Sumardi, R H and Anaman, K A (2004) Aggregate efficiency analysis of resource use and demand for labour by the construction industry in Brunei darussalam. Construction Management and Economics, 22(7), pp. 755-764. ISSN 01446193
Abstract
The construction industry is the third largest contributor to the gross domestic product (GDP) in Brunei Darussalam, the wealthiest Muslim country in the world based on per capita GDP. The construction industry in Brunei has been in a crisis since the Asian financial crisis of 1998 and the subsequent collapse in the same year of the Amedeo Company, the largest company dealing with construction-related business in Brunei. The objectives of this study are to gauge the overall aggregate level of inefficiency of the industry and to analyse the factors affecting aggregate labour demand in the industry. Econometric analysis, based on secondary time-series data of the construction industry from 1971 to 2001, was the main route used to fulfil these objectives. The technical inefficiency of the construction industry was undertaken using a stochastic frontier production function analysis. The results indicated that overall technical inefficiency of the industry was about 26.6%. The short-run demand for labour in the construction industry was estimated based on time-series secondary data using a partial expectation model. This particular analysis showed that construction firms were only getting about half of the desired increase in the workers that they wanted to employ.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Brunei; construction industry; economics of resource use; efficiency analysis; labour demand; southeast Asia; stochastic frontier production function |
| Index terms: | Asia, Muslim, construction firm, Brunei, econometric, construction industry, efficiency, gross domestic product, aggregate, function analysis, secondary data |
| Subjects: | Geography, performance management, industry analysis, cross-cultural studies, materials science, organization, data collection methods, economic analysis, regions and continents, data science |
| Topics: | Engineering Principles, Geographical Context, Research Practice, Business Strategy, Quality Management |
| Descriptive scope: | 5 PCTEA |
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