Comparative analysis of competitiveness of exporting agroindustrial beef chains in Goiás state
Notice bibliographique
Résumé
Brazil stands as the largest exporter of beef, and Goiás stands out as the second largest exporter state, third in beef production and quarter in effective herd, according to 2008 data (SEPIN, 2009a). Because of the importance of this activity to the State economy and the currency and relevance of the theme, we chose to comparatively analyze the competitiveness of agro-industrial exporting chains of beef in the State of Goiás. We started from the assumption that export food chains (formed from the slaughtering units) of beef in Goiás present settings, actors, resources and different transactions, which facilitates the design of differentiated chains. In addition, we started with the assumption that the slaughterhouses are the dynamizing actors and that the beef exporting chains in Goiás realize competitive advantages. We analyzed the areas of production (beef cattle), slaughter and processing (refrigerators), and distribution and consumption. Competitive analysis has been developed by drivers and sub-factors of competitiveness, which included 20 drivers and 146 sub-factors, considering the three segments. Their assessment was conducted from the perspective of slaughter and processing segment (refrigerators). In addition, we used secondary data and interviews with key actors. Through the data collected, it was found that the chains, even inserted a single geographical clipping, have different characteristics, such as: physical infrastructure, economic structure, management, market share, size of transactions, types of distribution channels, structure of distribution in foreign markets, types of transport, types of slaughtering, among others. Regarding coordination, the opinions of respondents disagreed, demonstrating clearly that there is no coordination defined in chain, but that the slaughters and processors are the strongest candidates do coordinate the whole chain. Even with differences in the designs of the two chains, the marks awarded to the drivers (three segments) by two refrigeration units, in most cases followed a similar trend, although not identical assignments of notes. It can be stated from the data that the two reviewed exporter chains have a competitive advantage. However, the livestock production sector had the lowest scores, demonstrating that the State of Goiás, even with comparative advantages, requires changes in management, use of more advanced technologies, and creating incentives for government actions that may be implemented. The other segments, even with the competitive advantages, require joint action in order to maintain their competitive position, and try to it. Some suggestions for joint activities involving the private and public sector were drawn up, namely: support and encourage the technological advancement of the production process and management of farms in the State of Goiás; coordination of production by market demand, adding value beef; improved system of regulation and supervision, cooperation between actors in the chain, diversification of markets for meat products, tax incentives, and improving distribution logistics.
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 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) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,001 | 0,004 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».