Results 191 to 200 of about 4,585,845 (309)

Advancing European Plant Variety Registration: Data‐Driven Insights and Stakeholder Perspectives

open access: yesAgribusiness, EarlyView.
ABSTRACT Efficient plant variety registration is crucial for fostering innovation in the European Union, yet the current regulatory framework is complex and faces calls for reform. This study provides data‐driven evidence to inform the ongoing legislative debate by employing a mixed‐methods approach.
Sergio Urioste Daza   +2 more
wiley   +1 more source

Mapping the Innovation DNA of Agribusiness Firms: A Multi‐Method Analysis of Strategic Capabilities and Performance

open access: yesAgribusiness, EarlyView.
ABSTRACT Innovation is essential for competitiveness in agribusiness facing dynamic environments. This study examines how market orientation, marketing, relational, and social capabilities influence innovation performance. Using data from 751 Spanish firms and a multi‐method approach that integrates Structural Equation Modeling (PLS‐SEM), Necessary ...
Beatriz Corchuelo Martínez‐Azúa   +1 more
wiley   +1 more source

Cost‐Benefit Analysis of the European Union Carbon Border Adjustment Mechanism in Fertilizer Trade

open access: yesAgribusiness, EarlyView.
ABSTRACT The carbon border adjustment mechanism (CBAM), launching 2026, will charge EU importers for embedded carbon emissions, aiming to reduce emissions but raising import costs. Shifts in demand following implementation may reduce carbon emissions, but importers will bear the cost of increased prices.
Natalie Crisci   +3 more
wiley   +1 more source

The Geography of Success: A Spatial Analysis of Export Intensity in the Italian Wine Industry

open access: yesAgribusiness, EarlyView.
ABSTRACT This paper investigates the paradox of how Italy's fragmented, SME‐dominated wine industry achieves global export success. Moving beyond purely firm‐centric explanations, we test whether export intensity is spatially dependent, clustering geographically in regional ecosystems.
Nicolas Depetris Chauvin, Jonas Di Vita
wiley   +1 more source

Which Method Best Predicts Postoperative Complications: Deep Learning, Machine Learning, or Conventional Logistic Regression?

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
Deep learning has shown promise in predicting postoperative complications, particularly when using image or time‐series data. However, on tabular clinical data such as the NCD, it often underperforms compared to conventional machine learning. Integrating multimodal data may enhance predictive accuracy and interpretability in surgical care.
Ryosuke Fukuyo   +4 more
wiley   +1 more source

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