Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/115578
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Type: Journal article
Title: Key performance indicators for regional construction supervision systems in China
Author: Ding, Z.
Wang, J.
Zuo, J.
Gong, W.
Citation: Engineering Management Journal, 2017; 29(3):179-188
Publisher: Taylor & Francis
Issue Date: 2017
ISSN: 1042-9247
2377-0643
Statement of
Responsibility: 
Zhikun Ding, Jiayuan Wang, Jian Zuo, Wenyan Gong
Abstract: This article aims to build a model to identify key performance indicators for regional supervision system performance in China. A quantitative model consisting of performance indicators using discriminant analysis method was developed using regional data from 2005 to 2009. Validity of the identified key performance indicators was verified using classification analysis and group membership prediction based on 2010 data. The results show, first, that the differences between groups arise from the scale, structure, and human resources of regional supervision systems. Second, regional supervision systems are labor intensive instead of knowledge intensive, no matter which group they belong to. Third, it may be appropriate to merge developing and underdeveloped regions. This implies that practicing engineering managers could play an even more significant role in these markets. Practicing engineering managers could provide knowledge-intensive services, such as design supervision and life-cycle cost supervision so that global consulting competitors could enter the Chinese supervision market and sustain a competitive edge. There are also lessons from China that there is a need for professional supervision engineers, which should be distinct from other engineering managers.
Keywords: Classification function; discriminant analysis; discriminant function; supervision engineers; supervision system
Rights: Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=uemj20
RMID: 0030078774
DOI: 10.1080/10429247.2017.1342477
Appears in Collections:Architecture publications

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