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중남미 다국적기업을 활용한 대중남미 경제협력 확대방안 (The Rise of Multilatinas in Latin America and the Implications for Korea)

2013· article· ko· W3121476055 sur OpenAlexaboutno aff
Ki-Su Kwon, Jin‐O Kim, Misook Park, Siun Yi, Taekyoon Lim

Notice bibliographique

RevuePolicy analyses · 2013
Typearticle
Langueko
DomaineBusiness, Management and Accounting
ThématiqueInternational Business and FDI
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésLatin AmericansMultinational corporationForeign direct investmentPolitical scienceEconomyDevelopment economicsEconomic growthEconomics
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

2000년대 들어 중남미 경제의 성장과 함께 중남미 다국적기업의 부상이 크게 주목받고 있다. 물티라티나스(Multilatinas)라고 불리는 중남미 다국적기업은 중남미 토종기업으로, 적어도 1개 이상의 국가에서 활동하고 있는 기업으로 정의된다. 2000년대 초부터 시작된 전 세계적인 일차산품 붐에 힘입어 세계적인 기업으로 성장하고 있는 중남미 다국적기업은 자원분야에서뿐만 아니라 제조업, 건설업, 서비스업 등 다양한 산업분야에서 높은 경쟁력을 갖고 있다. 이에 본 연구는 2000년대 들어 중남미 경제 및 산업에서 갈수록 커다란 영향력을 행사하고 있는 중남미 다국적기업을 활용한 대중남미 경제협력 확대방안을 제시하는 데 목적을 두고 추진되었다. 본 보고서는 크게 여섯 장으로 구성되었다. 먼저 제1장인 서론에서는 본 연구의 필요성 및 목적, 연구 구성 및 방법, 선행연구 현황에 대해 살펴보았다. 특히 본 장에서는 선진국 다국적기업을 중심으로 한 기업의 해외투자 이론, 신흥국 다국적기업의 해외투자 이론을 분석하고 중남미 다국적기업의 해외투자에 관한 선행연구를 검토하였다. Multinational firms originating in America, or “multilatinas,” have risen over the past twenty years, and they are now affecting American economies significantly. The current study draws attention to these relatively new economic actors and suggests how to promote economic cooperation with them. The study consists of six chapters. The first and introductory chapter discusses the purposes of the study, methodology and existing literature. Especially it reviews theories on the choices of firms for foreign direct investment according to their origins: developed countries, developing countries and America. Chapter two analyzes the current state of multilatinas and their major characteristics, especially in terms of sectors and geographical locations. The list of multilatinas included in this chapter are major multilatinas drawn from the ranking of multilatinas that The Boston Consulting Group and America Economia have reported. The third chapter closely discusses the process of the rise of multilatinas. It analyzes how multilatinas have become the world leaders, how they are affecting global economy. It also examines their influence on their own national economies by looking at their business networks at the national and regional levels. In so doing, this chapter introduces major families that own multilatinas in Brazil and Mexico since multilatinas are predominantly controlled by individual families. Chapter four presents several cases of non-Latin American foreign firms that have successfully utilized multilatinas to enter American markets. The nationalities of the foreign firms include the United States, Spain, Canada, UAE, Singapore, Australia and Japan. The cases of Korean firms cooperating with multilatinas are discussed as well. The sectors of cooperation are limited to plant construction, natural resource, and ICT. Finally, the concluding chapter includes some suggestions about how Korea can utilize multilatinas in order to expand the economic cooperation with America. To this end, it discusses Korean firms' perception of multilatinas, and the potential cooperation between them. The suggestions include i) creating multifaceted cooperation networks, ii) building strategic partnerships, and iii) inducing the investment of multilatinas in Korea. With respect to building multifaceted cooperation networks, first, the Korean government needs to support Korean firms in joining local industrial organizations or associations in America, to provide them with more useful information on multilatinas. The government also needs to help Korean firms, especially SMEs, strengthen their cooperation networks with multilatinas. Second, other than existing general conferences or councils, business councils classified specifically by industry, for instance the Korea-Latin America plant construction business summit, needs to be created. Third, business councils at a regional level are important since many American countries are eager to form one big integrated market. Fourth, business councils such as the Korean Chamber of Commerce needs to expand their membership to include American as well as Korean entrepreneurs. Fifth, Korean entrepreneurs need to actively participate in the annual 'Multilatinas Forum' so as to join the networks of multilatinas in America. Sixth, collaboration with American MBA schools would be useful because they are the sources of insightful knowledge on American business and have abundant human resources. Seventh, student internship programs that provide work experience in multilatinas may increase job opportunities for Korean college graduates in America and therefore expand networks with American business. As for building strategic partnerships with multilatinas, first, various forms of strategic partnership are needed to successfully enter American markets. Second, cooperation with American distribution companies, especially from Chile, needs to be promoted. Third, making a strategic alliance with Brazilian multinationals, especially construction engineering enterprises, is needed to reinforce the presence of Korean firms in the Brazilian market that is very closed to foreign firms. Fourth, multilatinas would be appropriate partners for Korean companies to enter BOP markets in America. Fifth, it is important to expand cooperation with national oil companies(NOCs) in America such as ENAP of Chile, Ecopetrol of Colombia, Petrobras of Brazil. Last but not the least, in regard to inducing the investment of multilatinas in Korea, Latin America Desk or Multilatinas Desk should be created within the Invest Korea for systematic promotion. Korea also needs to increase an awareness of Korea's positive business environment among multilatinas. In addition, Korea needs to promote itself as the hub for American firms to invest in Asia. To this end, Korea should promote institutional platforms for doing business with America, such as FTAs, Investment Promotion and Protection Agreements, and double tax avoidance agreements.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,559
Score d'incertitude au seuil0,937

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,001
Communication savante0,0000,001
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,055
Tête enseignante GPT0,346
Écart entre enseignants0,291 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2013
Routes d'admission1
Résumé présentoui

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