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Enregistrement W16606102 · doi:10.4018/978-1-59140-875-8.ch007

Business Process Outsourcing to Emerging Markets

2011· book-chapter· en· W16606102 sur OpenAlexaboutno aff
Jurgis Samulevičius, Valdas Samonis

Notice bibliographique

RevueIGI Global eBooks · 2011
Typebook-chapter
Langueen
DomaineBusiness, Management and Accounting
ThématiqueOutsourcing and Supply Chain Management
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésOffshoringOutsourcingBusinessKnowledge process outsourcingGlobalizationIndustrial organizationRestructuringSWOT analysisEmerging marketsCore competencyCommerceChinaOffshore outsourcingCompetitive advantageMarket economyMarketingEconomicsFinancePolitical science

Résumé

récupéré en direct d'OpenAlex

A major phenomenon of globalization, outsourcing is a complex and controversial issue. It occurs when companies contract out activities previously performed in-house or in-country to foreign (usually offshore) companies globally. Couched in the terms of a SWOT analysis and using a modified Harvard-style case study that was subjected to the SWOT analysis, the chapter analyzes business process outsourcing (BPO) to emerging markets, frequently called outsourcing or offshoring in short. The overarching advantage of outsourcing is that it allows a business to focus on core activities as called for by core competence, strategic alliance, and competitive advantage theories of international business. Such a global restructuring of production has been sometimes called the true WMD (weapon of mass destruction) of jobs in the developed world. However, a more balanced approach could borrow the term “creative destruction” from the prominent Austrian economist Josef Schumpeter and emphasize the all-important transformational aspect of outsourcing. A transformational aspect of outsourcing is evidently very important for emerging markets but also for many companies in the developed world; therefore, BPO is sometimes called BTO (business transformational outsourcing). The global digital/knowledge economy offers unprecedented opportunities to produce and sell on a mass scale, reduce costs, and customize to the needs of consumers, all at the same time. Whether you live in a large country such as the U.S. or China, mid-sized country such as Canada or a smaller country such as Lithuania, your potential market is of the same global size. And you can source (netsource) inexpensively wherever you wish. Added to that are immensely increased opportunities to access new knowledge and technologies, driving productivity and living standards further up. BPO to emerging markets is or should be driven by those fundamental reasons having to do with rapid organizational change, reshaping business models to make them viable in the long term, and launching new strategies. This is the essence of transformational outsourcing. In this chapter, BPO is used in the broader, integrated, and comprehensive understanding of changes in the company’s business models and strategies but first of all the company’s changing core competencies and competitive advantages: partnering with another company to achieve a rapid, substantial, and sustainable improvement in company-level performance. A knowledge management approach is advocated in this research that is to be continued in the future. The chapter concludes that outsourcing is a wave of the future. Postcommunist and other emerging markets countries are well advised to jump to these new opportunities as they represent the best chance yet to realize the “latecomer’s advantage” by leapfrogging to technologies and models of doing business which are new for Western countries as well. The chapter analyzes and outlines some of the ways in which contemporary and future business models are deeply transformed by the global digital/knowledge economy. Global outsourcing provides a compelling platform to research the issues of upgrading competitive advantage in developed countries and contract out non-core competencies to emerging markets. Therefore, suggestions for further research are included in the chapter as well.

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)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: aucune
GenreSignal candidat: Autre · Signal consensuel: aucune
Score de désaccord entre enseignants0,741
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0010,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,003

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 Opus0,017
Tête enseignante GPT0,222
Écart entre enseignants0,205 · 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.

Devis d'étudeThéorique ou conceptuel
Domainenon disponible
GenreAutre

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

En bref

Citations3
Publié2011
Routes d'admission1
Résumé présentoui

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