MétaCan
Menu
Back to cohort
Record W1565948322 · doi:10.1002/smj.2386

“We do what we must, and call it by the best names”: Can deliberate names offset the consequences of organizational atypicality?

2015· article· en· W1565948322 on OpenAlex
Edward B. Smith, Heewon Chae

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueStrategic Management Journal · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Strategy and Innovation
Canadian institutionsKellogg's (Canada)
Fundersnot available
KeywordsCompetitor analysisHedge fundBusinessFinancial crisisEconomicsMarketingFinance

Abstract

fetched live from OpenAlex

Research summary: This article focuses on organizational naming as a strategic choice organizations make to overcome liabilities of atypicality. We argue that, in markets presenting an “illegitimacy discount,” atypical organizations may use deliberate names—names that communicate the market categories to which organizations claim membership—to offset the consequences of atypicality. Using data from the global hedge fund industry, we show that atypical hedge funds are more likely than typical funds to have deliberate names. Importantly, the selection of a deliberate name is economically significant. First, funds with deliberate names grow faster than funds without deliberate names, especially among atypical funds. Second, while atypicality heightened the likelihood of failure during the recent financial crisis—even after controlling for fund performance—having a deliberate name mitigated this effect . Managerial summary: Differentiation is a core element of many organizations' competitive advantage. Nevertheless, as differentiation implies being atypical among one's competitors, differentiation strategies can also lead to an “illegitimacy discount” whereby differentiators are at risk of being misunderstood, miscategorized, and ignored by consumers. Here we investigate how atypical hedge funds—funds that differentiate themselves from their competitors by investing in notably unique ways—use names to offset the potential consequences associated with the “illegitimacy discount.” Our analysis of more than 12,000 hedge funds over 12 years highlighted a trend whereby atypical hedge funds were more likely to choose names that unambiguously associated them with a known investment strategy—for instance, choosing the name “Apex Global Macro Capital” over simply “Apex Capital.” Importantly, name selection proved to be economically significant. For example, among atypical hedge funds, those with unambiguous names grew faster than those without. Furthermore, while being atypical increased the level of disinvestment during the recent financial crisis, having an unambiguous name reversed this effect. Organizational names play an important communication role with consumers, which, while highly symbolic, may also help resolve the dual organizational need to both conform to consumer expectations and differentiate from market competitors . Copyright © 2015 John Wiley & Sons, Ltd.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.470
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.047
GPT teacher head0.250
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it