Impact of Digitalisation in Construction on Australian Designers and Builders: A Cross-Analysis Based on the Size of Organisations

Abstract

The construction industry has yet to reach significant levels of digitalisation compared to other sectors, which could enhance its processes. Recent building failures globally have eroded public trust in the industry, highlighting issues of compliance. This has prompted the introduction of building regulations, where digitalisation is expected to play a key role in supporting compliance. This paper aims to assess the impact of digitalisation on two key stakeholder groups within the construction industry—designers and builders—across various organisational sizes. A questionnaire survey was conducted with designers and builders in Australia, focusing on information technology (IT) infrastructure, digital capability, training, and research and development. Descriptive statistics were analysed and cross-analyses between designers and builders, as well as across different organisation sizes, were conducted using the Mann–Whitney U and Kruskal–Wallis H tests. The findings revealed clear differences between designers and builders regarding digitalisation across IT infrastructure, digital capability, training, and R&D. For example, builders primarily rely on cloud storage while designers use a combination of local and cloud storage. Designers allocate a higher percentage of their turnover to IT, whereas builders are twice as likely as designers to lack structured training for digital skills. When organisation size was considered independently, similarities were observed across sizes. These results provide insight into the current digitalisation landscape in construction, offering a foundation to support the adoption of future industry regulations.

1. Introduction

The construction industry stands at a pivotal moment for digitalisation, with Industry 4.0 technologies poised to drive significant advancements in productivity, sustainability, and resilience [1]. While construction remains one of the least digitalised sectors globally, lagging behind industries like manufacturing and logistics, it is increasingly adopting transformative technologies—such as Building Information Modelling (BIM), cloud computing, and digital twin systems—primarily due to growing regulatory and market pressures [2,3]. As these technologies become integrated into construction workflows, they offer the potential to increase accuracy, reduce waste, and enhance sustainable practices, aligning with broader industry goals of efficiency and compliance [4,5,6].

However, the rate and effectiveness of digitalisation in construction vary widely, impacting key stakeholders—particularly designers and builders—who have unique technological needs and challenges. Designers, including architects and engineers, typically rely on advanced digital tools for precision and complex modelling, whereas builders, such as contractors and subcontractors, focus more on practical applications, like project management and data accessibility [7,8]. Understanding how digitalisation affects these groups differently is essential for tailored industry strategies as each group faces distinct barriers to digital adoption, including disparities in IT investment, digital skills, and infrastructure [9,10].

The urgency of digitalisation in construction is underscored by recent building failures in New South Wales (NSW), such as those at the Opal and Mascot Towers, which have highlighted issues of quality, compliance, and consumer trust. In response, NSW has implemented significant regulatory reforms, including the Design and Building Practitioners Act 2020 (DBP Act 2020), aimed at ensuring better compliance and accountability among design and construction practitioners [11]. As these regulations evolve, digital tools play an increasingly critical role in enabling the industry to meet performance standards and regulatory requirements. A recent state-wide survey by Perera et al. [12] in 2021 has shown that digitalisation can support improved compliance and collaboration among designers and builders, though adoption remains uneven across organisation sizes and roles within the industry. This report highlights the need for a deeper examination of the factors influencing digitalisation among stakeholders, especially in light of these regulatory demands.

Given these dynamics, this study aims to examine the differential impacts of digitalisation on designers and builders, with attention to how organisational size further influences digital adoption. Specifically, this paper seeks to (1) identify key measurable aspects of digitalisation through a comprehensive literature review, (2) conduct a cross-analysis of digitalisation levels between designers and builders, and (3) assess digitalisation differences across organisations of various sizes. These objectives will provide a clearer understanding of digitalisation’s current impact on the construction sector in NSW, helping inform more effective, targeted policies and practices to support digital transformation across the industry.

2. Digitalisation of Construction

According to Gartner [13], digitalisation is ‘the use of digital technologies to change a business model and provide new revenue and value-producing opportunities; it is the process of moving to a digital business’. A key aspect of digitalisation is the increased adoption of information and communication technology (ICT) in business processes leading to ‘e-business’ or ‘e-procurement’ [14]. The requirement for digitalisation has extended to practices beyond these areas and into all aspects of design and construction practices. Recent research on construction e-businesses has explored the state of digitalisation in construction businesses, such as those in the UK [15] and in China [16]. The levels of digitalisation in terms of project management, administration, marketing, modelling and visualisation, e-procurement, IT investment, and skills development were some of the key aspects investigated in these studies.

A model developed by Ayinla and Adamu (2018) demonstrated the existence of a significant digital divide gap which limits the adoption of newer technologies, such as Building Information Modelling (BIM), in the construction sector. Saka, Chan, and Mahamadu [17] added that a significant relationship is lacking between organisation size and BIM implementation and encouraged empirical studies to determine the contemporary landscape of digital capabilities. Apollo and Burkacki [18] in 2023 identified the size of an organisation to significantly impact on the overall operation and efficiency. Hwang et al. [19] reported that organisation sizes impact the severity of the challenges faced within the construction industry regarding the adoption of smart technologies, like Internet of Things, robotics, big data, additive manufacturing, augmented and virtual realities, blockchain, and autonomous vehicles. A study on the adoption of ICT in the Swedish construction industry covering design and construction professionals explored the capability and extent of the use of different file formats (2D and 3D CAD), the reliance on e-commerce, and different motives for ICT investments [20]. Aghimien et al. [21] explored risks related to the digitalisation of construction and highlighted the importance of managing risks related to technology, legal and security issues, and socio-economic factors to attain better financial control, reduced errors, improved quality, and increased productivity. With regard to technology, the impact of digitalisation can be explored based on IT infrastructure and digital capability, as well as the training, research, and development aspects.

3. IT Infrastructure and Digital Capability

IT infrastructure and the digital capability of designers and builders can be used to gauge the overall level of digitalisation. The adoption of IT can be proportional to the technological development of any organisation [22]. IT has been established within the construction industry covering all aspects of communication, administration, accounting, estimation, project controls, scheduling, and computer-aided design (CAD) [23]. The researchers further established the importance of software tools for various aspects, including project management, scheduling, cost controlling and data sharing, while highlighting the preference towards cloud-based versions (online hosted) to be used in the industry.

Building information modelling (BIM), as a key feature of digitalisation, has been adopted within the sector in various capacities. Liu et al. [24] identified various types of software used within the industry and the influencing factors that included the initial investment in both software and hardware for BIM. Since the industry requires sufficient data storage and communication between different stakeholders, data sharing through networks and services like cloud computing has become paramount [25]. Further, the more advanced levels of digitalisation which lead to the extensive use of digital twins, would require sufficient forms of hardware, software, and storage. Another aspect of digitalisation that can be measured within the category of IT infrastructure and capability is the level of digital maturity, which is the status of digital transformation that includes the changes implemented and the capabilities acquired [26].

Based on the different aspects of digitalisation identified, the state of art of the level of the digitalisation of designers and builders can thus be explored via software usage, shared file formats, IT budget, data storage methods, IT services, and overall digital maturity level.

4. Training, Research, and Development

Digitalisation requires constant updating of knowledge and proper training to obtain new digital skills. A study on the risks of construction digitalisation by Aghimien et al. [21] revealed the need for education and training of existing staff. It would enable them to embrace the tools for digital transformation and avoid any risk of poor implementation caused by a lack of skills. Liu et al. [24] highlighted the importance of training provided by the organisation for capability development in relation to new technologies, like cloud computing. Eadie and Perera [27] found that providing better training for the staff is the highest-rated factor for improving the e-business capabilities of construction. Therefore, the level of training to obtain digital capabilities was considered a key factor to be explored when assessing the level of digitalisation. Research and development is another key aspect that goes along with digitalisation, which enables the advancement of technologies. R&D investment allows us to build the capacity of construction firms by improving the capabilities of innovation [28]. In Australia, expenditure on R&D for construction businesses stood at USD 244 million while that of manufacturing businesses was significantly higher at USD 4763 [29]. As such, exploring the investment in R&D is critical, especially considering the impact of it on digitalisation.

5. Research Method

This study employed a quantitative research approach, using a survey to examine the impact of digitalisation on designers and builders within the New South Wales (NSW) construction sector. The overall research design adopted in this paper is summarised in Figure 1. The survey focused on two main areas—IT infrastructure and digital capability and training, research, and development—to assess the current state of digitalisation across these dimensions. Descriptive statistics were used to capture a broad view of digitalisation in the sector while comparative statistical analyses identified significant differences between designers and builders and among organisations of different sizes.

The survey was designed and distributed via Qualtrics to ensure efficient data collection. Given the difficulty of conducting random sampling for the entire population, purposive sampling was used, targeting active designers and builders within NSW. The NSW Building Commissioner’s Office helped identify a target population of 30,465 professionals (18,742 designers and 11,723 builders), ensuring a representative sample of key industry stakeholders. From the initial contact, 591 designers and 483 builders expressed interest, with 347 designers and 195 builders ultimately completing the survey, resulting in completion rates of 59% and 40%, respectively. Respondents were then categorised by organisation size based on the classifications defined by the Australian Bureau of Statistics [30], which included micro (0–4 employees), small (5–19 employees), medium (20–199 employees), and large (200+ employees). This categorisation enabled further analysis of digitalisation trends across varying organisation sizes.

The survey questions were organised into two main sections, covering IT infrastructure, digital capability, training, research, and development. The questions were structured to capture quantitative data on digital tool usage, IT budgets, data storage preferences, training processes, and R&D investments. Each question was assigned a reference code, such as “IT.DB.1” for IT questions related to both designers and builders and “TR.DB.1” for training and R&D questions, to aid in data organisation and analysis.

To interpret survey results, both descriptive and inferential statistics were employed. Descriptive statistics provided an overview of current digitalisation practices and facilitated comparisons with prior studies on the digital transformation of the construction sector. Given that many of the data were ordinal and did not meet the assumptions required for parametric tests, two non-parametric tests were selected for inferential analysis. The Mann–Whitney U test was used to compare two independent groups—designers and builders—across survey variables, allowing the identification of statistically significant differences in digitalisation practices at a significance level of α = 0.05. This test was chosen for its suitability with ordinal data and its effectiveness with small sample sizes. To assess differences across more than two groups, specifically for analysing trends by organisation size, the Kruskal–Wallis H test was applied. This test accommodated ordinal data and permitted comparisons across micro, small, medium, and large organisations, uncovering statistically significant differences in digitalisation practices by organisation size.

Prior to conducting the MWU and KWH tests, several assumptions were verified to ensure the validity of the analyses. The dependent variables were confirmed as ordinal or continuous while the independent variables comprised categorical, independent groups. Additionally, observations were checked for independence to confirm there was no relationship between observations within or across groups and the non-normality of variables was validated, confirming that non-parametric tests were appropriate.

In summary, this methodology provided a comprehensive framework for examining digitalisation practices among designers and builders in the NSW construction industry. The combination of descriptive and inferential non-parametric analyses enabled a detailed assessment of digital capabilities, infrastructure, and training needs, offering valuable insights to inform policy and industry practices.

6. Statistical Tests

Unlike parametric tests, which are designed for idealised data, non-parametric tests are intended for more realistic data, which can be skewed, scattered, and have outliers [31]. The MWU test is considered one of the most frequently used non-parametric tests when comparing two unpaired groups. It can be carried out on small sample sizes and does not assume a normal data distribution [31,32]. Hence, the MWU test was used in this study to compare differences between the designer group and the builder group, which are two independent groups, as the dependent variables are mainly ordinal. It tested whether differences between the two groups were statistically significant at α = 0.05.

The KWH test was used in this study to determine if there are statistically significant differences between two or more groups of an independent variable on an ordinal dependent variable. It is also a non-parametric test but suitable for ascertaining the significant difference, especially for three or more categories of respondents [33]. In this study, the KWH test was used to compare differences between organisation size categories (micro, small, medium, and large) for different variables.

The following assumptions were checked prior to the application of both tests:

• Dependent variables should be ordinal or continuous;
• Independent variables should consist of two categorical, independent groups;
• There should be independence of observations such that there is no relationship between the observations in each group or between the groups themselves;
• The variables are not normally distributed.

7. Results, Analysis, and Discussion

This section is structured in a way that descriptive statistics, cross-analysis between designers and builders, and cross-analysis between different organisation sizes are presented consecutively, along with discussion. The reference codes of questions are explained below:

IT = IT infrastructure and digital capability; TR = Training, research, and development; D = Questions for designers; B = Questions for builders; DB = Questions for both parties.

The descriptive statistics of the respondent profile based on organisation size are provided in

Table 1. Respondent profile—Number of people employed by the organisation.

	Frequency (F) and Percentage (P)
	Designers		Builders
	F	P	F	P
Micro (0–4)	205	59%	86	44%
Small (5–19)	73	21%	70	36%
Medium (20–199)	53	15%	30	15%
Large (200 and over)	16	5%	9	5%

.

The results provide a clear picture of the organisation size with over 95% falling in the category of micro-SME. In total, 54% of designers and builders are micro-level organisations in terms of the number of people employed.

8. IT Infrastructure and Digital Capability

The descriptive statistics of questions related to IT infrastructure and digital capability are presented in

Table 2. Descriptive statistics of IT infrastructure and digital-capability-related questions.

No	Questionnaire Item	Answers	Frequency (F) and Percentage (P)
			Designers		Builders
			F	P	F	P
IT.DB.1	Use of AutoCAD for building designs/as-built drawings preparation	No usage	140	40%	17	38%
		Occasional usage	58	17%	7	16%
		Low usage	42	12%	4	9%
		Medium usage	31	9%	11	24%
		High usage	76	22%	6	13%
IT.DB.2	Use of Revit for building designs/as-built drawings preparation	No usage	177	51%	23	51%
		Occasional usage	22	6%	2	4%
		Low usage	14	4%	2	4%
		Medium usage	22	6%	4	9%
		High usage	112	32%	14	31%
IT.DB.3	Use of SketchUp for building designs/as-built drawings preparation	No usage	182	52%	28	62%
		Occasional usage	67	19%	5	11%
		Low usage	36	10%	4	9%
		Medium usage	28	8%	5	11%
		High usage	34	10%	3	7%
IT.DB.4	Use of Aconex as a project management software	No usage	202	58%	134	69%
		Occasional usage	34	10%	16	8%
		Low usage	20	6%	12	6%
		Medium usage	40	12%	12	6%
		High usage	51	15%	21	11%
IT.DB.5	Use of MS Project as a project management software	No usage	218	63%	76	39%
		Occasional usage	48	14%	25	13%
		Low usage	41	12%	22	11%
		Medium usage	28	8%	33	17%
		High usage	12	3%	39	20%
IT.DB.6	Current digital maturity of the organisation	Use of basic technologies to improve business operations	168	48%	112	57%
		Use of advanced technologies to improve business operations	155	45%	75	38%
		Integrated use of digital technologies to transform business operations	24	7%	8	4%
IT.DB.7	The level of use of local hard drives (individual computers) for data storage	No usage	120	35%	49	25%
		Low usage	97	28%	75	38%
		Medium usage	49	14%	27	14%
		High usage	19	5%	19	10%
		Very high usage	62	18%	25	13%
IT.DB.8	The level of use of cloud storage for data storage	No usage	105	30%	34	17%
		Low usage	79	23%	33	17%
		Medium usage	76	22%	45	23%
		High usage	29	8%	20	10%
		Very high usage	58	17%	63	32%
IT.DB.9	The level of use of network-attached hard drives (local server, NAS, etc.) for data storage	No usage	132	38%	97	50%
		Low usage	43	12%	36	18%
		Medium usage	53	15%	27	14%
		High usage	27	8%	8	4%
		Very high usage	92	27%	27	14%
IT.DB.10	The level of outsourcing IT services	100% Outsourced	87	25%	83	43%
		Outsourced but backed with minimal internal staff	101	29%	42	22%
		Outsourced but with significant internal staff	19	5%	8	4%
		100% internally managed	140	40%	62	32%
IT.DB.11	Average annual budget for IT as a % of turnover	0–1%	47	14%	99	51%
		1–3%	119	34%	64	33%
		3–5%	99	29%	22	11%
		5–10%	59	17%	8	4%
		More than 10%	23	7%	2	1%
IT.DB.12	Point in time able to submit PDF converted from CAD	Already achieved	331	95%	143	73%
		Achieve by 2022	11	3%	28	14%
		Achieve by 2025	2	1%	15	8%
		Achieve by 2030	0	0%	4	2%
		Achieve beyond 2030	3	1%	5	3%
IT.DB.13	Point in time able to submit 2D CAD files	Already achieved	276	80%	93	48%
		Achieve by 2022	34	10%	55	28%
		Achieve by 2025	12	3%	31	16%
		Achieve by 2030	10	3%	6	3%
		Achieve beyond 2030	15	4%	10	5%
IT.DB.14	Point in time able to submit 3D CAD files	Already achieved	198	57%	51	26%
		Achieve by 2022	56	16%	74	38%
		Achieve by 2025	41	12%	48	25%
		Achieve by 2030	20	6%	7	4%
		Achieve beyond 2030	32	9%	15	8%
IT.DB.15	Point in time able to submit Building Information Models	Already achieved	126	36%	32	16%
		Achieve by 2022	54	16%	57	29%
		Achieve by 2025	78	22%	57	29%
		Achieve by 2030	33	10%	22	11%
		Achieve beyond 2030	56	16%	27	14%
IT.DB.16	Point in time able to submit digital twin	Already achieved	27	8%	15	8%
		Achieve by 2022	55	16%	45	23%
		Achieve by 2025	93	27%	66	34%
		Achieve by 2030	54	16%	30	15%
		Achieve beyond 2030	118	34%	39	20%

.

For IT.DB.1, 2, and 3, out of a list of commonly used design software, AutoCAD, Revit, and SketchUp were rated as the top three. These results conform to the findings of Onur and Nouban [34], which indicated AutoCAD and Revit to be among the leading software at BIM Levels 1 and 2, respectively. Aconex and MS Project were rated to be the leading software used for project management (IT.DB.4 and 5) whereas Aconex was considered to be among the top six project collaboration tools [35]. Half of the respondents self-evaluated their organisations to be at the most basic level of digital maturity (IT.DB.6). Similarly, 42% of all the respondents considered them to be at the second level of digital maturity, where they use advanced technologies to improve business operations, while only a negligible percentage claim to be at the highest level. The findings resonate with a case study on digital maturity assessment of construction sites conducted by Wernicke et al. (2021), where, on average, the digital maturity was found to be at an intermediate level.

With regard to data storage methods (IT.DB.7, 8, and 9), the results indicate that 31% of the data handled by both parties is mostly stored in the cloud. This is on par with the use of cloud networks in the UK at 28% [15], significantly higher than in Bulgaria at 10% [27] and significantly lower than in Canada at 65.9% [36]. As directly compared by Bello et al. [37], the cost per terabyte is significantly low for cloud storage, contributing to the extent of its usage as evident from this survey. The results for IT.DB.10 indicated that 37% of both designers and builders would completely manage IT services within their organisations, implying the tendency to employ specialists to manage the IT services in-house. Comparatively, in a European study, it was found that only 8% of the organisations would employ IT specialists [38]. In terms of the average annual budget for IT (IT.DB.11), 77% of the designers would spend less than 5% of the turnover compared to 95% of the builders. Comparatively, 52.4% of the consultants and 55% of the contractors had similar budgets for IT, according to a previous study in Australia [14]. Compared to a similar survey conducted in 2005 in Australia, a clear improvement in IT investment within the industry is evident [39]. Accordingly, while 44% (in 2005) invested less than 1% of the turnover in IT, only 27% (in this survey) indicated the same. At the upper end (investing over 10% of the turnover in IT), the percentage of respondents had risen to 5% compared to 1% back in 2005.

At the time of the survey, only 73% of the builders indicated capability in submitting PDF files as opposed to 95% of the designers (IT.DB.12). The gaps between the two parties were much higher as the types of formats advanced. Accordingly, designers were around twice as capable of already submitting CAD and BIM files (IT.DB.13, 14, and 15). A similar percentage (8%) of designers and builders indicated that they are able to submit digital twins already (IT.DB.16). This very low value aligns with the numerous barriers to adopting digital twins within construction, as highlighted by Shahzad et al. [40] in 2022.

9. Cross-Analysis: IT Infrastructure and Digital Capability

Results of the statistical tests conducted for IT-infrastructure and digital-capability-related questions are presented in

Table 3. MWU test results for IT infrastructure and digital capability.

Item	Questionnaire Item	Mean Rank		Sum of Ranks		Mann–Whitney U	Wilcoxon W	Z	Asymp. Sig (2-Tailed)
		Designer (n= 347)	Builder (n = 195)	Designer (n = 347)	Builder (n = 195)
IT.DB.1	Use of AutoCAD for building designs/as-built drawings preparation	242.27	295.78 a	84,066.50	50,873.50 a	23,688.500	84,066.500	−3.960	0.000
IT.DB.2	Use of Revit for building designs/as-built drawings preparation	265.46	248.98 a	92,116.00	42,824.00 a	27,946.000	42,824.000	−1.284	0.199
IT.DB.3	Use of SketchUp for building designs/as-built drawings preparation	279.63	220.39 a	97,032.50	37,907.50 a	23,029.500	37,907.500	−4.789	0.000
IT.DB.4	Use of Aconex as a project management software	282.39	252.12	97,989.50	49,163.50	30,053.500	49,163.500	−2.481	0.013
IT.DB.5	Use of MS Project as a project management software	240.67	326.35	83,514.00	63,639.00	23,136.000	83,514.000	−6.693	0.000
IT.DB.6	Current digital maturity of the organisation	281.10	254.41	97,542.50	49,610.50	30,500.500	49,610.500	−2.149	0.032
IT.DB.7	The level of use of local hard drives (individual computers) for data storage	267.47	278.68	92,810.50	54,342.50	32,432.500	92,810.500	−0.829	0.407
IT.DB.8	The level of use of cloud storage for data storage	247.77	313.73	85,975.50	61,177.50	25,597.500	85,975.500	−4.825	0.000
IT.DB.9	The level of use of network-attached hard drives for data storage	289.96	238.65	100,615.50	46,537.50	27,427.500	46,537.50	−3.843	0.000
IT.DB.10	The level of outsourcing IT services	287.81	242.31	99,903.50	47,249.50	28,139.500	47,249.500	−3.432	0.001
IT.DB.11	Average annual budget for IT as a % of turnover	320.27	184.72	111,132.20	36,020.50	16,910.500	36,020.500	−10.034	0.000
IT.DB.12	Point in time able to submit PDF converted from CAD	249.87	309.98	86,706.00	60,447.00	26,328.000	86,706.000	−7.457	0.000
IT.DB.13	Point in time able to submit 2D CAD files	241.90	324.16	83,941.00	63,212.00	23,563.000	83,941.000	−7.120	0.000
IT.DB.14	Point in time able to submit 3D CAD files	247.82	313.64	85,994.00	61,159.00	25,616.000	85,994.000	−4.994	0.000
IT.DB.15	Point in time able to submit BIM models	259.86	292.22	90,171.00	56,982.00	29,793.000	90,171.000	−2.373	0.018
IT.DB.16	Point in time able to submit digital twin	287.07	243.78	99,615.00	47,538.00	28,428.000	47,538.000	−3.186	0.001

n value for ^a = 172.

,

Table 4. KWH test results for IT infrastructure and digital capability—Designers.

Item	Questionnaire Item	Mean Ranks				Kruskal–Wallis H	Asymp. Sig (2-Tailed)
		0–4 Employees (n = 205)	5–19 Employees (n = 73)	20–199 Employees (n = 53)	200 and Over Employees (n = 16)
IT.D.1	Use of AutoCAD for building designs/as-built drawings preparation	171.52	171.50	179.99	197.38	1.340	0.720
IT.D.2	Use of Revit for building designs/as-built drawings preparation	152.91	177.02	225.48	259.84	41.771	0.000
IT.D.3	Use of SketchUp for building designs/as-built drawings preparation	157.06	180.85	227.21	183.56	25.112	0.000
IT.D.4	The use of Aconex for project management	132.55	183.10	287.21	288.56	155.561	0.000
IT.D.5	The use of Microsoft Project for project management	152.40	185.80	217.88	251.59	40.458	0.000
IT.D.6	Current digital maturity of the organisation	143.84	188.96	239.87	273.97	73.887	0.000
IT.D.7	The level of use of local hard drives (individual computers) for data storage	204.53	127.02	135.23	125.56	48.779	0.000
IT.D.8	The level of use of cloud storage for data storage	165.51	174.55	187.13	236.69	8.887	0.031
IT.D.9	The level of use of network-attached hard drives for data storage	146.46	215.52	221.95	178.63	42.570	0.000
IT.D.10	The level of outsourcing IT services	191.46	139.05	144.29	208.16	24.141	0.000
IT.D.11	Average annual budget for IT as a percentage of turnover	163.81	173.89	203.15	208.44	9.125	0.028
IT.D.12	Point in time able to submit PDF files converted from CAD	178.71	166.00	166.00	176.69	9.576	0.023
IT.D.13	Point in time able to submit 2D CAD files	186.24	157.69	154.00	157.88	15.129	0.002
IT.D.14	Point in time able to submit 3D CAD files	196.25	150.57	135.53	123.31	32.134	0.000
IT.D.15	Point in time able to submit BIM models	199.33	159.59	112.82	117.84	42.177	0.000
IT.D.16	Point in time able to submit digital twin	186.41	166.41	148.93	132.66	10.268	0.016

and

Table 5. KWH test results for IT infrastructure and digital capability—Builders.

Item	Questionnaire Item	Mean Ranks				Kruskal–Wallis H	Asymp. Sig (2-Tailed)
		0–4 Employees (n = 86)	5–19 Employees (n = 70)	20–199 Employees (n = 30)	200 and Over Employees (n = 9)
IT.B.1	Use of AutoCAD for building designs/as-built drawings preparation	82.60 a	78.45 b	109.20 c	109.81 d	10.031	0.018
IT.B.2	Use of Revit for building designs/as-built drawings preparation	76.55 a	81.34 b	112.35 c	131.25 d	20.261	0.000
IT.B.3	Use of SketchUp for building designs/as-built drawings preparation	85.89 a	89.09 b	85.94 c	73.25 d	1.266	0.737
IT.B.4	The use of Aconex for project management	83.98	88.38	135.65	181.33	59.888	0.000
IT.B.5	The use of Microsoft Project for project management	80.55	104.25	122.10	135.78	20.101	0.000
IT.B.6	Current digital maturity of the organisation	81.38	101.17	127.48	133.83	25.866	0.000
IT.B.7	The level of use of local hard drives (individual computers) for data storage	118.88	82.46	77.47	87.72	21.749	0.000
IT.B.8	The level of use of cloud storage for data storage	90.61	102.11	105.33	112.22	2.946	0.400
IT.B.9	The level of use of network-attached hard drives (local server, NAS etc) for data storage	77.23	108.81	125.38	121.11	26.003	0.000
IT.B.10	The level of outsourcing IT services	107.17	86.32	84.25	147.00	15.710	0.001
IT.B.11	Average annual budget for IT as a percentage of turnover	89.25	103.70	103.20	119.94	5.283	0.152
IT.B.12	Point in time able to submit PDF files converted from CAD	108.24	97.02	78.83	72.00	13.713	0.003
IT.B.13	Point in time able to submit 2D CAD files	109.70	100.49	73.97	47.00	19.217	0.000
IT.B.14	Point in time able to submit 3D CAD files	103.01	102.74	87.97	46.67	10.489	0.015
IT.B.15	Point in time able to submit BIM models	103.20	103.31	88.80	37.67	13.205	0.004
IT.B.16	Point in time able to submit digital twin	100.77	96.24	101.55	73.33	2.256	0.521

n values for ^a = 73, ^b = 64, ^c = 27, ^d = 8. The next sections discuss the findings based on Table 4, Table 5 and Table 6 by comparing and contrasting the results and identifying the significant items.

.

10. Software Used for Building Design/As-Built Drawings

The use of building design/as-built drawings preparation software, such as AutoCAD and SketchUp, when analysed using MWU testing, indicated that there is a statistically significant difference between designers and builders (Table 3). This is expected as designers are more reliant on CAD-related software due to their nature of work, which primarily revolves around designing and draughting, while builders, in traditional head contractor roles, would not rely much on such software. Rather, the builders are likely to invest in drawing mark-up software or drawing viewing software, which are significantly cheaper and simpler to use. However, for Revit—a building information modelling software—the MWU test indicated that there is no statistically significant difference between designers and builders with p = 0.199 (Table 3). This is an interesting outcome, possibly due to the equally low number of designers and builders using the software in their projects regularly.

For designers, the KWH test showed that there was no statistically significant difference in the use of AutoCAD based on organisation sizes, at p = 0.720 (Table 4). This can be supported by the fact that designers would be heavily reliant on CAD software given the nature of their job, irrespective of the size of their organisation. Similarly, builders had a similar preference for SketchUp, regardless of the organisation size (with p = 0.737, Table 5). This too can be explained by the limited requirement of any sized builder to prepare drawings. Rather, the builders are likely to outsource design/as-built drawing preparation.

11. Software Used for Project Management

Microsoft Project and Aconex were the top two most used project management software by all respondents. The MWU test indicated that designers and builders had a statistically significant difference regarding the use of Aconex as well as Microsoft Project (Table 3). As a project management software, Microsoft Project is likely to be used more by builders for managing construction programmes and resources, which can be complex tasks. Designers are less likely to be dependent on such software given the nature of their work. Hence the significant difference among builders and designers seems logical. The same reasoning can be applied to Aconex, which indicated such a statistically significant difference between the two parties.

The KWH test revealed that the size of the organisation had no effect on the use of these two software (Table 4 and Table 5). For builders using Microsoft Project, this result is relatable as the software is somewhat affordable and familiar to use along with Microsoft Office Suite. This finding echoes similar research conducted in other countries, which found the common use of such software for project management across organisations of different calibres [41]. However, the use of Aconex, irrespective of the organisation size, is rather unexpected as it is more likely to be used for complex or large projects.

12. Current Digital Maturity of the Organisation

According to the MWU test, designers and builders have statistically significant differences among their current digital maturity levels (Table 3). Similarly, based on the KWH test, both designers and builders have statistically significant differences within their varying organisation sizes (Table 4 and Table 5). This implies that the perceived digital maturity of the organisation is unique to each field (designer vs. builder) as well as the organisation’s size. It indicates that digitalisation within the construction industry needs to be discipline-specific and organisation-size-specific.

13. Extent of Usage in Different Data Storage Methods

The level of usage of local hard drives for data storage by designers and builders was assessed. The MWU test indicated that there was no statistically significant difference between the two groups, with p = 0.407 (Table 3). This implies that both designers and builders are similar in the level of reliance on local hard drives for storing data. It is a positive result given that 63% of both designers and builders have low or no reliance on local storage, indicating better data management via shared/cloud services.

According to KWH tests, there were no statistically significant similarities among the different sizes of the designer or builder organisations (Table 4 and Table 5). In contrast to the use of local hard drives, cloud-based storage usage was found to be significantly different among the parties (Table 3). Builders had no statistically significant difference among the varying sizes with regard to their use of cloud storage, as per the KWH test with p = 0.400 (Table 5). Hence, irrespective of the organisation size, builders rely on remote forms of data storage, especially due to the dynamic nature of their work being attached to construction sites [42], whereas designers did not indicate such a correlation (Table 4).

14. Level of Outsourcing of IT Services

The level of outsourcing of IT services resulted in statistically significant differences between designers and builders (as per the MWU test in Table 3), among different organisation sizes of designers (as per the KWH test in Table 4), and among different organisation sizes of builders (as per the KWH test in Table 5). As per the findings of Ma et al. [43] in 2022, limitations in maintaining costs of IT specialists could be causing different outsourcing practices among different sizes of organisations. In general, smaller organisations may consider outsourcing IT services rather than maintaining an internal IT team compared to larger organisations. Larger organisations can afford such additional staff and may require additional cyber security measures based on the scale of projects and client data handled.

15. Average Annual Budget for IT as a Percentage of Turnover

The results of the MWU test indicated that designers and builders had statistically significant differences in terms of the average annual budget for IT (Table 3), relatable to the findings of Love, Irani, and Edwards [39]. This could be because designers significantly rely on IT in delivering their services compared to the builders.

Based on the KWH test, there is a statistically significant difference between different organisation sizes of designers considering the average annual budget for IT (Table 4). However, for builders, there is no statistically significant difference between the organisations (Table 5) with p = 0.152. This can be due to the fact that half of the builders were spending less than 1% of the turnover on the IT budget.

16. Time to Achieve Milestones in the Digitalisation of the Processes

The respondents indicated the year by which they can achieve the submission of drawings in different levels of digital formats, such as PDF, CAD, BIM, and digital twins. Based on the years indicated, designers and builders had significantly different sets of answers for all the formats, as suggested by MWU test results (Table 3). When compared based on organisation sizes, there is a statistically significant difference among designers to achieve the given milestones (Table 4). The outcome was almost the same for builders, except for the target for submitting digital twins. This implies that builders, irrespective of their sizes, were more optimistic about the ability to achieve digital twin usage by 2025. However, digital twin is a cutting-edge technology, which is still in its infancy [44]. Hence it is difficult to see any significant adoption at any scale. Accordingly, the KWH test revealed, with p = 0.521, that there is no statistically significant difference between different organisation sizes of builders with regard to the possible year to submit digital twins (Table 5). The findings are relatable to a study on 135 design and building organisations in Australia conducted by Hosseini et al. [45] that revealed no meaningful association about the capacity to implement BIM across different organisation sizes.

17. Training, Research, and Development

The descriptive statistics related to training, research, and development are given in

Table 6. Descriptive statistics of training, research, and development-related questions.

No	Questionnaire Item	Answers	Frequency (F) and Percentage (P)
			Designers		Builders
			F	P	F	P
TR.DB.1	Method of training to obtain new digital capabilities	No specific training method	59	17%	62	32%
		Ad hoc training processes (on the job)	174	50%	82	42%
		Structured training programme—external	30	9%	13	7%
		Structured training programme—internal	84	24%	38	19%
TR.DB.2	Average annual budget for research and development as a percentage of turnover	0	49	14%	35	18%
		Less than 1%	115	33%	97	50%
		1–3%	111	32%	45	23%
		3–5%	40	12%	8	4%
		5–10%	20	6%	6	3%
TR.B.3	Ease of finding personnel with digital capabilities required for the production of as-built drawings	Very Difficult			19	10%
		Difficult			79	41%
		Easy			81	42%
		Very Easy			16	8%

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According to TR.DB.1, 47% of designers and builders rely on ad hoc training processes to obtain new digital capabilities. It is comparable to the findings of the UK construction industry’s uptake of training, which indicated that the majority of the staff are self-taught [15]. The use of external training programmes was very low at 8%, although it has the potential to increase, as many large contractors are likely to roll out their in-house training programmes to the subcontractors engaged in their projects [46]. Overall, 54% of the designers and builders invested less than 1% of the annual turnover into R&D (TR.DB.2), which confirms the very low amount of total R&D expenditure, as reported by the Australian Bureau of Statistics [30]. TR.B.3 indicated that half of the builders struggle to find personnel with the digital capabilities required for the production of as-built drawings. Especially when going for wider adoption of technologies, like BIM, the limitations of training and difficulties in finding skilled professionals are evident from these results and resonate with previous research [47,48,49].

18. Cross-Analysis: Training, Research, and Development

Results of the statistical tests conducted for training, research, and development-related questions are presented in

Table 7. MWU test results for training, research, and development.

Item	Questionnaire Item	Mean Rank		Sum of Ranks		Mann–Whitney U	Wilcoxon W	Z	Asymp. Sig (2-Tailed)
		Designer (n = 347)	Builder (n = 195)	Designer (n = 347)	Builder (n = 195)
TR.DB.1	Method of training to obtain new digital capabilities	257.83	295.83	89,467.00	57,686.00	29,089.000	89,467.000	−2.904	0.004
TR.DB.2	Average annual budget for research and development as a percentage of turnover	291.94	235.13	101,303.50	45,849.50	26,739.500	45,849.500	−4.245	0.000

,

Table 8. KWH test results for training, research, and development—Designers.

Item	Questionnaire Item	Mean Ranks				Kruskal–Wallis H	Asymp. Sig (2-Tailed)
		0–4 Employees (n = 205)	5–19 Employees (n = 73)	20–199 Employees (n = 53)	200 and Over Employees (n = 16)
TR.D.1	Method of training to obtain new digital capabilities	173.26	168.25	188.44	161.91	1.852	0.604
TR.D.2	Average annual budget for research and development as a percentage of turnover	165.43	176.93	194.87	201.34	5.443	0.142

and

Table 9. KWH test results for training, research, and development—Builders.

Item	Questionnaire Item	Mean Ranks				Kruskal–Wallis H	Asymp. Sig (2-Tailed)
		0–4 Employees (n = 86)	5–19 Employees (n = 70)	20–199 Employees (n = 30)	200 and Over Employees (n = 9)
TR.B.1	Method of training to obtain new digital capabilities	96.06	103.64	89.05	102.50	1.821	0.610
TR.B.2	Average annual budget for research and development as a percentage of turnover	93.46	101.41	98.70	112.50	1.644	0.649
TR.B.3	Ease of finding personnel with digital capabilities required for the production of as-built drawings	94.83	96.23	108.00	108.78	1.873	0.599

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19. Method of Training to Obtain New Digital Capabilities

There are several ways an organisation provides training to the employees with regard to obtaining new digital capabilities. It ranges from having no specific training, followed by ad hoc training, and then more advanced levels that include internal or external structured training. Based on the MWU test, there is a statistically significant difference between designers and builders, as per Table 7. Conversely, both designers and builders do not have statistically significant differences based on the organisation size, as indicated through KWH tests, which resulted in p = 0.604 (for designers, Table 8) and p = 0.610 (for builders, Table 9).

20. Average Annual Budget for Research and Development as a Percentage of Turnover

The MWU test on the average annual budget for R&D as a percentage of the turnover of the organisation indicated that there is a statistically significant difference between designers and builders (Table 7). High reliance on costly software and a comparatively low annual turnover of the designers could cause this disparity. However, based on the KWH tests, both designers and builders do not have statistically significant differences among the varying sizes of organisations, with p = 0.142 (for designers, Table 8) and p = 0.649 (for builders, Table 9). Therefore, irrespective of the level of income, the construction sector businesses tend to invest in R&D in a similar manner (less than 3% mostly). While that amount could be substantial for larger-income-earning organisations, it is a significantly lower amount for the majority of the rest. However, this was not the case for European countries where a study reported that a small number of large enterprises were investing in R&D while a large group of SMEs had too little profit margins to invest [38]. Hence, the findings in the Australian (NSW) context seem to be somewhat positive.

21. Ease of Finding Personnel with Digital Capabilities Required for the Production of As-Built Drawings

This question was unique to the builders. KWH tests revealed that there is no statistically significant difference among builders of different organisation sizes, at p = 0.599 (Table 9), regarding finding personnel with digital capabilities, with half of the respondents indicating difficulty in the process.

22. Conclusions

This study cross-analysed digitalisation practices between designers, builders, and varying organisation sizes to better understand the state of digital adoption in the New South Wales construction sector. Focusing on IT infrastructure, digital capability, training, and research and development, this research provides valuable insights into the digital landscape of construction in Australia. The descriptive statistics allowed for comparisons with previous studies, enabling a clear assessment of current digitalisation levels in the sector. Furthermore, the cross-analysis using Mann–Whitney U and Kruskal–Wallis H tests highlighted key distinctions and similarities in digital practices between designers and builders, as well as among organisations of different sizes.

The results confirmed significant differences in digitalisation levels between designers and builders, alongside some similarities. In terms of IT infrastructure and digital capabilities, both designers and builders commonly use BIM-based software, like Revit, likely due to its utility in both design development and the production of as-built models. Software preference appears influenced more by functionality than by organisation size, with AutoCAD preferred by designers and SketchUp by builders, likely due to cost-effectiveness and functional requirements. AutoCAD’s advanced features meet designers’ need for detailed design work while SketchUp’s simpler, lower-cost structure suits builders’ needs for design interpretation and visualisation.

The analysis also showed no significant difference in the way designers and builders use local hard drives for data storage. Builders are more reliant on cloud storage for data portability, contrasting with designers, who balance local and cloud storage due to the large file sizes associated with design work. Designers also allocate a significantly larger percentage of their turnover to IT, driven by the need for more substantial investments in hardware and software, while builders’ lower IT budgets reflect their lesser dependence on design-intensive tools.

Regarding training, research, and development, the findings reveal that builders are twice as likely as designers to lack structured training for acquiring new digital skills. The nature of design work, which requires staying competitive with the latest digital tools, drives designers to maintain structured training programs. Builders, on the other hand, are less pressured to acquire new digital capabilities, as their focus is on physical production rather than virtual design. Regardless of organisation size, both groups show similar profiles in their training methods. In terms of research and development, half of the designers invest over 1% of their turnover annually, compared to less than a third of builders. This aligns with designers’ need for continual technological advancements, which is also reflected in their IT budgets. Builders, by contrast, show greater consistency in their cloud storage usage, IT spending, R&D investment, training methods, and ability to source digitally skilled personnel across different organisation sizes.

While this study focuses on the New South Wales construction sector, the findings are likely relevant across Australia, as most states follow similar processes and many surveyed organisations operate nationally. The insights gained provide an overview of the current level of digitalisation and its implications for designers and builders in terms of IT infrastructure, digital capabilities, and training and R&D needs. This study underscores that designers and builders cannot be treated as a homogeneous group regarding construction digitalisation. The findings offer practical insights for construction companies in tailoring digital adoption strategies according to their unique operational needs, organisation size, and digital readiness.

For designers, it is recommended to prioritise investment in robust IT infrastructure and advanced storage solutions that accommodate the large design files essential to their work. Designers would benefit from continuing to allocate higher budgets to IT to support both hardware and software needs critical for high-quality design development. Additionally, structured training programs are essential to maintain competitiveness, enabling designers to stay proficient in the latest digital tools and workflows. Increased R&D investment would also support the integration of emerging technologies, such as digital twin technology, to enhance design innovation and collaboration. Finally, designers could further optimise data management by leveraging a hybrid of local and cloud storage for efficient file access and storage flexibility.

For builders, recommendations focus on enhancing digital capability with cloud storage solutions to improve data accessibility across construction sites, which supports the mobility required for field-based work. Builders are also encouraged to establish consistent training programs for digital skills, particularly in using project management software, to improve collaboration and workflow efficiency. While builders generally have lower IT budgets, incremental investments in R&D can support the adoption of digital tools like BIM, which offers significant benefits in planning and scheduling. Builders should also consider cost-effective digital tools that can enhance productivity without requiring large upfront costs, facilitating a gradual but steady integration of digital processes into their workflows.

These insights should be used to develop policies and frameworks that support digitalisation across different organisation sizes. Additionally, IT service providers, construction software developers, and trainers can utilise these findings to better understand industry needs and address specific gaps in digitalisation for both designers and builders. Future research could extend these insights through international comparative studies and further explore digital practices across a wider range of construction organisations, enriching the global understanding of digitalisation in the industry.