Leveraging Global Value Chains to Bridge the Gap between Rural and Global Economies: Case of North Carolina’s Appalachian Automotive Industry
Bibliographic record
Abstract
Globalization has intensified challenges for rural regions. As countries have become increasingly aware of the need to increase innovation, resources are being allocated towards making cities and technology-intensive industries more competitive. While urban areas focus on knowledge and technology intensive areas, rural regions face distinct challenges in the push for greater economic prosperity. This article examines how the Global Value Chain (GVC) framework can be a key asset to policy makers interested in rural development by providing guidance on how to connect rural regions to globalized industries. GVC analysis has grown in popularity as a framework to facilitate economic prosperity, but has not yet been rigorously applied towards specific rural regions, only rural countries. This paper demonstrates the potential for the GVC framework to help rural areas leverage their strengths to become players in the global economy. The application of the GVC framework is focused on North Carolina’s automotive industry, in which researchers studied employment and wage data, educational infrastructure, key firms, and broader industry trends. The results of the GVC analysis led to several recommendations for North Carolina to increase its global competitiveness in the automotive sector by continuing to strengthen the community college system, invest in light-weight technologies and capture more of the value in high-tech parts manufacturing. The implications of the case study in Appalachia reveal the strengths of the GVC framework to applications in rural regions and communities. The holistic nature of the framework allows for the successful use of the GVC framework to both understand the advantages of a rural region and identify key strategies that will allow the region to generate value in globalized industries. By using Appalachia’s trucking industry as a case study, the findings of this study lay a foundation for the future application of GVC analysis to be used by rural regions seeking greater participation in globalized industries. Keywords: global value chains (GVCs), Appalachia, economic development, automotive industry, manufacturing ----------------------------------------------------------- Resume La mondialisation a intensifie les defis dans les regions rurales. Alors que les pays sont devenus de plus en plus conscients des besoins croissants d'innovation, les ressources ont ete allouees dans le but de rendre les villes et les industries a technologie de pointe plus competitives. Pendant que les zones urbaines se concentrent sur les zones de savoirs et les technologies intensives, les regions rurales font face a des defis distincts dans la course a une meilleure prosperite economique. Cet article examine dans quelle mesure le cadre de la chaine de valeurs mondiales (CVM ou GVC en anglais) peut etre un atout cle pour les responsables politiques interesses dans le developpement rural en fournissant un encadrement sur la maniere de connecter des regions rurales avec des industries mondialisees. L'analyse de la CVM a gagne en popularite comme cadre pour faciliter la prosperite economique, mais n'a pas encore ete rigoureusement applique aux regions rurales specifiques, seulement a certains pays ruraux. Cet article demontre que la CVM peut aider les zones rurales a exploiter leurs forces pour devenir des acteurs dans l'economie mondiale. L'application de la CVM se concentre sur l'industrie automobile de la Caroline du Nord, dans laquelle les chercheurs ont etudie l'emploi et les donnees de salaire, l'infrastructure educationnelle, les points cles des entreprises et les tendances generalisees de l'industrie. Les resultats de la CVM ont donne lieu a plusieurs recommandations en Caroline du Nord afin que cet etat puisse augmenter sa competitivite globale dans le secteur de l'automobile en continuant a renforcer le systeme de college communautaire, l'investissement dans les technologies legeres et a saisir davantage la plus value de l'industrie des composantes manufacturieres de haute-technologie. Les implications de ce cas d'etude dans les Appalaches revelent les points forts de l'application de la CVM dans les regions rurales et communautaires. La nature holistique de ce cadre permet le succes de l'utilisation de la GVC autant pour comprendre les avantages d'une region rurale que pour identifier les strategies cles qui permettront a la region de generer de la valeur dans des industries mondiales. En utilisant l'industrie de camionnage des Appalaches comme etude de cas, nous obtenons des resultats qui jettent des bases pour une utilisation future de la CVM comme methode d'analyse a etre utilisee par les regions rurales souhaitant une meilleure participation dans les industries mondiales.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".