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Article

Application of Digital Technologies Tools for Social and Sustainable Construction in a Developing Economy

by
Ayodeji Emmanuel Oke
1,2,3,*,
John Aliu
4,
Paramjit Singh Jamir Singh
3,*,
Solomon A. Onajite
1,
Ahmed Farouk Kineber
5 and
Mohamad Shaharudin Samsurijan
3
1
Department of Quantity Surveying, Federal University of Technology Akure, Akure 340110, Nigeria
2
CIDB Centre of Excellence, Faculty of Engineering and Built Environment, University of Johannesburg, Johannesburg 2092, South Africa
3
School of Social Sciences, Universiti Sains Malaysia, Minden 11800, Malaysia
4
Institute for Resilient Infrastructure Systems, College of Engineering, University of Georgia, Athens, GA 30602, USA
5
Department of Civil Engineering, College of Engineering in Al-Kharj, Prince Sattam Bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia
*
Authors to whom correspondence should be addressed.
Sustainability 2023, 15(23), 16378; https://doi.org/10.3390/su152316378
Submission received: 11 October 2023 / Revised: 21 November 2023 / Accepted: 23 November 2023 / Published: 28 November 2023
(This article belongs to the Special Issue Developing Sustainable Global Value Chain (GVC) in an Era of Digital Transformation and Crises)
Browse Figure
Review Reports Versions Notes

Abstract

:
This study aims to evaluate the diverse application areas of digital technologies (DTs) within the Nigerian construction industry, with the intention of gaining insights into their potential benefits, challenges, and opportunities for enhancing efficiency, productivity, and overall performance. This will help us to understand how innovative technologies can improve the various stages of construction projects. To achieve the objectives of this study, a convenience sampling approach was employed to distribute closed-ended questionnaires among construction professionals located in Lagos State. Several statistical tools were used to analyze the obtained data, including percentages, frequencies, mean item scores, and exploratory factor analyses were performed to gain a comprehensive understanding of the dataset. The major findings from the study indicated that architectural design, cost planning, building system analysis, structural analysis, and contract documentation are areas in which DT is mostly applied in the construction industry. Further analysis using factor analysis revealed four clusters of application areas as the pre-contract stage, construction stage, post-contract stage, and modeling stage. The findings of this study offer valuable insights into the effective utilization of DT in the construction industry, thereby contributing to informed decision-making and improved project management practices. The insights gained from this research can inform industry professionals, policymakers, and stakeholders in making informed decisions to drive positive changes and innovation within the sector.

1. Introduction

The technologies accompanying the Fourth Industrial Revolution (4IR) have transformed the landscape of several industries with the integration of automation and digitalization into activities and processes [1,2]. These digital technologies (DTs) are typically described as smart technologies due to their capabilities of self-executing, self-monitoring, and self-organizing predetermined tasks [3]. Moreover, these smart technologies have also been associated with work optimization and performance improvement thanks to the adoption of innovativeness [4].
In recent times, the use of DTs has gained momentum in the areas of aviation, business, education, energy, finance, health, and several other sectors [5]. For the construction industry to undergo digital transformations similar to other sectors, there is a critical need to harness the potential of digital technologies (DTs) at both the management and field levels. This involves integrating DTs into project planning, execution, monitoring, and data analysis, ultimately leading to improved project outcomes, cost efficiencies, and a safer working environment. Considering the adverse impact of construction activities on the environment like waste generation, air pollution, noise pollution, climatic change, and several others [6], the need for DT to address these issues has gained momentum across the globe. Also, due to the low productivity rates of the construction sector which is often caused by the high reliance on traditional manual labor, a lack of proper standards, and a scarcity of effective project management practices [7,8], the need for implementing DT into the activities and processes of the construction industry cannot be overemphasized. However, the construction sector has often been regarded as slow adopters of DTs due to its fragmented nature, which encompasses a wide range of stakeholders, each with its own set of processes, standards, and preferences [9,10].
Existing studies have shed light on the impact of DTs in construction activities. For instance, through the use of building information modeling (BIM), the construction industry has seen improvements in project collaboration, clash detection, cost estimation, and overall project efficiency [11,12]. Moreover, the utilization of artificial intelligence and machine learning algorithms in construction data analysis has the potential to optimize resource allocation, schedule management, and quality control. These advancements, coupled with the continuous evolution of digital technologies, offer promising opportunities for the construction sector to overcome its historical hesitance and fully embrace the benefits of DTs [13]. Through the use of digital twins, which create virtual replicas of physical construction assets and processes, stakeholders can gain a deeper understanding of real-time project status and performance. This technology allows for predictive maintenance, risk mitigation, and more informed decision-making, ultimately resulting in cost savings and improved project outcomes [9]. Additionally, the integration of augmented reality (AR) and virtual reality (VR) technologies in construction can enhance the visualization of complex designs and aid in training and safety simulations. Workers can use AR and VR to interact with 3D models, making it easier to understand project requirements and perform tasks more efficiently [4]. Through the use of 3D printing and autonomous robots, construction processes can be revolutionized. Three-dimensional printing technology allows for the rapid and cost-effective creation of building components, reducing construction time and waste [14]. Autonomous robots can perform tasks such as bricklaying, concrete pouring, and site inspection with precision and efficiency, enhancing productivity and safety on construction sites. Moreover, autonomous robots are projected to work closely with traditional construction systems in the near future to execute projects [1]. By harnessing the power of cloud computing, construction teams can access critical project data and collaborate in real time, regardless of their physical locations. This facilitates better communication and coordination among dispersed teams and helps streamline project workflows [15].
Due to the well-documented reluctance of the construction sector to embrace DT [1,10,11,16], more studies will be required to evaluate the ways in which DT can be applied in the construction industry. Previous industry-related studies have focused on the use of DT in the procurement of construction projects [1], construction safety [16], monitoring and control [17], cost management [18], achieving a circular economy [15], and several other aspects. However, very few studies have examined the application areas with a view to ensuring that construction projects are smarter and sustainable in a developing economy such as Nigeria. This study aims to fill this gap. The findings from this study will contribute valuable insights to inform the construction industry’s decision-makers, policymakers, and stakeholders. These insights can aid in shaping strategies and policies that promote the adoption of DTs in construction. Furthermore, the research outcomes may serve as a catalyst for innovation, encouraging the development of new DT solutions and applications tailored to the unique needs of the construction sector. Ultimately, the findings have the potential to drive positive changes in the industry, supporting its transition towards a more technology-driven and competitive landscape.

2. Understanding the Concept of Digital Technologies (DTs)

2.1. The Emergence of Digital Technologies (DTs)

Across the existing works of literature, four phases have been mentioned in the evolution of digital technologies (DTs). The first phase occurred pre-1838 when the first telegraphic transmission was invented by Samuel Morse to manually transmit information. The second phase witnessed the advent of electricity and electro-mechanical control which saw the invention of gadgets such as the radio, the telegraph, the telephone, and television. Following this, electronic technology was invented in the 1950s which saw the transmission of information in analog mode. The final phase saw the replacement of the analog mode of data with the digital system [19]. Subsequently, electronic devices and signal processing became the order of the day in the 1960s, which paved the way for digital goods such as compact discs (CDs) in the 1980s. Thus, while information and communications technology (ICT) was incubated for over a century, digitalization (translation of information into electronic language using imagery, sound, text, and voice) took over two decades to execute [19]. The capacity of DT to combine electronic networking and the computation of data in real time has led to the advent of computer gadgets, telecommunications systems, and automation networks to execute tasks. Thus, DT has been defined as the integration of various digital tools, systems, and processes aimed at enhancing construction activities, improving project outcomes, and optimizing resource utilization. DT can also be described as a transformative approach that leverages digital tools and data-driven solutions to enhance construction industry practices. It encompasses a wide range of technologies, including but not limited to building information modeling (BIM), Internet of Things (IoT), augmented reality (AR), virtual reality (VR), artificial intelligence (AI), and automation, with the goal of improving project efficiency, reducing costs, enhancing safety, and delivering higher-quality construction outcomes [18]. Moreso, the emergence of DT has prompted a paradigm shift in the construction industry. It has led to a fundamental change in how construction projects are planned, executed, and managed. DT has the potential to disrupt traditional practices by introducing innovative approaches that enable real-time monitoring, data-driven decision-making, and seamless collaboration among project stakeholders. This transformative impact positions the construction sector to adapt to the demands of the digital age and embrace new opportunities for increased productivity and sustainability.

2.2. Adoption of Digital Technologies (DTs) in the Construction Industry

2.2.1. Design Phase

According to [11] digital technologies (DTs) such as building information modeling (BIM) can be employed for facility planning, design, construction, and operations. It allows construction professionals to view what will be built in a simulated environment, allowing them to spot any potential design, construction, or operational difficulties. BIM and computer-aided design software is highly recommended during the design and engineering phase since they develop a cohesive working unit among the specialists who make up the design team. Other benefits of BIM adoption include improved communication and collaboration between construction professionals, cost reduction, the better coordination of projects, risk reduction, improved scheduling, increased productivity, greater efficiency, and better insight into the construction project [20]. Thus, with the incorporation of DT into the design and engineering stages of a construction project [21], efficiency may be improved and the cost and time overruns associated with design flaws can be guarded against.
Due to the complexity of construction projects often caused by sustainability demands and clients’ requirements, the design stage often involves simulating processes. BIM, virtual reality technology (VRT), 3D printing, and other technologies are used in this stage [2]. According to [11], BIM is frequently utilized on construction sites because of its capacity to provide a simulation of the building’s technical information, including cost estimates, material inventories, and completion time. As a result, BIM may be considered one of the initial technologies that paved the way for Construction 4.0 [16]. Although BIM has its flaws [22], the process can be combined with other technologies like cloud computing to fully harness its potential and capabilities.

2.2.2. Construction and Engineering Phase

The submission by [23] described how DT can be applied during the construction and engineering phase of a construction project. The use of unmanned aerial vehicles or drones can be employed to streamline construction site surveys, enabling precise mapping and real-time progress monitoring. Additionally, drones enhance safety by conducting remote inspections and provide valuable visual data for efficient decision-making in construction projects. Sharma et al. [24] posit that 3D printers can improve the construction phase of a project by reducing injuries and materials costs which can lead to waste reduction, faster delivery time, and the better durability of projects. The use of radio frequency identification (RFID) and GPS tracking technology in construction enables precise asset and equipment management, enhancing resource utilization and project efficiency. These technologies provide real-time data on the location and status of construction assets, leading to improved productivity and cost control [25].
According to [2], the idea of a smart construction site was created out of the unique concept of employing internet sensors to monitor building activities and operations onsite. DTs such as the Internet of Things (IoT), RFID, and other technologies are being used in smart factories. The use of RFID in construction enhances asset tracking and management, streamlining inventory control, reducing losses, and improving overall project efficiency by providing real-time visibility into the location and status of construction materials and equipment [25]. According to [26], the adoption of RFID could also help streamline logistics and supply chain operations in the construction industry by enabling the real-time tracking of materials and equipment, reducing delays, minimizing errors, and optimizing resource utilization, ultimately contributing to cost savings and improved project timelines. With regard to their application in construction operations, robotic automation has received a lot of attention [27]. Through robotics, tedious tasks such as drilling, excavation, and earthmoving can be carried out effectively and efficiently. Robotic automation can also reduce injuries as well as provide a safer working environment during the construction phase of projects [28].

2.2.3. Operation and Management Phase

According to [29], DT can be applied in the area of facilities management in construction projects. In a similar vein, Sajjad et al. [2] suggested that the use of DT during the operation and maintenance phases of a construction project will improve facility management and raise health and safety during the maintenance phase. Through the use of IoT (collection and exchange of data between physical devices and the cloud), project managers can obtain real time data that can be transmitted through sensors [30]. Thus, issues and potential problems can quickly be identified and resolved. Through the help of artificial intelligence (AI), physical assets can be monitored which makes it easier for project managers to predict the performance lifecycle of a construction project before it fails [31]. Consequently, it becomes easier for project managers to conduct preventive maintenance on projects, as they can resolve potential issues before they become problems [32].
The proliferation of IoT means that more data about a construction project will become readily available to project managers. This can be achieved by the installation of sensors on completed projects which can be used in BIM models to monitor energy usage, comfort levels, temperature patterns, defects, and short- and long-term maintenance requirements [31]. Thus, big data can help to improve the working conditiond of a construction project, promote collaboration among construction professionals and increase the efficiency of a construction project [21]. Also, through the use of drones, inspections can be easily conducted even during adverse weather conditions, which can minimize risks to the inspection teams. According to [33], drone technology is revolutionizing the way the inspection, monitoring, and surveillance of construction projects is performed, as they provide a faster and safer approach to the mass collection of data. Wearable technologies like smart badges can help to improve the security of construction projects as well as company data, as only individuals with such technologies can access certain parts of a building or construction project [34]. The analysis in Table 1 further shows the various application areas of DTs that have been discussed in previous literature reviews.

3. Research Methodology

As highlighted earlier, the use of smart technologies and the automation of work processes are pivotal in transforming the landscape of the construction industry [1]. Therefore, this study evaluated the application areas of digital technologies (DTs) in the construction industry, with a view to ensuring that construction projects are smarter and sustainable in the Nigerian construction sector. To be eligible for participation in this study, construction professionals had to be registered and possess knowledge in the field of digitization. Construction professionals based in Lagos State, including architects, builders, engineers, and quantity surveyors, were the primary focus of this study’s target population. Lagos State was selected for this research because of its status as Nigeria’s economic hub and its significant role in the construction and real estate sectors. Lagos is known for its rapid urbanization, large-scale infrastructure projects, and dynamic construction industry. The data collection process involved surveying these professionals to gather quantitative information, aligning with a post-positivism philosophical stance, and employing rigorous research methodology. A quantitative approach was deemed suitable for this study because it allows for the systematic collection and analysis of numerical data, providing statistical insights into the various application areas of digital technologies in the construction industry [45]. This study also adopted a well-structured questionnaire to gather data due to its ability to obtain responses from a vast range of participants within a short period [46]. The questionnaire was divided into two sections: the first section gathered background information from the participants, while the second section assessed 27 application areas of DT which were identified from previous studies. A Likert scale was considered appropriate for this study as it allowed participants to express their opinions and ratings on the 27 application areas in a structured and quantifiable manner, facilitating a comprehensive analysis of their perceptions and preferences [47]. Hence, a five-point Likert scale was utilized in the questionnaire, with ratings of five indicating “very high significance”, four representing “high significance”, three denoting “average significance”, two signifying “low significance”, and one indicating “very low significance”. The decision to employ a closed-ended questionnaire in this study was based on its effectiveness in gathering measurable and quantitative data.
For this study, a convenience sampling technique was chosen to select participants based on their accessibility and willingness to participate, aiming to strike a balance between practicality and data collection efficiency [46]. Given the resource constraints associated with conducting research, convenience sampling proved to be a cost-effective approach as it required fewer resources compared to more complex sampling methods, making it suitable for the available budget. The sampling technique was also adopted in similar studies such as that of [2,48]. Due to the ease of data collection and time-saving tendencies, a closed-ended questionnaire was adopted which was structured into two parts. The designed questionnaire was disseminated to construction professionals based in Lagos State, Nigeria, such as architects, builders, engineers, and quantity surveyors. A survey of the available annual reports from professional bodies representing construction professionals in Lagos State revealed a total population of 5330 members, including 1422 architects, 902 builders, 1504 engineers, and 1502 quantity surveyors (Architects Registration Council of Nigeria, 2021; Council of Registered Builders of Nigeria, 2021; Council for the Regulation of Engineering in Nigeria, 2021; Nigerian Institute of Quantity Surveyors, 2021). A sample size of 120 respondents was calculated from a sampling frame of 5330 construction professionals using the Yamane equation at a level of precision (e) of 9%. The Yamane equation was used because it provides a simplified formula to calculate sample sizes when the population size is known. The sample size formula which was proposed by Yamane and used for this study is shown in Equation (1).
n = N 1 + N ( e ) 2
where n = sample size; N = population; and e = error margin (8%).
Before questionnaires were disseminated to the construction professionals, a pilot test was conducted to evaluate the questionnaire’s clarity, comprehensibility, and overall effectiveness in gathering relevant data [46]. The information gathered from the pilot study was used to refine and improve the questionnaire, ensuring that it was clear, comprehensible, and effective in eliciting the necessary information from construction professionals. Google Forms was selected as the platform for survey administration due to its user-friendly interface, flexibility in questionnaire design and ease of data collection and analysis. Data collection spanned three months between April and June 2023. Out of the 120 questionnaires distributed to the identified construction professionals, 98 responses were received, indicating a response rate of approximately 81%. This high response rate reflects a significant level of engagement and willingness to participate among the surveyed professionals, which enhances the reliability of the study’s data analysis and findings. For data analysis, both the mean item score (MIS) and standard deviation (SD) were employed to examine the central tendency and dispersion of the collected data, providing a comprehensive understanding of the responses from the participants. Following this, exploratory factor analysis (EFA) was employed to identify and analyze underlying patterns or factors within the dataset, helping to categorize and interpret the responses related to the application areas of DT in the construction industry. A Cronbach’s alpha value of 0.885 was obtained from the data collection instrument, indicating a high level of internal consistency and reliability in the collected data, further supporting the validity of the study’s findings. This value was considered acceptable as it surpasses the 0.7 threshold [46].

4. Results

4.1. Background Information of Respondents

The analysis of the background information of the survey respondents provides valuable insights into the demographic and educational characteristics of the sample. Among the respondents, the most common educational qualification was a bachelor’s degree, accounting for 52% of the total (N = 51). Following this, 18.4% of the respondents held master’s degrees (N = 18), while 13.3% possessed national diploma certificates (N = 13). Notably, 11.2% of the respondents had a higher national diploma, and the least common academic qualification among the respondents was a Ph.D., representing 5.1% of the sample (N = 5.1). The predominance of bachelor’s and master’s degree holders suggests that the sample consists largely of professionals with varying levels of expertise. This diverse educational background can contribute to a well-rounded perspective on the subject matter and potentially lead to more comprehensive and nuanced responses in the questionnaire. In addition to educational qualifications, the analysis also revealed details about the professional affiliations of the respondents. The largest proportion of respondents, comprising 38.6% of the sample (N = 28), held registrations with the Quantity Surveyors Registration Board of Nigeria (QSRBN). Meanwhile, 27.6% of the respondents were affiliated with the Council for the Regulation of Engineering in Nigeria (COREN), with 23.5% being registered with the Architects Registration Council of Nigeria (ARCON). Additionally, 20.4% held registrations with the Council of Registered Builders of Nigeria (CORBON). The prevalence of QSRBN registration suggests that a significant portion of the respondents are associated with the quantity surveying profession. The affiliations with COREN, ARCON, and CORBON indicate a diverse range of professionals in the construction and engineering fields, highlighting the broad scope of expertise among the respondents and underscoring the potential for well-informed perspectives on various aspects of the industry.

4.2. Application Areas of Digital Technologies (DTs)

Subsequently, the analysis of the application areas of DTs was conducted and revealed. Table 2 provides a summary of the application areas ranked in descending order of significance. In cases where factors showed the same mean values, the factor with the lowest standard deviation was given a higher ranking, signifying its greater consistency in responses among the participants [46]. Table 2 shows that architectural design is the highest ranked area of the application of DT, with (( X ¯ ) = 4.35; SD = 0.954) which underlines its significance to the construction industry. Cost planning is ranked second, with (( X ¯ ) = 3.85; SD = 1.152), building system analysis is ranked third, with (( X ¯ ) = 3.84; SD = 1.091), structural analysis is ranked fourth, with (( X ¯ ) = 3.81; SD = 1.022), while contract documentation was ranked fifth, with (( X ¯ ) = 3.78; SD = 1.180). Concrete making, with (( X ¯ ) = 2.98; SD = 1.324), bricklaying, with (( X ¯ ) = 2.96; SD = 1.392), and fabrication, with (( X ¯ ) = 2.94; SD = 1.353), were among the least ranked areas of the application of DT, as shown in Table 2. Overall, the findings from Table 2 highlight the varying degrees of significance attributed to the different application areas of DT within the construction industry. Architectural design, cost planning, and building system analysis were among the most prominent areas, while activities such as bricklaying, concrete making, and fabrication ranked lower in importance. These insights can inform strategic decisions and resource allocation to maximize the benefits of DT adoption in construction.

4.3. Factor Analysis of the Areas of Application of Digital Technologies (DTs)

All 27 application areas underwent exploratory factor analysis (EFA) to identify underlying patterns or factors within the dataset, helping to categorize and interpret the relationships among these areas in the context of the study [46]. This study adopted both the Kaiser–Meyer–Olkin (KMO) and Bartlett’s test of sphericity to check the data suitability and appropriateness for EFA. The KMO examines the sampling adequacy and values less than 0.5 are considered not acceptable [46]. Table 3 reveals that a KMO value of 0.820 was achieved, confirming the data’s appropriateness for principal component analysis (PCA) and indicating that 82% of the collected data was suitable for factor analysis. Furthermore, Bartlett’s test of sphericity, presented in Table 3, yielded a significantly high chi-squared value of 2714.281 with 351 degrees of freedom. The PCA revealed that 24.854%, 22.258%, 20.028%, and 6.057% of the variance was explained by the four components, with eigenvalues exceeding 1, which had values of 12.349, 3.889, 2.266, and 1.259, respectively. The cumulative importance of these four clusters of application areas stands at 73.197% of the total, emphasizing their substantial influence on the digital technology landscape within the construction industry. Table 4 displays the rotated component matrix, employing varimax rotation, for detailed examination and analysis. Additionally, Figure 1 presents the scree plot, indicating a discernible break following the fourth factor, suggesting an appropriate choice in factor selection.
Comprising ten factors, the first principal components account for 24.9% of the total variance explained. Within this cluster, the following factors and their loadings on this component are noteworthy: contract management (85.2%), property management (84.5%), asset management (83.2%), procurement management (81.1%), construction supply (72.5%), chain management (71.6%), building system analysis (67.4%), contract documentation (60.7%), dispute resolution (57.5%), and supervision and surveying (57.4%). Taking into account the latent similarities among the rotated variables, this particular cluster of application areas has been renamed as the ‘pre-contract stage’. The second component, which represented 22.2% of the total explained variance, involved eight distinct factors. These factors, with their associated loadings within this cluster, encompassed concrete making (85.5%), fabrication (85.2%), carpentry (83.9%), painting (83.5%), bricklaying (79.5%), drilling (77.5%), excavation (73.1%), and maintenance schedule (65.6%). As a result of this composition, this cluster has been designated as the ‘construction stage’. In the case of the third component, accounting for 20% of the total explained variance, it encompassed seven factors: feasibility study (81.3%), payroll (81%), cost planning (76.8%), construction cost control (76.4%), structural analysis (67.9%), prefabrication (63.2%), and building system analysis (57.3%). This grouping is now identified as the ‘post-contract stage’. The fourth component, which contributed to 6.1% of the total explained variance, featured just two factors: architectural design (86.6%) and existing condition modeling (68.9%). Consequently, this cluster has been named the ‘modeling stage’. These cluster names were selected based on the inherent characteristics of the variables within each specific group.

5. Discussion of Findings

The objective of this study was to evaluate the application areas of digital technologies (DTs) with a view to ensuring that construction projects are smarter and sustainable in a developing economy such as Nigeria. Four clusters of application areas were extracted and are discussed next.
  • Component 1—Pre-contract stage
The objective of this study was to assess the application areas of adopting digital technologies (DTs) in the construction industry. From the results obtained from the survey, the leading areas of application were architectural design, cost planning, building system analysis, structural analysis, and contract documentation. These findings align with the studies of [2,7], who stated that the application of DT can be helpful in the efficient and effective handling of construction planning in the areas of cost planning, structural analysis, and contract documentation.
The first component of the exploratory factor analysis (EFA) encompasses application areas relating to the pre-contract stage such as contract management, property management, asset management, procurement management, construction supply, chain management, building system analysis, contract documentation, dispute resolution and supervision and surveying. These activities are commonly part of the documentation stage, in which several documents that define the scope and requirements of the projects are translated into reports, plans, and bills to execute the project, which agrees with the submission of [49]. Thus, the findings of this cluster align with the studies of [2,10,50] which suggest that digital technologies (DTs) are increasingly being used to enhance the pre-contract stage of construction such as procurement, contract documentation, tender process, the awarding of the contract, and construction supply. This is similar to the studies by [51,52], which state that activities such as asset management and building system analysis can be further improved by adopting DTs. Through the use of digital supply chain and procurement (DSCP) technologies, processes such as bidding and contract documentation can become more efficient and more effective [53]. Moreover, cloud computing has become increasingly prevalent in the construction industry, offering scalability, flexibility, and collaborative capabilities that enhance project management and data accessibility [54]. Similarly, machine learning coupled with artificial intelligence (AI) can significantly benefit procurement management by automating data analysis, predicting material demands, optimizing supplier selection, and reducing procurement costs through intelligent decision-making [55]. Digital building systems play a vital role in enhancing the effective planning of construction projects through visualization and simulation [56]. Augmented reality technology (ART) further complements this by providing on-site, real-time information and interactive 3D models, enabling improved decision-making and collaboration among project stakeholders [4].
  • Component 2—Construction stage
The second component focused on application areas relating to the construction stage such as concrete making, fabrication, carpentry, painting, bricklaying, drilling, excavation, and maintenance schedule. These findings echo the studies of [23,45,57], which describe how the adoption of digital technologies (DTs) can help to improve the performance of certain activities that occurs during the construction stage of a project such as concrete making, bricklaying, and the maintenance of a project schedule. The use of robotic concrete 3D printers to automate concrete production was studied by [45]. Aside from being mobile and agile, these robots can ease the transportation burdens of concrete materials to various sites which can help to reduce labor costs, and reduce waste as well as save time [58]. During the construction phase of infrastructure projects, Ikuabe et al. [23] highlight the importance of unmanned aerial vehicles, commonly known as drones. According to them, drones play a crucial role in providing real-time aerial surveillance, collecting data for progress monitoring, and enhancing overall project efficiency by offering a comprehensive view of the construction site. Moreover, they improve safety through remote inspections and reduce the reliance on manual surveys, ultimately contributing to more effective construction management [35]. Carpentry, which was highlighted in this study, is in line with the study of [41] who opined that the adoption of the Internet of Things (IoT) into carpentry has changed the landscape of the woodwork industry. IoT has also been found to revolutionize construction project monitoring and management by enabling real-time data collection, remote equipment monitoring, predictive maintenance, and enhanced decision-making [59]. Similarly, with the advent of bricklaying robots, construction processes have witnessed increased efficiency, accuracy, and speed. These robots can precisely lay bricks, reducing labor costs and time while improving the quality and consistency of construction work [60]. Likewise, autonomous construction vehicles equipped with advanced technologies, such as GPS and LiDAR systems, have streamlined excavation and earthmoving tasks. These vehicles operate with high precision, reducing human error and enhancing the overall efficiency of construction site operations [4].
  • Component 3—Post contract stage
The third component focused on application areas relating to the post-construction stage such as feasibility study, payroll, cost planning, construction cost control, structural analysis, prefabrication, and building system analysis. These findings agree with the studies of [61,62], who highlighted the roles of DT in enhancing the post-contract phase of construction activities which focus on reviewing, monitoring, and auditing tasks such as cost planning, construction cost control, and structural analysis. According to [1], the use of DT can help to accumulate accurate data which is processed into vital information that helps the construction team execute projects efficiently and effectively in a cost-effective way. Ormiston et al. [63] underscored the need for emphasis to be placed on construction-specific payroll software which will go a long way in automating the complicated calculations around issues such as wages, tax, payments, and deductions. With payroll software, it becomes easy to have a streamlined process of addressing issues of funds disbursements to employees on construction projects. Moreso, with cloud-based tools, it is easier for construction professionals to access data and files anywhere and at any time [64]. The findings of structural analysis and building system analysis in this study are consistent with the observations made by [11]. They emphasize the significance of methodologies like building information modeling (BIM) in optimizing structural design and enhancing the efficiency of building systems within construction projects. According to [65], BIM facilitates a holistic understanding of a building’s performance, fosters collaboration among project stakeholders, and ultimately promotes cost-effective and sustainable construction practices, aligning with the evolving requirements of the industry.
  • Component 4—Modelling stage
The fourth extracted component focused on application areas relating to the modeling stage of construction projects such as architectural design and existing condition modeling. Both [23,66] reinforce this in their studies around the ways in which DT is changing the landscape of architectural design in construction projects. According to [11], DTs such as machine learning, fabrication technologies, artificial intelligence, augmented reality technology (ART), and big data are rapidly changing the modeling stages of construction, especially in the architectural phases. More so, with touchscreen technology, it is now possible to sketch directly into software that can be translated into 3D applications [67]. This firmly relates to the submission of [68] which advocates for the use of BIM in architectural designs due to the object-oriented parametric modeling elements which are present. They opine that BIM saves time, encourages collaborations, fosters flexibility, enhances quality, and improves transparency during architectural designs. Oke et al. [4] also state that ART and virtual simulations allow construction professionals to overlay building plans to achieve desired results such as error-free architectural designs. Therefore, as technology continues to advance, so will architectural designs.

6. Conclusions and Recommendations

This study evaluated the application areas of digital technologies (DTs) to ensure that construction projects are executed in a smarter, faster, and cost-effective way to achieve construction revolution in a developing economy such as Nigeria. To attain the core objective of this study, a quantitative approach was utilized. This approach involved the collection and analysis of data, facilitating a structured evaluation of digital technology applications within the construction industry. It also allowed for the quantification of responses and the discernment of patterns, thereby enhancing the depth of understanding regarding the subject matter. The findings from this study revealed that the most applied areas of DT in construction are the areas of architectural design, cost planning, building system analysis, structural analysis, and contract documentation. Further analysis using EFA revealed four clusters of application areas as pre-contract stage, construction stage, post-contract stage, and modeling stage. The findings of this study can also offer guidance in the evaluation of specific application areas during the development of industry roadmaps to stimulate the acceptance and implementation of DT in the construction industry.
Although the construction industry has been known as a laggard in the adoption of DT, this study further makes a case for construction organizations to formulate ways to promote and enhance the use of innovative and smart approaches in various levels of construction activities and processes. A good way to begin is for construction managers and those at the top echelons of the decision-making food chain to embrace this new wave of digitalization by deploying innovative tools and visualization technologies to enhance work efficiency, boost labor productivity, increase project quality, and encourage sustainability practices. There is also a salient need for construction managers and top-level management to train the workforce in utilizing these technologies in various construction activities. This study, therefore, recommends that construction organizations invest in the upskilling, reskilling, and multiskilling of their employees to ensure a proper understanding of these technologies and their applications in the construction sector.
Overall, the findings from this study have several key implications:
(1)
The study provides construction organizations with insights into innovative ways in which digital technologies (DTs) can enhance various stages of construction projects.
(2)
Policymakers and government entities can leverage the study’s findings to make informed decisions about investing in DT for the benefit of the broader community.
(3)
The study encourages governments to support the digitalization of the construction industry by subsidizing the acquisition of DT, facilitating their widespread adoption in construction organizations.
(4)
Emphasizing the significant safety and productivity benefits of DT, the study advocates for developing countries to embrace and implement DT across various sectors to stimulate economic growth. These sectors include finance, health, energy, aviation, education, and others.
(5)
The study highlights the potential for construction organizations to achieve improved safety measures and enhanced productivity by integrating DT into their operations, which can lead to better outcomes for both workers and the industry as a whole.
(6)
It underscores the importance of staying current with technological advancements in the construction sector, as failing to adopt DT may result in missed opportunities for efficiency and competitiveness.
(7)
The study’s findings also emphasize the role of collaboration between construction organizations, technology providers, and government bodies to create an environment conducive to the successful implementation of DTs in the industry.
(8)
Policymakers can consider incentivizing research and development in DT tailored for the construction sector, as this can lead to the creation of specialized solutions that address industry-specific challenges.
As a limitation, this study focused on the application areas of DT in the context of the construction industry through a broad lens. Future research can be conducted to ascertain how DTs can transform the activities and processes of more specific construction fields such as the building of bridges, dams, highways, and even reservoirs. To gain a further understanding of the state of DT adoption, future studies can be conducted in other developing countries to understand the various drivers and barriers to adopting smarter technologies into the construction industry. This study was also limited to Lagos State in southwestern Nigeria. Further research can be conducted across other parts of the country and other developing nations to validate these findings.

Author Contributions

Conceptualization, A.E.O., J.A. and S.A.O.; methodology, J.A., A.F.K. and A.E.O.; software, J.A. and S.A.O.; validation, P.S.J.S., A.F.K. and M.S.S.; formal analysis, J.A. and S.A.O.; investigation, A.E.O. and S.A.O.; resources, A.E.O. and P.S.J.S.; writing—original draft preparation, J.A.; writing—review and editing, A.E.O. and J.A.; supervision, A.E.O., J.A. and M.S.S.; project administration, A.E.O., J.A. and S.A.O. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

Data are contained within the article.

Conflicts of Interest

The authors declare no conflict of interest.

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Sustainability 15 16378 g001
Figure 1. Scree plot for areas of applications of digital technologies.
Figure 1. Scree plot for areas of applications of digital technologies.
Sustainability 15 16378 g001
Table 1. Summary of the variable of construction areas of digital technologies.
Table 1. Summary of the variable of construction areas of digital technologies.
Areas of ApplicationABCDEFGHIJKLMNOP
Architectural design✓✓✓✓ ✓✓✓✓ ✓✓✓✓✓
Cost planning✓ ✓ ✓ ✓✓ ✓ ✓
Prefabrication ✓✓✓✓ ✓ ✓✓ ✓✓ ✓
Cost estimating ✓✓✓ ✓ ✓ ✓ ✓
Feasibility study✓ ✓ ✓ ✓ ✓
Construction cost control✓✓✓ ✓✓ ✓ ✓ ✓ ✓
Structural analysis ✓✓✓ ✓✓✓✓✓ ✓ ✓
Contract documentation ✓✓ ✓✓
Supervision and surveying ✓✓ ✓ ✓✓ ✓✓ ✓
Building system analysis✓✓ ✓✓✓ ✓✓✓✓ ✓ ✓
Facility management ✓✓ ✓
Dispute resolution✓ ✓ ✓ ✓ ✓✓✓✓
Procurement management ✓✓✓✓✓✓✓ ✓✓✓ ✓
Asset management✓✓ ✓✓✓ ✓✓ ✓ ✓
Property management✓✓ ✓✓ ✓ ✓ ✓✓✓✓
Construction supply✓ ✓✓✓ ✓✓✓ ✓ ✓
Contract management✓✓ ✓✓ ✓ ✓ ✓✓✓✓
Chain management ✓ ✓ ✓ ✓
Project management✓✓ ✓✓✓ ✓ ✓✓✓✓✓
Fabrication ✓ ✓ ✓ ✓✓
Concrete making✓✓ ✓✓ ✓✓✓✓
Carpentry ✓ ✓ ✓ ✓
Excavation ✓ ✓ ✓ ✓ ✓
Drilling ✓ ✓ ✓
Painting ✓ ✓ ✓✓✓✓
Maintenance schedule ✓ ✓ ✓✓✓✓✓
Existing condition modeling✓✓✓✓✓✓✓✓✓✓ ✓✓✓✓✓
Legend: A = [35]; B = [2]; C = [36]; D = [23]; E = [1]; F = [7]; G = [37]; H = [38]; I = [39]; J = [40]; K = [41]; L = [42]; M = [43]; N = [11]; O = [10]; P = [44].
Table 2. Areas of application of digital technologies.
Table 2. Areas of application of digital technologies.
Areas of ApplicationMean ( X ¯ )Std. Deviation (SD)Rank
Architectural design4.350.9541
Cost planning3.851.1522
Building system analysis3.841.0913
Structural analysis3.811.0224
Contract documentation3.781.1805
Construction cost control3.741.0966
Feasibility study3.741.1247
Contract management3.711.1588
Payroll3.661.16610
Supervision and surveying3.661.16611
Property management3.661.2189
Chain management3.631.21312
Project management3.611.31313
Asset management3.601.19914
Construction supply3.581.17515
Prefabrication3.551.15916
Procurement management3.451.20217
Dispute resolution3.421.17518
Existing condition modeling3.371.28719
Maintenance schedule3.261.31120
Excavation3.111.33121
Carpentry3.061.32222
Painting3.041.31523
Drilling2.981.31624
Concrete making2.981.32425
Bricklaying2.961.39226
Fabrication2.941.35327
Table 3. Total variance explained and reliabilities for areas of applications of digital technologies.
Table 3. Total variance explained and reliabilities for areas of applications of digital technologies.
ComponentInitial EigenvaluesRotation Sums of Squared Loadings
Total% of VarianceCumulative %Total% of VarianceCumulative %
112.34945.73945.7396.71124.85424.854
23.88914.40560.1446.01022.25847.113
32.2668.39168.5355.40720.02867.140
41.2594.66273.1971.6356.05773.197
50.7932.93876.135
60.7752.87079.005
70.7462.76481.769
80.6642.46084.229
90.5542.05186.280
100.4901.81488.094
110.4551.68689.780
120.3881.43791.217
130.3251.20492.421
140.2941.08893.509
150.2881.06594.574
160.2670.98795.561
170.2060.76296.323
180.1970.72997.052
190.1720.63597.688
200.1500.55798.244
210.1170.43598.679
220.0980.36599.044
230.0810.30199.345
240.0740.27499.619
250.0550.20399.822
260.0320.11899.940
270.0160.060100.000
Kaiser–Meyer–Olkin Measure of Sampling Adequacy0.820
Bartlett’s Test of SphericityApprox. Chi-Square2714.281
Df351
Sig.0.000
Table 4. Pattern matrix for areas of applications of digital technologies.
Table 4. Pattern matrix for areas of applications of digital technologies.
Application AreasComponent
1234
Pre-contract stage
Contract management0.852
Property management0.845
Asset management0.832
Procurement management0.811
Construction supply0.725
Chain management0.716
Building system analysis0.674
Contract documentation0.607
Dispute resolution0.575
Supervision and surveying0.574
Construction stage
Concrete making 0.855
Fabrication 0.852
Carpentry 0.839
Painting 0.835
Bricklaying 0.795
Drilling 0.775
Excavation 0.731
Maintenance schedule 0.656
Post contract stage
Feasibility study 0.813
Payroll 0.810
Cost planning 0.768
Construction cost control 0.764
Structural analysis 0.679
Prefabrication 0.632
Building system analysis 0.573
Modelling stage
Architectural design 0.866
Existing condition modeling 0.689
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Oke, A.E.; Aliu, J.; Jamir Singh, P.S.; Onajite, S.A.; Kineber, A.F.; Samsurijan, M.S. Application of Digital Technologies Tools for Social and Sustainable Construction in a Developing Economy. Sustainability 2023, 15, 16378. https://doi.org/10.3390/su152316378

AMA Style

Oke AE, Aliu J, Jamir Singh PS, Onajite SA, Kineber AF, Samsurijan MS. Application of Digital Technologies Tools for Social and Sustainable Construction in a Developing Economy. Sustainability. 2023; 15(23):16378. https://doi.org/10.3390/su152316378

Chicago/Turabian Style

Oke, Ayodeji Emmanuel, John Aliu, Paramjit Singh Jamir Singh, Solomon A. Onajite, Ahmed Farouk Kineber, and Mohamad Shaharudin Samsurijan. 2023. "Application of Digital Technologies Tools for Social and Sustainable Construction in a Developing Economy" Sustainability 15, no. 23: 16378. https://doi.org/10.3390/su152316378

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