臺灣博碩士論文加值系統

近年來，伴隨著人們購物模式的改變，以及對於獲得商品時效性的需求，物流運輸產業有著極大的轉變。在大數據的時代下，物流運輸產業與跨境電子商務的結合，第三方物流(Third-Party logistics, 3PL)公司提供更便利、更快速的運送服務，相較於傳統的物流運輸公司勢必遭受嚴重的衝擊，唯有透過轉型才能有效提升市場競爭力。本研究探討台灣與中國兩岸物流上市公司之營運績效差異，並分析影響其經營效率之因素。本研究選取台灣18家和中國22家物流上市公司為受評單位，研究期間為2014年至2016年，應用資料包絡分析法(Data Envelopment Analysis, DEA)、Malmquist生產力指數及System分析法，評估台灣與中國物流上市公司之間營運績效的優劣。實證結果顯示，兩岸相對較無效率之物流運輸公司，主要原因為規模無效率造成整體技術效率不佳；均呈現規模報酬遞減，差額變數分析提供相對效率較差的物流上市公司改善的方向。由System DEA比較分析中可發現，雖然兩岸物流營運效率前端的企業家數持平，但台灣佔後半段名次的比率逐年增加，使台灣物流上市公司整體營運績效差距被中國大陸拉開。

In recent years, People change the way of shopping, as well as the timeliness of obtaining commodity demand. Leading to logistics industry has the enormous transformation. Nowadays, people are going to the era of big data, the logistics and transportation industry combined with Cross-Border e-Commerce. In addition, Third-Party logistics companies provide more convenient and faster delivery services. The traditionallogistics companies will be a big challenge.Transformationbe able to enhance the market competitiveness.In this research, we wouldevaluate the performance evaluation of listed logistics companies between Taiwan and China using Data Envelopment Analysis (DEA) , Malmquist Productivity Index and System DEA , from 2014 to 2016. There are 18 Taiwanese and 22 Chinese logistics listed companies as the unit in this evaluation. Compare the performance between Taiwan and China.According to empirical results, we find that the cause of the companies inefficient reasons, most of them are due to the scale inefficiency caused .The Slack Variable Analysis provide suggestions for improvement. In the System DEA, although the number of the great proformance companies is flat,but the proportion of Taiwan accounted for the second half of the ranking increased year by year.So that the overall performance of cross-strait logistics listed companies operating performance gap.

摘要 i
Abstract ii
目錄 iii
表目錄 iv
圖目錄 vi
第一章　緒論 1
1.1　研究背景 1
1.2　研究目的 3
1.3　研究範圍 3
1.4　研究架構 3
第二章　文獻回顧 5
2.1物流產業介紹 5
2.2績效評估 16
2.3資料包絡分析法及Malmquist生產力指數 20
2.4 物流業績效評估之相關文獻 22
第三章　研究方法 24
3.1 資料包絡分析法(DEA)介紹 24
3.2 資料包絡分析法之模型 25
3.3 Malmquist生產力指數 29
3.4 System DEA 31
第四章　實證結果 33
4.1 資料來源及變數選擇 33
4.2 實證結果分析 35
第五章　結論與建議 51
參考文獻 53
附錄 57

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三、網路文獻
中華民國物流協會，http://www.talm.org.tw/，點閱日期(2017/05/30)
中華民國交通部，www.motc.gov.tw/，點閱日期(2017/05/30)
中國物聯網，http://www.iotcn.org.cn/，點閱日期(2017/05/30)
中國物流與採購聯合會，http://www.chinawuliu.com.cn/，點閱日期(2017/05/30)