近年來，服務業創造出的產值已成為社為財富的主要來源，大部份先進國家
服務業之產值均遠超過製造業。在國內，服務業提供的就業機會及其所衍生之產
值亦持續不斷地成長。自Gronroos (1982)將品質概念導入服務領域後，與服務品
質相關的研究議題便受到廣泛的重視。由於服務品質主要係源自顧客主觀的感受，
因此如何將消費者在服務過程中所感知的服務品質加以量化並以非常態製程能
力指標衡量之係本研究探討的主題。
我們參考製造業製程能力指標訂定之原則，提出適用於服務業之關鍵績效指
標(Key Performance Index, KPI) ，並利用拔靴法(bootstrap)建構出KPI 之信賴區
間，再以涵蓋率(coverage probability)評估拔靴信賴區間之可靠度。研究結果顯示
當服務水準較低(90%或95%時)，僅約需250 個樣本即可達到理想之信賴區間，
然而隨著服務水準的提高，則需要較大的樣本數才能獲得較可靠之信賴區間。
根據模擬分析結果，本研究進一步建構出在不同之服務水準下，欲達到特定
之涵蓋率所需樣本數的對照表，研究成果可作為業界在利用KPI 評估營運及服
務績效時的重要參考。

In recent years, the amount of monetary value produced by service industries has
become the main resource of social wealth, and it has exceeded the corresponding
amount obtained by manufacturing industries in most advanced countries. The job
opportunities and the created wealth from service in Taiwan are continuously growing.
The research topics related to service quality has been widely considered since quality
concepts were introduced by Gronroos in 1982. Due to the fact that service quality
mainly lies in customers’ perceptions, this thesis is focused on quantifying customers’
perceptions during the course of service and using Key Performance Index (KPI) to
measure the service performance.
Based on the definitions of process capability indices, we develop a Key
Performance Index, which is suitable to service industry. Then, a bootstrapping
method is used to construct KPI’s confidence interval and the coverage probability is
used to evaluate the reliability of the bootstrap confidence interval. The simulation
results indicate that for higher confidence and service levels are, larger sample size is
required.
Based on the simulation results, a table is further constructed in this paper to show
the required sample size under various combinations of service and confidence levels.
Hopefully, the KPI and its required sample size can be useful for performance evaluation in service industries.

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