臺灣博碩士論文加值系統

油棕櫚是全球熱帶地區最重要的作物之一，特別是在東南亞，其中泰國是世界第三大油棕櫚生產國。泰國以勞動力密集方式生產油棕， 大部分油棕種植區和油棕提煉廠位於泰國南部地區；但是，這一地區的種植園已經達到極限。泰國政府推動幾項有關油棕生產政策，以改善全國油棕產量。這些政策在全國各地普遍實施。因此，本文擬探討泰國四大地區（北、東北、中、南部等四區域）油棕的生產技術效率之差異。
本研究的目的是衡量泰國油棕生產力的技術效率和趨勢。研究將檢視四個地區：北部、東北部、中部和南部，覆蓋全國77個省份。因此，本研究透過四個區域共有77個DMU（決策單位）的樣本來評估油棕生產力的技術效率。採用三階段資料包絡分析模型和Malmquist生產率指數分析從 2007 年至 2016 年四個地區的泰國油棕種植資料。首先， 本研究採用三階段資料包絡分析方法和泰國油棕生產效率的投入導向模型。 資料包絡分析是依據DMU的輸出和輸入變數來衡量經營效率的方法，因此， 選擇變數對於效率的測量是非常重要的。本研究以產油量和產量價格為輸出變數，另以種植面積、肥料、農藥、拖拉機數量及勞動
力等五個輸入變數。此外，兩個環境因素的分析包括溫度和降雨量。最後，Malmquist生產率指數用於衡量油棕生產效率的變化，並通過使用 Malmquist生產率指數方法估計十年以上的油棕生產力趨勢。Malmquist 生產力指數可以分為兩個組成部分，即技術變動和效率變動。Malmquist 生產力指數的效率值等於1表示生產力成長率不變，大於1表示生產力成長率增加，小於 1 表示生產力成長率下降。
研究結果發現，使用三階段 DEA 方法的第 3 階段調整投入的技術效率值低於 DEA方法第1階段的效率值。此外，結果還顯示，南部地區在全區域技術效率最高，其次分別是中部、東北、北部地區。由於技術變動和效率變動趨勢的增長趨勢，泰國油棕產量的Malmquist指數呈上升趨勢，此結果表明生產力成長率為增加，這意味著2007年至2016年泰國油棕生產的生產力有所提高，也就是棕櫚產業永續發展的生產效率。因此，本研究可以向農民、泰國政府及油棕研究所提供重要信息，也可以提供各地區提高生產經營績效方面有用和實際的策略。

Oil palm is one of the most crucial crops in tropical regions worldwide, particularly in Southeast Asia. Thailand is the third largest oil palm producer in the world. In addition, Thailand also has a strong of oil palm production that represents a significant portion of the Thai economy and intensive labor force. The most of oil palm plantation area and oil palm extraction plants are located in Southern region of Thailand; however, the plantation area in this area has reached its limit. The Thai government has released several strong policies to improve oil palm production throughout the country. These policies have been implemented throughout the country, particularly at a regional level. Therefore, technology production of oil palm is variously different across the four regions of Thailand.
The purposes of this study are to measure the technical efficiency and trend of productivity’s change in Thai oil palm production. The study
examined four regions; Northern, Northeastern, Central, and Southern Thailand, covering 77 provinces. Consequently, this study assessed the technical efficiency of oil palm productivity by using a sample of 77 DMUs (decision making units) in the four regions. Secondary data were collected from Thai oil palm plantations in four regions from 2007 to 2016 by using a three-stage data envelopment analysis model and Malmquist productivity index analysis.
Firstly, this study used three-stage data envelopment analysis approach with input-oriented model for measuring efficiency of oil palm production in Thailand. Data envelopment analysis is a measure of performance and output and input variables of each DMU are the basic components of efficiency. Thus, the selection variables are very important in determining the measurement of efficiency. This study considers the output variables that is oil yield and price of quantity and analyzed a total of five input variables, namely plantation area, fertilizer, pesticide, number of tractors and labor force. Furthermore, the analysis of two environmental factors includes temperature and rainfall volume. Finally, Malmquist productivity index was used to measure the changes in oil palm production efficiency and to estimate the oil palm productivity trend in over a ten-year period by using Malmquist productivity index approach. Malmquist Productivity Index can be decomposed into two components, i.e. technical change and efficiency change. Malmquist productivity index’s score with equal 1 represents the unchanged growth rate for productivity, greater than 1 shows the productivity growth, and less than 1 means the productivity decline.
The findings indicate that the technical efficiency scores using the adjusted inputs in stage 3 of the DEA approach were less than the efficiency scores in stage 1 of the DEA approach. Moreover, the results also showed that Southern region had the best scores of technical efficiency throughout the region, followed by Central, Northeastern and Northern region, respectively. Malmquist index of Thai oil palm production showed an upward trend because of the increasing trends found in both the technical change and the efficiency change. Thus, the results showed that the productivity index has increased, which means that the country has improved in productivity for oil palm production in Thailand from 2007 to 2016. The findings from this study contribute to improving efficiency production for sustainable development. Therefore, this study can provide important information to the farmers, Thai government, the oil palm research institutes and the development partners to determine strategies that are useful and practical in raising efficiency performance in each region and to help increase the trend of oil palm productivity index in some areas of Thailand.

摘要 I
Abstract III
Acknowledgements VI
Table of Contents VII
List of Tables IX
List of Figures X
List of Abbreviations XI
1. Introduction 1
1.1 Research Background 1
1.2 Research Problems 4
1.3 Research Motivations 5
1.4 Research Hypotheses 5
1.5 Research Scope 5
1.6 Research Objectives 6
2. Literature Review 7
2.1 Three-Stage DEA Approach 7
2.2 Malmquist Productivity Index 11
2.3 An Overview of Agricultural Development and Oil Palm Plantation in Thailand 16
2.4 Factors Affecting Thai Oil Palm Production’s 23
2.4.1 Input 23
2.4.2 Output 27
2.4.3 Environmental Factors 28
2.5 Theory Framework 29
2.5.1 The Modified Three-Stage DEA Model 32
2.5.2 Malmquist Productivity Index (MPI) 35
3. Research Methodology 38
3.1 Data Sources 38
3.2 Research Areas 38
3.3 Data Collection 41
4. Results and Discussion 44
4.1 Data and Variable Description 44
4.2 Three–Stage DEA Efficiencies and Input Adjustments 45
4.2.1 Outcome of the Stage 1 45
4.2.2 Outcome of the Stage 2 52
4.2.3 Outcome of the Stage 3 56
4.3 Outcome of the Malmquist Productivity Index (MPI) 71
5. Conclusions and Implications 77
6. References 81
Bio–sketch of Author 93

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