solutions (NbS) which include interventions that prioritize non-climate benefits alongside climate (for example, biodiversity, food provisioning and water quality improvement) 4 . In many cases, GHG mitigation is considered a cobenefit that results from NbS actions focused on these other challenges 2 . In contrast, NbCS are broader than natural climate solutions, which are primarily focused on climate mitigation through conservation, restoration and improved land management, generally not moving ecosystems beyond their unmodified structure, function or composition 5 . NbCS may involve moving systems beyond their original function, for example by cultivating macroalgae in water deeper than their natural habitat.

The promise of NbCS has generated a proliferation of interest in using them in GHG mitigation plans 6 , 7 ; 104 of the 168 signatories to the Paris Accord included nature-based actions as part of their mitigation plans 8 . Success in long-term GHG management requires an accurate accounting of inputs and outputs to the atmosphere at scale, so NbCS credits must have robust, comprehensive and transparent scientific underpinnings 9 . Given the urgency of the climate problem, our goal is to identify NbCS pathways with a sufficient scientific foundation to provide broad confidence in their potential GHG mitigation impact, provide resources for confident implementation and identify priority research areas in more uncertain pathways. Evaluating implementation of mitigation projects is beyond our scope; this effort focuses on understanding the underlying science. The purpose is not evaluating any specific carbon crediting protocol or implementation framework but rather the current state of scientific understanding necessary to provide confidence in any NbCS.

In service of this goal, we first investigated nine biomes (boreal forests, coastal marine (salt marsh, mangrove, seagrass and coral reef), freshwater wetlands, grasslands, open ocean (large marine animal and mesopelagic zone biomass, seabed), peatlands, shrublands, temperate forests and tropical forests) and three cultivation types (agroforestry, croplands and macroalgae aquaculture); these were chosen because of their identified potential scale of global impact. In this context, impact is assessed as net GHG mitigation: the CO 2 sequestered or emissions reduced, for example, discounted by understood simultaneous emissions of other GHG (as when N 2 O is released simultaneously with carbon sequestration in cropland soils). From there, we identified 43 NbCS pathways which have been formally implemented (with or without market action) or informally proposed. We estimated the scale of mitigation impact for each pathway on the basis of this literature and, as a proxy measure of NbCS implementation, determined eligibility and activity under existing carbon crediting protocols. Eligibility means that the pathway is addressed by an existing GHG mitigation protocol; market activity means that credits are actively being bought under those eligibility requirements. We considered pathways across a spectrum from protection to improved management to restoration to manipulated systems, but some boundaries were necessary. We excluded primarily abiotically driven pathways (for example, ocean alkalinity enhancement) or where major land use or land-use trade-offs exist (for example, afforestation) 10 , 11 , 12 . Of the 43 pathways, 79% are at present eligible for carbon crediting (sometimes under several methodologies) and at least 65% of those have been implemented (Supplementary Table 1 ). This review was then appraised by 30 independent scholars (at least three per pathway; a complete review synthesis is given in the Supplementary Data ).

Consolidation of a broad body of scientific knowledge, with inherent variance, requires expert judgement. We used an expert elicitation process 13 , 14 , 15 with ten experts to place each proposed NbCS pathway into one of three readiness categories following their own assessment of the scientific literature, categorized by general sources of potential uncertainty: category 1, sufficient scientific basis to support a high-quality carbon accounting system or to support the development of such a system today; category 2, a >25% chance that focused research and reasonable funding would support development of high-quality carbon accounting (that is, move to category 1) within 5 years; or category 3, a <25% chance of development of high-quality carbon accounting within 5 years (for example, due to measurement challenges, unconstrained leakage, external factors which constrain viability).

If an expert ranked a pathway as category 2, they were also asked to rank general research needs to resolve: leakage/displacement (spillover to other areas), measuring, reporting and verification (the ability to quantify all salient stocks and fluxes), basic mechanisms of action (fundamental science), durability (ability to predict or compensate for uncertainty in timescale of effectiveness due to disturbances, climate change, human activity or other factors), geographic uncertainty (place-to-place variation), scaling potential (ability to estimate impact) and setting of a baseline (ability to estimate additionality over non-action; a counterfactual). To avoid biasing towards a particular a priori framework for evaluation of the scientific literature, reviewers could use their own framework for evaluating the NbCS literature about potential climate impact and so could choose to ignore or add relevant categorizations as well. Any pathway in category 1 would not need fundamental research for implementation; research gaps were considered too extensive for useful guidance on reducing uncertainty in category 3 pathways. Estimates of the global scale of likely potential impact (PgCO 2 e yr −1 ) and cobenefits were also collected from expert elicitors. See Methods and Supplementary Information for the survey instrument.

Four pathways with the highest current carbon market activity and high mitigation potential (tropical and temperate forest conservation and reforestation; Table 1 and Supplementary Data ), were consistently rated as high-confidence pathways in the expert elicitation survey. Other NbCS pathways, especially in the forestry sector, were rated relatively strongly by the experts for both confidence in scientific basis and scale of potential impact, with some spread across the experts (upper right quadrant, Fig. 1 ). Conversely, 13 pathways were consistently marked by experts as currently highly uncertain/low confidence (median score across experts: 2.5–3.0) and placed in category 3 (for example, cropland microbial amendments and coral reef restoration; Supplementary Tables 1 and 2 ). For the full review, including crediting protocols currently used, literature estimates of scale and details of sub-pathways, see Supplementary Data .

Pathways in the upper right quadrant have both high confidence in the scientific foundations and the largest potential scale of global impact; pathways in the lower left have the lowest confidence in our present scientific body of knowledge and an estimated smaller potential scale of impact. Designations of carbon credit eligibility under existing protocols and market activity at the present time are noted. Grassland enhanced mineral weathering (EMW) is not shown (mean category rating 2.9) as no scale of impact was estimated. See Supplementary Table 1 for specific pathway data. Bars represent 20th to 80th percentiles of individual estimates, if there was variability in estimates. A small amount of random noise was added to avoid overlap.

The experts assessed 26 pathways as having average confidence scores between 1.5 and 2.4, suggesting the potential for near-term resolution of uncertainties. This categorization arose from either consensus amongst experts on the uncertain potential (for example, boreal forest reforestation consistently rated category 2, with primary concerns about durability) or because experts disagreed, with some ranking category 1 and others category 3 (for example, pasture management). We note that where expert disagreement exists (seen as the spread of responses in Fig. 1 and Supplementary Table 1 ; also see Data availability for link to original data), this suggests caution against overconfidence in statements about these pathways. These results also suggest that confidence may be increased by targeted research on the identified sources of uncertainty (Supplementary Table 3 ).

Sources of uncertainty

Durability and baseline-setting were rated as high sources of uncertainty across all pathways ranked as category 2 by the experts (mean ratings of 3.6 and 3.4 out of 5, respectively; Supplementary Table 3 ). Understanding of mechanisms and geographic spread had the lowest uncertainty ratings (2.1 and 2.3, respectively), showing confidence in the basic science. Different subsets of pathways had different prioritizations, however, suggesting different research needs: forest-centric pathways were most uncertain in their durability and additionality (3.8 and 3.4, respectively), suggesting concerns about long-term climate and disturbance trajectories. Agricultural and grassland systems, however, had higher uncertainty in measurement methods and additionality (3.9 and 3.5 respectively). Although there were concerns about durability from some experts (for example, due to sea-level rise), some coastal blue carbon pathways such as mangrove restoration (mean category ranking: 1.7 (20th to 80th percentile 1.0–2.0)) have higher confidence than others (for example, seagrass restoration: mean category ranking 2.8, 20th to 80th percentile 2.6–3.0)), which are relatively poorly constrained in terms of net radiative forcing potential despite a potentially large carbon impact (seagrass median: 1.60 PgCO 2 e yr −1 ; see Supplementary Data for more scientific literature estimates).

Scale of impact

For those pathways with lower categorization by the expert elicitation (category 2 or 3) at the present time, scale of global impact is a potential heuristic for prioritizing further research. High variability, often two orders of magnitude, was evident in the mean estimated potential PgCO 2 e yr −1 impacts for the different pathways (Fig. 1 and Supplementary Table 2 ) and the review of the literature found even larger ranges produced by individual studies (Supplementary Data ). A probable cause of this wide range was different constraints on the estimated potential, with some studies focusing on potential maximum impact and others on more constrained realizable impacts. Only avoided loss of tropical forest and cropland biochar amendment were consistently estimated as having the likely potential to mitigate >2 PgCO 2 e yr −1 , although biochar was considered more uncertain by experts due to other factors germane to its overall viability as a climate solution, averaging a categorization of 2.2. The next four highest potential impact pathways, ranging from 1.6 to 1.7 PgCO 2 e yr −1 , spanned the spectrum from high readiness (temperate forest restoration) to moderate (cropland conversion from annual to perennial vegetation and grassland restoration) to low (seagrass restoration, with main uncertainties around scale of potential impact and durability).

There was high variability in the elicitors’ estimated potential scale of impact, even in pathways with strong support, such as tropical forest avoided loss (20th to 80th percentile confidence interval: 1–8 PgCO 2 e yr −1 ), again emphasizing the importance of consistent definitions and constraints on how NbCS are measured, evaluated and then used in broad-scale climate change mitigation planning and budgeting. Generally, as pathway readiness decreased (moving from category 1 to 3), the elicitor-estimated estimates of GHG mitigation potential decreased (Supplementary Fig. 1 ). Note that individual studies from the scientific literature may have higher or lower estimates (Supplementary Data ).

Expert elicitation meta-analyses suggest that 6–12 responses are sufficient for a robust and stable quantification of responses 15 . We tested that assumption via a Monte Carlo-based sensitivity assessment. Readiness categorizations by the ten experts were robust to a Monte Carlo simulation test, where further samples were randomly drawn from the observed distribution of responses: mean difference between the original and the boot-strapped data was 0.02 (s.d. = 0.05) with an absolute difference average of 0.06 (s.d. = 0.06). The maximum difference in readiness categorization means across all pathways was 0.20 (s.d. = 0.20) (Supplementary Table 2 ). The full dataset of responses is available online (see ʻData availabilityʼ).

These results highlight opportunities to accelerate implementation of NbCS in well-supported pathways and identify critical research needs in others (Fig. 1 ). We suggest focusing future efforts on resolving identified uncertainties for pathways at the intersection between moderate average readiness (for example, mean categorizations between ~1.5 and 2.0) and high potential impact (for example, median >0.5 PgCO 2 e yr −1 ; Supplementary Table 1 ): agroforestry, improved tropical and temperate forest management, tropical and boreal peatlands avoided loss and peatland restoration. Many, although not all, experts identified durability and baseline/additionality as key concerns to resolve in those systems; research explicitly targeted at those specific uncertainties (Supplementary Table 3 ) could rapidly improve confidence in those pathways.

We recommend a secondary research focus on the lower ranked (mean category 2.0 to 3.0) pathways with estimated potential impacts >1 PgCO 2 e yr −1 (Supplementary Fig. 2 ). For these pathways, explicit, quantitative incorporation into broad-scale GHG management plans will require further focus on systems-level carbon/GHG understandings to inspire confidence at all stages of action and/or identifying locations likely to support durable GHG mitigation, for example ref. 16 . Examples of this group include avoided loss and degradation of boreal forests (for example, fire, pests and pathogens and albedo 16 ) and effective mesopelagic fishery management, which some individual studies estimate would avoid future reductions of the currently sequestered 1.5–2.0 PgC yr −1 (refs. 17 , 18 ). These pathways may turn out to have higher or lower potential than the expert review suggests, on the basis of individual studies (Supplementary Data ) but strong support will require further, independent verification of that potential.

We note that category 3 rankings by expert elicitation do not necessarily imply non-viability but simply that much more research is needed to confidently incorporate actions into quantitative GHG mitigation plans. We found an unsurprising trend of lower readiness categorization with lower pathway familiarity (Supplementary Fig. 3 ). This correlation may result from two, non-exclusive potential causes: (1) lower elicitor expertise in some pathways (inevitable, although the panel was explicitly chosen for global perspectives, connections and diverse specialties) and (2) an actual lack of scientific evidence in the literature, which leads to that self-reported lack of familiarity, a common finding in the literature review (Supplementary Data ). Both explanations suggest a need to better consolidate, develop and disseminate the science in each pathway for global utility and recognition.

Our focus on GHG-related benefits in no way diminishes the substantial conservation, environmental and social cobenefits of these pathways (Supplementary Table 4 ), which often exceed their perceived climate benefits 1 , 19 , 20 , 21 . Where experts found climate impacts to remain highly uncertain but other NbS benefits are clear (for example, biodiversity and water quality; Supplementary Table 4 ), other incentives or financing mechanisms independent of carbon crediting should be pursued. While the goals here directly relate to using NbCS as a reliably quantifiable part of global climate action planning and thus strong GHG-related scientific foundations, non-climate NbS projects may provide climate benefits that are less well constrained (and thus less useful from a GHG budgeting standpoint) but also valuable. Potential trade-offs, if any, between ecosystem services and management actions, such as biodiversity and positive GHG outcomes, should be explored to ensure the best realization of desired goals 2 .

Finally, our focus in this study was on broad-scale NbCS potential in quantitative mitigation planning because of the principal and necessary role of NbCS in overall global warming targets. We recognize the range of project conditions that may increase, or decrease, the rigour of any pathway outside the global-scale focus here. We did not specifically evaluate the large and increasing number of crediting concepts (by pathway: Supplementary Data ), focusing rather on the underlying scientific body of knowledge within those pathways. Some broad pathways may have better defined sub-pathways within them, with a smaller potential scale of impact but potentially lower uncertainty (for example, macroalgae harvest cycling). Poorly enacted NbCS actions and/or crediting methodologies at project scales may result in loss of benefits even from high-ranking pathways 22 , 23 , 24 and attention to implementation should be paramount. Conversely, strong, careful project-scale methodologies may make lower readiness pathways beneficial for a given site.

Viable NbCS are vital to global climate change mitigation but NbCS pathways that lack strong scientific underpinnings threaten global accounting by potentially overestimating future climate benefits and eroding public trust in rigorous natural solutions. Both the review of the scientific literature and the expert elicitation survey identified high potential ready-to-implement pathways (for example, tropical reforestation), reinforcing present use of NbCS in planning.

However, uncertainty remains about the quantifiable GHG mitigation of some active and nascent NbCS pathways. On the basis of the expert elicitation survey and review of the scientific literature, we are concerned that large-scale implementation of less scientifically well-founded NbCS pathways in mitigation plans may undermine net GHG budget planning; those pathways require more study before they can be confidently promoted at broad scales and life-cycle analyses to integrate system-level emissions when calculating totals. The expert elicitation judgements suggest a precautionary approach to scaling lower confidence pathways until the scientific foundations are strengthened, especially for NbCS pathways with insufficient measurement and monitoring 10 , 24 , 25 or poorly understood or measured net GHG mitigation potentials 16 , 26 , 27 , 28 . While the need to implement more NbCS pathways for reducing GHG emissions and removing carbon from the atmosphere is urgent, advancing the implementation of poorly quantified pathways (in relation to their GHG mitigation efficacy) could give the false impression that they can balance ongoing, fossil emissions, thereby undermining overall support for more viable NbCS pathways. Explicitly targeting research to resolve these uncertainties in the baseline science could greatly bolster confidence in the less-established NbCS pathways, benefiting efforts to reduce GHG concentrations 29 .

The results of this study should inform both market-based mechanisms and non-market approaches to NbCS pathway management. Research and action that elucidates and advances pathways to ensure a solid scientific basis will provide confidence in the foundation for successfully implementing NbCS as a core component of global GHG management.

NbCS pathway selection

We synthesized scientific publications for nine biomes (boreal forests, coastal blue carbon, freshwater wetlands, grasslands, open ocean blue carbon, peatlands, shrublands, temperate forests and tropical forests) and three cultivation types (agroforestry, croplands and macroalgae aquaculture) (hereafter, systems) and the different pathways through which they may be able to remove carbon or reduce GHG emissions. Shrublands and grasslands were considered as independent ecosystems; nonetheless, we acknowledge that there is overlap in the numbers presented here because shrublands are often included with grasslands 5 , 30 , 31 , 32 , 33 .

The 12 systems were chosen because they have each been identified as having potential for emissions reductions or carbon removal at globally relevant scales. Within these systems, we identified 43 pathways which either have carbon credit protocols formally established or informally proposed for review (non-carbon associated credits were not evaluated). We obtained data on carbon crediting protocols from international, national and regional organizations and registries, such as Verra, American Carbon Registry, Climate Action Reserve, Gold Standard, Clean Development Mechanism, FAO and Nori. We also obtained data from the Voluntary Registry Offsets Database developed by the Berkeley Carbon Trading Project and Carbon Direct company 34 . While we found evidence of more Chinese carbon crediting protocols, we were not able to review these because of limited publicly available information. To maintain clarity and avoid misrepresentation, we used the language as written in each protocol. A full list of the organizations and registries for each system can be found in the Supplementary Data .

Literature searches and synthesis

We reviewed scientific literature and reviews (for example, IPCC special reports) to identify studies reporting data on carbon stocks, GHG dynamics and sequestration potential of each system. Peer-reviewed studies and meta-analyses were identified on Scopus, Web of Science and Google Scholar using simple queries combining the specific practice or pathway names or synonyms (for example, no-tillage, soil amendments, reduced stocking rates, improved forest management, avoided forest conversion and degradation, avoided mangrove conversion and degradation) and the following search terms: ‘carbon storage’, ‘carbon stocks’, ‘carbon sequestration’, ‘carbon sequestration potential’, ‘additional carbon storage’, ‘carbon dynamics’, ‘areal extent’ or ‘global’.

The full literature review was conducted between January and October 2021. We solicited an independent, external review of the syntheses (obtaining from at least three external reviewers per natural or working system; see p. 2 of the Supplementary Data ) as a second check against missing key papers or misinterpretation of data. The review was generally completed in March 2022. Data from additional relevant citations were added through October 2022 as they were discovered. For a complete list of all literature cited, see pp. 217–249 of the Supplementary Data .

From candidate papers, the papers were considered if their results/data could be applied to the following central questions:

How much carbon is stored (globally) at present in the system (total and on average per hectare) and what is the confidence?

At the global level, is the system a carbon source or sink at this time? What is the business-as-usual projection for its carbon dynamics?

Is it possible, through active management, to either increase net carbon sequestration in the system or prevent carbon emissions from that system? (Note that other GHG emissions and forcings were included here as well.)

What is the range of estimates for how much extra carbon could be sequestered globally?

How much confidence do we have in the present methods to detect any net increases in carbon sequestration in a system or net changes in areal extent of that?

From each paper, quantitative estimates for the above questions were extracted for each pathway, including any descriptive information/metadata necessary to understand the estimate. In addition, information on sample size, sampling scheme, geographic coverage, timeline of study, timeline of projections (if applicable) and specific study contexts (for example, wind-break agroforestry) were recorded.

We also tracked where the literature identified trade-offs between carbon sequestered or CO 2 emissions reduced and emissions of other GHG (for example, N 2 O or methane) for questions three and five above. For example, wetland restoration can result in increased CO 2 uptake from the atmosphere. However, it can also increase methane and N 2 O emissions to the atmosphere. Experts were asked to consider the uncertainty in assessing net GHG mitigation as they categorized the NbCS pathways.

Inclusion of each pathway in mitigation protocols and the specific carbon registries involved were also identified. These results are reported (grouped or individually as appropriate) in the Supplementary Data , organized by the central questions and including textual information for interpretation. The data and protocol summaries for each of the 12 systems were reviewed by at least three scientists each and accordingly revised.

These summaries were provided to the expert elicitation group as optional background information.

Unit conversions

Since this synthesis draws on literature from several sources that use different methods and units, all carbon measurements were standardized to the International System of Units (SI units). When referring to total stocks for each system, numbers are reported in SI units of elemental carbon (that is, PgC). When referring to mitigation potential, elemental carbon was converted to CO 2 by multiplying by 3.67. Differences in methodology, such as soil sampling depth, make it difficult to standardize across studies. Where applicable, the specific measurement used to develop each stock estimate is reported.

Expert elicitation process

To assess conclusions brought about by the initial review process described above, we conducted an expert elicitation survey to consolidate and add further, independent assessments to the original literature review. The expert elicitation survey design followed best practice recommendations 14 , with a focus on participant selection, explicitly defining uncertainty, minimizing cognitive and overconfidence biases and clarity of focus. Research on expert elicitation suggests that 6–12 responses are sufficient for a stable quantification of responses 15 . We identified >40 potential experts via a broad survey of leading academics, science-oriented NGO and government agency publications and products. These individuals have published on several NbCS pathways or could represent larger research efforts that spanned the NbCS under consideration. Careful attention was paid to the gender and sectoral breakdown of respondents to ensure equitable representation. Of the invitees, ten completed the full elicitation effort. Experts were offered compensation for their time.

Implementation of the expert elicitation process followed the IDEA protocol 15 . Briefly, after a short introductory interview, the survey was sent to the participants. Results were anonymized and standardized (methods below) and a meeting held with the entire group to discuss the initial results and calibrate understanding of questions. The purpose of this meeting was not to develop consensus on a singular answer but to discuss and ensure that all questions are being considered in the same way (for example, clarifying any potentially confusing language, discussing any questions that emerged as part of the process). The experts then revisited their initial rankings to provide final, anonymous rankings which were compiled in the same way. These final rankings are the results presented here and may be the same or different from the initial rankings, which were discarded.

Survey questions

The expert elicitation survey comprised five questions for each pathway. The data were collected via Google Forms and collated anonymously at the level of pathways, with each respondent contributing one datapoint for each pathway. The experts reported their familiarity (or the familiarity of the organization whose work they were representing) with the pathway and other cobenefits for the pathways.

The initial question ranked the NbCS pathway by category, from one to three.

Category 1 was defined as a pathway with sufficient scientific knowledge to support a high-quality carbon accounting system today (for example, meets the scientific criteria identified in the WWF-EDF-Oeko Institut and ICAO TAB) or to support the development of such a system today. The intended interpretation is that sufficient science is available for quantifying and verifying net GHG mitigation. Note that experts were not required to reference any given ‘high-quality’ crediting framework, which were provided only as examples. In other words, the evaluation was not intended to rank a given framework (for example, ref. 35 ) but rather expert confidence in the fundamental scientific understandings that underpin potential for carbon accounting overall. To this end, no categorization of uncertainty was required (reviewers could skip categorizations they felt were not necessary) and space was available to fill in new categories by individual reviewers (if they felt a category was missing or needed). Uncertainties at this category 1 level are deemed ‘acceptable’, for example, not precluding accounting now, although more research may further substantiate high-quality credits.

Category 2 pathways have a good chance (>25%) that with more research and within the next 5 years, the pathway could be developed into a high-quality pathway for carbon accounting and as a nature-based climate solution pathway. For these pathways, further understanding is needed for factors such as baseline processes, long-term stability, unconstrained fluxes, possible leakage or other before labelling as category 1 but the expert is confident that information can be developed, in 5 years or less, with more work. The >25% chance threshold and 5-year timeframe were determined a priori to reflect and identify pathways that experts identified as having the potential to meet the Paris Accord 2030 goal. Other thresholds (for example, longer timeframes) could have been chosen, which would impact the relative distribution of pathways in categories 2 and 3 (for example, a longer timeframe allowed could move some pathways from category 3 into category 2, for some reviewers). We emphasize that category 3 pathways do not necessarily mean non-valuable approaches but longer timeframes required for research than the one set here.

Category 3 responses denoted pathways that the expert thought had little chance (<25%) that with more research and within the next 5 years, this pathway could be developed into a suitable pathway for managing as a natural solutions pathway, either because present evidence already suggests GHG reduction is not likely to be viable, co-emissions or other biophysical feedbacks may offset those gains or because understanding of key factors is lacking and unlikely to be developed within the next 5 years. Notably, the last does not mean that the NbCS pathway is not valid or viable in the long-term, simply that physical and biological understandings are probably not established enough to enable scientific rigorous and valid NbCS activity in the near term.

The second question asked the experts to identify research gaps associated with those that they ranked as category 2 pathways to determine focal areas for further research. The experts were asked to rank concerns about durability (ability to predict or compensate for uncertainty in timescale of effectiveness due to disturbances, climate change, human activity or other factors), geographic uncertainty (place-to-place variation), leakage or displacement (spillover of activities to other areas), measuring, reporting and verification (MRV, referring to the ability to quantify all salient stocks and fluxes to fully assess climate impacts), basic mechanisms of action (fundamental science), scaling potential (ability to estimate potential growth) and setting of a baseline (ability to reasonably quantify additionality over non-action, a counterfactual). Respondents could also enter a different category if desired. For complete definitions of these categories, see the survey instrument ( Supplementary Information ). This question was not asked if the expert ranked the pathway as category 1, as those were deemed acceptable, or for category 3, respecting the substantial uncertainty in that rating. Note that responses were individual and so the same NbCS pathway could receive (for example) several individual category 1 rankings, which would indicate reasonable confidence from those experts, and several category 2 rankings from others, which would indicate that those reviewers have lingering concerns about the scientific basis, along with their rankings of the remaining key uncertainties in those pathways. These are important considerations, as they reflect the diversity of opinions and research priorities; individual responses are publicly available (anonymized: https://doi.org/10.5281/zenodo.7859146 ).

The third question involved quantification of the potential for moving from category 2 to 1 explicitly. Following ref. 14 , the respondents first reported the lowest plausible value for the potential likelihood of movement (representing the lower end of a 95% confidence interval), then the upper likelihood and then their best guess for the median/most likely probability. They were also asked for the odds that their chosen interval contained the true value, which was used to scale responses to standard 80% credible intervals and limit overconfidence bias 13 , 15 . This question was not asked if the expert ranked the pathway as category 3, respecting the substantial uncertainty in that rating.

The fourth question involved the scale of potential impact from the NbCS, given the range of uncertainties associated with effectiveness, area of applicability and other factors. The question followed the same pattern as the third, first asking about lowest, then highest, then best estimate for potential scale of impact (in PgCO 2 e yr −1 ). Experts were again asked to express their confidence in their own range, which was used to scale to a standard 80% credible interval. This estimate represents a consolidation of the best-available science by the reviewers. For a complete review including individual studies and their respective findings, see the Supplementary Data . This question was not asked if the expert ranked the pathway as category 3, respecting the substantial uncertainty in that rating.

Final results

After collection of the final survey responses, results were anonymized and compiled by pathway. For overall visualization and discussion purposes, responses were combined into a mean and 20th to 80th percentile range. The strength of the expert elicitation process lies in the collection of several independent assessments. Those different responses represent real differences in data interpretation and synthesis ascribed by experts. This can have meaningful impacts on decision-making by different individuals and organizations (for example, those that are more optimistic or pessimistic about any given pathway). Therefore, individual anonymous responses were retained by pathway to show the diversity of responses for any given pathway. The experts surveyed, despite their broad range of expertise, ranked themselves as less familiar with category 3 pathways than category 1 or 2 (linear regression, P  < 0.001, F  = 59.6 2, 394 ); this could be because of a lack of appropriate experts—although they represented all principal fields—or simply because the data are limited in those areas.

Sensitivity

To check for robustness against sample size variation, we conducted a Monte Carlo sensitivity analysis of the data on each pathway to generate responses of a further ten hypothetical experts. Briefly, the extra samples were randomly drawn from the observed category ranking mean and standard deviations for each individual pathway and appended to the original list; values <1 or >3 were truncated to those values. This analysis resulted in only minor differences in the mean categorization across all pathways: the mean difference between the original and the boot-strapped data was 0.02 (s.d. = 0.05) with an absolute difference average of 0.06 (s.d. = 0.06). The maximum difference in means across all pathways was 0.20 (s.d. = 0.20) (Supplementary Table 2 ). The results suggest that the response values are stable to additional responses.

All processing was done in R 36 , with packages including fmsb 37 and forcats 38 .

Data availability

Anonymized expert elicitation responses are available on Zenodo 39 : https://doi.org/10.5281/zenodo.7859146 .

Code availability

R code for analysis available on Zenodo 39 : https://doi.org/10.5281/zenodo.7859146 .

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Acknowledgements

This research was supported through gifts to the Environmental Defense Fund from the Bezos Earth Fund, King Philanthropies and Arcadia, a charitable fund of L. Rausing and P. Baldwin. We thank J. Rudek for help assembling the review and 30 experts who reviewed some or all of those data and protocol summaries (Supplementary Data ). S.M. was supported by a cooperative agreement between the National Science Foundation and Battelle that sponsors the National Ecological Observatory Network programme.

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Present address: Department of Atmospheric and Oceanic Sciences, University of Wisconsin-Madison, Madison, WI, USA

Present address: AtmoFacts, Longmont, CO, USA

R. N. Lubowski

Present address: Lombard Odier Investment Managers, New York, NY, USA

Present address: Ecological Carbon Offset Partners LLC, dba EP Carbon, Minneapolis, MN, USA

L. A. Moore

Present address: , San Francisco, CA, USA

J. Paltseva

Present address: ART, Arlington, VA, USA

N. A. Randazzo

Present address: NASA/GSFC, Greenbelt, MD, USA

Present address: University of Maryland, College Park, MD, USA

N. Uludere Aragon

Present address: Numerical Terradynamic Simulation Group, University of Montana, Missoula, MT, USA

These authors contributed equally: B. Buma, D. R. Gordon.

Authors and Affiliations

Environmental Defense Fund, New York, NY, USA

B. Buma, D. R. Gordon, K. M. Kleisner, A. Bartuska, J. R. Collins, A. J. Eagle, R. Fujita, E. Holst, J. M. Lavallee, R. N. Lubowski, C. Melikov, L. A. Moore, E. E. Oldfield, J. Paltseva, A. M. Raffeld, N. A. Randazzo, C. Schneider, N. Uludere Aragon & S. P. Hamburg

Department of Integrative Biology, University of Colorado, Denver, CO, USA

Department of Biology, University of Florida, Gainesville, FL, USA

D. R. Gordon

Resources for the Future, Washington, DC, USA

A. Bartuska

International Arctic Research Center, University of Alaska, Fairbanks, AK, USA

Department of Ecology Evolution and Environmental Biology and the Climate School, Columbia University, New York, NY, USA

The Nature Conservancy, Arlington, VA, USA

Faculty of Environment, Science and Economy, University of Exeter, Exeter, UK

P. Friedlingstein

Laboratoire de Météorologie Dynamique/Institut Pierre-Simon Laplace, CNRS, Ecole Normale Supérieure/Université PSL, Sorbonne Université, Ecole Polytechnique, Palaiseau, France

National Ecological Observatory Network, Battelle, Boulder, CO, USA

Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA, USA

O’Neill School of Public and Environmental Affairs, Indiana University, Bloomington, IN, USA

Department of Environmental Science and Policy, University of California, Davis, CA, USA

J. N. Sanchirico

Department of Marine Chemistry & Geochemistry, Woods Hole Oceanographic Institution, Woods Hole, MA, USA

J. R. Collins

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Contributions

D.R.G. and B.B. conceived of and executed the study design. D.R.G., K.M.K., J.R.C., A.J.E., R.F., E.H., J.M.L., R.N.L., C.M., L.A.M., E.E.O., J.P., A.M.R., N.A.R., C.S. and N.U.A. coordinated and conducted the literature review. G.M. and B.B. primarily designed the survey. A. Bartuska, A. Bidlack, B.B., J.N.S., K.N., P.E., P.F., R.D. and S.M. contributed to the elicitation. B.B. conducted the analysis and coding. S.P.H. coordinated funding. B.B. and D.R.G. were primary writers; all authors were invited to contribute to the initial drafting.

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The authors declare no competing interests. In the interest of full transparency, we note that while B.B., D.R.G., K.M.K., A.B., J.R.C., A.J.E., R.F., E.H., J.M.L., R.N.L., C.M., L.A.M., E.E.O., J.P., A.M.R., N.A.R., C.S., N.U.A., S.P.H. and P.E. are employed by organizations that have taken positions on specific NbCS frameworks or carbon crediting pathways (not the focus of this work), none have financial or other competing interest in any of the pathways and all relied on independent science in their contributions to the work.

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Supplementary information

Supplementary information.

Supplementary Tables 1–4, Figs. 1–3 and survey instrument.

Supplementary Data

Literature review and list of reviewers.

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Buma, B., Gordon, D.R., Kleisner, K.M. et al. Expert review of the science underlying nature-based climate solutions. Nat. Clim. Chang. (2024). https://doi.org/10.1038/s41558-024-01960-0

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Retraction Note: Converging concepts of sustainability and supply chain networks: a systematic literature review approach

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Hou, Y., Khokhar, M., Sharma, A. et al. Retraction Note: Converging concepts of sustainability and supply chain networks: a systematic literature review approach. Environ Sci Pollut Res (2024). https://doi.org/10.1007/s11356-024-33138-8

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