ANALYZING CORPORATE EXPANSION TO INTERNATIONAL MARKETS: THE CASE OF GERMANY, UNITED KINGDOM, CANADA, MEXICO AND CHINA
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Résumé
In this study, the authors utilized the Analytic Hierarchy Process (AHP) decision-making model to select the optimal market for international expansion for ABC Corporation located in Ohio[1]. The benefits of exporting to nine different countries: Germany, the United Kingdom, Canada, Mexico, Netherlands, China, United Arab Emirates, Australia and Brazil were analyzed. For the sake of more precise and in-depth research, preliminary studies performed on these nine countries were used to determine the top five markets: China, Mexico, Canada, Germany and the United Kingdom. Preliminary research included multiple factors about these nine countries. Market size, market growth rate, market consumption capacity, market intensity, market receptivity, commercial infrastructure, trade barriers, contribution margins, country risk and the growth rate of construction were the qualitative and quantitative criteria specifically considered. The importance of each criteria and sub-criteria were determined with export market experts and company decision makers. The AHP analysis enabled the authors to determine the best possible export market for the company by evaluating the data from China, Mexico, Canada, Germany and the United Kingdom. The robustness of the results was tested using sensitivity analysis. Sensitivity analysis results were then discussed with the decision makers. The best market was selected and alternative markets were presented with degrees of preference. Managerial implications of the study and future research directions will be discussed. [1] Company name has been disguised for confidentiality reasons. -This paper received “Best Student Achievement in International Business Award for Graduate Students”, Youngstown State University, Williamson College of Business, April 18, 2018. -Acknowledgement: This project allowed our group to become better researchers, taught us how to use AHP methodology in real - life decision making and allowed us to network with colleagues around the world. This was a fantastic experience for all of us and it will not be forgotten. Being able to represent Youngstown State University at the MCDM, 2017 Conference was an honor. We learned and did things that students cannot learn in the classroom. Working alongside Dr. Karpak allowed us to have a hands - on experience with the project and she was there when questions needed addressed. We feel that our research benefitted ABC and allowed them to gain a better understanding of what market they should export to. We are beyond grateful for this experience and glad that we were selected to go to Ottawa, Canada and to now be submitting our research to the IJAHP journal. The authors also thank the export expert Mr. Mousa Kassis, CGBP, Director, Ohio Small Business Development Center (SBDC) Export Assistance Network, Williamson College of Business Administration of Youngstown State University, for identifying ABC Company and giving his expert judgments on criteria evaluations.
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Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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