Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 324

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Embeddedness and Price Formation in the Corporate Law Market

Uzzi, Brian, Lancaster, Ryon·2004·American Sociological Review

Abstract

The determination of prices is a key function of markets, yet sociologists are just beginning to study it. Most theorists view prices as a consequence of economic processes. By contrast, we consider how social structure shapes prices. Building on embeddedness arguments and original fieldwork at large law firms, we propose that a firm's embedded relationships influence prices by prompting private-information flows and informal governance arrangements that add unique value to goods and services. We test our arguments with a separate longitudinal dataset on the pricing of legal services by law firms that represent corporate America. We find that embeddedness can significantly increase and decrease prices net of standard variables and in markets for both complex and routine legal services. Moreover, results show that three forms of embeddedness—embedded ties, board memberships, and status—affect prices in different directions and have different magnitudes of effects that depend on the complexity of the legal service.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1177/000312240406900301

Cites

4 of 4 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 4 references

Cited by

See all 324

Metadata

Authors
Uzzi, B., & Lancaster, R.
Venue
American Sociological Review
Published
2004-06
Volume
69
Issue
3
Pages
319-344
ISSN
  • 0003-1224 (ISSN-L)
  • 1939-8271
OpenAlex
W2004221960
Cited by
324
References
4
FWCI
21.52
Type
journal article
Language
en
Open access
closed

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

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Embeddedness and Price Formation in the Corporate Law Market. https://app.cochat.ai/papers/10.1177/000312240406900301
The paper
Uzzi, B., & Lancaster, R. (2004). Embeddedness and Price Formation in the Corporate Law Market. American Sociological Review. https://doi.org/10.1177/000312240406900301

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.