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Cited by 2,614Economic Growth and ProductivityInformation Technology Governance and StrategyICT Impact and Policies

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 access
Brynjolfsson, Erik·1993·Communications of the ACM

Abstract

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.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1145/163298.163309

Cites

22 of 22 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

0 Valid · 0 Not valid · 5 Not checked · 8 Own results and interpretations

5 more claims

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  • It may state two separate claims as one. 2
  • Probably not a substantial claim. 1

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Citations

Cites

Show all 23 references

Research works printed but not linked: 11

  1. Alpar P, 1990, Proceedings of the Twenty- Second Hawaiian International Conference On System Science (Honolufu. Hawaii
  2. Baily M.N., 1988, Brooking~ Papers on Economic A ctivi~,, W.C. Brainard, and G.I., Perry.
  3. Berndt E.R., 1991, National Bureau of Economic Research Manuscript
  4. Brooke G, 1991, University of Minnesota
  5. 10.5555/3217170.3217173 · doi:10.5555/3217170.3217173
  6. Harris S.E., 1989, Prorceedings of the Twenty--Second Hawaikm International Conqference ~m System Science (Honolulu
  7. Loveman G.W., July, 1988.
  8. Noyelle T., Ed., 1990, the Service Sector. Westview Press, Boulder, Col.
  9. Siegel D., Apr., 1991
  10. Strassmann A., 1990, Conn.
  11. Weill P. Do Computers Pay Off? iCII Press Washington D.C. 1990. Weill P. Do Computers Pay Off? iCII Press Washington D.C. 1990.

Cited by

Items 2,401–2,500 of 2,614

Metadata

Authors
Brynjolfsson, E.
Corresponding author
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
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
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

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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.