Date of Award
2024
Document Type
Thesis
Publisher
Edith Cowan University
Degree Name
Doctor of Philosophy
School
School of Business and Law
First Supervisor
Professor Kerry Brown
Second Supervisor
Dr Richard Fulford
Third Supervisor
Professor Mark Goh
Abstract
The construction industry plays a significant role in the development of economies. This industry in Australia contributed around 20% Australian Trade and Investment Commission (2023) to its gross domestic product (GDP) of over US$1.80 trillion (approximately AUD 2.85 trillion) (OECD, 2023).The federal budget for 2022–23 allocates AUD 17.9 billion over a decade towards major infrastructure projects, encompassing substantial funding for nationwide road and rail projects. The overall investment in major public infrastructure is anticipated to surpass AU$218 billion from 2021 to 2025. Approximately 182,000 individuals are employed in Australia's major public infrastructure projects, with an additional 1.2 million individuals working in related industries (Australian Trade and Investment Commission, 2023).
However, the construction industry confronts a wide range of challenges that influence their success. The inherent complexity and uncertainty of a construction project make it difficult to successfully manage even for experienced project managers. The Australian construction sector grapples with significant challenges, primarily marked by a lack of productivity growth and increased pressures related to risk management. Australia has faced persistently poor productivity over the past three decades, resulting in an estimated AU$47 billion in lost opportunities. According to the 2023 KPMG Global Construction Survey, a staggering 87% of project managers continue to encounter difficulties in project performance, characterized by schedule delays and cost overruns. Additionally, a mere 50% of project owners are successfully meeting completion deadlines, predominantly due to effective risk management (Johnston, 2023).Understanding and achieving project success is critical for project sponsors to control current and future projects. In practice, however, determining key success factors and key success criteria to evaluate the performance of construction projects and forecast the success of new projects is a difficult task.
This research explores project success factors and criteria for the Australia and New Zealand construction industry using multi-criteria decision-making (MCDM) techniques to achieve more targeted forecasting of project success. Aligned with the project-oriented theory and the contingency theory of organisations, this research views a construction project as a transient organisation or coalition that fulfils a purpose. This study goes beyond the traditional efficiency-oriented project success criteria and considers both efficiency- and effectiveness- iv oriented measures to evaluate project success. This research identifies a holistic set of project success factors and criteria and classifies them and contribute to the project-oriented theory and the contingency theory of organisations.
Comprising two bibliometric literature reviews, two multi-criteria analysis of critical success factors and criteria, and a study using adaptive neuro-fuzzy inference system (ANFIS) to forecast the success of medium and large construction projects, this research makes key contributions to the literature on project success in the construction industry. A total of 181 project managers from Australia and New Zealand participated in the empirical studies, providing 11 expert responses for a two-round Delphi study, 28 expert responses for the MCDM analysis of success factors and criteria, and 142 responses for forecasting project success using ANFIS. The major contributions of this study are in (1) determining the interrelations and priority of critical success factors and criteria for medium and large construction projects to effectively manage them and (2) developing an expert system using an adaptive neuro-fuzzy inference system (ANFIS) to forecast the success of medium and large construction projects. These findings may help construction project managers in public and private sectors to coordinate, manage, and control critical success factors and criteria towards improving project success and design appropriate decision support systems that accurately forecast it.
DOI
10.25958/zd4b-ax56
Access Note
Access to this thesis is embargoed until 21 August 2029.
Recommended Citation
Kiani Mavi, N. (2024). Forecasting project success in the construction industry using multi-criteria decision-making tools and adaptive neuro fuzzy inference system. Edith Cowan University. https://doi.org/10.25958/zd4b-ax56