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Record W3082320115 · doi:10.5539/ijef.v12n9p83

Effects of Corporate Profitability and Growth on the Shareholding Strategies of Banks: Evidence from Japan

2020· article· en· W3082320115 on OpenAlexvenueno aff
Kazuhiko Kobori

Bibliographic record

VenueInternational Journal of Economics and Finance · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsProfitability indexBusinessShareholderCorporate governanceSample (material)AccountingProduct (mathematics)Financial institutionFinanceInstitutionShare capitalMarketing

Abstract

fetched live from OpenAlex

This study scrutinised whether the profitability indexes of firms and the costs associated with product creation as reflections of growth potential affect the percentage of shareholding that Japanese banks acquire from Japanese client companies. To this end, multiple regression analysis was conducted on a sample of 302 firms on which 2,231 observations were made over the fiscal years 2006 to 2015. The findings indicated that the principle of shareholding alone does not drive banks to secure shares in client companies. Instead, the standard that prompts share acquisition is whether management is efficiently operating company business. The implication of this study is that a bank’s shareholding strategy requires client companies to implement management with an awareness of corporate governance, whose significance lies in advancing the realisation of returns from corporate activities by lenders and/or shareholders. In other words, banks are motivated to hold shares when client companies are highly profitable and efficient. Even under these conditions, a bank carries on serving as the financial institution with which a client company is primarily affiliated. As a main bank, a given financial institution seems to consider the pursuit of long-term corporate profits through the research and development of a client firm. However, whether banks will continue to seek such profits from client companies is doubtful.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.040
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.041
GPT teacher head0.212
Teacher spread0.171 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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