Ibrahim Motawa

A fuzzy system for evaluating the risk of change in construction projects

A major source of risk in construction is the potential changes occurring during the project lifetime. Changes in construction projects often result from the uncertainty associated with the imprecise and vague knowledge of much project information at the early stages of projects. IT systems for change management largely focus on managing reactive changes, in which changes are recorded and then propagated to the concerned project members. However, proactive change management is hardly dealt with. Proactive change management requires estimating the likelihood of occurrence of a change event as well as estimating the degree of change impacts on project parameters. A fuzzy system is proposed in this paper to maintain these requirements. The system simulates the relationships between change causes and effects, and is intended to facilitate proactive change management on projects.

A Change Management Toolkit for Construction Projects

Abstract Changes in construction projects often cause cost and time overruns. Because of the nature of design and construction of buildings, construction professionals often have to make decisions based on assumptions and previous experience. Changes at a later stage are sometimes inevitable. The aim of project change management is not to seek the elimination of all project changes, but to minimize the negative impact of necessary changes and to avoid unnecessary ones. At present, in practice, there is a lack of industrial standards for project change management procedures and methods. This often results in changes being poorly managed, on an ad hoc basis, by project teams during individual projects. This paper presents a change management toolkit, which was developed to provide a standard framework and tool support for change management in construction projects.

Modelling payment mechanisms for supply chain in construction

Purpose – Different direct/indirect managerial and contractual links throughout the supply chain have been researched to improve project performance. These links are undoubtedly influencing payment and cash flow mechanisms. As different members of the supply chains are affected differently by the factors influencing cash flow, payment mechanisms have to be designed in such a way that this uneven sensitivity to cash flow factors is addressed and linked to value and utility. The purpose of this paper is to introduce an IT system developed to model different payment mechanisms to enable the supply chain members to decide on the most appropriate payment mechanism.Design/methodology/approach – The adopted methodology to select the appropriate payment mechanism is first illustrated. The mathematical model is then developed. The IT system to automate the developed methodology is then presented. The system considers alternative payment terms and conditions across the supply chain in a transparent and negotiated m...

Case-based reasoning and BIM systems for asset management

Purpose – The next generation of Building Information Modelling (BIM) seeks to establish the concept of Building Knowledge Modelling (BKM). The current BIM applications in construction, including those for asset management, have been mainly used to ensure consistent information exchange among the stakeholders. However, BKM needs to utilise knowledge management (KM) techniques into building models to advance the use of these systems. The purpose of this paper is to develop an integrated system to capture, retrieve, and manage information/knowledge for one of the key operations of asset management: building maintenance (BM). Design/methodology/approach – The proposed system consists of two modules; BIM module to capture relevant information and case-based reasoning (CBR) module to capture the operational knowledge of maintenance activities. The structure of the CBR module was based on analysis of a number of interviews and case studies conducted with professionals working in public BM departments. This pape...

Structural equation modelling of energy consumption in buildings

Purpose – The purpose of this paper is to analyse the complex interrelationships among thedifferent variables purporting to explain household energy consumption and carbon emissions. Energy consumption and carbon emissions in dwellings have been argued to be a complex socio-technical problem that involves interaction of many variables that are interdependent on one another. Design/methodology/approach – The paper investigates the explanatory power of these variables through the use of structural equation modelling which has the advantage of handling complex real-life problems that cannot be modelled by other multivariate analysis methods. This study uses the publicly available datasets of the Scottish House Condition Survey and the Scottish Environmental Attitudes and Behaviours datasets. Findings – This paper found that floor area, energy efficiency in terms of standard assessment procedure value, number of occupants in the dwelling, household income, dwelling age, consumption behaviour and age of househ...

Stakeholders’ expectations in utilising financial models for public-private partnership projects

Purpose – The purpose of this paper is to explore stakeholders’ expectations in utilising PPP financial models in order to ensure that each stakeholder understands the expectations of others before negotiating and reaching contract agreement by all the stakeholders. Design/methodology/approach – Five common sets of 40 expectations have been identified through a systematic research approach, and their relative significances were verified based on pilot studies in India and the UK and expert opinion solicited worldwide through a structured questionnaire survey. The survey responses were evaluated by using statistical analyses. Findings – The most important stakeholders’ expectations in utilising PPP financial models were identified at five different stages in a project. They are bankable (at the pre-proposal stage), assessment of projects ability to carry senior debt (at the contract negotiation stage), sensitivity analysis for key commercial issues (at the finance-raising stage), debt service evaluation t...

Dynamic demand risk assessment for toll road projects

To bridge the gap between supply of and increasing demand for roads, public–private partnership (PPP) concession contracts in which the investment cost is recovered via payments from the end users have been established. Although this mechanism has been seen as an efficient way for road projects to be completed on time and within budget, the demand risk faced during the operation stage has considerably limited this efficiency. Demand depends on a range of interrelated and dynamic factors such as the demographic and economic conditions. In addition, uncertainty is an inherent aspect of most demand-underlying factors which always make demand estimation inaccurate. However, this uncertainty is largely ignored by modellers where a single demand estimate is often used when evaluating the facility. The aim is to develop a system dynamics model to assess demand risk in road projects. The model captures the factors affecting demand and their relationships and simulates their change over time. By employing Monte Carlo simulation, the model assesses the likelihood and potential effect of an event on the outcome and provides a full picture of the various effects of potential risk. The model can help public, private, and financial stakeholders of PPP facilities make more informed decisions.

Prioritization of Demand Risk Factors in PPP infrastructure projects

Risk Management is one of the key success factors of Public Private Partnerships (PPP) projects. Demand risk, being one of the major risks affecting PPP concessions, needs particular attention and effective management to avoid project failure. Thus, the objective of this study is to identify, rate and prioritize these factors. The literature provides a list of core factors influencing demand in PPP projects. The full range of factors has been categorized into three groups of user characteristics, facility characteristics and area characteristics. A questionnaire survey, based on receiving feedbacks from PPP stakeholders, is then used to rate and measure the relative importance of each influencing factor. Since the factors affecting demand risk interact with each other in a complex manner, demand risk identification should involve prioritizing the influencing factors considering their complex interactions. Hence, an Analytic Network Process (ANP) based technique for prioritizing demand risk factors in the PPP infrastructure concession has been developed. This prioritization process will help identify the most critical factors under each cluster to allow them to be given more attention and be subject to further analysis. The analysis shows that historical experience of paying and willingness to pay are the most important factors under user characteristics cluster, whereas fees of using the facility is most important under facility characteristics cluster while employment level is most important under area characteristics.

Spoken dialogue BIM systems - an application of Big Data in construction

Purpose With the rapid development in the internet technologies, the applications of big data in construction have seen considerable attention. Currently, there are many input/output modes of capturing construction knowledge related to all construction stages. On the other hand, building information modelling (BIM) systems have been developed to help in storing various structured data of buildings. However, these systems cannot fully capture the knowledge and unstructured data used in the operation of building systems in a usable format that uses the intelligent capabilities of BIM systems. Therefore, this research aims to adopt the concept of big data and develop a spoken dialogue BIM system to capture buildings operation knowledge, particularly for building maintenance and refurbishment. Design/methodology/approach The proposed system integrates cloud-based spoken dialogue system and case-based reasoning BIM system. Findings The system acts as an interactive expert agent that seeks answers from the user for questions specific to building maintenance problems and helps searching for solutions from previously stored knowledge cases. The practices of monitoring and maintaining buildings performance can be more efficient by the retrieval of relevant solutions from the captured knowledge to new problems when maintaining buildings components. The developed system enables easier capture and search for solutions to new problems with a more comprehensive retrieval of information. Originality/value Capturing multi-modes data into BIM systems using the cloud-based spoken dialogue systems will help construction teams use the high volume of data generated over building lifecycle and search for the most suitable solutions for maintenance problems. This new area of research also contributes to the current BIM systems by advancing their capabilities to instantly capture and retrieve knowledge of operations instead of only information.

Live capture of energy-related knowledge into BIM systems

Energy Management in buildings is about operating and maintaining many complex energy systems used by buildings’ occupants. The generation and collection of energy-related building information is commonly fragmented, created over the building’s lifecycle by different teams with different objectives, and stored in different systems. The development of BIM systems has helped in storing this various information. However, the knowledge utilised in maintaining energy systems has also to be captured to develop a building portfolio that is comprehensive enough to benefit buildings’ owners, occupants, and energy managers. Capturing knowledge in digital format is always a challenge when developing such systems. Therefore, this research proposes an innovative means for capturing energy-related knowledge when monitoring and maintaining building performance by the integration of Spoken Dialogue Systems (SDS) with BIM models. SDS presents a natural language interface where the expert’s utterances are understood and answered back in speech format. The advancements in Spoken Dialogue technology will be employed to enable capturing and retrieving experts/occupants’ knowledge with the system interviewing the expert concerning the problem at hand. This interface will also allow easier searching for solutions to new problems with a more comprehensive retrieval of information.