Wind power becomes one of the most promising energy sources in the electricity generation sector in Texas over the past decade by declining levelized cost of wind energy. However, recent studies show that the wind farms in Texas are relatively less productive. Hence, this study aims to find out reasons of inefficiencies by constructing a two-stage performance assessment of wind farms in Texas. In the first stage of analysis, comprehensive input- and output-oriented Data Envelopment Analysis (DEA) models are applied to evaluate productive efficiencies of the 95 large utility-scale wind farms by using pre-determined three input and two output variables. The sensitivity analysis is provided for the robustness of the DEA models with different combinations of input and output variables of the original model. The slack analysis and projection data are obtained for inefficient wind farms to find out optimal input-output variables. Tobit regression models are conducted for the second stage of the analysis to investigate the reasons of inefficiencies. DEA results indicate that half of the wind farms were operated efficiently in Texas during 2016. 13 wind farms were performed at the most productive scale size, ten wind farms should reduce their operational size to improve production efficiency, and 72 wind farms have the notable potential to increase their production efficiency by expanding operational sizes with modern wind turbine technologies. The sensitivity analysis shows the importance of each input-output variables. Tobit regression models indicate that elevation of the site, rotor diameter, hub height, and brand of the turbine have significant contributions to the relative efficiency scores of the wind farms, and the age of turbine has a negative impact on the productive efficiency of the wind farms.

Wind power is one of the most promising renewable energy sources that has gained enormous attention, especially in the electricity generation sector over the past decade in the United States. In this study Data Envelopment Analysis (DEA) is implemented to quantitatively evaluate the relative efficiencies of the 236 large utility-scale wind farms. Input- and output-oriented CCR (Charnes, Cooper, and Rhodes) and BCC (Banker, Charnes, and Cooper) models are applied to pre-determined three input and three output variables. The sensitivity analysis is conducted for the robustness of DEA by introducing seven new models with the various combinations of input and output variables of the original model. Tobit regression models are developed for the second stage of the analysis to investigate the effects of specifications of the wind turbine technologies. DEA results indicate that two-thirds of the wind farms are operated efficiently. On average, 70% of the wind farms have a considerable potential for further improvement in operational productivity by expanding these wind farm projects, 24% of them should reduce their operational size to increase their productivity level, and 6% of them are operating wind power at the most productive scale size. Nonparametric statistical tests show that the most efficient wind farms are located in Oklahoma because of the relatively high wind speed resources. Tobit regression model indicates the selection of the brand of the wind turbine has a significant contribution to the productive efficiency of the wind farms. The results of this study shed some light on the current efficiency assessments of the 236 large utility-scale wind farms in the United States and the future of wind energy for both energy practitioners and policy makers.

The average global surface temperature increased by 0.85 °C since 1850 because of irrepressible increase of the concentration of greenhouse gases (GHG). Electricity generation is the primary source of GHG emissions in the United States. Hence, renewable energy sources, which produce a negligible amount of GHG emissions, have gained enormous attention, especially in the electricity generation sector over the past decade. Wind power is the second largest renewable energy source to generate electricity in the United States. Therefore, in this study, a two-stage Data Envelopment Analysis (DEA) is developed to quantitatively evaluate the relative efficiencies of the 39 state's wind power performances for the electricity generation. Both input- and output-oriented CCR (Charnes, Cooper, and Rhodes (1978)) and BCC (Banker, Charnes, and Cooper (1984)) models are applied to pre-determined four input and six output variables. The sensitivity analysis is conducted to test the robustness of the DEA models. Tobit regression models are conducted by using the DEA results for the second stage analysis. The DEA results indicate that more than half of the states operate wind power efficiently. Tobit regression indicates that early installed wind power was more expensive and less productive relative the currently installed wind power. Findings of this study shed some light on the current efficiency assessments of the states and the future of wind energy for both energy practitioners and policy makers.

This study implements radial and non-radial Data Envelopment Analysis (DEA) models to assess eco-efficiency and eco-productivity of the 50 states in the United States in 2018. The models are based on three inputs (capital stock, employment, and energy consumption), a single desirable output (real gross domestic product) and a single undesirable output variable (CO2 emissions). The radial DEA models reveal that at least 32 states are operated efficiently. Five states perform at the most optimal scale size, whereas 17 states have considerable potential to boost their productive efficiencies by enlarging available resources, and 28 states are overinvested in their input variables given their current output levels. The non-radial DEA models show that, overall, the states’ capital efficiency is very high, whereas energy and emission efficiencies are very low. The states’ eco-productivity is relatively higher than the eco-efficiency levels. In the second stage of the analysis, non-parametric statistical tests and Tobit regressions are conducted for further investigation. According to the non-parametric statistical test, high capital stock, labor force, and energy usage do not affect the states’ productive efficiency. However, states with low carbon dioxide emissions have significantly higher eco-efficiency and eco-productivity levels. The Tobit regression results illustrate that nuclear power and renewable energy consumption significantly affect the states’ relative efficiencies.

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第19986号 / 工博第4230号 / 新制||工||1654(附属図書館) / 33082 / 京都大学大学院工学研究科都市環境工学専攻 / (主査)教授 酒井 伸一, 教授 米田 稔, 准教授 平井 康宏 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

近年來台灣筆記型電腦產業，在廠商延續過去多年的擴張競爭力下，在產值與產量上皆有大幅度的成長。但也由於低價風潮的盛行與全球景氣蕭條，使得該產業的獲利大不如從前；加重了國內廠商經營的困境與競爭程度，此時惟有掌握經營績效之廠商才可維持競爭優勢；以因應高度的競爭環境。在此同時，南韓已從金融風暴的創傷下逐漸走出；並挾帶著全球最大TFT-LCD及DRAM的量產國，並從輕薄型機種切入市場以及加入代工訂單的爭奪戰中。而日本擁有全球頂尖的設計創新能力，筆記型電腦自製率仍偏高。因此日、韓一直是台灣的主要競爭對手。 首先藉由資料包絡分析法評估我國筆記型電腦商於2000年至2003年間的經營效率；並為彌補DEA無法做跨時期的分析，應用Malmquist生產力指數予以分析；接著用Tobit迴歸分析來探討廠商無效率的原因。得到以下的結論： (1)於這4年間的技術效率平均值呈現年年上揚的情況，且規模較大的廠商不意謂著經營績效會較好。(2)這4年間的生產力亦是逐年提昇，主要是技術變動所致。(3)在Tobit迴歸分析中，存貨週轉率、總資產週轉率與品牌對效率有正向影響；而TCRI有負向影響。 接著對台、日、韓進行比較分析，得到以下結論：(1)台、日、韓三國的經營績效，以日本最優、韓其次、台最差；但日、韓的整體效率值逐年下滑，而台灣有逐漸改善的趨勢。(2)三國於2000~2001年間生產力皆下降，這與全球景氣蕭條及九一一事件有相當的關聯；2001~2002間由於無線上網的新技術致使消費性機種熱賣，因此於該期間，生產力呈提昇現象。(3)由Tobit迴歸分析得知存貨週轉率、總資產週轉率與經營年限對效率值有正向影響。 / In the recent years, Taiwanese Notebook manufacturers last the past years, extensions to make productive values and production grow up enormously. Due to the low price trend and global business trend stagnancy, resulting to profitability be not as good as the before for this industry. It deepens to operate and complete hard for the domestic manufacturers. At the same time, only the manufacturers that seizing operating the performance will maintain completing advantage to deal with highly completing enviornment. At the same time, South Korea has already got over from the shadow of 1998 crisis; and took along the most global productive country of TFT-LCD and DRAM; going into the market of frivolous type and join a battle of OEM/ODM orders. Japan owns global excellent design and capability of innovation and self-made ratio is still high. Therefore, Japan and South Korea are constantly Taiwanese major rivals. Firstly, it estimates how Taiwan Note Book manufacturers operate in 2000 to 2003 by Data Envelopment Analysis;In order to making up DEA not undertaking time-series analysis, using Malmquist Productivity Index to analyze; utilizing Tobit regression to analyze the factors that producers operate inefficiently. It gets the following conclusions:(1) In these four years, average technical efficiency is taken on rising year by year, and large scale producers do not imply better operating efficiency. (2) In these four years, the productivity is also rised year by year. This is due to technical change. (3) In Tobit regression analysis, there is a positive influence that inventory turnover, total asset turnover and brand affect efficiency; there is a negative influence that TCRI affects efficiency. This study gets the following conclusions;(1) For Taiwanese, Japanese and South Korea’ operating performance, Japan is the excellent, South Korea is the next, Taiwan is the worst. But Japanese and South Korea’ overall efficiency is worse year by year; Taiwan operating performance is gradually improved. (2) These three countries’ productivity decline from 2000 to 2001. It is concerned with global economic recession and 911 incident. The productivity is raised from 2001 to 2002. It results from WLAN type to sell briskly. Turnover ratio of inventory and turnover ratio of total asset tighter operating years all have a positive influence on efficiency.

有鑑於我國與大陸方面是否應簽訂ECFA仍有許多疑慮，本研究欲就香港與大陸所簽訂之CEPA協定對香港銀行業經營效率有何影響加以探討，以便對台灣未來可能簽訂ECFA時提供台灣銀行業相關參考及對策。 本研究針對2000年至2007年的18家香港地區銀行以及30家台灣地區銀行，採用資料包絡分析(DEA)計算業者之經營效率，最後控制銀行業者本身之財務特性及總體經濟環境因素，應用Tobit迴歸比較分析實施CEPA對香港銀行業之影響及台灣與香港業者之差異。 研究結果顯示港銀行業之經營效率八年間均較台灣銀行業為佳，此外CEPA協定之採用整體而言對台灣以及香港銀行業均無顯著影響，雖然協定採用後之第三、四兩年，香港銀行業之效率顯著高於實施後之前兩年與台灣銀行業者，亦即CEPA之效益要到協議三及四之後才顯現出來。因此可知CEPA簽訂後，效益不會立即顯現，須有更多的開放例如CEPA三及四對營業額及資本額的放寬才有可能顯現直接之效益。此點應可作為台灣未來與大陸談判時應考慮之因素。 / Since Taiwan still disputes whether to sign Economic Cooperation Framework Agreement, (ECFA) with mainland China or not, this research tries to analyze the efficient change of Hong Kong banking industry before and after singing Closer Economic Partnership Agreement (CEPA) with mainland China. And hope to gain some understandings about the effect of singing CEPA, so that to provide some strategic references for singing EFCA in the future. The research data draw from 2000 to 2007 of the 18 regional banks from Hong Kong and 30 regional banks from Taiwan. The research applies data envelopment analysis (DEA) to evaluate the operating efficiency of the banks. After controlling banks’ financial characteristics and macro economics variables, the Tobit regression denotes the following suggestions. The efficient of Hong Kong banking industry showed a better efficiency than Taiwan banking industry. After signing CEPA for two years, Hong Kong banking industry finally revealed a significant improvement than first two years as well as Taiwan’s banking industry. The results suggest that signing CEPA does not immediately increase the efficiency of the industry; the agreement might need fewer restrictions, such as fewer amounts of sales restriction and less capital restriction in CPEA III and IV, in order to boost the performance of the industry. The results should provide a good strategic consideration about the future EFCA talk for Taiwan.

Submitted by JOSIANE SANTOS DE OLIVEIRA (josianeso) on 2017-08-01T16:26:56Z No. of bitstreams: 1 Rafael Marques_.pdf: 4496236 bytes, checksum: bab4ea70204769795db496f2150de294 (MD5) / Made available in DSpace on 2017-08-01T16:26:56Z (GMT). No. of bitstreams: 1 Rafael Marques_.pdf: 4496236 bytes, checksum: bab4ea70204769795db496f2150de294 (MD5) Previous issue date: 2017-05-16 / Nenhuma / A melhoria da eficiência e da produtividade nas operações tornou-se um desafio constante para as empresas de serviços. Apesar da relevância do tema, trabalhos que exploram a eficiência e produtividade em operações de serviços, por meio de elementos objetivos, são escassos na literatura. Ademais, pesquisas que abordam eficiência e produtividade têm sido direcionadas para o ambiente de manufatura. Neste sentido, a avaliação da eficiência nas operações de serviços, baseado em elementos concretos, torna-se uma importante ferramenta para as empresas tomarem decisões. Este estudo analisa a eficiência e as influências dos clientes na operação de uma locadora de veículos. A eficiência foi analisada longitudinalmente baseada na avaliação dos contratos de serviços por meio da Análise Envoltória de Dados (DEA) e Análise de Variância (ANOVA). Três perspectivas foram consideradas na análise da eficiência, a saber: perspectiva do cliente, perspectiva do prestador de serviços e perspectiva integrada. As influências dos clientes na operação foram analisadas por meio da técnica estatística Regressão Tobit. Os resultados mostram que a eficiência na perspectiva dos clientes é significativamente diferente da eficiência para o prestador de serviços e eficiência integrada. Ainda, observa-se que os clientes influenciam, substancialmente, a eficiência da operação do serviço por meio de suas características. / The efficiency and productivity improvement in operations has become a constant challenge for companies and services. Although the relevance of this issue, there are few academic works regarding efficiency and productivity in service operations by objective elements. Moreover, researches concerning efficiency and productivity have been oriented to manufacture environment. In this sense, the efficiency evaluation in the service operations based on concrete elements becomes an important tool for the decision making of companies. This paper analyses the efficiency and the influence of clients in the operation of a car rental company. The efficiency was longitudinally analyzed based on the evaluation of service contracts by the Data Envelopment Analysis (DEA) and Analysis of Variance (ANOVA). Three perspectives were considered in the efficiency analysis: client perspective, service provider perspective and integrated perspective. The influences of the clients in the operation were analyzed by Tobit Regression statistic technique. The results show that the efficiency based on the client perspective is significantly different from the ones from service provider and integrated perspectives. Moreover, it is observed that the clients influenced significantly the efficiency in service operations through its characteristics.

都市經濟發展同時卻也造成環境衝擊的影響，在永續發展理念下，經濟和環境議題調和為重要議題，過去評估都市永續性主要透過永續指標建構、生態足跡、能值分析等方法，但缺乏將環境和經濟兩者同時考量，因而有經濟-生態效率（Eco-efficiency）評估方式產生。本文嘗試利用此評估方式於探討台灣在民國85、90及95年經濟與環境變化情形，並分析哪些縣市為發展上具有效率以及影響縣市經濟-生態效率上差異性原因。本研究第一階段利用可處理多投入及多產出之資料包絡分析計算效率，第二階段則將以都市發展程度等為原因探討對於縣市效率值變動影響情形。 研究結果顯示，縣市中以北部縣市效率值較高而南部效率值較低，個別縣市觀察以台北市、新竹縣、新竹市、台中市、嘉義市和台東縣為三個年度中皆具有效率的縣市。而縣市欲提升效率值則需從汽柴油銷售量及用電量著手；此外，總用水量和二、三級產業就業員工數為縣市經濟-生態效率值之優勢因素。更近一步透過Tobit迴歸分析影響縣市效率值差異性原因，都市發展程度及污染性產業比例與效率值呈現負向變動，而每人每年可支配所得高低則呈正向變動。因此，建議政府對產業的汙染管制宜改善，而於都市發展程度較高的縣市提升能源使用效率並降低對環境影響，以提升縣市發展之經濟-生態效率。 關鍵詞：經濟-生態效率、資料包絡分析、Tobit迴歸分析 / Urban development creates economic values and results in environmental impact at the same time. Based on the concept of sustainable development, several methods, such as sustainable indicator frameworks, ecological footprints, urban metabolism, were reported to assess urban sustainability. However, these methods seldom focus on the relation between environment and economy. Therefore, World Business Council proposed Eco-efficiency. This research tried to apply Eco-efficiency to analyze which cities/counties are relatively eco-efficient and find causes bringing about discrepancies among twenty-two cities/counties in Taiwan. In the first stage, this research applies Data Envelopment Analysis(DEA) to figure out Eco-efficiency scores and applies Tobit regression method to analyze in the second stage. The results show that efficiency scores of northern cities/counties are higher than other areas and the ones of southern cities/counties are lower above four areas. Further discussion of analyzing from individual county/city perspectives, the efficiency scores of Taipei city, Hsinchu county, Hsinchu city, Taichung city, Chiayi city and Taitung county are relatively better in 1996, 2001 and 2006. Within comparatively inefficient cities/counties, oil consumption and electricity need to reduce. Water consumption and industry employees are superior factors in twenty-two cities/counties. Furthermore, the intensity of urban development and polluting industry ratio of second and third industries have significant positive effects on the eco-efficiency scores. Disposable income per person per year has significant positive effect on the eco-efficiency scores. Thus, this research suggests that government should improve the regulation on industry pollution. In addition, for those counties/cities with high intensity urban development need to ameliorate energy efficiency and reduce environmental impact. Key words：Eco-efficiency、Data Envelopment Analysis、Tobit regression

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