The DOI matches its Crossref record; 22 of the 23 references it cites were found in a registry or an index; none of the 5 sources its claims cite is checked for support yet.
The productivity paradox of information technology
Open accessAbstract
The relationship between information technology (IT) and productivity is widely discussed but little understood.Delivered computing power in the U.S. economy has increased by more than two orders of magnitude since 1970 (Figure 1) yet productivity; especially in the B u s i n e s s C o m p u t i n g 1~ble 2. Studies of IT in M a n u f a c t u r i n g 'robl® 3. Studies of IT in Services
Overview
CoChat Summary
TL;DR
Brynjolfsson reviews the “IT productivity paradox”—large increases in computing power and IT investment without clear aggregate productivity gains—and argues the shortfall is at least partly due to measurement and methodological deficiencies rather than solely mismanagement. He organizes explanations into measurement errors, lags, redistribution, and mismanagement, and notes that some firm-level evidence finds high returns to IT.
Key findings
- U.S. delivered computing power increased by more than two orders of magnitude since 1970 while service-sector productivity stagnated; Solow’s summary is quoted: “we see computers everywhere except in the productivity statistics.”
- Roach’s cited statistics indicate output per production worker grew 16.9% between the mid-1970s and 1986, while output per information worker decreased 6.6%.
- Four explanations for the paradox are assessed: measurement errors, lags, redistribution, and mismanagement. The paper argues measurement difficulties may account for “the lion’s share” of the gap; Baily and Gordon’s revisions add 2.3% per year to productivity between 1973 and 1987 in finance, insurance, and real estate.
- Brynjolfsson and Hitt found service firms’ return on investment averaged over 60% per year, and the study with the largest and most detailed data set found no productivity shortfall. Lags are also noted: executives expected up to five years for IT payoffs, and an econometric study found two-to-three-year lags.
Methods
- Review and synthesis, not new primary data collection.
- Based on a computerized literature search of 30 leading journals in information systems and economics, plus discussions with leading researchers.
- Assesses principal empirical studies of IT and productivity across manufacturing and services and evaluates four hypotheses for the paradox.
Limitations
- The paper states there is still no definitive answer to whether IT’s productivity impact has actually been unusually low; research tools remain “blunt,” and the measurement problem is becoming more severe. It also cautions that “a shortfall of evidence is not necessarily evidence of a shortfall.”
- The paper states that studies usually spell out data and method limitations, but media may report only surprising conclusions, and managers tend to overemphasize productivity studies.
- Evident from the text: as a literature review, its conclusions depend on cited studies and their measurement and methodological limitations; it provides no new empirical estimates.
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Claims the paper makes
0 Valid · 0 Not valid · 5 Not checked · 8 Own results and interpretations
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The sharp drop in productivity roughly coincided with the rapid increase in the use of IT (Figure 1).”
§ THE PRODUCTIVITY PARADOX OF INFORMATION TECHNOLOGY > EconomywJde Productivity and the Information Worker
plainstates an association- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A statement the paper makes itself — it cites no source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Econometric estimates have also indicated low IT capital productivity in a variety of manufacturing and service industries.”
§ THE PRODUCTIVITY PARADOX OF INFORMATION TECHNOLOGY > Dimensions of the Paradox
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“While a number of dimensions of the paradox are disturbing and provoking, we still do not have a definitive answer to the question of whether the productivity impact of IT has actually been unusually low.”
§ THE PRODUCTIVITY PARADOX OF INFORMATION TECHNOLOGY > Conclusion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“Using a standard production function approach, Brynjolfsson and Hitt Business Computing [7] found that for the service firms in their sample, return on investment averaged over 60% per year.”
§ THE PRODUCTIVITY PARADOX OF INFORMATION TECHNOLOGY > COMMUNI CATI ONS OF THE ACM
What the sources say
- Not matchedcites [7]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Not matched
In the paper
“This accords with a recent econometric study by Brynjolfsson et al. [8] which found lags of two-tothree years before the strongest organizational impacts of IT were felt.”
§ THE PRODUCTIVITY PARADOX OF INFORMATION TECHNOLOGY > Lags
What the sources say
- Not matchedcites [8]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Not matched
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Love, P. E. D., & Zahir Irani, A. (2004) · Information & Management · doi:10.1016/j.im.2003.12.011 · Cited by 273
The Extroverted Firm: How External Information Practices Affect Innovation and Productivity
Tambe, P., Hitt, L. M., & Brynjolfsson, E. (2012) · Management Science · doi:10.1287/mnsc.1110.1446 · Cited by 272
Self-citationDeterminants of a sustainable competitive advantage due to an IT-enabled strategy
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Measuring the Performance of Information Systems: A Functional Scorecard
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Metadata
- Authors
- Brynjolfsson, E.
- Corresponding author
- Brynjolfsson, Erik
- ORCID
- Brynjolfsson, Erik
- Venue
- Communications of the ACM
- Published
- 1993-12
- Volume
- 36
- Issue
- 12
- Pages
- 66-77
- ISSN
- 0001-0782 (ISSN-L)
- 1557-7317
- OpenAlex
- W1978484347
- Semantic Scholar
- 2b9a95f6e1bc5dd2f1b17bcaafe11e28368aa4ca
- Cited by
- 2,604
- References
- 23
- Citations by year
- 2026: 148 · 2025: 85 · 2024: 72 · 2023: 77 · 2022: 68 · 2021: 70 · 2020: 82 · 2019: 77 · 2018: 79 · 2017: 84 · 2016: 85 · 2015: 104 · 2014: 112 · 2013: 100 · 2012: 129
- FWCI
- 79.59
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Communications of the ACM (publishedVersion)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Economic Growth and Productivity
- Social Sciences › Business, Management and Accounting › Management Information Systems › Information Technology Governance and Strategy
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › ICT Impact and Policies
- Keywords
- information technology, productivity, productivity paradox, computational power, business computing, manufacturing industry, service, IT investment returns
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-11-14, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-11-14 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
