在部分國家，鋼鐵產業往往會因為受到政府高度保護而呈現獨占或寡占的 局面，然而受到世界貿易組織之自由貿易政策的影響，全球鋼鐵產業已經面臨 激烈無比的競爭。本研究的主要目的是分析並評估環境的變遷對全球30 家鋼 鐵廠營運效率的影響，特別是研究所得的結果將可以有效地協助效率不佳的鋼 鐵廠商改進其經營績效。 本研究在取得每一家鋼鐵廠商的營運資料後，利用標竿學習以及資料包絡法(DEA)，分別評估30 家鋼鐵廠商的經營績效，並為其找到標竿學習的夥伴； 而且在進一步檢事各群組的生產力指數後，發現擁有較高技術效率與規模效率 的廠商，相對可獲得較佳的生產績效。此外，本研究亦進一步利用鋼鐵廠在 1992年至2003年生產效率的變化模式來分析鋼鐵產業效率在不同時間點的 變化趨勢。整體而言，本研究利用DEA 與Malmquist 生產力指數方法評估鋼 鐵產業的競爭優勢以及標竿學習的實務做法可以為實務界提供個有效的決策支援工具。

In many countries, the steel industry is a highly protected industry that operates in a state of monopoly or oligopoly. However, under the WTO and its policy of trade liberalization, many steel firms have faced more severe and competitive environments. This study intends to find out how the changes of competitive environments affects the operational efficiency of 30 major steelmakers worldwide, and most importantly, to identity how the weakest firms could improve their performance. By using the DEA approach and benchmarking practices, this study obtained each steelmakers' efficiency data, then evaluated how they performed and compared with others in the steel industry, what benchmark objective(s) they should improve, and which company could be their benchmark partner. From the results of examining productivity indicators of three firm clusters, it is indicated that steel firms with higher technical and scale efficiency tend to use their input factors more efficiently and achieve higher productivity performance. The study also investigated the patterns of efficiency change in steel firms from 1992 to 2003 to illustrate improvements over time. This study offers a very useful decision support tool for academicians and practitioners to evaluate competitive advantages and benchmarking practices of firms through DEA and Malmquist productivity index.

This study adopts benchmarking technique and DEA approach to evaluate the operational efficiency of the major integrated steel firms in a worldwide spectrum. Besides, the Malmquist productivity index is used to analyze the productivity changes of firms in the steel industry worldwide. From the analysis of DEA, the results suggest for each sample firm exactly which firm(s) should be the benchmark partner(s) and how much and which input slack should reduce to become more competitive. All the steel firms appear to attain a similar pattern in technology and efficiency improvement. However, from the comparison of long-term productivity indicators among cluster groupings, firms with higher technical efficiency and scale efficiency tend to maintain a more moderate and smooth progression in TFP than those inefficient ones. The major differences in efficiency among these firms are, in fact, caused by the inappropriate use of input resources. Once low efficiency firms can substantially increase their management capability in the use of resources, they will improve their technical efficiency in the same way as their benchmark partners. On the other hand, it is strongly recommended that, for those firms that have better performance, internal benchmarking practice may be useful. The results of this study provide a starting point for managers in steel firms to correctly implement their benchmarking program. However, it should be noted that there are some other critical factors in management and operations which may influence a benchmarking project, including adequate planning, training, open interdepartmental communication, support and commitment by senior management, and a focus on customers and employees. This study contributes to provide the steel firms with a management direction as to how well a firm can enhance its productivity by improving its utilization of input factors in accordance with the DEA analysis.