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Enregistrement W7000513915

Foreign direct investment attraction and impacts in Oman

2023· dissertation· en· W7000513915 sur OpenAlexfundno aff

Notice bibliographique

RevueNottingham Trent University's Institutional Repository (Nottingham Trent Repository) · 2023
Typedissertation
Langueen
DomaineBusiness, Management and Accounting
ThématiqueInternational Business and FDI
Établissements canadiensnon disponible
Organismes subventionnairesTrent UniversityNottingham Trent University
Mots-clésForeign direct investmentDiversification (marketing strategy)AttractionCompetition (biology)Government (linguistics)Developing countryOrder (exchange)
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

A crucial element of Oman Vision 2020 is to enhance Oman’s economic development by accelerating the diversification of its economy in order to further reduce its economic dependency on oil. The Omani government has established legal and institutional frameworks to promote Foreign Direct Investment (FDI) as a means for the diversification of various economic activities and established FDI policies intended to sensitize the public and foreign investors. These concerted efforts by the Omani Government have borne fruit, as the Oman National Centre for Statistics and Information (NCSI, 2016) reports that the accumulation of FDI to date has attracted more than $27 billion to the Omani economy, albeit with the oil and gas industry contributing the lion’s share of this.
\n 
\nGlobal competition among developing countries to attract FDI is at a level that international business has not previously witnessed. Governments in developing economies see FDI as a source of economic development and potential foreign investors are lured by a number of factors.
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\nHowever, despite its undisputable importance, FDI Attraction and Impact is not yet a perfect science but a long-term “trial-and-error” approach which requires a rigorous feedback loop to interpret and build on what has been learnt in a continuous quest to improve FDI Attraction and Impact performance. In this regard, the literature on FDI Attraction and Impact in the Gulf Cooperation Council (GCC), specifically in Oman is, to say the least, bleak and inaccurate.
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\nThis empirical study focused on assessing the performance of 39 FDI Attraction and Impact Factors within the Sultanate of Oman, which were specially derived for this study. The aims were to establish a cause-and-effect relationship and generate a set of FDI performance improvement recommendations. To achieve this, the researcher adopted a relativist ontological and interpretivist epistemological position, employing a mixed-use method that incorporated an inductive approach to support the predominantly qualitative methods (with, in limited instances, a positivist philosophy that incorporated a deductive approach to support quantitative methods). Finally, a descriptive research design as part of a case study research strategy was implemented to uncover the factual aspects of the FDI Attraction and Impact phenomenon in Oman.
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\nIn total, the study generated ten prioritised improvement recommendations to enhance FDI Attraction and Impact in the Sultanate of Oman. In order of priority (highest to lowest), these are as follows:
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\nCreate and fund private vocational training centres, and offer to subsidise the salaries of Omani employees to fast-track their onboarding by investors and continue their accelerated development through on job training under the “Talent Development”
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\nCreate a dedicated fund for “early stage” SME funding, along with Government incentives in the form of subsidies to promote MNC and SME collaboration, and establish a Centre for Excellence for reliable SMEs to support the offerings of MNCs, all under the “SMEs Ecosystem”.
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\nReinforce the role of a central policy making body, mandate the Central Bank to create an ecosystem that is conducive for competitive FDI attraction, and activate reliable data and information centres, all under “Economic Development Policies”
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\nEncourage Possible Public-Private-Partnership (PPP) models to enhance the scope and quality of delivery of Public Services and Public Healthcare under “Social Infrastructure”
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\nThese recommendations for improvement are as comprehensive as they are pragmatic and practical. They will ensure engagement of all concerned stakeholders and be well paced over time to ensure a rapid, yet sustainable improvement in FDI Attraction and Impact performance in the Sultanate of Oman. The researcher will make it his professional life mission to ensure this happens.

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), Études des sciences et des technologies
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 enseignants0,424
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
Bibliométrie0,0020,001
Études des sciences et des technologies0,0020,000
Communication savante0,0010,002
Science ouverte0,0010,000
Intégrité de la recherche0,0010,001
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 Opus0,013
Tête enseignante GPT0,216
Écart entre enseignants0,203 · 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'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
Publié2023
Routes d'admission1
Résumé présentoui

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