SAAD H. AL‐JIBOURI and MICHAEL J. MAWDESLEY
This paper describes the development and initial use of a management game to teach project planning and control. It covers all aspects of the game including its design, the choice…
Abstract
This paper describes the development and initial use of a management game to teach project planning and control. It covers all aspects of the game including its design, the choice of the project to be modelled, the user interface and how it makes use of the computer power available. The sections on the use of the game describe experience gained in its use as part of an undergraduate course and as a demonstration on a course run for industry. Both the design and the use of the game are critically assessed and suggestions for improvement are made. The game was produced as a result of international collaboration between British and Dutch academics with input, where appropriate from construction companies of both nations.
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Michael J. Mawdesley, William H. Askew and Saad H. Al‐Jibouri
This paper describes the integration of various models to provide a realistic decision support system for linear project site layout. Initially, the paper describes an…
Abstract
This paper describes the integration of various models to provide a realistic decision support system for linear project site layout. Initially, the paper describes an investigation to determine the actual methods currently used by project managers and planners. A review of both techniques adopted by the managers and the knowledge acquisition methods employed are included in the paper. Following this, this paper describes the work done to automate the existing systems. This resulted in a system which has been used in practice and has been shown to be a great help to managers. It is based on the traditional method of mass‐haul diagrams used to determine the earthworks activities. A separate simulation and artificial intelligence model of earthworks are described. This will be extended to model linear projects more realistically than does mass‐haul.
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Tatsiana Haponava and Saad Al‐Jibouri
Design process is a focal point in any construction process. It is within this process that the product to be built is defined, shaped and specified. To be able to control the…
Abstract
Purpose
Design process is a focal point in any construction process. It is within this process that the product to be built is defined, shaped and specified. To be able to control the design process, it is necessary to control the performance of its main sub‐processes in order to make sure that end‐project goals have a better chance of being achieved. This paper aims to propose a model for identifying process performance of the design stage through the performance of its key sub‐processes and linking them to the end‐project goals.
Design/methodology/approach
The research method used consisted of the following steps: identifying the key performance indicators (KPIs) to control the performance of the key design sub‐processes based on the literature review and a number of the interviews; and establishing the relationship between the design process performance represented by the identified KPIs and end‐project goals. This was done using experts during interviews.
Findings
The paper has resulted in a number of process‐based KPIs assessed to be critical for control of the design stage. Analysis of the interviews highlighted some similarities and differences in perceptions of clients and contractors on the priorities in controlling the design process. Analysis also showed that the identified KPIs have different degrees of influence on the end‐project goals.
Originality/value
The proposed model offers a systemic way of controlling the design process performance towards the desired goals using the identified KPIs. It also helps to understand the relationship between the design process performance and the end‐project goals.
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Michael J. Mawdesley and Saad Al‐Jibouri
Improvement in productivity will not be achieved without bearing in mind that there is an enormous number of factors affecting productivity and that there is a necessity to locate…
Abstract
Purpose
Improvement in productivity will not be achieved without bearing in mind that there is an enormous number of factors affecting productivity and that there is a necessity to locate the most influential ones among them. Doing so will enable researchers as well as practitioners to pinpoint the areas where efforts are to be directed in order to reach the optimum productivity of the studied project. The work described in this paper is based on data collected from the construction industry in the UK. In collecting the information, there are three initial aims: to determine what factors affected productivity at site level, to determine how these factors interacted and to determine the significance of the factors.
Design/methodology/approach
The research method undertaken is to model productivity in construction using system dynamics. In particular, it concentrates on the use of system dynamics and project level productivity. The literature identifies 34 factors affecting productivity but based on a survey of professionals, five of these are recognised as important. They form the basis of a systems model whose development is described.
Findings
The results of testing the developed model have suggested that investments in planning and control have most benefits on project productivity and that investments in safety, motivation and reduction of disruptions are beneficial.
Originality/value
The use of system dynamics to model productivity represents untraditional and novel approach in research in construction. The developed model is valuable in that it can be used to evaluate management strategies and their effects on project productivity.
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Tatsiana Haponava and Saad Al‐Jibouri
The need for measuring construction project performance has led to development and implementation of various key performance indicators (KPIs). This paper aims to present and…
Abstract
Purpose
The need for measuring construction project performance has led to development and implementation of various key performance indicators (KPIs). This paper aims to present and discuss the results of a pilot study and interviews to identify process‐based KPIs for use in control of the pre‐project stage.
Design/methodology/approach
Initially, the process of the pre‐project stage was mapped to define its main generic sub‐processes and outputs based on the literature review. The process map was then verified through a pilot study. Based on the verified sub‐processes, a number of process‐based KPIs were identified and later validated by experts during the interviews.
Findings
As a consequence of the refinement process due to the results of the pilot study and the interviews, the process‐based KPIs for the pre‐project stage were identified and the main issues they have to encompass were discussed.
Originality/value
The identified KPIs offer a significant step towards process control within the pre‐project stage. They provide a basis for further development to improve process transparency and to explain the relationships between the various sub‐processes.
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Farman Afzal, Shao Yunfei, Mubasher Nazir and Saad Mahmood Bhatti
In the past decades, artificial intelligence (AI)-based hybrid methods have been increasingly applied in construction risk management practices. The purpose of this paper is to…
Abstract
Purpose
In the past decades, artificial intelligence (AI)-based hybrid methods have been increasingly applied in construction risk management practices. The purpose of this paper is to review and compile the current AI methods used for cost-risk assessment in the construction management domain in order to capture complexity and risk interdependencies under high uncertainty.
Design/methodology/approach
This paper makes a content analysis, based on a comprehensive literature review of articles published in high-quality journals from the years 2008 to 2018. Fuzzy hybrid methods, such as fuzzy-analytical network processing, fuzzy-artificial neural network and fuzzy-simulation, have been widely used and dominated in the literature due to their ability to measure the complexity and uncertainty of the system.
Findings
The findings of this review article suggest that due to the limitation of subjective risk data and complex computation, the applications of these AI methods are limited in order to address cost overrun issues under high uncertainty. It is suggested that a hybrid approach of fuzzy logic and extended form of Bayesian belief network (BBN) can be applied in cost-risk assessment to better capture complexity-risk interdependencies under uncertainty.
Research limitations/implications
This study only focuses on the subjective risk assessment methods applied in construction management to overcome cost overrun problem. Therefore, future research can be extended to interpret the input data required to deal with uncertainties, rather than relying solely on subjective judgments in risk assessment analysis.
Practical implications
These results may assist in the management of cost overrun while addressing complexity and uncertainty to avoid chaos in a project. In addition, project managers, experts and practitioners should address the interrelationship between key complexity and risk factors in order to plan risk impact on project cost. The proposed hybrid method of fuzzy logic and BBN can better support the management implications in recent construction risk management practice.
Originality/value
This study addresses the applications of AI-based methods in complex construction projects. A proposed hybrid approach could better address the complexity-risk interdependencies which increase cost uncertainty in project.