The digital transformation of the construction industry: a review

The construction sector significantly contributes to economic growth directly through gross domestic product formation and indirectly by supporting other sectors (Chiang, Tao, & Wong, 2015). Despite this, it lags in digitalization and virtualization adoption (Prebanić & Vukomanović, 2021). COVID-19 accelerated digital transformation (DT) in the sector (Olanipekun & Sutrisna, 2021), prompting managers to incorporate digital tools for organizational efficiency and business continuity (Kim, Lee, Yu, & Son, 2022).

The literature reveals not only a rapid increase in implementation cases, but also an adaptation of digital technologies to the operational methods of construction companies (Oesterreich & Teuteberg, 2016). Building information modeling (BIM), Internet of Things (IoT), cloud computing, blockchain, virtual reality tools, digital twin and smart devices (Weber-Lewerenz, 2021) are the technologies changing the traditional operating methods of companies. Construction organizations are still in the process of adapting to the changes brought about by DT, which results in a lack of standardized procedures or well-defined frameworks to facilitate the systematic and efficient integration of technologies. Currently, some technologies have not yet achieved an optimal level of economic efficiency, making them less cost-effective compared to other available solutions (Aghimien, Aigbavboa, Chan, & Aghimien, 2022; Yilmaz, Salter, McFarlane, & Schönfuß, 2023).

On the other hand, the research concerning DT process in the sector is at its beginning, primarily focusing on identifying the benefits and impact of digital technology implementation (Stanley & Thurnell, 2014; Zhang, Ye, Zhong, & Chen, 2023), possible barriers (Liu, Xie, Tivendale, & Liu, 2015; Succar, 2009; Wang, Guo, Zhang, & Schaefer, 2022), drivers of DT process (Nguyen, Do, Nguyen, & Nguyen, 2022; Shojaei, Oti-Sarpong, & Burgess, 2023; Silverio-Fernández, Renukappa, & Suresh, 2021), focusing less on specific cases of DT in the aforementioned organizations (Lasni & Boton, 2022; Shojaei et al., 2023). Academics have also increased their efforts on this topic, the Web of Science database containing 343 studies published between 2020 and 2022, out of a total of 498 studies concerning the DT of the construction sector. Notwithstanding the relatively recent research efforts on analyzing DT in the construction sector, there are literature reviews which analyze different connected topics: the current state of blockchain technology and the development of a coherent approach to support adoption (Li, Greenwood, & Kassem, 2019), the research themes and clusters related to Construction 4.0 (Boton, Rivest, Ghnaya, & Chouchen, 2021), the evaluation of technologies which can be utilized to unleash the full potential of BIM from a technical perspective (Khudhair, Li, Ren, & Liu, 2021), the bibliometrics of DT research in construction (Adekunle, Aigbavboa, Ejohwomu, Adekunle, & Thwala, 2021), the vectors that can transform the construction industry (Menegon & Da Silva Filho, 2023), and the links between digitization and productivity improvement (Zulu, Saad, & Omotayo, 2023).

Due to the early stage of research on DT in the construction industry and field fragmentation (McNamara & Sepasgozar, 2021), an integrative review methodology and systematic research are needed (Zulu et al., 2023). Recent studies call for further research on DT adoption phenomena (Zulu et al., 2023), associated barriers (Gerger, Urban, & Schranz, 2023; Zhang et al., 2023), the factors influencing DT adoption and implementation (Oke, Aliu, Oluwasefunmi Fadamiro, Akanni, & Stephen, 2023), the impact on construction projects’ success (Adekunle et al., 2021; Gerger et al., 2023) and other DT outputs (Yilmaz, Akcamete, & Demirors, 2023).

In response to these requests, this research provides a holistic understanding of the DT process within construction organizations. Therefore, the fundamental question underlying this academic research is as follows:

The systematicity of the analysis is ensured by the use of the context-interventions-mechanisms-outcomes (CIMO) framework, an approach that facilitates the generation of new knowledge, suited for performing literature reviews within the management science (Denyer, Tranfield, & Van Aken, 2008; Halminen, Chen, Tenhunen, & Lillrank, 2021). CIMO’s use in the field of management is related to its capability to generate results even where the literature is highly fragmented (James & Denyer, 2009). It mainly answers the question: how specific interventions (I) produce varied outcomes (O) in different contexts (C)? The interactions occurring among these three categories are termed mechanisms (M) and represent the explanations on why specific interventions lead to certain outcomes in specific contexts (Halminen et al., 2021).

This paper is structured as follows. In Section 2, we present the research on the DT of the construction industry. Section 3 outlines the methodology, detailing the general approach, the search method and the analysis. Section 4 is dedicated to presenting the results of the CIMO analysis, Section 5 contains the mechanisms and the discussions and Section 6 concludes the study.

DT focuses on how organizations change by the use of digital technologies, modifying the value they deliver to their customers (Hanelt, Bohnsack, Marz, & Antunes Marante, 2021). The link between digital technology and the traditional construction industry breaks organizational boundaries, bringing new opportunities for innovation (Warner & Wäger, 2019) and changing the value creation process. In this sector, DT has materialized through the adoption of generic technologies like social media tools (Al-Shehan & Assbeihat, 2021), smart devices (Silverio-Fernández et al., 2021), the IoT (Aghimien, Aigbavboa, Oke, Thwala, & Moripe, 2022), blockchain (Li et al., 2019), resulting in improved project management and team collaboration. Additionally, a limited range of specific tools for the construction industry has been developed, among which the most well-known one is BIM (Succar, 2009).

Research on DT in construction is relatively recent. Initially, researchers focused on studying the BIM standard. The first study on the subject was published in 2003, when researchers began to discuss the shortcomings of computer-aided design (CAD) and proposed BIM as a standard replacement (Ibrahim & Krawczyk, 2003). Subsequently, there was a period of research into commercial, organizational and regulatory barriers (Liu et al., 2015; Succar, 2009), interoperability issues for the industry (Wakefield, 2006), drivers for adoption (Eadie, Odeyinka, Browne, McKeown, & Yohanis, 2013; Wakefield, 2006), organizational benefits (Stanley & Thurnell, 2014) as well as risks associated with BIM adoption by construction companies (Liu et al., 2015). More recently, aspects related to the integration of BIM with other digital tools have been analyzed (Moradi & Sormunen, 2023).

In a relatively recent two-step process, research in the field has focused on the entire spectrum of DT. The first research was published by Oesterreich and Teuteberg (2016), and studied digitization in the construction industry, aiming to identify the stage of adoption of techniques and technologies derived from Industry 4.0. Other papers have analyzed digitization, focusing on issues concerning existing ecosystems and platforms for exchanging information applicable to the sector (Väre & Kiviniemi, 2016), identifying the level of digitization in the construction sector (Dubas & Pasławski, 2017), analyzing technologies and applications (Mesároš, Mandičák, Behún, & Smetanková, 2018), comparing various digital surveying technologies (Krämer & Besenyői, 2018), utilizing data and digital technologies to create value for clients (Lavikka, Kallio, Casey, & Airaksinen, 2018), as well as developing platforms that improve communication among stakeholders of construction projects (Väre & Kiviniemi, 2016).

The concept of “digital transformation” began to be studied in 2018, when concerns were raised about the promises associated with the new technologies, such as the IoT. Subsequently, studies focused on the benefits and impact of implementing digital technologies (Zhang et al., 2023), enablers for implementing digital technologies (Nguyen et al., 2022; Shojaei et al., 2023; Silverio-Fernández et al., 2021), factors hindering the spread of digital technologies (Silverio-Fernández et al., 2021; Wang et al., 2022; Zhang et al., 2023), assessing the levels of DT implementation in the construction industry in different countries (Stojanovska-Georgievska et al., 2022; Zhang et al., 2023), and the role of leadership in the change process that DT entails (Zulu & Khosrowshahi, 2021).

As in other fields, the new technologies of distributed ledger technology (DLT), also known as blockchain, and by some authors as “Web 3.0” (Drexler, 2023), have attracted research efforts. There are few studies and applications of blockchain in construction practices, and most current research involves qualitative studies (Yang et al., 2020). The first study was published by Turk and Klinc (2017) and investigates the solutions that blockchain technology could bring to improve the construction process. Among the topics addressed in the literature are the analysis of DLT maturity in the construction industry (Cheng, Liu, Xu, & Chi, 2021; Li et al., 2019), the sustainability assessment of specific cases through decision support tools, and the proposal of implementation frameworks (Li et al., 2019), the evaluation of smart contract applications (McNamara & Sepasgozar, 2021), the feasibility of applying blockchain in construction materials logistics using RFID technology and the advantages and disadvantages of blockchain technology (Cheng et al., 2021), the perspectives and challenges encountered in implementing blockchain technology in the construction industry (Cheng et al., 2021; Perera, Nanayakkara, Rodrigo, Senaratne, & Weinand, 2020) as well as the potential merger between blockchain and BIM (Li et al., 2019).

It could be concluded that there is a transition from BIM to DT and new technologies, while the research is very fragmented.

According to the model proposed by Tranfield, Denyer, and Smart (2003), this literature review consists of three phases, namely: (1) Planning, which involves establishing the research question; (2) Searching for relevant literature and analyzing it (screening, extraction and coding) and (3) Reporting. The procedure we have followed, including the activities undertaken at each phase, is described in Figure 1.

We began our search (Activity A1 – see Figure 1) in January 2023 in the Web of Science database. We chose this database because it includes a wide range of academic sources. Following the recommendation of Torres-Carrion, Gonzalez-Gonzalez, Aciar, and Rodriguez-Morales (2018), we established a pair of keywords that describe the purpose of this research: “digital transformation” and “construction”, searching within titles, abstracts and keywords. This led us to a total of 331 academic sources (R1). We proceeded with the first screening process (A2), reviewing the titles and abstracts of the sources returned in the previous step, guided by inclusion criteria (cases which detail DT or digital technologies adoption in construction organizations) and exclusion criteria (sources on other topics than DT, focus on other sectors, conceptual papers). The results of the initial screening were 68 eligible sources (R2) and 263 irrelevant sources (R3). The second screening (A3) involved the full reading of the 68 eligible sources, taking into account the previous inclusion and exclusion criteria, this leads to 15 relevant studies (R4) and 53 irrelevant studies (R5).

The data extraction and coding (A4) of the 15 sources was performed considering the CIMO, proposed by Denyer et al. (2008). The 15 sources presented 12 cases of DT implementation and three cases testing certain hypotheses. We have considered more coding categories (CC): for bibliometrics – the type of work, the covered geographic area, and the methodology used; for context – adoption drivers, factors facilitating implementation, barriers to adoption and early adoption risks; for intervention – used technologies and adoption barriers; and for results – the internal and external output. Mechanisms (M) were to be identified following the C-I-O analysis.

The 15 sources were published between 2018 and 2023, indicating that research on the implementation of DT within construction companies is in its early stages. The majority (n = 14) are journal articles, and one is a conference paper. The most cited article belongs to Li et al. (2019), with 426 citations on Google Scholar, followed by Papadonikolaki (2018) – 103, Greif, Stein, and Flath (2020) – 97, Koseoglu, Keskin, and Ozorhon (2019) – 52, while the rest have less than 50 citations, as can be observed in Table 1. Most sources focus on Western Europe (n = 3) and Africa (n = 2), with the remaining sources concentrating on Asia (n = 2) and North America (n = 1). For the rest, the region is not mentioned.

Most of the sources are purely empirical (n = 14), and one source tests conceptual models through empirical analyses. The used methods are interviews (n = 8), questionnaires (n = 5), internal document analysis (n = 4), statistical analysis (n = 3), observation (n = 2), expert panel (n = 1), discussions within a focus group (n = 1) and Delphi method (n = 1).

The context refers to internal and external environmental factors that can influence organizational behavior change (Denyer et al., 2008). In our case, we have considered multiple dimensions which describe the context: adoption drivers, facilitating factors of implementation, barriers to DT and risks identified at the beginning of the DT process. Eleven sources have focused their scientific efforts on at least one of the previously mentioned context dimensions.

The elements identified in the analyzed dimensions were divided into four categories of context based on the similarity and nature of the information, namely: economic, operational and procedural, technological, and security and strategic. The economic context refers to the contextual factors that can be more easily influenced by the company and pertains to: implementation cost (n = 5), project cost (n = 4), company size (n = 4), financial, accounting, and liquidity risks (n = 3), efficiency (n = 3), exchange rate volatility (n = 1), training cost (n = 1), return on investment rate (n = 1). The operational and procedural context refers to factors related to the management of the company's day-to-day activities, as well as the procedures the company adopts in the DT process: employee training and motivation (n = 12), organizational management (n = 9), definition, requirements, and characteristics (n = 8), communication and information (n = 3), team empowerment (n = 2), asset management (n = 2), energy consumption (n = 2). The technological and security context refers to those environmental factors related to how DT is integrated into organizational processes, as well as the firm's ability to maintain the security of its data: connectivity and accessibility (n = 11), technical capabilities of HR (n = 10), quality interfaces (n = 7), availability of tools (n = 7), data security (n = 3), interoperability (n = 3), software compatibility (n = 2), technological state of the industry (n = 2), cyber-attacks (n = 1). The strategic context encompasses the internal and external environmental factors that influence the direction of DT and the strategic decisions adopted by the company to achieve a competitive advantage: organizational culture (n = 13), full integration into the supply chain (n = 13), digital strategy (n = 6), top management support (n = 5), competitive pressure (n = 4), talent retention capability (n = 1).

Concerning the intervention, we have considered two dimensions: the technologies and the barriers encountered during the DT process.

All 15 sources revealed the technologies. Primarily mentioned was the BIM tool (n = 6), followed by the IoT (n = 2), cloud computing (n = 2), digital twin (n = 2), augmented reality (n = 2), blockchain (n = 2), smart devices (n = 1), machine learning technologies (n = 1), webcams with headsets (n = 1), digital markers (n = 1), virtual reality glasses (n = 1), AI sensors for defect and fault detection (n = 1), sensors for material defects, temperature changes, humidity (n = 1), robots for automated 3D scanning on-site (n = 1), autonomous construction machines (n = 1), autonomous and semi-autonomous bulldozers (n = 1), data complexity structuring systems (n = 1), big data (n = 1), drones (n = 1), 3D printing (n = 1), autonomous robots (n = 1), Power BI (n = 1), MS Project (n = 1), Low-Code Development Platform (LCDP) – Microsoft Power Apps (n = 1). Following the model proposed by Oesterreich and Teuteberg (2016) and adapted to the construction sector, three types of clusters regarding the types of implemented technological tools were identified: smart construction (n = 13), simulation and modeling (n = 8), and digitization and virtualization (n = 3).

The barriers that occur during the implementation process change in comparison to those identified before the initiation of the DT implementation process. Following the model proposed (Saberi, Kouhizadeh, Sarkis, & Shen, 2019), we grouped the barriers obtained from our sources into four main categories: intra-organizational, inter-organizational, system and external, and the results showed that most of the barriers that arise during the implementation process fall within the system (n = 6), intra-organizational (n = 5) and inter-organizational (n = 1) spectra. Unlike the barriers at the beginning of adoption, we note the disappearance of external barriers, while the proportion of other types changes.

To analyze the results, we operationalized these intervention effects in terms of internal and external benefits associated with DT implementation. Out of a total of 15 sources, 10 of them do not mention any category of results obtained following the implementation of DT.

Considering Bunduchi, Weisshaar, and Smart (2011), we differentiate between internal benefits based on their strategic importance, namely: direct, indirect and strategic benefits. Out of a total of 15 sources, 8 of them investigate the internal benefits of the studied phenomenon. The direct benefits (n = 16) include: easing human labor (n = 1), data accessibility (n = 1), reviewing design and planning (n = 1), visualizing changes (n = 1), access to RFI and submitted documents (n = 1), notification of control documents (n = 1), constant tracking of site progress and subcontractor achievements (n = 1), subsequent evaluation of construction phases (n = 1), precise planning of project resources storage and procurement (n = 1), prefabrication of construction components (n = 1), BIM allows better utilization on-site (n = 1), real-time planning and financing (n = 1), providing real-time information (n = 1), assigning predefined routes for goods delivery (n = 1), ability to monitor the site (n = 1) and accurate inventory records (n = 1). The indirect benefits (n = 23) refer to: cost reduction (n = 6), improved work efficiency (n = 5), high quality (n = 4), better productivity (n = 4), error minimization (n = 2), more efficient time management (n = 2), increased stability through lean construction processes (n = 2), making better decisions based on generated data (n = 1), reduced routine processes for employees (n = 1), controlled division of labor (n = 1), more efficient problem management (n = 1), improved service delivery (n = 1), lower labor costs (n = 1), reduced accidents on site (n = 1), enhanced project performance (n = 1), tracking and allocation of safety and health issues on site (n = 1), reduced workload (n = 1), providing better clarity regarding the design process (n = 1), better employee motivation (n = 1), high efficacy (n = 1), better demand forecasting (n = 1), staff restructuring (n = 1). The strategic benefits (n = 9) include: reducing the implementation period of investment-construction projects (n = 5), improving the attractiveness of services and products (n = 1), enhanced skills and expertise (n = 1), gaining a competitive advantage (n = 1), expanding the portfolio of services offered (n = 1), a knowledge network spanning all digital boundaries (n = 1), predicting future events and ease in decision-making (n = 1), attracting talents to the organization (n = 1), as well as new and more competitive business models (n = 1).

We observe that the majority of internal benefits identified by our sources fall into the category of indirect benefits (n = 23), followed by direct benefits (n = 16) and strategic benefits (n = 9).

Regarding external benefits, seven sources have identified such outcomes. These primarily relate to better results within the supply chain (n = 5): providing transparency and trust for stakeholders (n = 1), increasing collaboration in the supply chain (n = 1), a better understanding of the project from the customer's perspective (n = 1), involving the customer in the process (n = 1), resolving understanding issues between designer-builder-client (n = 1), providing descriptive analysis services to customers (n = 1). Additionally, there are results with an impact in the ecological sphere (n = 3): protecting natural resources and the climate (n = 1), a high social contribution to the transition toward a climate-friendly society (n = 1) and energy efficiency for clients (n = 1).

Within the CIMO framework, mechanisms are the elements that give meaning to existing data, establishing the connections between specific interventions and the contexts in which they occur, while observing the outcomes that are generated (Denyer et al., 2008). To establish the mechanisms characterizing DT within construction companies, we analyzed the evident connections between the dimensions analyzed regarding context, intervention and outcomes. The refinement of dimensions involved grouping context categories based on their nature, namely economic, operational and procedural, technological and security, and strategic. Additionally, we grouped the technologies used into three categories: basic technologies, which include tools such as BIM, Enterprise Resource Planning (ERP) platforms, social media platforms and smart devices; specialized technologies, where we included LCDPs, Power Apps, Geopogo AR, Power BI and MS Project; and advanced technologies, where we included tools such as blockchain, cloud, the IoT, big data, etc. We kept the grouping of benefits according to Bunduchi et al. (2011), namely direct, indirect and strategic benefits.

As a result, we managed to identify three mechanisms that correspond to a certain level of maturity for the companies implementing DT. The first two categories are quite common and describe the transformation of traditional construction companies, while the last category is disruptive in terms of the business model of organizations.

The three mechanisms directly explain the relationships that occur between interventions and outcomes, where a specific intervention leads to a specific set of results, but also indirectly, where a specific mechanism triggers other mechanisms (for example, traditional DT can be combined with niche DT, which in turn can lead to advanced DT), as can be observed below.

M1. The traditional DT is a fundamental mechanism that describes construction companies that have implemented basic interventions, such as BIM technologies, social media tools, smart devices and ERP platforms. It occurs in an economic, operational, procedural, technological and security-favorable context, predominantly leading to direct and indirect outcomes, such as efficient monitoring of work, accurate inventory records, cost reduction, time and error reduction, quality improvement, efficiency and effectiveness. The main purpose of this type of DT is to improve both internal organizational communications and communications between the company and other stakeholders (clients, designers, etc.). Another important objective is anticipating errors even before the construction stage, a specific goal of implementing BIM technology. As a fundamental mechanism, it often, but not necessarily, complements other types of mechanisms corresponding to a higher level of maturity.

The traditional DT of construction companies is present in six sources (Koseoglu et al., 2019; Nguyen et al., 2022; Papadonikolaki, 2018; Shojaei et al., 2023; Silverio-Fernández et al., 2021; Stojanovska-Georgievska et al., 2022). The transition from a previous stage of non-digitization to this stage has necessitated numerous organizational changes (Westerman, Bonnet, & McAfee, 2014), and construction companies have generally encountered resistance to change among employees (Li et al., 2019; Mazurchenko & Zelenka, 2022). This stage of digital development for construction companies involves changes in the operational structure of the companies, which is why the results obtained from the implementation of basic technologies mainly consist of direct and indirect benefits, similar to the results of Kim et al. (2022). Although some authors consider the entire construction industry to be in an early development phase (Prebanić & Vukomanović, 2021), our research indicates that it is indeed a commonly encountered mechanism in construction organizations, but we cannot identify it as predominant, regardless of the context in which it occurs.

M2. The specialized DT is a mechanism that describes construction organizations that have implemented specialized technologies such as Microsoft Power Apps, Geopogo AR, Power BI and MS Project platforms. This is achieved in an operational and procedural, technological and security-favorable context, predominantly leading to indirect outcomes, such as cost reduction, errors, and construction time, increased productivity, profitability, efficiency and effectiveness, improved quality, and employee motivation. The main purpose of this type of DT is to improve the efficiency of construction projects. This mechanism transcends the boundaries of traditional methods, transitioning toward advanced DT. To achieve this, it is necessary for the construction organizations to have undergone the traditional DT process, having at least some basic technologies such as smart devices. In practical terms, a company reaches the niche DT level by adding one or more specialized technologies to the existing ones, leading to better indirect results.

In our research, specialized DT was identified in three sources (Cai et al., 2022; Griffith & Alpert, 2022; Lasni & Boton, 2022). Typically, a company adopts such technology, especially to improve its organizational efficiency and effectiveness, reduce costs, and, most importantly, achieve higher quality in construction projects. Regarding the geographical area, we noticed that this mechanism is identified in economically developed countries such as Germany and Canada, where special attention is given to both research on DT in the organizational context and technological research, as support for implementation within companies, fact aligns with the observations made by Oesterreich and Teuteberg (2016). In line with (Olanipekun & Sutrisna, 2021), we have observed that the implementation of specialized technologies like these only began in 2022.

M3. The advanced DT is a mechanism achieved within a favorable strategic, technological and security context, leading to predominantly strategic outcomes through the implementation of advanced technologies such as blockchain, cloud computing, etc. (see Figure 2). The strategic outcomes primarily involve predicting future events, improving decision quality, forecasting demand, expanding the service portfolio and creating sustainable and energy-efficient structures. However, the primary purpose of implementing such advanced technologies remains gaining a competitive advantage in the dynamic and ever-changing construction industry market (Aghimien, Aigbavboa, Oke et al., 2022), offering customers new services (Greif et al., 2020) or superior quality services (Weber-Lewerenz, 2021).

Six sources illustrate this mechanism (Aghimien, Aigbavboa, Chan, & Aghimien, 2022; Aghimien, Aigbavboa, Oke, & Aliu, 2022; Greif et al., 2020; Li et al., 2019; Sadeghi et al., 2022; Weber-Lewerenz, 2021). This mechanism has been identified in countries such as the United Kingdom, Germany and South Africa, which are at the forefront of countries regarding research on innovative technologies. Chronologically, the first analyzed study describing the implementation of advanced technology was published in 2019 (Li et al., 2019). Since then, the organizational impact of these operational changes has been under investigation. In terms of frequency in our data source, advanced DT holds a prominent position, constituting 40%, on par with traditional DT.

For practitioners, the results of our work summarize the DT that the construction industry is undergoing and should help them establish a path for DT within their own companies. The results of this research confirm that the adoption and implementation of digital technologies have transformed the construction world, and this process cannot be ignored by companies in the industry; otherwise, they risk losing market share and even endangering their existence. In short, an increasing number of construction companies have adopted and utilized digital tools in recent years to enhance their construction projects, anticipate potential errors, and complete construction projects either on time or even ahead of schedule. Considering the entire entrepreneurial spectrum and aligning with previous statements made in the literature (Li et al., 2022), to remain relevant and competitive in the market, firms must adopt new strategies and question their business model. In an increasingly digitized world, where information and data are expanding rapidly, customer expectations are continuously rising, and project delivery deadlines are becoming shorter, the lack of adopting technologies that support organizational objectives in line with customer needs will pose a challenge for companies lagging behind the digital curve and an opportunity for those choosing to invest in digitization (Härting, Reichstein, & Schüle, 2022). Without a change/adaptation in the business model, where specialized technological information and IT tools play an integrated role, construction companies cannot take advantage of this immense opportunity (Woodhead, Stephenson, & Morrey, 2018).

We began this review with the aim of analyzing specific cases of DT adoption within construction companies and generating prescriptive knowledge about the paths that construction organizations can follow in the DT process. The construction industry lags behind in terms of digitalization, not yet reaching a mature level in this regard (Prebanić & Vukomanović, 2021), but adoption cases are rapidly accelerating (Olanipekun & Sutrisna, 2021).

Through our analysis, which involved the use of the CIMO framework, we managed to provide a comprehensive analysis of the specialized literature regarding the adoption of DT in construction organizations, integrating elements related to the context, interventions and implementation process outcomes. In the end, we present our findings in the form of three mechanisms or paths that construction companies could follow: advanced, niche and comprehensive DT. These three paths could correspond to a maturity model.

Our research has several limitations. The data source for the CIMO analysis conducted is relatively small because studies on DT in construction firms are limited, as is the implementation of DT in these companies. Unfortunately, there are few sources that provide sufficient details regarding the entire adoption process and how DT has practically impacted construction companies. Another limitation is related to the CIMO methodology itself, its goal being to generate mechanisms/designs based on the analysis of literature (Denyer et al., 2008), without targeting the analysis of trends concerning different phenomena.

These limitations leave room for possible future research that can be conducted in different directions, at various levels. Firstly, considering the mechanisms identified in this study, several empirical analyses regarding DT within construction companies can be conducted using qualitative methodologies, examining the process as a whole. Secondly, from a human resources perspective, a future research direction could be analyzing how DT alters the nature of positions in construction, ranging from unskilled laborers to project managers, considering the new skills required.