989 resultados para Sugar industry


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Originally: "Confidential".

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At head of title: Department of commerce. Bureau of foreign and domestic commerce. A.H. Baldwin, chief.

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Special agent: Charles F. Saylor.

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Mode of access: Internet.

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Australian sugar-producing regions have differed in terms of the extent and rate of incorporation of new technology into harvesting systems. The Mackay sugar industry has lagged behind most other sugar-producing regions in this regard. The reasons for this are addressed by invoking an evolutionary economics perspective. The development of harvesting systems, and the role of technology in shaping them, is mapped and interpreted using the concept of path dependency. Key events in the evolution of harvesting systems are identified, which show how the past has shaped the regional development of harvesting systems. From an evolutionary economics perspective, the outcomes observed are the end result of a specific history.

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Purpose – The data used in this study is for the period 1980-2000. Almost midway through this period (in 1992), the Kenyan government liberalized the sugar industry and the role of the market increased, while the government's role with respect to control of prices, imports and other aspects in the sector declined. This exposed the local sugar manufacturers to external competition from other sugar producers, especially from the COMESA region. This study aims to find whether there were any changes in efficiency of production between the two periods (pre and post-liberalization). Design/methodology/approach – The study utilized two methodologies to efficiency estimation: data envelopment analysis (DEA) and the stochastic frontier. DEA uses mathematical programming techniques and does not impose any functional form on the data. However, it attributes all deviation from the mean function to inefficiencies. The stochastic frontier utilizes econometric techniques. Findings – The test for structural differences in the two periods does not show any statistically significant differences between the two periods. However, both methodologies show a decline in efficiency levels from 1992, with the lowest period experienced in 1998. From then on, efficiency levels began to increase. Originality/value – To the best of the authors' knowledge, this is the first paper to use both methodologies in the sugar industry in Kenya. It is shown that in industries where the noise (error) term is minimal (such as manufacturing), the DEA and stochastic frontier give similar results.

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An environmental impact study was conducted to determine the Piracicamirim's creek water quality in order to assess the influence of effluents from a sugar industry in this water body. For this, toxicity tests were performed with a water sample upstream and downstream the industry using the microcrustaceans Daphnia magna, Ceriodaphnia dubia and Ceriodaphnia silvestrii as test organisms, as well as physical and chemical analysis of water. Results showed that physical and chemical parameters did not change during the sampling period, except for the dissolved oxygen. No toxicity was observed for D. magna and reproduction of C. dubia and C. silvestrii in both sampling points. Thus, the industry was not negatively impacting the quality of this water body.