Air transportation is a paramount element within the transport infrastructure of any country. In recent years, several factors have led to an increased demand in the civil aviation industry in Brazil, putting pressure on the country’s airport infrastructure, which by itself justifies industry-related efficiency studies. Although the airport efficiency analysis is widely discussed in the literature, studies aiming to compare public and private Brazilian international airports are still scarce. The main objective of this study is to comparatively analyze the efficiency of public and private Brazilian international airports. To do so, efficiency was studied under two mathematical approaches: the two-stage DEA model and the Malmquist Index. Subsequent statistical analyses show a significant difference in efficiency between government-managed airports and those under concession to the private sector.
The main purpose of this paper is to analyze the efficiency of Clean Development Mechanism (CDM) projects implemented worldwide and understand their main characteristics, seeking to support investment decisions and expand the scientific understanding of the financial and environmental impact of these projects. To achieve this goal, a sample of 2352 CDM projects was selected from a United Nations Framework Convention on Climate Change (UNFCCC) database and analyzed first with a two‐stage data envelopment analysis (DEA) model that allowed the evaluation of the financial return and environmental efficiency of these projects. DEA results provide an efficiency ranking that was then analyzed with a classification tree (CHAID algorithm), revealing some main characteristics of the projects with higher efficiencies, like their sizes, locations, and type of CDM. CDMs are projects that demand a significant quantity of resources and effort to produce the expected outcomes, so it is crucial for public managers and investors to know the project profiles that generate the best financial and environmental results. In this sense, this study presents a completely original methodology for this kind of analysis and reveals important insights for these agents and researchers in this field.
Planejamento da safra de soja no Oeste do Paraná RESUMOA soja é o grão mais produzido no Brasil e tem dado ao país o título de maior exportador desta commodity. A pouca quantidade de produto disponível internamente e a alta do dólar tem elevado o seu preço a valores recorde, com desdobramentos na área de cultivo, que vem aumentando com o passar dos anos. Este artigo tem o objetivo de aplicar modelos de previsão de demanda para o cenário de rendimento de soja no Oeste do Paraná e discutir os seus resultados quanto aos erros em relação aos valores reais. Dados referentes ao rendimento do grão por hectare no Oeste do Paraná, entre os anos de 1980 e 2014, foram coletados e submetidos a quatro testes de hipóteses para determinar os modelos de previsão mais adequados para comparação. Os resultados obtidos validaram a modelagem, que pode servir de base para o planejamento dos produtores rurais em relação às estimativas de rendimento de soja no curto prazo.Palavras-chave: Soja, previsão de demanda, séries temporais.
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ABSTRACTSoybean is the most produced grain in Brazil and has given the country the title of largest exporter of this commodity. The small amount of internally available product and the Dollar high exchange rates have raised its the price to record levels, with extensions in the harvesting area, which has been increasing over the years. This article aims to apply forecasting methods for soybean yield scenario in western Parana and to discuss the results of the errors against the original values. Data on the grain hectare yield in the west of Parana were collected, between the years of 1980 and 2014, and four tests of hypotheses were applied to point out the most appropriate forecasting methods for comparison. The results validated the model, which may become the basis for the farmers' crop planning regarding soybean yield in the short-term period.
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