Digital Shift in Construction in Australia

Unlocking Potential with AI and Blockchain

Authors

DOI:

https://doi.org/10.25120/jre.4.2.2024.4155

Keywords:

Artificial Intelligence, Blockchain, Construction Industry, Leadership, Digital Transformation, Digital Leadership

Abstract

For any country, the construction industry forms the backbone of economic growth and development. In recent times, Australian construction sector has been struggling to keep up with the increasing demands of economic growth. Being one of the least digitalised industries, the construction industry is facing myriad of challenges including inaccurate cost efficiencies, labour shortages and poor quality management and limited visibility to all the stakeholders. The advancement of digital technologies such as Artificial Intelligence (AI) and Blockchain has proven to be transformational in other sectors such as finance and banking. This research paper examines the benefits of Artificial Intelligence (AI) and blockchain throughout the different phases of the construction project lifecycle. The adoption of AI is met with resistance from leadership and sceptic approach from users. The role of leadership becomes pivotal in widespread adoption of AI and thus changing the attitude of users from “resistance to change” to “receptiveness to change.” Furthermore, various management strategies and recommendations have been discussed in detail to help the leadership teams to accelerate the digital transformation in the Australian construction industry.

References

Chan-Sik Park, D.-Y. L.-S. (2013). A framework for proactive construction defect management using BIM, augmented reality and ontology-based data collection template,. doi:https://doi.org/10.1016/j.autcon.2012.09.010

Chui, M. &. (2017). Artificial intelligence the next digital frontier. McKinsey and Company Global Institute.

Dena Mahmudnia, M. A. (2022). Blockchain in construction management: Applications, advantages. doi:https://doi.org/10.1016/j.autcon.2022.104379

Górecki J, B. E.-G. (2022). Leadership models in era of new technological challenges in construction project. doi:https://doi.org/10.1371/journal.pone.0278847

Hao Wang, H. Q. (2020). Blockchain-based fair payment smart contract for public cloud storage auditing. Information Sciences. doi:ttps://doi.org/10.1016/j.ins.2020.01.051

Lines, B. C. (2015). Overcoming resistance to change in engineering and construction: Change management factors for owner organizations. International Journal of Project Management. doi:https://doi.org/10.1016/j.ijproman.2015.01.008

Longhui Liao, E. A. (2019, September). Reducing Critical Hindrances to Building Information Modeling Implementation. doi:https://doi.org/10.3390/app9183833

Longhui Liao, E. A. (2019, September). Reducing Critical Hindrances to Building Information Modeling Implementation: : The Case of the Singapore Construction Industry. doi:https://doi.org/10.3390/app9183833

Massimo Regona, T. Y. (2022). Opportunities and Adoption Challenges of AI in the Construction Industry: A PRISMA Review. Journal of Open Innovation: Technology, Market, and Complexity. doi:https://doi.org/10.3390/joitmc8010045

Mésároš, P. S. (2024). The Potential of Using Artificial Intelligence (AI) to Analyse the Impact of Construction Industry on the Carbon Footprint. SpringerLink. doi:https://doi.org/10.1007/s11036-024-02368-y

Moumita Das, X. T. (2022). A blockchain-based integrated document management framework for construction applications. doi:https://doi.org/10.1016/j.autcon.2021.104001

Nyathani, R. (2023). AI-Driven HR Analytics: Unleashing the Power of HR Data Management. Journal of Technology and Systems. doi:10.47941/jts.1513

Obinnaya Chikezie Victor, N. (2023). The application of artificial intelligence for construction project planning. doi:https://doi.org/10.21203/rs.3.rs-2801695/v1

Olorunshogo Benjamin Ogundipe, A. C. (2024). material, Optimizing construction supply chains through AI: Streamlining material procurement and logistics for project success. doi:https://doi.org/10.30574/gscarr.2024.20.1.0258

Omotayo Sanni, O. A.-C. (2024). Prediction of inhibition performance of agro-waste extract in simulated acidizing media via machine learning. doi:https://doi.org/10.1016/j.fuel.2023.129527

Shengluan Hou, S. Z. (2020). Rhetorical structure theory: A comprehensive review of theory, parsing methods and applications,.

Shengluan Hou, S. Z. (2020). Rhetorical structure theory: A comprehensive review of theory, parsing methods and applications,. doi:https://doi.org/10.1016/j.eswa.2020.113421.

Sofiat O. Abioye, L. O. (2021). Artificial intelligence in the construction industry: A review of present status, opportunities and future challenges. doi:https://doi.org/10.1016/j.jobe.2021.103299

Williams, S. (2024). AI use surges in Australia's construction industry. Retrieved from https://itbrief.com.au/story/ai-use-surges-in-australia-s-construction-industry

Zulu, S. L. (2023). Digital leadership enactment in the construction industry: barriers undermining effective transformation. Engineering, Construction and Architectural Management. doi:https://doi.org/10.1108/ECAM-05-2022-0491

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Published

2024-12-30

How to Cite

Gupta, M., & Nofal Arif, R. (2024). Digital Shift in Construction in Australia: Unlocking Potential with AI and Blockchain . Journal of Resilient Economies (ISSN: 2653-1917), 4(2). https://doi.org/10.25120/jre.4.2.2024.4155