Modeling Performance Measurement in Organizations

业绩衡量和基准是我们经济体系的重要基础，特别是加拿大庞大的服务业。银行、医院、学校和快餐店只是几个可以从基准和效率评估中受益的组织。通过拥有有效的工具来衡量任何组织相对于其同行或竞争对手的业绩，该组织可以更好地了解它目前所处的位置和其潜力所在之间可能存在的任何差距。拟议的研究旨在开发决策支持工具，用于对组织的业绩进行建模和确定最佳做法。要使用的模型结构是数据包络分析(DEA)，它属于更广泛的多标准决策方法集。DEA研究已经跨越了三十年；拟议的研究计划审查了在将DEA应用于现实世界问题的过程中出现的一些主要问题。供应链管理是当前研究的一个重要领域。拥有分析供应链并在供应商及其相关供应链之间进行业绩比较的手段，现在正成为“为了利润”和“不为了利润”两种情况下的必备条件。DEA方法有可能成为这里的一种选择工具，但目前的形式不够强大，无法提供所需的详细分析。拟议研究的主要部分侧重于解决数据包络分析方法中的一些缺陷。

Performance measurement and benchmarking are important underpinnings of our economic system, particularly the large Canadian service sector. Banks, hospitals, schools, and fast food restaurants are but a few examples of organizations that can benefit from benchmarking and efficiency evaluation. By having effective tools for measuring the performance of any organization relative to its peers or competitors, that organization can have a better understanding of any gaps that may exist between where it currently stands and where its potential lies. The proposed research is aimed at developing decision support tools for modeling performance and identifying best practice in organizations. The model structure to be used is data envelopment analysis (DEA), which falls within the broader set of multiple criteria decision-making methodologies. DEA research has spanned three decades; the proposed research program examines some of the major issues that have arisen in the process of applying DEA to real world problems. An important area of current research is supply chain management. Having the means for analyzing supply chains and making performance comparisons between vendors and their associated supply chains, is now becoming a must in both 'for profit' and 'not for profit' settings. The DEA methodology has the potential to become a tool of choice here, but is not robust enough in its current form to provide the detailed analysis needed. A major portion of the proposed research focuses on addressing some of these shortcomings in the DEA methodology.