The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.
Goodbye Pareto Principle, Hello Long Tail: The Effect of Search Costs on the Concentration of Product Sales
Open accessAbstract
Many markets have historically been dominated by a small number of best-selling products. The Pareto principle, also known as the 80/20 rule, describes this common pattern of sales concentration. However, information technology in general and Internet markets in particular have the potential to substantially increase the collective share of niche products, thereby creating a longer tail in the distribution of sales. This paper investigates the Internet's “long tail” phenomenon. By analyzing data collected from a multichannel retailer, it provides empirical evidence that the Internet channel exhibits a significantly less concentrated sales distribution when compared with traditional channels. Previous explanations for this result have focused on differences in product availability between channels. However, we demonstrate that the result survives even when the Internet and traditional channels share exactly the same product availability and prices. Instead, we find that consumers' usage of Internet search and discovery tools, such as recommendation engines, are associated with an increase the share of niche products. We conclude that the Internet's long tail is not solely due to the increase in product selection but may also partly reflect lower search costs on the Internet. If the relationships we uncover persist, the underlying trends in technology portend an ongoing shift in the distribution of product sales. This paper was accepted by Ramayya Krishnan, information systems.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“This rule has been applied in a variety of fields, such as economics, 4-7 biology, 8,9 ethology, 10,11 and civil engineering, 12,13 where its validity and usefulness have been demonstrated.”
From Pareto's 80/20 Rule and the Gaussian Distribution (2018) · cites this paper as [7]
Citations
Cites
The central role of the propensity score in observational studies for causal effects
ROSENBAUM, P. R., & RUBIN, D. B. (1983) · Biometrika · doi:10.1093/biomet/70.1.41 · Cited by 31,241
Stigler, G. J. (1961) · Journal of Political Economy · doi:10.1086/258464 · Cited by 5,332
Frictionless commerce? A comparison of Internet and conventional retailers
Brynjolfsson, E., & Smith, M. D. (2000) · Management Science · doi:10.1287/mnsc.46.4.563.12061 · Cited by 2,498
Self-citationMethods of Measuring the Concentration of Wealth
Lorenz, M. (1905) · Publications of the American Statistical Association · doi:10.2307/2276207 · Cited by 2,376
Reducing buyer search costs: Implications for electronic marketplaces
Bakos, J. Y. (1997) · Management Science · doi:10.1287/mnsc.43.12.1676 · Cited by 2,259
Alba, J. W., Lynch, J. G., Weitz, B. A., Janiszewski, C. A., Lutz, R., Sawyer, A. G., & Wood, S. L. (1997) · Journal of Marketing · doi:10.1177/002224299706100303 · Cited by 2,211
Pareto, V. (1964) · Librairie Droz eBooks · doi:10.3917/droz.paret.1964.01 · Cited by 1,839
Glaeser, E. L., Kolko, J., & Sáiz, A. (2001) · Journal of Economic Geography · doi:10.1093/jeg/1.1.27 · Cited by 1,737
Diamond, P. A. (1971) · Journal of Economic Theory · doi:10.1016/0022-0531(71)90013-5 · Cited by 1,680
Brynjolfsson, E., Hu, Y. J., & Smith, M. D. (2003) · Management Science · doi:10.1287/mnsc.49.11.1580.20580 · Cited by 1,164
Self-citation
Flagged first, then by citations
Research works printed but not linked: 9
- Agins T., 1999, Wall Street Journal, B1
- Anderson C., 2004, Wired Magazine, 170
- Brynjolfsson E., 2006, Sloan Management Rev., 47, 67
- Chellappa R., 2007, Workshop Inform. Systems Econom.
- Engel J., 1996, Consumer Behavior
- Frank R., 1995, The Winner-Take-All Society: Why the Few at the Top Get So Much More Than the Rest of Us
- Gini C., 1955, Memorie di Metodologica Statistica
- Kotler P., 2002, Marketing Management
- 10.1207/S15327663JCP13-1&2_03 · DOI
Cited by
Sorted by citations
Items 801–847 of 847
Do Intellectual Property Rights Protection in RTAs Contribute to the Stability of Services Trade?
Gao, R., He, W., & Elahi, E. (2025) · SAGE Open · doi:10.1177/21582440251377719
DCL4Rec: An Effective Debiased Contrastive Learning Framework for Long-Tail Recommendation
Lin, C., Li, Y., Hong, Y., Liu, Y., He, X., & Yuan, X. (2025) · International Symposium on Intelligent Robotics and Systems (ISoIRS) · doi:10.1109/isoirs65690.2025.11167952
juanjuan, Y. U., Peng, M., wu, C., & Dong, Y. M. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5549438
Generative AI and Firm Productivity: Field Experiments in Online RetailPreprint
Fang, L., Yuan, Z., Zhang, K., Donati, D., & Sárváry, M. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5637573 · Cited by 1
Catching Lightning: Social Media Virality, Performance, and Strategy in a Creative IndustryPreprint
Kim, K., & Raj, M. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5682404
How Data Shapes Competition on Digital Platforms: Consumer Welfare and Firm RiskPreprint
Won, P. Y. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5756562
Huang, Y., Dong, Y., Li, W., & Xu, Y. (2025) · Management System Engineering · doi:10.1007/s44176-025-00054-1
Markopoulos, P., Aron, R., & Ungar, L. (2013)
The Hidden Game: How Corporate Social Media Shapes Product Marketing
Qiu, L. (2026) · New perspectives in organizational communication · doi:10.1007/978-3-032-14713-4_4
Xu, H. (2025) · Journal of business and marketing. · doi:10.62517/jbm.202509402
Multichannel Experience, Product Attributes, and Consumer Return Behavior: An Empirical Analysis
Lim, S. F. W. T. (2026) · Production and Operations Management · doi:10.1177/10591478261422031
The Impact of New Digital Infrastructure on Resource Misallocation
Wang, Q., Zhang, S., Du, M., Zhang, L., & Zhou, X. (2026) · Discrete Dynamics in Nature and Society · doi:10.1155/ddns/1125498
Balcıoğlu, Y. S., & Altındağ, E. (2026) · Entertainment Computing · doi:10.1016/j.entcom.2026.101115
Ma, S., Pan, G., & Zhang, D. (2026) · World Economy · doi:10.1111/twec.70068
When Aggregate Tradeoffs Mask Individual Alignment: Evidence from Follower-Targeted RecommendationPreprint
Feng, Y., Cheng, Y., & Shen, Z. M. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6312018
Online Price Discrimination via Product VarietyPreprint
Mauring, E. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6616851
Auction design with ex post ROI constraints
Lv, H., Bei, X., Zheng, Z., & Wu, F. (2026) · Artificial Intelligence · doi:10.1016/j.artint.2026.104543
Personalization and Customer Engagement Using AI-Powered Analytics
Dhyani, S., Sharma, M., & Valecha, S. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-3648-0.ch008
Fewer Reviews but Better Content: When an Online Review Platform Disables Downvotes
Yu, Y., Yin, D.-Z., & Khern-am-nuai, W. (2026) · Journal of Management Information Systems · doi:10.1080/07421222.2026.2647471
Матрица сравнения ключевых элементов ЭЭ по Адаму Смиту и их современное отражение в ритейле
Коломиец, В. (2026) · Cifra LLC Journals · doi:10.60797/irj.2026.167.15.1
Матрица сравнения ключевых элементов ЭЭ по Давиду Рикардо и их современное отражение в ритейле
Коломиец, В. (2026) · Cifra LLC Journals · doi:10.60797/irj.2026.167.15.2
Матрица сравнения ключевых элементов ЭЭ по Ж.-Б. Сэю и их современное отражение в ритейле
Коломиец, В. (2026) · Cifra LLC Journals · doi:10.60797/irj.2026.167.15.3
Yan, Y., & Chen, F. (2026) · Frontiers in Human Dynamics · doi:10.3389/fhumd.2026.1814966
Nash, K. (2026) · Journal of Database Management · doi:10.4018/jdm.411204
Zhang, A., 胡珑瑛, & Ren, X. (2026) · Electronic Commerce Research · doi:10.1007/s10660-026-10150-3
The Impact of Selected Variables on Customer Lifetime Value
Kvíčala, D., Starzyczná, H., & Mikšík, O. (2026) · Acta academica karviniensia · doi:10.25142/aak.2026.003
The long tale of the long tail: The internet as counterforce to cultural homogeneity
Mellody, J. C. (2026) · New Media & Society · doi:10.1177/14614448261454335
Xiang, Q., Limniou, M., & Ahmed, F. (2026) · Springer eBooks · doi:10.1007/978-3-031-52643-5_240-1
Long tail patterns in online reviews for search and experienced goods: Evidence from Amazon
Jain, A., & Singh, S. (2026) · Acta Psychologica · doi:10.1016/j.actpsy.2026.107408
Incentivizing inequality: how platform rewards exacerbate review disparities
Qian, Y., Zhou, X., & Sun, Y. (2026) · International Journal of Research in Marketing · doi:10.1016/j.ijresmar.2026.07.004
Thi, Y., Lin, L.-C., Vu, M.-Q., & Truong, G. N. T. (2026) · Internet Technology Letters · doi:10.1002/itl2.70352
Kim, J., Kim, S., Hong, J., Gwon, M., & Yun, W. (2026) · Journal of Channel and Retailing · doi:10.17657/jcr.2026.7.31.2
Li, G., Bian, Y., & Xi, P. (2026) · International Review of Economics & Finance · doi:10.1016/j.iref.2026.105761
AI Summaries Overrepresent Fake Reviews: Evidence from AmazonPreprint
Zhai, S., & Ching, A. T. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.7370198
Ma, S., Zhang, D., & Hu, Z. (2026) · China Finance and Economic Review · doi:10.1515/cfer-2026-0017
Pricing with bandits in the long tail: The role of competitive monitoring
Israeli, A., & Anderson, E. T. (2026) · Quantitative Marketing and Economics · doi:10.1007/s11129-026-09314-0
Bennett, D., Rowlinson, M., & Stern, P. (2026) · Enterprise & Society · doi:10.1017/eso.2026.10139
When reach and loyalty scale together: a digital music benchmark for marketing analytics
Šulik, M. (2026) · Journal of Marketing Analytics · doi:10.1057/s41270-026-00541-8
Balancing Personalization and Homogenization in AI-Generated Consumer Recommendations
Kaur, J., & Singh, H. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-9589-0.ch005
Troshkov, O. (2024) · Universal Library of business and economics. · doi:10.70315/uloap.ulbec.2024.0102019
Yang, X., Lin, Z., & Cai, Y. (2026) · MIS Quarterly · doi:10.25300/misq/2026/19632
SmallODs: Understanding the Aggregation Impact of Long-Tail Effect on Urban Rail Flow DistributionPreprint
Xu, C., & Zhu, W. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.7675620
Hoe verandert personalisatie de dynamiek van zoeken en vinden bij informatievergaring
Bos, P. (2014) · Utrecht University Repository (Utrecht University)
HEALTH ANALYTICS AND PREDICTIVE MODELING: FOUR ESSAYS ON HEALTH INFORMATICS
Lin, Y.-K. (2015) · UA Campus Repository (The University of Arizona)
Metadata
- Authors
- Brynjolfsson, E., Hu, Y. (., & Simester, D.
- Affiliations
- National Bureau of Economic Research (US)
- Georgia Institute of Technology (US)
- Massachusetts Institute of Technology (US)
- Venue
- Management Science
- Published
- 2011-08
- Volume
- 57
- Issue
- 8
- Pages
- 1373-1386
- ISSN
- 0025-1909 (ISSN-L)
- 1526-5501
- OpenAlex
- W2159347126
- Cited by
- 847
- References
- 43
- Citations by year
- 2026: 43 · 2025: 54 · 2024: 62 · 2023: 71 · 2022: 43 · 2021: 53 · 2020: 49 · 2019: 49 · 2018: 56 · 2017: 56 · 2016: 55 · 2015: 49 · 2014: 46 · 2013: 33 · 2012: 35
- FWCI
- 127.93
- Type
- journal article
- Language
- en
- Open access
- green
- orcid.org
- Licence
- cc-by-nc-sa
- Locations
- Management Science (publishedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc-sa)
- SSRN Electronic Journal (submittedVersion)
- SSRN Electronic Journal
- Funders
- National Science Foundation (0085725)
- Carnegie Mellon University
- Sloan School of Management, Massachusetts Institute of Technology
- Topics
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Market Behavior and Pricing
- Social Sciences › Business, Management and Accounting › Strategy and Management › Digital Platforms and Economics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Supply Chain and Inventory Management
- Keywords
- long tail, Pareto principle, sales concentration, search costs, niche products, online retail, recommender systems, multichannel retailing, product availability, sales distribution
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.
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 ›
Are you an author, or do you see a problem with this page? Request a review