Notice bibliographique
Résumé
The broiler farming sector in tropical area suffer from high temperature and humidity stress and reduced daily bird growth rate. Small scale broiler farms at Sultanate of Oman has been performing poorly due to many constrains, including poor poultry farming practices, climate condition variability, feed grain price increase. The import of frozen poultry with cheap price and feed cost increased after Ukraine conflict and global food security issue significantly affect broiler cost of production and farming economic sustainability. Poultry feeding cost increased by 36% compared to last year due to corn and soybean grain price increased and exposed farmers to high risk and income uncertainties and jeopardize food security sustainability. The study applied Monte Carlo Simulation approach to assess risk management strategies and economic sustainability of three production level, products mix alternative under deferent market constrains. The broiler products mix and marketing constrains were examined considering different risk preference and ARAC of decisions makers. The stress analysis performed to test economic performance of alternative production strategies and identify factors affect broiler farming continuity and resilience. The overall results showed that broiler marketing risk and sale revenue volatilities is a highly uncertain and dynamically integrated complex system. Sale incentive policy need to be addressed and controlled through appropriate risk assessment and mitigation strategies and optimization production operation and control cost increase through vulnerability assessment. The net profit (baseline) scenarios with right production level and products mix following profitable market channels is more risk-efficient and sustainable compared to products mix with over supply production and without fast marketing access support channels. The study performed stochastic efficiency with respect to a function (SERF) and calculate Certain equivalent (CE) figure to rank alternative stress management strategies under stress situation. Stress management analysis showed that demand for parts and fresh products with sale revenue decline are risk averse and has highest CE figures followed by (cost frozen) products at all ARAC. The risk premium and willingness to pay analysis showed that (cost parts) products has highest risk premium figures followed by (cost fresh) and (demand frozen) products compared to baseline. The risk of cost increase needs to be monitored and controlled to avoid inside organization risk vulnerability. Risk premium (RP) needed to change from (cost fresh) to (cost frozen) products is RO 67,553 for risk neutral absolute risk aversion coefficient (ARAC). The study showed risk premium (RP) need to be paid to motivate a change from (demand frozen) alternative to (demand fresh) products activities is RO 24,928 and to change from (demand frozen) to (demand parts) is RO 64,379 for risk neutral absolute risk aversion coefficient (ARAC). Marketing incentive programs and regulating market are needed to understand broiler business risk and avoid significant loss due to sale delay and improve risk mitigation programs and imposed anti-dumping and countervailing duties on broiler products import. The risk of feed cost increase needs to be monitored and subsidized by Government to mitigate broiler farming risk and maintain business sustainability.
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) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 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 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 ».