Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 881

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

Network Learning: The Effects of Partners' Heterogeneity of Experience on Corporate Acquisitions

Beckman, Christine M., Haunschild, Pamela R.·2002·Administrative Science Quarterly

Abstract

To examine the effects of interorganizational network structures on acquisition decisions, we propose a model whereby firms learn by sampling the diverse experiences of their network partners. We tested this model by examining the effect of diversity of network partners' experience on firms' acquisition decisions, using data on acquisition premiums and acquirers' stock market performance from 1986 to 1997. Results show that firms tied to others with heterogeneous prior premium experience tend to pay less for their acquisitions and have better-performing acquisitions than those tied to others with homogeneous experience. Firms also pay lower premiums when their network partners (1) have completed deals of diverse sizes, (2) have unique information, and (3) are themselves of diverse sizes. Firms that have multiplex relationships with their partners receive even more benefit. The results extend prior research on networks and learning by showing that collective network experience affects firms' decision quality.

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 · 10.2307/3094892

Cites

5 of 5 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 5 references

Cited by

Metadata

Authors
Beckman, C. M., & Haunschild, P. R.
Venue
Administrative Science Quarterly
Publisher
JSTOR
Published
2002-03
Volume
47
Issue
1
Pages
92-124
ISSN
  • 0001-8392 (ISSN-L)
  • 1930-3815
OpenAlex
W2141086182
Cited by
881
References
5
FWCI
43.03
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

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.