Search results

Project selection is a critical decision for any organization seeking to commission a large-scale construction project. Project selection is a complex multi-criteria decision-making problem with significant uncertainty and high risks. Fuzzy set theory has been used to address various aspects of project uncertainty, but with key practical limitations. This study aims to develop and apply a novel Pythagorean fuzzy sets (PFSs) approach that overcomes these key limitations.

The study is particular to complex project selection in the context of increasing interest in resilience as a key project selection criterion. Project resilience is proposed and considered in the specific situation of a large-scale construction project selection case study. The case study develops and applies a PFS approach to manage project uncertainty. The case study is presented to demonstrate how PFS is applied to a practical problem of realistic complexity. Working through the case study highlights some of the key benefits of the PFS approach for practicing project managers and decision-makers in general.

The PFSs approach proposed in this study is shown to be scalable, efficient, generalizable and practical. The results confirm that the inclusion of last aggregation and last defuzzification avoids the potentially critical information loss and relative lack of transparency. Most especially, the developed PFS is able to accommodate and manage domain expert expressions of uncertainty that are realistic and practical.

The main novelty of this study is to address project resilience in the form of multi-criteria evaluation and decision-making under PFS uncertainty. The approach is defined mathematically and presented as a six-step approach to decision-making. The PFS approach is given to allow multiple domain experts to focus more clearly on accurate expressions of their agreement and disagreement. PFS is shown to be an important new direction in practical multi-criteria decision-making methods for the project management practitioner.

A review of techniques used in industry showed that there is an absence of a formalised, systematic approach to earthworks planning. The techniques used tend to be subjective and time consuming with a heavy reliance given to the experience and knowledge of the planner. This absence of a formalised technique can lead to inaccurate planning and makes explanation of the techniques difficult. This paper describes the development of a new automated approach for use by the planners to generate earthworks activities that overcomes such limitations. As well as creating activity sets in a much shorter time, the ability to compare various sets allows the planner more scope when planning earthworks. The model is able to generate activity sets that are comparable to those generated by a project planner.

The purpose of this study is to examine product innovation as a means of addressing infrastructure shortages in developed economies and to improve the sustainability of infrastructure. The obstacles to product innovation in the road industry are compared between different types of participants in the supply chain to provide guidelines for interventions to improve innovation rates.

This exploratory study uses descriptive data from a large scale survey of the Australian road industry. The three top-rated product innovation obstacles for the following four types of participants are examined: contractors, consultants, suppliers and clients.

The four groups were found to disagree about the relative importance of the obstacles. Contractors and suppliers ranked “restrictive price-only tender assessment” used by clients as their number one obstacle, while consultants thought there was too much emphasis by the clients on direct costs compared with whole-of-life costs. On the other hand, clients felt suppliers do not do enough thorough testing prior to proposing a new product and disagreed with suppliers about who should carry the risk of new product failure.

The conceptual framework was found to yield novel insights with significant policy implications. The construction-specific contextual determinants that were integrated by the authors into a broad innovation diffusion process proved useful in categorising road product innovation obstacles across the four surveyed supply chain groups – without overlap or omission. The new framework also proved useful in ordering the key obstacles across groups for interpretation and discussion. In disaggregating product obstacles according to groups, these contextual determinants were proven to be mutually exclusive and to represent important focal points in promoting the uptake of product innovation in construction. Although the current study has usefully provided quantitative data concerning construction innovation obstacles, there are limitations due to its reliance on descriptive statistics. Future work by the authors is proposed to analyse the relationships between innovation obstacles and supply chain partners using inferential statistics to further develop and validate these early findings. The current study is an interim step in this work and an important contribution in identifying and addressing firm-level barriers seen to be constraining construction product innovation.

Results suggest there is a need for government clients to carefully consider the differing perspectives across the supply chain when developing strategies to encourage the adoption of mutually-beneficial innovative products on their construction projects. Inclusive focus groups examining the drivers, configuration and benefits of collaborative procurement systems are recommended to reduce innovation obstacles.

Society relies on urban infrastructure for daily living and the current study contributes to stretching infrastructure investment dollars and reducing the environmental impact of infrastructure provision.

No previous study has compared the perception of product innovation obstacles across different road industry supply chain partners. This is a significant gap, as differences in opinions across the supply chain need to be understood to develop the shared expectations and the improved relationships required to improve product innovation rates. Product innovation is important because it has been shown to improve efficiency (potentially addressing the road investment gap) and reduce deleterious environmental impacts.

The steel bars account for a high percentage of material costs for the current construction projects. At the present time, most of the construction projects for the factories of thin‐film transistor liquid crystal display (TFT‐LCD) complete the transactions of steel bars when the suppliers ship the steel bars to the temporary storage/processing sites. This paper applies the buy‐in concept in the Theory of Constraint (TOC) on the supply chain of steel bars. In this study, suppliers are required to establish warehouses at the construction sites and complete the transactions when the formed and processed steel bars are shipped into the factory sites. The aim is to find a win‐win solution to meet with the expectations from constructors as they hope that there is no need to build up inventories but supply is ready at any time. Also, this paper compares and analyzes the traditional supply/inventory model of steel bars and the Demand‐Pull (D‐P) model under the TOC framework. It is proved that Vendor Management Inventory (VMI) in the D‐P model is able to more effectively manage steel bars as a material.

Previous approaches to decision support for project planning using rule‐based expert systems techniques have failed to make an impact in practice. This is primarily because of the complexity and large‐scale nature of construction information, and problems with expert systems including: knowledge acquisition; rule‐based knowledge representation; information storage (or memory); learning; and robustness. Case‐based reasoning is one area of current research which may hold the key to overcoming a number of these problems. In the present paper, previous related case‐based reasoning work is examined. The key factors which influence the formulation of construction project plans are identified. This knowledge is used to develop a conceptual framework within which previous planning experiences can be captured and reused in new situations as a means of providing system decision support in construction planning and control. A prototype system, CBRidge, developed to test and demonstrate the concepts within the framework is presented. The results are very encouraging and provide a sound basis for the further development of case‐based reasoning for construction planning in practice.

The aim of this study is to understand the environmental benefits and economic savings associated with adoption of circular economy in the construction sector. The research findings will support different stakeholders and decision makers to develop business models based on responsible consumption of resources and build sustainable business models.

The research uses mixed methodology wherein inventory for life cycle assessment and life cycle costing for environmental and economic impacts is based on primary data using on-site visits for qualitative and quantitative data.

Different types of land transportation infrastructures are compared for their environmental impacts. It is found that bridges have the highest environmental impacts as compared to tunnels, roads and railways. Further, the results affirm the environmental and economic benefits of adopting circular economy practices.

This is one of a kind research that compares the environmental and economic tradeoffs of adopting circular economy in different types of land transportation infrastructures.

This paper explores the impact of both government subsidies and decision makers' loss-averse behavior on the determination of transportation build-operate-transfer (BOT) concession periods based on cumulative prospect theory (CPT). The prospect value of a transportation project under traffic risk can be formulated according to the value function for gains and losses and the decision weight for gains and losses. As an extra income for investors, government subsidy is designed for highly risky aspects of BOT transportation projects: uncertain initial traffic volumes and fluctuating growth rates.

A decision-making model determining the concession period of a transportation BOT project is proposed by using the Monte-Carlo simulation method based on CPT, and the effects of risky behaviors of private investors on concession period decision making are analyzed. A subsidy method related to the internal rate-of-return (IRR) corresponding to a specific initial traffic volume and growth rate is proposed. The case of an actual BOT highway project is examined to illustrate how the method proposed can be used to determine the concession period of a transportation BOT project considering decision makers' loss-averse behavior and government subsidy. Contingency analysis is discussed to cope with possible misestimating of key factors such as initial traffic volume and cost coefficients. Sensitivity analysis is employed to investigate the impact of CPT parameters on the concession period decisions. An actual BOT case which failed to attract private capital is introduced to show the practical application. The results are then interpreted to conclude this paper.

Based on comparisons drawn between a concession period decision-making model considering the psychological behaviors of decision makers and a model not considering them, the authors conclude that the concession period based on CPT is distinctly different from that of the loss-neutral model. The concession period based on CPT is longer than the loss-neutral concession period. That is, loss-averse private investors tend to ask for long concession periods to make up for losses they will face in the future. Government subsidies serve as extra income for investors, allowing appointed profits to be secured sooner. For the benefit side of contingency variables, the normal state of initial traffic volume, average annual traffic growth rate and bias degree and the government subsidy need to be paid close attention during the project life span. For the cost side of contingency variables, the annual operating cost variable has a significant impact on the length of predicted concession period, while the large-scale cost variable has minor impact.

With an actual BOT highway project, the determination of transportation BOT concession periods based on the psychological behaviors of decision makers is analyzed in this paper. As the psychological behaviors of decision makers heavily impact the decision-making process, the authors analyze their impacts on concession period decision making. Government subsidy is specifically designed for various states of initial traffic volume and fluctuating growth rates to cope with corresponding high risks and mitigate private investors' loss-averse behaviors. Contingency analysis and sensitivity analysis are discussed as the estimated values of parameters may not be authentic in actual situations.