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Record W4319160940 · doi:10.1108/ijoem-08-2021-1299

Firm internationalization approaches and performance: the moderating role of the home country's formal institutions

2023· article· en· W4319160940 on OpenAlexaff
Henrique Corrêa da Cunha, Mohamed Amal, Dinorá Eliete Floriani, Maria Tereza Leme Fleury

Bibliographic record

VenueInternational Journal of Emerging Markets · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsInternationalizationMultinational corporationCorporate governancePanel dataEmerging marketsForeign direct investmentBusinessQuality (philosophy)Order (exchange)Test (biology)Industrial organizationMarketingEconomicsInternational tradeEconometricsMacroeconomicsFinance

Abstract

fetched live from OpenAlex

Purpose This study investigates how the degree of internationalization (DOI) affects the financial performance of emerging market companies by making the distinction between export intensity and multinationality (i.e. foreign direct investment). The authors argue that the different DOI-performance patterns in the literature relate to different internationalization approaches, which are moderated in distinct ways by formal institutions in the home country. Design/methodology/approach Based on data of Brazilian firms in several industries and with different internationalization patterns including 100 exporting firms and 30 multinational companies with varying degrees of multinationality over a period of five consecutive years, the authors test their hypotheses using an unbalanced panel data with 346 firm-year observations. In order to test how the quality of formal institutions moderate the DOI-performance relationships, the authors estimate the changes in the slope of the regression line by adding and subtracting one standard deviation to the Worldwide Governance Indicators (WGI) variables. Findings A positive and linear association between export intensity-performance (EI-P) highlights the location specific comparative advantages of exporting Brazilian firms, while the multinationality-performance (M-P) relationship points to a horizontal S-shape pattern which conforms to the theoretical assumptions of the three-stage internationalization process. Formal institutions moderate positively the EI-P relationship, but moderate negatively each of the three stages of the M-P relationship. Research limitations/implications The findings from this study provide critical insights that contribute to the ongoing debate on how formal institutions in the home country affect the DOI-performance relationship of emerging market companies (EMCs). However, the authors consider that it has limitations as they focused exclusively on formal institutions captured by governance institutions in the Brazilian context. Practical implications This study provides relevant insights to managers and policy makers. Findings reveal that strong formal institutions in the home country make it easier (cheaper) for EMCs to invest abroad, and, at the same time, increase the efficiency of exporting firms and positively influence financial performance. Moreover, results show that during downturns in their domestic markets, multinational EMCs outperform domestic firms. In that sense, while policy makers can promote the internationalization and competitiveness of EMCs by implementing more supportive formal institutions, managers should consider a proactive approach and invest abroad when conditions in the home country are favorable. Originality/value By making the distinction between export intensity and multinationality this study contributes to the literature on the DOI-performance of EMCs providing a more nuanced view on how formal institutions in the home country moderate the EI-P and M-P relationships in different ways.

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)0.003
metaresearch head score (Gemma)0.017
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 score0.006
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.026
GPT teacher head0.241
Teacher spread0.216 · 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

Citations15
Published2023
Admission routes1
Has abstractyes

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