基于模糊集理论的服务过程绩效度量与评价概念模型

S. Amini, R. Jochem
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引用次数: 5

摘要

服务过程的正确度量和评价对公司来说仍然是一个巨大的挑战。特别是在服务的生产过程中,客户和供应商之间需要相互作用,这使得服务的度量和评价变得困难。在这种情况下,软因素(如员工的友好度和能力)起着重要作用。软因素的测量和评价是一个非常具有挑战性的问题。软因素不能用客观的测量设备来测量(比如用秒表测量吞吐量时间)。软因素必须由人来衡量和评估。在这里,人是主观的测量工具。使用Liker量表是测量和评价软因素的常用方法。但是李克特量表并没有充分考虑人类的感知。本文提出了一种基于模糊集理论的概念性五阶段模型来衡量和评价服务过程的绩效。模糊集是经典集合的扩展,允许元素逐渐归属于一个集合。利用模糊集的这一特性对服务过程的度量和评价过程进行了客观化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Conceptual Model Based on the Fuzzy Set Theory to Measure and Evaluate the Performance of Service Processes
Correct measurement and evaluation of service processes is still an enormous challenge for companies. Especially the need for interaction between customer and supplier during the production of a service makes it difficult to measure and evaluate services. In this context soft factors (like friendliness and competence of the employees) play an important role. The measurement and evaluation of soft factors is very challenging. Soft factors cannot be measured by using objective measuring equipment (like the measurement of throughput time with the aid of a stop watch). Soft factors rather have to be measured and evaluated by people. Here people function as subjective measuring equipments. The use of Liker scales is the common way to measure and evaluate soft factors. But Likert scales do not sufficiently consider human perception. The current paper presents a conceptual five stage model based on the fuzzy set theory to measure and evaluate the performance of service processes. Fuzzy sets are an extension of classical sets and allow elements to belong gradually to a set. This characteristic of fuzzy sets is used to objectify the measurement and evaluation procedure of service processes.
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