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Record W4412932397 · doi:10.3390/jrfm18080432

Financial Decision-Making Beyond Economic Considerations: A Strategic View for Family Firms in India

2025· article· en· W4412932397 on OpenAlexvenueno aff
Manpreet Kaur Khurana, Muhammad Shahin Miah, Shweta Sharma

Bibliographic record

VenueJournal of risk and financial management · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFamily Business Performance and Succession
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessFinanceFinancial system

Abstract

fetched live from OpenAlex

The study examines economic and non-economic endeavors to explore the association between family involvement and financial decisions within family firms. The non-economic factors of a family drive the need to analyze the impact of socioemotional factors on the financial policies of the family firms. The study explores the impact of family ownership, family management, and family control drawn from agency theory and socioemotional wealth perspectives on the financial decisions of family firms. Our findings in support of the socioemotional wealth perspective show a positive relationship between family ownership and debt financing with a desire to finance growth and avoid control dilution, with an increase in the level of debt. However, the involvement of family members in management and the top management team leads to an adverse relationship between family ownership and debt level, exhibiting the risk-averse behavior of a firm, which drives firms to reduce debt levels. Overall, our findings suggest that the perceptions of the socioemotional wealth theoretical paradigm are important in determining capital structure decisions in family enterprises. The results are resilient to potential endogeneity and heterogeneity difficulties, which may assist scholars and practitioners in assessing capital structure decisions in emerging economies.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.635
Threshold uncertainty score0.626

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.011
GPT teacher head0.246
Teacher spread0.235 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations1
Published2025
Admission routes1
Has abstractyes

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