introduction with literature review

How to write a literature review introduction (+ examples)

The introduction to a literature review serves as your reader’s guide through your academic work and thought process. Explore the significance of literature review introductions in review papers, academic papers, essays, theses, and dissertations. We delve into the purpose and necessity of these introductions, explore the essential components of literature review introductions, and provide step-by-step guidance on how to craft your own, along with examples.

Why you need an introduction for a literature review

In academic writing , the introduction for a literature review is an indispensable component. Effective academic writing requires proper paragraph structuring to guide your reader through your argumentation. This includes providing an introduction to your literature review.

It is imperative to remember that you should never start sharing your findings abruptly. Even if there isn’t a dedicated introduction section .

When you need an introduction for a literature review

There are three main scenarios in which you need an introduction for a literature review:

What to include in a literature review introduction

It is crucial to customize the content and depth of your literature review introduction according to the specific format of your academic work.

Academic literature review paper

The introduction of an academic literature review paper, which does not rely on empirical data, often necessitates a more extensive introduction than the brief literature review introductions typically found in empirical papers. It should encompass:

Regular literature review section in an academic article or essay

In a standard 8000-word journal article, the literature review section typically spans between 750 and 1250 words. The first few sentences or the first paragraph within this section often serve as an introduction. It should encompass:

Introduction to a literature review chapter in thesis or dissertation

Some students choose to incorporate a brief introductory section at the beginning of each chapter, including the literature review chapter. Alternatively, others opt to seamlessly integrate the introduction into the initial sentences of the literature review itself. Both approaches are acceptable, provided that you incorporate the following elements:

Examples of literature review introductions

Example 1: an effective introduction for an academic literature review paper.

To begin, let’s delve into the introduction of an academic literature review paper. We will examine the paper “How does culture influence innovation? A systematic literature review”, which was published in 2018 in the journal Management Decision.

Example 2: An effective introduction to a literature review section in an academic paper

The second example represents a typical academic paper, encompassing not only a literature review section but also empirical data, a case study, and other elements. We will closely examine the introduction to the literature review section in the paper “The environmentalism of the subalterns: a case study of environmental activism in Eastern Kurdistan/Rojhelat”, which was published in 2021 in the journal Local Environment.

Thus, the author successfully introduces the literature review, from which point onward it dives into the main concept (‘subalternity’) of the research, and reviews the literature on socio-economic justice and environmental degradation.

Examples 3-5: Effective introductions to literature review chapters

Numerous universities offer online repositories where you can access theses and dissertations from previous years, serving as valuable sources of reference. Many of these repositories, however, may require you to log in through your university account. Nevertheless, a few open-access repositories are accessible to anyone, such as the one by the University of Manchester . It’s important to note though that copyright restrictions apply to these resources, just as they would with published papers.

Master’s thesis literature review introduction

Phd thesis literature review chapter introduction.

The second example is Deep Learning on Semi-Structured Data and its Applications to Video-Game AI, Woof, W. (Author). 31 Dec 2020, a PhD thesis completed at the University of Manchester . In Chapter 2, the author offers a comprehensive introduction to the topic in four paragraphs, with the final paragraph serving as an overview of the chapter’s structure:

PhD thesis literature review introduction

The last example is the doctoral thesis Metacognitive strategies and beliefs: Child correlates and early experiences Chan, K. Y. M. (Author). 31 Dec 2020 . The author clearly conducted a systematic literature review, commencing the review section with a discussion of the methodology and approach employed in locating and analyzing the selected records.

Steps to write your own literature review introduction

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• 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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• 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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See an example

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

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

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

Download Word doc Download Google doc

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

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

Make a list of keywords

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

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

Search for relevant sources

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

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

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

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

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

For each publication, ask yourself:

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

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

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

Take notes and cite your sources

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

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

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

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

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

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

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

Chronological

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

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

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

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

Methodological

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

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

Theoretical

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

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

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

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

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

As you write, you can follow these tips:

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

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

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

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

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

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

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

 Statistics

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

Research bias

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

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

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

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

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

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

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

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

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

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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: .

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

Frequently asked questions 

What is a literature review .

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

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

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

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

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

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

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

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

Literature review example 

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

Literature Review on Climate Change Impacts on Biodiversity:  

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

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. 

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. 

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. 

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

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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. 

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

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

Conducting a literature review 

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

Choose a Topic and Define the Research Question:  

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

Decide on the Scope of Your Review:  

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

Select Databases for Searches:  

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

Conduct Searches and Keep Track:  

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

Review the Literature:  

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

Organize and Write Your Literature Review:  

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

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How to write a literature review faster with Paperpal?  

Paperpal, an AI writing assistant, integrates powerful academic search capabilities within its writing platform. With the Research | Cite feature, you get 100% factual insights, with citations backed by 250M+ verified research articles, directly within your writing interface. It also allows you auto-cite references in 10,000+ styles and save relevant references in your Citation Library. By eliminating the need to switch tabs to find answers to all your research questions, Paperpal saves time and helps you stay focused on your writing.   

Here’s how to use the Research feature:  

• Ask a question: Get started with a new document on paperpal.com. Click on the “Research | Cite” feature and type your question in plain English. Paperpal will scour over 250 million research articles, including conference papers and preprints, to provide you with accurate insights and citations. 

• Review and Save: Paperpal summarizes the information, while citing sources and listing relevant reads. You can quickly scan the results to identify relevant references and save these directly to your built-in citations library for later access. 
• Cite with Confidence: Paperpal makes it easy to incorporate relevant citations and references in 10,000+ styles into your writing, ensuring your arguments are well-supported by credible sources. This translates to a polished, well-researched literature review. 

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

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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Writing a Literature Review

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

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

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

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

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

What are the parts of a lit review?

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

Introduction:

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

Conclusion:

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

How should I organize my lit review?

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

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

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

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

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

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

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

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

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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.

Prevent plagiarism, run a free check.

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.

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

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

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

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

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

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

Chronological

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

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

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

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

Methodological

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

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

Theoretical

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

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

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

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

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

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

As you write, make sure to follow these tips:

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

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

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

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

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

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

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

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

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

Cite this Scribbr article

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McCombes, S. (2022, June 07). What is a Literature Review? | Guide, Template, & Examples. Scribbr. Retrieved 18 September 2024, from https://www.scribbr.co.uk/thesis-dissertation/literature-review/

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Introduction to Literature Reviews

Introduction.

• Step One: Define
• Step Two: Research
• Step Three: Write
• Suggested Readings

A literature review is a written work that :

• Compiles significant research published on a topic by accredited scholars and researchers;
• Surveys scholarly articles, books, dissertations, conference proceedings, and other sources;
• Examines contrasting perspectives, theoretical approaches, methodologies, findings, results, conclusions.
• Reviews critically, analyzes, and synthesizes existing research on a topic; and,
• Performs a thorough “re” view, “overview”, or “look again” of past and current works on a subject, issue, or theory.

From these analyses, the writer then offers an overview of the current status of a particular area of knowledge from both a practical and theoretical perspective.

Literature reviews are important because they are usually a  required  step in a thesis proposal (Master's or PhD). The proposal will not be well-supported without a literature review. Also, literature reviews are important because they help you learn important authors and ideas in your field. This is useful for your coursework and your writing. Knowing key authors also helps you become acquainted with other researchers in your field.

Look at this diagram and imagine that your research is the "something new." This shows how your research should relate to major works and other sources.

Olivia Whitfield | Graduate Reference Assistant | 2012-2015

• Next: Step One: Define >>
• Last Updated: Aug 29, 2024 1:55 PM
• URL: https://libraryguides.missouri.edu/literaturereview

Literature Reviews

What this handout is about.

This handout will explain what literature reviews are and offer insights into the form and construction of literature reviews in the humanities, social sciences, and sciences.

Introduction

OK. You’ve got to write a literature review. You dust off a novel and a book of poetry, settle down in your chair, and get ready to issue a “thumbs up” or “thumbs down” as you leaf through the pages. “Literature review” done. Right?

Wrong! The “literature” of a literature review refers to any collection of materials on a topic, not necessarily the great literary texts of the world. “Literature” could be anything from a set of government pamphlets on British colonial methods in Africa to scholarly articles on the treatment of a torn ACL. And a review does not necessarily mean that your reader wants you to give your personal opinion on whether or not you liked these sources.

What is a literature review, then?

A literature review discusses published information in a particular subject area, and sometimes information in a particular subject area within a certain time period.

A literature review can be just a simple summary of the sources, but it usually has an organizational pattern and combines both summary and synthesis. A summary is a recap of the important information of the source, but a synthesis is a re-organization, or a reshuffling, of that information. It might give a new interpretation of old material or combine new with old interpretations. Or it might trace the intellectual progression of the field, including major debates. And depending on the situation, the literature review may evaluate the sources and advise the reader on the most pertinent or relevant.

But how is a literature review different from an academic research paper?

The main focus of an academic research paper is to develop a new argument, and a research paper is likely to contain a literature review as one of its parts. In a research paper, you use the literature as a foundation and as support for a new insight that you contribute. The focus of a literature review, however, is to summarize and synthesize the arguments and ideas of others without adding new contributions.

Why do we write literature reviews?

Literature reviews provide you with a handy guide to a particular topic. If you have limited time to conduct research, literature reviews can give you an overview or act as a stepping stone. For professionals, they are useful reports that keep them up to date with what is current in the field. For scholars, the depth and breadth of the literature review emphasizes the credibility of the writer in his or her field. Literature reviews also provide a solid background for a research paper’s investigation. Comprehensive knowledge of the literature of the field is essential to most research papers.

Who writes these things, anyway?

Literature reviews are written occasionally in the humanities, but mostly in the sciences and social sciences; in experiment and lab reports, they constitute a section of the paper. Sometimes a literature review is written as a paper in itself.

Let’s get to it! What should I do before writing the literature review?

If your assignment is not very specific, seek clarification from your instructor:

• Roughly how many sources should you include?
• What types of sources (books, journal articles, websites)?
• Should you summarize, synthesize, or critique your sources by discussing a common theme or issue?
• Should you evaluate your sources?
• Should you provide subheadings and other background information, such as definitions and/or a history?

Find models

Look for other literature reviews in your area of interest or in the discipline and read them to get a sense of the types of themes you might want to look for in your own research or ways to organize your final review. You can simply put the word “review” in your search engine along with your other topic terms to find articles of this type on the Internet or in an electronic database. The bibliography or reference section of sources you’ve already read are also excellent entry points into your own research.

Narrow your topic

There are hundreds or even thousands of articles and books on most areas of study. The narrower your topic, the easier it will be to limit the number of sources you need to read in order to get a good survey of the material. Your instructor will probably not expect you to read everything that’s out there on the topic, but you’ll make your job easier if you first limit your scope.

Keep in mind that UNC Libraries have research guides and to databases relevant to many fields of study. You can reach out to the subject librarian for a consultation: https://library.unc.edu/support/consultations/ .

And don’t forget to tap into your professor’s (or other professors’) knowledge in the field. Ask your professor questions such as: “If you had to read only one book from the 90’s on topic X, what would it be?” Questions such as this help you to find and determine quickly the most seminal pieces in the field.

Consider whether your sources are current

Some disciplines require that you use information that is as current as possible. In the sciences, for instance, treatments for medical problems are constantly changing according to the latest studies. Information even two years old could be obsolete. However, if you are writing a review in the humanities, history, or social sciences, a survey of the history of the literature may be what is needed, because what is important is how perspectives have changed through the years or within a certain time period. Try sorting through some other current bibliographies or literature reviews in the field to get a sense of what your discipline expects. You can also use this method to consider what is currently of interest to scholars in this field and what is not.

Strategies for writing the literature review

Find a focus.

A literature review, like a term paper, is usually organized around ideas, not the sources themselves as an annotated bibliography would be organized. This means that you will not just simply list your sources and go into detail about each one of them, one at a time. No. As you read widely but selectively in your topic area, consider instead what themes or issues connect your sources together. Do they present one or different solutions? Is there an aspect of the field that is missing? How well do they present the material and do they portray it according to an appropriate theory? Do they reveal a trend in the field? A raging debate? Pick one of these themes to focus the organization of your review.

Convey it to your reader

A literature review may not have a traditional thesis statement (one that makes an argument), but you do need to tell readers what to expect. Try writing a simple statement that lets the reader know what is your main organizing principle. Here are a couple of examples:

The current trend in treatment for congestive heart failure combines surgery and medicine. More and more cultural studies scholars are accepting popular media as a subject worthy of academic consideration.

Consider organization

You’ve got a focus, and you’ve stated it clearly and directly. Now what is the most effective way of presenting the information? What are the most important topics, subtopics, etc., that your review needs to include? And in what order should you present them? Develop an organization for your review at both a global and local level:

First, cover the basic categories

Just like most academic papers, literature reviews also must contain at least three basic elements: an introduction or background information section; the body of the review containing the discussion of sources; and, finally, a conclusion and/or recommendations section to end the paper. The following provides a brief description of the content of each:

• Introduction: Gives a quick idea of the topic of the literature review, such as the central theme or organizational pattern.
• Body: Contains your discussion of sources and is organized either chronologically, thematically, or methodologically (see below for more information on each).
• Conclusions/Recommendations: Discuss what you have drawn from reviewing literature so far. Where might the discussion proceed?

Organizing the body

Once you have the basic categories in place, then you must consider how you will present the sources themselves within the body of your paper. Create an organizational method to focus this section even further.

To help you come up with an overall organizational framework for your review, consider the following scenario:

You’ve decided to focus your literature review on materials dealing with sperm whales. This is because you’ve just finished reading Moby Dick, and you wonder if that whale’s portrayal is really real. You start with some articles about the physiology of sperm whales in biology journals written in the 1980’s. But these articles refer to some British biological studies performed on whales in the early 18th century. So you check those out. Then you look up a book written in 1968 with information on how sperm whales have been portrayed in other forms of art, such as in Alaskan poetry, in French painting, or on whale bone, as the whale hunters in the late 19th century used to do. This makes you wonder about American whaling methods during the time portrayed in Moby Dick, so you find some academic articles published in the last five years on how accurately Herman Melville portrayed the whaling scene in his novel.

Now consider some typical ways of organizing the sources into a review:

• Chronological: If your review follows the chronological method, you could write about the materials above according to when they were published. For instance, first you would talk about the British biological studies of the 18th century, then about Moby Dick, published in 1851, then the book on sperm whales in other art (1968), and finally the biology articles (1980s) and the recent articles on American whaling of the 19th century. But there is relatively no continuity among subjects here. And notice that even though the sources on sperm whales in other art and on American whaling are written recently, they are about other subjects/objects that were created much earlier. Thus, the review loses its chronological focus.
• By publication: Order your sources by publication chronology, then, only if the order demonstrates a more important trend. For instance, you could order a review of literature on biological studies of sperm whales if the progression revealed a change in dissection practices of the researchers who wrote and/or conducted the studies.
• By trend: A better way to organize the above sources chronologically is to examine the sources under another trend, such as the history of whaling. Then your review would have subsections according to eras within this period. For instance, the review might examine whaling from pre-1600-1699, 1700-1799, and 1800-1899. Under this method, you would combine the recent studies on American whaling in the 19th century with Moby Dick itself in the 1800-1899 category, even though the authors wrote a century apart.
• Thematic: Thematic reviews of literature are organized around a topic or issue, rather than the progression of time. However, progression of time may still be an important factor in a thematic review. For instance, the sperm whale review could focus on the development of the harpoon for whale hunting. While the study focuses on one topic, harpoon technology, it will still be organized chronologically. The only difference here between a “chronological” and a “thematic” approach is what is emphasized the most: the development of the harpoon or the harpoon technology.But more authentic thematic reviews tend to break away from chronological order. For instance, a thematic review of material on sperm whales might examine how they are portrayed as “evil” in cultural documents. The subsections might include how they are personified, how their proportions are exaggerated, and their behaviors misunderstood. A review organized in this manner would shift between time periods within each section according to the point made.
• Methodological: A methodological approach differs from the two above in that the focusing factor usually does not have to do with the content of the material. Instead, it focuses on the “methods” of the researcher or writer. For the sperm whale project, one methodological approach would be to look at cultural differences between the portrayal of whales in American, British, and French art work. Or the review might focus on the economic impact of whaling on a community. A methodological scope will influence either the types of documents in the review or the way in which these documents are discussed. Once you’ve decided on the organizational method for the body of the review, the sections you need to include in the paper should be easy to figure out. They should arise out of your organizational strategy. In other words, a chronological review would have subsections for each vital time period. A thematic review would have subtopics based upon factors that relate to the theme or issue.

Sometimes, though, you might need to add additional sections that are necessary for your study, but do not fit in the organizational strategy of the body. What other sections you include in the body is up to you. Put in only what is necessary. Here are a few other sections you might want to consider:

• Current Situation: Information necessary to understand the topic or focus of the literature review.
• History: The chronological progression of the field, the literature, or an idea that is necessary to understand the literature review, if the body of the literature review is not already a chronology.
• Methods and/or Standards: The criteria you used to select the sources in your literature review or the way in which you present your information. For instance, you might explain that your review includes only peer-reviewed articles and journals.

Questions for Further Research: What questions about the field has the review sparked? How will you further your research as a result of the review?

Begin composing

Once you’ve settled on a general pattern of organization, you’re ready to write each section. There are a few guidelines you should follow during the writing stage as well. Here is a sample paragraph from a literature review about sexism and language to illuminate the following discussion:

However, other studies have shown that even gender-neutral antecedents are more likely to produce masculine images than feminine ones (Gastil, 1990). Hamilton (1988) asked students to complete sentences that required them to fill in pronouns that agreed with gender-neutral antecedents such as “writer,” “pedestrian,” and “persons.” The students were asked to describe any image they had when writing the sentence. Hamilton found that people imagined 3.3 men to each woman in the masculine “generic” condition and 1.5 men per woman in the unbiased condition. Thus, while ambient sexism accounted for some of the masculine bias, sexist language amplified the effect. (Source: Erika Falk and Jordan Mills, “Why Sexist Language Affects Persuasion: The Role of Homophily, Intended Audience, and Offense,” Women and Language19:2).

Use evidence

In the example above, the writers refer to several other sources when making their point. A literature review in this sense is just like any other academic research paper. Your interpretation of the available sources must be backed up with evidence to show that what you are saying is valid.

Be selective

Select only the most important points in each source to highlight in the review. The type of information you choose to mention should relate directly to the review’s focus, whether it is thematic, methodological, or chronological.

Use quotes sparingly

Falk and Mills do not use any direct quotes. That is because the survey nature of the literature review does not allow for in-depth discussion or detailed quotes from the text. Some short quotes here and there are okay, though, if you want to emphasize a point, or if what the author said just cannot be rewritten in your own words. Notice that Falk and Mills do quote certain terms that were coined by the author, not common knowledge, or taken directly from the study. But if you find yourself wanting to put in more quotes, check with your instructor.

Summarize and synthesize

Remember to summarize and synthesize your sources within each paragraph as well as throughout the review. The authors here recapitulate important features of Hamilton’s study, but then synthesize it by rephrasing the study’s significance and relating it to their own work.

Keep your own voice

While the literature review presents others’ ideas, your voice (the writer’s) should remain front and center. Notice that Falk and Mills weave references to other sources into their own text, but they still maintain their own voice by starting and ending the paragraph with their own ideas and their own words. The sources support what Falk and Mills are saying.

Use caution when paraphrasing

When paraphrasing a source that is not your own, be sure to represent the author’s information or opinions accurately and in your own words. In the preceding example, Falk and Mills either directly refer in the text to the author of their source, such as Hamilton, or they provide ample notation in the text when the ideas they are mentioning are not their own, for example, Gastil’s. For more information, please see our handout on plagiarism .

Revise, revise, revise

Draft in hand? Now you’re ready to revise. Spending a lot of time revising is a wise idea, because your main objective is to present the material, not the argument. So check over your review again to make sure it follows the assignment and/or your outline. Then, just as you would for most other academic forms of writing, rewrite or rework the language of your review so that you’ve presented your information in the most concise manner possible. Be sure to use terminology familiar to your audience; get rid of unnecessary jargon or slang. Finally, double check that you’ve documented your sources and formatted the review appropriately for your discipline. For tips on the revising and editing process, see our handout on revising drafts .

Works consulted

We consulted these works while writing this handout. This is not a comprehensive list of resources on the handout’s topic, and we encourage you to do your own research to find additional publications. Please do not use this list as a model for the format of your own reference list, as it may not match the citation style you are using. For guidance on formatting citations, please see the UNC Libraries citation tutorial . We revise these tips periodically and welcome feedback.

Anson, Chris M., and Robert A. Schwegler. 2010. The Longman Handbook for Writers and Readers , 6th ed. New York: Longman.

Jones, Robert, Patrick Bizzaro, and Cynthia Selfe. 1997. The Harcourt Brace Guide to Writing in the Disciplines . New York: Harcourt Brace.

Lamb, Sandra E. 1998. How to Write It: A Complete Guide to Everything You’ll Ever Write . Berkeley: Ten Speed Press.

Rosen, Leonard J., and Laurence Behrens. 2003. The Allyn & Bacon Handbook , 5th ed. New York: Longman.

Troyka, Lynn Quittman, and Doug Hesse. 2016. Simon and Schuster Handbook for Writers , 11th ed. London: Pearson.

You may reproduce it for non-commercial use if you use the entire handout and attribute the source: The Writing Center, University of North Carolina at Chapel Hill

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

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

Importance of a Good Literature Review

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

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

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

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

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

Types of Literature Reviews

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

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

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

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

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

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

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

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

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

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

Structure and Writing Style

I.  Thinking About Your Literature Review

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

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

The critical evaluation of each work should consider :

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

II.  Development of the Literature Review

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

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

III.  Ways to Organize Your Literature Review

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

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

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

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

IV.  Writing Your Literature Review

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

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

V.  Common Mistakes to Avoid

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

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

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

Writing Tip

Break Out of Your Disciplinary Box!

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

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

Another Writing Tip

Don't Just Review for Content!

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

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

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

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

Yet Another Writing Tip

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

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

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

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

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How to Write a Literature Review

What is a literature review.

• What Is the Literature
• Writing the Review

A literature review is much more than an annotated bibliography or a list of separate reviews of articles and books. It is a critical, analytical summary and synthesis of the current knowledge of a topic. Thus it should compare and relate different theories, findings, etc, rather than just summarize them individually. In addition, it should have a particular focus or theme to organize the review. It does not have to be an exhaustive account of everything published on the topic, but it should discuss all the significant academic literature and other relevant sources important for that focus.

This is meant to be a general guide to writing a literature review: ways to structure one, what to include, how it supplements other research. For more specific help on writing a review, and especially for help on finding the literature to review, sign up for a Personal Research Session .

The specific organization of a literature review depends on the type and purpose of the review, as well as on the specific field or topic being reviewed. But in general, it is a relatively brief but thorough exploration of past and current work on a topic. Rather than a chronological listing of previous work, though, literature reviews are usually organized thematically, such as different theoretical approaches, methodologies, or specific issues or concepts involved in the topic. A thematic organization makes it much easier to examine contrasting perspectives, theoretical approaches, methodologies, findings, etc, and to analyze the strengths and weaknesses of, and point out any gaps in, previous research. And this is the heart of what a literature review is about. A literature review may offer new interpretations, theoretical approaches, or other ideas; if it is part of a research proposal or report it should demonstrate the relationship of the proposed or reported research to others' work; but whatever else it does, it must provide a critical overview of the current state of research efforts. 

Literature reviews are common and very important in the sciences and social sciences. They are less common and have a less important role in the humanities, but they do have a place, especially stand-alone reviews.

Types of Literature Reviews

There are different types of literature reviews, and different purposes for writing a review, but the most common are:

• Stand-alone literature review articles . These provide an overview and analysis of the current state of research on a topic or question. The goal is to evaluate and compare previous research on a topic to provide an analysis of what is currently known, and also to reveal controversies, weaknesses, and gaps in current work, thus pointing to directions for future research. You can find examples published in any number of academic journals, but there is a series of Annual Reviews of *Subject* which are specifically devoted to literature review articles. Writing a stand-alone review is often an effective way to get a good handle on a topic and to develop ideas for your own research program. For example, contrasting theoretical approaches or conflicting interpretations of findings can be the basis of your research project: can you find evidence supporting one interpretation against another, or can you propose an alternative interpretation that overcomes their limitations?
• Part of a research proposal . This could be a proposal for a PhD dissertation, a senior thesis, or a class project. It could also be a submission for a grant. The literature review, by pointing out the current issues and questions concerning a topic, is a crucial part of demonstrating how your proposed research will contribute to the field, and thus of convincing your thesis committee to allow you to pursue the topic of your interest or a funding agency to pay for your research efforts.
• Part of a research report . When you finish your research and write your thesis or paper to present your findings, it should include a literature review to provide the context to which your work is a contribution. Your report, in addition to detailing the methods, results, etc. of your research, should show how your work relates to others' work.

A literature review for a research report is often a revision of the review for a research proposal, which can be a revision of a stand-alone review. Each revision should be a fairly extensive revision. With the increased knowledge of and experience in the topic as you proceed, your understanding of the topic will increase. Thus, you will be in a better position to analyze and critique the literature. In addition, your focus will change as you proceed in your research. Some areas of the literature you initially reviewed will be marginal or irrelevant for your eventual research, and you will need to explore other areas more thoroughly. 

Examples of Literature Reviews

See the series of Annual Reviews of *Subject* which are specifically devoted to literature review articles to find many examples of stand-alone literature reviews in the biomedical, physical, and social sciences. 

Research report articles vary in how they are organized, but a common general structure is to have sections such as:

• Abstract - Brief summary of the contents of the article
• Introduction - A explanation of the purpose of the study, a statement of the research question(s) the study intends to address
• Literature review - A critical assessment of the work done so far on this topic, to show how the current study relates to what has already been done
• Methods - How the study was carried out (e.g. instruments or equipment, procedures, methods to gather and analyze data)
• Results - What was found in the course of the study
• Discussion - What do the results mean
• Conclusion - State the conclusions and implications of the results, and discuss how it relates to the work reviewed in the literature review; also, point to directions for further work in the area

Here are some articles that illustrate variations on this theme. There is no need to read the entire articles (unless the contents interest you); just quickly browse through to see the sections, and see how each section is introduced and what is contained in them.

The Determinants of Undergraduate Grade Point Average: The Relative Importance of Family Background, High School Resources, and Peer Group Effects , in The Journal of Human Resources , v. 34 no. 2 (Spring 1999), p. 268-293.

This article has a standard breakdown of sections:

• Introduction
• Literature Review
• Some discussion sections

First Encounters of the Bureaucratic Kind: Early Freshman Experiences with a Campus Bureaucracy , in The Journal of Higher Education , v. 67 no. 6 (Nov-Dec 1996), p. 660-691.

This one does not have a section specifically labeled as a "literature review" or "review of the literature," but the first few sections cite a long list of other sources discussing previous research in the area before the authors present their own study they are reporting.

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How To Structure Your Literature Review

3 options to help structure your chapter.

By: Amy Rommelspacher (PhD) | Reviewer: Dr Eunice Rautenbach | November 2020 (Updated May 2023)

Writing the literature review chapter can seem pretty daunting when you’re piecing together your dissertation or thesis. As  we’ve discussed before , a good literature review needs to achieve a few very important objectives – it should:

• Demonstrate your knowledge of the research topic
• Identify the gaps in the literature and show how your research links to these
• Provide the foundation for your conceptual framework (if you have one)
• Inform your own  methodology and research design

To achieve this, your literature review needs a well-thought-out structure . Get the structure of your literature review chapter wrong and you’ll struggle to achieve these objectives. Don’t worry though – in this post, we’ll look at how to structure your literature review for maximum impact (and marks!).

But wait – is this the right time?

Deciding on the structure of your literature review should come towards the end of the literature review process – after you have collected and digested the literature, but before you start writing the chapter. 

In other words, you need to first develop a rich understanding of the literature before you even attempt to map out a structure. There’s no use trying to develop a structure before you’ve fully wrapped your head around the existing research.

Equally importantly, you need to have a structure in place before you start writing , or your literature review will most likely end up a rambling, disjointed mess. 

Importantly, don’t feel that once you’ve defined a structure you can’t iterate on it. It’s perfectly natural to adjust as you engage in the writing process. As we’ve discussed before , writing is a way of developing your thinking, so it’s quite common for your thinking to change – and therefore, for your chapter structure to change – as you write. 

Need a helping hand?

Like any other chapter in your thesis or dissertation, your literature review needs to have a clear, logical structure. At a minimum, it should have three essential components – an  introduction , a  body   and a  conclusion . 

Let’s take a closer look at each of these.

1: The Introduction Section

Just like any good introduction, the introduction section of your literature review should introduce the purpose and layout (organisation) of the chapter. In other words, your introduction needs to give the reader a taste of what’s to come, and how you’re going to lay that out. Essentially, you should provide the reader with a high-level roadmap of your chapter to give them a taste of the journey that lies ahead.

Here’s an example of the layout visualised in a literature review introduction:

Your introduction should also outline your topic (including any tricky terminology or jargon) and provide an explanation of the scope of your literature review – in other words, what you  will   and  won’t   be covering (the delimitations ). This helps ringfence your review and achieve a clear focus . The clearer and narrower your focus, the deeper you can dive into the topic (which is typically where the magic lies). 

Depending on the nature of your project, you could also present your stance or point of view at this stage. In other words, after grappling with the literature you’ll have an opinion about what the trends and concerns are in the field as well as what’s lacking. The introduction section can then present these ideas so that it is clear to examiners that you’re aware of how your research connects with existing knowledge .

2: The Body Section

The body of your literature review is the centre of your work. This is where you’ll present, analyse, evaluate and synthesise the existing research. In other words, this is where you’re going to earn (or lose) the most marks. Therefore, it’s important to carefully think about how you will organise your discussion to present it in a clear way. 

The body of your literature review should do just as the description of this chapter suggests. It should “review” the literature – in other words, identify, analyse, and synthesise it. So, when thinking about structuring your literature review, you need to think about which structural approach will provide the best “review” for your specific type of research and objectives (we’ll get to this shortly).

There are (broadly speaking)  three options  for organising your literature review.

Option 1: Chronological (according to date)

Organising the literature chronologically is one of the simplest ways to structure your literature review. You start with what was published first and work your way through the literature until you reach the work published most recently. Pretty straightforward.

The benefit of this option is that it makes it easy to discuss the developments and debates in the field as they emerged over time. Organising your literature chronologically also allows you to highlight how specific articles or pieces of work might have changed the course of the field – in other words, which research has had the most impact . Therefore, this approach is very useful when your research is aimed at understanding how the topic has unfolded over time and is often used by scholars in the field of history. That said, this approach can be utilised by anyone that wants to explore change over time .

For example , if a student of politics is investigating how the understanding of democracy has evolved over time, they could use the chronological approach to provide a narrative that demonstrates how this understanding has changed through the ages.

Here are some questions you can ask yourself to help you structure your literature review chronologically.

• What is the earliest literature published relating to this topic?
• How has the field changed over time? Why?
• What are the most recent discoveries/theories?

In some ways, chronology plays a part whichever way you decide to structure your literature review, because you will always, to a certain extent, be analysing how the literature has developed. However, with the chronological approach, the emphasis is very firmly on how the discussion has evolved over time , as opposed to how all the literature links together (which we’ll discuss next ).

Option 2: Thematic (grouped by theme)

The thematic approach to structuring a literature review means organising your literature by theme or category – for example, by independent variables (i.e. factors that have an impact on a specific outcome).

As you’ve been collecting and synthesising literature , you’ll likely have started seeing some themes or patterns emerging. You can then use these themes or patterns as a structure for your body discussion. The thematic approach is the most common approach and is useful for structuring literature reviews in most fields.

For example, if you were researching which factors contributed towards people trusting an organisation, you might find themes such as consumers’ perceptions of an organisation’s competence, benevolence and integrity. Structuring your literature review thematically would mean structuring your literature review’s body section to discuss each of these themes, one section at a time.

Here are some questions to ask yourself when structuring your literature review by themes:

• Are there any patterns that have come to light in the literature?
• What are the central themes and categories used by the researchers?
• Do I have enough evidence of these themes?

PS – you can see an example of a thematically structured literature review in our literature review sample walkthrough video here.

Option 3: Methodological

The methodological option is a way of structuring your literature review by the research methodologies used . In other words, organising your discussion based on the angle from which each piece of research was approached – for example, qualitative , quantitative or mixed  methodologies.

Structuring your literature review by methodology can be useful if you are drawing research from a variety of disciplines and are critiquing different methodologies. The point of this approach is to question  how  existing research has been conducted, as opposed to  what  the conclusions and/or findings the research were.

For example, a sociologist might centre their research around critiquing specific fieldwork practices. Their literature review will then be a summary of the fieldwork methodologies used by different studies.

Here are some questions you can ask yourself when structuring your literature review according to methodology:

• Which methodologies have been utilised in this field?
• Which methodology is the most popular (and why)?
• What are the strengths and weaknesses of the various methodologies?
• How can the existing methodologies inform my own methodology?

3: The Conclusion Section

Once you’ve completed the body section of your literature review using one of the structural approaches we discussed above, you’ll need to “wrap up” your literature review and pull all the pieces together to set the direction for the rest of your dissertation or thesis.

The conclusion is where you’ll present the key findings of your literature review. In this section, you should emphasise the research that is especially important to your research questions and highlight the gaps that exist in the literature. Based on this, you need to make it clear what you will add to the literature – in other words, justify your own research by showing how it will help fill one or more of the gaps you just identified.

Last but not least, if it’s your intention to develop a conceptual framework for your dissertation or thesis, the conclusion section is a good place to present this.

Example: Thematically Structured Review

In the video below, we unpack a literature review chapter so that you can see an example of a thematically structure review in practice.

Let’s Recap

In this article, we’ve  discussed how to structure your literature review for maximum impact. Here’s a quick recap of what  you need to keep in mind when deciding on your literature review structure:

• Just like other chapters, your literature review needs a clear introduction , body and conclusion .
• The introduction section should provide an overview of what you will discuss in your literature review.
• The body section of your literature review can be organised by chronology , theme or methodology . The right structural approach depends on what you’re trying to achieve with your research.
• The conclusion section should draw together the key findings of your literature review and link them to your research questions.

If you’re ready to get started, be sure to download our free literature review template to fast-track your chapter outline.

Psst… there’s more!

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

29 Comments

Great work. This is exactly what I was looking for and helps a lot together with your previous post on literature review. One last thing is missing: a link to a great literature chapter of an journal article (maybe with comments of the different sections in this review chapter). Do you know any great literature review chapters?

I agree with you Marin… A great piece

I agree with Marin. This would be quite helpful if you annotate a nicely structured literature from previously published research articles.

Awesome article for my research.

I thank you immensely for this wonderful guide

It is indeed thought and supportive work for the futurist researcher and students

Very educative and good time to get guide. Thank you

Great work, very insightful. Thank you.

Thanks for this wonderful presentation. My question is that do I put all the variables into a single conceptual framework or each hypothesis will have it own conceptual framework?

Thank you very much, very helpful

This is very educative and precise . Thank you very much for dropping this kind of write up .

Pheeww, so damn helpful, thank you for this informative piece.

I’m doing a research project topic ; stool analysis for parasitic worm (enteric) worm, how do I structure it, thanks.

comprehensive explanation. Help us by pasting the URL of some good “literature review” for better understanding.

great piece. thanks for the awesome explanation. it is really worth sharing. I have a little question, if anyone can help me out, which of the options in the body of literature can be best fit if you are writing an architectural thesis that deals with design?

I am doing a research on nanofluids how can l structure it?

Beautifully clear.nThank you!

Lucid! Thankyou!

Brilliant work, well understood, many thanks

I like how this was so clear with simple language 😊😊 thank you so much 😊 for these information 😊

Insightful. I was struggling to come up with a sensible literature review but this has been really helpful. Thank you!

You have given thought-provoking information about the review of the literature.

Thank you. It has made my own research better and to impart your work to students I teach

I learnt a lot from this teaching. It’s a great piece.

I am doing research on EFL teacher motivation for his/her job. How Can I structure it? Is there any detailed template, additional to this?

You are so cool! I do not think I’ve read through something like this before. So nice to find somebody with some genuine thoughts on this issue. Seriously.. thank you for starting this up. This site is one thing that is required on the internet, someone with a little originality!

I’m asked to do conceptual, theoretical and empirical literature, and i just don’t know how to structure it

Asking questions are actually fastidious thing if you are not understanding anything fully, but this article presents good understanding yet.

thank you SOOO much it is really helpful ..

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What is a literature review?

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

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

Why is it important?

A literature review is important because it:

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

APA7 Style resources

APA Style Blog - for those harder to find answers

1. Choose a topic. Define your research question.

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

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

2. Decide on the scope of your review

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

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

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

Make a list of the databases you will search. 

Where to find databases:

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

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

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

Review the literature

Some questions to help you analyze the research:

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

Tips: 

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

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A literature review should be structured like any other essay: it should have an introduction, a middle or main body, and a conclusion.

The introduction should:

• define your topic and provide an appropriate context for reviewing the literature;
• establish your reasons – i.e. point of view – for
• reviewing the literature;
• explain the organisation – i.e. sequence – of the review;
• state the scope of the review – i.e. what is included and what isn’t included. For example, if you were reviewing the literature on obesity in children you might say something like: There are a large number of studies of obesity trends in the general population. However, since the focus of this research is on obesity in children, these will not be reviewed in detail and will only be referred to as appropriate.

The middle or main body should:

• organise the literature according to common themes;
• provide insight into the relation between your chosen topic and the wider subject area e.g. between obesity in children and obesity in general;
• move from a general, wider view of the literature being reviewed to the specific focus of your research.

The conclusion should:

• summarise the important aspects of the existing body of literature;
• evaluate the current state of the literature reviewed;
• identify significant flaws or gaps in existing knowledge;
• outline areas for future study;
• link your research to existing knowledge.

Literature reviews

What this guide covers, what is a literature review, literature review resources, types of literature reviews, what is the difference between a literature review and a systematic review, related information and guides, further help.

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Attribute our work under a Creative Commons Attribution-NonCommercial 4.0 International License.

The literature review process involves a number of steps.

This guide focuses on:

• evaluating.

A literature review is a survey and critical analysis of what has been written on a particular topic, theory, question or method.

"In writing the literature review, the purpose is to explore what knowledge and ideas have been established on a topic, what approaches and viewpoints have been adopted, and what are their strengths and weaknesses."

Source: "Focus and frame". (2008). In Eriksson, P. & Kovalainen, A. Introducing Qualitative Methods: Qualitative methods in business research (pp. 44) . London: SAGE Publications Ltd. doi: 10.4135/9780857028044.

Get an overview on doing a literature review:

• Sage research methods online - Literature review methods map Information on the literature review methodology with links to further resources - the Project Planner, books, articles, videos and more.
• Ten simple rules for writing a literature review Gives 10 tips on how to approach and carry out a literature review. By Pautasso M (2013) Ten Simple Rules for Writing a Literature Review. PLoS Comput Biol9(7): e1003149.
• The literature review. In: Doing your undergraduate program This chapter looks at the purpose of literature reviews, how it is done, setting the boundaries of your search and more.

• More books on literature reviews A selection of literature review books available via UQ Library Search.

The type of literature review you do will depend on a variety of factors:

• Your discipline
• The purpose - undergraduate assessment, PHD thesis, journal article?
• Your lecturer or supervisor's requirements.

Always follow the guidelines outlined by your lecturer or supervisor or consult the instructions for authors (for journal articles), when conducting your literature review.

• is an overview of the significant literature on a topic
• typically includes a critical analysis of each work included
• demonstrates the reviewers knowledge of the topic.
• is a list of citations of research sources (books, journal articles, websites etc) on a topic
• includes a brief summary and analysis or evaluation of each citation = the annotation.
• a critical assessment of all research studies on a particular research question
• has specific criteria for collecting and evaluating the literature
• includes a synthesis of the findings of the included studies.
• This method developed by Griffith University's School of Environment bridges the gap between traditional narrative review methods and meta-analyses to enable students to produce results that are reliable, quantifiable and reproducible.

The requirements of narrative literature reviews are usually quite different than systematic reviews . However, you may be required to adopt some of the characteristics of a systematic approach when doing your literature review. Check the guidelines or criteria that have been set by your supervisor so you know what is expected of you.

Characteristics of reviews

• Meeting the review family: Exploring review types and associated information retrieval requirements This article defines different review types and discusses appropriate search methods for each type.
• Writing literature reviews - Student Support Student Support provides information on how to write effective literature reviews.
• Writing skills Learn strategies for good writing from the Graduate School.
• Systematic reviews An overview of systematic reviews and resources to support producing one.
• Subject guides See recommended resources in different subject areas.
• Grey literature Find literature that is not available in traditional channels of publishing and distribution.
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Writing: Literature Review Basics

• What is Synthesis?
• Organizing Your Research
• Paraphrasing, Summary, or Direct Quotation?
• Introductions
• Conclusions
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The Most Important Thing

The best time to write an introduction is AFTER you write the body of your paper.

Well, how do you know what to introduce until after you've figured out what you want to say?

The best time to write an introduction is as one of the last things you do.

Basic Introduction Template

For any other sort of scholarly writing, the following basic structure works well for an introduction:

• What has been said or done on this topic?  
• What is the problem with what has been said or done?
• What will you offer to solve the problem?  (The answer to this is your thesis statement.)
• How does your solution address necessary change?

Writing an Introduction

The job of an introduction is to preview what you are going to say so the audience knows what is coming.  A good introduction starts out generally and works towards a specific statement of what you intend to discuss in your writing. 

The introduction explains the focus and establishes the importance of the subject. It discusses what kind of work has been done on the topic and identifies any controversies within the field or any recent research which has raised questions about earlier assumptions. It may provide background or history, and it indicates why the topic is important, interesting, problematic, or relevant in some way.  It concludes with a purpose or thesis statement. In a stand-alone literature review, this statement will sum up and evaluate the state of the art in this field of research; in a review that is an introduction or preparatory to a larger work, such as the Culminating Project, it will suggest how the review findings will lead to the research the writer proposes to undertake.

In a literature review, an introduction may contain the following:

• A concise definition of a topic under consideration (this may be a descriptive or argumentative thesis, or proposal), as well as the scope of the related literature being investigated. (Example: If the topic under consideration is ‘women’s wartime diaries’, the scope of the review may be limited to published or unpublished works, works in English, works from a particular location, time period, or conflict, etc.)  
• The introduction should also note what topics are being included and what are intentional exclusions. (Example: “This review will not explore the diaries of adolescent girls.”)
• A final sentence should signal the list of key topics that will be used to discuss the selected sources.

Many theories have been proposed to explain what motivates human behavior. Although the literature covers a wide variety of such theories, this review will focus on five major themes which emerge repeatedly throughout the literature reviewed. These themes are incorporation of the self-concept into traditional theories of motivation, the influence of rewards on motivation, the increasing importance of internal forces of motivation, autonomy and self-control as sources of motivation, and narcissism as an essential component of motivation. Although the literature presents these themes in a variety of contexts, this paper will primarily focus on their application to self-motivation.

Let's break that apart.

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Writing Research Papers

• Writing a Literature Review

When writing a research paper on a specific topic, you will often need to include an overview of any prior research that has been conducted on that topic.  For example, if your research paper is describing an experiment on fear conditioning, then you will probably need to provide an overview of prior research on fear conditioning.  That overview is typically known as a literature review.  

Please note that a full-length literature review article may be suitable for fulfilling the requirements for the Psychology B.S. Degree Research Paper .  For further details, please check with your faculty advisor.

Different Types of Literature Reviews

Literature reviews come in many forms.  They can be part of a research paper, for example as part of the Introduction section.  They can be one chapter of a doctoral dissertation.  Literature reviews can also “stand alone” as separate articles by themselves.  For instance, some journals such as Annual Review of Psychology , Psychological Bulletin , and others typically publish full-length review articles.  Similarly, in courses at UCSD, you may be asked to write a research paper that is itself a literature review (such as, with an instructor’s permission, in fulfillment of the B.S. Degree Research Paper requirement). Alternatively, you may be expected to include a literature review as part of a larger research paper (such as part of an Honors Thesis). 

Literature reviews can be written using a variety of different styles.  These may differ in the way prior research is reviewed as well as the way in which the literature review is organized.  Examples of stylistic variations in literature reviews include: 

• Summarization of prior work vs. critical evaluation. In some cases, prior research is simply described and summarized; in other cases, the writer compares, contrasts, and may even critique prior research (for example, discusses their strengths and weaknesses).
• Chronological vs. categorical and other types of organization. In some cases, the literature review begins with the oldest research and advances until it concludes with the latest research.  In other cases, research is discussed by category (such as in groupings of closely related studies) without regard for chronological order.  In yet other cases, research is discussed in terms of opposing views (such as when different research studies or researchers disagree with one another).

Overall, all literature reviews, whether they are written as a part of a larger work or as separate articles unto themselves, have a common feature: they do not present new research; rather, they provide an overview of prior research on a specific topic . 

How to Write a Literature Review

When writing a literature review, it can be helpful to rely on the following steps.  Please note that these procedures are not necessarily only for writing a literature review that becomes part of a larger article; they can also be used for writing a full-length article that is itself a literature review (although such reviews are typically more detailed and exhaustive; for more information please refer to the Further Resources section of this page).

Steps for Writing a Literature Review

1. Identify and define the topic that you will be reviewing.

The topic, which is commonly a research question (or problem) of some kind, needs to be identified and defined as clearly as possible.  You need to have an idea of what you will be reviewing in order to effectively search for references and to write a coherent summary of the research on it.  At this stage it can be helpful to write down a description of the research question, area, or topic that you will be reviewing, as well as to identify any keywords that you will be using to search for relevant research.

2. Conduct a literature search.

Use a range of keywords to search databases such as PsycINFO and any others that may contain relevant articles.  You should focus on peer-reviewed, scholarly articles.  Published books may also be helpful, but keep in mind that peer-reviewed articles are widely considered to be the “gold standard” of scientific research.  Read through titles and abstracts, select and obtain articles (that is, download, copy, or print them out), and save your searches as needed.  For more information about this step, please see the Using Databases and Finding Scholarly References section of this website.

3. Read through the research that you have found and take notes.

Absorb as much information as you can.  Read through the articles and books that you have found, and as you do, take notes.  The notes should include anything that will be helpful in advancing your own thinking about the topic and in helping you write the literature review (such as key points, ideas, or even page numbers that index key information).  Some references may turn out to be more helpful than others; you may notice patterns or striking contrasts between different sources ; and some sources may refer to yet other sources of potential interest.  This is often the most time-consuming part of the review process.  However, it is also where you get to learn about the topic in great detail.  For more details about taking notes, please see the “Reading Sources and Taking Notes” section of the Finding Scholarly References page of this website.

4. Organize your notes and thoughts; create an outline.

At this stage, you are close to writing the review itself.  However, it is often helpful to first reflect on all the reading that you have done.  What patterns stand out?  Do the different sources converge on a consensus?  Or not?  What unresolved questions still remain?  You should look over your notes (it may also be helpful to reorganize them), and as you do, to think about how you will present this research in your literature review.  Are you going to summarize or critically evaluate?  Are you going to use a chronological or other type of organizational structure?  It can also be helpful to create an outline of how your literature review will be structured.

5. Write the literature review itself and edit and revise as needed.

The final stage involves writing.  When writing, keep in mind that literature reviews are generally characterized by a summary style in which prior research is described sufficiently to explain critical findings but does not include a high level of detail (if readers want to learn about all the specific details of a study, then they can look up the references that you cite and read the original articles themselves).  However, the degree of emphasis that is given to individual studies may vary (more or less detail may be warranted depending on how critical or unique a given study was).   After you have written a first draft, you should read it carefully and then edit and revise as needed.  You may need to repeat this process more than once.  It may be helpful to have another person read through your draft(s) and provide feedback.

6. Incorporate the literature review into your research paper draft.

After the literature review is complete, you should incorporate it into your research paper (if you are writing the review as one component of a larger paper).  Depending on the stage at which your paper is at, this may involve merging your literature review into a partially complete Introduction section, writing the rest of the paper around the literature review, or other processes.

Further Tips for Writing a Literature Review

Full-length literature reviews

• Many full-length literature review articles use a three-part structure: Introduction (where the topic is identified and any trends or major problems in the literature are introduced), Body (where the studies that comprise the literature on that topic are discussed), and Discussion or Conclusion (where major patterns and points are discussed and the general state of what is known about the topic is summarized)

Literature reviews as part of a larger paper

• An “express method” of writing a literature review for a research paper is as follows: first, write a one paragraph description of each article that you read. Second, choose how you will order all the paragraphs and combine them in one document.  Third, add transitions between the paragraphs, as well as an introductory and concluding paragraph. 1
• A literature review that is part of a larger research paper typically does not have to be exhaustive. Rather, it should contain most or all of the significant studies about a research topic but not tangential or loosely related ones. 2   Generally, literature reviews should be sufficient for the reader to understand the major issues and key findings about a research topic.  You may however need to confer with your instructor or editor to determine how comprehensive you need to be.

Benefits of Literature Reviews

By summarizing prior research on a topic, literature reviews have multiple benefits.  These include:

• Literature reviews help readers understand what is known about a topic without having to find and read through multiple sources.
• Literature reviews help “set the stage” for later reading about new research on a given topic (such as if they are placed in the Introduction of a larger research paper). In other words, they provide helpful background and context.
• Literature reviews can also help the writer learn about a given topic while in the process of preparing the review itself. In the act of research and writing the literature review, the writer gains expertise on the topic .

Downloadable Resources

• How to Write APA Style Research Papers (a comprehensive guide) [ PDF ]
• Tips for Writing APA Style Research Papers (a brief summary) [ PDF ]
• Example APA Style Research Paper (for B.S. Degree – literature review) [ PDF ]

Further Resources

How-To Videos     

• Writing Research Paper Videos
• UCSD Library Psychology Research Guide: Literature Reviews

External Resources

• Developing and Writing a Literature Review from N Carolina A&T State University
• Example of a Short Literature Review from York College CUNY
• How to Write a Review of Literature from UW-Madison
• Writing a Literature Review from UC Santa Cruz  
• Pautasso, M. (2013). Ten Simple Rules for Writing a Literature Review. PLoS Computational Biology, 9 (7), e1003149. doi : 1371/journal.pcbi.1003149

1 Ashton, W. Writing a short literature review . [PDF]     

2 carver, l. (2014).  writing the research paper [workshop]. , prepared by s. c. pan for ucsd psychology.

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Writing and Presenting Guide

Writing literature reviews, what is a literature review.

"A literature review discusses published information in a particular subject area, and sometimes information in a particular subject area within a certain time period. A literature review can be just a simple summary of the sources, but it usually has an organizational pattern and combines both summary and synthesis. A summary is a recap of the important information of the source, but a synthesis is a re-organization, or a reshuffling, of that information. It might give a new interpretation of old material or combine new with old interpretations. Or it might trace the intellectual progression of the field, including major debates. And depending on the situation, the literature review may evaluate the sources and advise the reader on the most pertinent or relevant." Source: The Writing Center at UNC-Chapel Hill. (2013). Literature Reviews. Retrieved from https://writingcenter.unc.edu/handouts/literature-reviews/ This link opens in a new window

Need help writing a literature review?

Check out these resources:

Helpful Books from the Library

Helpful Web Resources

• Literature Reviews (UNC Writing Center) This link opens in a new window
• Learn How to Write a Review of Literature (The Writing Center at the Univ. of Wisconsin) This link opens in
• The Literature Review (Univ. of Toronto) This link opens in a new window
• Write a Literature Review (University Library at Univ. Of California Santa Cruz) This link opens in a new wi
• Literature Reviews (Ithaca) This link opens in a new window
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• Open access
• Published: 19 September 2024

Machine learning in business and finance: a literature review and research opportunities

• Hanyao Gao 1 ,
• Gang Kou 2 ,
• Haiming Liang 1 ,
• Hengjie Zhang 3 ,
• Xiangrui Chao 1 ,
• Cong-Cong Li 5 &
• Yucheng Dong 1 , 4  

Financial Innovation volume  10 , Article number:  86 ( 2024 ) Cite this article

Metrics details

This study provides a comprehensive review of machine learning (ML) applications in the fields of business and finance. First, it introduces the most commonly used ML techniques and explores their diverse applications in marketing, stock analysis, demand forecasting, and energy marketing. In particular, this review critically analyzes over 100 articles and reveals a strong inclination toward deep learning techniques, such as deep neural, convolutional neural, and recurrent neural networks, which have garnered immense popularity in financial contexts owing to their remarkable performance. This review shows that ML techniques, particularly deep learning, demonstrate substantial potential for enhancing business decision-making processes and achieving more accurate and efficient predictions of financial outcomes. In particular, ML techniques exhibit promising research prospects in cryptocurrencies, financial crime detection, and marketing, underscoring the extensive opportunities in these areas. However, some limitations regarding ML applications in the business and finance domains remain, including issues related to linguistic information processes, interpretability, data quality, generalization, and the oversights related to social networks and causal relationships. Thus, addressing these challenges is a promising avenue for future research.

Introduction

The rapid development of information and database technologies, coupled with notable progress in data analysis methods and computer hardware, has led to an exponential increase in the application of ML techniques in various areas, including business and finance (Ghoddusi et al. 2019 ; Gogas and Papadimitriou 2021 ; Chen et al. 2022 ; Hoang and Wiegratz 2022 ; Nazareth and Ramana 2023 ; Ozbayoglu et al. 2020 ; Xiao and Ke 2021 ). The progress in ML techniques in business and finance applications, such as marketing, e-commerce, and energy, has been highly successful, yielding promising results (Athey and Imbens 2019 ). Compared to traditional econometric models, ML techniques can more effectively handle large amounts of structured and unstructured data, enabling rapid decision-making and forecasting. These benefits stem from ML techniques’ ability to avoid making specific assumptions about the functional form, parameter distribution, or variable interactions and instead focus on making accurate predictions about the dependent variables based on other variables.

Exploring scientific databases, such as the Thomson Reuters Web of Science, reveals a significant exponential increase in the utilization of ML in business and finance. Figure  1 illustrates the outcomes of an inquiry into fundamental ML applications in emerging business and financial domains over the past few decades. Numerous studies in this field have applied ML techniques to resolve business and financial problems. Table 1 lists some of their applications. Boughanmi and Ansari ( 2021 ) developed a multimodal ML framework that integrates different types of non-parametric data to accommodate diverse effects. Additionally, they combined multimedia data in creative product settings and applied their model to predict the success of musical albums and playlists. Zhu et al. ( 2021 ) asserted that accurate demand forecasting is critical for supply chain efficiency, especially for the pharmaceutical supply chain, owing to its unique characteristics. However, a lack of sufficient data has prevented forecasters from pursuing advanced models. Accordingly, they proposed a demand forecasting framework that “borrows” time-series data from many other products and trains the data with advanced ML models. Yan and Ouyang ( 2018 ) proposed a time-series prediction model that combines wavelet analysis with a long short-term memory neural network to capture the complex features of financial time series and showed that this neural network had a better prediction effect. Zhang et al. ( 2020a , b ) employed a Bayesian learning model with a rich dataset to analyze the decision-making behavior of taxi drivers in a large Asian city to understand the key factors that drive the supply side of urban mobility markets.

Trend of articles on applied ML techniques in business and finance (2007–2021)

Several review papers have explored the potential of ML to enhance various domains, including agriculture (Raj et al. 2015 ; Coble et al. 2018 ; Kamilaris and Prenafeta-Boldu 2018 ; Storm et al. 2020 ), economic analysis (Einav and Levin 2014 ; Bajari et al. 2015 ; Grimmer 2015 ; Nguyen et al. 2020 ; Nosratabadi et al. 2020 ), and financial crisis prediction (Lin et al. 2012 ; Canhoto 2021 ; Dastile et al. 2020 ; Nanduri et al. 2020 ). Kou et al. ( 2019 ) conducted a survey encompassing research and methodologies related to the assessment and measurement of financial systemic risk that incorporated various ML techniques, including big data analysis, network analysis, and sentiment analysis. Meng and Khushi ( 2019 ) reviewed articles that focused on stock/forex prediction or trading, where reinforcement learning served as the primary ML method. Similarly, Nti et al. ( 2020 ) reviewed approximately 122 pertinent studies published in academic journals over an 11-year span, concentrating on the application of ML to stock market prediction.

Despite these valuable contributions, it is worth noting that the existing review papers primarily concentrate on specific issues within the realm of business and finance, such as the financial system and stock market. Consequently, although a substantial body of research exists in this area, a comprehensive and systematic review of the extensive applications of ML in various aspects of business and finance is lacking. In addition, existing review articles do not provide a comprehensive review of common ML techniques utilized in business and finance. To bridge the aforementioned gaps in the literature, we aim to provide an all-encompassing and methodological review of the extensive spectrum of ML applications in the business and finance domains. To begin with, we identify the most commonly utilized ML techniques in the business and finance domains. Then we introduce the fundamental ML concepts and frequently employed techniques and algorithms. Next, we systematically examine the extensive applications of ML in various sub-domains within business and finance, including marketing, stock markets, e-commerce, cryptocurrency, finance, accounting, credit risk management, and energy. We critically analyze the existing research that explores the implementation of ML techniques in business and finance to offer valuable insights to researchers, practitioners, and decision-makers, thereby facilitating better-informed decision-making and driving future research directions in this field.

The remainder of this paper is organized as follows. Section “ Keywords, distribution of articles, and common technologies in the application of ML techniques in business and finance ” outlines the literature retrieval process and presents the statistical findings from the literature analysis, including an analysis of common application trends and ML techniques. Section “ Machine learning: a brief introduction ” introduces fundamental concepts and terminology related to ML. Sections “ Supervised learning ” and “ Unsupervised learning ” explore in-depth common supervised and unsupervised learning techniques, respectively. Section “ Applications of machine learning techniques in business and finance ” discusses the most recent applications of ML in business and finance. Section “ Critical discussions and future research directions ” discusses some limitations of ML in this domain and analyzes future research opportunities. Finally, “ Conclusions ” section concludes.

Keywords, distribution of articles, and common technologies in the application of ML techniques in business and finance

The primary focus of this review is to explore the advancements in ML in business- and finance-related fields involving ML applications in various market-related issues, including prices, investments, and customer behaviors. This review employs the following strategies to identify existing literature. Initially, we identify relevant journals known for publishing papers that utilize ML techniques to address business and finance problems, such as the UTD-24. Table 2 lists the keywords used in the literature search. During the search process, we input various combinations of ML keywords and business/finance keywords, such as “support vector machine” and “marketing.” By cross-referencing the selected journals and keywords and thoroughly examining the citations of highly cited papers, we aimed to achieve a comprehensive and unbiased representation of the current literature.

After identifying journals and keywords, we searched for articles in the Thomson Reuters Web of Science and Elsevier Scopus databases using the same set of keywords. Once the collection phase was complete, the filtering process was initiated. Initially, duplicate articles were excluded to ensure that only unique articles remained for further analysis. Subsequently, we carefully reviewed the full text of each article to eliminate irrelevant or inappropriate items and thus ensure that the final selection comprised relevant and meaningful literature.

Figure  2 illustrates the process of article selection for the review. In the identification phase, we retrieved 154 articles from the search and identified an additional 37 articles through reference checking. During the second phase, duplicates and inappropriate articles were filtered out, resulting in a total of 68 articles eligible for inclusion in this study. Based on the review of these articles, we categorized them into seven different applications: stock market, marketing, e-commerce, energy marketing, cryptocurrency, accounting, and credit risk management, as depicted in Fig.  3 and Tables 3 , 4 , 5 , 6 , 7 , 8 and 9 . Statistical analyses have revealed that ML research in the business and finance domain is predominantly concentrated in the areas of stock market and marketing. The research on e-commerce, cryptocurrency, and energy market applications is nearly equivalent in quantity. Conversely, articles focusing on accounting and credit risk management applications are relatively limited. Figure  4 provides a summary of the ML techniques employed in the reviewed articles. Deep learning, support vector machine, and decision tree methods emerged as the most prominent research technologies. In contrast, the application of unsupervised learning techniques, such as k-means and reinforcement learning, were less common.

Flow diagram for article identification and filtering

Number of papers employing ML techniques

Prominent methods applied in the business and finance domains

Machine learning: a brief introduction

This section introduces the basic concepts of ML, including its goals and terminology. Thereafter, we present the model selection method and how to improve the performance.

Goals and terminology

The key objective in various scientific disciplines is to model the relationships between multiple explanatory variables and a set of dependent variables. When a theoretical mathematical model is established, researchers can use it to predict or control desired variables. However, in real-world scenarios, the underlying model is often too complex to be formulated as a closed-form input–output relationship. This complexity has led researchers in the field of ML to focus on developing algorithms (Wu et al. 2008 ; Chao et al. 2018 ). The primary goal of these algorithms is to predict certain variables based on other variables or to classify units using limited information; for example, they can be used to classify handwritten digits based on pixel values. ML techniques can automatically construct computational models that capture the intricate relationships present in available data by maximizing the problem-dependent performance criterion or minimizing the error term, which allows them to establish a robust representation of the underlying relationships.

In the context of ML, the sample used to estimate the parameters is usually referred to as a “training sample,” and the procedure for estimating the parameters is known as “training.” Let N be the sample size, k be the number of features, and q be the number of all possible outcomes. ML can be classified into two main types: supervised and unsupervised. In supervised learning problems, we know both the feature \({\mathbf{X}}_{i} = (x_{i1} ,...,x_{ik} ),\; \, i = 1,2,...,N\) and the outcome \(Y_{i} = (y_{i1} ,y_{i2} ,...,y_{iq} )\) , where \(y_{ij}\) represents the outcome of \(y_{i}\) in the dimension \(j\) . For example, in a recommendation system, the quality of product can be scored from 1 to 5, indicating that “q” equals 5. In unsupervised learning problems, we only observe the features \({\mathbf{X}}_{i}\) (input data) and aim to group them into clusters based on their similarities or patterns.

Cross-validation, overfitting, and regularization

Cross-validation is frequently used for model selection in ML that is applied to each model; the technique is applied to each model and the one with the lowest expected out-of-sample prediction error is selected.

The ML literature shows significantly higher concern about overfitting than the standard statistics or econometrics literature. In the ML community, the degrees of freedom are not explicitly considered, and many ML methods involve a large number of parameters, which can potentially lead to negative degrees of freedom.

Limiting overfitting is commonly achieved through regularization in ML, which controls the complexity of a model. As stated by Vapnik ( 2013 ), the regularization theory was one of the first signs of intelligent inference. The complexity of the model describes its ability to approximate various functions. As the complexity increases, the risk of overfitting also increases, whereas less complex and more regularized models may lead to underfitting. Regularization is often implemented by selecting a parsimonious number of variables and using specific functional forms without explicitly controlling for overfitting. Instead of directly optimizing an objective function, a regularization term is added to the objective function, which penalizes the complexity of the model. This approach encourages the model to generalize better and avoids overfitting by promoting simpler and more interpretable solutions.

Here, we provide an example to illustrate how regularization works. The following linear regression model was used:

where N is the sample size, k is the numbers of features, and q is the number of all possible outcomes. The variable \(y_{{ij}} (i = 1,2,...,N,\quad j = 1,2,...,q)\) represents the outcome of \(y_{i}\) in the j th dimension. Additionally, \(b_{pj} (p = 1,2,...,k,j = 1,2,...,q)\) represents the coefficient of feature p in the j th dimension. By using vector notations, \({{\varvec{\upsigma}}} = (\sigma_{1} ,...,\sigma_{q} )^{{ \top }}\) , \({\mathbf{b}} = (b_{{11}} ,b_{{21}} ,...,b_{{k1}} ,b_{{12}} ,b_{{22}} ,...,b_{{k2}} ,...,b_{{1q}} ,b_{{2q}} ,...,b_{{kq}} )^{{ \top }}\) and \(Y_{i} = (y_{i1} ,y_{i2} ,...,y_{iq} )\) , we can rewrite Eq. ( 1 ) as follows:

where \({\mathbf{b}}\) is the solution of

\(\lambda\) is a penalty parameter that can be selected through out-of-sample cross-validation to optimize the model’s out-of-sample predictive performance.

Supervised learning

This section introduces common supervised learning technologies. Compared to traditional statistics, supervised learning methods exhibit certain desired properties when optimizing predictions in large datasets, such as transaction and financial time series data. In business and finance, supervised learning models have proven to be among the most effective tools for detecting credit card fraud (Lebichot et al. 2021 ). In the following subsections, we briefly describe the commonly used supervised ML methods for business and finance.

Shrinkage methods

The traditional least-squares method often yields complex models with an excessive number of explanatory variables. In particular, when the number of features, k , is large compared to the sample size N , the least-squares estimator, \({\hat{\mathbf{b}}}\) , does not have good predictive properties, even if the conditional mean of the outcome is linear. To address this problem, regularization is typically used to adjust the estimation parameters dynamically and reduce the complexity of the model. The shrinkage method is the most common regularization method and can reduce the values of the parameters to be estimated. Shrinkage methods, such as ridge regression (Hoerl and Kennard 1970 ) and least absolute shrinkage and selection operator (LASSO) (Tibshirani 1996 ), are linear regression models that add a penalty term to the size of the coefficients. This penalty term pushes the coefficients towards zero, effectively shrinking their values. Shrinkage methods can be effectively used to predict continuous outcomes or classification tasks, particularly when dealing with datasets containing numerous explanatory variables.

Compared to the traditional approach that estimates the regression function using least squares,

shrinkage methods add a penalty term that shrinks \({\mathbf{b}}\) toward zero, aiming to minimize the following objective function:

where \(\left\| {\mathbf{b}} \right\|_{q} = \sum\nolimits_{i = 1}^{N} {\left| {b_{i} } \right|^{q} }\) . In \(q = 1\) , this formulation leads to a LASSO. However, when \(q = 2\) is used, this formulation degenerates ridge regression.

Tree-based method

Regression trees (Breiman et al. 1984 ) and random forests (Breiman 2001 ) are effective methods for estimating regression functions with minimal tuning, especially when out-of-sample predictive abilities are required. Considering a sample \((x_{i1} ,...,x_{ik} ,Y_{i} )\) for \(i = 1,2,...,N\) , the idea of a regression tree is to split the sample into subsamples where the regression functions are being estimated. The splits process is sequential and based on feature value \(x_{ij}\) exceeding threshold \(c\) . Let \(R_{1} (j,c)\) and \(R_{2} (j,c)\) be two sets based on the feature \(j\) and threshold \(c\) , where \(R_{1} (j,c) = \left\{ {{\mathbf{X}}_{i} |x_{ij} \le c} \right\}\) and \(R_{2} (j,c) = \left\{ {{\mathbf{X}}_{i} |x_{ij} > c} \right\}\) . Naturally, the dataset \(R\) is divided into two parts, \(R_{1}\) and \(R_{2}\) , based on the chosen feature and threshold.

Let \(c_{1} = \frac{1}{{|R_{1} |}}\sum\nolimits_{{{\mathbf{X}}_{i} \in R_{1} }} {x_{ij} }\) and \(c_{2} = \frac{1}{{|R_{2} |}}\sum\nolimits_{{{\mathbf{X}}_{i} \in R_{2} }} {x_{ij} }\) , where \(| \bullet |\) refer to the cardinality of the set. Then we can construct the following optimization model to calculate the errors of the \(R_{1}\) and \(R_{2}\) datasets:

For all \(x_{ij}\) and threshold \(c \in ( - \infty , + \infty )\) , the method finds the optimal feature \(j^{*}\) and threshold \(c^{*}\) that minimizes errors and splits the sample into subsets based on these criteria. By selecting the best feature and threshold, the method obtains the optimal classification of \(R_{1}^{*}\) and \(R_{2}^{*}\) . This process is repeated recursively, leading to further splits that minimize the squared error and improve the overall model performance. However, researchers should be cautious about overfitting, wherein the model fits the training data too closely and fails to generalize well to new data. To address this issue, a penalty term can be added to the objective function to encourage simpler and more regularized models. The coefficients of the model are then selected through cross-validation, optimizing the penalty parameter to achieve the best trade-off between model complexity and predictive performance on new, unseen data. This helps prevent overfitting and ensures that the model's performance is robust and reliable.

Random forest builds on the tree algorithm to better estimate the regression function. This approach smooths the regression function by averaging across multiple trees, thus exhibiting two distinct differences. First, instead of using the original sample, each tree is constructed based on a bootstrap sample or a subsample of the data, a technique known as “bagging.” Second, at each stage of building a tree, the splits are not optimized over all possible features (covariates) but rather over a random subset of the features. Consequently, feature selection varies in each split, which enhances the diversity of the individual trees.

Deep learning and neural networks

Deep learning and neural networks have been proven to be highly effective in complex settings. However, it is worth noting that the practical implementation of deep learning often demands a considerable amount of tuning compared to other methods, such as decision trees or random forests.

Deep neural networks

As with any other supervised learning methods, deep neural networks (DNNs) can be viewed as a straightforward mapping \(y=f(x;\theta )\) from the input feature vector \(x\) to the output vector or scalar \(y\) , which is governed by the unknown parameters \(\theta\) . This mapping typically consists of layers that form chain-like structures. Figure  5 illustrates the structure of the DNN. For a DNN with multiple layers, the structure can be represented as

Structure of DNN

In a fully connected DNN, the \(i\) th layer has a structure given by \(h^{(i)} = f^{(i)} (x) = g^{(i)} ({\mathbf{W}}^{(i)} h^{(i - 1)} + {\mathbf{b}}^{(i)} )\) , where \({\mathbf{W}}\) is the matrix of unknown parameters and \({\mathbf{b}}^{\left( i \right)}\) is the vector of basis factors. A typical choice for \(g^{\left( i \right)}\) , called the “activation function,” can be a rectified linear unit, tanh transformation function, or sigmoid function. The 0th layer \(h^{(0)} = x\) , which represents the input vector. The row dimension of \(b\) or the column dimension of the \({\mathbf{W}}\) species is the number of neurons in each layer. The weight matrix \({\mathbf{W}}\) is learned by minimizing a loss function, which can be the mean squared error for regression tasks or the cross-entropy for classification tasks. In particular, when the DNN has one layer, \(y\) is scalar. The activation function is set to linear or logistic, and we obtain a linear or logistic regression.

Convolutional neural networks

Although neural networks have many different architectures, the two most classical and relevant are convolutional neural networks (CNNs) and recurrent neural networks (RNNs). A classical CNN structure, which contains three main components—convolutional, pooling, and fully connected layers—is shown in Fig.  6 . In contrast to the previously mentioned fully connected structure, in the convolutional layer, each neuron connects with only a small fraction of the neurons from the former layer; however, they share the same parameters. Therefore, sparse connections and parameter sharing significantly reduces the number of estimated parameters.

Structure of CNN

Different layers play different roles in the training process and are introduced in more detail as follows:

Convolutional layer : This layer comprises a collection of trained filters that are used to extract features from the input data. Assuming that \(X\) is the input and there are \(k\) filters, the output of the convolutional layer can be formulated as follows:

where \(\omega_{j}\) and \(b_{j}\) denote the weights and bias, respectively; \(f\) represents the activation function; and \(*\) denotes the convolutional operator.

Pooling layer : This layer reduces the features and parameters of the network. The most popular pooling methods are the maximum and average pooling.

CNN are designed to handle one-dimensional time-series data or images. Intuitively, each convolutional layer can be considered a set of filters that move across images or shift along time sequences. For example, some filters may learn to detect textures, whereas others may identify specific shapes. Each filter generates a feature map and the subsequent convolutional layer integrates these features to create a more complex structure, resulting in a map of learned features. Suppose that \(S\) is an \(p \times p\) window size. Then the average pooling process can be formulated as

where \(x_{ij}\) is the activation value at location \((i,j)\) , and N is the total number of \(S\) .

Recurrent neural networks

Recurrent neural networks (RNNs) are well suited for processing sequential data, dynamic relations, and long-term dependencies. RNNs, particularly those employing long short-term memory (LSTM) cells, have become popular and have shown significant potential in natural language processing (Schmidhuber 2015 ). A key feature of this architecture is its ability to maintain past information over time using a cell-state vector. In each time step, new variables are combined with past information in the cell vector, enabling the RNN to learn how to encode information and determine which encoded information should be retained or forgotten. Similar to CNNs, RNN benefit from parameter sharing, which allows them to detect specific patterns in sequential data.

Figure  7 illustrates the structure of the LSTM network, which contains a memory unit \({C}_{t}\) , a hidden state \({h}_{t}\) , and three types of gates. Index \(t\) refers to the time step. At each step \(t\) , the LTSM combines input \({x}_{t}\) with the previous hidden state \({h}_{t-1}\) , calculates the activations of all gates, and updates the memory units and hidden states accordingly.

Structure of LSTM

The computations of LSTM networks are described as follows:

where \(W\) denotes the weight of the inputs, and \(\omega_{f}\) and \(\omega_{i}\) represent the weights of the outputs and biases, respectively. The subscript \(f,i,{\text{ and }}O\) refer to the forget, input, and output gate vectors, respectively. \(b\) indicates biases and \(\circ\) is an element-wise multiplication.

Wavelet neural networks

Wavelet neural networks (Zhang and Benveniste  1992 ) use the wavelet function as the activation function, thus combining the advantages of both the wavelet transform and neural networks. The structure of wavelet neural networks is based on backpropagation neural networks, and the transfer function of the hidden layer neuron is the mother wavelet function. For input features \({\mathbf{x}} = (x_{1} ,...,x_{n} )\) , the output of the hidden layer can be expressed as follows:

where \(h(j)\) is the output value for neuron \(j\) , \(h_{j}\) is the mother wavelet function, \(\omega_{ij}\) is the weight between the input and hidden layers, \(b_{j}\) is the shift factor, and \(a_{j}\) is the stretch factor for \(h_{j}\) .

Support vector machine and kernels

Support vector machines (SVM) are flexible classification methods (Cortes and Vapnik 1995 ). Let us consider a binary classification problem, where we have an \(N\) observation \({\mathbf{X}}_{i}\) , each with \(k\) features, and a binary label \(y_{i} \in \{ - 1,1\}\) . Subsequently, a hyperplane \(x \in {\mathbf{\mathbb{R}}}\) s. t. \(w^{{ \top }} {\mathbf{X}}_{i} + b = 0\) is defined, which can be considered a binary classifier \({\text{sgn}} (w^{{ \top }} {\mathbf{X}}_{i} + b)\) . The goal of SVM is to find a hyperplane such that the observations can be separated into two classes: + 1 and − 1. From the hyperplane space, SVM selects the option that maximizes the distance from the closest sample. In an SVM, there is typically a small set of samples with the same maximal distance, which are referred to as “support vectors.”

The above-mentioned process can be written as the following optimization model:

To solve the above optimization model, we rewrite it in terms of Lagrangian multipliers as follows:

where \(\alpha_{i}\) is the Lagrangian multiplier of the original restriction and \(Y_{i} (\omega^{{ \top }} {\mathbf{X}}_{i} + b) \ge 1\) . The model above is equivalent to

We can obtain the Lagrangian multiplier \({{\varvec{\upalpha}}} = (\alpha_{1} ,...,\alpha_{N} )\) from Model ( 15 ), and then \(\widehat{b}\) can be solved from \(\sum\nolimits_{i = 1}^{N} {\hat{\alpha }_{i} (Y_{i} (\omega^{{ \top }} {\mathbf{X}}_{i} + b) - 1)} = 0\) . Furthermore, we can obtain the classifier:

Traditional SVM assumes linearly separable training samples. However, SVM can also deal with non-linear cases by mapping the original covariates to a new feature space using the function \(\phi ({\mathbf{X}}_{i} )\) and then finding the optimal hyperplane in this transformed feature space; that is, \(f(x_{i} ) = \omega^{{ \top }} \phi (x_{i} ) + b\) . Thus, the optimization problem in the transformed feature space can be formulated as

where \(K({\mathbf{X}}_{i} ,{\mathbf{X}}_{j} ) = \phi ({\mathbf{X}}_{i} )^{{ \top }} \phi ({\mathbf{X}}_{j} )\) . The kernel function \(K( \bullet )\) can be linear, polynomial, or sigmoid. Once the kernel function is determined, we can solve for the value of the Lagrangian multiplier \(\alpha\) . Then \(\widehat{b}\) can be solved from \(\sum\nolimits_{i = 1}^{N} {\hat{\alpha }_{i} (Y_{i} (\omega^{{ \top }} {\mathbf{X}}_{i} + b) - 1)} = 0\) , which allows us to derive the classifier:

Bayesian classifier

A Bayesian network is a graphical model that represents the probabilistic relationships among a set of features (Friedman et al. 1997 ). The Bayesian network structure \(S\) is a directed acyclic graph. Formally, a Bayesian network is a pair \(B = \left\langle {G,\Theta } \right\rangle\) , where \(G\) is a directed acyclic graph whose nodes represent the random variable \(\left( {X_{1} ,...,X_{n} } \right)\) , whose edges represent the dependencies between variables, and \(\Theta\) is the set of parameters that quantify the graph.

Assuming that there are \(q\) labels; that is, \({\mathbf{Y}} = \{ c_{1} ,...,c_{q} \}\) , \(\lambda_{ij}\) is the loss caused by misclassifying the sample with the true label \(c_{j}\) as \(c_{i}\) , and \({\mathbb{X}}\) represents the sample space. Then, based on the posterior probability \(P(c_{i} |{\mathbf{x}})\) , we can calculate the expected loss of classifying sample \({\mathbf{x}}\) into the label \(c_{i}\) as follows:

Therefore, the aim of the Bayesian classifier is to find a criterion \(h:{\mathbb{X}} \to {\mathbf{Y}}\) that minimizes the total risk

Obviously, for each sample \({\mathbf{x}}\) , when \(h\) can minimize the conditional risk \(R(h({\mathbf{x}})|{\mathbf{x}})\) , the total risk \(R(h)\) will also be minimized. This leads to the concept of Bayes decision rules: to minimize the total risk, we need to classify each sample into the label that minimizes the conditional risk \(R(h({\mathbf{x}})|{\mathbf{x}})\) , namely

We then used \(h^{*}\) as the Bayes-optimal classifier and \(R(h^{*} )\) as the Bayes risk.

K-nearest neighbor

The K-nearest neighbor (KNN) algorithm is a lazy-learning algorithm because it defers to the induction process until classification is required (Wettschereck et al. 1997 ). The lazy-learning algorithm requires less computation time during the training process compared to eager-learning algorithms such as decision trees, neural networks, and Bayes networks. However, it may require additional time during the classification phase.

The kNN algorithm is based on the assumption that instances close to each other in a feature space are likely to have similar properties. If instances with the same classification label are found nearby, an unlabeled instance can be assigned the same class label as its nearest neighbors. kNN locates the k-nearest instances to the unlabeled instance and determines its label by observing the most frequent class label among these neighbors.

The choice of k significantly affects the performance of the kNN algorithm. Let us discuss the performance of kNN during \(k = 1\) . Given sample \({\mathbf{x}}\) and its nearest sample \({\mathbf{z}}\) , the probability of error can be expressed as follows:

Suppose the samples are independent and identically distributed. For any \({\mathbf{x}}\) and any positive number \(\delta\) , there always exists at least one sample \({\mathbf{z}}\) within a distance of \(\delta\) from \({\mathbf{x}}\) . Let \(c^{*} ({\mathbf{x}})\mathop {\arg \min }\limits_{{c \in {\mathbf{Y}}}} P(c|{\mathbf{x}})\) be the outcome the Bayes optimal classifier. Then we have:

According to (23), despite the simplicity of kNN, the generalization error is no more than twice that of the Bayes-optimal classifier.

Unsupervised learning

In unsupervised learning, researchers can only access observations without any labeled information, and their primary interest lies in partitioning a sample into subsamples or clusters. Unsupervised learning methods are particularly useful in descriptive tasks because they aim to find relationships in a data structure without measuring the outcomes. Several approaches commonly used in business and finance research fall under the umbrella of unsupervised learning, including k-means clustering and reinforcement learning. Accordingly, unsupervised learning can be used in qualitative business and finance. For example, it can be particularly beneficial during stakeholder analysis, when stakeholders must be mapped and classified by considering certain predefined attributes. It can also be useful for customer management. A company can employ an unsupervised ML method to cluster guests, which influences its marketing strategy for specific groups and leads to a competitive advantage. This section introduces unsupervised learning technologies that are widely used in business and finance.

K-means clustering

The K-means algorithm aims to find K points in the sample space and classify the samples that are closest to these points. Using an iterative method, the values of each cluster center are updated step-by-step to achieve the best clustering results. When partitioning the feature space into K clusters, the k-means algorithm selects centroids and assigns observations to clusters based on their proximity to them. \(b_{1} ,...,b_{k}\) . The algorithm proceeds as follows. First, we begin with the K centroids \(b_{1} ,...,b_{k}\) , which are initially scattered throughout the feature space. Next, in accordance with the chosen centroids, each observation is assigned to clusters that minimize the distance between the observation and the centroid of the cluster:

Next, we update the centroid by computing the average of \(X_{i}\) across each cluster:

where \(I( \bullet )\) is the indicative function. When choosing the number of clusters, K, we must exercise caution because no cross-validation method is available to compare the values.

Reinforcement learning

Reinforcement learning (RL) draws inspiration from the trial-and-error procedure conducted by Thorndike in his 1898 study of cat behavior. Originating from animal learning, RL aims to mimic human behavior by making decisions that maximize profits through interactions with the environment. Mnih et al. ( 2015 ) proposed deep RL by employing a deep Q-network to create an agent that outperformed a professional player in a game and further advanced the field of RL.

In deep RL, the learning algorithm plays an essential role in improving efficiency. These algorithms can be categorized into three types: value-based, policy-based, and model-based RL, as illustrated in Fig.  8 .

Learning algorithm-based reinforcement learning

RL consists of four components—agent, state, action and reward—with the agent as its core. When an action leads to a profitable state, it receives a reward, otherwise, it is discouraged. In RL, an agent is defined as any decision-maker, while everything else is considered the environment. The interactions between the environments and the agents are described by state \(s\) , action \(a\) , and reward \(r\) . At time step \(t\) , the environment is in state \(s_{t}\) , and the agent takes action \(a_{t}\) . Consequently, the environment transitions to state \(s_{t + 1}\) and rewards agent \(r_{t + 1}\) .

The agent’s decision is formalized by a policy \(\pi\) , which maps state \(s\) to action \(a\) . This is deterministic when the probability of choosing action \(a\) in state \(s\) equals one (i.e., \(\pi (a|s) = p(a|s) = 1\) ). In contrast, it is stochastic when \(p(a|s) < 1\) is used. Policy \(\pi\) can be defined as the probability distribution of all actions selected from a certain \(s\) , as follows:

where \(\Delta_{\pi }\) represents all possible actions of \(\pi\) .

In each step, the agent receives an immediate reward \(r_{t + 1}\) until it reaches the final state \(s_{T}\) . However, the immediate reward does not ensure a long-term profit. To address this, a generalized return value is used at time step \(t\) , defined as \(R_{t}\) :

where \(0 \le \gamma \le 1\) . The agents become more farsighted when \(\gamma\) approaches 1, and more shortsighted when it approaches 0.

The next step is to define a score function \(V\) to estimate the goodness of the state:

Then, we determine the goodness of a state-action pair \((s,a)\) :

Finally, we access the goodness between two policies:

Finally, we can expand \(V_{\pi } (s)\) and \(Q_{\pi } (s,a)\) through \(R_{t}\) to represent the relationship between \(s\) and \(s_{t + 1}\) as

where \(W_{{s \to s^{\prime}|a}} = E[r_{t + 1} |s_{t} = s,a_{t} = a,s_{t + 1} = s^{\prime}]\) . By solving ( 31 ) and ( 32 ), we obtain \(V\) and \(S\) , respectively.

Restricted Boltzmann machines

As Fig.  9 shows, a restricted Boltzmann machine (RBM) can be considered an undirected neural network with two layers, called the “hidden” and “visible” layers. Hidden layers are used to detect the features, whereas visible layers are used to train the input data. Given the \(n\) visible layers \(v\) and \(m\) hidden layers \(h\) , the energy function is given by

where \(\alpha_{ij}\) is the weight between the unit \(i\) \(j\) , and \(a_{i}\) and \(b_{j}\) are the biases for \(v\) and \(h\) , respectively.

Structure of RBM

Applications of machine learning techniques in business and finance

This section considers the application fields in the following categories: marketing, stock market, e-commerce, cryptocurrency, finance, accounting, credit risk management, and energy economy. This study reviews the application status of ML in these fields.

ML is an innovative technology that can potentially improve forecasting models and assist in management decision-making. ML applications can be highly beneficial in the marketing domain because they rely heavily on building accurate predictive models from databases. Compared to the traditional statistical approach for forecasting consumer behavior, researchers have recently applied ML technology, which offers several distinctive advantages for data mining with large, noisy databases (Sirignano and Cont 2019 ). An early example of ML in marketing can be found in the work of Zahavi and Levin ( 1997 ), who used neural networks (NNs) to model consumer responses to direct marketing. Compared with the statistical approach, simple forms of NNs are free from the assumptions of normality or complete data, making them particularly robust in handling noisy data. Recently, as shown in Table  3 , ML techniques have been predominantly used to study customer behaviors and demands. These applications enable marketers to gain valuable insights and make data-driven decisions to optimize marketing strategies.

Consumer behavior refers to the actions taken by consumers to request, use, and dispose of consumer goods, as well as the decision-making process that precedes and determines these actions. In the context of direct marketing, Cui et al. ( 2006 ) proposed Bayesian networks that learn by evolutionary programming to model consumer responses to direct marketing using a large direct marketing dataset. In the supply chain domain, Melancon et al. ( 2021 ) used gradient-boosted decision trees to predict service-level failures in advance and provide timely alerts to planners for proactive actions. Regarding unsupervised learning in consumer behavior analysis, Dingli et al. ( 2017 ) implemented a CNN and an RBM to predict customer churn. However, they found that their performance was comparable to that of supervised learning when introducing added complexity in specific operations and settings. Overall, ML techniques have demonstrated their potential for understanding and predicting consumer behavior, thereby enabling businesses to make informed decisions and optimize their marketing strategies (Machado and Karray 2022 ; Mao and Chao 2021 ).

Predicting consumer demand plays a critical role in helping enterprises efficiently arrange production and generate profits. Timoshenko and Hauser ( 2019 ) used a CNN to facilitate qualitative analysis by selecting the content for an efficient review. Zhang et al. ( 2020a , b ) used a Bayesian learning model with a rich dataset to analyze the decision-making behavior of taxi drivers in a large Asian city to understand the key factors that drive the supply side of urban mobility markets. Ferreira et al. ( 2016 ) employed ML techniques to estimate historical lost sales and predict future demand for new products. For the application of consumer demand-level prediction, most of the research we reviewed used supervised learning technologies because learning consumer consumption preferences requires historical data of consumers, and only clustering consumers is insufficient to predict their consumption levels.

Stock market

ML applications in the stock market have gained immense popularity, with the majority focusing on financial time series for stock price predictions. Table 4 summarizes the reviewed articles that employed ML methods in stock market studies, including references, research objectives, data sources, applied techniques, and journals. Investing in the stock market can be highly profitable but also entails risk. Therefore, investors always try to determine and estimate stock values before taking any action. Researchers have mostly used ML techniques to predict stock prices (Bennett et al. 2022 ; Moon and Kim 2019 ). However, predicting stock values can be challenging due to the influence of uncontrollable economic and political factors that make it difficult to identify future market trends. Additionally, financial time-series data are often noisy and non-stationary, rendering traditional forecasting methods less reliable for stock value predictions. Researchers have explored ML in sentiment analysis to identify future trends in the stock market (Baba and Sevil 2021 ). Furthermore, other studies have focused on objectives such as algorithmic trading, portfolio management, and S&P 500 index trend prediction using ML techniques (Cuomo et al. 2022 ; Go and Hong 2019 ).

Various ML techniques have been successfully applied for stock price predictions. Fischer and Krauss ( 2018 ) applied LSTM networks to predict the out-of-sample directional movements of the constituent stocks of the S&P 500 from 1992 to 2015, demonstrating that LSTM networks outperform memory-free classification methods. Wu et al. ( 2021 ) applied LASSO, random forest, gradient boosting, and a DNN to cross-sectional return predictions in hedge fund selection and found that ML techniques significantly outperformed four styles of hedge fund research indices in almost all situations. Bao et al. ( 2017 ) fed high-level denoising features into the LSTM to forecast the next day’s closing price. Sabeena and Venkata ( 2019 ) proposed a modified adversarial-network-based framework that integrated a gated recurrent unit and a CNN to acquire data from online financial sites and processed the obtained information using an adversarial network to generate predictions. Song et al. ( 2019 ) used deep learning methods to predict future stock prices. Sohangir et al. ( 2018 ) applied several NN models to stock market opinions posted on StockTwits to determine whether deep learning models could be adapted to improve the performance of sentiment analysis on StockTwits. Bianchi et al. ( 2021 ) showed that extreme trees and NNs provide strong statistical evidence in favor of bond return predictability. Vo et al. ( 2019 ) proposed a deep responsible investment portfolio model containing an LSTM network to predict stock returns. All of these stock price applications use supervised learning techniques and financial time-series data to supervise learning. In contrast, it is challenging to apply unsupervised learning methods, particularly clustering, in this domain (Chullamonthon and Tangamchit 2023 ). However, RL still has certain applications in the stock markets. Lei ( 2020 ) combined deep learning and RL models to develop a time-driven, feature-aware joint deep RL model for financial time-series forecasting in algorithmic trading, thus demonstrating the potential of RL in this domain.

Additionally, the evidence suggests that hybrid LSTM methods can outperform other single-supervised ML methods in certain scenarios. Thus, in applying ML to the stock market, researchers have explored the combination of LSTM with different methods to develop hybrid models for improved performance. For instance, Tamura et al. ( 2018 ) used LSTM to predict stock prices and reported that the accuracy test results outperformed those of other models, indicating the effectiveness of the hybrid LSTM approach in stock price prediction.

Researchers have explored various hybrid approaches that combine wavelet transforms and LSTM with other techniques to predict stock prices and financial time series. Bao et al. ( 2017 ) established a new method for predicting stock prices that integrated wavelet transforms, stacked autoencoders, and LSTM. In the first stage, they eliminate noise to decompose the stock price time series. In the next stage, predictive features for the stock price are created. Finally, LSTM is applied to predict the next day’s closing price based on the features of the previous stage. The authors claimed that their model outperformed state-of-the-art models in terms of predictive accuracy and profitability. To address the non-linearity and non-stationary characteristics of financial time series, Yan and Ouyang ( 2018 ) integrated wavelet analysis with LSTM to forecast the daily closing price of the Shanghai Composite Index. Their proposed model outperformed multiple layer perceptron, SVM, and KNN with respect to finding patterns in financial time-series data. Fang et al. ( 2019 ) developed a methodology to predict exchange trade–fund option prices by integrating LSTM with support vector regression (SVR). They used two LSTM-SVR models to model the final transaction price. In the second generation of LSTM-SVR, the hidden state vectors of the LSTM and the seven factors affecting the option price were considered as SVR inputs. Their proposed model outperformed other methods, including LSTM and RF, in predicting option prices.

Online shopping, which allows users to purchase products from companies via the Internet, falls under the umbrella of e-commerce. In today’s rapidly evolving online shopping landscape, companies employ effective methods to recognize their buyers’ purchasing patterns, thereby enhancing their overall client experience. Customer reviews play a crucial role in this process as they are not only utilized by companies to improve their products and services but also by customers to assess the quality of a product and make informed purchase decisions (Da et al. 2022 ). Consequently, the decision-making process is significantly improved through analysis of reviews that provide valuable insights to customers.

Traditionally, enterprises’ e-commerce strategic planning involves assessing the performance of organizational e-commerce adoption behavior at the strategic level. In this context, the decision-making process exhibits typical behavioral characteristics. With regard to organizations’ adoption of technology, it is important to note that the entity adopting the technology is no longer an individual but the organization as a whole. However, technology adoption decisions are still made by people within an organization, and these decisions are influenced by individual cognitive factors (Zha et al. 2021 ). Individuals involved in the decision-making process have their own perspectives, beliefs, and cognitive biases, which can significantly impact an organization’s technology adoption choices and strategies (Li et al. 2019 ; Xu et al. 2021 ). Therefore, the behavioral perspective of technology acceptance provides a new perspective for e-commerce strategic planning research. With the development of ML, research on technology acceptance has been hindered by the limitations of traditional strategic e-commerce planning. Different general models of information technology acceptance behaviors are commonly explored.

Table 5 provides a summary of the aforementioned studies. Cui et al. ( 2021 ) constructed an e-commerce product marketing model based on an SVM to improve the marketing effects of e-commerce products. Pang and Zhang ( 2021 ) built an SVM model to more effectively solve the decision support problem of e-commerce strategic planning. To increase buyers’ trust in the quality of the products and encourage online purchases, Saravanan and Charanya ( 2018 ) designed an algorithm that categorizes products based on several criteria, including reviews and ratings from other users. They proposed a hybrid feature-extraction method using an SVM to classify and separate products based on their features, best product ratings, and positive reviews. Wang et al. ( 2018a , b , c ) employed LSTM to improve the effectiveness and efficiency of mapping customer requirements to design parameters. The results of their model revealed the superior performance of the RNN over the KNN. Xu et al. ( 2019 ) designed an advanced credit risk evaluation system for e-commerce platforms to minimize the transaction risks associated with buyers and sellers. To this end, they employed a hybrid ML model combined with a decision tree ANN (DT-ANN) and found that it had high accuracy and outperformed other hybrid ML models, such as logistic regression and dynamic Bayesian network. Cai et al. ( 2018 ) used deep RL to develop an algorithm to address the allocation of impression problems on e-commerce websites such as www.taobao.com , www.ebay.com , and www.amazon.com . In this algorithm, buyers are allocated to sellers based on their impressions and strategies to maximize the income of the platform. To do so, they applied a gated recurrent unit, and their findings demonstrated that it outperformed a deep deterministic policy gradient. Wu and Yan ( 2018 ) claimed that the main assumption of current production recommender models for e-commerce websites is that all historical user data are recorded. In practice, however, many platforms fail to capture such data. Consequently, they devised a list-wise DNN to model the temporal online behavior of users and offered recommendations for anonymous users.

In the accounting field, ML techniques are employed to detect fraud and estimate accounting indicators. Most companies’ financial statements reflect accounts or disclosure amounts that require estimations. Accounting estimates are pervasive in financial statements and often significantly impact a company’s financial position and operational results. The evolution of financial reporting frameworks has led to the increased use of fair value measurements, which necessitates estimation. Most financial statement items are based on subjective managerial estimates and ML has the potential to provide an independent estimate generator (Kou et al. 2021 ).

Chen and Shi ( 2020 ) utilized bagging and boosting ensemble strategies to develop two models: bagged-proportion support vector machines (pSVM) and boosted-pSVMs. Using datasets from LibSVM, they tested their models and demonstrated that ensemble learning strategies significantly enhanced model performance in bankruptcy prediction. Lin et al. ( 2019 ) emphasized the importance of finding the best match between feature selection and classification techniques to improve the prediction performance of bankruptcy prediction models. Their results revealed that using a genetic algorithm as the wrapper-based feature selection method, combined with naïve Bayes and support vector machine classifiers, resulted in remarkable predictive performance. Faris et al. ( 2019 ) investigated a combination of resampling (oversampling) techniques and multiple election method features to improve the accuracy of bankruptcy prediction methods. According to their findings, employing the oversampling technique and the AdaBoost ensemble method using a reduced error pruning (REP) tree provided reliable and promising results for bankruptcy prediction.

The earlier studies by Perols ( 2011 ) and Perols et al. ( 2017 ) were among the first to predict accounting fraud. Two recent studies by Bao et al. ( 2020 ) and Bertomeu et al. (2020) used various accounting variables to improve the detection of ongoing irregularities. Bao et al. ( 2020 ) employed ensemble learning to develop a fraud-prediction model that demonstrated superior performance compared to the logistic regression and support vector machine models with a financial kernel. Huang et al. ( 2014 ) used Bayesian networks to extract textual opinions, and their findings showed that they outperformed dictionary-based approaches, both general and financial. Ding et al. ( 2020 ) used insurance companies’ data on loss reserve estimates and realizations and documented that the loss estimates generated by ML were superior to the actual managerial estimates reported in financial statements in four out of the five insurance lines examined.

Many companies commission accounting firms to handle accounting and bookkeeping and provide them access to transaction data, documentation, and other relevant information. Mapping daily financial transactions into accounts is one of the most common accounting tasks. Therefore, Jorgensen and Igel ( 2021 ) devised ML systems based on random forest to automate the mapping process of financial transfers to the appropriate accounts. Their approach achieved an impressive accuracy of 80.50%, outperforming baseline methods that either excluded transaction text or relied on lexical bag-of-words text representations. The success of ML systems indicates the potential of ML to streamline accounting processes and increase the efficiency of financial transaction’ mapping. Table 6 summarizes the ML techniques described in “ Accounting ” section.

Credit risk management

The scoring process is an essential part of the credit risk management system used in financial institutions to predict the risk of loan applications because credit scores imply a certain probability of default. Hence, credit scoring modes have been widely developed and investigated for credit approval assessment of new applicants. This process uses a statistical model that considers both the application and performance data of a credit or loan applicant to estimate the likelihood of default, which is the most significant factor used by lenders to prioritize applicants in decision-making. Given the substantial volume of decisions involved in the consumer lending business, it is necessary to rely on models and algorithms rather than on human discretion (Bao et al. 2019 ; Husmann et al. 2022 ; Liu et al. 2019 ). Furthermore, such algorithmic decisions are based on “hard” information, such as consumer credit file characteristics collected by credit bureau agencies.

Supervised and unsupervised ML methods are widely used for credit risk management. Supervised ML techniques are used in credit scoring models to determine the relationships between customer features and credit default risk and subsequently predict classifications. Unsupervised techniques, mainly clustering algorithms, are used as data mining techniques to group samples into clusters (Wang et al. 2019 ). Hence, unsupervised learning techniques often complement supervised techniques in credit risk management.

Despite the high accuracy of ML, it is not possible to explain its predictions. However, financial institutions must maintain transparency in their decision-making processes. Fortunately, researchers have shown that ML can deduce rules to mitigate a lack of transparency without compromising accuracy (Baesens et al. 2003 ). Table 7 summarizes the recent applications of ML methods in credit risk management. Liu et al. ( 2022 ) use KNN, SVM, and random forest to predict the default probability of online loan borrowers and compare their prediction performance with that of a logistic model. Khandani et al. ( 2010 ) applied regression trees to construct non-linear, non-parametric forecasting models for consumer credit risk.

Cryptocurrency

A cryptocurrency is a digital or virtual currency used to securely exchange and transfer assets. Cryptography is used to securely transfer assets, control and regulate the addition of cryptocurrencies, and secure their transactions (Garcia et al. 2014 ); hence, the term “cryptocurrency.” In contrast to standard currencies, which depend on the central banking system, cryptocurrencies are founded on the principle of decentralized control (Zhao 2021 ). Owing to its uncontrolled and untraceable nature, the cryptocurrency market has evolved exponentially over a short period. The growing interest in cryptocurrencies in the fields of economics and finance has drawn the attention of researchers in this domain. However, the applications of cryptocurrencies and associated technologies are not limited to financing. There is a significant body of computer science literature that focuses on the supporting technologies of cryptocurrencies, which can lead to innovative and efficient approaches for handling Bitcoin and other cryptocurrencies, as well as addressing their price volatility and other related technologies (Khedr et al. 2021 ).

Generating an accurate prediction model for such complex problems is challenging. As a result, cryptocurrency price prediction is still in its nascent stages and further research efforts are required to explore this area. In recent years, ML has become one of the most popular approaches for cryptocurrency price prediction owing to its ability to identify general trends and fluctuations. Table 8 presents a survey of cryptocurrency price prediction research using ML methods. Derbentsev et al. ( 2019 ) presented a short-term forecasting model to predict the cryptocurrency prices of Ripples, Bitcoin, and Ethereum using an ML approach. Greaves and Au ( 2015 ) applied blockchain data to Bitcoin price predictions and employed various ML techniques, including SVM, ANN, and linear and logistic regression. Among the ML classifiers used, the NN classifier with two hidden layers achieved the highest price accuracy of 55%, followed by logistic regression and SVM. Additionally, the research mentioned an analysis using several tree-based models and KNN.

The most recent LSTM networks appear to be more suitable and convenient for handling sequential data, such as time series. Lahmiri and Bekiros ( 2019 ) were the first to use LSTM to predict the digital currency prices of the three currencies that were used the most at the time they conducted their study: Bitcoin, Ripple, and digital cash. In their study, long memory was used to assess the market efficiency of cryptocurrencies, and the inherent non-linear dynamics encompassing chaoticity and fractality were examined to gauge the predictability of digital currencies. Chowdhury et al. ( 2020 ) applied LSTM to the indices and constituents of cryptocurrencies to predict prices. Lahmiri and Bekiros ( 2019 ) implemented LSTM to forecast the prices of the three most widely traded cryptocurrencies. Furthermore, Altan et al. ( 2019 ) built a novel hybrid forecasting model based on LSTM to predict digital currency time series.

The existing applications of ML techniques in energy economics can be classified into two major categories: energy price and energy demand prediction. Energy prices typically demonstrate complex features, such as non-linearity, lag dependence, and non-stationarity, which present challenges for the application of simple traditional models (Chen et al. 2018 ). Owing to their high flexibility, ML techniques can provide superior prediction performance. In energy demand predictions, lagged values of consumption and socioeconomic and technological variables, such as GDP per capita, population, and technology trends, are typically utilized. Table 9 presents a summary of these studies. A critical distinction between “price” and “consumption” prediction is that the latter is not subject to market efficiency dynamics. The prediction of consumption has little effect on the actual consumption of the agents. However, price prediction tends to offset itself by creating opportunities for traders to use this information.

Predicting prices in energy markets is a complicated process because prices are subject to physical constraints on electricity generation and transmission and market power potential (Young et al. 2014 ). Predicting prices using ML techniques is one of the oldest applications in energy economics. In the early 2000s, a wave of studies attempted to forecast electricity prices using conventional ANN techniques. Ding ( 2018 ) combined ensemble empirical mode decomposition and an artificial NN to forecast international crude oil prices. Zhang et al. ( 2020a , b ) employed the LSTM method to forecast day-ahead electricity prices in a deregulated electricity market. They also investigated the intricate dependence structure within the price-forecasting model. Peng et al. ( 2018 ) applied LSTM with a differential evolution algorithm to predict electricity prices. Lago et al. ( 2018 ) first proposed a DNN to improve the predictive accuracy in a local market and then proposed a second model that simultaneously predicts prices from two markets to further improve the forecasting accuracy. Huang and Wang ( 2018 ) proposed a model that combines wavelet NNs with random time-effective functions to improve the prediction accuracy of crude oil price fluctuations.

Understanding the future energy demand and consumption is essential for short- and long-term planning. A wide range of users, including government agencies, local development authorities, financial institutions, and trading institutions, are interested in obtaining realistic forecasts of future consumption portfolios (Lei et al. 2020 ). For demand prediction, Chen et al. ( 2018 ) used ridge regression to combine extreme gradient boosting forest and feedforward deep networks to predict the annual household electricity consumption. Wang et al. ( 2018a , b , c ) first built a model using a self-adaptive multi-verse optimizer to optimize the SVM and then employed it to predict China’s primary energy consumption.

Critical discussions and future research directions

ML techniques have proven valuable in establishing computational models that capture complex relationships with the available data. Consequently, ML has become a useful tool in business and finance. This section critically discusses the existing research and outlines future directions.

Critical discussions

Although ML techniques are widely employed in business and finance, several issues need to be addressed.

Linguistic information is abundant in business and finance, encompassing online commodity comments and investors’ emotional responses in the stock market. Nonetheless, the existing research has predominantly concentrated on processing numerical data. When juxtaposed with numerical information, linguistic data harbor intricate characteristics, notably personalized individual semantics (Li et al. 2022a , b ; Zhang et al. 2021a , b ; Hoang and Wiegratz 2022 ).

The integration of ML into business and finance can lead to interpretability issues. In ML, an interpretable model refers to one in which a human observer can readily comprehend how the model transforms an observation into a prediction (Freitas 2014 ). Typically, decision-makers are hesitant to accept recommendations generated by ML techniques unless they can grasp the reasoning behind them. Unfortunately, the existing research in business and finance, particularly those employing DNNs, has seldom emphasized the interpretability of their models.

Social networks are prevalent in the marketing domain within businesses (Zha et al. 2020 ). For instance, social networks exist among consumers, whose purchasing behavior is influenced by the opinions of trusted peers or friends. However, the existing research that applies ML to marketing has predominantly concentrated on personal customer attributes, such as personality, purchasing power, and preferences (Dong et al. 2021 ). Regrettably, the potential impact of social networks and their influence on customer behavior have been largely overlooked in these studies.

ML techniques typically focus on exploring the statistical relationships between dependent and independent variables and emphasize feature correlations. However, in the context of business and finance applications, causal relationships exist between variables. For instance, consider a study suggesting that girls who have breakfast tend to have lower weights than those who do not’, based on which one might conclude that having breakfast aids in weight loss. However, in reality, these two events may only exhibit a correlation rather than causation (Yao et al. 2021 ). Causality plays a significant role in ML techniques’ performance. However, many current business and finance applications have failed to account for this crucial factor. Ignoring causality may lead to misleading conclusions and hinder accurate modeling of real-world scenarios. Therefore, incorporating causality into ML methodologies within the business and finance domains is essential for enhancing the reliability and validity of predictive models and decision-making processes.

In the emerging cryptocurrency field, although traditional statistical methods are simple to implement and interpret, they require many unrealistic statistical assumptions, making ML the best technology in this field. Although many ML techniques exist, challenges remain in accurately predicting cryptocurrency prices. However, most ML techniques require further investigation.

In recent years, rapid growth in digital payments has led to significant shifts in fraud and financial crimes (Canhoto 2021 ; Prusti et al. 2022 ; Wang et al. 2023 ). While some studies have shown the effective use of ML in detecting financial crimes, there remains a limitation in the research dedicated to this area. As highlighted by Pourhabibi et al. ( 2020 ), the complex nature of financial crime detection applications poses challenges in terms of deploying and achieving the desired detection performance levels. These challenges are manifested in two primary aspects. First, ML solutions encounter substantial pressure to deliver real-time responses owing to the constraints of processing data in real time. Second, in addition to inherent data noise, criminals often attempt to introduce deceptive data to obfuscate illicit activities (Pitropakis et al. 2019 ). Regrettably, few studies have investigated the robustness and performance of the underlying algorithmic solutions when confronted with data quality issues.

In the finance domain, an important limitation of the current literature on energy and ML is that most works highlight the computer science perspective to optimize computational parameters (e.g., the accuracy rate), while finance intuition may be ignored.

Future research directions

Thus, we propose that future research on this topic follow the directions below:

As analyzed above, there is abundant linguistic information exists in business and finance. Consequently, leveraging natural language processing technology to handle and analyze linguistic data in these domains represents a highly promising research direction.

The amalgamation of theoretical models using ML techniques is an important research topic. The incorporation of interpretable models can effectively reveal the black-box nature of ML-driven analyses, thereby elucidating the underlying reasoning behind the results. Consequently, the introduction of interpretable models into business and finance while applying ML can yield substantial benefits.

The interactions and behaviors are often intertwined within social networks, making it crucial to incorporate social network dynamics when modeling their influence on consumer behavior. Introducing the social network aspect into ML models has tremendous potential for enhancing marketing strategies and outcomes  (Trandafili and Biba 2013 ).

Causality has garnered increasing attention in the field of ML in recent years. Accordingly, we believe it is an intriguing avenue to explore when applying ML to address problems in business and finance.

Further studies need to include all relevant factors affecting market mood and track them over a longer period to understand the anomalous behavior of cryptocurrencies and their prices. We recommend that researchers analyze the use of LSTM models in future research, such as CNN LSTM and encoder–decoder LSTM, and compare the results to obtain future insights and improve price prediction results. In addition, researchers can apply sentiment analysis to collect social signals, which can be further enhanced by improving the quality of content and using more content sources. Another area of opportunity is the use of more specialized models with different types of approaches, such as LSTM networks.

Graph NNs and emerging adaptive solutions provide important opportunities for shaping the future of fraud and financial crime detection owing to their parallel structures. Because of the complexity of digital transaction processing and the ever-changing nature of fraud, robustness should be treated as the primary design goal when applying ML to detect financial crimes. Finally, focusing on real-time responses and data noise issues is necessary to improve the performance of current ML solutions for financial crime detection.

Currently, the application of unsupervised learning methods in different areas, such as marketing and risk management, is limited. Some problems related to marketing and customer management could be analyzed using clustering techniques, such as K-means, to segment clients by different demographic or behavioral characteristics and by their likelihood of default or switching companies. In energy risk management, extreme events can be identified as outliers using principal component analysis or ranking algorithms.

Conclusions

Having already made notable contributions to business and finance, ML techniques for addressing issues in these domains are significantly increasing. This review discusses advancements in ML in business and finance by examining seven research directions of ML techniques: cryptocurrency, marketing, e-commerce, energy marketing, stock market, accounting, and credit risk management. Deep learning models, such as DNN, CNN, RNN, random forests, and SVM are highlighted in almost every domain of business and finance. Finally, we analyze some limitations of existing studies and suggest several avenues for future research. This review is helpful for researchers in understanding the progress of ML applications in business and finance, thereby promoting further developments in these fields.

Availability of data and materials

Not applicable.

Abbreviations

• Machine learning

Long short-term memory

Support vector machine

Restricted Boltzmann machine

Least absolute shrinkage and selection operator

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Acknowledgements

We would like to acknowledge financial support from the grant (No. 72271171) from the National Natural Science Foundation of China, the grant (No. sksy12021-02) from Sichuan University, and National Outstanding Youth Science Fund Project of National Natural Science Foundation of China (71725001).

This work was supported by the grant (No. 72271171) from the National Natural Science Foundation of China, the grant (No. sksy12021-02) from Sichuan University, National Outstanding Youth Science Fund Project of National Natural Science Foundation of China (71725001), and the Open Project of Xiangjiang Laboratory (No. 22XJ03028).

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Hanyao Gao, Haiming Liang, Xiangrui Chao & Yucheng Dong

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Business School, Hohai University, Nanjing, 211100, China

Hengjie Zhang

Xiangjiang Laboratory, Changsha, 410205, China

Yucheng Dong

School of Economics and Management, Southwest Jiaotong University, Chengdu, 610031, China

Cong-Cong Li

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HG, GK and YD contributed to the completion of the idea and writing of this paper. HG, GK and YD contributed to the discussion of the content of the organization and HL and HZ contributed to the improvement of the text of the manuscript. HG and HL contributed to Methodology. XC, and CL contributed to the literature collection of this paper. All authors read and approved the final manuscript.

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Gao, H., Kou, G., Liang, H. et al. Machine learning in business and finance: a literature review and research opportunities. Financ Innov 10 , 86 (2024). https://doi.org/10.1186/s40854-024-00629-z

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DOI : https://doi.org/10.1186/s40854-024-00629-z

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Hailey-Hailey disease successfully treated with tralokinumab and literature review of successful treatment with dupilumab

Kareena s. garg.

a Georgetown University School of Medicine, Washington, District of Columbia

Jonathan Silverberg

b Department of Dermatology, The George Washington University School of Medicine and Health Sciences, Washington, District of Columbia

Leonardo Tjahjono

c Pinnacle Dermatology, Woodbridge, Virginia

Introduction

Familial benign chronic pemphigus, also known as Hailey-Hailey disease (HHD), is a rare autosomal dominant genodermatosis that presents as chronic, painful, erythematous, erosive plaques, and fissures. Patients with HHD often suffer from comorbid impacts on psychosocial health and quality of life. HHD is due to a mutation in the ATP2C1 gene on chromosome 3, leading to defective Golgi apparatus calcium homeostasis, disruption in keratinocyte adhesion, and consequent development of intraepidermal acantholysis. Traditional medical treatment options for HHD are limited and have unreliable efficacy; these include topical steroids and calcineurin inhibitors, topical and systemic antibiotics, oral retinoids, and opioid modulators. 1

Tralokinumab is a novel interleukin 13 (IL-13) inhibitor. It is Food and Drug Administration–approved for atopic dermatitis in patients 12 years and older. We report a case of HHD refractory to conventional treatments, successfully treated with tralokinumab samples provided by manufacturer.

Case report

A 58-year-old man with past medical history of hypertension, hyperlipidemia, and a 20-year history of chronic HHD presented to clinic as a referral with a severe flare of painful erythematous, eroded pink plaques on his inner thighs. He does not have any known family history of HHD. Multiple biopsies from external facilities showed epidermal hyperplasia, parakeratosis, and diffused epidermal acantholysis with negative direct immunofluorescence, supportive for HHD. The disease was recalcitrant to long-term trial of topical antibiotics, systemic antibiotics, topical corticosteroids, and systemic naltrexone for 20 years with persistent pain and no significant improvement in cutaneous presentation. After receiving tralokinumab loading dose of subcutaneous 600 mg and subsequent 300 mg every 2 weeks, his pain symptoms started to improve after the first 300-mg dose. He was then able to discontinue topical corticosteroids and topical antibiotics. The erythematous, eroded plaques resolved on his 6-week follow-up ( Figs 1 and ​ and2). 2 ). He was able to maintain remission on 3-month follow-up with subcutaneous 150 mg of tralokinumab every 4 weeks without any adverse effect throughout duration of his treatment. The patient reported that he was able to perform physical exercise for the first time in decades.

Hailey-Hailey disease of the left thigh; resolution of painful, erosive, erythematous plaque ( A ) after 6 weeks of tralokinumab ( B ).

Hailey-Hailey disease of the right thigh; resolution of painful, erosive erythematous plaque ( A ) after 6 weeks of tralokinumab, except for cutaneous atrophy in the setting of long-term topical corticosteroids use ( B ).

Tralokinumab, an IL-13 inhibitor, has a similar mechanism of action as dupilumab by inhibiting the effect of downstream cytokines produced by T-helper 2 cell, which subsequently dampens stimulation of eosinophils and basophils. Dupilumab has been reported to improve HHD in the literature, which we summarized in Table I 2 , 3 , 4 , 5 , 6 While the mechanism is unclear, a possible explanation of tralokinumab’s efficacy is that IL-13 inhibition increases influx of calcium into keratinocytes, which is critical for normal keratinocytes differentiations and cellular adhesion; this likely negates abnormal intracellular calcium signaling caused by HHD genetic defect. 7 Tralokinumab and IL-13 inhibition also attenuate C-C chemokine receptor type 3 and eotaxin-3 interactions downstream effect, which attract eosinophils and basophils; both cells inhibit the release of intracellular calcium. 8 The attenuation likely promotes influx of calcium into keratinocytes, promoting normal keratinocytes differentiations and cellular adhesion.

Summarized Hailey-Hailey disease treated with dupilumab in the literature

A , Acitretin; Ah , antihistamine; AP , apremilast; CsA , cyclosporine; DS , dapsone; Et , etanercept; HCQ , hydroxycholoroquine; I , isotretinoin; ICS , intralesional corticosteroids; LDN , low dose naltrexone; MMF , mycophenolate mofetil; MTX , methotreaxate; OABX , oral antibiotics; OG , oral glycopyrrolate; Pr , prednisone; SAZ , sulfadiazine; TCI , topical calcineurin inhibitor; TCS , topical corticosteroids.

To our knowledge, this is the first report of tralokinumab as a treatment option for HHD. While promising, further controlled studies are needed to evaluate tralokinumab as a treatment option for recalcitrant HHD.

Conflicts of interest

Dr Tjahjono has served as a consultant for Bristol Myers Squibb. Dr Silverberg is an advisor, speaker, or consultant for AbbVie, Asana Biosciences, Dermavant, Galderma, GlaxoSmithKline, Glenmark, Kiniksa, LEO Pharma, Lilly, Menlo Therapeutics, Novartis, Pfizer, Realm Pharma, and Regeneron-Sanofi; and also a researcher for GlaxoSmithKline. Author Garg has no conflicts of interest to declare.

Funding sources: None.

Patient consent: The authors obtained written consent from patients for their photographs and medical information to be published in print and online and with the understanding that this information may be publicly available. Patient consent forms were not provided to the journal but are retained by the authors.

IRB approval status: Not applicable.