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Productivity Growth in the Transportation Industries in the United States: An Application of the DEA Malmquist Productivity Index
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作者 Jaesung Choi David C. Roberts EunSu Lee 《American Journal of Operations Research》 2015年第1期1-20,共20页
This study reviews productivity growth in the five major transportation industries in the United States (airline, truck, rail, pipeline, and water) and the pooled transportation industry from 2004 to 2011. We measure ... This study reviews productivity growth in the five major transportation industries in the United States (airline, truck, rail, pipeline, and water) and the pooled transportation industry from 2004 to 2011. We measure the average productivity for these eight years by state in each transportation industry and the annual average productivity by transportation industry. The major findings are that the U.S. transportation industry shows strong and positive productivity growth except that in the years of the global financial crisis in 2007, 2008, and 2010, and among the five transportation industries, the rail and water sectors show the highest productivity growth in 2011. 展开更多
关键词 DEA MALMQUIST PRODUCTIVITY Index PRODUCTIVITY Growth U.S. TRANSPORTATION Industry
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Forecasting Oil Production in North Dakota Using the Seasonal Autoregressive Integrated Moving Average (S-ARIMA) 被引量:1
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作者 Jaesung Choi David C. Roberts EunSu Lee 《Natural Resources》 2015年第1期16-26,共11页
North Dakota’s oil production has been rapidly increasing during the past several years. The state’s oil production in March 2013 even increased to more than twice the quantity produced in March 2011, and the estima... North Dakota’s oil production has been rapidly increasing during the past several years. The state’s oil production in March 2013 even increased to more than twice the quantity produced in March 2011, and the estimated Bakken Formation reserves were reported very large compared with those of the United Arab Emirates. It eventually makes a question to us of how much oil will be able to be actually extracted with currently available technologies. To answer this question, this paper forecasts future oil development trend in North Dakota using the Seasonal Autoregressive Integrated Moving Average (S-ARIMA) model. Nonstationarity derived from a stochastic trend and the abrupt structural change of oil industry was a big potential problem, but through the Quandt Likelihood Ratio test, we found break points, which allowed us to select a model fitting period suitable for the S-ARIMA method to provide accurate statistical inference for the historical period. The seven major oil producing counties were investigated to determine whether the current oil boom was consistent across all oil fields in North Dakota. Empirical estimates show that North Dakota’s oil production will be more than double in the next five years. What we can predict with great certainty is that North Dakota’s influence over domestic and global oil supply systems will increase in the near future, especially over the next five to six years. This is good news for those who are concerned about domestic energy security in the USA. 展开更多
关键词 Bakken FORMATION Forecasting NORTH Dakota OIL S-ARIMA
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Reshaping Tribal Road Network Using Public Information
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作者 Jaesung Choi EunSu Lee David C. Roberts 《Journal of Geographic Information System》 2014年第6期594-604,共11页
The area with the fastest growing Native American population in North Dakota is the Fort Berthold Reservation. State and federal road information available to the public is not identical in terms of the number of phys... The area with the fastest growing Native American population in North Dakota is the Fort Berthold Reservation. State and federal road information available to the public is not identical in terms of the number of physical road segments or in the attribute information provided for the road network. In this study we develop: 1) a navigable road network achieved by improving connectivity among road segments, updating road information, and making a comprehensive network;and 2) a standard process for integrating the state and federal local road information. The standard process broadly consists of three Parts: 1) combining road segments from each source;2) providing legitimacy to snapping distance;and 3) performing a snapping based on the result of Part 2 to connect those road segments, which remained unconnected from Part 1. The findings show that data on local roads on the Fort Berthold Reservation from the two different sources are joined through the standard process, and the process saves considerable time and resources required for fixing the road network. The standard process that has been developed here can be applied to a variety of other Indian road information integration projects to join not only physical road segments, but also plural attribute information. The process will also be useful for a variety of other projects integrating road information, which is available to the public, in order to overcome financial and time limitations. 展开更多
关键词 GIS Standard Process TRIBAL ROADS GEOPROCESSING TOPOLOGY ERROR ERROR INSPECTION
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