The Effect of Quality‐Environmental Investment on Horticultural Firms' Competitiveness
Bibliographic record
Abstract
The aim of this paper is to analyze the impact that environment‐friendly and management‐quality improvements have on the firm's competitiveness (profitability and market share) within the fresh fruit and vegetable sector. Andalusian farming/marketing entities (producer organizations) serve as a reference for our analysis. For these entities, there are subsidy programs aimed at developing quality and environmental practices. Such programs are a top priority for the CAP's Common Market Organizations. An analysis of a simultaneous equations model is suggested, considering the distinguishing effect of quality‐environmental investment and the possible endogeneity problems among the variables. The results show a positive correlation between the application of the aforementioned activities and the competitiveness of the horticultural firms. L'objectif de ce travail c'est d'analyser l'impact des pratiques de production favorables à l'environnement ainsi que de la gestion de la qualité (rentabilité et part du marché) par rapport aux secteurs des fruits et légumes frais. Les organismes de commercialisation agricole d'Andalousie (organ‐ismes de production) représentent un point de référence pour notre analyse. Ces organismes bénéficient de programs d'aide au développement de la qualité et des pratiques favorables à l'environnement. Ces pro‐grammes constituent une priorité majeure pour les Organisations du Marché Commun dans le cadre des Politiques Agricoles Communes (PAC). Nous proposons ici une analyse d'un modèle aux équations simul‐tanées considérant l'effet caractéristique d'un investissement de qualité de l'environnement ainsi que les possibles problèmes à caractère endogène parmi les variables. Le résultat met en évidence une corrélation positive entre l'application des activités précédemment citées et la compétitivité des entreprises horticoles.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".