parts of a journal article review

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• Critical Reviews

How to Write an Article Review (With Examples)

Last Updated: April 24, 2024 Fact Checked

Preparing to Write Your Review

Writing the article review, sample article reviews, expert q&a.

This article was co-authored by Jake Adams . Jake Adams is an academic tutor and the owner of Simplifi EDU, a Santa Monica, California based online tutoring business offering learning resources and online tutors for academic subjects K-College, SAT & ACT prep, and college admissions applications. With over 14 years of professional tutoring experience, Jake is dedicated to providing his clients the very best online tutoring experience and access to a network of excellent undergraduate and graduate-level tutors from top colleges all over the nation. Jake holds a BS in International Business and Marketing from Pepperdine University. There are 12 references cited in this article, which can be found at the bottom of the page. This article has been fact-checked, ensuring the accuracy of any cited facts and confirming the authority of its sources. This article has been viewed 3,102,196 times.

An article review is both a summary and an evaluation of another writer's article. Teachers often assign article reviews to introduce students to the work of experts in the field. Experts also are often asked to review the work of other professionals. Understanding the main points and arguments of the article is essential for an accurate summation. Logical evaluation of the article's main theme, supporting arguments, and implications for further research is an important element of a review . Here are a few guidelines for writing an article review.

Education specialist Alexander Peterman recommends: "In the case of a review, your objective should be to reflect on the effectiveness of what has already been written, rather than writing to inform your audience about a subject."

Article Review 101

• Read the article very closely, and then take time to reflect on your evaluation. Consider whether the article effectively achieves what it set out to.
• Write out a full article review by completing your intro, summary, evaluation, and conclusion. Don't forget to add a title, too!
• Proofread your review for mistakes (like grammar and usage), while also cutting down on needless information.

• Article reviews present more than just an opinion. You will engage with the text to create a response to the scholarly writer's ideas. You will respond to and use ideas, theories, and research from your studies. Your critique of the article will be based on proof and your own thoughtful reasoning.
• An article review only responds to the author's research. It typically does not provide any new research. However, if you are correcting misleading or otherwise incorrect points, some new data may be presented.
• An article review both summarizes and evaluates the article.

• Summarize the article. Focus on the important points, claims, and information.
• Discuss the positive aspects of the article. Think about what the author does well, good points she makes, and insightful observations.
• Identify contradictions, gaps, and inconsistencies in the text. Determine if there is enough data or research included to support the author's claims. Find any unanswered questions left in the article.

• Make note of words or issues you don't understand and questions you have.
• Look up terms or concepts you are unfamiliar with, so you can fully understand the article. Read about concepts in-depth to make sure you understand their full context.

• Pay careful attention to the meaning of the article. Make sure you fully understand the article. The only way to write a good article review is to understand the article.

• With either method, make an outline of the main points made in the article and the supporting research or arguments. It is strictly a restatement of the main points of the article and does not include your opinions.
• After putting the article in your own words, decide which parts of the article you want to discuss in your review. You can focus on the theoretical approach, the content, the presentation or interpretation of evidence, or the style. You will always discuss the main issues of the article, but you can sometimes also focus on certain aspects. This comes in handy if you want to focus the review towards the content of a course.
• Review the summary outline to eliminate unnecessary items. Erase or cross out the less important arguments or supplemental information. Your revised summary can serve as the basis for the summary you provide at the beginning of your review.

• What does the article set out to do?
• What is the theoretical framework or assumptions?
• Are the central concepts clearly defined?
• How adequate is the evidence?
• How does the article fit into the literature and field?
• Does it advance the knowledge of the subject?
• How clear is the author's writing? Don't: include superficial opinions or your personal reaction. Do: pay attention to your biases, so you can overcome them.

• For example, in MLA , a citation may look like: Duvall, John N. "The (Super)Marketplace of Images: Television as Unmediated Mediation in DeLillo's White Noise ." Arizona Quarterly 50.3 (1994): 127-53. Print. [9] X Trustworthy Source Purdue Online Writing Lab Trusted resource for writing and citation guidelines Go to source

• For example: The article, "Condom use will increase the spread of AIDS," was written by Anthony Zimmerman, a Catholic priest.

• Your introduction should only be 10-25% of your review.
• End the introduction with your thesis. Your thesis should address the above issues. For example: Although the author has some good points, his article is biased and contains some misinterpretation of data from others’ analysis of the effectiveness of the condom.

• Use direct quotes from the author sparingly.
• Review the summary you have written. Read over your summary many times to ensure that your words are an accurate description of the author's article.

• Support your critique with evidence from the article or other texts.
• The summary portion is very important for your critique. You must make the author's argument clear in the summary section for your evaluation to make sense.
• Remember, this is not where you say if you liked the article or not. You are assessing the significance and relevance of the article.
• Use a topic sentence and supportive arguments for each opinion. For example, you might address a particular strength in the first sentence of the opinion section, followed by several sentences elaborating on the significance of the point.

• This should only be about 10% of your overall essay.
• For example: This critical review has evaluated the article "Condom use will increase the spread of AIDS" by Anthony Zimmerman. The arguments in the article show the presence of bias, prejudice, argumentative writing without supporting details, and misinformation. These points weaken the author’s arguments and reduce his credibility.

• Make sure you have identified and discussed the 3-4 key issues in the article.

You Might Also Like

• ↑ https://libguides.cmich.edu/writinghelp/articlereview
• ↑ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4548566/
• ↑ Jake Adams. Academic Tutor & Test Prep Specialist. Expert Interview. 24 July 2020.
• ↑ https://guides.library.queensu.ca/introduction-research/writing/critical
• ↑ https://www.iup.edu/writingcenter/writing-resources/organization-and-structure/creating-an-outline.html
• ↑ https://writing.umn.edu/sws/assets/pdf/quicktips/titles.pdf
• ↑ https://owl.purdue.edu/owl/research_and_citation/mla_style/mla_formatting_and_style_guide/mla_works_cited_periodicals.html
• ↑ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4548565/
• ↑ https://writingcenter.uconn.edu/wp-content/uploads/sites/593/2014/06/How_to_Summarize_a_Research_Article1.pdf
• ↑ https://www.uis.edu/learning-hub/writing-resources/handouts/learning-hub/how-to-review-a-journal-article
• ↑ https://writingcenter.unc.edu/tips-and-tools/editing-and-proofreading/

About This Article

If you have to write an article review, read through the original article closely, taking notes and highlighting important sections as you read. Next, rewrite the article in your own words, either in a long paragraph or as an outline. Open your article review by citing the article, then write an introduction which states the article’s thesis. Next, summarize the article, followed by your opinion about whether the article was clear, thorough, and useful. Finish with a paragraph that summarizes the main points of the article and your opinions. To learn more about what to include in your personal critique of the article, keep reading the article! Did this summary help you? Yes No

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How to write a journal article review: Do the writing

• What's in this Guide
• What is a journal article?
• Create a template
• Choose your article to review
• Read your article carefully

Do the writing

• Remember to edit
• Additional resources

Start to write. Follow the instructions of your assessment, then structure your writing accordingly.

The four key parts of a journal article review are:

3. A critique, or a discussion about the key points of the journal article.

A critique is a discussion about the key points of the journal article. It should be a balanced discussion about the  strengths and weaknesses of the key points and structure of the article.

You will also need to discuss if the author(s) points are valid (supported by other literature) and robust (would you get the same outcome if the way the information was gathered was repeated).

Example of part of a critique

4. A conclusion - a final evaluation of the article

1. Give an overall opinion of the text.

2. Briefly summarise key points and determine if they are valid, useful, accurate etc.

3. Remember, do not include new ideas or opinions in the conclusion.

Pathways and Academic Learning Support

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• Last Updated: Apr 27, 2023 4:28 PM
• URL: https://libguides.newcastle.edu.au/how-to-write-a-journal-article-review

How to Write an Article Review: Template & Examples

An article review is an academic assignment that invites you to study a piece of academic research closely. Then, you should present its summary and critically evaluate it using the knowledge you’ve gained in class and during your independent study. If you get such a task at college or university, you shouldn’t confuse it with a response paper, which is a distinct assignment with other purposes (we’ll talk about it in detail below).

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In this article, prepared by Custom-Writing experts, you’ll find:

• the intricacies of article review writing;
• the difference between an article review and similar assignments;
• a step-by-step algorithm for review composition;
• a couple of samples to guide you throughout the writing process.

So, if you wish to study our article review example and discover helpful writing tips, keep reading.

❓ What Is an Article Review?

• ✍️ Writing Steps

📑 Article Review Format

🔗 references.

An article review is an academic paper that summarizes and critically evaluates the information presented in your selected article.

The first thing you should note when approaching the task of an article review is that not every article is suitable for this assignment. Let’s have a look at the variety of articles to understand what you can choose from.

Popular Vs. Scholarly Articles

In most cases, you’ll be required to review a scholarly, peer-reviewed article – one composed in compliance with rigorous academic standards. Yet, the Web is also full of popular articles that don’t present original scientific value and shouldn’t be selected for a review.

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Not sure how to distinguish these two types? Here is a comparative table to help you out.

Article Review vs. Response Paper

Now, let’s consider the difference between an article review and a response paper:

• If you’re assigned to critique a scholarly article , you will need to compose an article review .
• If your subject of analysis is a popular article , you can respond to it with a well-crafted response paper .

The reason for such distinctions is the quality and structure of these two article types. Peer-reviewed, scholarly articles have clear-cut quality criteria, allowing you to conduct and present a structured assessment of the assigned material. Popular magazines have loose or non-existent quality criteria and don’t offer an opportunity for structured evaluation. So, they are only fit for a subjective response, in which you can summarize your reactions and emotions related to the reading material.

All in all, you can structure your response assignments as outlined in the tips below.

✍️ How to Write an Article Review: Step by Step

Here is a tried and tested algorithm for article review writing from our experts. We’ll consider only the critical review variety of this academic assignment. So, let’s get down to the stages you need to cover to get a stellar review.

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Read the Article

As with any reviews, reports, and critiques, you must first familiarize yourself with the assigned material. It’s impossible to review something you haven’t read, so set some time for close, careful reading of the article to identify:

• The author’s main points and message.
• The arguments they use to prove their points.
• The methodology they use to approach the subject.

In terms of research type , your article will usually belong to one of three types explained below.

Summarize the Article

Now that you’ve read the text and have a general impression of the content, it’s time to summarize it for your readers. Look into the article’s text closely to determine:

• The thesis statement , or general message of the author.
• Research question, purpose, and context of research.
• Supporting points for the author’s assumptions and claims.
• Major findings and supporting evidence.

As you study the article thoroughly, make notes on the margins or write these elements out on a sheet of paper. You can also apply a different technique: read the text section by section and formulate its gist in one phrase or sentence. Once you’re done, you’ll have a summary skeleton in front of you.

Evaluate the Article

The next step of review is content evaluation. Keep in mind that various research types will require a different set of review questions. Here is a complete list of evaluation points you can include.

Get an originally-written paper according to your instructions!

Write the Text

After completing the critical review stage, it’s time to compose your article review.

The format of this assignment is standard – you will have an introduction, a body, and a conclusion. The introduction should present your article and summarize its content. The body will contain a structured review according to all four dimensions covered in the previous section. The concluding part will typically recap all the main points you’ve identified during your assessment.

It is essential to note that an article review is, first of all, an academic assignment. Therefore, it should follow all rules and conventions of academic composition, such as:

• No contractions . Don’t use short forms, such as “don’t,” “can’t,” “I’ll,” etc. in academic writing. You need to spell out all those words.
• Formal language and style . Avoid conversational phrasing and words that you would naturally use in blog posts or informal communication. For example, don’t use words like “pretty,” “kind of,” and “like.”
• Third-person narrative . Academic reviews should be written from the third-person point of view, avoiding statements like “I think,” “in my opinion,” and so on.
• No conversational forms . You shouldn’t turn to your readers directly in the text by addressing them with the pronoun “you.” It’s vital to keep the narrative neutral and impersonal.
• Proper abbreviation use . Consult the list of correct abbreviations , like “e.g.” or “i.e.,” for use in your academic writing. If you use informal abbreviations like “FYA” or “f.i.,” your professor will reduce the grade.
• Complete sentences . Make sure your sentences contain the subject and the predicate; avoid shortened or sketch-form phrases suitable for a draft only.
• No conjunctions at the beginning of a sentence . Remember the FANBOYS rule – don’t start a sentence with words like “and” or “but.” They often seem the right way to build a coherent narrative, but academic writing rules disfavor such usage.
• No abbreviations or figures at the beginning of a sentence . Never start a sentence with a number — spell it out if you need to use it anyway. Besides, sentences should never begin with abbreviations like “e.g.”

Finally, a vital rule for an article review is properly formatting the citations. We’ll discuss the correct use of citation styles in the following section.

When composing an article review, keep these points in mind:

• Start with a full reference to the reviewed article so the reader can locate it quickly.
• Ensure correct formatting of in-text references.
• Provide a complete list of used external sources on the last page of the review – your bibliographical entries .

You’ll need to understand the rules of your chosen citation style to meet all these requirements. Below, we’ll discuss the two most common referencing styles – APA and MLA.

Article Review in APA

When you need to compose an article review in the APA format , here is the general bibliographical entry format you should use for journal articles on your reference page:

• Author’s last name, First initial. Middle initial. (Year of Publication). Name of the article. Name of the Journal, volume (number), pp. #-#. https://doi.org/xx.xxx/yyyy

Horigian, V. E., Schmidt, R. D., & Feaster, D. J. (2021). Loneliness, mental health, and substance use among US young adults during COVID-19. Journal of Psychoactive Drugs, 53 (1), pp. 1-9. https://doi.org/10.1080/02791072.2020.1836435

Your in-text citations should follow the author-date format like this:

• If you paraphrase the source and mention the author in the text: According to Horigian et al. (2021), young adults experienced increased levels of loneliness, depression, and anxiety during the pandemic.
• If you paraphrase the source and don’t mention the author in the text: Young adults experienced increased levels of loneliness, depression, and anxiety during the pandemic (Horigian et al., 2021).
• If you quote the source: As Horigian et al. (2021) point out, there were “elevated levels of loneliness, depression, anxiety, alcohol use, and drug use among young adults during COVID-19” (p. 6).

Note that your in-text citations should include “et al.,” as in the examples above, if your article has 3 or more authors. If you have one or two authors, your in-text citations would look like this:

• One author: “According to Smith (2020), depression is…” or “Depression is … (Smith, 2020).”
• Two authors: “According to Smith and Brown (2020), anxiety means…” or “Anxiety means (Smith & Brown, 2020).”

Finally, in case you have to review a book or a website article, here are the general formats for citing these source types on your APA reference list.

Article Review in MLA

If your assignment requires MLA-format referencing, here’s the general format you should use for citing journal articles on your Works Cited page:

• Author’s last name, First name. “Title of an Article.” Title of the Journal , vol. #, no. #, year, pp. #-#.

Horigian, Viviana E., et al. “Loneliness, Mental Health, and Substance Use Among US Young Adults During COVID-19.” Journal of Psychoactive Drugs , vol. 53, no. 1, 2021, pp. 1-9.

In-text citations in the MLA format follow the author-page citation format and look like this:

• According to Horigian et al., young adults experienced increased levels of loneliness, depression, and anxiety during the pandemic (6).
• Young adults experienced increased levels of loneliness, depression, and anxiety during the pandemic (Horigian et al. 6).

Like in APA, the abbreviation “et al.” is only needed in MLA if your article has 3 or more authors.

If you need to cite a book or a website page, here are the general MLA formats for these types of sources.

✅ Article Review Template

Here is a handy, universal article review template to help you move on with any review assignment. We’ve tried to make it as generic as possible to guide you in the academic process.

📝 Article Review Examples

The theory is good, but practice is even better. Thus, we’ve created three brief examples to show you how to write an article review. You can study the full-text samples by following the links.

📃 Men, Women, & Money  

This article review examines a famous piece, “Men, Women & Money – How the Sexes Differ with Their Finances,” published by Amy Livingston in 2020. The author of this article claims that men generally spend more money than women. She makes this conclusion from a close analysis of gender-specific expenditures across five main categories: food, clothing, cars, entertainment, and general spending patterns. Livingston also looks at men’s approach to saving to argue that counter to the common perception of women’s light-hearted attitude to money, men are those who spend more on average.

📃 When and Why Nationalism Beats Globalism

This is a review of Jonathan Heidt’s 2016 article titled “When and Why Nationalism Beats Globalism,” written as an advocacy of right-wing populism rising in many Western states. The author illustrates the case with the election of Donald Trump as the US President and the rise of right-wing rhetoric in many Western countries. These examples show how nationalist sentiment represents a reaction to global immigration and a failure of globalization.

📃 Sleep Deprivation  

This is a review of the American Heart Association’s article titled “The Dangers of Sleep Deprivation.” It discusses how the national organization concerned with the American population’s cardiovascular health links the lack of high-quality sleep to far-reaching health consequences. The organization’s experts reveal how a consistent lack of sleep leads to Alzheimer’s disease development, obesity, type 2 diabetes, etc.

✏️ Article Review FAQ

A high-quality article review should summarize the assigned article’s content and offer data-backed reactions and evaluations of its quality in terms of the article’s purpose, methodology, and data used to argue the main points. It should be detailed, comprehensive, objective, and evidence-based.

The purpose of writing a review is to allow students to reflect on research quality and showcase their critical thinking and evaluation skills. Students should exhibit their mastery of close reading of research publications and their unbiased assessment.

The content of your article review will be the same in any format, with the only difference in the assignment’s formatting before submission. Ensure you have a separate title page made according to APA standards and cite sources using the parenthetical author-date referencing format.

You need to take a closer look at various dimensions of an assigned article to compose a valuable review. Study the author’s object of analysis, the purpose of their research, the chosen method, data, and findings. Evaluate all these dimensions critically to see whether the author has achieved the initial goals. Finally, offer improvement recommendations to add a critique aspect to your paper.

• Scientific Article Review: Duke University
• Book and Article Reviews: William & Mary, Writing Resources Center
• Sample Format for Reviewing a Journal Article: Boonshoft School of Medicine
• Research Paper Review – Structure and Format Guidelines: New Jersey Institute of Technology
• Article Review: University of Waterloo
• Article Review: University of South Australia
• How to Write a Journal Article Review: University of Newcastle Library Guides
• Writing Help: The Article Review: Central Michigan University Libraries
• Write a Critical Review of a Scientific Journal Article: McLaughlin Library
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How to Review a Journal Article

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For many kinds of assignments, like a  literature review , you may be asked to offer a critique or review of a journal article. This is an opportunity for you as a scholar to offer your  qualified opinion  and  evaluation  of how another scholar has composed their article, argument, and research. That means you will be expected to go beyond a simple  summary  of the article and evaluate it on a deeper level. As a college student, this might sound intimidating. However, as you engage with the research process, you are becoming immersed in a particular topic, and your insights about the way that topic is presented are valuable and can contribute to the overall conversation surrounding your topic.

IMPORTANT NOTE!!

Some disciplines, like Criminal Justice, may only want you to summarize the article without including your opinion or evaluation. If your assignment is to summarize the article only, please see our literature review handout.

Before getting started on the critique, it is important to review the article thoroughly and critically. To do this, we recommend take notes,  annotating , and reading the article several times before critiquing. As you read, be sure to note important items like the thesis, purpose, research questions, hypotheses, methods, evidence, key findings, major conclusions, tone, and publication information. Depending on your writing context, some of these items may not be applicable.

Questions to Consider

To evaluate a source, consider some of the following questions. They are broken down into different categories, but answering these questions will help you consider what areas to examine. With each category, we recommend identifying the strengths and weaknesses in each since that is a critical part of evaluation.

Evaluating Purpose and Argument

• How well is the purpose made clear in the introduction through background/context and thesis?
• How well does the abstract represent and summarize the article’s major points and argument?
• How well does the objective of the experiment or of the observation fill a need for the field?
• How well is the argument/purpose articulated and discussed throughout the body of the text?
• How well does the discussion maintain cohesion?

Evaluating the Presentation/Organization of Information

• How appropriate and clear is the title of the article?
• Where could the author have benefited from expanding, condensing, or omitting ideas?
• How clear are the author’s statements? Challenge ambiguous statements.
• What underlying assumptions does the author have, and how does this affect the credibility or clarity of their article?
• How objective is the author in his or her discussion of the topic?
• How well does the organization fit the article’s purpose and articulate key goals?

Evaluating Methods

• How appropriate are the study design and methods for the purposes of the study?
• How detailed are the methods being described? Is the author leaving out important steps or considerations?
• Have the procedures been presented in enough detail to enable the reader to duplicate them?

Evaluating Data

• Scan and spot-check calculations. Are the statistical methods appropriate?
• Do you find any content repeated or duplicated?
• How many errors of fact and interpretation does the author include? (You can check on this by looking up the references the author cites).
• What pertinent literature has the author cited, and have they used this literature appropriately?

Following, we have an example of a summary and an evaluation of a research article. Note that in most literature review contexts, the summary and evaluation would be much shorter. This extended example shows the different ways a student can critique and write about an article.

Chik, A. (2012). Digital gameplay for autonomous foreign language learning: Gamers’ and language teachers’ perspectives. In H. Reinders (ed.),  Digital games in language learning and teaching  (pp. 95-114). Eastbourne, UK: Palgrave Macmillan.

Be sure to include the full citation either in a reference page or near your evaluation if writing an  annotated bibliography .

In Chik’s article “Digital Gameplay for Autonomous Foreign Language Learning: Gamers’ and Teachers’ Perspectives”, she explores the ways in which “digital gamers manage gaming and gaming-related activities to assume autonomy in their foreign language learning,” (96) which is presented in contrast to how teachers view the “pedagogical potential” of gaming. The research was described as an “umbrella project” consisting of two parts. The first part examined 34 language teachers’ perspectives who had limited experience with gaming (only five stated they played games regularly) (99). Their data was recorded through a survey, class discussion, and a seven-day gaming trial done by six teachers who recorded their reflections through personal blog posts. The second part explored undergraduate gaming habits of ten Hong Kong students who were regular gamers. Their habits were recorded through language learning histories, videotaped gaming sessions, blog entries of gaming practices, group discussion sessions, stimulated recall sessions on gaming videos, interviews with other gamers, and posts from online discussion forums. The research shows that while students recognize the educational potential of games and have seen benefits of it in their lives, the instructors overall do not see the positive impacts of gaming on foreign language learning.

The summary includes the article’s purpose, methods, results, discussion, and citations when necessary.

This article did a good job representing the undergraduate gamers’ voices through extended quotes and stories. Particularly for the data collection of the undergraduate gamers, there were many opportunities for an in-depth examination of their gaming practices and histories. However, the representation of the teachers in this study was very uneven when compared to the students. Not only were teachers labeled as numbers while the students picked out their own pseudonyms, but also when viewing the data collection, the undergraduate students were more closely examined in comparison to the teachers in the study. While the students have fifteen extended quotes describing their experiences in their research section, the teachers only have two of these instances in their section, which shows just how imbalanced the study is when presenting instructor voices.

Some research methods, like the recorded gaming sessions, were only used with students whereas teachers were only asked to blog about their gaming experiences. This creates a richer narrative for the students while also failing to give instructors the chance to have more nuanced perspectives. This lack of nuance also stems from the emphasis of the non-gamer teachers over the gamer teachers. The non-gamer teachers’ perspectives provide a stark contrast to the undergraduate gamer experiences and fits neatly with the narrative of teachers not valuing gaming as an educational tool. However, the study mentioned five teachers that were regular gamers whose perspectives are left to a short section at the end of the presentation of the teachers’ results. This was an opportunity to give the teacher group a more complex story, and the opportunity was entirely missed.

Additionally, the context of this study was not entirely clear. The instructors were recruited through a master’s level course, but the content of the course and the institution’s background is not discussed. Understanding this context helps us understand the course’s purpose(s) and how those purposes may have influenced the ways in which these teachers interpreted and saw games. It was also unclear how Chik was connected to this masters’ class and to the students. Why these particular teachers and students were recruited was not explicitly defined and also has the potential to skew results in a particular direction.

Overall, I was inclined to agree with the idea that students can benefit from language acquisition through gaming while instructors may not see the instructional value, but I believe the way the research was conducted and portrayed in this article made it very difficult to support Chik’s specific findings.

Some professors like you to begin an evaluation with something positive but isn’t always necessary.

The evaluation is clearly organized and uses transitional phrases when moving to a new topic.

This evaluation includes a summative statement that gives the overall impression of the article at the end, but this can also be placed at the beginning of the evaluation.

This evaluation mainly discusses the representation of data and methods. However, other areas, like organization, are open to critique.

How to Write an Article Review: Tips and Examples

Did you know that article reviews are not just academic exercises but also a valuable skill in today's information age? In a world inundated with content, being able to dissect and evaluate articles critically can help you separate the wheat from the chaff. Whether you're a student aiming to excel in your coursework or a professional looking to stay well-informed, mastering the art of writing article reviews is an invaluable skill.

Short Description

In this article, our research paper writing service experts will start by unraveling the concept of article reviews and discussing the various types. You'll also gain insights into the art of formatting your review effectively. To ensure you're well-prepared, we'll take you through the pre-writing process, offering tips on setting the stage for your review. But it doesn't stop there. You'll find a practical example of an article review to help you grasp the concepts in action. To complete your journey, we'll guide you through the post-writing process, equipping you with essential proofreading techniques to ensure your work shines with clarity and precision!

What Is an Article Review: Grasping the Concept 

A review article is a type of professional paper writing that demands a high level of in-depth analysis and a well-structured presentation of arguments. It is a critical, constructive evaluation of literature in a particular field through summary, classification, analysis, and comparison.

If you write a scientific review, you have to use database searches to portray the research. Your primary goal is to summarize everything and present a clear understanding of the topic you've been working on.

Writing Involves:

• Summarization, classification, analysis, critiques, and comparison.
• The analysis, evaluation, and comparison require the use of theories, ideas, and research relevant to the subject area of the article.
• It is also worth nothing if a review does not introduce new information, but instead presents a response to another writer's work.
• Check out other samples to gain a better understanding of how to review the article.

Types of Review

When it comes to article reviews, there's more than one way to approach the task. Understanding the various types of reviews is like having a versatile toolkit at your disposal. In this section, we'll walk you through the different dimensions of review types, each offering a unique perspective and purpose. Whether you're dissecting a scholarly article, critiquing a piece of literature, or evaluating a product, you'll discover the diverse landscape of article reviews and how to navigate it effectively.

Journal Article Review

Just like other types of reviews, a journal article review assesses the merits and shortcomings of a published work. To illustrate, consider a review of an academic paper on climate change, where the writer meticulously analyzes and interprets the article's significance within the context of environmental science.

Research Article Review

Distinguished by its focus on research methodologies, a research article review scrutinizes the techniques used in a study and evaluates them in light of the subsequent analysis and critique. For instance, when reviewing a research article on the effects of a new drug, the reviewer would delve into the methods employed to gather data and assess their reliability.

Science Article Review

In the realm of scientific literature, a science article review encompasses a wide array of subjects. Scientific publications often provide extensive background information, which can be instrumental in conducting a comprehensive analysis. For example, when reviewing an article about the latest breakthroughs in genetics, the reviewer may draw upon the background knowledge provided to facilitate a more in-depth evaluation of the publication.

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Formatting an Article Review

The format of the article should always adhere to the citation style required by your professor. If you're not sure, seek clarification on the preferred format and ask him to clarify several other pointers to complete the formatting of an article review adequately.

How Many Publications Should You Review?

• In what format should you cite your articles (MLA, APA, ASA, Chicago, etc.)?
• What length should your review be?
• Should you include a summary, critique, or personal opinion in your assignment?
• Do you need to call attention to a theme or central idea within the articles?
• Does your instructor require background information?

When you know the answers to these questions, you may start writing your assignment. Below are examples of MLA and APA formats, as those are the two most common citation styles.

Using the APA Format

Articles appear most commonly in academic journals, newspapers, and websites. If you write an article review in the APA format, you will need to write bibliographical entries for the sources you use:

• Web : Author [last name], A.A [first and middle initial]. (Year, Month, Date of Publication). Title. Retrieved from {link}
• Journal : Author [last name], A.A [first and middle initial]. (Publication Year). Publication Title. Periodical Title, Volume(Issue), pp.-pp.
• Newspaper : Author [last name], A.A [first and middle initial]. (Year, Month, Date of Publication). Publication Title. Magazine Title, pp. xx-xx.

Using MLA Format

• Web : Last, First Middle Initial. “Publication Title.” Website Title. Website Publisher, Date Month Year Published. Web. Date Month Year Accessed.
• Newspaper : Last, First M. “Publication Title.” Newspaper Title [City] Date, Month, Year Published: Page(s). Print.
• Journal : Last, First M. “Publication Title.” Journal Title Series Volume. Issue (Year Published): Page(s). Database Name. Web. Date Month Year Accessed.

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The Pre-Writing Process

Facing this task for the first time can really get confusing and can leave you unsure of where to begin. To create a top-notch article review, start with a few preparatory steps. Here are the two main stages from our dissertation services to get you started:

Step 1: Define the right organization for your review. Knowing the future setup of your paper will help you define how you should read the article. Here are the steps to follow:

• Summarize the article — seek out the main points, ideas, claims, and general information presented in the article.
• Define the positive points — identify the strong aspects, ideas, and insightful observations the author has made.
• Find the gaps —- determine whether or not the author has any contradictions, gaps, or inconsistencies in the article and evaluate whether or not he or she used a sufficient amount of arguments and information to support his or her ideas.
• Identify unanswered questions — finally, identify if there are any questions left unanswered after reading the piece.

Step 2: Move on and review the article. Here is a small and simple guide to help you do it right:

• Start off by looking at and assessing the title of the piece, its abstract, introductory part, headings and subheadings, opening sentences in its paragraphs, and its conclusion.
• First, read only the beginning and the ending of the piece (introduction and conclusion). These are the parts where authors include all of their key arguments and points. Therefore, if you start with reading these parts, it will give you a good sense of the author's main points.
• Finally, read the article fully.

These three steps make up most of the prewriting process. After you are done with them, you can move on to writing your own review—and we are going to guide you through the writing process as well.

Outline and Template

As you progress with reading your article, organize your thoughts into coherent sections in an outline. As you read, jot down important facts, contributions, or contradictions. Identify the shortcomings and strengths of your publication. Begin to map your outline accordingly.

If your professor does not want a summary section or a personal critique section, then you must alleviate those parts from your writing. Much like other assignments, an article review must contain an introduction, a body, and a conclusion. Thus, you might consider dividing your outline according to these sections as well as subheadings within the body. If you find yourself troubled with the pre-writing and the brainstorming process for this assignment, seek out a sample outline.

Your custom essay must contain these constituent parts:

• Pre-Title Page - Before diving into your review, start with essential details: article type, publication title, and author names with affiliations (position, department, institution, location, and email). Include corresponding author info if needed.
• Running Head - In APA format, use a concise title (under 40 characters) to ensure consistent formatting.
• Summary Page - Optional but useful. Summarize the article in 800 words, covering background, purpose, results, and methodology, avoiding verbatim text or references.
• Title Page - Include the full title, a 250-word abstract, and 4-6 keywords for discoverability.
• Introduction - Set the stage with an engaging overview of the article.
• Body - Organize your analysis with headings and subheadings.
• Works Cited/References - Properly cite all sources used in your review.
• Optional Suggested Reading Page - If permitted, suggest further readings for in-depth exploration.
• Tables and Figure Legends (if instructed by the professor) - Include visuals when requested by your professor for clarity.

Example of an Article Review

You might wonder why we've dedicated a section of this article to discuss an article review sample. Not everyone may realize it, but examining multiple well-constructed examples of review articles is a crucial step in the writing process. In the following section, our essay writing service experts will explain why.

Looking through relevant article review examples can be beneficial for you in the following ways:

• To get you introduced to the key works of experts in your field.
• To help you identify the key people engaged in a particular field of science.
• To help you define what significant discoveries and advances were made in your field.
• To help you unveil the major gaps within the existing knowledge of your field—which contributes to finding fresh solutions.
• To help you find solid references and arguments for your own review.
• To help you generate some ideas about any further field of research.
• To help you gain a better understanding of the area and become an expert in this specific field.
• To get a clear idea of how to write a good review.

View Our Writer’s Sample Before Crafting Your Own!

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Steps for Writing an Article Review

Here is a guide with critique paper format on how to write a review paper:

Step 1: Write the Title

First of all, you need to write a title that reflects the main focus of your work. Respectively, the title can be either interrogative, descriptive, or declarative.

Step 2: Cite the Article

Next, create a proper citation for the reviewed article and input it following the title. At this step, the most important thing to keep in mind is the style of citation specified by your instructor in the requirements for the paper. For example, an article citation in the MLA style should look as follows:

Author's last and first name. "The title of the article." Journal's title and issue(publication date): page(s). Print

Abraham John. "The World of Dreams." Virginia Quarterly 60.2(1991): 125-67. Print.

Step 3: Article Identification

After your citation, you need to include the identification of your reviewed article:

• Title of the article
• Title of the journal
• Year of publication

All of this information should be included in the first paragraph of your paper.

The report "Poverty increases school drop-outs" was written by Brian Faith – a Health officer – in 2000.

Step 4: Introduction

Your organization in an assignment like this is of the utmost importance. Before embarking on your writing process, you should outline your assignment or use an article review template to organize your thoughts coherently.

• If you are wondering how to start an article review, begin with an introduction that mentions the article and your thesis for the review.
• Follow up with a summary of the main points of the article.
• Highlight the positive aspects and facts presented in the publication.
• Critique the publication by identifying gaps, contradictions, disparities in the text, and unanswered questions.

Step 5: Summarize the Article

Make a summary of the article by revisiting what the author has written about. Note any relevant facts and findings from the article. Include the author's conclusions in this section.

Step 6: Critique It

Present the strengths and weaknesses you have found in the publication. Highlight the knowledge that the author has contributed to the field. Also, write about any gaps and/or contradictions you have found in the article. Take a standpoint of either supporting or not supporting the author's assertions, but back up your arguments with facts and relevant theories that are pertinent to that area of knowledge. Rubrics and templates can also be used to evaluate and grade the person who wrote the article.

Step 7: Craft a Conclusion

In this section, revisit the critical points of your piece, your findings in the article, and your critique. Also, write about the accuracy, validity, and relevance of the results of the article review. Present a way forward for future research in the field of study. Before submitting your article, keep these pointers in mind:

• As you read the article, highlight the key points. This will help you pinpoint the article's main argument and the evidence that they used to support that argument.
• While you write your review, use evidence from your sources to make a point. This is best done using direct quotations.
• Select quotes and supporting evidence adequately and use direct quotations sparingly. Take time to analyze the article adequately.
• Every time you reference a publication or use a direct quotation, use a parenthetical citation to avoid accidentally plagiarizing your article.
• Re-read your piece a day after you finish writing it. This will help you to spot grammar mistakes and to notice any flaws in your organization.
• Use a spell-checker and get a second opinion on your paper.

The Post-Writing Process: Proofread Your Work

Finally, when all of the parts of your article review are set and ready, you have one last thing to take care of — proofreading. Although students often neglect this step, proofreading is a vital part of the writing process and will help you polish your paper to ensure that there are no mistakes or inconsistencies.

To proofread your paper properly, start by reading it fully and checking the following points:

• Punctuation
• Other mistakes

Afterward, take a moment to check for any unnecessary information in your paper and, if found, consider removing it to streamline your content. Finally, double-check that you've covered at least 3-4 key points in your discussion.

And remember, if you ever need help with proofreading, rewriting your essay, or even want to buy essay , our friendly team is always here to assist you.

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What Is A Review Article?

How to write an article review, how to write an article review in apa format, related articles.

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How to Write a Peer Review

When you write a peer review for a manuscript, what should you include in your comments? What should you leave out? And how should the review be formatted?

This guide provides quick tips for writing and organizing your reviewer report.

Review Outline

Use an outline for your reviewer report so it’s easy for the editors and author to follow. This will also help you keep your comments organized.

Think about structuring your review like an inverted pyramid. Put the most important information at the top, followed by details and examples in the center, and any additional points at the very bottom.

Here’s how your outline might look:

1. Summary of the research and your overall impression

In your own words, summarize what the manuscript claims to report. This shows the editor how you interpreted the manuscript and will highlight any major differences in perspective between you and the other reviewers. Give an overview of the manuscript’s strengths and weaknesses. Think about this as your “take-home” message for the editors. End this section with your recommended course of action.

2. Discussion of specific areas for improvement

It’s helpful to divide this section into two parts: one for major issues and one for minor issues. Within each section, you can talk about the biggest issues first or go systematically figure-by-figure or claim-by-claim. Number each item so that your points are easy to follow (this will also make it easier for the authors to respond to each point). Refer to specific lines, pages, sections, or figure and table numbers so the authors (and editors) know exactly what you’re talking about.

Major vs. minor issues

What’s the difference between a major and minor issue? Major issues should consist of the essential points the authors need to address before the manuscript can proceed. Make sure you focus on what is  fundamental for the current study . In other words, it’s not helpful to recommend additional work that would be considered the “next step” in the study. Minor issues are still important but typically will not affect the overall conclusions of the manuscript. Here are some examples of what would might go in the “minor” category:

• Missing references (but depending on what is missing, this could also be a major issue)
• Technical clarifications (e.g., the authors should clarify how a reagent works)
• Data presentation (e.g., the authors should present p-values differently)
• Typos, spelling, grammar, and phrasing issues

3. Any other points

Confidential comments for the editors.

Some journals have a space for reviewers to enter confidential comments about the manuscript. Use this space to mention concerns about the submission that you’d want the editors to consider before sharing your feedback with the authors, such as concerns about ethical guidelines or language quality. Any serious issues should be raised directly and immediately with the journal as well.

This section is also where you will disclose any potentially competing interests, and mention whether you’re willing to look at a revised version of the manuscript.

Do not use this space to critique the manuscript, since comments entered here will not be passed along to the authors.  If you’re not sure what should go in the confidential comments, read the reviewer instructions or check with the journal first before submitting your review. If you are reviewing for a journal that does not offer a space for confidential comments, consider writing to the editorial office directly with your concerns.

Get this outline in a template

Giving Feedback

Giving feedback is hard. Giving effective feedback can be even more challenging. Remember that your ultimate goal is to discuss what the authors would need to do in order to qualify for publication. The point is not to nitpick every piece of the manuscript. Your focus should be on providing constructive and critical feedback that the authors can use to improve their study.

If you’ve ever had your own work reviewed, you already know that it’s not always easy to receive feedback. Follow the golden rule: Write the type of review you’d want to receive if you were the author. Even if you decide not to identify yourself in the review, you should write comments that you would be comfortable signing your name to.

In your comments, use phrases like “ the authors’ discussion of X” instead of “ your discussion of X .” This will depersonalize the feedback and keep the focus on the manuscript instead of the authors.

General guidelines for effective feedback

• Justify your recommendation with concrete evidence and specific examples.
• Be specific so the authors know what they need to do to improve.
• Be thorough. This might be the only time you read the manuscript.
• Be professional and respectful. The authors will be reading these comments too.
• Remember to say what you liked about the manuscript!

Don’t

• Recommend additional experiments or  unnecessary elements that are out of scope for the study or for the journal criteria.
• Tell the authors exactly how to revise their manuscript—you don’t need to do their work for them.
• Use the review to promote your own research or hypotheses.
• Focus on typos and grammar. If the manuscript needs significant editing for language and writing quality, just mention this in your comments.
• Submit your review without proofreading it and checking everything one more time.

Before and After: Sample Reviewer Comments

Keeping in mind the guidelines above, how do you put your thoughts into words? Here are some sample “before” and “after” reviewer comments

✗ Before

“The authors appear to have no idea what they are talking about. I don’t think they have read any of the literature on this topic.”

✓ After

“The study fails to address how the findings relate to previous research in this area. The authors should rewrite their Introduction and Discussion to reference the related literature, especially recently published work such as Darwin et al.”

“The writing is so bad, it is practically unreadable. I could barely bring myself to finish it.”

“While the study appears to be sound, the language is unclear, making it difficult to follow. I advise the authors work with a writing coach or copyeditor to improve the flow and readability of the text.”

“It’s obvious that this type of experiment should have been included. I have no idea why the authors didn’t use it. This is a big mistake.”

“The authors are off to a good start, however, this study requires additional experiments, particularly [type of experiment]. Alternatively, the authors should include more information that clarifies and justifies their choice of methods.”

Suggested Language for Tricky Situations

You might find yourself in a situation where you’re not sure how to explain the problem or provide feedback in a constructive and respectful way. Here is some suggested language for common issues you might experience.

What you think : The manuscript is fatally flawed. What you could say: “The study does not appear to be sound” or “the authors have missed something crucial”.

What you think : You don’t completely understand the manuscript. What you could say : “The authors should clarify the following sections to avoid confusion…”

What you think : The technical details don’t make sense. What you could say : “The technical details should be expanded and clarified to ensure that readers understand exactly what the researchers studied.”

What you think: The writing is terrible. What you could say : “The authors should revise the language to improve readability.”

What you think : The authors have over-interpreted the findings. What you could say : “The authors aim to demonstrate [XYZ], however, the data does not fully support this conclusion. Specifically…”

What does a good review look like?

Check out the peer review examples at F1000 Research to see how other reviewers write up their reports and give constructive feedback to authors.

Time to Submit the Review!

Be sure you turn in your report on time. Need an extension? Tell the journal so that they know what to expect. If you need a lot of extra time, the journal might need to contact other reviewers or notify the author about the delay.

Tip: Building a relationship with an editor

You’ll be more likely to be asked to review again if you provide high-quality feedback and if you turn in the review on time. Especially if it’s your first review for a journal, it’s important to show that you are reliable. Prove yourself once and you’ll get asked to review again!

• Getting started as a reviewer
• Responding to an invitation
• Reading a manuscript
• Writing a peer review

The contents of the Peer Review Center are also available as a live, interactive training session, complete with slides, talking points, and activities. …

The contents of the Writing Center are also available as a live, interactive training session, complete with slides, talking points, and activities. …

There’s a lot to consider when deciding where to submit your work. Learn how to choose a journal that will help your study reach its audience, while reflecting your values as a researcher…

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A Step-by-Step Guide to Writing a Scientific Review Article

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Manisha Bahl, A Step-by-Step Guide to Writing a Scientific Review Article, Journal of Breast Imaging , Volume 5, Issue 4, July/August 2023, Pages 480–485, https://doi.org/10.1093/jbi/wbad028

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Scientific review articles are comprehensive, focused reviews of the scientific literature written by subject matter experts. The task of writing a scientific review article can seem overwhelming; however, it can be managed by using an organized approach and devoting sufficient time to the process. The process involves selecting a topic about which the authors are knowledgeable and enthusiastic, conducting a literature search and critical analysis of the literature, and writing the article, which is composed of an abstract, introduction, body, and conclusion, with accompanying tables and figures. This article, which focuses on the narrative or traditional literature review, is intended to serve as a guide with practical steps for new writers. Tips for success are also discussed, including selecting a focused topic, maintaining objectivity and balance while writing, avoiding tedious data presentation in a laundry list format, moving from descriptions of the literature to critical analysis, avoiding simplistic conclusions, and budgeting time for the overall process.

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Write a Critical Review

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• To introduce the source, its main ideas, key details, and its place within the field
• To present your assessment of the quality of the source

In general, the introduction of your critical review should include

• Author(s) name
• Title of the source 
• What is the author's central purpose?
• What methods or theoretical frameworks were used to accomplish this purpose?
• What topic areas, chapters, sections, or key points did the author use to structure the source?
• What were the results or findings of the study?
• How were the results or findings interpreted? How were they related to the original problem (author's view of evidence rather than objective findings)?
• Who conducted the research? What were/are their interests?
• Why did they do this research?
• Was this research pertinent only within the author’s field, or did it have broader (even global) relevance?
• On what prior research was this source-based? What gap is the author attempting to address?
• How important was the research question posed by the researcher?
• Your overall opinion of the quality of the source. Think of this like a thesis or main argument.
• Present your evaluation of the source, providing evidence from the text (or other sources) to support your assessment.

In general, the body of your critical review should include

• Is the material organized logically and with appropriate headings?
• Are there stylistic problems in logical, clarity or language?
• Were the author(s) able to answer the question (test the hypothesis) raised
• What was the objective of the study?
• Does all the information lead coherently to the purpose of the study?
• Are the methods valid for studying the problem or gap?
• Could the study be duplicated from the information provided?
• Is the experimental design logical and reliable?
• How are the data organized? Is it logical and interpretable?
• Do the results reveal what the researcher intended?
• Do the authors present a logical interpretation of the results?
• Have the limitations of the research been addressed?
• Does the study consider other key studies in the field or other research possibilities or directions?
• How was the significance of the work described?
• Follow the structure of the journal article (e.g. Introduction, Methods, Results, Discussion) - highlighting the strengths and weaknesses in each section
• Present the weaknesses of the article, and then the strengths of the article (or vice versa).
• Group your ideas according to different research themes presented in the source
• Group the strengths and weaknesses of the article into the following areas: originality, reliability, validity, relevance, and presentation

Purpose: 

• To summarize the strengths and weaknesses of the article as a whole
• To assert the article’s practical and theoretical significance

In general, the conclusion of your critical review should include

• A restatement of your overall opinion
• A summary of the key strengths and weaknesses of the research that support your overall opinion of the source
• Did the research reported in this source result in the formation of new questions, theories or hypotheses by the authors or other researchers?
• Have other researchers subsequently supported or refuted the observations or interpretations of these authors?
• Did the research provide new factual information, a new understanding of a phenomenon in the field, a new research technique?
• Did the research produce any practical applications? 
• What are the social, political, technological, or medical implications of this research?
• How do you evaluate the significance of the research? 
• Find out what style guide you are required to follow (e.g., APA, MLA, Chicago) and follow the guidelines to create a reference list (may be called a bibliography or works cited).
• Be sure to include citations in the text when you refer to the source itself or external sources. 
• Check out our Cite Your Sources Guide for more information. 
• Read assignment instructions carefully and refer to them throughout the writing process.
• Make an outline of your main sections before you write.
• If your professor does not assign a topic or source, you must choose one yourself. Select a source that interests you and is written clearly so you can understand it.
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BSCI 1510L Literature and Stats Guide: 3.2 Components of a scientific paper

• 1 What is a scientific paper?
• 2 Referencing and accessing papers
• 2.1 Literature Cited
• 2.2 Accessing Scientific Papers
• 2.3 Traversing the web of citations
• 2.4 Keyword Searches
• 3 Style of scientific writing
• 3.1 Specific details regarding scientific writing

3.2 Components of a scientific paper

• 4 For further information
• Appendix A: Calculation Final Concentrations
• 1 Formulas in Excel
• 2 Basic operations in Excel
• 3 Measurement and Variation
• 3.1 Describing Quantities and Their Variation
• 3.2 Samples Versus Populations
• 3.3 Calculating Descriptive Statistics using Excel
• 4 Variation and differences
• 5 Differences in Experimental Science
• 5.1 Aside: Commuting to Nashville
• 5.2 P and Detecting Differences in Variable Quantities
• 5.3 Statistical significance
• 5.4 A test for differences of sample means: 95% Confidence Intervals
• 5.5 Error bars in figures
• 5.6 Discussing statistics in your scientific writing
• 6 Scatter plot, trendline, and linear regression
• 7 The t-test of Means
• 8 Paired t-test
• 9 Two-Tailed and One-Tailed Tests
• 10 Variation on t-tests: ANOVA
• 11 Reporting the Results of a Statistical Test
• 12 Summary of statistical tests
• 1 Objectives
• 2 Project timeline
• 3 Background
• 4 Previous work in the BSCI 111 class
• 5 General notes about the project
• 6 About the paper
• 7 References

Nearly all journal articles are divided into the following major sections: abstract, introduction, methods, results, discussion, and references.  Usually the sections are labeled as such, although often the introduction (and sometimes the abstract) is not labeled.  Sometimes alternative section titles are used.  The abstract is sometimes called the "summary", the methods are sometimes called "materials and methods", and the discussion is sometimes called "conclusions".   Some journals also include the minor sections of "key words" following the abstract, and "acknowledgments" following the discussion.  In some journals, the sections may be divided into subsections that are given descriptive titles.  However, the general division into the six major sections is nearly universal.

3.2.1 Abstract

The abstract is a short summary (150-200 words or less) of the important points of the paper.  It does not generally include background information.  There may be a very brief statement of the rationale for conducting the study.  It describes what was done, but without details.  It also describes the results in a summarized way that usually includes whether or not the statistical tests were significant.  It usually concludes with a brief statement of the importance of the results.  Abstracts do not include references.  When writing a paper, the abstract is always the last part to be written.

The purpose of the abstract is to allow potential readers of a paper to find out the important points of the paper without having to actually read the paper.  It should be a self-contained unit capable of being understood without the benefit of the text of the article . It essentially serves as an "advertisement" for the paper that readers use to determine whether or not they actually want to wade through the entire paper or not.  Abstracts are generally freely available in electronic form and are often presented in the results of an electronic search.  If searchers do not have electronic access to the journal in which the article is published, the abstract is the only means that they have to decide whether to go through the effort (going to the library to look up the paper journal, requesting a reprint from the author, buying a copy of the article from a service, requesting the article by Interlibrary Loan) of acquiring the article.  Therefore it is important that the abstract accurately and succinctly presents the most important information in the article.

3.2.2 Introduction

The introduction provides the background information necessary to understand why the described experiment was conducted.  The introduction should describe previous research on the topic that has led to the unanswered questions being addressed by the experiment and should cite important previous papers that form the background for the experiment.  The introduction should also state in an organized fashion the goals of the research, i.e. the particular, specific questions that will be tested in the experiments.  There should be a one-to-one correspondence between questions raised in the introduction and points discussed in the conclusion section of the paper.  In other words, do not raise questions in the introduction unless you are going to have some kind of answer to the question that you intend to discuss at the end of the paper. 

You may have been told that every paper must have a hypothesis that can be clearly stated.  That is often true, but not always.  If your experiment involves a manipulation which tests a specific hypothesis, then you should clearly state that hypothesis.  On the other hand, if your experiment was primarily exploratory, descriptive, or measurative, then you probably did not have an a priori hypothesis, so don't pretend that you did and make one up.  (See the discussion in the introduction to Experiment 4 for more on this.)  If you state a hypothesis in the introduction, it should be a general hypothesis and not a null or alternative hypothesis for a statistical test.  If it is necessary to explain how a statistical test will help you evaluate your general hypothesis, explain that in the methods section. 

A good introduction should be fairly heavy with citations.  This indicates to the reader that the authors are informed about previous work on the topic and are not working in a vacuum.  Citations also provide jumping-off points to allow the reader to explore other tangents to the subject that are not directly addressed in the paper.  If the paper supports or refutes previous work, readers can look up the citations and make a comparison for themselves. 

"Do not get lost in reviewing background information. Remember that the Introduction is meant to introduce the reader to your research, not summarize and evaluate all past literature on the subject (which is the purpose of a review paper). Many of the other studies you may be tempted to discuss in your Introduction are better saved for the Discussion, where they become a powerful tool for comparing and interpreting your results. Include only enough background information to allow your reader to understand why you are asking the questions you are and why your hyptheses are reasonable ones. Often, a brief explanation of the theory involved is sufficient. …

Write this section in the past or present tense, never in the future. " (Steingraber et al. 1985)

3.2.3 Methods (taken verbatim from Steingraber et al. 1985)

The function of this section is to describe all experimental procedures, including controls. The description should be complete enough to enable someone else to repeat your work. If there is more than one part to the experiment, it is a good idea to describe your methods and present your results in the same order in each section. This may not be the same order in which the experiments were performed -it is up to you to decide what order of presentation will make the most sense to your reader.

1. Explain why each procedure was done, i.e., what variable were you measuring and why? Example:

Difficult to understand : First, I removed the frog muscle and then I poured Ringer’s solution on it. Next, I attached it to the kymograph.

Improved: I removed the frog muscle and poured Ringer’s solution on it to prevent it from drying out. I then attached the muscle to the kymograph in order to determine the minimum voltage required for contraction.

2. Experimental procedures and results are narrated in the past tense (what you did, what you found, etc.) whereas conclusions from your results are given in the present tense.

3. Mathematical equations and statistical tests are considered mathematical methods and should be described in this section along with the actual experimental work.

4. Use active rather than passive voice when possible.  [Note: see Section 3.1.4 for more about this.]  Always use the singular "I" rather than the plural "we" when you are the only author of the paper.  Throughout the paper, avoid contractions, e.g. did not vs. didn’t.

5. If any of your methods is fully described in a previous publication (yours or someone else’s), you can cite that instead of describing the procedure again.

Example: The chromosomes were counted at meiosis in the anthers with the standard acetocarmine technique of Snow (1955).

3.2.4 Results (with excerpts from Steingraber et al. 1985)

The function of this section is to summarize general trends in the data without comment, bias, or interpretation. The results of statistical tests applied to your data are reported in this section although conclusions about your original hypotheses are saved for the Discussion section.

Tables and figures should be used when they are a more efficient way to convey information than verbal description. They must be independent units, accompanied by explanatory captions that allow them to be understood by someone who has not read the text. Do not repeat in the text the information in tables and figures, but do cite them, with a summary statement when that is appropriate.  Example:

Incorrect: The results are given in Figure 1.

Correct: Temperature was directly proportional to metabolic rate (Fig. 1).

Please note that the entire word "Figure" is almost never written in an article.  It is nearly always abbreviated as "Fig." and capitalized.  Tables are cited in the same way, although Table is not abbreviated.

Whenever possible, use a figure instead of a table. Relationships between numbers are more readily grasped when they are presented graphically rather than as columns in a table.

Data may be presented in figures and tables, but this may not substitute for a verbal summary of the findings. The text should be understandable by someone who has not seen your figures and tables.

1. All results should be presented, including those that do not support the hypothesis.

2. Statements made in the text must be supported by the results contained in figures and tables.

3. The results of statistical tests can be presented in parentheses following a verbal description.

Example: Fruit size was significantly greater in trees growing alone (t = 3.65, df = 2, p < 0.05).

Simple results of statistical tests may be reported in the text as shown in the preceding example.  The results of multiple tests may be reported in a table if that increases clarity. (See Section 11 of the Statistics Manual for more details about reporting the results of statistical tests.)  It is not necessary to provide a citation for a simple t-test of means, paired t-test, or linear regression.  If you use other tests, you should cite the text or reference you followed to do the test.  In your materials and methods section, you should report how you did the test (e.g. using the statistical analysis package of Excel). 

It is NEVER appropriate to simply paste the results from statistical software into the results section of your paper.  The output generally reports more information than is required and it is not in an appropriate format for a paper.

3.2.4.1 Tables

• Do not repeat information in a table that you are depicting in a graph or histogram; include a table only if it presents new information.
• It is easier to compare numbers by reading down a column rather than across a row. Therefore, list sets of data you want your reader to compare in vertical form.
• Provide each table with a number (Table 1, Table 2, etc.) and a title. The numbered title is placed above the table .
• Please see Section 11 of the Excel Reference and Statistics Manual for further information on reporting the results of statistical tests.

3.2.4.2. Figures

• These comprise graphs, histograms, and illustrations, both drawings and photographs. Provide each figure with a number (Fig. 1, Fig. 2, etc.) and a caption (or "legend") that explains what the figure shows. The numbered caption is placed below the figure .  Figure legend = Figure caption.
• Figures submitted for publication must be "photo ready," i.e., they will appear just as you submit them, or photographically reduced. Therefore, when you graduate from student papers to publishable manuscripts, you must learn to prepare figures that will not embarrass you. At the present time, virtually all journals require manuscripts to be submitted electronically and it is generally assumed that all graphs and maps will be created using software rather than being created by hand.  Nearly all journals have specific guidelines for the file types, resolution, and physical widths required for figures.  Only in a few cases (e.g. sketched diagrams) would figures still be created by hand using ink and those figures would be scanned and labeled using graphics software.  Proportions must be the same as those of the page in the journal to which the paper will be submitted. 
• Graphs and Histograms: Both can be used to compare two variables. However, graphs show continuous change, whereas histograms show discrete variables only.  You can compare groups of data by plotting two or even three lines on one graph, but avoid cluttered graphs that are hard to read, and do not plot unrelated trends on the same graph. For both graphs, and histograms, plot the independent variable on the horizontal (x) axis and the dependent variable on the vertical (y) axis. Label both axes, including units of measurement except in the few cases where variables are unitless, such as absorbance.
• Drawings and Photographs: These are used to illustrate organisms, experimental apparatus, models of structures, cellular and subcellular structure, and results of procedures like electrophoresis. Preparing such figures well is a lot of work and can be very expensive, so each figure must add enough to justify its preparation and publication, but good figures can greatly enhance a professional article, as your reading in biological journals has already shown.

3.2.5 Discussion (taken from Steingraber et al. 1985)

The function of this section is to analyze the data and relate them to other studies. To "analyze" means to evaluate the meaning of your results in terms of the original question or hypothesis and point out their biological significance.

1. The Discussion should contain at least:

• the relationship between the results and the original hypothesis, i.e., whether they support the hypothesis, or cause it to be rejected or modified
• an integration of your results with those of previous studies in order to arrive at explanations for the observed phenomena
• possible explanations for unexpected results and observations, phrased as hypotheses that can be tested by realistic experimental procedures, which you should describe

2. Trends that are not statistically significant can still be discussed if they are suggestive or interesting, but cannot be made the basis for conclusions as if they were significant.

3. Avoid redundancy between the Results and the Discussion section. Do not repeat detailed descriptions of the data and results in the Discussion. In some journals, Results and Discussions are joined in a single section, in order to permit a single integrated treatment with minimal repetition. This is more appropriate for short, simple articles than for longer, more complicated ones.

4. End the Discussion with a summary of the principal points you want the reader to remember. This is also the appropriate place to propose specific further study if that will serve some purpose, but do not end with the tired cliché that "this problem needs more study." All problems in biology need more study. Do not close on what you wish you had done, rather finish stating your conclusions and contributions.

3.2.6 Title

The title of the paper should be the last thing that you write.  That is because it should distill the essence of the paper even more than the abstract (the next to last thing that you write). 

The title should contain three elements:

1. the name of the organism studied;

2. the particular aspect or system studied;

3. the variable(s) manipulated.

Do not be afraid to be grammatically creative. Here are some variations on a theme, all suitable as titles:

THE EFFECT OF TEMPERATURE ON GERMINATION OF ZEA MAYS

DOES TEMPERATURE AFFECT GERMINATION OF ZEA MAYS?

TEMPERATURE AND ZEA MAYS GERMINATION: IMPLICATIONS FOR AGRICULTURE

Sometimes it is possible to include the principal result or conclusion in the title:

HIGH TEMPERATURES REDUCE GERMINATION OF ZEA MAYS

Note for the BSCI 1510L class: to make your paper look more like a real paper, you can list all of the other group members as co-authors.  However, if you do that, you should list you name first so that we know that you wrote it.

3.2.7 Literature Cited

Please refer to section 2.1 of this guide.

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• Comm Research Strategies
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• Interlibrary loan
• How to distinguish between types of journal articles
• Components of a scholarly article, and things to consider when reading one
• Critically evaluating articles & other resources
• Literature reviews (opens a new guide) This link opens in a new window
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Components of a scholarly article

• Experimentation
• Results, analysis, & discussion
• Limitations
• Conclusion(s)

“What is this article about?”

Abstract : Most articles start with a paragraph called the “abstract”, which very briefly summarizes the whole article.

Introduction : This section introduces the research question under consideration in the article, and discusses what the article contributes to existing knowledge within the field.

Modified from the Department of Sociology, SUNY Brockport: https://www.brockport.edu/academics/sociology/journal.html

“What do we already know about this topic and what is left to discover?”

Literature review : the authors will review the existing research and theory on the topic, either as part of the introduction, or after the introduction under its own subtitle. The review of literature is meant to discuss previous work on the topic, point out what questions remain, and relate the research presented in the rest of the article to the existing literature.

“How did the author do the research?  Why this way and not this other way?”

Methodology : There is always some discussion of the methods used by the authors to conduct the study being reported.  If these is any sort of control group being used as part of the methodology, it will be described here.

"What specifically did the authors do?"

Experimentation : A description of the experimentation in which the authors engaged.  This section will report any data produced by the experiment, be it numerical data, qualitative response data, etc.  Data comes in many different forms.

“What did the authors find?  What did their findings reveal or say in response to their research question?”

Results, analysis, & discussion : A section or multiple sections will be devoted to analyzing the experiment that was conducted, as well as its results.  These sections then discuss the results, and what the analysis of these results revealed.

"What limitations does this research have, and how might they affect the conclusions that may be drawn from this research?"

Limitations: A description of any limitations of the experimentation in which the authors engaged, and how these limitations may affect the conclusions that may be drawn from this experimentation.

“What does it all mean and why is it important?”

Discussion and Conclusion : Articles typically end by discussing what the results mean and how the study contributes to existing knowledge. Answers to research questions are addressed in this section, as is whether any hypotheses were supported or not. The conclusion typically places the research in a larger context and discusses where future research on the topic may be headed.

Things to consider when reading a scholarly article / Shortcuts to reading journal articles

• Things to consider when reading a scholarly article
• Shortcuts to reading journal articles

Owen Lin. (2012, May 23). Deep Thoughts. Retrieved from https://www.flickr.com/photos/owen-pics/8406656015/. Used under the Creative Commons License.

• Know your research question or argument.  Though your question/argument may change or evolve as you delve deeper into the research process, you will want to have a solid idea of your research focus.  
• You don't have to read the entire article in order.  Start with the abstract which will give you a general summary of the article. If the abstract seems relevant then move to the conclusion or discussion section of the article to gain a better understanding of the article's main claims. At this point if the article does not seem relevant or useful then discard it. However, if the article does seem useful then spend as much time as necessary reading the article.  
• Read critically.  What is the author's argument? You will need to use your judgment when evaluating each source of information. Further research may be necessary if you find the author to be biased or you do not believe the validity of their argument.  
• Read the reference section.  Reading the references or works cited may lead you to other useful resources. You might also get a better understanding of the major players in the area you are researching.  
• Take notes.  How you do this is up to you. Make sure you keep your research question and argument in mind so you can be more efficient when taking notes. Created by Rachel Arteaga, for CSU Chico: http://libguides.csuchico.edu/c.php?g=462359&p=3163509

• Read the abstract first : Titles don’t always give much information. The abstract should give you just enough information to let you know the basics of the article. From this you will know whether you should read on or look elsewhere for your project. Some journals print a list of keywords pertaining to the article as well. These are further clues about the article.  
• Read the introduction and discussion/conclusion next : These sections will give you the main argument of the article, which should be helpful in determining its relevance to you and your project. You’ll also get a glimpse of the findings of the research being reported.  
• Read about the methods next : If what you’ve read so far interests you, get a sense of how the research was done. Is it a qualitative or quantitative project? What data are the study based on?  
• Read the Analysis and results next : If you decide that you are committed to this article, you should read in more detail about this research.

Created by the Department of Sociology, SUNY Brockport: https://www.brockport.edu/academics/sociology/journal.html

What makes information peer-reviewed vs. scholarly vs. non-scholarly? Which type of source should I use?

• What makes information peer-reviewed vs. scholarly vs. non-scholarly?
• Which type of source should I use?

There is a nuanced distinction between peer-review and scholarship, which typically doesn't matter when evaluating sources for possible citation in your own work.  Peer-review is a process through which editors of a journal have other experts in the field evaluate articles submitted to the journal for possible publication.  Different journals have different ways of defining an expert in the field.  Scholarly works, by contrast have an editorial process, but this process does not involve expert peer-reviewers.  Rather, one or more editors, who are themselves often highly decorated scholars in a field, evaluate submissions for possible publication.  This editorial process can be more economically driven than a peer-review process, with a greater emphasis on marketing and selling the published material, but as a general rule this distinction is trivial with regard to evaluating information for possible citation in your own work.

What is perhaps a more salient way of thinking about the peer-review / scholarship distinction is to recognize that while peer-reviewed information is typically highly authoritative, and is generally considered "good" information, the absence of a peer-review process doesn't automatically make information "bad."  More specifically, the only thing the absence of a peer-review process means is that information published in this manner is not peer-reviewed.  Nothing more.  Information that falls into this category is sometimes referred to as "non-scholarly" information -- but again, that doesn't mean this information is somehow necessarily problematic.

Where does that leave you in terms of deciding what type of information to use in producing your own work?  That is a highly individual decision that you must make.  The Which type of source should I use?  tab in this box offers further guidance on answering this question, though it is important to be aware that many WSU instructors will only consider peer-reviewed sources to be acceptable in the coursework you turn in .  You can ask your instructor for his or her thoughts on the types of sources s/he will accept in student work.

Image:  Martin Grater. (2017, Nov. 1). Deep Thought. Retrieved from https://www.flickr.com/photos/152721954@N05/24304490568/. Used under the Creative Commons License.

Your topic and research question or thesis statement will guide you on which resources are best.  Sources can be defined as primary, secondary and tertiary levels away from an event or original idea. Researchers may want to start with tertiary or secondary source for background information. Learning more about a topic will help most researchers make better use of primary sources.

While articles from scholarly journals are often the most prominent of the sources you will consider incorporating into your coursework, they are not the only sources available to you.  Which sources are most appropriate to your research is a direct consequence of they type of research question you decide to address.  In other words, while most university-level papers will require you to reference scholarly sources, not all will.  A student in an English course writing a paper analyzing Bob Dylan's lyrics, for example, may find an interview with Dylan published in Rolling Stone magazine a useful source to cite alongside other scholarly works of literary criticism.

The WSU University Libraries' What Sources Should I Use? handout, as well as the other sub-tabs under the  Evaluating information  section of this guide (which is indeed the section you are currently viewing) offer further guidance on understanding and identifying scholarly resources, and comparing them against different criteria to evaluate if they will be of value to your research.  How many non-scholarly works (if any) you are at liberty to cite alongside scholarly ones is often a question to ask of your professor.  Some may not want you to cite any, whereas others may be ok with some non-scholarly works cited alongside scholarly ones.

Image:  Brett Woods. (2006, Jan. 6). Deep Thoughts. Retrieved from https://www.flickr.com/photos/brettanicus/87653641/. Used under the Creative Commons License.

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Ten Simple Rules for Writing a Literature Review

Marco pautasso.

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

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

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

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

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

Rule 1: Define a Topic and Audience

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

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

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

Rule 2: Search and Re-search the Literature

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

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

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

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

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

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

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

Rule 3: Take Notes While Reading

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

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

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

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

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

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

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

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

Rule 6: Be Critical and Consistent

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

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

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

Rule 7: Find a Logical Structure

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

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

Rule 8: Make Use of Feedback

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

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

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

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

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

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

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

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

Acknowledgments

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

Funding Statement

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

Crossroads between Big Data and entrepreneurship: current key trends

• Open access
• Published: 13 May 2024

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• Juan J. Lull 1 ,
• Roberto Cervelló-Royo 2 &
• José Luis Galdón   ORCID: orcid.org/0009-0004-2911-4308 1  

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Entrepreneurship is vital for economic growth and development, as it fosters innovation, creates jobs, and enhances competition and competitiveness. At the same time, in contemporary society, where the Internet has assumed the role of the primary instrument for both communication and commerce, effective utilisation of vast amounts of data has become imperative for businesses, especially in the entrepreneurial environment. To identify the main connections in two of the currently most trending concepts in business, we undertook a systematic literature review focusing on Big Data, entrepreneurship, and their interconnections in business management through 301 research documents. While numerous studies have already delved individually into Big Data and entrepreneurship, the interconnection between these concepts still has research potential. Our results reflect a growing interest in leading research on these topics, with specific leading authors and countries. Furthermore, we show and discuss a conceptual map consisting of five clusters, unveiling interesting connections such as the impact of blockchain on firms, the correlation between Big Data and firm performance, the role of data science, and the significance of Big Data analytics for operational performance. The article ends by examining how Big Data and entrepreneurship change the business landscape. While entrepreneurs use data for decision-making, innovation, and tailored customer experiences, there are lingering concerns such as data security and privacy. The future of business and innovation will depend, in part, on the crossroads between entrepreneurs and Big Data technologies.

Avoid common mistakes on your manuscript.

Introduction

Entrepreneurship is considered a universal tool for economic growth, job creation, and expanding economic opportunities for countries (Krysko, 2022 ). The relevance of entrepreneurship in the economy and society has been analysed in depth and has attracted the attention of academics, researchers and practitioners. For instance, Santos ( 2012 ) highlights that “entrepreneurship is having profound implications in the economic system: creating new industries, validating new business models, and allocating resources to neglected societal problems” (p.335).

Entrepreneurship has become a critical area of interdisciplinary education, focusing on value creation and the ability to assume high levels of risk and uncertainty (Obschonka, 2017 ). Tan et al. ( 2005 ) define entrepreneurship as “the process of attempting to make business profits by innovation in the face of risks” (p.357). These risks and the difficulties of being an entrepreneur are based on the need to efficiently manage many areas of knowledge, such as marketing, management, business strategies, and leadership (Bresciani et al., 2021 ). One of the concepts that can help mitigate these risks for entrepreneurs is the quantity and quality of available data, which is considered one of the most essential company assets (Albergaria & Chiappetta Jabbour, 2020 ; Kozjek et al., 2018 ). In this area, Guéneau et al. ( 2022 ) stress the importance of information and knowledge flow and a collaborative environment to make entrepreneurship foster entrepreneurial dynamics.

Along with entrepreneurship, the phenomenon of digitalisation, which has brought about a revolution and has had a positive impact on businesses, should also be considered (Yildirim & Erdil, 2024 ). Digital technology promotes the output of business production by reducing costs and improving efficiency and innovation (Zhang et al., 2022 ). Digitalisation has made the use of data essential for companies. This impact of data on business has been deeply analysed in the literature (Casson, 2005 ). It is even more critical in entrepreneurial environments, where information about the specific characteristics of any new business is not static and is often uncertain and insufficient (Eckhardt et al., 2018 ).

The capacity and availability of data have grown exponentially, coining the term Big Data (Sagiroglu & Sinanc, 2013 ), which refers to both the explosion of data and the tools to analyse vast amounts of data. In this line of thinking, many authors highlight the relevance of managing extensive, high-quality data to develop better business strategies and performance (Gaur et al., 2014 ; Scuotto et al., 2017 ). According to Sestino et al. ( 2020 ), Big Data plays a crucial role in Schumpeterian-level disruption, leading to the conversion of previously immovable and static information into dynamic and transferable resources. In this domain, the quality and breadth of data become a critical factor and, in many cases, the main path to success (Ranjan & Foropon, 2021 ). An excellent example of this can be found in the work of Du et al. ( 2023 ), which demonstrates how information extracted in a Big Data environment helps reduce companies’ operational risks and improve their performance.

Big Data can be understood as extracting information to better support decision-making processes and properly use massive amounts of data and knowledge (Jin et al., 2015 ; Staegemann et al., 2021 ). The core features of Big Data are Velocity, Volume and Variety. A vast amount of data (volume) that is generated with a high-speed rate (velocity) and is heterogeneous (variety) needs new visualisation, aggregation, normalisation, and storage tools that will let companies take advantage of massive amounts of data collected from their own companies, competitors, customers, etc. (Lull et al., 2022 ). According to Obschonka and Audretsch ( 2020 ), Big Data is gaining importance in broader research fields that are often considered foundational for research on entrepreneurship, such as management (George et al., 2014 ; Ransbotham et al., 2017 ), economics (Acemoglu & Restrepo, 2018 ; Brynjolfsson & Mcafee, 2014 , 2017; Brynjolfsson et al., 2017 ; Einav & Levin, 2014 ) and economic policy (Agrawal et al., 2018 , 2019 ). In this vein, authors have shown the relationship of the phenomenon of entrepreneurship with digitalisation (González-Padilla et al., 2023 ; Lull et al., 2022 ), with social media (Olanrewaju et al., 2020 ) and with the internationalisation of firms (Baier-Fuentes et al., 2019 ). Likewise, this data revolution is also disrupting application fields associated with entrepreneurship, including innovation, industry, and business management (Cockburn et al., 2018 ). In the words of Obschonka and Audretsch ( 2020 ), “AI and Big Data might not only enrich and transform future entrepreneurship research, but they might also transform at least some aspects of the actual real-world phenomena that entrepreneurship researchers usually study when they try to understand determinants and effects of the entrepreneurial process” (p.532). Furthermore, Big Data has been recognised as creating new opportunities for entrepreneurship and sustainable development, especially in the context of social entrepreneurship (Zulkefly et al., 2021 ). The emergence of Big Data offers organisations unprecedented opportunities to gain and maintain a competitive advantage, which is crucial in the entrepreneurial landscape (Wiener et al., 2020 ).

A recent example of the use of Big Data for entrepreneurs is the case of ChatGPT, a massive language model chatbot developed by OpenAI that opened to the public on November 30, 2022 (Gordijn & Have, 2023 ). The model is trained on a massive volume of text data (Big Data) and can learn and give users appropriate responses. How an entrepreneur can use ChatGPT to their advantage is a question that can be posed to chatbots. In the bot’s own words, “ChatGPT is useful for entrepreneurs in many ways because it can do a wide range of tasks and give them a lot of information and ideas”. More specifically, ChatGPT provides several support options for entrepreneurs, such as market research, planning for business, customer service assistance, production of business material or training and development programs (Rahaman et al., 2023 ).

Big Data and its contribution to many aspects of business development have yet to be thoroughly examined concerning Big Data and entrepreneurship (Akhtar et al., 2019 ). To address this research gap, we conducted a systematic literature review on the concepts of Big Data, entrepreneurship, and their connections in the management field. The bibliometric review is a commonly used method for recognising keywords, their relationship to each other and the citations of the articles published within a defined timeframe (Zhong et al., 2015 , 2016 ).

As mentioned above, there are numerous studies that have individually delved into Big Data and entrepreneurship, but the interconnection between these concepts still has plenty of potential for further study. Therefore, this paper aims to give an overview of the past, present and future research directions of the concepts of Big Data and entrepreneurship by performing a bibliometric analysis systematically on the research articles that explore both topics. The main value of this study is to conduct an in-depth bibliometric study that provides interesting information on the scientific production (quantity, quality and impact) on Big Data and entrepreneurship (across different journals, authors and countries) that will serve as a theoretical basis for future researchers in the formulation of hypotheses and variables for the identification of quantitative models.

To achieve this purpose, the paper is organised as follows. The next section provides a theoretical background of Big Data, entrepreneurship, and the connection between the two. Subsequently, the research methodology adopted for the systematic literature review is shown. The study is based on 470 articles from the Web of Science (WoS) and 168 articles from Scopus, with a list of 301 articles after manual screening. Afterwards, we illustrate the significant findings of the review, analyse research topics, data sources, and data collection methods, and provide clear reporting and visualisation of the main results. The importance of the findings is then discussed. Finally, we highlight significant conclusions.

Theoretical background

In 2021, the overall amount of data generated worldwide was estimated to be around 79 zettabytes; by 2025, this amount is expected to double. In this sense, managing efficiently and securely this volume of data has become a real challenge for any type of organisation, such as businesses, scientific research, the health sector, architecture and engineering, among others, which use data regularly.

Therefore, the collection of massive and diverse data sets requiring advanced techniques and technologies to allow the capture, storage, distribution, management, and analysis of information, can be conceptualised as Big Data (Gandomi & Haider, 2015 ). Although the concept of Big Data may still be ambiguous and with a lack of consensus among researchers, after a deep study of existing notions of this term, the definition of Big Data can be focused on the three most relevant factors according to its appearance in academic and business literature: Information, Technologies and Business Impact.

The importance of adequately using information in companies is a critical matter, even more so in the last decades, when organisations manage millions of bytes of information on their customers, suppliers, operations, or industrial machines. Information management is critical, and technologies that enable storing and processing large volumes of data through powerful computational processing are relevant from a Big Data context. In this sense, the Big Data phenomenon is driven by technological advances and the exponentially increasing number of devices connected to the Internet.

Even though the concept of Big Data has been explored from the three points of view previously mentioned, there are many more studies based on the informational and technical aspects than on the business impact. The explosion of Big Data has transformed how organisations manage and effectively compete (Gangwar, 2018 ). In this vein, Big Data can be understood as a revolution for decision-making processes, increasing organisational performance and generating new competitive advantages (Davenport, 2014 ; Raguseo, 2018 ). In the same direction, the use of Big Data can positively impact the management of organisations in terms of improving customer service, identifying new products and services, and enhancing new strategic directions (Gangwar, 2018 ). In other words, “the new business challenges in the B2B sector are determined by connected ecosystems, where data-driven decision-making is crucial for successful strategies” (Saura et al., 2021 , p.161).

Further specifying how the efficient management of the Big Data environment can help companies improve their business, many authors have stated in which specific part of the business processes the use of Big Data techniques can be efficient. Lee ( 2017 ), for instance, establishes six technical and managerial processes in which Big Data development positively impacts management. Șerban ( 2017 ) analyses how companies need to manage Big Data to their business advantage and how it impacts sustainability to grow and profit while benefiting society. Other authors specify the positive impact of Big Data on the improvement of the company in financial terms, such as Begenau et al. ( 2018 ), who argue that the efficient use of Big Data analysis could improve investors’ forecasts and reduce equity uncertainty, enabling large firms to grow larger. In the same vein, Hasan et al. ( 2020 ) show how Big Data influences different business sectors, more specifically in the financial sector, and Raguseo et al. ( 2020 ) provide empirical evidence of the positive business impact of Big Data analytics on firm profitability. It is precisely in these terms of improving business performance that entrepreneurship acquires particular relevance (Faisha et al., 2024 ).

Entrepreneurship has been deeply analysed in the last decades, and several papers have defined and highlighted the importance of entrepreneurship (Minniti & Lévesque, 2010 ; Chaston & Scott, 2012 ; Hameed & Irfan, 2019 ; Vladasel et al., 2021 ). Concretising the importance of entrepreneurship, many authors have furthered the hypothesis that an entrepreneurial environment can improve business performance. Wiklund and Shepherd ( 2005 ) suggest that an entrepreneurial orientation can positively impact small business performance. Investigating the relationship between entrepreneurship, access to capital, and environmental dynamism, Georgellis et al. ( 2000 ) investigate how entrepreneurial behaviour, characterised by innovation and the willingness to take risks, could positively affect business performance. Moreover, they propose entrepreneurship as one of the three main competencies that predict business performance. Similarly, Haltiwanger ( 2022 ) discusses the impact of entrepreneurship on business performance, connecting entrepreneurship with the launch of start-ups. Finally, with a very similar point of view, Teruel-Sánchez et al. ( 2021 ) highlight identifying factors that positively influence business performance, one of the most critical entrepreneurial capacities.

In the same way we already mentioned, something similar happens in entrepreneurship due to the wide range of possible orientations to the concept of Big Data. In this sense, we can find in the recent literature connections between entrepreneurship and digitalisation (González-Padilla et al., 2023 ), social media (Olanrewaju et al., 2020 ; Wilk et al., 2021 ), internationalisation of firms (Baier-Fuentes et al., 2019), ecological sustainability (Zeng, 2018 ) or pro-activeness, risk-taking and innovativeness (Davis et al., 1991 ; Knight, 2000 ). These findings suggest that Big Data and Entrepreneurship are mutually influenced and connected but poorly explored as a whole. This article will fill this gap to show an overall picture of the crossroads between Big Data and Entrepreneurship. In the next section, a methodology of the work is provided.

Methodology

We conducted a Systematic Literature Review following the PRISMA approach to assess the existing link between Big Data and entrepreneurship, as well as the different interactions (Page et al., 2021 ). Academic articles indexed in the Web of Science (WoS) and Scopus databases were selected and processed. Afterwards, we observed different aspects of knowledge we could extract from the available information.

Data sampling

The most comprehensive comparison between WoS and Scopus was performed by Vieira and Gomes in 2009 (Vieira & Gomes, 2009 ). They found that WoS was a more curated repository of academic articles. It was also more focused on English language journals. On the other hand, Scopus was found to have articles with fewer citations and a higher number of journals in specific fields, such as Health. Scopus was also found to be richer in terms of the languages of the journals included in the database.

More recent studies have been conducted that partially confirm Vieiria’s statements (Singh et al., 2021 ; Waltman, 2016 ), which is essential since the study by Vieira and Gomes could be deemed as old, especially considering that the Scopus database began in 2004, only five years before Vieira’s study was published.

We decided to include academic articles from both WoS and Scopus in our literature review by searching for the terms Big Data and entrepreneurship. Initially, we performed a search on WoS that contained both the topics “Big Data” and “entrepreneur*” (for the last topic, the asterisk means that all words that started with entrepreneur, such as entrepreneurial or entrepreneurship, were included). A list was created in WoS with the results, containing 472 scientific papers.

Another search was performed in Scopus. All the articles that included both “Big Data” and “entrepreneur*” as keywords were selected. A list of the 168 resulting papers was created. All searches, as well as the final compilation of the list, were conducted in May 2023.

Data processing

The whole process of selecting the final papers appears in Fig.  1 . The lists were merged into a spreadsheet document with a row per article. The information included the title, the abstract and the keywords, among many other fields. After duplicates were removed, 620 papers remained. Two authors individually assessed whether each article addressed both Big Data and entrepreneurship, voting on whether the article was relevant and dealt with the topics. The possible voting possibilities were three: the article should be included, the article should not be included, and it needed to be clarified if it should be included. In order to vote, the title, abstract, and keywords of each article were reviewed.

Selection process of articles for the review

After each author reviewed the papers and classified them, the ones that were considered as suitable by both researchers were directly introduced in the final list (275 articles), while those deemed as unsuitable by both were discarded (137 articles). Finally, the ones classified differently by the authors were jointly reviewed by both and a final vote was cast, either selecting the paper or not (208 articles had been seen as suitable by only one of the authors or that generated doubts about their classification). A final list with 382 articles was accepted.

The initial WoS list with 472 articles was reduced, removing the unaccepted papers. Those from Scopus that had been selected were added to the list. Some of the articles were not available at WoS, specifically 81 papers. However, the information about each journal at WoS was more extensive, including Keywords Plus (Garfield & Sher, 1993 )–automatically generated keywords based on the references that a journal cites–and the information was also more complete in the WoS database. Furthermore, when the authors randomly searched for articles missing in WoS, they found that some had been retracted. Thus, the list of 301 papers was used as the basis for the literature review. The process of the selection of publications can be seen in Fig.  1 .

The final list was exported from WoS and then introduced into the Bibliometrix software (Aria & Cucurullo, 2017 ), and the general information can be seen in Table  1 . The 301 articles presented no missing information about the title, authors, journals, publication year, and total citations. Less than 5% of articles had no abstract (specifically, eight papers), no corresponding author (nine papers) or no cited references (five papers). 19% of papers did not include the DOI, 20% missed the keywords, and 34% missed Keywords Plus.

The most relevant articles, sorted by the number of global and local citations, were examined in depth according to their purpose and main concepts. Precisely, the formula to extract the relevance index and to weigh the importance of the documents was:

where LC is the number of citations received among the selected documents; GC is the number of citations received in general; YSP accounts for the number of years since the document was published.

In this way, both local and global citations were taken into account. The effect of a higher number of citations because of the time a document had been published was also countered in the formula.

General information

The timespan was from 2013 until May 2023, with 224 document sources (e.g., journal, book, proceedings). The annual growth rate during those years was 27.1%. The growth for each year may be seen in Fig.  2 . Average citations per document were 12.8%. The rest of the relevant general information about the dataset may be seen in Table  1 . In Table  2 , the top ten journals in terms of published papers are displayed. The journal with the highest number of publications about Big Data and entrepreneurship was Technological Forecasting and Social Change, with 11 articles, followed by the Journal of Business Research and Mobile Information Systems, with seven articles each. Four journals had five articles published each. Mathematical Problems in Engineering had four articles. Six journals had three articles. Thirty-four journals had two articles, and 193 accounted for one article each.

Documents published per year

Most relevant paper. In-depth analysis

The top 30 most relevant documents, as defined in the Methodology section, are presented in Table  3 , with in-depth information about their purpose and main concepts. As an example, Ciampi et al. ( 2021 ) was the research piece with the highest relevance (specifically, the research piece had received more than 100 global citations and a total of 6 local citations since its publication).

Impact and citations across journals

The Technological Forecasting and Social Change journal had the highest h-index, with a value of 11. However, it only had 213 local citations, below the Journal of Business Research (h-index 4), which had the highest number of local citations, 344, and Strategic Management Journal with 242 citations. The number of citations per paper was as follows: 13 had at least 100 local citations; 19 had between 50 and 100 citations; 39 had between 25 and 50; 6334 sources had less than 25 citations. The ten most locally cited sources can be seen in Table  4 .

Relevant authors and their countries

Table  5 shows the top ten most relevant authors according to the number of articles and fractionalised articles (i.e., divided by the number of authors per document). As can be seen in the table, Dr Martin Obschonka was the author with the highest number of local citations and the one with the highest fractionalised citations among the authors with three articles. In general, 91 authors were cited at least once, while 648 received no citations.

Regarding authors’ countries, the ones with the highest production over time, as can be seen in Fig.  3 ; Table  6 , were China (with 173 articles), the U.S.A (65 articles), Italy (57 articles), the United Kingdom (46 articles), India (20 articles) and Russia (20 articles). The total number of citations per country follows a different pattern: The most cited country is Italy, with 582 citations, followed by the United Kingdom, with 437 citations and the U.S.A., with 428 citations. China was the sixth country, with 226 citations. The fourth and fifth positions were Cyprus and Australia, with 414 and 240 citations, respectively.

Top 5 highest publishing countries, accumulated publications

Also, the corresponding authors’ countries were observed. Even though the information had a high overlap with the previous data about countries, this gave us additional insights. Specifically, the corresponding authors’ countries were, in descendent order of the number of documents: China, Italy, the U.S.A, the U.K., Australia, Russia and Germany, as seen in Fig.  4 . Most importantly, we know the number of publications with at least one co-author from another country. Thus, we can state how much collaboration with other countries there was for each country where the corresponding author came from. This is shown in Table  7 . The ratio of documents from multiple countries compared to one country per document showed a very different result. In the top 10 corresponding author’s countries, the countries with the highest multiple country documents were, subsequently, France, Australia, the United Kingdom and India, with at least half the publications coming from different countries. Then came, also ordered from higher to lower collaboration across countries, Italy, Germany, Russia, the USA, Spain, and finally China, with around 11% publications that were collaborations between countries.

Corresponding authors’ countries. SCP: Single Country Publication. MCP: Multiple Country Publication

Interestingly, the country with the highest number of average citations per document was Cyprus (with 420 citations), since Dr. Spyros Makridakis, who is a Cypriot, was the author with the highest (global) citation figure (see Table  8 ).

An overview of the most relevant authors

As already mentioned, Obschonka was the author with the highest number of articles and local citations. The article that was published first (Obschonka, 2017 ) versed on how psychological Big Data (e.g., behavioural data based on millions of subjects) let researchers put new questions about entrepreneurship, e.g., regional variations on personality traits that lead to a higher or lower entrepreneurial mindset. The second piece of research (Obschonka et al., 2020 ) was practical, applying Machine Learning through publicly available social media Big Data to study how personality traits affected U.S. entrepreneurship regionally. The third article (Obschonka & Audretsch, 2020 ) may be seen as an introduction to a Special Issue where many questions are proposed about how Big Data may impact entrepreneurship research based on readily available conceptual work by different researchers.

Makridakis had the highest number of citations from publications outside our database (i.e., global citations). Compared to Obschonka’s aggregated global 121 citations, Makridakis received more than 400 citations for one single piece of research (Makridakis, 2017 ). We could thus state that Makridakis’s work is generally well-established. Also, the topic is broader since it reviews how Artificial Intelligence and Big Data may impact society and firms shortly. This broader perspective would explain why the author’s ratio of local citations over global citations is lower than Obschonka’s.

Conceptual structure: factorial analysis of keywords

A Multiple Component Analysis was performed on the keywords defined by the authors. The aim of this type of Factorial Analysis is to show the relationship between words in the selected documents by finding dimensions that separate keywords or bring them closer together depending on their proximity. The more articles with two common keywords exist, the nearer they will appear. This can be represented graphically. Specifically, the representation for our case can be seen in Fig.  5 . Five clusters that show different fields have been identified. Even though the clusters are not clear cut, they mainly include (1) the use of Big Data by academics to help future entrepreneurs find business opportunities that may not be covered at the moment; (2) the optimisation of logistics processes; (3) social applications arising from new opportunities offered by data, such as open data; (4) a cluster with Big Data as a source for collaborative work; finally, (5) there is also a body of research that focuses on novel business models centred on Big Data that entrepreneurs can exploit.

Conceptual structure map with author-defined keywords

Some documents were representative of the different clusters. Specifically, the article with the most citations in cluster 1 was Frizzo-Barker J ( 2020 ), Int. J. Inform. Manage. (Frizzo-Barker et al., 2020 ) with 166 citations. It consisted of a Systematic Review of the implications of blockchain in the business landscape. The papers that contributed the most in cluster 1 were Huang XM, (2022), Front. Psychol.; Zeng J, (2019), Manage. Decis.; Wang Y, (2023), J. Enterp. Inf. Manag.; Wang TD, (2022), Front. Psychol.; Ciampi F, (2021), J. Bus. Res.; and Lin CC, ( 2019 ), J. Bus. Res.

Cluster 2, which included keywords such as firm performance, dynamic capabilities, data analytics, decision-making, and entrepreneurial orientation, was represented by one single document, Akhtar P, ( 2019 ), Brit. J. Manage.

Regarding citations, cluster 3 -comprised of keywords such as Data Science, Information Technology, Future and Framework- was led by Dubey et al. ( 2020 ). This document was among the ones that contributed the most to the cluster, along with Vitari C, (2020), Int. J. Prod. Res.; and Kummitha RKR, (2019), Technol. Forecast. Soc. Finally, clusters 4 and 5 did not have representative documents.

Conceptual structure: strategic themes

A map with the most strategic themes in the field is shown in Fig.  6 . This map was created by automatically classifying author keywords, exposing the main themes, and classifying them in a quadrant with four regions (Cobo et al., 2011 ).

Thematic map

Basic themes mainly included the most significant cluster, with the theme around Big Data, entrepreneurship, Artificial Intelligence, and innovation as the most representative keywords. Other basic themes included the green cluster around innovation performance, the pink cluster with text mining and SMEs, and two less dense clusters (the purple cluster about intellectual capital and the lilac one about environmental uncertainty).

Motor themes included a red cluster with digital transformation, digitalisation, collaboration, digital marketing, digital technologies, etc.; a grey cluster with the keywords ICT, smart cities, entrepreneurial ecosystems and social capital, among others; a brown cluster with the keywords entrepreneurial orientation, Big Data analytics capabilities, digital technology, dynamic capabilities, etc.; a pink cluster with the keywords education, research, supply chain management and additive manufacturing; a blue cluster with data mining, analytics, case study, data analytics, open innovation, sentiment analysis, etc.; and an aquamarine cluster that includes digital economy and digital platforms.

The niche themes included a red cluster with Big Data analytics capability, contingency theory, financial performance, market performance and resource-based view; a blue one with international entrepreneurship, Business Intelligence, international business and international management; a dark green cluster with college students, Big Data era and social network.

In the middle, between the motor and the niche themes, with the highest level of relevance, there was a pale green cluster with personal data, privacy, quantified self and surveillance.

Finally, among the emerging or declining themes quadrant, the most representative cluster was the one that included the themes of innovation and entrepreneurship combined, which showed a decline in interest over time. A pale purple cluster represented a highly relevant topic, fuzzy set Qualitative Comparative Analysis, an emerging theme during the last few years.

In the ever-evolving business and technology landscape, the interplay between Big Data and entrepreneurship has become a focal point of discussion and exploration (Obschonka & Audretsch, 2020 ; Prüfer & Prüfer, 2020 ; Makridakis, 2017 ). The integration of Big Data analytics into entrepreneurial ventures has ushered in a new era of opportunities and challenges. This discussion delves into the intricate relationship between Big Data and entrepreneurship, as pointed out by the present review of the existing literature. We will examine how each influences the other and the broader implications for the business ecosystem.

One of the most prominent impacts of Big Data on entrepreneurship is its role as a catalyst for innovation, fostering a culture of continuous improvement and adaptation within entrepreneurial ventures. In this sense, Big Data can be seen as part of the organisational dynamic capabilities (Lin & Kunnathur, 2019 ). Specifically, entrepreneurs can leverage Big Data analytics to identify gaps in the market, emerging trends and operational performance opportunities and unmet consumer needs (Ciampi et al., 2021 ; Dubey et al., 2020 ; Gnizy, 2019 ). This, in turn, facilitates the development of innovative products and services that have the potential to disrupt existing markets, through open innovation among others (Saura et al., 2023 ). The agility to adapt and innovate becomes a defining factor for entrepreneurial success in an environment driven by Big Data (Ranjan & Foropon, 2021 ).

Another key element in the Big Data environment is detecting entrepreneurial traits. As such, some research papers focused on detecting these traits through Big Data (Obschonka et al., 2020 ; von Bloh et al., 2020 ). In both referenced studies, vast information in social media and news was the platform to detect differences in regional entrepreneurial qualities, though they were not conclusive in the case of von Bloh et al. ( 2020 ). However, Obschonka et al. ( 2020 ) were able to find relationships between the personality estimates obtained through 1.5 billion tweets and the entrepreneurial personality profiles. This could even lead us to deduct information on entrepreneurial traits from Big Data that could be as potent as if explored through questionnaires.

The vast amount of data generated and collected enables entrepreneurs to make informed, data-driven decisions, thus transforming the decision-making processes (Trabucchi & Buganza, 2019 ). This not only minimises risks but also enhances the precision of strategic planning. Entrepreneurs can harness insights from customer behaviour, market trends, and competitor analysis to pivot and adapt their business strategies dynamically.

Entrepreneurial ventures thrive when they understand their customers’ needs and preferences. Big Data plays a pivotal role in this aspect by providing a comprehensive view of customer behaviour and preferences (Mariani & Nambisan, 2021 ). Through advanced analytics, entrepreneurs can tailor their products and services to meet specific customer demands, leading to increased customer satisfaction and loyalty. The ability to personalise offerings based on data insights is a significant competitive advantage in today’s dynamic business landscape.

While the integration of Big Data offers immense potential for entrepreneurs, it comes with its set of challenges, particularly in the realm of data security and privacy. Entrepreneurs need to navigate the complexities of handling sensitive customer information responsibly. Data breaches and privacy concerns can significantly impact the reputation of an entrepreneurial venture. There are examples that show privacy issues when governments use AI strategies, that are akin to the concerns we are currently discussing (Saura et al., 2022 ). Striking the right balance between utilising Big Data for business insights and safeguarding customer privacy is an ongoing challenge that entrepreneurs must address. The concern about security and privacy has not been a focal point in the research pieces we studied. Thus, we propose this as an interesting future research guideline. In fact, many entrepreneurs may unfairly take advantage of opportunities based on irresponsible management of personal data, given that legislation usually moves slower than technological advances.

Conversely, entrepreneurship also influences the development and evolution of Big Data technologies. The demand for innovative solutions prompts entrepreneurs to invest in creating tools and platforms that facilitate the collection, storage, and analysis of large datasets. This reciprocal relationship between entrepreneurship and Big Data technologies contributes to a cycle of continuous improvement and evolution, with entrepreneurs driving the demand for more sophisticated data-driven tools. In the literature, this is not a topic that has taken traction since big companies or communities are the ones who easily attract the attention of both media and academia.

The intersection of Big Data and entrepreneurship fosters collaborative ecosystems where knowledge sharing becomes a cornerstone of success. One interesting paper (Elia et al., 2020 ) proposes this, based on a real case of a multi-national company that established a Virtual Brand Community. Entrepreneurs can benefit from shared insights, industry benchmarks, and best practices derived from Big Data analytics. This collaborative spirit creates a supportive environment where emerging entrepreneurs can learn from the experiences of others and adapt their strategies accordingly, ultimately contributing to the overall growth of the entrepreneurial ecosystem.

To sum up, the symbiotic relationship between Big Data and entrepreneurship is reshaping the business landscape. The infusion of data-driven decision-making, innovation, and personalised customer experiences empowers entrepreneurs to navigate an increasingly complex and competitive market. However, challenges such as data security and privacy underscore the need for responsible utilisation of Big Data. As entrepreneurs continue to shape and be shaped by Big Data technologies, the ongoing dialogue between these two realms will undoubtedly define the future of business and innovation.

Conclusions

This study showed a review that identified 301 academic contributions that target both Big Data and entrepreneurship. We then analysed those documents in depth and individually studied the most relevant ones, showing their main contributions and purpose. Systematic bibliometric tools were applied to extract knowledge about the research corpus.

We discovered that some authors stand out, such as Obschonka and Makridakis, with Obschonka’s influence being more locally focused and Makridakis earning the highest global citations. Country-wise, we found that a global competition is apparent, particularly between two leading economies, China and the United States of America, which have the highest number of publications. We found that the UK leads international collaborations across countries, and Italian and British authors receive the most citations.

Theoretical implications

The results of the current study carry the following theoretical implications. The conceptual structure showed the most representative previous and basic research themes, focused on Big Data, innovation, Artificial Intelligence, and entrepreneurship, representing a pivotal role in entrepreneurial endeavours with current examples such as ChatGPT, which embodies the synergy of these concepts. We detected that certain scholars draw a clear distinction between social and economic impacts, considering them as entirely separate entities. We found that the innovation and entrepreneurship theme showed an apparent decline, particularly in 2016–2020, while fuzzy-set Qualitative Comparative Analysis appeared as an emerging theme. Thus, at a theoretical level, forthcoming research can employ the methodology outlined in this study as a foundation for fresh concepts in knowledge generation and extraction of insights from the confluence of topics such as Big Data, innovation and Artificial Intelligence with entrepreneurship.

Furthermore, the themes uncovered in this study can be translated into operationalized variables and investigated using quantitative models aiming for statistical significance. Therefore, while this study is mainly exploratory, it lays the groundwork for future quantitative research on Big Data and entrepreneurship. Our focus was not hypothesis testing, but rather the identification of variables to formulate future empirical hypotheses. Moreover, the issues delineated in this study can serve as a reference point for future research efforts, which may involve building statistical models and substantiating theoretical variables related to Big Data and entrepreneurship. With these variables at their disposal, fellow researchers can leverage the insights gleaned from this study to formulate research questions and objectives, corroborate hypotheses, or design questionnaires.

Finally, an interesting gap was found. Specifically, how entrepreneurship affects Big Data technically is a field that has not been explored. This field has an enormous interest for academics since Big Data advances because of innovators and entrepreneurs that need new tools that may analyse more unstructured data at a higher rate from different sources.

Practical implications

The findings of this study are highly practical. Big Data fosters companies’ competitiveness, but it requires deep strategic changes. Businesses need an entrepreneurial orientation so they may take advantage of Big Data capabilities. There are also new opportunities for entrepreneurs that they may detect through Big Data. Furthermore, Big Data may be used as a source of competitive advantage and part of the business model.

There is also wide evidence that Big Data is effectively employed to analyse the most sought-afer entrepreneurial carachteristics. Universities and Business Schools are already leveraging this to shape their curriculum, ensuring the education of entrepreneurs is effective. This is particularly crucial for educational institutions that are slow to adapt their teaching content, as proficiency in Big Data might soon become a necessity, potentially posing a threat to these institutions.

In a more general vein, the findings provide valuable insights based on the conceptual map. The rising importance of Big Data analytics as a prominent niche theme underscores the increasing significance of data analytics. This emphasises the point that Big Data analytics empowers companies and entrepreneurs to enhance their understanding of information for better decision-making. A notable recurring theme focused on social and sustainable entrepreneurship was detected, indicating its well-established and integral position within the research corpus. This type of entrepreneurship directly impacts society in diverse ways, including areas such as smart cities, urban environments, and technology (Han, 2024 ). In addition, the results offer valuable insights into the optimal structuring and promotion of information and development, support for entrepreneurial initiatives, the organization and promotion of ideas, the structuring and organization of teams, the role of sustainability and technology within entrepreneurship. In summary, the results show valuable insights on the relationship between Big Data and entrepreneurial activity that both show new trends and how society may take advantage of the existing literature.

Limitations and future research

Some limitations are present in this study. For instance, a manual selection had to be made from the 640 documents that passed the search criteria, possibly leading to bias. This was minimised by a blinded selection by two researchers and a subsequent examination of the documents that had not reached an initial consensus. In addition, we found an inherent problem in the corpus: As already hinted at, there appears to be a race for the highest number of publications, creating a prevalence of superficial exploration rather than substantial advances, as suggested by the large number of publications without any citations. This also coincides with the surge in publications during the last few years, as noted by some researchers (Goel & Faria, 2007 ; Ioannidis et al., 2023 ). Related to the previous limitation, there are authors who consider that tools such as ChatGPT will soon provide extensive literature reviews and propose research gaps to be covered (Rana, 2023 ).

The study suggests that future research should delve deeper into exploring the interplay between entrepreneurship and other disruptive technologies like Artificial Intelligence (AI), Business Analytics, Industry 4.0, and digitalisation. Another field that should be studied is the privacy concerns about Big Data related to entrepreneurship. As previously commented, we detected that certain scholars draw a clear distinction between social and economic impacts, considering them as entirely separate entities. However, an alternative perspective acknowledges that economic impact can be encompassed within the broader social impact category due to its alignment with the mission and overall influence of business. Future research in this domain could beneficially extend its focus beyond discerning the distinctions and similarities between economic and social impacts, aiming to explore a holistic perspective encompassing both dimensions. Finally, this study represents an exploratory inquiry that generated qualitative findings. Consequently, there is a need for subsequent quantitative research to rigorously test the relations unearthed herein.

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Lull, J.J., Cervelló-Royo, R. & Galdón, J.L. Crossroads between Big Data and entrepreneurship: current key trends. Int Entrep Manag J (2024). https://doi.org/10.1007/s11365-024-00986-2

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Jimmie Johnson to attempt his own version of Indy 500 & NASCAR doubleheader

FILE - Jimmie Johnson stands on pit lane during practice for the Indianapolis 500 auto race at Indianapolis Motor Speedway, Tuesday, May 17, 2022, in Indianapolis. Johnson will attempt his own version of “The Double” when he becomes the first driver to be part of the Indianapolis 500 broadcast team hours before he competes in NASCAR’s Coca-Cola 600. (AP Photo/Darron Cummings, File)

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INDIANAPOLIS (AP) — Jimmie Johnson will attempt his own version of “The Double” when he becomes the first driver to be part of the Indianapolis 500 broadcast team hours before he competes in NASCAR’s Coca-Cola 600.

Johnson, who ran the Indy 500 in 2022, was part of NBC Sports’ broadcast booth in 2021 when he ran only the road and street courses on IndyCar’s schedule. He added ovals in his second and final season in American open-wheel racing.

NBC said Tuesday that Johnson will be part of the broadcast team at Indianapolis Motor Speedway for the May 26 race. It will be the first of recurring analyst opportunities for Johnson with the network this year.

“To have the opportunity to experience ‘The Greatest Spectacle in Racing’ once again is such an honor,” Johnson said. “I was part of the NBC broadcast team in 2021 and it just fueled the fire I needed to make my childhood dream of racing in the Indianapolis 500 one day a reality. Competing in this race as a driver was a chance of a lifetime, so to be able to experience the pageantry again is just so special.”

Johnson will fly to Charlotte, North Carolina, after the Indy 500 to compete in NASCAR’s longest race of the year. The Hall of Famer won the Coca-Cola 600 four times as a full-time NASCAR driver. Johnson now races a partial schedule as co-owner of Legacy Motor Club.

For NBC, Johnson will also be an analyst later this season for NASCAR races at Daytona and Talladega, as well as races he’s schedule to compete in.

“Any time you can add one of the greatest drivers of all time and an icon of the sport, you jump at the opportunity,” said Sam Flood, lead producer for NBC Sports’ motorsports coverage. “We are thrilled to be working with Jimmie and adding his unique perspective on every race he covers, as well as having him become the first person ever to do the ‘Double’ — history awaits.”

Kyle Larson will become the fifth driver to attempt to complete both the Indy 500 and the Coca-Cola 600 on the same day. Tony Stewart in 2001 became the only driver to complete all 1,100-miles of racing.

AP Motorsports: https://apnews.com/hub/auto-racing