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Record W2081434173 · doi:10.1177/0149206311398135

Geographic and Product Diversification in Charitable Organizations

2011· article· en· W2081434173 on OpenAlexaff
Geoffrey M. Kistruck, Israr Qureshi, Paul W. Beamish

Bibliographic record

VenueJournal of Management · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsWestern University
Fundersnot available
KeywordsDiversification (marketing strategy)Multinational corporationBusinessTransaction costMarketingIndustrial organizationEconomicsFinance

Abstract

fetched live from OpenAlex

The diversification of firms into new geographic and product markets has received a tremendous amount of attention in the field of management. Charities, on the other hand, have garnered attention among management scholars primarily as social influencers on multinational corporations. However, over the past half-century, charities have become significant diversified entities in and of themselves. At their core, both charitable and for-profit organizations are bundles of routines that struggle to deal with administrative issues related to institutional isomorphism, organizational slack, and resource dependency. However, from a contextual standpoint, one of the primary mechanisms by which the diversification of charities impacts efficiency is the transaction costs associated with seeking out and maintaining external resources from donors in addition to charities’ internal set of capabilities and routines. Using panel data involving 3,616 charities over a five-year period, the authors’ findings suggest that while the main relationship between geographic diversification and efficiency is U shaped in nature, the main relationship between product diversification and efficiency is inverted U shaped. From an interaction perspective, the authors’ results also suggest that while charities that maintain lower levels of product diversification follow a similar U-shaped curve as they increasingly diversify into new regions, this curve is inverted for charities that are engaged in unrelated types of product diversification. Therefore, the study suggests that the extent to which one type of diversification produces positive or negative efficiencies depends significantly on the level of the other type of diversification. Such findings have theoretical implications for both the charitable and for-profit sectors.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.030
GPT teacher head0.258
Teacher spread0.228 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations88
Published2011
Admission routes1
Has abstractyes

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