台灣上市連接器產業公司經營績效之探討 - 資料包絡分析法之應用

台灣的連接器產業在台灣經濟發展中扮演著重要的角色，其產品應用領域包含NB、消費電子、聲學模組、光學、汽車及醫療等；近年來，由於中國的經濟崛起，人口紅利不在，再加上紅色供應鏈快速崛起，導致台灣的連接器廠商獲利受到影響，毛利不斷被壓縮，造成極大的競爭壓力。因此，本研究主要探討台灣上市連接器產業之經營效率，預期從中找出績效最好的標竿企業，比較影響經營效率的各種因素，作為經營績效改善之參考。本研究選擇了台灣上市連接器產業的22家公司，作為經營績效研究的樣本公司，數據採集自2016年至2019年，透過資料包絡分析法(DEA)進行CCR及BCC模型的分析、差額分析及敏感性分析，最後再以Tobit迴歸模型，進行影響經營績效效率值的探討。研究結果顯示: 一、CCR及BCC模式：就個別廠商來看，以太空梭、健和興、鴻名、信邦、維熹及貿聯-KY表現最好，可提供給其他相對無效率的廠商作為經營效率改善之參考。二、敏感性分析：對整體技術效率影響最大的投入及產出項變數為總資產及營業收入淨額，影響最小的則是產出項變數營業利益。三、Tobit迴歸分析：地理位置(X1)、員工教育程度(X2)及董監事(含經理人)持股比例(X6)，呈現正相關顯著；員工流動率(X3)及員工平均年齡(X5)，則呈現負相關顯著。

關鍵字

台灣上市連接器產業公司；資料包絡分析法； Tobit迴歸模型；經營績效

並列摘要

The connector industry plays an important role in the economic development in Taiwan. The product application fields include NB, consumer electronics, acoustic modules, optics, automotive and medical, etc. In recent years, the absence of a demographic dividend, coupled with the rapid rise of the red supply chain due to China's economic rise, resulting in Taiwan's connector manufacturers profit impact, gross margin slack, and have great competitive pressure. Therefore, this paper mainly explores the operational efficiency of Taiwan listed connector industry, and expects to find out the best-performing benchmark enterprises, comparing the factors affecting the efficiency of operation, as a reference for improving business performance. 22 companies listed in Taiwan's markets are selected as the sample companies of operating efficiency study, the data is collected from 2016 until 2019, CCR and BCC models of the data envelopment analysis (DEA) and difference analysis and sensitivity analysis are used to derive findings. Finally, the Tobit regression model is carried out to discuss operating performance efficiency. The results show that: First, CCR and BCC model: in terms of individual manufacturers, the Space Shuttle, K.S. Terminals, Welltend, SINBON, Well Shin and Bizlink performed best, can be provided to other relatively inefficient manufacturers as a reference for operational efficiency improvement. Second, sensitivity analysis: the most impact on the overall technical efficiency of input and output variables for total assets and net operating income, the least impact is the output variable operating benefits. Third, Tobit regression analysis: location (X1), employee education level (X2) and the Stockholding of Directors and Supervisors (X6), showing positive correlation. Employee turnover (X3) and average age (X5) showed negative correlation.