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Aouad, G F, Kirkham, J A, Brandon, P S, Brown, F E, Cooper, G S, Ford, S R, Oxman, R E, Sarshar, M and Young, B A (1993) Information modelling in the construction industry: the information engineering approach. Construction Management and Economics, 11(05), 384-97.
Chau, K W (1993) Estimating industry-level productivity trends in the building industry from building cost and price data. Construction Management and Economics, 11(05), 370-83.
Kodikara, G W and McCaffer, R (1993) Flow of estimating data in Sri Lankan building contractor organizations. Construction Management and Economics, 11(05), 341-6.
Koo, T K and Tiong, R L K (1993) An expert system for assessing the performance of RC beams and slabs. Construction Management and Economics, 11(05), 347-57.
Langford, D A, Iyagba, R and Komba, D M (1993) Prediction of solvency in construction companies. Construction Management and Economics, 11(05), 317-25.
Ranasinghe, M and Russell, A D (1993) Elicitation of subjective probabilities for economic risk analysis: An investigation. Construction Management and Economics, 11(05), 326-40.
Scott, S (1993) The nature and effects of construction delays. Construction Management and Economics, 11(05), 358-69.
Tan, R R and Chang, D S (1993) The formulation of performance indicators in evaluating the implementation of automation in the construction industry. Construction Management and Economics, 11(05), 398-403.
- Type: Journal Article
- Keywords: automation; China; national planning; performance indicator
- ISBN/ISSN: 0144-6193
- URL: https://doi.org/10.1080/01446199300000043
- Abstract:
The focus of the paper is to present the processes in formulating a system of performance indicators to evaluate the implementation of a National Construction Industry Automation Plan in the Republic of China. We approach the formulation as a ’construction automation transformation system’ which consists of three major components: (1) the inputs, such as funding, manpower and supports, (2) the sub-systems, and (3) the outputs. There are three sub-systems, the receiving sub-system and the socio-economic sub-system. Corresponding to each sub-system, a set of output performance indicators is developed. Program output performance indicators are proposed to measure the effectiveness of the processing sub-system. The industry effectiveness performance indicators are recommended to measure the effectiveness of the receiving sub-systems and the socio-economic sub-system respectively.