contributor author | Gongbo Lin | |
contributor author | Geoffrey Qiping Shen | |
contributor author | Ming Sun | |
contributor author | John Kelly | |
date accessioned | 2017-05-08T21:39:24Z | |
date available | 2017-05-08T21:39:24Z | |
date copyright | September 2011 | |
date issued | 2011 | |
identifier other | %28asce%29co%2E1943-7862%2E0000355.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/58506 | |
description abstract | Value management (VM) is widely regarded as a useful tool for management to meet the challenges, such as limited resources and tight schedules arising in the construction industry. A rigorous measurement on the performance of VM studies is likely to improve the implementation of the VM methodology and enhance the confidence of clients about their investment in VM. The identification of key performance indicators (KPIs) is an essential first step in developing a proper performance measurement framework. This paper aims to identify the KPIs for measuring the performance of VM studies in construction. Delegates of international VM conferences hosted by SAVE International and Hong Kong Institute of Value Management during the period 2005 to 2007 were used as the target group for a questionnaire survey. The survey results identified 18 KPIs out of 47 potential performance indicators. They are divided into three groups: predicting indicators, process-related indicators, and outcome-related indicators, according to their characteristics. Three principal components were identified by using factor analysis of the KPIs, which reveals the interrelationship among the KPIs. Details on how to implement these KPIs, such as data providers, weightings, and scoring methods, are also presented. | |
publisher | American Society of Civil Engineers | |
title | Identification of Key Performance Indicators for Measuring the Performance of Value Management Studies in Construction | |
type | Journal Paper | |
journal volume | 137 | |
journal issue | 9 | |
journal title | Journal of Construction Engineering and Management | |
identifier doi | 10.1061/(ASCE)CO.1943-7862.0000348 | |
tree | Journal of Construction Engineering and Management:;2011:;Volume ( 137 ):;issue: 009 | |
contenttype | Fulltext | |