面對全球ICT投資成長趨勢，帶來了資訊服務業的龐大商機，引起各資訊服務企業投入競爭，企業必須不斷強化競爭優勢，採行適當措施以調整企業本身體質。企業利用既有資源的互補、結合，可使企業毋須額外投入資源或投入有限資源情況下達到提升企業競爭力目的，稱為策略聯盟。 企業策略聯盟時，須同時考量企業內部經營績效與尋求外部聯盟的企業狀況，如何有效選擇聯盟合作企業，以及聯盟後是否能有效提升企業競爭力，實為當今企業管理者在面臨嚴苛經營環境必須面對專注的課題。 企業管理透過績效評估工具，可使管理者瞭解資源運用的效果，並可作為企業未來資源調配的參考，使企業資源運用能與經營目標結合。 灰預測(Grey Prediction)為根據過去簡單歷史資料即可準確推估未來，為衡量企業未來表現之科學評估方法；資料包絡分析法 (Data Envelopment Analysis，DEA)用於解決多投入多產出項問題，利用客觀計量運算及邏輯推導，於企業進行策略聯盟時，最適合應用此方法作為聯盟對象之選擇。 本研究建立台灣資訊服務業進行策略聯盟時之績效評估模式，提供管理者選擇最適聯盟對象之決策參考，藉以提升企業經營效率，強化競爭能力。 / The growing trend of global investments in ICT has brought enormous opportunities in the information service industry. Under this trend, companies must continue to strengthen their competitive advantages. The integration of existing and/or complementary resources across different companies through co-operation could allow an individual enterprise to limit resource input and therefore achieve better competitiveness. This concept is known as strategic alliances. To form a strategic alliance, a company must consider both internal operating performance and external business conditions. How to choose a partner and determine whether the alliance could effectively enhance the competitiveness of the business should be the focuses of today's business managers. Through the use of performance evaluation tools, the managers of an enterprise can understand the efficiency of resource utilization, which can in turn be used as a reference for future resource allocation. Company resources can therefore be applied to the business objectives of the enterprise more efficiently. Grey prediction is a scientific assessment method that can accurately estimate future simply based on historical data. It can therefore be used to estimate the future performance of the company. Data Envelopment Analysis (DEA) is a method that deals with multi-input and multi-output scenarios by using objective measurement of operations and logical deductions. When a business enterprise plans to form a strategic alliance, DEA is the most suitable method to be used to select a partner. This study establishes the performance evaluation model of strategic alliances between business enterprises within the IT service industry of Taiwan, and in turn provides business managers a useful reference for better decision-making, thus serves as an effective tool to help enhance business efficiency and competitiveness.

自2002年《殯葬管理條例》將骨灰拋灑或植存納入明文以來，不僅相關實施規定未臻完備，推動成效亦屬不彰，迄今全台僅台北縣立金山環保生命園區一處劃定實施骨灰植存。基此，本研究希望建立一套周全的骨灰拋灑或植存專區劃設評估架構，作為未來規劃設計之衡量依據，俾供相關單位參考應用。 首先，以環保自然葬及殯葬設施相關文獻為基礎，並參考金山環保生命園區案例經驗，初步擬定骨灰拋灑或植存專區劃設時，必須審慎考量的各項原則性評估因子。其次，採用模糊德爾菲法整合產、官、學各領域專家之意見，修訂初擬之評估準則，確立骨灰拋灑或植存專區劃設評估架構。最後，依據網絡層級分析法建立網絡層級架構，將影響因素間存在的交互性質納入考量，並整合產、官、學各領域專家對要素相對重要程度之判斷，求解其準則權重關係。 研究結果顯示，骨灰拋灑或植存專區之劃設，應落實環境永續發展之理念，並達成社會調和共存之理想。在環境永續方面，以「植被完整性」最為重要，其次為「管理完善性」、「水土保持性」、「土壤適宜性」，最後是「動物保護性」；在社會調和方面，以「居民接受性」最為重要，其次為「聚落市街距離保持性」、「使用相容性」、「飲用水源距離保持性」，最後是「遺族接受性」。

本文根據2002年至2008年的各綜合券商財報資料，採用三階段資料包絡分析法，評估綜合券商之經營效率分析，研究的對象包含台灣金控體系下十四家綜合券商和上市櫃十一家綜合券商證券公司（非金控體系）共25家綜合券商。實證結果如下：第一階段廠商無效率之主要來源為純技術無效率與第三階段之部分，估計之結果不同，綜合券商經營管理無效率的情形相當嚴重，綜合券商純技術效率平均值為0.955，規模效率平均值為0.769，代表受評綜合券商經營上產生無效率之來源為生產規模之無效率，假若不考慮外在因素之衝擊則會低估純技術效率值，將造成廠商無效率來源之誤判，本文利用Wilcoxon符號等級檢定(Wilcoxon signed rank test)檢驗第一階段與第三階段效率值，顯示在1%的顯著水準下，第一階段與第三階段 DEA 估計之技術效率值、純技術效率值及規模效率值確實存在顯著差異；SFA迴歸評估結果顯示，營運據點數、董事規模、董監事股權質押比率對勞動投入差額呈顯著正向關係，2008金融風暴、業務集中度、業務風險、發放員工分紅對勞動投入差額呈顯著負向關係；營運據點數、業務集中度、業務風險、董事規模、董監事股權質押比率對資本投入差額呈顯著正向關係，2008金融風暴及發放員工紅利，對資本投入差額呈顯著負向關係；2008金融風暴、業務風險、發放員工紅利、董事規模、董監事股權質押比率對其他費用投入差額呈顯著正向關係，營運據點數、業務集中度，對其他費用投入差額呈顯著負向關係。

為了加入世界貿易組織，台灣早已自80年代逐步進行金融自由化的工作：早在1983年政府就擴大存放款利差，1984年允許銀行根據其個別情況制定基本放款利率並放寬本國銀行設立分行的家數與條件。然而金融自由化最重大的里程碑則是在1989年7月財政部修訂銀行法，開放新銀行設立並解除利率管制，自此之後台灣才真正成為金融自由化的國家。 本研究針對1986年到2002年的本國銀行，採用資料包絡分析法計算效率值，旨在探討台灣銀行業在開放新銀行設立前後的效率與生產力變動情形。不同於其他研究僅以年度為基礎來計算相對效率值，本研究使用「大邊界」的觀念建構出單一效率邊界，更能顯示出在一致的比較基礎上效率變動的趨勢。本研究的主要結果如下： 1.銀行業全體與開放前既存之舊銀行，在開放前的效率值均顯著大於開放後。至於開放後新舊銀行效率的比較，新銀行的整體技術效率與規模效率較高，舊銀行則在純技術效率上領先新銀行，但檢定結果僅有規模效率一項為顯著。 2.金控子銀行的效率值較非金控子銀行為高，顯示金控公司會挑選表現好的銀行作為合作夥伴。 3.在生產力分析部分，舊銀行開放後的總生產力仍小於開放前，儘管舊銀行在開放後的各項經營效率變動較開放前高，但因技術的大幅衰退以致整體生產力仍呈現衰退現象。顯示舊銀行雖然在效率上有所改善，但對於營運上的創新仍太過保守。 4.在Tobit迴歸分析的部分，股東權益報酬率、資產規模、流動準備率和效率值的關係為正向；分行家數、可控制費用、催收款比率和效率值的關係則為負向。 關鍵詞：銀行業、效率分析、資料包絡分析法、解除管制 / In order to join World Trade Organization, Taiwan has been gradually liberating its banking industry since 1980s. In 1983 Taiwan augmented the interest difference between loans and savings in banking industry. In 1984 Taiwan allowed a bank to set its own basic interest rate of loans base on business difference and reduced the restriction of setting up the new branches. The biggest leap was in 1989, Taiwan passed the new banking law which deregulated the banking industry. The new law opened the market for the new entrants and abandoned the interest regulation. The purpose of this research is to examine the efficiency and productivity changes before and after deregulation of Taiwan’s banking industry. This research applies Data Envelopment Analysis (DEA) approach to measure efficiency scores. The data include most of the domestic banks in Taiwan from 1986 to 2002. Unlike other research use yearly basis to measure relative efficiency difference, this research constructs a single efficiency frontier, grand frontier, to measure the trends of efficiency changes. The major findings of this research as follows. 1. The statistical results of the full sample exhibit that the efficiency measures before deregulation are statistically significant greater than that of after deregulation. Although the new entrants exhibit higher efficiency scores in total technical efficiency and scale efficiency than incumbents after deregulation, however, only scale efficiency indicates statistically significant level. Incumbents exhibit a higher pure technical efficiency than the new entrants after deregulation. 2. Banks that joined the financial holding company exhibit higher efficient scores than those of do not join the financial holding company. 3. The total factor productivity denotes a regress after deregulation. The major factor of productivity regress is due to technology decrease. However, the efficiency change of incumbent banks exhibits a significant increase after deregulation. The finding suggests that although the incumbent banks have significant improvements in efficiency, they are still too conservative in innovations. 4. The Tobit regression suggests that return on equity (ROE), total assets, and current-reserve ratio have a positive effect on efficiency measures; however, the number of branches, controllable expenses, and bad debt ratio have a negative effect on efficiency measures. Keywords: Bank industry, Efficiency analysis, Data envelopment analysis, Deregulation

本研究試圖探討中東歐國家由中央集權計劃經濟轉型為市場經濟之後，對其效率及生產力之影響。本研究針對1980至2000年的歐洲國家，採用資料包絡分析法(DEA)與大邊界法(Grand Frontier)畫出所有樣本的單一效率邊界並計算其整體技術效率、純技術效率、規模效率值。 新興主權國家的整體技術效率、純技術效率、規模效率值在經濟轉型後均降低，顯示經濟轉型後的新興主權國家的確有經濟效率低落的狀況，尤其在經濟轉型初期市場不健全、經濟體質不良使資源配置不佳。傳統工業國家的整體技術效率及純技術效率在經濟轉型後較高，規模效率經濟轉型後降低。傳統工業國家於經濟轉型後整體技術效率、純技術效率及規模效率顯著的高於轉型國家、新興主權國家。 Malmquist生產力指數分析，結果顯示傳統工業國家在經濟轉型後顯示生產力有進步，而生產力成長主要貢獻是技術進步(innovation)，但傳統工業國家技術效率變動則呈現退步現象，進一步分析原因主要是由於規模效率變動退步所致。另外選擇1993年及2000年進行比較，結果發現傳統工業國家與新興國家的生產力均退步，主要原因是技術效率變動退步，但技術有進步。

本研究以某醫院為例，探討議題如下： (一)個案醫院導入平衡計分卡之需求、過程以及所遭遇之問題。 (二)將層級分析法(Analytic Hierarchy Process, AHP)與平衡計分卡指標權重設定相結合，以釐清多重指標之下，各個指標之相對權重關係，避免過多指標對指標管理造成混淆的抵銷影響。 分析結果顯示：個案醫院護理部門平衡計分卡五大構面中以學習與成長構面為最重要，顯示個案醫院護理部門對專業知識的重視。此外，平衡計分卡各構面之策略性衡量指標以顧客構面之住院病人整體滿意度策略性衡量指標權重最高，其次依序為學習與成長構面之舉辦護理使命共識營參與人數、內部流程構面之病房危機應變作業完成率、社會承諾構面之安寧照護推廣活動、財務構面之未達使用件年限之財產報銷金額占總報銷金額之比率。 / This study uses a medical center in Taiwan as a case study subject, and discusses the following issues: 1. Understanding why and how the subject hospital uses balanced scorecard at the organization and divisional levels. 2. Integrating Analytic Hierarchy Process (AHP) with balanced scorecard to clarify the relative weighting relationship among different strategic measures. The balanced scorecard performance measurement system of the subject hospital includes twenty-four strategic measures. The study adopts Analytic Hierarchy Process approach to solve the measurement problems from the nursing department of the subject hospital. The results show that the learning and growth dimension was the most important factors to achieve the strategic goal of the subject nursing department. Besides, customer satisfaction measure received a weight of 8.940% out of the twenty-four measures, which means that the nursing department members consider the customer satisfaction measure as the most important measure, so the strategic action plan for the customer satisfaction should be implemented first.

本研究以我國行動電話通信服務業客戶服務為研究對象，探討支付費用狀況對於行動電話通信消費者對客戶服務喜好程度的影響程度以及不同類型的消費者對於收費狀況與其他服務屬性的權衡關係，而進一步探討客戶服務收費之可能性。首先利用集群分析將全體樣本區隔成成本屬性導向群以及利益屬性導向群，再以客服使用量、通話貢獻量以及所得高低為事前區隔變數，將全體樣本區隔成高低度客服使用群、高低度通話貢獻群以及高低所得群，進而探討全體樣本以及各集群對於服務屬性的相對重視程度以及各服務屬性間的權衡關係。最後以收費可能性為主題，分別探討其在各集群中之存在關係。 經由統計分析，本研究有以下主要結論： 一、全體樣本、成本屬性導向群、高度客服使用群、低度客服使用群 高通話貢獻群、低通話貢獻群、高所得群與低所得群，最重視的 服務屬性皆為客戶服務專線收費狀況，且其相對重要性遠比其他服務屬性高。利益屬性導向群最重視的服務屬性則為接通速度，但其與其他各項服務屬性的相對重要性差距不大。 二、對於客戶服務專線收費狀況此一服務屬性，全體樣本、高度客服 使用群、高通話貢獻群與高所得群，皆必須以接通速度、接聽方 式與人員服務時間三項屬性同時抵換。而利益屬性導向群則可單 獨以接通速度或接聽方式加以抵換，或同時以人員服務時間與接 通速度或人員服務時間與接聽方式加以抵換。 三、就全體樣本、利益屬性導向群、高度客服使用群、高通話貢獻群 與高所得群而言，其客戶服務收費之可能性存在，但其前提是以 改善目前服務品質為前提，才得以維持目前消費者之滿意度。

資料包絡分析法乃是利用數學規劃模式求取決策單位之相對效率，故本研究針對本文針對競爭激烈之金控環境下,14至15家金控子銀行進行推估其經營效率。 銀行經營效率評估，主要以財務比率法、資料包絡法及隨機生產（或成本）邊界法。財務比率法大多利用單一投入與產出之比值，不符合生產函數之理論架構；DEA已經針對投入與產出之關係，作一嚴謹的分析，而能推估數個投入與產出之效率指標，此一效率指標，較能評估各廠商之經營績效。本文運用Farrell對於多項投入及多項產出效率衡量的概念，去推估各金控子銀行從1999年至2004年的經營效率，並建議這些銀行如何去配置最佳技術效率組合。 本研究的結論得出公營金控公司子銀行的績效不如民營金控子銀行來的佳。且金控公司子銀行未來應加強創新，增進風險管理的能力，促使銀行、證券及保險平台的結合，以便提高競爭力。 / Data Envelopment Analysis (DEA) is a mathematical programming approach to accessing relative efficiencies within a group of Decision Making Units (DMUS). therefore this research controls the environment in view of this article in view of the competition intense gold next the bank to carry on,14 to 15 Financial company bankings pushes estimates its management efficiency. 　　The bank management efficiency appraised, mainly by Financial Ratio Approachs, Data Envelopment Approachs and The Stochastic production (or cost) Frontier Approachs. The financial ratio Approachs mostly uses the sole investment with to deliver the ratio, does not conform to theory of overhead construction the production function; DEA already aimed at the investment with to deliver the relations, made a rigorous analysis, but could push estimates several investments with to deliver the efficiency target. This efficiency target, comparatively can appraise management achievements various merchants. This article utilizes Farrell delivers the efficiency weight regarding many investments and many items the concept, pushes estimates various Jin K'ungtzu the bank from 1999 to 2004 management efficiency, and suggested how these banks do dispose the best technical efficiency combination. 　　This research conclusion obtains the public-operated gold to control the company sub- bank the achievements to be inferior to privately operated Financial company bankings comes good. Also the gold will control the company sub- bank future to be supposed to strengthen the innovation, will promote the risk management the ability, will urge the bank, the negotiable securities and insures the platform the union, in order to enhancement competitive ability.

在運動產業逐漸興起的現代，如何評比球隊或運動員的表現好壞，似乎成了現在新興的熱門話題。經濟學上用來評估一家廠商的生產績效優劣，常用的是生產效率分析，生產活動偏離生產邊界的程度代表不效率高低。而球隊比賽的過程就像廠商生產的過程，運用各種投入得到產出。在籃球比賽中，比賽的投入可為球隊的各種技術統計，例如：投籃命中率、抄截、火鍋…等等，產出則是比賽的得分數。因此，在本篇文章中，我們利用經濟學中的生產效率分析來分析球隊的表現優劣，即評估各球隊發揮其潛能的程度。 評估生產效率的模型有很多，由於比賽的性質，有時候統計誤差、運氣也佔了很重要的部份，所以在選擇模型時，選的是隨機邊界效率分析模型（Stochastic Frontier Approach, SFA），除了利用隨機邊界分析模型分析球隊的生產效率，也利用預估的效率值來預測比賽結果排名，並與一般常用來預測結果的模型PROBIT MODEL做比較。我們利用大陸男子甲A籃球聯賽2003-2004和2004-2005賽季作為實證樣本，發現隨機邊界分析模型不只可以用來評估效率，在預測比賽結果排名上，隨機邊界分析模型預測能力則與PROBIT MODEL沒有顯著統計性的差異。 關鍵字：生產效率、隨機邊界分析法、運動產業 / Today, sports industry is getting popular, and how to evaluate the performance of sports teams or players seems also to be a newly hot interesting topic. In economics, production efficiency is often applied to evaluate a firm’s production performance. The inefficiency of a production activity is measured as its deviation from the production frontier. The process of a sport game is similar to a firm’s production process, which transforming various inputs into output(s). For basketball games, inputs can be the various technical statistics, such as field goal rate, steals, blacks, assistant attack, etc. Output(s) can be the scores of the teams got. Therefore, in this paper we use the production efficiency to gauge the performance of sports teams. There are many models measuring production efficiency. In this paper we choose the Stochastic Frontier Approach (SFA) to evaluate the sport team’s efficiency on account of the white noises which exist in the sport game obviously. We also use estimated efficiency scores to predict the outcome ranking of teams, and compare it to that of the PROBIT MODEL which is usually used to predict the outcome of a game. The sample we used are the results of the CBA men’s regular season and playoff season, and we found that the SFA is not only to evaluate efficiency but also can predict the outcome of competition, and its prediction ability is not significantly statistically different to that of PROBIT MODEL. Keywords: Production Efficiency, Stochastic Frontier Approach, Sports Industry

隨著金融控股公司法的實施，國內的金融機構紛紛朝金融控股公司的型態發展。然而，金控銀行的經營效率是否如預期般的有明顯的改善? 隸屬於金控集團的銀行其生產力是否優於無金控背景銀行?其生產力差異源自於哪些因素?。本研究採DEA模型，衡量金融控股公司與非金融控股公司效率差異，並透過差額變數分析（Slack Variable Analysis），使相對無效率銀行瞭解其缺失所在，進而尋求改進之道，將過多的投入量減少及過少的產出量增加；再利用Tobit迴歸模型，探討銀行之資本適足率、逾放比率、市場佔有率、風險水準、成本收益指標與經營效率之關係。 研究發現「金融控股公司」的平均總效率、技術效率值均高於「非金融控股公司」 。且不論是「金融控股公司」或「非金融控股公司」相對上都需減少固定資產及增加非利息收入，因而全體樣本銀行不僅需裁減人員還需廣增存款以外的利息收入或費用，以免在存款減少下引發資金不足的營運危機。