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Record W4293221741 · doi:10.1111/ajfs.12363

A Survey of Asian Family Business Research*

2022· article· en· W4293221741 on OpenAlex

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

VenueAsia-Pacific Journal of Financial Studies · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFamily Business Performance and Succession
Canadian institutionsUniversity of Alberta
FundersDanmarks GrundforskningsfondNational Research Foundation
KeywordsFamily businessSurvey researchBusinessBusiness administration

Abstract

fetched live from OpenAlex

Abstract We survey the literature on family firms with a focus on Asian countries. We begin with identifying three key motivational drivers of international research on family business—their dominance, relative performance, and extent of family embeddedness in the business. Second, we provide a brief survey of family firms in eight Asian economies with a focus on the history and current challenges faced by family firms in each country. Third, we document the variety of family firm definitions used in the literature and the resulting difficulty in drawing inferences due to a lack of definitional consistency. Fourth, we discuss the strategic advantages family assets such as legacy and networks bring to family firms in the Asian context. Fifth, we identify some unique challenges family firms face in their countries, and provide examples of how ownership and succession structures mitigate these challenges. We close this survey by suggesting some open research questions relevant for Asian family firms.

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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.330
Threshold uncertainty score0.761

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.004
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.101
GPT teacher head0.319
Teacher spread0.218 · 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