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Record W2022447548 · doi:10.1300/j130v07n01_04

Foreign Market Strategies of European and United States Transnational Management-Consulting Firms in South East Asia: The Case of Thailand

2002· article· en· W2022447548 on OpenAlexaff
Qadeer Hussain, Shaukat Ali, Jan Nowak

Bibliographic record

VenueJournal of Transnational Management Development · 2002
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsForeign direct investmentBusinessContext (archaeology)Service (business)ExploitMarket shareEmerging marketsCompetitive advantageInternational tradeMarketingEconomicsFinance

Abstract

fetched live from OpenAlex

ABSTRACT The share of transnational corporations' (TNCs) foreign investment in the global investment has increased over the years. In this context, the international activities of transnational service corporations (TSCs) have become an important topic of discussion for international managers, governments, researchers, and academics. An even greater expansion has taken place in the case of management consulting services. The core subject of this study are entry strategies and FDI motives observed among transnational management-consulting firms (TMCFs) from the United States, Europe and Asia operating in Thailand. A management interview approach was the major tool for data collection in this study. Eighteen foreign TMCFs operating in Thailand were the main source of primary research data, which were analysed both quantitatively and qualitatively. The results indicate that TMCFs prefer full-ownership participation as an entry mode into the Thai market. As to their FDI motives, the most important one identified is to exploit the existing market opportunities in host countries. Other important motives include: market expansion, exploitation of competitive advantage, and following the client's international involvement. KEYWORDS: Transnational management-consulting firmsFDI motivesforeign-market entry strategiesFDI in South-East AsiaFDI in Thailand

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 score0.954
Threshold uncertainty score0.618

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.019
GPT teacher head0.207
Teacher spread0.188 · 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

Citations3
Published2002
Admission routes1
Has abstractyes

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