The DOI matches its Crossref record; 107 of the 107 references it cites were found in a registry or an index.
Cognitive Processes of Opportunity Recognition: The Role of Structural Alignment
Abstract
Substantial gains can be made by individuals and organizations adept at detecting new opportunities. But how do business leaders do that concretely? Organization research shows that managers are more inclined to identify threats than opportunities, but it is still not clear why this is the case. Likewise, research points to several factors that may facilitate the recognition of opportunities. Yet empirical observations have been limited by retrospective biases and other conceptual challenges. As a result, key questions remain not only about what factors facilitate the recognition of opportunities, but also about why these factors play such a role. To further understanding of these issues, we study the reasoning strategies that individuals mobilize for recognizing opportunities. We develop a model of opportunity recognition as a cognitive process of structural alignment, and analyze the think-aloud verbalizations of executive entrepreneurs as they try to recognize opportunities for new technologies. In contrast to prior research, the qualitative and quantitative data do not provide evidence that individuals use prototypes to recognize opportunities. Instead, we find that different kinds of mental connections play different roles in the process of recognizing opportunities, with different consequences. We also document why and how prior knowledge may facilitate this process. By drawing attention to the cognitive underpinnings of opportunity recognition, we cast light on why it constitutes such a challenging task for individuals and organizations. In turn, this provides a useful basis for exploring the factors that explain why some individuals/organizations are able to recognize opportunities that others simply fail to see.
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“For example, research has found that knowledge (Grégoire et al., 2010), information (Ozgen and Baron, 2007;Shane, 2000) and social networks (Ma et al., 2011;Singh, 2000) are essential resources within the opportunity recognition process.”
From Work hard or play hard: the effect of leisure crafting on opportunity recognition and venture performance (2023) · cites this paper as Grégoire et al., 2010
In the citing paper
“Entrepreneurs can craft their leisure time so that they can engage in learning experiences directed at acquiring knowledge and skills, which can positively influence their ability to recognize opportunities (cf.Grégoire et al., 2010).”
From Work hard or play hard: the effect of leisure crafting on opportunity recognition and venture performance (2023) · cites this paper as Grégoire et al., 2010
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Metadata
- Authors
- Grégoire, D. A., Barr, P. S., & Shepherd, D. A.
- Affiliations
- Georgia State University (US)
- Indiana University Bloomington (US)
- Venue
- Organization Science
- Published
- 2010-04
- Volume
- 21
- Issue
- 2
- Pages
- 413-431
- ISSN
- 1047-7039 (ISSN-L)
- 1526-5455
- OpenAlex
- W2118430729
- Cited by
- 582
- References
- 107
- Citations by year
- 2026: 49 · 2025: 38 · 2024: 31 · 2023: 38 · 2022: 39 · 2021: 56 · 2020: 41 · 2019: 28 · 2018: 49 · 2017: 42 · 2016: 32 · 2015: 32 · 2014: 39 · 2013: 25 · 2012: 18
- FWCI
- 26.43
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Organization Science (publishedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Management of Technology and Innovation › Entrepreneurship Studies and Influences
- Social Sciences › Business, Management and Accounting › Strategy and Management › Innovation and Knowledge Management
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Management and Organizational Studies
- Keywords
- opportunity recognition, structural alignment, cognitive processes, prior knowledge, prototype
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 ›
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