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題名：台灣中部地區製造業效率之研究
作者：賴昱禔
作者(外文)：LAI, YU-TI
校院名稱：長榮大學
系所名稱：管理學院經營管理博士班
指導教授：劉春初
學位類別：博士
出版日期：2021
主題關鍵詞：製造業；生產效率；總要素生產力；資料包絡分析；逆資料包絡分析；Manufacturing；Productive Efficiency；Total Factor Productivity；Data Envelopment Analysis；Inverse DEA
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製造業是一國工業體系的核心，亦是台灣經濟成長的重心，其成長狀況直接影響經濟成長的速度和效率，本研究以智慧機械為重心的中台灣為研究區域，效率觀點進行生產力的分析，應用資料包絡分析法(DEA) / 麥氏生產力指數(MPI) / 逆資料包絡分析法(Inverse DEA) 對中台灣五縣市製造業評估生產效率、總要素生產力與技術效率，探討影響生產力變化之因素及預測調整。
本研究發現，金屬機電工業效率分析呈現快速成長趨勢、資訊電子工業為台灣具競爭力之製造業，有經營發展空間。非金屬礦物製品業、其他化學製品業、機械設備製造業、電腦電子產品及光學製品業等4項產業具技術變革創新具有高度競爭力、高度生產動能。在運用逆資料包絡分析法於各製造業中分類預測要求達到效率值發現，以該縣市主要發展的製造產業，會進行較高的投入與產出要素的增減作為調整，提供政策預測配置之參考。
Manufacturing is the core of a country's industrial system as well as manufacturing is the main emphasis of Taiwan's economic growth, and the growth status of which will influence a country's speed and efficiency of economic growth directly. In this study, Central Taiwan, which lays emphasis on smart machinery, was taken as the study area and productivity analysis is conducted from an efficiency perspective. With Data Envelopment Analysis (DEA), Malmquist Productivity Index (MPI) and Inverse Data Envelopment Analysis, the productive efficiency, technical efficiency, and total factor productivity (TFP) of the manufacturing of the five counties and cities in Central Taiwan was evaluated, the factors influencing the change in productivity and prediction adjustment were discussed.
The study found that the efficiency analysis of Metal electromechanical industry showed a rapid growth trend, and the Information-electronics industry is a competitive manufacturing in Taiwan with room for business expansion. [Manufacture of Other Non-metallic Mineral Products], [Manufacture of Other Chemical Products], [Manufacture of Machinery and Equipment], and [Manufacture of Computers, Electronic and Optical Products] are 4 divisions with technological innovation, high competitiveness, and high productivity momentum.
The prediction with inverse DEA, the division of manufacturing requires the achievement of efficiency scores found that: The major division of manufacturing industries developed in the county and city will be adjusted with higher range input and output variables increases and decreases to provide references for policy regarding prediction allocation.
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