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Record W4220746121 · doi:10.1057/s41267-022-00500-2

The impact of initial public offerings on SMEs’ foreign investment decisions

2022· article· en· W4220746121 on OpenAlexaff
Guoliang Frank Jiang, Jeffrey J. Reuer, Colette Southam, Paul W. Beamish

Bibliographic record

VenueJournal of International Business Studies · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsWestern UniversityCarleton University
Fundersnot available
KeywordsInternationalizationInitial public offeringSubsidiaryPaceBusinessForeign direct investmentSample (material)Investment (military)International businessIndustrial organizationMarketingEconomicsFinanceMultinational corporationInternational tradeManagement

Abstract

fetched live from OpenAlex

Abstract This study aims to bridge the research on the internationalization of small- and medium-sized enterprises (SMEs) with the literature on initial public offerings (IPOs). It investigates how IPOs affect SMEs’ foreign investment decisions as they internationalize. We argue that IPOs enable SMEs to engage in a period of accelerated foreign expansion, resulting in a wave-like pattern, as suggested by Håkanson and Kappen’s (J Int Bus Stud 48(9):1103–1113, 2017) ‘Casino model’ of internationalization. We also propose that there will be a post-IPO shift in SMEs entering less familiar locations and towards taking higher ownership stakes in new subsidiaries. We use a difference-in-differences design combined with coarsened exact matching to isolate the effects of IPOs. Our analysis of overseas investments by a matched sample of newly listed Japanese manufacturing SMEs and their private counterparts provides strong evidence that SMEs accelerate the pace of establishing new foreign subsidiaries after going public. The results also reveal nuanced changes in the location and ownership patterns in the post-IPO period. This study identifies the IPO as a significant antecedent to SME foreign expansion and offers a new explanation for intertemporal variance in the pace, direction, and commitment of the SME internationalization process.

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)0.002
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 score0.640
Threshold uncertainty score0.471

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.068
GPT teacher head0.337
Teacher spread0.269 · 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

Citations18
Published2022
Admission routes1
Has abstractyes

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