Template-Type: ReDIF-Article 1.0 Author-Name: Vladimír KONEČNÝ Author-Workplace-Name: Department of Computer Science, Faculty of Business and Economy, Mendel University in Brno, Brno, Czech Republic Author-Name: Oldřich TRENZ Author-Workplace-Name: Department of Computer Science, Faculty of Business and Economy, Mendel University in Brno, Brno, Czech Republic Author-Name: Eliška SVOBODOVÁ Author-Workplace-Name: Department of Regional and Business Economics, Faculty of Regional Development and International Studies, Mendel University in Brno, Brno, Czech Republic Title: Classification of companies with theassistance of self-learning neural networks Abstract: The article is focused on rating classification of financial situation of enterprises using self-learning artificial neural networks. This is such a situation where the sets of objects of the particular classes are not well-known. Otherwise, it would be possible to use a multi-layer neural network with learning according to models. The advantage of a self-learning network is particularly the fact that its classification is not burdened by a subjective view. With reference to complexity, this sorting into groups may be very difficult even for experienced experts. The article also comprises the examples which confirm the described method functionality and the neural network model used. A major attention is focused on the classification of agricultural companies. For this purpose, financial indicators of eighty one agricultural companies were used. Keywords: artificial intelligence, neural network, Kohonen network, learning, classification Journal: Agricultural Economics Pages: 51-58 Volume: 56 Issue: 2 Year: 2010 DOI: 10.17221/60/2009-AGRICECON File-URL: http://agricecon.agriculturejournals.cz/doi/10.17221/60/2009-AGRICECON.html File-Format: text/html X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/age-201002-0001.txt Handle: RePEc:caa:jnlage:v:56:y:2010:i:2:id:60-2009-AGRICECON Template-Type: ReDIF-Article 1.0 Author-Name: Jaroslav SEDLÁČEK Author-Workplace-Name: Faculty of Economics and Administration, Masaryk University, Brno, Czech Republic Title: The methods of valuation in agricultural accounting Abstract: This paper deals with the valuation of the biological assets and agricultural production. There are analyzed two approaches: Czech and international. The International Accounting Standards are emulative of more authentic presentment of economic processes in agricultural activities than Czech accounting legislation. From the comparison the both approaches accrued some differences, which can influent the financial statements of enterprises. The causation of main difference appears an application of fair value, which is prescribed for biological assets and agricultural production in international accounting standards. In international accounting standards is preferred principle of fair and true view, while in Czech accounting is preferred prudence principle. Keywords: biological assets, agricultural production, recognition of assets, methods of valuation, accounting procedure, fair value, historical cost, impairment, cost model, fair value model Journal: Agricultural Economics Pages: 59-66 Volume: 56 Issue: 2 Year: 2010 DOI: 10.17221/1487-AGRICECON File-URL: http://agricecon.agriculturejournals.cz/doi/10.17221/1487-AGRICECON.html File-Format: text/html X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/age-201002-0002.txt Handle: RePEc:caa:jnlage:v:56:y:2010:i:2:id:1487-AGRICECON Template-Type: ReDIF-Article 1.0 Author-Name: XU Pei Author-Workplace-Name: School of Agriculture and Natural Resources, State University of New York at Morrisville, Morrisville, New York, U.S.A. Author-Name: Shi ZHENG Author-Workplace-Name: School of Business, Renmin University of China, Beijing, Beijing, China Author-Name: Mesbah MOTAMED Author-Workplace-Name: Department of Agricultural Economics, Purdue University, West Lafayette, Title: Perceived risks and safety concerns about fluid milk among Chinese college students Abstract: The study uses the questionnaire information collected through personal interviews with college students at a large university in Beijing, China to discuss the students' perceived milk risks and their milk safety concerns. We analyzed the milk risks perceived by students and found out that the top three listed risks are: (1) the use of low quality materials in milk packaging; (2) bacteria contaminations in milk production and processing; and (3) unsafe milk caused by the use of cow antibiotics. The binomial probit regression analysis shows that the health conscious milk consumers who consume milk frequently are likely to be worried about the safety of milk. Wealthy students from a household of three members or more are likely to be concerned about the milk safety. This study demonstrates that the current government efforts to raise milk consumption among college students are insufficient. Policies that reduce the perceived risks can be an effective strategy to raise milk consumption among the educated youth. Keywords: perceived milk risks, milk consumption behaviour, Chinese college students' milk consumption, milk safety regulations Journal: Agricultural Economics Pages: 67-78 Volume: 56 Issue: 2 Year: 2010 DOI: 10.17221/18/2009-AGRICECON File-URL: http://agricecon.agriculturejournals.cz/doi/10.17221/18/2009-AGRICECON.html File-Format: text/html X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/age-201002-0003.txt Handle: RePEc:caa:jnlage:v:56:y:2010:i:2:id:18-2009-AGRICECON Template-Type: ReDIF-Article 1.0 Author-Name: Edward Ebo ONUMAH Author-Workplace-Name: Department of Agricultural Economics and Rural Development, Georg-August University, Göttingen, Germany Author-Name: Bernhard BRÜMMER Author-Workplace-Name: Department of Agricultural Economics and Rural Development, Georg-August University, Göttingen, Germany Author-Name: Gabriele HÖRSTGEN-SCHWARK Author-Workplace-Name: Department of Animal Sciences, Georg-August University, Göttingen, Germany Title: Productivity of the hired and family labour and determinants of technical inefficiency in Ghana's fish farms Abstract: This paper examines the productivity of hired and family labour and determinants of technical inefficiency of fish farms in Ghana. A modified Cobb-Douglas stochastic frontier production function which accounts for zero usage of family and hired labour is employed on cross-sectional data of 150 farmers collected in 2007. The results reveal that family labour, hired labour, feed, seed, land, other costs and extension visit have a reasserting influence on fish farm production. Findings also show that family and hired labour used for fish farming production in Ghana may be equally productive. The combined effects of operational and farm specific factors (age, experience, land, gender, pond type and education) influence technical inefficiency although individual effects of some variables may not be significant. Mean technical efficiency is estimated to be 79 percent. Given the present state of technology and input level, the possibility of enhancing production can be achieved by reducing technical inefficiency by 21 percent through adoption of practices of the best fish farm. Keywords: Ghana, fish farms, technical inefficiency, hired and family labour, stochastic frontier Journal: Agricultural Economics Pages: 79-88 Volume: 56 Issue: 2 Year: 2010 DOI: 10.17221/38/2009-AGRICECON File-URL: http://agricecon.agriculturejournals.cz/doi/10.17221/38/2009-AGRICECON.html File-Format: text/html X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/age-201002-0004.txt Handle: RePEc:caa:jnlage:v:56:y:2010:i:2:id:38-2009-AGRICECON Template-Type: ReDIF-Article 1.0 Author-Name: M. Metin ARTUKOGLU Author-Workplace-Name: Department of Agricultural Economics, Ege University, Faculty of Agriculture, Bornova-Izmir, Turkey Author-Name: Akin OLGUN Author-Workplace-Name: Department of Agricultural Economics, Ege University, Faculty of Agriculture, Bornova-Izmir, Turkey Author-Name: Hakan ADANACIOGLU Author-Workplace-Name: Department of Agricultural Economics, Ege University, Faculty of Agriculture, Bornova-Izmir, Turkey Title: The efficiency analysis of organic and conventional olive farms: Case of Turkey Abstract: This paper investigates technical and economically efficiency of 62 organic and 62 conventional olive producing farms in Turkey. According to the study results; by using the CRS model which is input and output-oriented, the average technical efficiency of organic olive farms is 67.68%, the average technical efficiency of conventional olive farms is 47.93%. The technical efficiency of the output-oriented VRS model is 74.78%, and the technical efficiency of the input-oriented VRS model is 93.46%. Also, considering the same model, the average efficiency of the conventional olive farms in the input and output are 59.58% and 94.97%, respectively. Therefore, according to the Data Envelopment Analysis, the technical efficiency in conventional olive farms is less than in the organic ones. When the farms have been evaluated one by one in the light of the total potential improvement values, inputs and outputs, improvement is needed in all values. Keywords: olive, efficiency analysis, farm efficiency, data envelopment analysis Journal: Agricultural Economics Pages: 89-96 Volume: 56 Issue: 2 Year: 2010 DOI: 10.17221/620-AGRICECON File-URL: http://agricecon.agriculturejournals.cz/doi/10.17221/620-AGRICECON.html File-Format: text/html X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/age-201002-0005.txt Handle: RePEc:caa:jnlage:v:56:y:2010:i:2:id:620-AGRICECON