Integration of Emerging Technologies with Construction Practices in Australia

Abstract

Although the construction sector significantly bolsters the Australian economy, it is widely recognised for lagging behind other industries in adopting emerging technologies. This study reviews existing literature to explore the current state of technology integration in the Australian construction industry, focusing on its impact on safety, cost, quality, and project timelines. The research methodology involved conducting interviews and surveys with industry stakeholders to collect qualitative and quantitative data regarding technology integration. The analysis of survey data provided insights into the current and anticipated future adoption of emerging technologies in Australia, identifying significant obstacles that impede the industry’s digital transformation. Based on the survey results, a specialised system was developed for Tier 1 and Tier 2 construction firms, enabling them to evaluate their present and predicted future use of emerging technologies. Additionally, this system helps university graduates gauge their understanding and awareness of emerging technologies to meet the expectations of leading industry professionals. The findings of this study aim to enhance the understanding and implementation of emerging technologies within the construction sector, thereby fostering a new generation of professionals who recognise the significant potential of these technologies to revolutionise construction practices.

1. Introduction

The Reserve Bank of Australia places the construction industry as the fourth greatest contributor to the Australian economy [1]. Despite this substantial contribution, the productivity gap in construction is widening, with construction falling 1.6% since 1990, while most industries have grown by 35.2% [2]. This poor productivity costs the Australian economy $47 billion annually [3]. There has also been an 80% rise in skilled construction worker vacancies since 2019, and a deficit of 105,000 skilled professionals [3,4]. The Australian economy would be $28.6 billion larger with the absence of work-related injuries and illnesses, for which construction is substantially responsible [5]. Further, rectifying building defects burdens the Australian economy by $6.2 billion [6]. It is thus evident that a new approach to enhance construction practices is required. The rapid digitisation of industries after the COVID-19 pandemic, paired with the recent emergence of readily accessible Artificial Intelligence through ChatGPT, encourages the investigation into emerging technologies to address the shortcomings of construction practices [7,8,9,10]. Scholars such as Soltani, Maxwell [7] posit the Industry 4.0 theory, which suggests that the digitisation of the construction environment is necessary to improve construction practices.

The objectives of this paper are (i) to perform a critical analysis of the literature from the past three decades exploring the integration of emerging technology with construction practices; (ii) to investigate the current and future state of emerging technology integration in Australian construction practices according to the experience of leading industry experts; and (iii) to investigate the state of industry training and the expected competency levels among professionals and university students in adopting emerging technologies in Australian construction practices.

The scope of emerging technologies studied was limited to those deemed the most critical and relevant amongst construction practices according to recent literature. These technologies are Building Information Modelling (BIM), Artificial Intelligence (AI), Digital Twin (DT), Virtual Reality (VR), Augmented Reality (AR), Unmanned Aerial Vehicles (UAVs), and sensor-related technologies. The integration of emerging technologies was explored in relation to the design and construction phases of the project lifecycle. Interviews were conducted with leading experts in the Australian construction industry who occupy senior roles with significant years of experience and/or expertise in the deployment of digital technologies. Questionnaires were subsequently conducted with a variety of industry stakeholders from tier 1, tier 2, tier 3, and boutique-sized construction organisations. These industry stakeholders were categorised into two main groups for the purpose of analysis: (1) “Senior Executives” and (2) “Engineers”. Figure 1 provides a summary of the scope of this paper and the industry stakeholders classified under each of these two questionnaire participant groups.

2. Materials and Methods

To establish how emerging technologies are integrated in construction practices, it is crucial that the nature of the construction industry, as discussed in the literature, is analysed.

2.1. General State of the Construction Industry

Innovation and technology adoption in the construction industry consistently fall behind other industries [7]. The importance of digitising construction is explored in the literature through numerous theoretical frameworks. Industry 4.0 is a key theory described as “the integration of physical and digital environments, driven by trends in connectivity [and] advanced technology” to improve construction practices [7]. Although other theories are often explored, such as the Technology Acceptance Model, Building Information Modelling Theory, and Sustainability and Green Building Theories, these theories focus on the potential of one specific technology or on improving a project’s sustainability, rather than addressing construction practices themselves. The principles of Industry 4.0 prioritise improving the efficiency, safety, quality, and productivity of a project. Thus, the theoretical framework of Industry 4.0 was deemed most suitable as the basis for this paper.

While there is substantive international literature exploring the integration of emerging technologies, there is limited analysis of the Australian construction industry [7,8,10]. The complexity of construction projects and the numerous stakeholders often lead to lower project performance, such as cost overruns or project delays [9]. Construction research is often completed at the project level [11]. Project performance is often analysed by researchers by investigating four key factors: the safety, cost, delay, and quality of a project, in line with the theory of Industry 4.0 [11,12]. There is currently no literary discussion on the perspectives of industry professionals, which is vital for successfully advancing technology integration. Understanding these perceptions ensures technology is successfully developed and implemented in alignment with actual industry practices, rather than in a fragmented manner.

Barriers Hindering Emerging Technology Integration with Construction Practices

To understand the current and future integration of emerging technologies, it is crucial to examine the various factors identified by scholars as hindering their adoption in an Australian context. Soltani, Maxwell [7] explains that understanding and addressing these barriers is important as it will increase the sustainability and productivity of the industry while reducing construction costs. A fragmented industry landscape, a reluctance to embrace new approaches, significant expenses, and limited resources are major challenges to the integration of emerging technology [7]. Davila Delgado, Oyedele [13] state that technology is not integrated into construction due to inadequate training and a lack of knowledge.

Research in relation to barriers critical to industry leaders is limited and inconsistent. Bigham, Adamtey [14] investigated the Australian public’s perception of Artificial Intelligence (AI) based on social media posts. Although insightful, it was conducted in a pre-COVID environment with a focus on AI alone. The results of Perera, Xiaohua [15] affirm that the top three barriers for Australian builders to the adoption of technology are the high costs of software purchasing/licensing, high costs of digital tools, and inadequate fees to support digital innovation. Meanwhile, Chen, Chang-Richards [16] results were obtained from industry professionals in New Zealand and revealed the major barriers are the status quo industry standards, a lack of client interest, and insufficient funding. Psychological barriers, including apprehension about changes in the workplace and a lack of confidence in emerging technologies, were major factors hindering technological adoption [17]. Temel and Durst [18] discuss how the adoption of new technologies raises fears, particularly among older staff, regarding the risk of job redundancy.

While it is known that government regulations influence the construction industry, its influence on emerging technology integration is less clear. According to Dubois and Gadde [19], government legislation often hinders innovation. However, there has been a shift towards the implementation of ‘performance-based’ regulations that define the final regulatory outcome, rather than prescriptive regulations. The results of Hardie and Newell [20] emphasise that regulatory climate is the most important factor influencing technological innovation in the construction industry. Their results suggest that prescriptive policies are restrictive and limit opportunities to adopt new products [20]. In contrast, performance-based legislation creates high standards that push firms to innovate beyond the capabilities of existing technology, encouraging them to adopt emerging technologies [21]. While these studies provide insights, there is a large gap in the perspectives of industry leaders in Australia regarding the overall impact of regulations on innovation and technology adoption.

Ultimately, there is a significant gap, described by Soltani, Maxwell [7], as a scarcity and “dearth in existing literature” regarding the key factors that Australian industry professionals perceive as the greatest barriers to integrating emerging technologies in the Australian construction industry.

2.2. Integration of Technologies Across the Four Key Construction Factors

2.2.1. Integration of Emerging Technologies to Improve the Safety of Construction Practices

Awolusi, Marks [22], affirmed by Okpala, Nnaji [23], stress the considerable potential of emerging technologies to mitigate the safety risks of construction practices. Utilising AI removes elements of human error, such as the impact of fatigue in decreasing site inspection accuracy, as well as increasing the speed and accuracy with which risks are identified [24]. Monitoring and inspecting the physical entities on site, predicting problems that may arise, and providing feedback to inform decision-making processes are features of DT [25]. On-site sensors capture data, images, and videos to monitor and map construction progress, rendering human inspection unnecessary [26]. ML can analyse and process this data to propose changes and safety measures that should be implemented [27]. Yap, Skitmore [28] emphasise the ability of UAVs to provide high-resolution visuals and perform dangerous site inspections, such as tunnel and bridge inspections. Choi, Hwang [29] achieve a biometric screening of the physical characteristics and safety equipment on-site by incorporating sensor technology and sensing devices on mobile phones and smart watches. Due to Australia’s multicultural landscape, 24% of the construction industry are migrants, many of whom have low levels of literacy and a weakened ability to understand safety requirements [30]. Polmear and Simmons [31] and Tender, Couto [32] posit the benefit of VR and AR for multilingual workers, which is particularly suited to the Australian landscape and workers with low literacy levels. The results of [33] and Polmear and Simmons [31] clearly indicate that visual technique methods are well understood as a source of safety training. Stewart, Mohamed [34] reiterate that workers are motivated to participate in safety training through VR and safety simulations in AR, as it requires less cognitive load, less time to develop skills, and increases enthusiasm. Although academics discuss the benefits of emerging technologies in mitigating safety risks in construction practices, there is a gap in the literature regarding their current application to the Australian construction industry and the opinions of professionals on the effectiveness of these technologies.

2.2.2. Integration of Emerging Technologies to Improve the Cost of Construction Practices

A key indicator of a construction project’s success is the effective management of the costs of construction practices. Emphasis has previously been placed on completing projects at the lowest acquisition cost. There is now a greater shift towards prioritising cost consideration throughout the building’s entire life cycle [35]. The complex, dynamic nature of modern construction projects makes cost management, especially cost reduction, increasingly challenging and intricate [36]. The increasing complexity and dynamic nature of projects necessitate change, as conventional approaches may no longer be effective and appropriate for addressing evolving challenges [37]. Uchenna Sampson, Mohamad [36] highlight the undeniable importance of utilising emerging technology to manage and reduce costs. However, they note that it is not yet widely implemented across the industry. There is a clear gap in the literature regarding the extent of adoption in Australia and the perspectives of those who have implemented these technologies.

Kulkarni and Mhetar [38] use case studies in India to conclude that BIM is effective in accurately estimating cost, scheduling, and monitoring to eliminate unbudgeted changes. VR and AR allow for virtual, detailed inspections of a project’s components and design, providing foresight to potential, expensive problems, which reduces the cost overruns of construction practices [39]. ML uses statistical techniques and neural networks to predict the costs of practices by employing data analysis methods, including principal component regression and evolutionary fuzzy neural inference models [36]. UAVs offer remote sensing, actuation, and predictive capabilities that greatly enhance operational efficiency and greatly lower labour costs [36]. On-site sensors capture data, images, and videos to monitor and map construction development, rendering human inspection unnecessary and reducing construction costs [26]. Thus, various emerging technologies and their potential to reduce the costs of construction practices are discussed. However, there is no literature concerning the current adoption of emerging technologies to reduce costs within the Australian construction industry and the opinions of industry experts.

2.2.3. Integration of Emerging Technologies to Reduce the Delay of Construction Practices

A key indicator of a project’s success is whether it was completed within the planned schedule. Delays often occur due to the complexity, dynamism, and uncertainty of a project [40]. Approximately 72% of projects internationally experience delay in project delivery [41]. Delays in construction practices cause adverse consequences, including productivity loss, revenue loss, client dissatisfaction, and high overhead costs due to possible longer working hours [42]. These delays greatly contribute to legal disputes within the construction industry [43].

Scholars discuss how technology may be used to reduce delays in construction practices. Btoush and Harun [44] investigate delay in construction practices in Jordan, finding that the most common factors causing delay are inadequate design, insufficient communication between stakeholders, and poor scheduling. Btoush and Harun [44] propose BIM as a technology that enables strong coordination and communication between stakeholders through a shared model updated in real time. BIM also identifies design issues early and helps develop accurate schedules and management of resources. Gurgun, Koc [45] reiterate BIMs effectiveness in reducing delays as its 3D and 4D solutions facilitate early clash detection, enhance visualisation, and provide real-time updates. Gurgun, Koc [45] further discuss integrating AI and ML due to their predictive analysis through iterative processing of historical data to forecast delays and take preventative measures. Sensors also reduce delay due to their ability to collect real-time data by monitoring construction progress and tracking material movement [45]. The predictive analytics of DT monitors construction to forecast potential issues and promote better resource management and scheduling [46]. The extensive literary discussion recognises delay as a critical aspect of construction that must be addressed, but there is an absence of research on the present state of technology integration within the Australian industry to reduce delay.

2.2.4. Integration of Emerging Technologies to Improve the Quality of Construction Practices

The quality of construction practices is one of the four major characteristics of a project’s construction. Improving project quality is critical as it creates better outcomes across the project lifecycle by increasing sustainability, cost-efficiency, and general lifecycle management [47]. Researchers are exploring the potential for emerging technologies to improve construction quality [48].

DT improves the quality of construction practices by quickly identifying and resolving quality control issues while also pinpointing their underlying causes [49]. BIM, when integrated with simulation technologies, assists in selecting design solutions that optimise efficiency, sustainability, and space utilisation, ensuring the construction practices that produce the final product are of the highest quality [50]. Blanco, Fuchs [51] state that AI can analyse data obtained from sensors to provide real-time solutions that prioritise preventative maintenance and improve operational efficiency, directly enhancing the quality of construction practices. Heidari, Peyvastehgar [47] and Xu, Wang [48] emphasise how VR and AR improve teamwork by facilitating collaboration amongst various stakeholders in a construction project, which helps identify potential errors early, minimising rework and thus improving the overall quality of the project [47]. AI and ML can analyse images collected from UAVs to detect construction defects, ensuring the quality of construction practices fulfils stakeholder expectations [51]. Although academics discuss the potential for emerging technologies, there is a gap in the literature regarding their current application to the Australian construction industry and the experiences of professionals on the effectiveness of the immersive technologies in improving the quality of construction practices.

2.3. Skills in Using Emerging Technologies

The insurgency of technologies capable of optimising construction practices has rendered digital proficiency among engineers a crucial skill [52]. However, its integration is significantly hindered due to insufficient skills, knowledge, expertise, and experience [7,53,54].

2.3.1. State of Graduate Skills in Using Emerging Technologies

There is a great necessity for the next generation of engineers to develop skills in using emerging technologies to remain competitive and capable [54,55]. A student’s experience in academia directly influences their success within the STEM industry [56]. Scholars argue that there is a significant gap between the skills employers believe graduates have and the skills they actually possess [57]. Thus, the adoption of emerging technologies within the industry creates a pressing need for university curricula to equip students with the necessary technical skills to succeed within the workforce [55].

The results of Suprun, Perisic [54] reveal the level of understanding of students as ‘not very familiar’ with using AR, ‘slightly familiar’ with Sensors, and have ‘some experience’ using BIM. The qualitative analysis completed by Suprun, Perisic [54] reveals that industry professionals believe universities fall short in teaching students the software currently being integrated within the industry. Universities are encouraged to determine the current state of technology implementation in the industry and implement relevant courses within the degree. Broo and Schooling [58] argue that a failure to improve students’ understanding of technologies will impede the rate at which the industry can become more digitised and innovative. Although BIM is widely adopted in the construction industry, the competency of civil engineering students in using BIM must improve as BIM software is continuously evolving to address its own limitations [59]. Similar to Suprun, Perisic [54], Elzomor and Pradhananga [55] results portray that students in the US have a low level of familiarity with technologies including AR, VR, and UAVs, concluding a need to upgrade university curriculum. However, no indication is provided to universities of the level of proficiency and understanding required by students. There is a clear gap in literature concerning the proficiency and understanding of emerging technologies Australian industry professionals expect of students. Further, technologies that are likely to be implemented within industry in the future should be taught in advance [54]. This paper will address this scope for future research by determining the current technologies implemented within the industry, the technologies that are likely to be integrated in the future, and the demand from industry professionals as to the desired level of experience and understanding required of graduate students.

2.3.2. State of Employee Training to Facilitate the Integration of Emerging Technologies

Creating and maintaining skilled workers is imperative to the success of the construction industry [60]. However, most research on training focuses on university students, rather than employees [60]. Kazaz, Manisali [61] articulate that increasing the skill level across graduate students is not a solution to the lack of skills among employees. Department of Employment and Workplace Relations [62] argues that the greatest barrier to integrating emerging technologies is the insufficient skillsets and knowledge bases of employees. Thus, upskilling and reskilling the workforce is crucial to ensure technology is integrated effectively [63].

The Australian Workforce and Productivity Agent have highlighted since 2012 the growing requirement for specialised skills “due to the changing technological and social nature of the workplace” [64]. Since this report, limited studies have investigated the state of training within the construction industry [65]. Francis and Paton-Cole [66] highlighted the 2017 findings by the Victorian government that approximately 75% of construction industry professionals believe there is a gap in technical and job-specific skills, which negatively impacts project productivity [67]. As the adoption of digital technologies accelerates and evolves, Australia must seek to adopt a mindset constantly in favour of acquiring new skills and knowledge [68]. Upeksha Madanayake, Bert Ediale Young [69] and Solis, Howe [70] reiterate that a lack of training has hindered the integration of technologies in industry. Scholars including Olanipekun and Sutrisna [71] and Douglas Omoregie Aghimien, Clinton Ohis Aigbavboa [72], based on their experience in New Zealand and South Africa, respectively, argue that training has improved employees’ digital skills and capabilities. Institutionalised training and intraorganizational training are also considered opportunities to train employees. Despite this literary discussion, there is no evidence of what approach to training is being used in the Australian construction industry.

3. Research Methodology

To achieve the research objectives, a combination of qualitative and quantitative data were obtained using interviews and surveys. The methodology obtained the opinions and experiences of industry professionals on the current and future integration of emerging technologies with construction practices.

3.1. Literature Review on Different Interview Styles

Interviews were conducted to facilitate detailed verbal discussion into the integration of emerging technologies with construction practices in the Australian construction industry. Unstructured, structured, and semi-structured interview styles are the most beneficial methods for evaluating and assessing the opinions and experiences of participants [73]. Unstructured interviews have minimal preset structure and often consist of the interviewee talking while the interviewer maintains the role of listener [74]. Structured interviews contain a standardised list of questions to reduce variability across interviews. However, utilising this interview form limits the flexibility of discussions, which would provide greater understanding into the current state of the construction industry and thus can hinder the interpretation of results [73]. Semi-structured interviews consist of initially structured questions with an opportunity for follow-up and open-ended questions, allowing the interviewer to query angles and comments made, navigate the conversation towards the topics being discussed, and ensure that all required data are obtained [74].

There are, however, limitations to semi-structured interviews. The resources and time required to recruit participants, conduct the interview, edit the transcripts, and analyse the data are often underestimated [75]. Another issue is that interviewees may be difficult to converse with or may not be comfortable sharing information, which can negatively affect the depth and quality of the data collected [75]. The success of semi-structured interviews is dependent on the interviewee’s strengths in actively listening, asking follow-up questions, and probing for more information where necessary [75]. Language barriers may impact the depth of the conversation, and industry leaders may not have time to participate in the interview [76].

A semi-structured format was deemed the most appropriate interview style, as the interview can contain two components: the prepared set of interview questions and open discussion with participants to provide an in-depth understanding of the reasoning and experience that influenced their responses. The limitations for this interview style are easily addressed or inapplicable.

3.2. Conducting the Interview to Obtain Primary Qualitative Data

3.2.1. Design of Semi-Structured Interviews with Industry Experts

The interview was designed to have three sections. The first section of the interview is an introductory section on the participant and collects the interviewee’s personal information, including age, years of experience, job position, and place of employment. The second section is the ‘Emerging Technology Analysis’. This section identifies which emerging technologies are currently being integrated and their specific applications, as well as the technologies likely to be integrated in the future. Participants were also asked about the role of factors such as project budgets, timelines, and project stakeholders in determining which emerging technologies were integrated. This section also explores the benefits, shortfalls, and limitations associated with integrating emerging technologies with construction practices. Participants were invited to discuss the current and future risks prevalent to the increased adoption of these technologies. The final section of the interview is ‘Graduate Skills and Training’. Participants were asked to discuss the key skills graduates required to effectively meet industry demands in relation to emerging technologies. Participants were also asked to reflect on any training they had received in using emerging technologies and evaluate its effectiveness.

3.2.2. Addressing Limitations of the Semi-Structured Interview with Industry Experts

Potential limitations specific to interviewing industry experts were also addressed from the outset. Interviewers must protect the confidentiality of participants and reduce the risk of exploitation [75]. To address this, informed consent for participation was obtained from all subjects involved in the study. Further, at the beginning of each interview, participants were informed that no personal, confidential, or business-related information was required. If any confidential information was disclosed, it would be redacted in the written transcripts, and participants could request the removal of any other statements made during the interview. The researchers thoroughly reviewed the transcripts against the Zoom recordings to ensure the accuracy of all statements made and correct any discrepancies.

The target audience of the interview was industry experts, such as headquarters managers, construction directors, digital services specialists, and CEOs. Participants were contacted via personal connections developed through Industry Nights, external networking events, work relations, and USYD and UNSW alumni. To broaden the scope of interviewee candidates, research was conducted into conferences discussing the construction industry, such as the Sydney Build Expo 2024, and individuals deemed relevant to the study were contacted. Individuals were contacted via text message or email to enquire about their willingness to participate in the interview. A total of nine industry experts were interviewed. Each interview participant will be referred to as Participant 1 (P1), Participant 2 (P2), etc. The interviews were 45–60 min in duration and were completed over a two-week period.

3.3. Literature Review on Different Survey Styles

Mixed modes of data collection enhance research validity by triangulating data from multiple sources [77]. Alongside the interview, a survey was used to acquire primary quantitative data.

A survey was chosen as the primary data collection method as it is a scientifically accepted and validated manner to measure the attitudes of industry professionals toward different technologies [78]. Quantitative data were gathered from the questions that adopted the 5-point Likert numerical scale. Surveys are efficient in “collect(ing) information directly from people in a systematic, standardised way” [79].

Three mediums were considered for the survey: telephone, mail, or online. Telephone surveys would negatively impact response rates as people would not have the flexibility of completing the survey at a time convenient to them. It is also time-consuming, as the interviewer must read out all the questions, and some people may assume it is a scam [80]. Unlike mail or online surveys, telephone surveys require an interviewer, which may introduce interviewer bias and place a large responsibility on the interviewer in accurately reading out the questions and recording the responses [80]. Mail surveys were deemed inefficient, as unlike telephone and online surveys where participants press ‘Submit’ or end the call, respondents are required to physically mail their responses back to the researchers, which also risks delaying the receipt of results within the research deadlines. This additional effort is time-consuming and may discourage participation in a digital age where people are accustomed to online interactions [80]. There are also additional printing and postage costs.

Obtaining data online is advantageous as it can be acquired in large volumes in a very short amount of time [81]. As this study aims to investigate the integration of emerging technologies in construction practices across Australia, online surveys allow responses to be obtained nationwide [82]. It is also completed with little to no cost, as there are no paper, postage, or telephone fees [80]. Online surveys allow for flexible designs, where questions may be presented in interactive or diverse formats, which promotes participant engagement [81]. The data collection process is streamlined as results can be directly integrated into analytical databases, minimising human error in transcribing and transferring data [83]. Online surveys do not have the pressure of immediate completion, providing substantial flexibility to participants as they can complete the survey at any time convenient to them prior to the close of the survey [84]. When conducting online surveys, a few limitations may arise. There may be low response rates due to a fear that the online survey is ‘spam’ or junk. Companies also may not circulate externally created surveys. Online surveys completed anonymously prevent follow-up questions to respondents who provide interesting answers. Finally, in the event of technical issues, potential participants are likely to delete the email, rather than request the survey be reissued. Thus, online surveys were selected due to their numerous advantages, with many limitations being manageable and minimised.

3.4. Conducting the Survey to Obtain Primary Quantitative Data

3.4.1. Design of Online Survey for Industry Professionals

The survey was designed as an online questionnaire with a series of multiple-choice questions and a few open response questions. To maximise participation rates across a wide range of time-constrained industry professionals, the survey was designed to have 3 sections, 21 questions, and an estimated completion time of 10 min. The first section is an Introductory section to the Participant, which mirrors the introductory questions found in the interview (discussed in Section 3.2). This section obtains personal factors including age, years of experience, job position, and place of employment. It should be noted that these are not personal identifiers of the recipient themself. Rather, it provides a general indication as to the participants’ demographic and position within the industry.

The second section is the ‘Emerging Technology Analysis’. The survey questions were designed to gather the opinions of industry professionals. Participants were asked to rate the importance of emerging technologies in their current projects and the projected importance in their future projects. They were also asked to rate the importance of emerging technologies in improving the safety and quality and minimising the delays and costs of construction practices. The responses to the survey questions were designed to follow the five-point Likert scale, as it is a scientifically validated questioning style to measure the attitudes of participants to a general topic [78]. This approach allows qualitative attitudes to be converted into quantitative data for analysis. A symmetric Likert scale from 1 to 5 was used, where 1 = Very Unimportant, 2 = Unimportant, 3 = Neutral, 4 = Important, and 5 = Very Important. The two responses reflecting support and the two responses reflecting opposition provided participants with the independence to choose any response in a balanced manner with no bias [78]. At the end of this section, participants could provide additional textual commentary to provide insight into their opinions and experiences that have influenced their decision. Issuing the same survey to all participants maintained the reliability and validity of the data [85]. The final section is ‘Graduate Skills and Training’, which includes Likert scale questions, multiple choice, and open-ended responses to gather quantitative data and additional comments. This combination allows for more comprehensive analysis by obtaining structured data and nuanced participant insights.

3.4.2. Ethical Considerations When Designing the Survey

Various ethical factors were considered when designing the survey. It is required that any researchers at the University of Sydney obtaining data from humans complete the Human Ethics Application. The Application process is rigorous and incredibly detailed, ensuring that the research is completely ethical. To ensure the research was conducted ethically, the survey was designed to be confidential and anonymous. Taylor-Powell and Hermann [79] posit that participants are more likely to complete the survey if their responses are anonymous. The questions were carefully draughted to ensure that no information that directly identifies individual participants would be required. A landing page for the survey was created for participants to review prior to beginning the survey. The landing page stated that “no personal or confidential information is required to complete the survey”, emphasising the anonymity and ethical nature of the survey. After all the data were received, it was stored securely on password-protected University servers. The researchers amended the original survey questions, necessitating a revision to the Ethics Application. This process involved redrafting the survey, submitting a tracked changes document outlining all modifications, providing written justifications for each change, and waiting one month for the Ethics Committee’s feedback on amendments that may be required. No amendments were required. Taylor-Powell and Hermann [79] emphasise the necessity of obtaining the participants’ consent before completing the survey. To address this, participation in the survey was voluntary, and respondents could discontinue at any time prior to submitting their answers. A consent form was also included within the survey’s landing page. Participants were informed that pressing “Submit” would provide their consent for their response to be recorded and used within the data analysis.

3.4.3. Addressing Limitations of the Online Survey

Potential limitations of the survey were addressed from the outset. Participants may default to completing the survey on a range of devices other than a computer [80,81,84]. If the user interface of a survey is not optimised on a smaller screen, whereby the layout is difficult or unclear to navigate, it may hinder a participant’s ability to effectively complete the survey and create a reluctance to complete it due to the lack of clarity. This was addressed by using Microsoft Forms, which has a mobile experience that ensures all features are fully functional and optimised on a mobile device [86]. Technical challenges, such as mobile coverage, internet access, and digital literacy, could also impact participant responses [81,87]. This limitation is not relevant here, as construction industry professionals typically have reliable internet and mobile access through their work infrastructure. Further, only basic digital literacy, which is common across the workforce, is required to complete the survey. Multitasking or distractions while completing the survey may impact the quality of the results [82,84]. To minimise this, the survey was designed to be concise, with 21 questions and an estimated completion time of 5–10 min, encouraging respondents to complete it in one sitting without feeling the need to multitask.

3.4.4. Target Audience of the Online Survey

The survey was distributed to 190 people. Individuals were contacted via text message or email to enquire about their willingness to participate in the survey. Additional details regarding the nature, anonymity, and confidentiality of the survey were also provided to ensure informed participation. A range of construction industry workers were contacted, including CEOs, Directors, engineers, project managers, consultants, and site engineers. Sample sizes between 20 and 60 participants are most frequently observed in qualitative research [88]. This range served as an initial guide for our expected sample size. A total of 66 responses were received over a three-week period, leading to a response rate of 35%.

4. Results and Discussion

4.1. Literature Review on Different Survey Styles

4.1.1. Interpreting the Interview Results

The primary purpose of the interviews was to collect qualitative data on the opinions of industry experts on the integration of emerging technologies with construction practices. In preparation for analysis, the interview transcripts were edited and cross-checked against the audio recordings, as discussed in Section 3.2. To analyse the qualitative data, the edited transcripts were imported into NVivo. NVivo 15 is a software that facilitates numerous stages of qualitative research, helping manage and organise large volumes of data [89]. NVivo offers significant advantages for qualitative data analysis. It simplifies complex tasks, such as identifying key themes and subthemes [89]. NVivo enhances the credibility of qualitative research by promoting rigour through systematic coding, which transparently documents each step of the analysis. This process makes research conclusions more trustworthy by reducing the ambiguity around the origin of insights; that is, by clarifying whether they come from participants or the researcher’s interpretation [89]. NVivo’s visualisation tools improve the efficiency and overall quality of data analysis [89].

4.1.2. Analysing the Qualitative Data Using Thematic Analysis

Thematic analysis was used to interpret the interview results, as it is a proven form of qualitative research [90]. It involves identifying key themes and coding the data into those themes beyond the interviewee’s explicit words [91]. This method allows researchers to derive patterns and deeper meanings within the data, creating a structured approach to qualitative analysis that is flexible and iterative [91]. NVivo was used to code all transcripts and qualitatively analyse the data. Due to the semi-structured nature of the interviews, not all questions were answered within their designated sections, with some responses provided ahead of the corresponding question. Therefore, the transcripts required thorough analysis to organise and allocate the information accurately. This was completed through creating twelve codes based on the survey questions and recurring discussion points, as themes should not be defined in advance but rather created by the coding process [90,91]. The transcripts were then manually reviewed, and relevant participant quotes were assigned to the corresponding codes. This analysis allows easy access to participant responses categorised under each code, which was used to develop the schematic in Figure 2 below representing key themes.

4.2. Interpreting the Survey Results

As outlined in Section 3.4, 66 participants completed the survey with a response rate of 35%. The first section of the survey obtained introductory information about the participants. Figure 3 shows the years of experience of each participant in the construction industry, with approximately 40% of survey participants having over 20 years of experience.

The position of employment of the survey participants is displayed in Figure 4, with a third of all survey participants being engineers.

Analysing the Qualitative Data Using Thematic Analysis

The Analytical Hierarchy Process (AHP) is a “multicriteria decision-making approach in which factors are arranged in a hierarchic structure” [92]. The hierarchic structure facilitates a process of pairwise comparisons to derive a set of priorities/weights, which transform subjective judgements into objective measures [92,93]. The AHP works through establishing ‘criteria’ to obtain data, ‘alternatives’ to assess the criteria, and a weight for each criterion and alternative [94]. Saaty, Vargas [95] explain that a key strength of the pairwise comparison is that it can be adjusted according to the expertise and knowledge of the stakeholders, resulting in adaptable and context-specific weightings. This method of data analysis is particularly appropriate for this paper as it allows the calculation of the weight of each criterion and its alternatives to consider the participant’s personal context. Given the research objective, to investigate the current and future state of emerging technology integration in Australian construction practices, it is important to consider the participant’s personal context, as it may influence their level of experience and understanding of the actual state of integration. Thus, the AHP was determined to be a suitable method to analyse the data.

Criteria are independent attributes that make one participant’s solutions preferable to another’s with respect to understanding the integration of emerging technologies [93]. In this study, a set of criteria was established. Each criterion had a set of alternatives, which were the multiple-choice options within the survey. The different criteria, alternatives, and justifications for each criterion selected for this paper are shown in Figure 5 below.

The AHP provided a new, weighted score for the Likert scale response for every question from all 66 participants using the following formula [92]:

$${Score}_{weighted}=\left({\displaystyle \frac{C_p}{C_{p_{max}}}}\times {\omega }_p+{\displaystyle \frac{C_e}{C_{e_{max}}}}\times {\omega }_e+{\displaystyle \frac{C_t}{C_{t_{max}}}}\times {\omega }_t+{\displaystyle \frac{C_r}{C_{r_{max} }}}\times {\omega }_r\right)\times {Score}_{Likert Scale}$$

(1)

The weighted eigenvector of each criteria (ω), and the weight of the alternatives for each criteria ($C_p, C_e, C_t, C_r$), as shown in (1), were calculated using the following steps [96]:

• An n × n matrix was created, where n = number of criteria.
• Pairwise comparisons were completed between each combination of criteria, as per

  Table 1. n × n matrix rating each criterion between 1 and 9 for a pairwise comparison.

  	${\mathit{C}}_{\mathit{p}}$	${\mathit{C}}_{\mathit{e}}$	${\mathit{C}}_{\mathit{t}}$	${\mathit{C}}_{\mathit{r}}$
  $C_p$	1.00	3.00	0.50	4.00
  $C_e$	0.33	1.00	0.25	6.00
  $C_t$	2.00	4.00	1.00	9.00
  $C_r$	0.25	0.17	0.11	1.00
  Total	3.58	8.17	1.86	20.00

  . The comparison is based on a relative importance scale of 1–9, where 1 indicates the criteria are of equal importance, and 9 indicates that one criterion is of extreme importance relative to the comparative criterion. As the matrix is inversely symmetrical, the reciprocal of each rating was applied above the diagonal of the matrix [97]. The value for each pairwise comparison constitutes an eigenvector.

  Table 2. The criteria given a greater weighting and its justification.

  Criteria 1	Criteria 2	More Important Criteria	Reasoning
  Position	Experience	Position	Position of employment is considered more important as individuals in higher executive roles, such as CEOs, are required to stay informed about the adoption of new technologies. While individuals with over 20 years of experience may possess substantial knowledge, if their role has remained limited to lower, more confined positions, they may lack a broad exposure or interest in learning about newer technologies.
  Tier	Position	Tier	Tier is more important than position as the target audience for the research and expert system being created is Tier 1 and 2 companies. The responses of participants from these Tiers are more valuable in understanding the current state of industry practices.
  Range	Tier	Tier	Tier is more important than occupation as the target audience for the research and expert system being created is Tier 1 and 2 companies. Further, Tier 1 and 2 firms are at the forefront of technological adoption, so their insights are more relevant to the study, regardless of their geographical scope.

  below summarises the reasoning behind the relative weightings of the criteria.
• A standardised matrix was produced by dividing each eigenvector in Table 1 by the sum of the eigenvectors for each Criterion.
• The average of each row of the standardised eigenvectors for each criterion was calculated [97]. This average constitutes the value of the weighted eigenvector (respondent weighting).
• Steps 1–4 were repeated for the alternatives for $C_p, C_e, C_t, C_r$. The n × n matrix contains the alternatives for each criterion.

Table 3. Weighting of the criteria.

Criteria	Weight of Criteria
Position (${\mathrm{\omega }}_p$)	0.279
Experience (${\mathrm{\omega }}_e$)	0.162
Tier (${\mathrm{\omega }}_t$)	0.509
Range (${\mathrm{\omega }}_r$)	0.050

and

Table 4. Weighting of each alternative.

Criteria	Alternatives	Weight of Alternatives
	$C_p$
Position of Employment	CEO/Executive	0.184
	Principal Engineer	0.184
	Construction/Project Manager	0.184
	Digital Services Specialist	0.184
	Engineer/Consulting Engineer	0.097
	Site Engineer	0.097
	Business/Legal Management	0.035
	Architect	0.035
	$C_e$
Years of Experience	0–2 years	0.082
	2–5 years	0.082
	5–10 years	0.149
	10–15 years	0.149
	15–20 years	0.269
	20+ years	0.269
	$C_t$
Tier of Employment Firm	Tier 1	0.425
	Tier 2	0.425
	Tier 3	0.094
	Boutique	0.056
	$C_r$
Range	Yes	1.000
	No	0.000

summarise the weight for each criterion and alternative.

Difficulty maintaining comparability across criteria sets is a possible limitation in the AHP, as each criterion has a unique number of alternatives and weightings. Criteria with greater maximum values, such as Ct with a maximum value of 0.425, will disproportionately affect the final score and overshadow criteria such as Cp, where the maximum value is 0.184. Normalisation techniques are used within the AHP to address these potential issues [98]. Normalising the values for C will create a comparable scale across all the criteria, preventing disproportionate results. When normalised, each criterion’s impact on the final score is balanced according to its designated importance [99]. The data were normalised using the normalisation technique thatVafaei, Ribeiro [98] concluded was the most suitable for the AHP; each criterion is divided by the maximum value of the criteria weighting for that specific set.

Finally, to synthesise the large volume of data, the weighted scores were grouped together. Participants were classified into three groups based on their occupation, shown in

Table 5. Groupings of survey participants based on their position of employment.

Group 1 (‘Executives’)	Group 2 (‘Engineers’)	Group 3 (‘Architects/Business’)
Position of Employment	CEO/Executive	0.184
	Principal Engineer	0.184
	Construction/Project Manager	0.184
	Digital Services Specialist	0.184
	Engineer/Consulting Engineer	0.097
	Site Engineer	0.097
	Business/Legal Management	0.035
	Architect	0.035

below. The three groups were then analysed within the Tier of the company at which they were employed.

The weighted scores of the groups were calculated by taking the averages of each position. For ease of reference, the remainder of this paper will refer to Group 1 as ‘Executives’, Group 2 as ‘Engineers’, and Group 3 as ‘Architects/Business’. No survey participants fell into the Tier 3 and Boutique firms’ Group 3 category.

A major limitation of the AHP is the subjective nature of evaluating the importance of each combination of alternatives. This subjectivity often prevents the matrix from being consistent [97]. To address this limitation, the consistency ratio of each matrix was calculated according to the following steps:

• The Consistency index (S) of each matrix was calculated using the equation $S={\displaystyle \frac{{\lambda }_{max}-n}{n-1}}$, where $n$ = number of alternatives and ${\lambda }_{max}$ = average of the priority eigenvectors.
• To calculate ${\lambda }_{max}$, the priority eigenvectors were required. A priority eigenvector matrix was created by multiplying each pairwise comparison eigenvalue by its corresponding weighted eigenvector. The priority eigenvector was then calculated by dividing the sum of all priority vectors by its corresponding weighted eigenvector [93].
• The consistency ratio was calculated using the equation $C={\displaystyle \frac{S}{R_S}}$, where $R_S$ = the random consistency index [97].
• A CR < 10% is deemed acceptable, and thus the matrix is consistent [93,95]. As each CR < 10%, the matrices were consistent, and the impact of the subjective nature of the AHP was minimised. This was satisfied for all matrices.

4.3. Discussion of Results

This discussion will delve into the findings from the semi-structured interviews and the online survey, aiming to bridge the gaps identified in the Literature Review. We will first provide a general analysis of the current state of emerging technology integration within the construction sector, subsequently focusing on its alignment with the four primary aspects of construction practices. Additionally, we will explore the prospects of integrating emerging technologies and identify the obstacles that impede their adoption.

Considering the crucial role of professional training and education in fostering technology adoption, we will assess the existing industry training frameworks and the requisite skill sets expected from new graduates. Furthermore, we will introduce two expert systems to enhance industry engagement with emerging technologies. The first system will enable Tier 1 and Tier 2 companies to evaluate their technology usage against the survey results. The second system will help graduates assess their understanding of emerging technologies compared to industry standards. All data presented will be based on the weighted Likert ratings derived from the Analytic Hierarchy Process (AHP) analysis.

4.3.1. Current Integration of Emerging Technologies in Construction Projects

The literature review revealed a fundamental reality: the construction industry is lagging behind other industries in its adoption of emerging technology, and there is substantial room for improvement [7]. Figure 6, Figure 7 and Figure 8 below show the survey participants’ ratings of the importance of each emerging technology in their current projects.

Most industry professionals regard Building Information Modelling (BIM) as a pivotal emerging technology in construction projects. This view aligns with its nearly two decades of integration into the industry. Similarly, sensors and UAV technology are recognised across all three industry tiers as significantly important in ongoing projects. This perspective is underscored by comments from Participant 4, who noted that “Adoption of new technology is hard” and “human beings are resistant to change”. Consequently, it is understandable that technologies like sensors and UAVs, which are relatively inexpensive, have limited application scopes, and offer immediate utility, are more appealing and broadly implemented. On the other hand, Virtual Reality (VR) and Augmented Reality (AR) are considered the least important emerging technologies. This perception aligns with the literature that points to the substantial costs involved in acquiring the necessary hardware and software and designing simulation environments [100].

4.3.2. Integration of Emerging Technologies to Improve Construction Practices

The literature review highlighted how emerging technologies could potentially reduce safety risks associated with construction practices. Nevertheless, it exposed a significant gap concerning the perspectives of Australian professionals on the effectiveness of these technologies in enhancing safety measures. Figure 9, Figure 10 and Figure 11 detail the participants’ evaluations regarding the importance of each technology in improving safety standards.

The results in Figure 9 indicate that Sensors and UAVs are the most important technologies to mitigate construction safety risks in Tier 1 firms and are of similar importance in other Tiers. This aligns with the literature that emphasises that Sensors and UAVs increase risk detection, provide high-resolution visuals, improve site monitoring, and achieve a biometric screening of the safety equipment of the workforce [26,28,29,32]. P8 supported these findings, stating that “where [a technology] is reducing the amount of labour involvement, particularly physical labour, [it] will naturally improve safety, and drones are a perfect example of that”.

Tier 2 firms, as per Figure 10, and Engineers in Tier 1 firms ranked BIM to be of similar importance to UAVs and Sensors. Although BIM may be useful in mitigating safety, its high ranking may be influenced by its more advanced integration within the industry compared to other technologies.

The results of participants in the online survey further reveal mixed messages on the role of Immersive technologies in mitigating the safety risks of construction practices. All three groups across Tier 1 and Tier 3 companies rated VR and AR in the bottom three technologies for safety mitigation. However, Executives in Tier 2 companies (Figure 10) rated immersive technologies, particularly VR, to be the most important technology for mitigating safety. P6 agreed with this, stating, “there is a lot of interest in immersive technology. Because there’s a whole bunch of safety concerns around a lot of environments”. Contrastingly, Tier 2 Engineers and Architects/Business rated VR in the bottom three technologies. The disparity in the perceived importance of immersive technologies contrasts the literature’s unified stance on their safety benefits. Thus, the inconsistent perspective between industry and the literature could be explored in future research by investigating why immersive technologies, despite their strong theoretical potential, are considered of lower importance by industry professionals. Digital Twin received similar inconsistency in the survey results. Although generally rated as less important than most other technologies, Executives in Tier 2 companies regarded it as one of the most important. However, the generally lower rating of DT is expected, as unlike VR, AR, and AI, it is briefly discussed in the literature as a mitigator of safety issues in construction. Despite the numerous benefits of ML outlined in the literature, AI was generally rated in the bottom half of technologies important for mitigating safety risks. Many of MLs potentials to improve safety, such as identifying risks at increased speed, can be achieved using Sensors and UAVs, which may be easier to integrate with construction practices as they are more isolated components [24].

Safety is discussed within the literature as preventing harm to workers on site. P7 mentioned a component of safety entirely overlooked by the literature: “safety is obviously a personal liability for directors and owners. So that’s one area that people are very, very focused on”. This rare insight highlights that this research on integrating emerging technologies to improve the safety of construction practices is also appealing to prevent liability claims and legal disputes.

Figure 12, Figure 13 and Figure 14 show the participants’ ratings of the importance of each emerging technology in reducing the cost of construction practices.

BIM is regarded by all Tier 1 professionals as the most important technology for reducing the cost of construction practices.

Where BIM is not ranked as the most important technology (Executives Tier 2 and Engineers Tier 3 below), it is considered the second most important technology. This result is consistent with the literature that BIM is effective in accurately estimating cost, scheduling, and monitoring to eliminate unbudgeted changes [38]. It is clear there is a unified opinion across the entire Australian construction industry on the importance of BIM in reducing costs. Almost all survey participants perceived VR and AR as the least important technologies in reducing the costs of construction practices. The potential contributions of these technologies, such as virtual site inspections that offer foresight into expensive issues, are also outlined in the literature as features of other technologies. Thus, it may not be worth the time, cost, and training required to implement VR and AR specifically for the intention of reducing costs [39].

Literature suggests that AI, through ML, can support cost management through its statistical capabilities, such as principal component regression to predict project expenses [36]. All Tier 2 Industry professionals (Figure 13) ranked AI as the most or second most effective technology to reduce costs, and Tier 3 professionals ranked AI as third, showing a similarity in perspective across the construction industry. Tier 1 firms showed greater discrepancy on the influence of AI, with Executives and Architects/Business considering it as the technology with the greatest importance at reducing costs after BIM, while Engineers ranked it in the bottom three. This difference creates an interesting point of future research, where the attitudes of different construction workers are investigated and reasoned on a more detailed level. DT is considered by all participants to be one of the top four technologies to reduce costs of construction practices. The opinions of industry professionals on UAVs and Sensors are mixed. Tier 1 firms and most professionals in Tier 2 and Tier 3 firms consider UAVs to be the second to fourth most important technology to reduce construction costs. These opinions are validated by literary perspectives, as scholars such as Uchenna Sampson, Mohamad [36] emphasise how UAVs substantially lower labour costs through remote sensing, which enhances operational efficiency.

The participants’ ratings of the importance of each emerging technology in reducing the delay of construction practices are displayed in Figure 15, Figure 16 and Figure 17.

Digital Twin is one of the top three emerging technologies perceived by Tier 1 professionals as important to reducing delays.

Executives and Architects/Business in Tier 2 companies consider DT to be the second or equally tied first emerging technology to reduce delays. These findings are reiterated by P4, who states that DT was developed to create “our single source of truth”. Considering this, DT ensures that delays in construction practices are minimised due to better resource management through the “single” source, which is also discussed in literature [44,46]. AI is generally ranked by all industry professionals except Tier 1 Engineers in the top three emerging technologies that reduce delay. This is contextualised by P6, who states, “obviously, AI is a really big one at the moment, things like automation,” which can reduce delay through automating a various range of construction processes. This view also aligns with the promotion of AI and ML across the literature due to their iterative processing capabilities to foresee and prevent delay.

All survey participants perceive BIM to be the most important emerging technology in reducing delays in construction practices. This perception is validated by various sources of the literature that reiterate BIMs ability to reduce delays through systems of strong coordination and communication between stakeholders and identifying design issues early to develop accurate schedules [44,45]. P3 contextualises these findings by describing the role of “BIM specialists, who actually look after that and bring all those [stakeholders] together into one space”. P2 furthers this notion, stating that “BIM is very good now in Australia and all around the world”.

The final component that was investigated in the online survey is quality. The participants’ ratings of the importance of each emerging technology in improving the quality of construction practices are displayed in Figure 18, Figure 19 and Figure 20.

The results of the online survey indicate that all professionals perceive BIM as the most important technology in improving the quality of construction practices. This is consistent with the literature that posits that BIM optimises efficiency, sustainability, and utilisation to increase the quality of a project [50]. P8 elaborates on this, explaining that BIM “start(s) at a high Level of Detail of 100, which is not much detail. And each iteration of the BIM model is meant to get you to a high level of detail. You put more information in around the structure of the materials and the detail around that building to get you to the next LOD”. This recurring level of detail works towards improving the quality and calibre of the project.

Tier 2 and Tier 3 look favourably upon utilising AI to improve the quality of construction practices, ranking it among the top three technologies. P2 agrees with the importance of AI to enhance quality, stating, “This is definitely something that can be done”. Although Blanco, Fuchs [51] highlight AIs ability to analyse Sensor data to improve efficiency and provide real-time solutions to enhance project quality, there is generally limited literature on adopting AI to improve construction quality. The minimal literature aligns with Tier 1 professionals’ unoptimistic perspectives towards AI as a key technology in improving quality, with Executives rating it the lowest and Engineers rating it in the bottom three. The diversity of industry opinion provides unique insights by emphasising that companies of different sizes within the Australian construction industry have contrasting opinions on the importance of emerging technology. These findings underscore the importance of this study in capturing the diversity of thought in the industry and that it is these differing perspectives that should be further investigated and addressed.

Furthermore, the results of participants in the online survey reveal mixed messages about a range of emerging technologies. There is inconsistency in the ranking of Immersive Technologies. Engineers and Architects/Business in Tier 2 firms and Executives and Engineers in Tier 3 firms rate Immersive Technologies in the bottom three technologies for improving quality. Their ratings, however, change in Tier 1. Executives and Engineers rate VR as the technology with the least importance in improving quality, while AR is rated in the middle. Similarly, Tier 1 Architects/Business rate AR as the least important, while VR is closer to the middle. The literature demonstrates how Immersive Technologies improve construction quality by facilitating teamwork among stakeholders, which ensures the early identification of errors and minimises rework [47]. Similarly, opinions on DT are mixed. Some professionals, including Engineers Tier 1, Executives Tier 2, and Architects/Business Tier 2, perceive DT as essential for improving quality, while others, such as Executives Tier 1 and Engineers Tier 2, do not share this perspective. P4 states, “the more complex and typically the longer the construction process, the more compelling the case to use digital twin technology because it’s going to be awfully hard to collate information”. This statement highlights the perspective that DT improves the quality of construction practices through its advanced capabilities to organise and collate information. Opinions in favour of DT improving quality are supported by the literature that discusses the ability of the technology to identify and resolve issues while pinpointing their underlying causes [49]. The inconsistency in the opinions of industry professionals emphasises the need for companies developing these technologies to provide clearer information on the functionality and features of their technologies.

Figure 21, Figure 22 and Figure 23 reveal the differences in ratings for the importance of each technology in current versus future projects, displaying the emerging technologies that industry professionals anticipate will grow in significance.

The survey results reveal a unified perspective on the considerable potential for AI to be integrated into construction practices in the future. The rise of ChatGPT has brought AI to the forefront of discussions on technology, which is likely to have contributed to this unified perspective, as the potential of AI is widely apparent. Its ability to be applied on small scales and slowly integrated into practices increases its appeal. Meanwhile, opinions on DTs role in future projects are inconsistent. Executives consider DT to be significantly important in the future. Engineers, however, do not share the forecasted projection of DT integration. Some survey participants provide context for these differing views. Survey participant 25 explained that there is a “Lack of awareness of the potential benefits of BIM and DT to construction activities (i.e., general lack of understanding how they can be utilised, dismissal as too complicated or a fad)”. Participant 29 similarly argued that there is “A lack of understanding and knowledge of the benefits and applications of technologies by the wider industry”. Other participants also explain the prevalence of cultural attitudes. Participant 30 explained that “Our industry is full of older-school business owners who are resistant to change and always strong toward doing things to old-school way”. Participant 45 stated that there exists an “Industry culture [of an] aging non-savvy workforce”. These results reveal the significant lack of understanding across the workforce regarding the innovation and potential of emerging technologies.

The results further emphasise the significant presence of the theory of Industry 4.0 in the workforce: there is a desire for future innovation and integration of technologies into construction practices, but it is prevented by fears of adopting technology early. P3 stated, “because the technology is still nascent or embryonic, the issue with all nascent technology is that you could end up wasting time until you develop something that works”. As discussed by Obiso, Himang [17], a lack of confidence in emerging technologies by being an early adopter is a factor that prevents adoption. P7 elaborated on this, stating, “if the technology isn’t as well developed as you imagine, then obviously, there are issues. And that’s why there is version 1, version 2, etc. Most people wait until you’re up to version 5 before they’ll feel comfortable with it”. Survey participant 7 stated there is a “Fear of embracing new technology”, and Survey participant 26 commented that there are concerns about the “Maturity of technology”. It is evident that the concern of being early adopters of technology is significant; however, future adoption is likely.

To understand the future integration of emerging technologies, the survey analysed six barriers to the adoption of emerging technology. Figure 24, Figure 25 and Figure 26 represent the ratings of industry professionals on the extent to which these barriers impact the integration of emerging technologies.

P3 introduced that the “1st barrier is cost. There is a huge cost”. Industry firms are generally hesitant to spend money, often considering the question succinctly stated by P2: “Does the cost-benefit analysis work?”. The interview results reveal that the issue of cost, as a barrier to integrating emerging technologies, is more complex and multifaceted than what is outlined in the literature.

First, there is the cost of the technology itself. P3 explained that currently in the construction industry, “there are some tools that are extremely expensive”. However, this expense may be justified as “it’s the equivalent of having something there that churns through all those calculations; it shouldn’t make as many mistakes,” making it “the equivalent cost of a mid-level engineer in one software”. P3 further explained that Tier 1 and Tier 2 companies often enter into special enterprise agreements to make the integration of technology more cost-effective, purchasing multiple licenses to use the technology. However, P3 noted from experience that “there are bits of software where we’ll only have like one license in Australia because it’s so expensive. So, if you’re using it in Brisbane, I can’t use it in Sydney”. Some interviewees were unaware of the cost of these technologies, as P2 admitted, “I still don’t know how much digital twin costs”. This reflects a widespread frustration and lack of knowledge across the industry, as information around the cost of emerging technologies is not being proactively distributed. Further, it is vital to consider other aspects of cost. These include the cost of personnel to maintain the technology, learn how to operate it, and train others to use it, which, as P3 highlighted, “the biggest cost is people”. Additionally, the cost of errors must be considered. P8 illustrated that numerous individuals are using technology to solve problems, but if the technology fails, it results in expensive mistakes.

Industry professionals also noted that there is a greater willingness to integrate emerging technologies if the benefits and usefulness of the technology are clearly foreseeable. P4 provided rough cost estimates for building a BIM model, stating it could be “half a percent of the construction cost”. P4 emphasised that although “it is not outrageously expensive”, it is “not an insignificant amount of money” and will only be invested in “if you could see yourself realizing significant benefits”. P6 reiterated this, noting that the adoption of digital technologies is slow “unless there is a very clear value that [companies] can derive from it”. P4 argued that despite its cost, BIM and DT in construction will become standardised because “handover would be a dog’s breakfast without [BIM and Digital Twin]. This is very cumbersome to undertake them. Thus, commissioning will be a lot more time consuming and difficult”.

Since 6 out of the 8 interviews identified cost as a major barrier, it was subsequently included in the survey to gain deeper understanding into its impacts on the integration of emerging technologies. Figure 24 portrays that Executives Tier 1 firms ranked cost as the second most significant barrier, falling closely behind “Lack of training”. Tier 1 Engineers also ranked cost as the second greatest barrier, placing slightly more emphasis on it than Executives. In Tier 2 firms, as illustrated in Figure 25, Executives similarly ranked cost as the second greatest barrier, but to a greater extent than their Tier 1 counterparts. Conversely, Engineers in Tier 2 firms ranked cost as the second greatest barrier, but with a slightly lower emphasis than Executives. Both Executives and Engineers in Tier 3 consistently ranked cost as the most significant barrier to technology integration overall, as shown in Figure 26.

The coding of the interviews revealed that 50% of interviewees mentioned cybersecurity as a significant risk to integration. Participant 4, a CEO, co-founder, and founding director of a company building Digital Twin, emphasised that cybersecurity is the primary risk associated with DT. The dangers are two-fold; it affects the users of the building and the owner. P4 states, “I mean, imagine if you can hack a digital twin. You could cause the lift to go up and down randomly. You could switch off the lights or turn them on and off repeatedly. They can cause havoc for my tenants”. He elaborates on this risk further, noting, “it would go into the press, you become a laughingstock”. Similarly, P6 expressed strong concerns in relation to cyber-security, stating, “everything’s cloud now governments are really worried about the ability for a foreign agent to be able to go and like turn the water off, or something like that”. P8 expanded on this, arguing that cybersecurity is a risk that applies to all technologies “because every piece of technology that’s coming out there now will almost always be connected to the Internet. And once you’re connected to the Internet, you’re exposing yourself to all sorts of interference. It’s a very messy playground, very dirty place to play”. This concern also extends to AI, as P3 stated, “I would say that if the AI goes rogue and it starts doing things without human authority, it can have the potential also to be very disruptive”. Therefore, top-tier industry leaders view cybersecurity as a major risk to the integration of emerging technologies.

This risk was mentioned minimally within the literature, and its unexpected recurrence in interviews prompted its inclusion in the survey to better understand the extent to which it poses a barrier to integrating emerging technologies. Figure 24 shows that Executives and Engineers in Tier 1 firms consider cybersecurity to be one of the top three barriers to integrating emerging technologies. Contrastingly, Tier 2 Executives, as shown in Figure 25, consider cybersecurity as a less significant barrier to implementation compared to other challenges. Meanwhile, Tier 2 Engineers consider cybersecurity to be among the top 3 barriers impeding the integration of emerging technologies. Tier 3 industry professionals, as indicated in Figure 26, perceive cybersecurity as a less significant barrier to implementation, relative to the other barriers. The variation across Tiers may be explained by the nature of the projects handled by the firms. Tier 1 firms often complete high-end, multibillion-dollar projects, including government works and confidential defence and military projects, where cybersecurity presents a tremendous risk that must be avoided.

Literature emphasised the critical role of skilled workers in the success of the construction industry with a growing demand for specialised skills [60]. P3 explained the need for training as “you can’t get the work until people know how to do the work. So, you teach them how to do the work so you can get the work”. Teaching employees how to carry out the work to acquire more projects requires effective training in using emerging technologies. P8 explained that the current state of training within the construction industry is often “in formalised and ad hoc,” where “a lot of my staff will go off and figure out what they need to learn in very small chunks [and] they learn from each other”. Effective training requires immediate application, as P3 outlined that “for any training, if you’re not going to use it pretty much straight away, and then again and again, it trails off and you forget about it”. P8 elaborated on this, suggesting that there is little value in training unless it is applied quickly, as “You might go off for a 3 or 4- or 5-day course, and unless you come back and apply that to the problem straight away, most people forget and then they go, ‘why did I do that’?” P3 also revealed that despite his senior position at a Tier 1 firm, he has not received formal training in using emerging technologies and argues that the real challenge is the consistent usage after training is received, as “You really need to be using [the technology] and getting familiar with it”.

The views of the 66 industry professionals surveyed are consistent with the industry experts interviewed. Executives and Engineers in Tier 1 and Tier 2 ranked ‘Lack of Training’ as the most significant barrier to the integration of emerging technologies. Similarly, Executives and Engineers professionals from Tier 3 firms ranked ‘Lack of Training’ as the second most significant barrier, with ‘Cost’ being the primary barrier. These findings strongly align with the conclusions of Upeksha Madanayake, Bert Ediale Young [69], and Solis, Howe [70], that a lack of training has hindered the integration of technologies in construction practices. These results contribute to closing the gap in the literature by revealing that industry professionals perceive a severe shortage of adequate training in the Australian construction industry, which is primarily responsible for hindering the adoption of technology.

The risk of worker redundancy was not mentioned in the interviews as impeding the integration of emerging technologies. However, the researchers included it in the survey to address the gap in the literature and to determine its prevalence in the current Australian construction context. All survey participants, except Tier 3 Engineers, ranked the risk of redundancy as the least significant barrier. This suggests that while there may be an initial fear and resistance to the adoption of emerging technologies, the Australian construction industry places a greater focus on utilising the long-term benefits of these technologies [101]. This clear distinction between significant and less significant barriers reveals the industry’s attitude towards innovation: the strong desire to innovate is prevented by practical challenges, such as cost and a lack of training, as opposed to personal challenges, such as over-reliance and work redundancy.

The risk of employees over-relying on emerging technology was discussed in interviews. P5 introduced the concern of “overconfidence in the accuracy of the digital model” and the inherent risk of over-reliance that comes with the appeal of emerging technologies. He explained, “Just because it’s a really sexy looking digital model and it’s in colour, and you can manipulate it and all that kind of stuff, that doesn’t actually mean it’s right”. He further elaborated, “if a human practitioner normally does something, and they look at what comes out of a computer model, they go, nah! That’s clearly nonsense. But if you don’t have people who’ve done it themselves, will they recognize that what comes out of the computer model is rubbish?” Over-reliance on emerging technologies can negatively affect construction practices, as industry professionals may lack the requisite knowledge to effectively optimise the use of these technologies. P7 provided evidence for this, arguing that over-reliance may lead to circumstances where “people using that technology haven’t had the vision or haven’t had the experience or haven’t got the knowledge of how to manipulate the technology to make it work for their benefit”. P7 also noted that client pressures, particularly in cost-conscious scenarios leads to “shortcuts taken, which means that technology is dumbing down the design”, reducing the innovative skills of the workforce. P2 emphasised the need to create “some sort of quality assurance or quality control, different from the traditional quality assurance” due to the high likelihood that professionals will rely on technology without verifying its accuracy.

The discussion of over reliance on technology prompted the researchers to include it in the survey to gain a deeper understanding of the attitudes held by a broader range of industry professionals. Figure 24 highlights that Tier 1 Executives and Engineers consider over-reliance as the least and second least significant barriers, respectively, to integrating emerging technologies. Contrastingly, Tier 1 Architects/Business ranked overreliance as one of the top 3 barriers. Tier 2 firms considered overreliance as a greater risk than Tier 1. Executives in Tier 2 firms ranked over-reliance as the second most significant barrier to integrating technologies, tied with Cost, while Engineers and Architects/Business ranked over-reliance as a barrier with considerably lower weight.

The interviews did not directly discuss the influence of regulatory requirements on the adoption of emerging technologies. Nevertheless, this topic was included in the survey to fill this literature gap and assess its relevance in the current Australian construction landscape. Architects and businesses across Tier 1 and 2 firms identified the absence of regulatory frameworks as the most significant impediment to adopting emerging technologies. Similarly, Tier 1 and Tier 3 executives, along with Tier 1 and Tier 2 engineers, regard the lack of regulations as a more substantial barrier than either the overreliance on technology or the risk of redundancy. In contrast, Tier 2 executives and Tier 3 engineers consider regulatory deficiencies the least significant obstacle.

This finding diverges from the conclusions of Hardie and Newell (2011), indicating that the regulatory environment may not be perceived as the primary barrier to technology integration within the construction industry. This discrepancy underscores a crucial point for policymakers: if the goal is to encourage innovation and progress in a sector critical to the economy, the legislative focus should shift towards developing performance-based regulations that actively support adopting emerging technologies rather than merely addressing workforce redundancy. The current state of training in the Australian construction industry is entirely undocumented in the literature. The survey asked participants, “Have you received any training during your employment regarding the following emerging technologies? Please select all that apply”. Figure 27 highlights the percentage of survey participants who have received training in each technology.

Despite BIM being the most widely integrated technology, only 55% of professionals have received formal training in its use. After BIM, participants received the most training in using UAVs. This result is surprising given the limited literature discussing UAVs. However, it may be explained as unlike expensive technologies that require extensive training, such as DT, incorporating UAVs is simpler as it is the least constrained by the barriers; it is less expensive, requires smaller teams for operation, and requires little training. Less than one-fifth of professionals have received training in all other technologies, emphasising that major improvements within the Australian construction industry are required to integrate emerging technologies [62]. Thus, the general state of industry training in Australia is significantly inadequate, despite the promising potential of emerging technologies in optimising the construction workforce.

Figure 28 represents the number of technologies in which each participant has received training. Almost one-third of participants have received no training in using any emerging technologies, and 75.8% of participants have not received training in more than 2 technologies. This suggests that the mindset facilitating the acquisition of new skills and knowledge is yet to be adopted in Australia [68].

Figure 29, Figure 30 and Figure 31 present the industry professionals’ opinions on the importance of graduates possessing skills in using each technology. The survey results align with many scholars, including Elzomor and Pradhananga [55] and Suprun, Perisic [54], as the results clearly depict the importance of graduates possessing skills in using emerging technologies. Industry professionals across all Tiers perceive BIM as the technology in that graduates should be the most skilled in using. The substantial emphasis placed on graduates possessing skills in using BIM is consistent with the literature, as Fitriani and Ajayi [59] explain that the competency of civil engineering students in using BIM must be high due to its wide adoption and continuous evolvement.

Despite less than one-fifth of professionals receiving industry training in DT and AI, most professionals across all Tiers consider these technologies as essential for graduates to be skilled in using. The simulation, integration, testing, monitoring, and maintenance capabilities of DT render it incredibly complex [46,102]. Thus, in-depth study of DT within university courses would ensure students build a solid foundation in the technology and its application. These results address a gap in the literature by identifying which technologies industry professionals consider to be the most important for graduates to master.

Interview participants discussed the state of university education. P6 stated that one Sydney-based university is implementing courses where students are “doing BIM modelling. They’re looking at construction logistics and staging. So, they’re not just going in and being told, This is a Gantt chart, this is a program, this is how you manage the project—They’re being taught the skills they need as juniors to get in”. P2 posed the question to the researchers, “Here you are at university in 2024, and you’re going to be in 2025. Is there a course about AI?”. Beyond the technologies, numerous interviewees discussed the importance of courses that teach engineering graduates data skills. P6 stated, “The next shift probably needs to be more around data analytics and teaching people how to do the analysis of the data that’s getting generated from those new models. I’m not really seeing much of that come through”. This was similarly discussed by P8, who said, “data analytics skills are still a division of study that more engineers absolutely should know”.

5. Conclusions

This paper delves into integrating emerging technologies within the Australian construction industry, exploring alignment with Industry 4.0 principles, mainly focusing on enhancing safety, reducing costs, minimising delays, and improving quality. The comprehensive literature review identifies that, despite the potential benefits, the construction industry significantly lags behind other sectors in digital adoption due to numerous barriers, including a profound training deficiency for existing professionals and university graduates. The research utilised a mixed-methods approach, integrating surveys and interviews with industry stakeholders. The findings reveal a disparity in the adoption and perception of technologies like Building Information Modelling (BIM), which is broadly recognised for its effectiveness in reducing costs and improving project timelines. Tier 1 firms frequently cited the importance of sensors and UAVs in enhancing safety measures, whereas Tier 2 firms showed mixed responses. Furthermore, while BIM is favoured for its efficiency improvements, Tier 2 firms are increasingly looking towards AI as a cost-effective tool. Looking forward, participants expressed a strong potential for the integration of AI into construction practices, though they also highlighted significant barriers, such as the high costs associated with technology acquisition, employee training, and ongoing maintenance. Additional concerns raised include cybersecurity risks and intellectual property issues related to the outputs produced by these new technologies. The study found that while some barriers, like worker over-reliance on technology, were viewed differently across firm tiers, the overarching challenges were tied to practical implementation issues rather than worker attitudes. The results also highlighted a stark lack of industry training, with a third of survey participants reporting no training in emerging technologies and the majority having been trained in fewer than three technologies. This training deficit underscores a critical barrier to the successful integration of new technologies within the industry. Furthermore, this research illuminated the cultural resistance within the workforce to adopt new practices, driven by a fear of being early adopters. Many professionals prefer to observe the technologies’ failures and improvements in other settings before committing resources to them. The study concludes by synthesising these insights into actionable strategies for both private firms and public bodies. It suggests that the successful integration of emerging technologies requires a concerted effort to enhance education and training initiatives, starting from academic settings and extending into continuous professional development. This approach not only addresses the practical barriers but also mitigates the cultural resistance to change.

Overall, this paper significantly advances understanding of the current attitudes and challenges associated with integrating emerging technologies in the Australian construction industry. It provides a nuanced view across different firm sizes and offers strategic insights for optimising technology integration, ultimately contributing to the industry’s competitiveness and efficiency.