| dc.creator | Vlontzos G., Pardalos P.M. | en |
| dc.date.accessioned | 2023-01-31T11:37:06Z | |
| dc.date.available | 2023-01-31T11:37:06Z | |
| dc.date.issued | 2017 | |
| dc.identifier | 10.4018/978-1-5225-2107-5.ch001 | |
| dc.identifier.isbn | 9781522521082; 1522521070; 9781522521075 | |
| dc.identifier.uri | http://hdl.handle.net/11615/80711 | |
| dc.description.abstract | Efficiency assessment in agriculture is a research field were quite important methodologies have been implemented. Data Envelopment Analysis (DEA) in one of the most recognized approaches due to the considerable advantages of it. In this paper the implementation of DEA Window analysis assesses efficiency scores of the primary sectors of EU member states on both operational and environmental level, verifying considerable efficiency differences among them and a continuous improvement after the application of the latest Common Agricultural Policy (CAP) reform. Regarding prognostication of crop and animal output, as well as Green House Gas (GHG) emissions, the application of Artificial Neural Networks (ANNs) is being proposed, succeeding satisfactory quality characteristics for the models being proposed for operational and environmental predictions in EU agriculture. © 2017, IGI Global. All rights reserved. | en |
| dc.language.iso | en | en |
| dc.source | Driving Agribusiness With Technology Innovations | en |
| dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85027339260&doi=10.4018%2f978-1-5225-2107-5.ch001&partnerID=40&md5=4e3e215aae1bdce7dc32b607aadcdcf4 | |
| dc.subject | IGI Global | en |
| dc.title | Assess and prognosticate operational and environmental efficiency of primary sectors of EU countries: Implementation of DEA window analysis and ANNs | en |
| dc.type | bookChapter | en |
