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Cited by 481

The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.

Dual clocks: Entry order influences on incumbent and newcomer market share and survival when specialized assets retain their value

Mitchell, Will·1991·Strategic Management Journal

Abstract

Entry order analysis often shows that early entrants to an industry or technical subfield of an industry outperform laggards. Some studies, though, have found that late entrants prevail. This paper tests dual‐clock hypotheses of entry order effects on performance, measured both as market share and survival. One entry clock records the entry of all entrants to a new technical subfield within an industry, while a second clock records the entry of industry incumbents. Relative to the appropriate clock, early entrants are predicted to outperform laggards, but when entry is measured on only one clock, the estimated influences may be inaccurate. Error will be particularly likely if a study contains a survivor bias. The study, which finds entry timing trade‐offs between market share and survival, is generalizable to cases in which a plausible set of conditions is found.

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Metadata

Authors
Mitchell, W.
Venue
Strategic Management Journal
Publisher
Wiley
Published
1991-02
Volume
12
Issue
2
Pages
85-100
ISSN
  • 0143-2095 (ISSN-L)
  • 1097-0266
OpenAlex
W2044453045
Cited by
481
References
38
FWCI
14.75
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Dual clocks: Entry order influences on incumbent and newcomer market share and survival when specialized assets retain their value. https://app.cochat.ai/papers/10.1002/smj.4250120202
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Mitchell, W. (1991). Dual clocks: Entry order influences on incumbent and newcomer market share and survival when specialized assets retain their value. Strategic Management Journal. https://doi.org/10.1002/smj.4250120202

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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.