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Record W2953618271 · doi:10.1177/0256090920010403

International Joint Ventures and Shareholder Value Creation: Evidence from Manufacturing and Non-manufacturing Sectors

2001· article· en· W2953618271 on OpenAlexaff
Hemant Merchant

Bibliographic record

VenueVikalpa The Journal for Decision Makers · 2001
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsShareholderShareholder valueSample (material)BusinessValue (mathematics)Empirical researchCapital marketIndustrial organizationCapital (architecture)Economic Value AddedEmpirical evidenceCorporate governanceMonetary economicsEconomicsMicroeconomicsFinance

Abstract

fetched live from OpenAlex

Numerous empirical studies have suggested that the economic performance of international joint ventures (IJVs) is modest, at best. This suggestion may be inaccurate, however, since the studies' findings are based on ex post managerial perceptions of IJV performance that are found to be biased. Stated differently, there is a need to investigate IJV performance from ex ante “external* perspective—that of capital markets. Consequently, this study investigates the extent to which IJVformation announcements increase the shareholder value pf participating firms. Despite the merits of engaging a capital markets' perspective, it is necessary to investigate the extent to which capital markets are informationally ‘efflcient’- particularly given persistent doubts about whether capital markets really are as efficient as is widely accepted. Hence, this study compares IJV&' expected performance with their actual performance that is reported in other empirical studies. This study engages the event-study methodology to examine the impact of IJV formation announcements on the shareholder value of IJV parents, and tries to circumvent the methodology's principal limitations in doing so. Based on a sample of more than 500 IJVs, the study's findings indicate participation in IJVs increases parents' shareholder value by an average of approximately one per cent, albeit this figure varies across industry sectors (manufacturing; non-manufacturing) and firm size (large; small). Shareholder value is created for about 50 per cent Of firms in the sample. Moreover, the study's findings suggest that capital markets are informationally efficient

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.738
Threshold uncertainty score0.603

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
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 head0.036
GPT teacher head0.264
Teacher spread0.227 · 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 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

Citations3
Published2001
Admission routes1
Has abstractyes

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