Papers by Bee Hua Goh, Ph.D.
Construction Economics and Building, 2015
Green Building Certification Systems (GBCS) are carried out in many countries due to the rising a... more Green Building Certification Systems (GBCS) are carried out in many countries due to the rising awareness of the importance of sustainability in the building industry. The intention should have motivated participants to construct and operate buildings sustainably, however, there is not yet a method developed to investigate the motivation of the participants. Based on the GBCS, this paper proposes the contribution index as a standard global method to analyze the performance of participants in the green building industry. Three contribution indices, namely Frequency Contribution Index (FCI), Intensity Contribution Index (ICI) and Comprehensive Contribution Index (CCI) that concern each different category of participant, have been formulated. Three further analyses based on the index were undertaken to investigate some features of the industry. A case study of Singapore was conducted to show how the contribution index could be used to extract industry patterns and trends and assess the...
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Building and Environment, Mar 1, 2006
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Building and Environment, Feb 1, 2005
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SUMMARY Quality function deployment (QFD) is a new approach to supporting constructable design de... more SUMMARY Quality function deployment (QFD) is a new approach to supporting constructable design decision- making. This paper proposed a Knowledge Management model for Constructable Designs with QFD (KM-CD-QFD), which is developed to facilitate the transfer QFD-relevant knowledge and information into the early design decision-making process and extend the application of conventional QFD in constructable designs. Three components of the KM-CD-QFD
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Building and Environment, 2005
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CIB REPORT, 2003
... Quality (HOQ) matrices of QFD and combine the adapted HOQ with intelligent support tools ... ... more ... Quality (HOQ) matrices of QFD and combine the adapted HOQ with intelligent support tools ... QFD is a method for structured product planning and development that enables a ... customer needs, and how to provide quality control process charts to manufacturing before production ...
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Built Environment Project and Asset Management, 2016
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Article usage statistics combine cumulative total PDF downloads and full-text HTML views from pub... more Article usage statistics combine cumulative total PDF downloads and full-text HTML views from publication date (but no earlier than 25 Jun 2011, launch date of this website) to 12 Feb 2013. Article views are only counted from this site. Although these data are updated every 24 hours, there may be a 48-hour delay before the most recent numbers are available.
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Article usage statistics combine cumulative total PDF downloads and full-text HTML views from pub... more Article usage statistics combine cumulative total PDF downloads and full-text HTML views from publication date (but no earlier than 25 Jun 2011, launch date of this website) to 13 Feb 2013. Article views are only counted from this site. Although these data are updated every 24 hours, there may be a 48-hour delay before the most recent numbers are available.
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The potential of green building rating systems supporting the development of building designs has... more The potential of green building rating systems supporting the development of building designs has been stated. In essence, such rating systems can be integrated with building information modelling (BIM) to achieve sustainable building designs that meet assessment criteria relating to environmental impact and performance. A proposed rule-based system that contains decision-support rules pertaining to the assessment of whole-life cost implications for building projects is described. The system incorporates and classifies by building element the assessment criteria of Singapore’s Green Mark Scheme, which is a green building rating system developed by the Building and Construction Authority, and maps them onto two components of whole-life costs which are the initial capital cost and operating cost. With this tool, the client and his team of consultants are guided by fuzzy logic decision rules, which take into account whole-life cost implications, in their design of an energy efficient building as conceived from the elemental cost plan. In the context of creating sustainable designs, this tool can interface with CAD applications (Design and Green BIM tools) to facilitate designers in designing to a better ascertained whole-life budget for the proposed building.
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The published literature abounds with evidence of a need to relate the construction industry with... more The published literature abounds with evidence of a need to relate the construction industry with the general economic environment. The effect of economic fluctuations has a major impact on the performance of this sector of the economy. Economic indicators, which are measures of performance of the national economy, may serve as viable input variables to model construction demand. The general groups of economic measures that are examined to be related to demand for residential, industrial and commercial building construction include national output, population and employment, government fiscal policies, national consumption, investment and savings, industry and commerce, balance of payments, money and interest rates, and prices and wages. Traditionally, in macroeconomic modelling studies, independent variables are selected systematically by satisfying two main criteria: economic significance and statistical adequacy. However, this has not been the case in construction demand modelling studies. There has yet to be a systematic approach available for variable selection as part of the whole modelling process. Therefore, a stage-by-stage method is proposed to supplement the process of modelling demand.
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Construction is a labour-intensive activity. In Singapore, labour is in very short supply. Constr... more Construction is a labour-intensive activity. In Singapore, labour is in very short supply. Construction workers, both skilled and unskilled, are even rarer. Thus, efforts have been made to limit the construction industry’s requirement for labour by increasing productivity on site. To this end, it is necessary to assess progress made over time in the attempt to raise construction productivity. For this purpose, it is important that a definitive, realistic and practically relevant measure of construction productivity be found.
This paper discusses the concept of productivity and how it is generally measured. It then evaluates various ways by which construction productivity is assessed, and points out that there are few existing methods for estimating project- and industry-level. An empirical study is conducted to generate a univariate time-series model to forecast Singapore’s industry-level productivity using the Box-Jenkins approach. The generated model proves to be accurate in its ex-post forecasts based on prediction intervals and point forecasts. The prevailing approach to the measurement of construction productivity in Singapore, and its merits and weaknesses are next considered. Finally, an alternative yardstick is offered.
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Singapore’s construction industry has experienced different stages of growth for IT since the inc... more Singapore’s construction industry has experienced different stages of growth for IT since the inception of CORENET in 1995. Reviewing the key milestones shows three distinct phases: 1995 to 1998; 1999 to 2005; and 2006 to 2015. In order to ascertain the stage of growth by the second phase, Nolan’s Stages of Growth Model, is adapted and applied to analyse the characteristics of IT users, enablers and suppliers by their respective degrees of awareness, application and integration. The results support the hypothesis that growth is at “Stage II – Growth” by 2004. A similar survey is conducted in 2011 and the results are compared. There are notable improvements. The recommendations are to instill a ‘Culture of Collaboration’, adopt performance-oriented procurement arrangements for improved collaboration and standardise the building project process. Mobile and BIM technologies have to be user-friendly to attract demand. Workers and professionals have to be trained to become multi-disciplinary and process-oriented.
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Building an intelligent construction industry complements the aim of iN2015. The article highligh... more Building an intelligent construction industry complements the aim of iN2015. The article highlights prevailing standardisation and ICT developments in the construction industry and suggests new areas in view of globalisation and rapid technological change. A review of current issues and recommendations on the thrusts of creating an active information standardisation community, promoting IT use to smaller businesses and promoting IT use to larger businesses is made. As the next phase of standardisation efforts, process modelling is proposed as a natural progression from 3D to 4D models. On the potential of Singapore construction-sector companies becoming intelligent, the systems and applications to be acquired are discussed. The article concludes that in the long run, the industry still needs to close the technology and knowledge gaps through innovation, research and training. And, it continues to emphasize that integration of people, processes and technology is crucial for creating a holistic ICT solution for an intelligent enterprise.
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The use of artificial intelligence (AI) methods, such as artificial neural networks (ANNs), in th... more The use of artificial intelligence (AI) methods, such as artificial neural networks (ANNs), in the construction field has been in experimentation since the evolution of one of the most important ANN paradigm known as Backpropagation in the mid-eighties. This paper presents a review of studies that have applied biological-based AI methods, such as genetic algorithms (GAs) and ANNs, to the simulation and optimization of construction processes, and the modelling and forecasting of construction variables such as tender bids, demand and cost, respectively. Some of the highlighted works include the use of ANNs and GAs to solve complex construction site operational problems; to identify the most appropriate construction method, plant combination and labour allocation, so as to optimize costs, time and production; to examine the relationships between variables in the construction bidding process for the purpose of predicting future tender bids; to model the complex nonlinear relationship between demand for construction and its influencing economic factors; and to model and estimate construction cost using subjective or 'noisy' data. The key benefits cited include a more efficient method of simulating construction activity owing to the parallel processing of information; a more effective search and optimization approach that can quickly locate high performance regions in extremely large and complex search spaces; the building of more complex nonlinear models to produce realistic and accurate forecasts; and the availability of techniques that can perform nonlinear modelling and adaptation automatically without the need for functional assumptions. For quantitative research in the field of construction management and economics, the review serves to formalise the transition from traditional statistical techniques to those that are AI-based. It is timely to acknowledge a paradigm shift in quantitative construction research so that researchers can better prepare themselves for the future by acquiring new skills and knowledge.
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The utilisation of benefit cost approach for investment appraisal requires a price that can be us... more The utilisation of benefit cost approach for investment appraisal requires a price that can be used in comparing economic benefits of projected consumption growth with the cost of incremental supply. A pricing approach that ensures expansion of capacity and consumption is at the correct level, places the burden on the consumer to reveal willingness to pay and hence value of water consumed. If the price paid is at least equal to the cost of providing additional supplies, investment in additional capacity is warranted. If not, existing capacity should be rationed. This forward-looking approach to pricing can provide the test for project justification in urban water supply.
This paper describes a study that was carried out to estimate WTP for urban water supply. The study looked at three types of consumers typically found in urban areas in developing countries. Those who receive water through: existing connections; stand posts; and water wells. To estimate WTP, two forecasting techniques are applied, namely, Artificial Neural Networks (ANN) and Multiple Regression (MR). The former being a state-of-the-art technique while the latter a conventional one. A comparative study is carried out to determine whether the estimate for WTP with the application of the ANN technique can produce better predictions than with the MR method. A comparison is made between the ANN and MR models, in terms of their forecasting accuracy, by using a relative measure known as the mean absolute percentage error (MAPE). The forecasting error of the best ANN model is found to be about half of that derived from the best MR model. From the MR models, it is seen that the significant variables that determine WTP, differ depending on the type of consumer, and from those variables that are typically considered as significant for WTP by urban consumers in developed countries.
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Papers by Bee Hua Goh, Ph.D.
This paper discusses the concept of productivity and how it is generally measured. It then evaluates various ways by which construction productivity is assessed, and points out that there are few existing methods for estimating project- and industry-level. An empirical study is conducted to generate a univariate time-series model to forecast Singapore’s industry-level productivity using the Box-Jenkins approach. The generated model proves to be accurate in its ex-post forecasts based on prediction intervals and point forecasts. The prevailing approach to the measurement of construction productivity in Singapore, and its merits and weaknesses are next considered. Finally, an alternative yardstick is offered.
This paper describes a study that was carried out to estimate WTP for urban water supply. The study looked at three types of consumers typically found in urban areas in developing countries. Those who receive water through: existing connections; stand posts; and water wells. To estimate WTP, two forecasting techniques are applied, namely, Artificial Neural Networks (ANN) and Multiple Regression (MR). The former being a state-of-the-art technique while the latter a conventional one. A comparative study is carried out to determine whether the estimate for WTP with the application of the ANN technique can produce better predictions than with the MR method. A comparison is made between the ANN and MR models, in terms of their forecasting accuracy, by using a relative measure known as the mean absolute percentage error (MAPE). The forecasting error of the best ANN model is found to be about half of that derived from the best MR model. From the MR models, it is seen that the significant variables that determine WTP, differ depending on the type of consumer, and from those variables that are typically considered as significant for WTP by urban consumers in developed countries.
This paper discusses the concept of productivity and how it is generally measured. It then evaluates various ways by which construction productivity is assessed, and points out that there are few existing methods for estimating project- and industry-level. An empirical study is conducted to generate a univariate time-series model to forecast Singapore’s industry-level productivity using the Box-Jenkins approach. The generated model proves to be accurate in its ex-post forecasts based on prediction intervals and point forecasts. The prevailing approach to the measurement of construction productivity in Singapore, and its merits and weaknesses are next considered. Finally, an alternative yardstick is offered.
This paper describes a study that was carried out to estimate WTP for urban water supply. The study looked at three types of consumers typically found in urban areas in developing countries. Those who receive water through: existing connections; stand posts; and water wells. To estimate WTP, two forecasting techniques are applied, namely, Artificial Neural Networks (ANN) and Multiple Regression (MR). The former being a state-of-the-art technique while the latter a conventional one. A comparative study is carried out to determine whether the estimate for WTP with the application of the ANN technique can produce better predictions than with the MR method. A comparison is made between the ANN and MR models, in terms of their forecasting accuracy, by using a relative measure known as the mean absolute percentage error (MAPE). The forecasting error of the best ANN model is found to be about half of that derived from the best MR model. From the MR models, it is seen that the significant variables that determine WTP, differ depending on the type of consumer, and from those variables that are typically considered as significant for WTP by urban consumers in developed countries.