Journal Impact Factor: What It Is and Why It Matters

Introduction

If you have spent any time in academic circles, you have heard the phrase “impact factor” bandied about as a shorthand for journal quality. Submit to a journal with a high impact factor and your work is prestigious; submit to one with a low impact factor and it is not. Or so the folklore goes. The reality is more complicated — and more interesting — than the folklore. The journal impact factor is a specific metric, calculated in a specific way, with specific uses and specific abuses. Understanding it properly is essential for any scholar who needs to choose where to publish, evaluate where to submit, or read citation statistics critically.

This guide explains what the journal impact factor actually measures, how it is calculated, why it matters (and when it does not), and which alternative metrics — CiteScore, SCImago Journal Rank, h5-index, SNIP, Eigenfactor — have emerged to compensate for its limitations. If you are choosing where to publish your first paper, see our first-paper publishing guide and our journal selection guide. For hands-on help, our publication support service covers journal shortlisting with a side-by-side metric comparison.

What Is Journal Impact Factor?

The journal impact factor (IF or JIF) is a citation-based metric that measures the average number of citations received in a given year by articles published in a journal during the two preceding years. It was developed by Eugene Garfield, the founder of the Institute for Scientific Information (ISI), in the early 1960s and is now published annually in the Journal Citation Reports (JCR) by Clarivate Analytics, the successor organisation to ISI.

The IF was originally designed as a tool for librarians to decide which journals to subscribe to. It was never intended as a measure of the quality of individual articles or authors. Over time, however, it became widely used (and widely misused) as a proxy for research quality, journal prestige, and even individual researcher merit. The 2013 San Francisco Declaration on Research Assessment (DORA), now signed by more than 2,400 organisations and 18,000 individuals, was a coordinated attempt to push back against this misuse.

Today, the impact factor is reported for roughly 12,000 journals indexed in the Science Citation Index Expanded (SCIE) and 3,000 journals in the Social Sciences Citation Index (SSCI). Arts and humanities journals are largely absent from the JCR — one of the metric’s most visible limitations.

How Impact Factor Is Calculated

The impact factor for a given year Y is calculated as:

IF(Y) = (citations in year Y to articles published in Y−1 and Y−2) ÷ (number of “citable” articles published in Y−1 and Y−2)

In other words, the numerator counts how many times articles published in the previous two years were cited during the current year; the denominator counts how many “citable” items (research articles and reviews) were published in the previous two years. The division yields the average citation count per article.

Several features of this calculation are worth noting. First, the IF uses a two-year citation window — which favours fast-moving fields like molecular biology and disadvantages slower-moving fields like mathematics, where citations often take five or more years to accumulate. Second, the denominator counts only “citable items” (research articles and reviews), but the numerator counts citations to all items published in the journal, including editorials, letters, and news pieces that are not counted in the denominator. This asymmetry inflates the IF for journals that publish heavily cited front-matter. Third, the IF is a journal-level mean — it tells you nothing about the distribution of citations across articles. A small minority of highly cited papers can carry the IF for an entire journal.

The Math Behind IF: A Worked Example

To see how the calculation works in practice, consider a hypothetical journal that published 100 research articles and reviews in 2023 and 120 in 2024. In 2025, those 220 articles collectively received 660 citations. The 2025 impact factor for this journal is:

IF(2025) = 660 ÷ 220 = 3.00

So a 2025 impact factor of 3.00 means that, on average, each citable article published in 2023 or 2024 was cited three times in 2025. The same calculation applies to every journal indexed in the JCR. The 2024 JCR release covers citations in 2024 to articles published in 2022 and 2023.

The skewness of citation distributions matters enormously. Studies by Per Seglen (1992) and others have shown that for most journals, the top 20% of articles receive around 80% of the citations — a Pareto-like distribution. The IF, as a journal-level mean, hides this skew. Two journals with identical IFs of 3.00 may have very different underlying citation patterns: one might be uniformly cited at around 3 citations per article; the other might have 80% of articles with 0–1 citations and 20% with 10–15 citations.

Why Impact Factor Matters (and Why It Is Misused)

The journal impact factor matters for three legitimate reasons. First, it provides a rough comparison of journals within the same discipline — useful for librarians making subscription decisions and for authors shortlisting publication venues. Second, it correlates with downstream citation counts: papers in higher-IF journals tend to receive more citations, partly because of the prestige signal and partly because of wider circulation. Third, it is widely recognised by hiring committees, grant panels, and tenure boards — a fact of academic life even for scholars who disagree with it.

It is misused when it is treated as a measure of individual article quality or researcher merit. The most cited paper in a journal may be an order of magnitude more cited than the average; a paper published in Nature (IF ≈ 50) with 0 citations is not more impactful than a paper in a specialist journal (IF ≈ 2) with 50 citations. Yet academic reward systems often treat the former as the better paper. DORA and the Leiden Manifesto (Hicks et al., 2015) both warn against this misuse.

The IF is also misused when it is compared across disciplines. A 2024 impact factor of 5.00 is exceptional in mathematics (where the field median is around 0.9), average in chemistry (median ~4.5), and below average in immunology (median ~5.5). Cross-disciplinary IF comparisons are meaningless without field normalisation. Always compare IFs within a discipline, and consult the JCR’s subject category rankings rather than the absolute number.

The impact factor is a journal-level metric that was designed to help librarians choose subscriptions. Using it to evaluate individual researchers or articles is like judging a person’s height by the average height of their city.

Alternatives to Impact Factor

Several alternative metrics have emerged to address the IF’s limitations. None is perfect; each captures a different facet of journal influence.

• CiteScore (Elsevier/Scopus): Uses a three-year citation window and counts citations to all items in the denominator (eliminating the numerator/denominator asymmetry). Generally lower than IF for the same journal. Available for ~24,000 Scopus-indexed journals — roughly twice the IF’s coverage.
• SCImago Journal Rank (SJR): Uses a three-year window, but weights citations by the prestige of the citing journal (citations from high-SJR journals count more than citations from low-SJR journals). Reports quartiles (Q1–Q4) within each subject category. Free and publicly available at scimagojr.com.
• Source Normalised Impact per Paper (SNIP): Field-normalised metric that compares a journal’s citation rate to the average citation rate in its subject field. A SNIP of 1.0 means the journal is at the field average; above 1.0 is above average.
• h5-index (Google Scholar Metrics): The largest h-index among the papers published in the journal over the last five complete years. A journal with an h5-index of 50 has published at least 50 papers in the last five years that each received at least 50 citations. Robust to extreme outliers and free to view.
• Eigenfactor Score: Uses a PageRank-like algorithm that weights citations by the influence of the citing journal. Measures total influence rather than per-article impact, so larger journals tend to score higher.

For most practical purposes, the combination of IF, CiteScore, and SJR quartile gives a balanced picture of a journal’s standing. Our journal selection guide walks through how to combine these metrics when shortlisting journals.

Field-Normalised Metrics: SNIP and Eigenfactor

The most important conceptual advance over the IF is field normalisation. SNIP (Source Normalised Impact per Paper), developed by Henk Moed at CWTS Leiden, divides a journal’s average citation rate by the average citation rate in its subject field. A SNIP of 1.0 means the journal sits at the field average; above 1.0 is above average; below 1.0 is below average. Because the metric is normalised, SNIP can be compared across disciplines — unlike IF, which cannot.

The Eigenfactor Score, developed by Carl Bergstrom and Jevin West at the a top US university, takes a different approach. It treats the entire citation network as a graph and uses a PageRank-like algorithm to weight citations by the prestige of the citing journal. A citation from Nature counts more than a citation from a regional specialist journal. Eigenfactor also comes with an Article Influence Score, the per-article version, which is more directly comparable to IF.

Both metrics are freely available: SNIP on the journal’s Scopus page, Eigenfactor at eigenfactor.org. Neither is universally accepted, but both compensate for known IF limitations and are worth consulting when making a journal decision.

How to Use Impact Factor Responsibly

For most scholars, the question is not whether to use the IF but how to use it responsibly. Five principles:

1. Compare within disciplines, not across them. Use the JCR subject category rankings rather than the absolute number.
2. Use multiple metrics. Combine IF with CiteScore, SJR, and h5-index for a balanced view.
3. Do not use IF to evaluate individuals or articles. Sign DORA if you agree; many universities and funders have.
4. Read the journal, not just the metric. Scan the last 12 months of published papers. A journal with a respectable IF that publishes work outside your scope is not a good fit, no matter what the number says.
5. Be wary of journals that aggressively promote their IF. Predatory journals often invent fake impact factors or quote metrics from non-Clarivate sources. Verify every IF on the official JCR site. See our predatory journals guide.

For broader context on how IF compares with other indexing and citation databases, see our Scopus vs Web of Science comparison.

Conclusion

The journal impact factor is a journal-level citation metric calculated as the average number of citations in a given year to articles published in the previous two years. It is useful for comparing journals within the same discipline, helpful for librarians making subscription decisions, and widely recognised by academic reward systems — but it is not a measure of individual article quality or researcher merit. The numerator/denominator asymmetry, the two-year citation window, the cross-disciplinary incomparability, and the hidden skewness of citation distributions are real limitations that responsible scholars acknowledge. Complement the IF with CiteScore, SJR quartile, SNIP, h5-index, and Eigenfactor; sign DORA; and always read the journal itself rather than relying on the metric alone. If you would like help shortlisting journals for your next paper, our publication support service provides side-by-side metric comparisons. Pair this guide with our journal selection guide, predatory journals guide, and first-paper publishing guide, and reach us through our contact page for a free consultation.

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