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CHAPTER 2 REVIEW OF RELATED LITERATURE AND STUDIES

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How to Write Review of Related Literature (RRL) in Research

sample related literature and studies in research

A review of related literature (a.k.a RRL in research) is a comprehensive review of the existing literature pertaining to a specific topic or research question. An effective review provides the reader with an organized analysis and synthesis of the existing knowledge about a subject. With the increasing amount of new information being disseminated every day, conducting a review of related literature is becoming more difficult and the purpose of review of related literature is clearer than ever.

All new knowledge is necessarily based on previously known information, and every new scientific study must be conducted and reported in the context of previous studies. This makes a review of related literature essential for research, and although it may be tedious work at times , most researchers will complete many such reviews of varying depths during their career. So, why exactly is a review of related literature important?

Table of Contents

Why a review of related literature in research is important

Before thinking how to do reviews of related literature , it is necessary to understand its importance. Although the purpose of a review of related literature varies depending on the discipline and how it will be used, its importance is never in question. Here are some ways in which a review can be crucial.

Identify gaps in the knowledge – This is the primary purpose of a review of related literature (often called RRL in research ). To create new knowledge, you must first determine what knowledge may be missing. This also helps to identify the scope of your study.
Avoid duplication of research efforts – Not only will a review of related literature indicate gaps in the existing research, but it will also lead you away from duplicating research that has already been done and thus save precious resources.
Provide an overview of disparate and interdisciplinary research areas – Researchers cannot possibly know everything related to their disciplines. Therefore, it is very helpful to have access to a review of related literature already written and published.
Highlight researcher’s familiarity with their topic 1 – A strong review of related literature in a study strengthens readers’ confidence in that study and that researcher.

Tips on how to write a review of related literature in research

Given that you will probably need to produce a number of these at some point, here are a few general tips on how to write an effective review of related literature 2 .

Define your topic, audience, and purpose: You will be spending a lot of time with this review, so choose a topic that is interesting to you. While deciding what to write in a review of related literature , think about who you expect to read the review – researchers in your discipline, other scientists, the general public – and tailor the language to the audience. Also, think about the purpose of your review of related literature .
Conduct a comprehensive literature search: While writing your review of related literature , emphasize more recent works but don’t forget to include some older publications as well. Cast a wide net, as you may find some interesting and relevant literature in unexpected databases or library corners. Don’t forget to search for recent conference papers.
Review the identified articles and take notes: It is a good idea to take notes in a way such that individual items in your notes can be moved around when you organize them. For example, index cards are great tools for this. Write each individual idea on a separate card along with the source. The cards can then be easily grouped and organized.
Determine how to organize your review: A review of related literature should not be merely a listing of descriptions. It should be organized by some criterion, such as chronologically or thematically.
Be critical and objective: Don’t just report the findings of other studies in your review of related literature . Challenge the methodology, find errors in the analysis, question the conclusions. Use what you find to improve your research. However, do not insert your opinions into the review of related literature. Remain objective and open-minded.
Structure your review logically: Guide the reader through the information. The structure will depend on the function of the review of related literature. Creating an outline prior to writing the RRL in research is a good way to ensure the presented information flows well.

As you read more extensively in your discipline, you will notice that the review of related literature appears in various forms in different places. For example, when you read an article about an experimental study, you will typically see a literature review or a RRL in research , in the introduction that includes brief descriptions of similar studies. In longer research studies and dissertations, especially in the social sciences, the review of related literature will typically be a separate chapter and include more information on methodologies and theory building. In addition, stand-alone review articles will be published that are extremely useful to researchers.

The review of relevant literature or often abbreviated as, RRL in research , is an important communication tool that can be used in many forms for many purposes. It is a tool that all researchers should befriend.

University of North Carolina at Chapel Hill Writing Center. Literature Reviews. https://writingcenter.unc.edu/tips-and-tools/literature-reviews/ [Accessed September 8, 2022]
Pautasso M. Ten simple rules for writing a literature review. PLoS Comput Biol. 2013, 9. doi: 10.1371/journal.pcbi.1003149.

Q: Is research complete without a review of related literature?

A research project is usually considered incomplete without a proper review of related literature. The review of related literature is a crucial component of any research project as it provides context for the research question, identifies gaps in existing literature, and ensures novelty by avoiding duplication. It also helps inform research design and supports arguments, highlights the significance of a study, and demonstrates your knowledge an expertise.

Q: What is difference between RRL and RRS?

The key difference between an RRL and an RRS lies in their focus and scope. An RRL or review of related literature examines a broad range of literature, including theoretical frameworks, concepts, and empirical studies, to establish the context and significance of the research topic. On the other hand, an RRS or review of research studies specifically focuses on analyzing and summarizing previous research studies within a specific research domain to gain insights into methodologies, findings, and gaps in the existing body of knowledge. While there may be some overlap between the two, they serve distinct purposes and cover different aspects of the research process.

Q: Does review of related literature improve accuracy and validity of research?

Yes, a comprehensive review of related literature (RRL) plays a vital role in improving the accuracy and validity of research. It helps authors gain a deeper understanding and offers different perspectives on the research topic. RRL can help you identify research gaps, dictate the selection of appropriate research methodologies, enhance theoretical frameworks, avoid biases and errors, and even provide support for research design and interpretation. By building upon and critically engaging with existing related literature, researchers can ensure their work is rigorous, reliable, and contributes meaningfully to their field of study.

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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.

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

How to write a good literature review

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

What is a literature review?

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

What is the purpose of literature review?

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

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

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

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

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

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

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

Literature review example

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

Literature Review on Climate Change Impacts on Biodiversity:

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

a. Habitat Loss and Species Extinction:

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

b. Range Shifts and Phenological Changes:

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

c. Ocean Acidification and Coral Reefs:

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

d. Adaptive Strategies and Conservation Efforts:

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

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

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

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

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

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

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

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

Conducting a literature review

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

Choose a Topic and Define the Research Question:

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

Decide on the Scope of Your Review:

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

Select Databases for Searches:

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

Conduct Searches and Keep Track:

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

Review the Literature:

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

Organize and Write Your Literature Review:

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

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Frequently asked questions

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

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

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

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

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

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

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

	Annotated Bibliography	Literature Review
Purpose	List of citations of books, articles, and other sources with a brief description (annotation) of each source.	Comprehensive and critical analysis of existing literature on a specific topic.
Focus	Summary and evaluation of each source, including its relevance, methodology, and key findings.	Provides an overview of the current state of knowledge on a particular subject and identifies gaps, trends, and patterns in existing literature.
Structure	Each citation is followed by a concise paragraph (annotation) that describes the source’s content, methodology, and its contribution to the topic.	The literature review is organized thematically or chronologically and involves a synthesis of the findings from different sources to build a narrative or argument.
Length	Typically 100-200 words	Length of literature review ranges from a few pages to several chapters
Independence	Each source is treated separately, with less emphasis on synthesizing the information across sources.	The writer synthesizes information from multiple sources to present a cohesive overview of the topic.

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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Bibliography

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

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

Importance of a Good Literature Review

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

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

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

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

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

Types of Literature Reviews

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

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

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

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

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

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

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

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

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

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

Structure and Writing Style

I. Thinking About Your Literature Review

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

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

The critical evaluation of each work should consider :

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

II. Development of the Literature Review

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

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

III. Ways to Organize Your Literature Review

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

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

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

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

IV. Writing Your Literature Review

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

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

V. Common Mistakes to Avoid

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

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

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

Writing Tip

Break Out of Your Disciplinary Box!

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

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

Another Writing Tip

Don't Just Review for Content!

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

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

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

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

Yet Another Writing Tip

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

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

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

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

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Research Guides

How to Write a Literature Review

6. Synthesize
Literature Reviews: A Recap
Reading Journal Articles
Does it Describe a Literature Review?
1. Identify the Question
2. Review Discipline Styles
Searching Article Databases
Finding Full-Text of an Article
Citation Chaining
When to Stop Searching
4. Manage Your References
5. Critically Analyze and Evaluate

Synthesis Visualization

Synthesis matrix example.

7. Write a Literature Review

Synthesis Worksheet

About Synthesis

What is synthesis?	What synthesis is NOT:

Approaches to Synthesis

You can sort the literature in various ways, for example:

How to Begin?

Read your sources carefully and find the main idea(s) of each source

Look for similarities in your sources – which sources are talking about the same main ideas? (for example, sources that discuss the historical background on your topic)

Use the worksheet (above) or synthesis matrix (below) to get organized

This work can be messy. Don't worry if you have to go through a few iterations of the worksheet or matrix as you work on your lit review!

Four Examples of Student Writing

In the four examples below, only ONE shows a good example of synthesis: the fourth column, or Student D . For a web accessible version, click the link below the image.

Long description of "Four Examples of Student Writing" for web accessibility

Download a copy of the "Four Examples of Student Writing" chart

Click on the example to view the pdf.

From Jennifer Lim

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Research Process :: Step by Step

Introduction
Select Topic
Identify Keywords
Background Information
Develop Research Questions
Refine Topic
Search Strategy
Popular Databases
Evaluate Sources
Types of Periodicals
Reading Scholarly Articles
Primary & Secondary Sources
Organize / Take Notes
Writing & Grammar Resources
Annotated Bibliography
Literature Review
Citation Styles
Paraphrasing
Privacy / Confidentiality
Research Process
Selecting Your Topic
Identifying Keywords
Gathering Background Info
Evaluating Sources

Organize the literature review into sections that present themes or identify trends, including relevant theory. You are not trying to list all the material published, but to synthesize and evaluate it according to the guiding concept of your thesis or research question.

What is a literature review?

A literature review is an account of what has been published on a topic by accredited scholars and researchers. Occasionally you will be asked to write one as a separate assignment, but more often it is part of the introduction to an essay, research report, or thesis. 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

A literature review must do these things:

be organized around and related directly to the thesis or research question you are developing
synthesize results into a summary of what is and is not known
identify areas of controversy in the literature
formulate questions that need further research

Ask yourself questions like these:

What is the specific thesis, problem, or research question that my literature review helps to define?
What type of literature review am I conducting? Am I looking at issues of theory? methodology? policy? quantitative research (e.g. on the effectiveness of a new procedure)? qualitative research (e.g., studies of loneliness among migrant workers)?
What is the scope of my literature review? What types of publications am I using (e.g., journals, books, government documents, popular media)? What discipline am I working in (e.g., nursing psychology, sociology, medicine)?
How good was my information seeking? Has my search been wide enough to ensure I've found all the relevant material? Has it been narrow enough to exclude irrelevant material? Is the number of sources I've used appropriate for the length of my paper?
Have I critically analyzed the literature I use? Do I follow through a set of concepts and questions, comparing items to each other in the ways they deal with them? Instead of just listing and summarizing items, do I assess them, discussing strengths and weaknesses?
Have I cited and discussed studies contrary to my perspective?
Will the reader find my literature review relevant, appropriate, and useful?

Ask yourself questions like these about each book or article you include:

Has the author formulated a problem/issue?
Is it clearly defined? Is its significance (scope, severity, relevance) clearly established?
Could the problem have been approached more effectively from another perspective?
What is the author's research orientation (e.g., interpretive, critical science, combination)?
What is the author's theoretical framework (e.g., psychological, developmental, feminist)?
What is the relationship between the theoretical and research perspectives?
Has the author evaluated the literature relevant to the problem/issue? Does the author include literature taking positions she or he does not agree with?
In a research study, how good are the basic components of the study design (e.g., population, intervention, outcome)? How accurate and valid are the measurements? Is the analysis of the data accurate and relevant to the research question? Are the conclusions validly based upon the data and analysis?
In material written for a popular readership, does the author use appeals to emotion, one-sided examples, or rhetorically-charged language and tone? Is there an objective basis to the reasoning, or is the author merely "proving" what he or she already believes?
How does the author structure the argument? Can you "deconstruct" the flow of the argument to see whether or where it breaks down logically (e.g., in establishing cause-effect relationships)?
In what ways does this book or article contribute to our understanding of the problem under study, and in what ways is it useful for practice? What are the strengths and limitations?
How does this book or article relate to the specific thesis or question I am developing?

Text written by Dena Taylor, Health Sciences Writing Centre, University of Toronto

http://www.writing.utoronto.ca/advice/specific-types-of-writing/literature-review

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Get Organized

Lit Review Prep Use this template to help you evaluate your sources, create article summaries for an annotated bibliography, and a synthesis matrix for your lit review outline.

Synthesize your Information

Synthesize: combine separate elements to form a whole.

Synthesis Matrix

A synthesis matrix helps you record the main points of each source and document how sources relate to each other.

After summarizing and evaluating your sources, arrange them in a matrix or use a citation manager to help you see how they relate to each other and apply to each of your themes or variables.

By arranging your sources by theme or variable, you can see how your sources relate to each other, and can start thinking about how you weave them together to create a narrative.

Step-by-Step Approach
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Literature Syntheis 101

How To Synthesise The Existing Research (With Examples)

By: Derek Jansen (MBA) | Expert Reviewer: Eunice Rautenbach (DTech) | August 2023

One of the most common mistakes that students make when writing a literature review is that they err on the side of describing the existing literature rather than providing a critical synthesis of it. In this post, we’ll unpack what exactly synthesis means and show you how to craft a strong literature synthesis using practical examples.

This post is based on our popular online course, Literature Review Bootcamp . In the course, we walk you through the full process of developing a literature review, step by step. If it’s your first time writing a literature review, you definitely want to use this link to get 50% off the course (limited-time offer).

Overview: Literature Synthesis

What exactly does “synthesis” mean?
Aspect 1: Agreement
Aspect 2: Disagreement
Aspect 3: Key theories
Aspect 4: Contexts
Aspect 5: Methodologies
Bringing it all together

What does “synthesis” actually mean?

As a starting point, let’s quickly define what exactly we mean when we use the term “synthesis” within the context of a literature review.

Simply put, literature synthesis means going beyond just describing what everyone has said and found. Instead, synthesis is about bringing together all the information from various sources to present a cohesive assessment of the current state of knowledge in relation to your study’s research aims and questions .

Put another way, a good synthesis tells the reader exactly where the current research is “at” in terms of the topic you’re interested in – specifically, what’s known , what’s not , and where there’s a need for more research .

So, how do you go about doing this?

Well, there’s no “one right way” when it comes to literature synthesis, but we’ve found that it’s particularly useful to ask yourself five key questions when you’re working on your literature review. Having done so, you can then address them more articulately within your actual write up. So, let’s take a look at each of these questions.

1. Points Of Agreement

The first question that you need to ask yourself is: “Overall, what things seem to be agreed upon by the vast majority of the literature?”

For example, if your research aim is to identify which factors contribute toward job satisfaction, you’ll need to identify which factors are broadly agreed upon and “settled” within the literature. Naturally, there may at times be some lone contrarian that has a radical viewpoint , but, provided that the vast majority of researchers are in agreement, you can put these random outliers to the side. That is, of course, unless your research aims to explore a contrarian viewpoint and there’s a clear justification for doing so.

Identifying what’s broadly agreed upon is an essential starting point for synthesising the literature, because you generally don’t want (or need) to reinvent the wheel or run down a road investigating something that is already well established . So, addressing this question first lays a foundation of “settled” knowledge.

Need a helping hand?

2. Points Of Disagreement

Related to the previous point, but on the other end of the spectrum, is the equally important question: “Where do the disagreements lie?” .

In other words, which things are not well agreed upon by current researchers? It’s important to clarify here that by disagreement, we don’t mean that researchers are (necessarily) fighting over it – just that there are relatively mixed findings within the empirical research , with no firm consensus amongst researchers.

This is a really important question to address as these “disagreements” will often set the stage for the research gap(s). In other words, they provide clues regarding potential opportunities for further research, which your study can then (hopefully) contribute toward filling. If you’re not familiar with the concept of a research gap, be sure to check out our explainer video covering exactly that .

3. Key Theories

The next question you need to ask yourself is: “Which key theories seem to be coming up repeatedly?” .

Within most research spaces, you’ll find that you keep running into a handful of key theories that are referred to over and over again. Apart from identifying these theories, you’ll also need to think about how they’re connected to each other. Specifically, you need to ask yourself:

Are they all covering the same ground or do they have different focal points or underlying assumptions ?
Do some of them feed into each other and if so, is there an opportunity to integrate them into a more cohesive theory?
Do some of them pull in different directions ? If so, why might this be?
Do all of the theories define the key concepts and variables in the same way, or is there some disconnect? If so, what’s the impact of this ?

Simply put, you’ll need to pay careful attention to the key theories in your research area, as they will need to feature within your theoretical framework , which will form a critical component within your final literature review. This will set the foundation for your entire study, so it’s essential that you be critical in this area of your literature synthesis.

If this sounds a bit fluffy, don’t worry. We deep dive into the theoretical framework (as well as the conceptual framework) and look at practical examples in Literature Review Bootcamp . If you’d like to learn more, take advantage of our limited-time offer to get 60% off the standard price.

4. Contexts

The next question that you need to address in your literature synthesis is an important one, and that is: “Which contexts have (and have not) been covered by the existing research?” .

For example, sticking with our earlier hypothetical topic (factors that impact job satisfaction), you may find that most of the research has focused on white-collar , management-level staff within a primarily Western context, but little has been done on blue-collar workers in an Eastern context. Given the significant socio-cultural differences between these two groups, this is an important observation, as it could present a contextual research gap .

In practical terms, this means that you’ll need to carefully assess the context of each piece of literature that you’re engaging with, especially the empirical research (i.e., studies that have collected and analysed real-world data). Ideally, you should keep notes regarding the context of each study in some sort of catalogue or sheet, so that you can easily make sense of this before you start the writing phase. If you’d like, our free literature catalogue worksheet is a great tool for this task.

5. Methodological Approaches

Last but certainly not least, you need to ask yourself the question: “What types of research methodologies have (and haven’t) been used?”

For example, you might find that most studies have approached the topic using qualitative methods such as interviews and thematic analysis. Alternatively, you might find that most studies have used quantitative methods such as online surveys and statistical analysis.

But why does this matter?

Well, it can run in one of two potential directions . If you find that the vast majority of studies use a specific methodological approach, this could provide you with a firm foundation on which to base your own study’s methodology . In other words, you can use the methodologies of similar studies to inform (and justify) your own study’s research design .

On the other hand, you might argue that the lack of diverse methodological approaches presents a research gap , and therefore your study could contribute toward filling that gap by taking a different approach. For example, taking a qualitative approach to a research area that is typically approached quantitatively. Of course, if you’re going to go against the methodological grain, you’ll need to provide a strong justification for why your proposed approach makes sense. Nevertheless, it is something worth at least considering.

Regardless of which route you opt for, you need to pay careful attention to the methodologies used in the relevant studies and provide at least some discussion about this in your write-up. Again, it’s useful to keep track of this on some sort of spreadsheet or catalogue as you digest each article, so consider grabbing a copy of our free literature catalogue if you don’t have anything in place.

Looking at the methodologies of existing, similar studies will help you develop a strong research methodology for your own study.

Bringing It All Together

Alright, so we’ve looked at five important questions that you need to ask (and answer) to help you develop a strong synthesis within your literature review. To recap, these are:

Which things are broadly agreed upon within the current research?
Which things are the subject of disagreement (or at least, present mixed findings)?
Which theories seem to be central to your research topic and how do they relate or compare to each other?
Which contexts have (and haven’t) been covered?
Which methodological approaches are most common?

Importantly, you’re not just asking yourself these questions for the sake of asking them – they’re not just a reflection exercise. You need to weave your answers to them into your actual literature review when you write it up. How exactly you do this will vary from project to project depending on the structure you opt for, but you’ll still need to address them within your literature review, whichever route you go.

The best approach is to spend some time actually writing out your answers to these questions, as opposed to just thinking about them in your head. Putting your thoughts onto paper really helps you flesh out your thinking . As you do this, don’t just write down the answers – instead, think about what they mean in terms of the research gap you’ll present , as well as the methodological approach you’ll take . Your literature synthesis needs to lay the groundwork for these two things, so it’s essential that you link all of it together in your mind, and of course, on paper.

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 .

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Review of Related Literature: Format, Example, & How to Make RRL

A review of related literature is a separate paper or a part of an article that collects and synthesizes discussion on a topic. Its purpose is to show the current state of research on the issue and highlight gaps in existing knowledge. A literature review can be included in a research paper or scholarly article, typically following the introduction and before the research methods section.

The picture provides introductory definition of a review of related literature.

This article will clarify the definition, significance, and structure of a review of related literature. You’ll also learn how to organize your literature review and discover ideas for an RRL in different subjects.

🔤 What Is RRL?

❗ Significance of Literature Review
🔎 How to Search for Literature
🧩 Literature Review Structure
📋 Format of RRL — APA, MLA, & Others
✍️ How to Write an RRL
📚 Examples of RRL

🔗 References

A review of related literature (RRL) is a part of the research report that examines significant studies, theories, and concepts published in scholarly sources on a particular topic. An RRL includes 3 main components:

A short overview and critique of the previous research.
Similarities and differences between past studies and the current one.
An explanation of the theoretical frameworks underpinning the research.

❗ Significance of Review of Related Literature

Although the goal of a review of related literature differs depending on the discipline and its intended use, its significance cannot be overstated. Here are some examples of how a review might be beneficial:

It helps determine knowledge gaps .
It saves from duplicating research that has already been conducted.
It provides an overview of various research areas within the discipline.
It demonstrates the researcher’s familiarity with the topic.

🔎 How to Perform a Literature Search

Including a description of your search strategy in the literature review section can significantly increase your grade. You can search sources with the following steps:

	You should specify all the keywords and their synonyms used to look for relevant sources.
	Using your search terms, look through the online (libraries and databases) and offline (books and journals) sources related to your topic.
	It is not possible to discuss all of the sources you have discovered. Instead, use the works of the most notable researchers and authors.
	From the remaining references, you should pick those with the most significant contribution to the research area development.
	Your literature should prioritize new publications over older ones to cover the latest research advancements.

🧩 Literature Review Structure Example

The majority of literature reviews follow a standard introduction-body-conclusion structure. Let’s look at the RRL structure in detail.

This image shows the literature review structure.

Introduction of Review of Related Literature: Sample

An introduction should clarify the study topic and the depth of the information to be delivered. It should also explain the types of sources used. If your lit. review is part of a larger research proposal or project, you can combine its introductory paragraph with the introduction of your paper.

Here is a sample introduction to an RRL about cyberbullying:

Bullying has troubled people since the beginning of time. However, with modern technological advancements, especially social media, bullying has evolved into cyberbullying. As a result, nowadays, teenagers and adults cannot flee their bullies, which makes them feel lonely and helpless. This literature review will examine recent studies on cyberbullying.

Sample Review of Related Literature Thesis

A thesis statement should include the central idea of your literature review and the primary supporting elements you discovered in the literature. Thesis statements are typically put at the end of the introductory paragraph.

Look at a sample thesis of a review of related literature:

This literature review shows that scholars have recently covered the issues of bullies’ motivation, the impact of bullying on victims and aggressors, common cyberbullying techniques, and victims’ coping strategies. However, there is still no agreement on the best practices to address cyberbullying.

Literature Review Body Paragraph Example

The main body of a literature review should provide an overview of the existing research on the issue. Body paragraphs should not just summarize each source but analyze them. You can organize your paragraphs with these 3 elements:

Claim . Start with a topic sentence linked to your literature review purpose.
Evidence . Cite relevant information from your chosen sources.
Discussion . Explain how the cited data supports your claim.

Here’s a literature review body paragraph example:

Scholars have examined the link between the aggressor and the victim. Beran et al. (2007) state that students bullied online often become cyberbullies themselves. Faucher et al. (2014) confirm this with their findings: they discovered that male and female students began engaging in cyberbullying after being subject to bullying. Hence, one can conclude that being a victim of bullying increases one’s likelihood of becoming a cyberbully.

Review of Related Literature: Conclusion

A conclusion presents a general consensus on the topic. Depending on your literature review purpose, it might include the following:

Introduction to further research . If you write a literature review as part of a larger research project, you can present your research question in your conclusion .
Overview of theories . You can summarize critical theories and concepts to help your reader understand the topic better.
Discussion of the gap . If you identified a research gap in the reviewed literature, your conclusion could explain why that gap is significant.

Check out a conclusion example that discusses a research gap:

There is extensive research into bullies’ motivation, the consequences of bullying for victims and aggressors, strategies for bullying, and coping with it. Yet, scholars still have not reached a consensus on what to consider the best practices to combat cyberbullying. This question is of great importance because of the significant adverse effects of cyberbullying on victims and bullies.

📋 Format of RRL — APA, MLA, & Others

In this section, we will discuss how to format an RRL according to the most common citation styles: APA, Chicago, MLA, and Harvard.

Writing a literature review using the APA7 style requires the following text formatting:

	Times New Roman or Arial, 12 pt
	Double spacing
	All sides — 1″ (2.54 cm)
	Top right-hand corner, starting with the title page

When using APA in-text citations , include the author’s last name and the year of publication in parentheses.
For direct quotations , you must also add the page number. If you use sources without page numbers, such as websites or e-books, include a paragraph number instead.
When referring to the author’s name in a sentence , you do not need to repeat it at the end of the sentence. Instead, include the year of publication inside the parentheses after their name.
The reference list should be included at the end of your literature review. It is always alphabetized by the last name of the author (from A to Z), and the lines are indented one-half inch from the left margin of your paper. Do not forget to invert authors’ names (the last name should come first) and include the full titles of journals instead of their abbreviations. If you use an online source, add its URL.

The RRL format in the Chicago style is as follows:

	12-pt Times New Roman, Arial, or Palatino
	Double spacing, single spacing is used to format block quotations, titles of tables and figures, footnotes, and bibliographical entries.
	All sides — 1″ (2.54 cm)
	Top right-hand corner. There should be no numbered pages on the title page or the page with the table of contents.

Author-date . You place your citations in brackets within the text, indicating the name of the author and the year of publication.
Notes and bibliography . You place your citations in numbered footnotes or endnotes to connect the citation back to the source in the bibliography.
The reference list, or bibliography , in Chicago style, is at the end of a literature review. The sources are arranged alphabetically and single-spaced. Each bibliography entry begins with the author’s name and the source’s title, followed by publication information, such as the city of publication, the publisher, and the year of publication.

Writing a literature review using the MLA style requires the following text formatting:

Font	12-pt Times New Roman or Arial
Line spacing	Double spacing
Margins	All sides — 1″ (2.54 cm)
Page numbers	Top right-hand corner. Your last name should precede the page number.
Title page	Not required. Instead, include a header in the top left-hand corner of the first page with content. It should contain:

In the MLA format, you can cite a source in the text by indicating the author’s last name and the page number in parentheses at the end of the citation. If the cited information takes several pages, you need to include all the page numbers.
The reference list in MLA style is titled “ Works Cited .” In this section, all sources used in the paper should be listed in alphabetical order. Each entry should contain the author, title of the source, title of the journal or a larger volume, other contributors, version, number, publisher, and publication date.

The Harvard style requires you to use the following text formatting for your RRL:

	12-pt Times New Roman or Arial
	Double spacing
	All sides — 1″ (2.54 cm)
	Top right-hand corner. Your last name should precede the page number.

In-text citations in the Harvard style include the author’s last name and the year of publication. If you are using a direct quote in your literature review, you need to add the page number as well.
Arrange your list of references alphabetically. Each entry should contain the author’s last name, their initials, the year of publication, the title of the source, and other publication information, like the journal title and issue number or the publisher.

✍️ How to Write Review of Related Literature – Sample

Literature reviews can be organized in many ways depending on what you want to achieve with them. In this section, we will look at 3 examples of how you can write your RRL.

This image shows the organizational patterns of a literature review.

Thematic Literature Review

A thematic literature review is arranged around central themes or issues discussed in the sources. If you have identified some recurring themes in the literature, you can divide your RRL into sections that address various aspects of the topic. For example, if you examine studies on e-learning, you can distinguish such themes as the cost-effectiveness of online learning, the technologies used, and its effectiveness compared to traditional education.

Chronological Literature Review

A chronological literature review is a way to track the development of the topic over time. If you use this method, avoid merely listing and summarizing sources in chronological order. Instead, try to analyze the trends, turning moments, and critical debates that have shaped the field’s path. Also, you can give your interpretation of how and why specific advances occurred.

Methodological Literature Review

A methodological literature review differs from the preceding ones in that it usually doesn’t focus on the sources’ content. Instead, it is concerned with the research methods . So, if your references come from several disciplines or fields employing various research techniques, you can compare the findings and conclusions of different methodologies, for instance:

empirical vs. theoretical studies;
qualitative vs. quantitative research.

📚 Examples of Review of Related Literature and Studies

We have prepared a short example of RRL on climate change for you to see how everything works in practice!

Climate change is one of the most important issues nowadays. Based on a variety of facts, it is now clearer than ever that humans are altering the Earth's climate. The atmosphere and oceans have warmed, causing sea level rise, a significant loss of Arctic ice, and other climate-related changes. This literature review provides a thorough summary of research on climate change, focusing on climate change fingerprints and evidence of human influence on the Earth's climate system.

Physical Mechanisms and Evidence of Human Influence

Scientists are convinced that climate change is directly influenced by the emission of greenhouse gases. They have carefully analyzed various climate data and evidence, concluding that the majority of the observed global warming over the past 50 years cannot be explained by natural factors alone. Instead, there is compelling evidence pointing to a significant contribution of human activities, primarily the emission of greenhouse gases (Walker, 2014). For example, based on simple physics calculations, doubled carbon dioxide concentration in the atmosphere can lead to a global temperature increase of approximately 1 degree Celsius. (Elderfield, 2022). In order to determine the human influence on climate, scientists still have to analyze a lot of natural changes that affect temperature, precipitation, and other components of climate on timeframes ranging from days to decades and beyond.

Fingerprinting Climate Change

Fingerprinting climate change is a useful tool to identify the causes of global warming because different factors leave unique marks on climate records. This is evident when scientists look beyond overall temperature changes and examine how warming is distributed geographically and over time (Watson, 2022). By investigating these climate patterns, scientists can obtain a more complex understanding of the connections between natural climate variability and climate variability caused by human activity.

Modeling Climate Change and Feedback

To accurately predict the consequences of feedback mechanisms, the rate of warming, and regional climate change, scientists can employ sophisticated mathematical models of the atmosphere, ocean, land, and ice (the cryosphere). These models are grounded in well-established physical laws and incorporate the latest scientific understanding of climate-related processes (Shuckburgh, 2013). Although different climate models produce slightly varying projections for future warming, they all will agree that feedback mechanisms play a significant role in amplifying the initial warming caused by greenhouse gas emissions. (Meehl, 2019).

In conclusion, the literature on global warming indicates that there are well-understood physical processes that link variations in greenhouse gas concentrations to climate change. In addition, it covers the scientific proof that the rates of these gases in the atmosphere have increased and continue to rise fast. According to the sources, the majority of this recent change is almost definitely caused by greenhouse gas emissions produced by human activities. Citizens and governments can alter their energy production methods and consumption patterns to reduce greenhouse gas emissions and, thus, the magnitude of climate change. By acting now, society can prevent the worst consequences of climate change and build a more resilient and sustainable future for generations to come.

Have you ever struggled with finding the topic for an RRL in different subjects? Read the following paragraphs to get some ideas!

Nursing Literature Review Example

Many topics in the nursing field require research. For example, you can write a review of literature related to dengue fever . Give a general overview of dengue virus infections, including its clinical symptoms, diagnosis, prevention, and therapy.

Another good idea is to review related literature and studies about teenage pregnancy . This review can describe the effectiveness of specific programs for adolescent mothers and their children and summarize recommendations for preventing early pregnancy.

📝 Check out some more valuable examples below:

Hospital Readmissions: Literature Review .
Literature Review: Lower Sepsis Mortality Rates .
Breast Cancer: Literature Review .
Sexually Transmitted Diseases: Literature Review .
PICO for Pressure Ulcers: Literature Review .
COVID-19 Spread Prevention: Literature Review .
Chronic Obstructive Pulmonary Disease: Literature Review .
Hypertension Treatment Adherence: Literature Review .
Neonatal Sepsis Prevention: Literature Review .
Healthcare-Associated Infections: Literature Review .
Understaffing in Nursing: Literature Review .

Psychology Literature Review Example

If you look for an RRL topic in psychology , you can write a review of related literature about stress . Summarize scientific evidence about stress stages, side effects, types, or reduction strategies. Or you can write a review of related literature about computer game addiction . In this case, you may concentrate on the neural mechanisms underlying the internet gaming disorder, compare it to other addictions, or evaluate treatment strategies.

A review of related literature about cyberbullying is another interesting option. You can highlight the impact of cyberbullying on undergraduate students’ academic, social, and emotional development.

📝 Look at the examples that we have prepared for you to come up with some more ideas:

Mindfulness in Counseling: A Literature Review .
Team-Building Across Cultures: Literature Review .
Anxiety and Decision Making: Literature Review .
Literature Review on Depression .
Literature Review on Narcissism .
Effects of Depression Among Adolescents .
Causes and Effects of Anxiety in Children .

Literature Review — Sociology Example

Sociological research poses critical questions about social structures and phenomena. For example, you can write a review of related literature about child labor , exploring cultural beliefs and social norms that normalize the exploitation of children. Or you can create a review of related literature about social media . It can investigate the impact of social media on relationships between adolescents or the role of social networks on immigrants’ acculturation .

📝 You can find some more ideas below!

Single Mothers’ Experiences of Relationships with Their Adolescent Sons .
Teachers and Students’ Gender-Based Interactions .
Gender Identity: Biological Perspective and Social Cognitive Theory .
Gender: Culturally-Prescribed Role or Biological Sex .
The Influence of Opioid Misuse on Academic Achievement of Veteran Students .
The Importance of Ethics in Research .
The Role of Family and Social Network Support in Mental Health .

Education Literature Review Example

For your education studies , you can write a review of related literature about academic performance to determine factors that affect student achievement and highlight research gaps. One more idea is to create a review of related literature on study habits , considering their role in the student’s life and academic outcomes.

You can also evaluate a computerized grading system in a review of related literature to single out its advantages and barriers to implementation. Or you can complete a review of related literature on instructional materials to identify their most common types and effects on student achievement.

📝 Find some inspiration in the examples below:

Literature Review on Online Learning Challenges From COVID-19 .
Education, Leadership, and Management: Literature Review .
Literature Review: Standardized Testing Bias .
Bullying of Disabled Children in School .
Interventions and Letter & Sound Recognition: A Literature Review .
Social-Emotional Skills Program for Preschoolers .
Effectiveness of Educational Leadership Management Skills .

Business Research Literature Review

If you’re a business student, you can focus on customer satisfaction in your review of related literature. Discuss specific customer satisfaction features and how it is affected by service quality and prices. You can also create a theoretical literature review about consumer buying behavior to evaluate theories that have significantly contributed to understanding how consumers make purchasing decisions.

📝 Look at the examples to get more exciting ideas:

Leadership and Communication: Literature Review .
Human Resource Development: Literature Review .
Project Management. Literature Review .
Strategic HRM: A Literature Review .
Customer Relationship Management: Literature Review .
Literature Review on International Financial Reporting Standards .
Cultures of Management: Literature Review .

To conclude, a review of related literature is a significant genre of scholarly works that can be applied in various disciplines and for multiple goals. The sources examined in an RRL provide theoretical frameworks for future studies and help create original research questions and hypotheses.

When you finish your outstanding literature review, don’t forget to check whether it sounds logical and coherent. Our text-to-speech tool can help you with that!

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Steps in Conducting a Literature Review

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

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1. Choose a topic. Define your research question.

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

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

2. Decide on the scope of your review

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

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

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

Make a list of the databases you will search.

Where to find databases:

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

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

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

Review the literature

Some questions to help you analyze the research:

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

Tips:

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

Marco pautasso.

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

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

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

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

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

Rule 1: Define a Topic and Audience

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

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

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

Rule 2: Search and Re-search the Literature

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

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

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

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Object name is pcbi.1003149.g001.jpg

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

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

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

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

Rule 3: Take Notes While Reading

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

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

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

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

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

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

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

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

Rule 6: Be Critical and Consistent

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

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

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

Rule 7: Find a Logical Structure

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

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

Rule 8: Make Use of Feedback

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

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

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

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

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

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

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

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

Acknowledgments

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

Funding Statement

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

Learn how to write a review of literature

What is a review of literature.

The format of a review of literature may vary from discipline to discipline and from assignment to assignment.

A review may be a self-contained unit — an end in itself — or a preface to and rationale for engaging in primary research. A review is a required part of grant and research proposals and often a chapter in theses and dissertations.

Generally, the purpose of a review is to analyze critically a segment of a published body of knowledge through summary, classification, and comparison of prior research studies, reviews of literature, and theoretical articles.

Writing the introduction

In the introduction, you should:

Define or identify the general topic, issue, or area of concern, thus providing an appropriate context for reviewing the literature.

Point out overall trends in what has been published about the topic; or conflicts in theory, methodology, evidence, and conclusions; or gaps in research and scholarship; or a single problem or new perspective of immediate interest.

Establish the writer’s reason (point of view) for reviewing the literature; explain the criteria to be used in analyzing and comparing literature and the organization of the review (sequence); and, when necessary, state why certain literature is or is not included (scope).

Writing the body

In the body, you should:

Group research studies and other types of literature (reviews, theoretical articles, case studies, etc.) according to common denominators such as qualitative versus quantitative approaches, conclusions of authors, specific purpose or objective, chronology, etc.

Summarize individual studies or articles with as much or as little detail as each merits according to its comparative importance in the literature, remembering that space (length) denotes significance.

Provide the reader with strong “umbrella” sentences at beginnings of paragraphs, “signposts” throughout, and brief “so what” summary sentences at intermediate points in the review to aid in understanding comparisons and analyses.

Writing the conclusion

In the conclusion, you should:

Summarize major contributions of significant studies and articles to the body of knowledge under review, maintaining the focus established in the introduction.

Evaluate the current “state of the art” for the body of knowledge reviewed, pointing out major methodological flaws or gaps in research, inconsistencies in theory and findings, and areas or issues pertinent to future study.

Conclude by providing some insight into the relationship between the central topic of the literature review and a larger area of study such as a discipline, a scientific endeavor, or a profession.

For further information see our handouts on Writing a Critical Review of a Nonfiction Book or Article or Reading a Book to Review It .

To learn more about literature reviews, take a look at our workshop on Writing Literature Reviews of Published Research.

Sample Literature Reviews

An important strategy for learning how to compose literature reviews in your field or within a specific genre is to locate and analyze representative examples. The following collection of annotated sample literature reviews written and co-written by colleagues associated with UW-Madison showcases how these reviews can do different kind of work for different purposes. Use these successful examples as a starting point for understanding how other writers have approached the challenging and important task of situating their idea in the context of established research.

Sample 1 (PDF) A brief literature review within a political scientists’ National Science Foundation Graduate Research Fellowship grant
Sample 2 (PDF) A several-page literature review at the beginning of a published, academic article about philosophy
Sample 3 (PDF) A brief literature review at the beginning of a published, academic article about photochemistry

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Working with sources
Synthesizing Sources | Examples & Synthesis Matrix

Synthesizing Sources | Examples & Synthesis Matrix

Published on July 4, 2022 by Eoghan Ryan . Revised on May 31, 2023.

Synthesizing sources involves combining the work of other scholars to provide new insights. It’s a way of integrating sources that helps situate your work in relation to existing research.

Synthesizing sources involves more than just summarizing . You must emphasize how each source contributes to current debates, highlighting points of (dis)agreement and putting the sources in conversation with each other.

You might synthesize sources in your literature review to give an overview of the field or throughout your research paper when you want to position your work in relation to existing research.

Example of synthesizing sources, how to synthesize sources, synthesis matrix, other interesting articles, frequently asked questions about synthesizing sources.

Let’s take a look at an example where sources are not properly synthesized, and then see what can be done to improve it.

This paragraph provides no context for the information and does not explain the relationships between the sources described. It also doesn’t analyze the sources or consider gaps in existing research.

Research on the barriers to second language acquisition has primarily focused on age-related difficulties. Building on Lenneberg’s (1967) theory of a critical period of language acquisition, Johnson and Newport (1988) tested Lenneberg’s idea in the context of second language acquisition. Their research seemed to confirm that young learners acquire a second language more easily than older learners. Recent research has considered other potential barriers to language acquisition. Schepens, van Hout, and van der Slik (2022) have revealed that the difficulties of learning a second language at an older age are compounded by dissimilarity between a learner’s first language and the language they aim to acquire. Further research needs to be carried out to determine whether the difficulty faced by adult monoglot speakers is also faced by adults who acquired a second language during the “critical period.”

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To synthesize sources, group them around a specific theme or point of contention.

As you read sources, ask:

What questions or ideas recur? Do the sources focus on the same points, or do they look at the issue from different angles?
How does each source relate to others? Does it confirm or challenge the findings of past research?
Where do the sources agree or disagree?

Once you have a clear idea of how each source positions itself, put them in conversation with each other. Analyze and interpret their points of agreement and disagreement. This displays the relationships among sources and creates a sense of coherence.

Consider both implicit and explicit (dis)agreements. Whether one source specifically refutes another or just happens to come to different conclusions without specifically engaging with it, you can mention it in your synthesis either way.

Synthesize your sources using:

Topic sentences to introduce the relationship between the sources
Signal phrases to attribute ideas to their authors
Transition words and phrases to link together different ideas

To more easily determine the similarities and dissimilarities among your sources, you can create a visual representation of their main ideas with a synthesis matrix . This is a tool that you can use when researching and writing your paper, not a part of the final text.

In a synthesis matrix, each column represents one source, and each row represents a common theme or idea among the sources. In the relevant rows, fill in a short summary of how the source treats each theme or topic.

This helps you to clearly see the commonalities or points of divergence among your sources. You can then synthesize these sources in your work by explaining their relationship.

Example: Synthesis matrix
	Lenneberg (1967)	Johnson and Newport (1988)	Schepens, van Hout, and van der Slik (2022)
Approach	Primarily theoretical, due to the ethical implications of delaying the age at which humans are exposed to language	Testing the English grammar proficiency of 46 native Korean or Chinese speakers who moved to the US between the ages of 3 and 39 (all participants had lived in the US for at least 3 years at the time of testing)	Analyzing the results of 56,024 adult immigrants to the Netherlands from 50 different language backgrounds
Enabling factors in language acquisition	A critical period between early infancy and puberty after which language acquisition capabilities decline	A critical period (following Lenneberg)	General age effects (outside of a contested critical period), as well as the similarity between a learner’s first language and target language
Barriers to language acquisition	Aging	Aging (following Lenneberg)	Aging as well as the dissimilarity between a learner’s first language and target language

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Synthesizing sources means comparing and contrasting the work of other scholars to provide new insights.

It involves analyzing and interpreting the points of agreement and disagreement among sources.

You might synthesize sources in your literature review to give an overview of the field of research or throughout your paper when you want to contribute something new to existing research.

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.

Topic sentences help keep your writing focused and guide the reader through your argument.

In an essay or paper , each paragraph should focus on a single idea. By stating the main idea in the topic sentence, you clarify what the paragraph is about for both yourself and your reader.

At college level, you must properly cite your sources in all essays , research papers , and other academic texts (except exams and in-class exercises).

Add a citation whenever you quote , paraphrase , or summarize information or ideas from a source. You should also give full source details in a bibliography or reference list at the end of your text.

The exact format of your citations depends on which citation style you are instructed to use. The most common styles are APA , MLA , and Chicago .

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Ryan, E. (2023, May 31). Synthesizing Sources | Examples & Synthesis Matrix. Scribbr. Retrieved August 21, 2024, from https://www.scribbr.com/working-with-sources/synthesizing-sources/

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

Open access
Published: 23 August 2024

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

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

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1 Introduction

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

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

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

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

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

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

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

2 Methodology

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

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

Methodical procedure of our SLR following PRISMA [ 41 ]

2.1 Data identification

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

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

2.2 Data analysis

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

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

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

2.3 Descriptive analysis

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

Descriptive analyses of the selected articles addressing AI adoption in production

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

2.4 Factor analysis

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

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

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

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

3 Factors influencing AI adoption

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

Framework of factors influencing AI adoption in production

3.1 Internal Environment

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

3.1.1 Business and structure

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

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

3.1.2 Organizational effectiveness

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

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

3.1.3 Technology and System

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

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

3.1.4 Data management

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

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

3.2 External environment

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

3.2.1 Regulatory environment

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

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

3.2.2 Business environment

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

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

3.2.3 Economic environment

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

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

3.3 Future research directions

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

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

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

4 Conclusions

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

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

4.1 Contributions

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

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

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

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

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

4.2 Limitations

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

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

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

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

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

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Ten Simple Rules for Writing a Literature Review
A conceptual diagram of the need for different types of literature reviews depending on the amount of published research papers and literature reviews.
Guidance on Conducting a Systematic Literature Review
In this article, through a systematic search on the methodology of literature review, we categorize a typology of literature reviews, discuss steps in conducting a systematic literature review, and provide suggestions on how to enhance rigor in literature reviews in planning education and research.
Learn how to write a review of literature
A review is a required part of grant and research proposals and often a chapter in theses and dissertations. Generally, the purpose of a review is to analyze critically a segment of a published body of knowledge through summary, classification, and comparison of prior research studies, reviews of literature, and theoretical articles.
CHAPTER 2 REVIEW OF RELATED LITERATURE
A review of literature is a classification and evaluation of what accredited scholars and. researchers have written on a topic, organized according to a guiding concept such as a research ...
Q: How do I do a review of related literature (RRL)?
A review of related literature (RRL) is a detailed review of existing literature related to the topic of a thesis or dissertation. In an RRL, you talk about knowledge and findings from existing literature relevant to your topic. If you find gaps or conflicts in existing literature, you can also discuss these in your review, and if applicable, how you plan to address these gaps or resolve these ...
Sample Literature Reviews
This guide will provide research and writing tips to help students complete a literature review assignment.
Research Guides: Conducting a Literature Review: Synthesize
Interactive learning module that guides you through the process of identifying, evaluating, and using scholarly information to research and write a literature review.
Synthesizing Sources
You might synthesize sources in your literature review to give an overview of the field or throughout your research paper when you want to position your work in relation to existing research.
(PDF) Review Of Related Literature And Related Studies on Health
Abstract This chapter presents the relevant literature and studies that the researcher considered in strengthening the claim and importance of the present study. Defining Health Literacy The U.S ...
Example of Review of Related Literature and Studies
Related Literature In this part of the research study, the researchers will include all the related literature and studies, providing five (5) literatures and five (5) studies.
Exploring the factors driving AI adoption in production: a ...
We review the scientific literature published between 2010 and May 2024 to analyze the current state of research on AI in production. Following a systematic approach to select relevant studies, our literature review is based on a sample of articles that contribute to production-specific AI adoption.
23 FEB SAMPLE Genetic Screening and Breast Cancer Multi ...
Alternative methods to the standard cancer-related treatment plans The perceived risk and lack of knowledge influence preventive care. There have been several studies to encourage alternative methods of the current clinical standard and hopefully change the perceived risks. One such method is suggested by Schwartz (2019).
Sample Size for Feasibility Survey
Meaghan Brown For survey research where inferential statistics are not being used, there isn't a strict rule for sample size, but a common benchmark in survey research is to aim for a response ...

CHAPTER 2 REVIEW OF RELATED LITERATURE AND STUDIES

Related Papers

RELATED PAPERS

How to Write Review of Related Literature (RRL) in Research

Why a review of related literature in research is important

Tips on how to write a review of related literature in research

Q: Is research complete without a review of related literature?

Q: What is difference between RRL and RRS?

Q: Does review of related literature improve accuracy and validity of research?

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

Table of Contents

How to write a good literature review

What is a literature review?

What is the purpose of literature review?

Literature review example

Literature Review on Climate Change Impacts on Biodiversity:

a. Habitat Loss and Species Extinction:

b. Range Shifts and Phenological Changes:

c. Ocean Acidification and Coral Reefs:

d. Adaptive Strategies and Conservation Efforts:

Conducting a literature review

Choose a Topic and Define the Research Question:

Decide on the Scope of Your Review:

Select Databases for Searches:

Conduct Searches and Keep Track:

Review the Literature:

Organize and Write Your Literature Review:

How to write a literature review faster with Paperpal?

Frequently asked questions

Related Reads:

6 Tips for Post-Doc Researchers to Take Their Career to the Next Level

Organizing Your Social Sciences Research Paper

Importance of a Good Literature Review

Structure and Writing Style

Writing Tip

Another Writing Tip

Yet Another Writing Tip

How to Write a Literature Review

Synthesis Visualization

About Synthesis

Approaches to Synthesis

How to Begin?

Four Examples of Student Writing

Research Process :: Step by Step

Ask yourself questions like these:

Ask yourself questions like these about each book or article you include:

The Sheridan Libraries

Get Organized

Synthesize your Information

Synthesis Matrix

Literature Syntheis 101

Overview: Literature Synthesis

What does “synthesis” actually mean?

1. Points Of Agreement

Need a helping hand?

2. Points Of Disagreement

3. Key Theories

4. Contexts

5. Methodological Approaches

Bringing It All Together

Psst… there’s more!

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Review of Related Literature: Format, Example, & How to Make RRL

🔤 What Is RRL?

🔗 References

❗ Significance of Review of Related Literature

🔎 How to Perform a Literature Search

🧩 Literature Review Structure Example

Introduction of Review of Related Literature: Sample

Sample Review of Related Literature Thesis

Literature Review Body Paragraph Example

Review of Related Literature: Conclusion

📋 Format of RRL — APA, MLA, & Others

✍️ How to Write Review of Related Literature – Sample

Thematic Literature Review

Chronological Literature Review

Methodological Literature Review