A Holistic Evaluation of BIM Implementation Barriers in the Indian Construction Industry: Pre- and Post-Adoption Perspectives

ABSTRACT

The existing Building Information Modelling (BIM) research does not provide a holistic understanding of pre- and post-adoption barriers to its implementation, especially in developing countries such as India, where BIM adoption lags. First, a total of 32 barriers to BIM implementation were identified after a comprehensive literature review. Second, after discussion with experts, the barriers were classified into 23 pre- and 21 post-adoption barriers. Next, the barriers were ranked based on 218 completed survey responses from professionals working in 125 organizations in the Indian construction industry. Finally, an independent samples t-test was conducted to understand differences in the perceptions of different groups of participants. The top five pre-adoption barriers were (1) high hardware costs, (2) high software costs, (3) low adoption across the supply chain, (4) low market support, and (5) unclear benefit evaluation. In comparison, the top five post-adoption barriers were (1) high ongoing cost (license renewal, training cost, etc.), (2) shortage of skills and expertise, (3) unclear benefit evaluation, (4) client’s lack of understanding, and (5) user resistance. Moreover, clients, contractors and consultants shared different views on very few barriers, which shows that these barriers are prevalent across different types of organizations in the Indian construction industry.

KEYWORDS:

• Building Information Modelling (BIM)
• technology adoption
• construction organization
• adopters
• non-adopters

Introduction

Building information modeling (BIM) has been embraced in the Architecture, Engineering, and Construction (AEC) industry as a catalytic agent to change how design, construction and building maintenance information is processed, managed, stored and communicated during the project lifecycle and beyond. The National Institute of Building Sciences (NIBS) defines BIM as “a business process that generates data to be used during the various phases of a building’s life cycle including design, construction, operation and maintenance” (National Institute of Building Sciences NIBS, 2015).

BIM is considered a technological and process innovation that could improve productivity in construction projects and elevate the overall performance of construction organizations (Arayici et al., 2011; Lee et al., 2015). For example, Li et al., (2019) integrated BIM into prefabrication housing production to enhance decision-making, collaboration, and efficiency. Wang et al., (2023) proposed a BIM-based framework to prevent and control construction disputes throughout the project life cycle. Previous studies demonstrate that adopting BIM could provide a wide range of benefits to construction organizations from the conceptual stage to the construction and operational phases, such as 3D visualization, clash detection, quantity take-off, improved productivity, fewer change orders, reduced construction time and costs, and facility management (Mostafa et al., 2020; Olbina & Elliott, 2019; Sawhney et al., 2014).

The plethora of research on BIM applications in different projects and contexts supports the claims that BIM has the potential to offer numerous benefits to project participants and organizations in the construction industry. However, despite the substantial evidence concerning various applications of BIM and associated perceived or tangible benefits, the adoption of BIM in the construction industry remains non-uniform worldwide (Ahuja et al., 2020; Sawhney et al., 2014). For instance, a higher level of BIM implementation is reported in developed countries such as the United States (Lee & Yu, 2016), the United Kingdom (Lam et al., 2017), Australia (Hong et al., 2019), and South Korea (Lee & Yu, 2016) than in developing countries such as India (Ahuja et al., 2016) and Malaysia (Rogers et al., 2015).

Moreover, there is a lack of research on a holistic understanding of pre- and post-adoption barriers to BIM implementation in the construction industry. The existing studies sometimes do not differentiate between these two phases of technology adoption. Moreover, many studies mainly focus on barriers to initial BIM adoption (Babatunde et al., 2020; Hall et al., 2023). Zhou (2011) describes the initial adoption phase as the first-time usage of a technology or service. In contrast, the post-adoption phase refers to the continued and repeated use of technology or services. In the post-adoption phase, technology becomes part of the routine activity (Bhattacherjee, 2001). Therefore, the long-term success and associated productivity gains of technology implementation rely on technology’s integrated and continued use in the post-adoption phase (Son & Han, 2011). The benefits that can be gained from technology implementation depend on its actual usage (Saeed & Abdinnour-Helm, 2008; Hasan, Ahn, Baroudi, et al., 2021; Hasan, Ahn, Rameezdeen, et al., 2021). When construction organizations adopt a technology, users’ reluctance to accept and use it in the post-adoption phase could reduce its usage and the associated benefits (Hasan, Ahn, Baroudi, et al., 2021; Hasan, Ahn, Rameezdeen, et al., 2021). Many construction organizations have been found to discontinue BIM usage after applying it to some projects or limit the use of BIM to the design phase only rather than using it during all project phases (Nanajkar & Gao, 2014).

Since the initial adoption has different characteristics from the post-adoption stage (Bhattacherjee, 2001; Hasan, Ahn, Baroudi, et al., 2021; Hasan, Ahn, Rameezdeen, et al., 2021; Zhou, 2011), understanding the factors affecting BIM adoption decision and its post-adoption usage based on the perception of non-adopters and adopters is vital for the successful adoption and continued use of BIM in the construction industry. Since BIM adoption refers to the decision to use BIM software and protocols on construction projects (Mohammad et al., 2018), pre-adoption is the stage when a construction organization is considering the decision to adopt BIM, while post-adoption refers to the stage when the BIM adoption decision has already been implemented, i.e., the organization has started using BIM in projects, services or facility management.

In the present study, the barriers affecting the adoption decision of BIM have been collectively referred to as the pre-adoption barriers. On the other hand, the barriers organizations experience following the BIM adoption decision, when the target behavior is continued BIM usage, have been collectively referred to as the post-adoption barriers. Various barriers that need to be resolved before BIM adoption (i.e., pre-adoption barriers) can be expected to be different from unknown barriers that will only be known and resolved when BIM is adopted (i.e., post-adoption barriers) (Olugboyega & Windapo, 2022). Yet, little research has been done to provide a cross-sectional view of pre- and post-adoption barriers to BIM implementation in the construction industry.

Successful BIM implementation in construction organizations in developing countries such as India could play an instrumental role in meeting their massive urbanization and infrastructure development needs. Prasad et al. (2019) recommended mandating the use of BIM in the Indian construction industry to identify and minimize design-related delays in building projects. However, construction organizations in India lag in the BIM adoption journey, and consequently, the Indian construction industry is yet to realize the full potential of BIM (Ahuja et al., 2016, 2020).

Against this background, this study aims to shed some light on the factors affecting BIM implementation during the pre- and post-adoption phases to provide a holistic view of barriers to BIM implementation in the context of the Indian construction industry. Specifically, the two objectives set for the study are:

1. To identify critical barriers to BIM implementation during pre- and post-adoption phases.

2. To investigate the differences in perceptions of construction professionals concerning pre- and post-adoption barriers to BIM implementation.

The rest of the paper is organized as follows. First, the extant literature on technology implementation and factors affecting BIM implementation in the construction industry is presented. This is followed by an overview of the research methodology. Consequently, important barriers during the pre- and post-adoption phases are discussed along with the implications of the study for theory and practice. Finally, the conclusion section summarizes the key findings and presents the study’s limitations.

Literature review

Technology implementation - lifecycle perspective

There are numerous studies focusing on technology adoption models and determinants of technology acceptance and utilization among users (Lee et al., 2015). The technology adoption lifecycle could be divided into four phases – pre-adoption, initial adoption, post-adoption, and termination (Maier et al., 2015). The beliefs that users hold for the continued use of technology could differ from those that led to the initial adoption of technology. As a result, the user perceptions or beliefs may change during the post-adoption phase as users gain actual experience of the technology usage when more information is available through their direct experience with technology than through word-of-mouth or pre-conceived notions (Bhattacherjee & Premkumar, 2004). Moreover, if the technology does not meet the expectations of the users or organization, they may decide to reduce or terminate its usage (Hasan, Ahn, Baroudi, et al., 2021). Therefore, initial adoption is only one of the critical decisions organizations make during their technology implementation journey and may not always result in successful implementation.

While several studies claim numerous perceived benefits of BIM adoption and promote its adoption in the construction industry, the mere adoption of BIM may not always translate into its successful implementation and integration into the existing processes and workflows. Sometimes, construction organizations may not realize the full benefits of BIM due to its limited use or flawed implementation. Dowsett and Harty (2019) argue that heterogeneous teams and disparate practices and procedures in construction projects could make BIM implementation a complex process. Hasan, Ahn, Baroudi, et al. (2021) also found that the successful implementation of technology in project-based construction organizations can be far more complicated than institutional technology adoption and use. Therefore, assuming the benefits of using the new technology as an inevitable outcome of adoption could be problematic (Winch, 1994). Specifically, underutilizing technology during the post-adoption phase could undermine organizations’ efforts to improve productivity and performance and derive benefits from such systems (Venkatesh et al., 2008). Consequently, attention must be paid to both pre and post-adoption phases for successful technology implementation and usage.

Barriers to BIM adoption and use in developing countries

Many researchers have studied the barriers to BIM implementation in developing countries. For instance, the top five ranked barriers affecting BIM implementation in contracting firms in Nigeria were the high cost of hardware and software and its updates, not knowing where to start, interoperability issues and the cost of BIM training (Babatunde et al., 2020). Similarly, other studies have identified lack of awareness, lack of skill, lack of government support and cost of implementation as the impeding barriers to the proliferation of BIM in the Nigerian construction industry (Ogunmakinde & Umeh, 2018; Olanrewaju et al., 2020).

Olugboyega and Windapo (2022) found that organizational challenges and planning difficulties constituted barriers to sustained BIM adoption in the South African construction industry. Belay et al. (2021) showed that inadequate data infrastructure, lack of government support and absence of BIM-related teaching and research affected BIM implementation in Ethiopia. Whereas Alemayehu et al. (2022) identified lack of BIM professionals, unavailability of proper BIM training, lack of BIM-ready stakeholders, lack of guidelines and standards, and lack of supportive delivery methods or integrated design as the top-five ranked BIM adoption barriers in the Ethiopian construction industry. Tehami and Seddiki (2023) found that people and policy factors were the most critical barriers to BIM implementation in Algeria. They concluded that BIM implementation would not occur unless local authorities and policymakers work toward promoting and accelerating BIM adoption.

The significant barriers to BIM implementation in prefabricated construction in China were insufficient BIM research in the country and a lack of standards and domestic-oriented tools (T. Tan et al., 2019). The five most significant barriers to BIM implementation in the Hong Kong construction industry were resistance to change, interoperability issues, organizational structure not supporting BIM, lack of industry standards and difficulties in evaluating the benefits of BIM. Additionally, a relatively good level of consensus was observed among the respondents’ groups (client-consultant-contractor) on the rankings of the barriers to BIM implementation (Chan et al., 2019). Rogers et al. (2015) revealed that a lack of well-trained personnel, guidance, and governmental support were significant barriers to low levels of BIM implementation among Engineering Consulting Services firms in Malaysia.

Gerges et al. (2017) identified five major obstacles to BIM implementation in the Middle East: comparison of BIM to CAD, resistance to change, additional cost incurred in BIM implementation, lack of a BIM specialist in the region and absence of client demand. In the Kingdom of Saudi Arabia (KSA), a lack of interest by clients and industry stakeholders, inadequate experience of the BIM team, and lack of mentorship from a BIM champion adversely affected BIM adoption (Almuntaser et al., 2018). In another study, the lack of policy initiatives and the need for reengineering projects were found to be significant barriers to a successful transition toward BIM in the KSA (Al-Yami & Sanni-Anibire, 2021). Mehran (2016) identified three significant barriers to BIM adoption in the construction industry of the United Arab Emirates (UAE): lack of BIM standards, lack of BIM awareness, and resistance to change. On the other hand, Omar and Dulaimi (2023) found resistance to change, lack of top management support, and the significant effort needed to make changes in workflow as the main barriers to BIM adoption in the UAE.

Ahuja et al. (2016) utilized a technology-organization-environment framework to investigate the reasons for slow BIM adoption by Indian architectural firms. The study found that factors such as the complexity of BIM implementation, compatibility of BIM technology, perceived cost, trade partner readiness and client requirements have no significant influence on BIM adoption decisions. In contrast, factors such as trialability, top management support and BIM expertise have a strong positive effect on BIM adoption. Hong et al. (2019) found that the importance of challenges associated with BIM adoption somewhat differs between BIM users and non-users. While BIM users reported users or staff’s resistance to change and high implementation costs as the main challenges to BIM adoption, non-users considered high implementation expenses and staff’s inadequate experiences in BIM utilization as significant BIM adoption barriers.

Akdag and Maqsood (2019) pointed out two critical issues for further adoption and implementation of BIM in Pakistan: the lack of professional BIM users and education and training issues. In Egypt, Marzouk et al. (2022) revealed factors such as lack of governmental support and absence of implementation strategy affecting BIM adoption in the construction industry. Hatem et al. (2018) identified a weakness of the government’s efforts, poor knowledge about the benefits of BIM, and resistance to change as the top three potential barriers to using BIM in construction projects in Iraq. In the Turkish construction industry, factors such as ignorance about the added value of BIM in the industry, lack of standards or legislation, lack of encouraging or obligatory contractual clauses, inefficient leadership, high initial investment cost of the BIM software and hardware and technological deficiencies of the stakeholders were the major obstacles to BIM implementation (Aladag et al., 2016).

In Lebanon, Syria, Jordan, and North African countries, poorer government initiations to support BIM and a lack of mandated BIM use affected BIM adoption (El Hajj et al., 2023). The high cost of training, lack of BIM standards and lack of BIM awareness were identified as the extreme barriers to BIM adoption in the Jordanian construction industry (Matarneh & Hamed, 2017). In comparison, significant barriers to BIM implementation for industrialized buildings in China were capital-related factors and the lack of support from clients (P. Wu et al., 2021). The major barrier to adopting BIM in the Vietnamese construction industry was the stakeholders’ lack of consistency and participation in the BIM implementation process (Dao et al., 2021).

From the existing literature on barriers to BIM adoption and use, 32 barriers to BIM implementation in construction organizations were identified. Table 1 shows the barriers to BIM implementation and their sources.

Table 1. List of BIM implementation barriers

S. No	Barrier	Source(s)	Barrier classification
1	Contractor’s lack of understanding of BIM	Khosrowshahi and Arayici (2012), Doan et al. (2021)	Pre-adoption barrier
2	High cost of hardware for required BIM adoption	Gerges et al. (2017), Ogunmakinde and Umeh (2018), Olanrewaju et al. (2020)	Pre-adoption barrier
3	High cost of software for required BIM adoption	Khosrowshahi and Arayici (2012), Abubakar et al. (2014)	Pre-adoption barrier
4	Risks and liabilities associated with BIM implementation	Lam et al. (2017)	Pre-adoption barrier
5	Chances of contractual disputes	T. Tan et al. (2019)	Pre-adoption barrier
6	Business disruption due to changes in the existing processes	Chien et al. (2014)	Pre-adoption barrier
7	Resource-intensive implementation process	Eastman et al. (2011)	Pre-adoption barrier
8	Data ownership issues	Rogers et al. (2015)	Pre-adoption barrier
9	Lack of government policies and incentives	Rogers et al. (2015), Ahuja et al. (2020)	Pre-adoption barrier
10	Complicated and time-consuming BIM processes	Becerik-Gerber and Kensek (2010)	Pre-adoption barrier
11	Adequacy of the existing CAD/software systems (i.e., BIM is not needed)	Alreshidi et al. (2017)	Pre-adoption barrier
12	Variations in client’s demand	Gerges et al. (2017)	Post-adoption barrier
13	Communication issues with other project participants/supply chain partners	Chan et al. (2019)	Post-adoption barrier
14	Contract conditions concerning the use of BIM	Chien et al. (2014)	Post-adoption barrier
15	Ongoing high cost of implementation (license renewal, training cost, etc.)	Abubakar et al. (2014), Alreshidi et al. (2017)	Post-adoption barrier
16	Unsuitable for all types of projects (e.g., small building projects)	Won et al. (2013), Lam et al. (2017)	Post-adoption barrier
17	Reduced working efficiency during the change process	Becerik-Gerber and Kensek (2010)	Post-adoption barrier
18	Difficulties in learning and using BIM (lack of ease of use)	Eadie et al. (2013)	Post-adoption barrier
19	Increased workload	T. Tan et al. (2019)	Post-adoption barrier
20	User resistance (Attachment to conventional methods, e.g., 2D drafting or paper drawings)	Hasan, Ahn, Rameezdeen, et al. (2021)	Post-adoption barrier
21	Client’s lack of understanding of BIM	Doan et al. (2021)	Both
22	Low adoption across the supply chain	Won et al. (2013)	Both
23	Shortage of skills and expertise	Zhang et al. (2018)	Both
24	Lack of BIM benefits evaluation	Hosseini et al. (2018)	Both
25	Cost and time associated with employee training and upskilling	Ogunmakinde and Umeh (2018), Babatunde et al. (2020)	Both
26	Interoperability concerns (Integration of BIM with the existing software)	Chan et al. (2019)	Both
27	Data security concerns	Hasan, Ahn, Rameezdeen, et al. (2021)	Both
28	Lack of standards and comprehensive framework for BIM implementation	Alemayehu et al. (2022)	Both
29	Complicated change process	Chien et al. (2014)	Both
30	Lack of market support for BIM implementation	Gerges et al. (2017), Doan et al. (2021)	Both
31	Poor internet connectivity	Abubakar et al. (2014)	Both
32	Lack of top management support	Eastman et al. (2011), Won et al. (2013)	Both

Table 1 shows that different studies have captured various impediments to BIM adoption and use in different contexts. However, most studies either focus on the pre- or post-adoption barriers. Thus, a holistic picture of barriers to adoption and post-adoption usage of BIM remains to be developed to help construction organizations and the industry not just overcome the initial hurdles but also plan for ongoing issues to maximize the use of BIM and returns on their investment.

Research methodology

Questionnaire design and pilot study

32 BIM implementation barriers obtained from the literature (Table 1) were classified under pre- and post-adoption barriers based on discussions with two academic experts with an average of 10 years of experience. Subsequently, four project managers from client and contractor organizations with an average of five years of experience in BIM implementation in the Indian construction industry were consulted to ensure that the identified list of barriers was exhaustive and their classification into the pre- and post-adoption stages of BIM implementation was correct. The experts suggested that few barriers are relevant to both pre- and post-adoption stages, as shown in Table 1 (last column). Finally, the discussions with the academic and industry experts identified 23 pre- and 21 post-adoption barriers to BIM implementation. The two-step process (literature review and subsequent discussion with experts) established the questionnaire items’ content (or face) validity. Two questionnaires were designed to evaluate various pre- and post-adoption barriers to BIM implementation in the Indian construction industry. The questionnaire based on pre-adoption barriers was distributed to construction professionals working in organizations that had not adopted BIM but were considering implementing BIM. At the same time, the questionnaire based on post-adoption barriers was distributed to construction professionals working in organizations that already had implemented BIM and were using it at the time of data collection.

Pilot surveys could help elicit reliable and valid responses as they check the potential participants’ ability to understand the questions and their willingness to respond (Peterson, 2013). Moreover, they can help researchers identify problems in the questions and the questionnaire (Rowley, 2014). Therefore, a separate group of six construction professionals were selected for the pilot survey using convenience sampling. The pilot survey helped make minor changes in the language, layout, and presentation of the self-administered questionnaires to improve their quality and interpretation. The questionnaires were designed to collect ratings on a five-point Likert scale (strongly disagree = 1, disagree = 2, neutral = 3, agree = 4 and strongly agree = 5) on each barrier to BIM implementation.

Sampling and questionnaire administration

The sample selection was based on non-probability purposive sampling. No publicly available database or directory has contact details of all construction professionals working in the Indian construction industry or construction organizations using BIM or looking to adopt BIM to enable the selection of a random sample. Purposive sampling is frequently used in construction management research (Fellows & Liu, 2008; Abowitz & Toole, 2009; Gounder et al., 2023). Previous studies suggest that a relatively large number of respondents from different organizations could increase confidence in the general reliability of the data. Consequently, a minimum sample size of over 100 is recommended for robust research and significant findings (Fellows and Liu, 2008; Abowitz & Toole, 2009; Rowley, 2014).

Respondents were identified through the snowball sampling technique based on referrals from initial respondents to generate additional respondents. The respondents were contacted via e-mail and messaging on LinkedIn, and self-administered questionnaires were distributed using a Google form link.

Data analysis

Of 400 questionnaire invitations, 218 completed survey responses from construction professionals working in 125 construction organizations were received after three months of follow-up at a response rate of 54.5%. Of 125 organizations, 72 were using BIM (adopters). Of 218 participants, 125 were from adopter organizations, and the remaining 93 were from non-adopter organizations. Except for 17, all participants held a graduate or postgraduate qualification. The survey participants represented a good mix of respondents from client, contractor and consultant organizations. Table 2 shows the details of the survey participants.

Table 2. Survey participant details

Characteristic	Categories	Number	Percentage of total number (n),(in %)
Organization’s BIM implementation status (n = 125)	Adopters	72	57.6
	Non-Adopters	53	42.4
Adopter organization’s BIM usage duration (in years) (n = 72)	>10	21	29.2
	5–10	30	41.6
	<5	21	29.2
Type of organization (n = 125)	Client	33	26.4
	Contractor	40	32.0
	Consultant	52	41.6
Number of participants (n = 218)	Adopters	125	57.3
	Non-Adopters	93	42.7
Participants’ industry experience (in years) (n = 218)	>20	19	8.7
	16–20	15	6.9
	11–15	18	8.2
	5–10	83	38.1
	<5	83	38.1
Number of participants from each organization type (n = 218)	Client	61	28.0
	Contractor	71	32.6
	Consultant	86	39.4

From the five-point Likert scale used in the questionnaire, barriers to BIM implementation were ranked according to their Relative Importance Index (RII) using the following formula (Jarkas & Bitar, 2012).

(1) $\mathrm{RII}=\mathit{\hspace{0.17em}}\frac{\mathrm{\Sigma }\mathit{w}}{\left(\mathrm{A}\ast \mathrm{N}\right)}$(1)

In Equation (1)(1) $\mathrm{RII}=\mathit{\hspace{0.17em}}\frac{\mathrm{\Sigma }\mathit{w}}{\left(\mathrm{A}\ast \mathrm{N}\right)}$(1) , w represents weights (1–5) assigned to each barrier by the participants; A represents the highest weight (in this case, 5); and N is the total number of participants. The barrier with the highest RII value was ranked as the most critical barrier, and the barrier with the second highest RII value was ranked as the next most critical barrier and so on. If two or more barriers had the same RII values, then the barrier with a lower standard deviation was ranked higher.

Furthermore, an independent samples t-test using SPSS version 29 (for Windows) was conducted at the significance level α = .05 to measure any significant differences among the means of responses of various groups. Stakeholders such as clients and contractors have different business objectives and, therefore, could have different perspectives on project outcomes and the processes and technologies used to achieve them (Hasan & Jha, 2019). They may primarily focus on self-interest and share different perceptions (Chalker & Loosemore, 2016). For instance, previous studies identify the client as the party receiving maximum benefits from BIM adoption (R. Jin, Hancock, et al., 2017). In comparison, contractors may focus more on maximizing their profit and minimizing disruption to their existing work processes (Xiao & Proverbs, 2002). Y. Tan et al. (2017) highlighted that the innovation ability of subcontractors is the weakest. According to S. Wu et al. (2014), architects and designers are ahead of contractors in BIM adoption. Architects and service engineers possess the highest level of expertise compared to the rest of the stakeholders, and structural engineers were identified as stakeholders with the frequent use of BIM levels (Eadie et al., 2015).

In short, different stakeholders may have different perceptions concerning the barriers to BIM adoption and use due to differences in their BIM usage patterns and competencies. Therefore, the survey participants for the independent samples t-test were classified into three groups: client, contractor and consultants. The following null and alternate hypotheses for the independent samples t-test were stated.

H₀:

There is no significant difference between the group means based on perceptions of different respondent group samples concerning the severity of a barrier (i.e., µ₁=µ₂).

H₁:

There is a significant difference between the group means based on perceptions of different respondent group samples concerning the severity of a barrier (i.e., µ₁≠µ₂).

The null hypothesis is rejected if the p-value is equal to or less than .05, indicating that the difference between the means of different groups is statistically significant.

Findings

Pre-adoption barriers to BIM implementation

Table 3 shows the ranking of 23 pre-adoption barriers to BIM implementation in construction organizations. The top five barriers associated with BIM implementation during the pre-adoption stage are high costs of hardware (RII = .752), high costs of software (RII = .748), low adoption across the supply chain (RII = .748), low market support (RII = .736), and unclear benefit evaluation (RII = .730). These top five perceived pre-implementation barriers imply that cost consideration, low adoption across the supply chain and lack of a strong business case lead to a non-adoption decision or delay in BIM adoption in the construction industry in developing countries such as India.

Table 3. Ranking and independent t-test results - pre-adoption barriers

Rank	Pre-adoption barriers	RII	Standard deviation	Independent t-test results at significance level .05, p-value
				Client-Contractor	Contractor-Consultant	Consultant-Client
1	High costs of hardware required for BIM adoption	0.752	1.127	0.573	0.218	0.410
2	High costs of software required for BIM adoption	0.748	1.083	0.120	0.056	0.513
3	Low adoption across the supply chain	0.748	1.188	0.278	0.179	0.688
4	Lack of market support for BIM implementation	0.736	1.190	0.253	0.998	0.256
5	Lack of BIM benefits evaluation	0.730	1.129	0.249	0.682	0.433
6	Lack of top management support	0.726	1.178	0.092	0.619	0.216
7	Cost and time associated with employee training and upskilling	0.722	1.133	0.022*	0.091	0.808
8	Contractor’s lack of understanding of BIM	0.714	1.228	0.523	0.655	0.879
9	Resource-intensive implementation process	0.710	0.927	0.171	0.888	0.238
10	Risks and liabilities associated with BIM implementation	0.710	1.006	0.749	0.645	0.851
11	Shortage of skills and expertise	0.710	1.184	0.655	0.416	0.638
12	Interoperability concerns (Integration of BIM with the existing software)	0.704	0.985	0.267	0.883	0.208
13	Lack of standards and comprehensive framework for BIM implementation	0.704	1.167	0.139	0.369	0.682
14	Client’s lack of understanding of BIM	0.704	1.230	0.050*	0.417	0.210
15	Complicated change process	0.698	1.059	0.010*	0.353	0.125
16	Lack of government policies and incentives	0.696	1.203	0.338	0.525	0.819
17	Adequacy of the existing CAD/software systems (i.e., BIM is not needed)	0.692	1.048	0.190	0.507	0.575
18	Data ownership issues	0.688	1.058	0.413	0.200	0.013*
19	Complicated and time-consuming BIM processes	0.682	1.055	0.114	0.315	0.683
20	Business disruption due to changes in the existing processes	0.666	1.067	0.208	0.945	0.235
21	Data security concerns	0.666	1.210	0.632	0.357	0.574
22	Poor internet connectivity	0.658	1.290	0.059	0.627	0.111
23	Chances of contractual disputes	0.650	1.080	0.995	0.271	0.155

*Mean difference significant at the .05 level.

The study shows that the significant financial investment required for BIM implementation is the main barrier to BIM adoption due to the limited financial capacity of many Indian construction organizations to invest in costly technology adoption. BIM implementation typically requires new software and new or upgraded hardware to run the large software files (Eastman et al., 2011). Such extra cost may impede an organization’s decision to adopt BIM (Love et al., 2013). The capital required for procuring BIM software and hardware or equipment could be significant for construction organizations in developing countries. Dainty et al. (2017) also suggested that BIM uptake can be problematic for firms without the capacity to invest in technology.

Furthermore, the study shows that low adoption across the supply chain and lack of market support discourage construction organizations from adopting BIM. The benefits of BIM adoption cannot be fully realized without the involvement of relevant stakeholders. While large contractors possess BIM expertise and in-house resources necessary for BIM adoption, the technical and financial capabilities of suppliers and subcontractors could vary significantly due to various constraints, interoperability issues between BIM software and lack of expertise (Y. Wang et al., 2017). Finally, the study shows that it is crucial to present a strong business case justifying the investment to generate interest in BIM adoption across the supply chain. Although BIM offers several benefits, measuring project-level financial gains and identifying tangible outcomes from BIM implementation is challenging. Most BIM benefits are soft or intangible and difficult to measure or quantify (Y. Wang et al., 2017).

The p-values higher than .05 for each pre-adoption barrier among contractors and consultants suggest no significant difference between the group means based on their perceptions concerning the severity of a barrier. However, clients and consultants significantly differed in their perception of data ownership issues (p-value = .013). In inter-party BIM use, data ownership issues may arise at the end of the project due to concerns related to intellectual property rights and consultancy agreements. Previous studies also found that architects and consultants showed concern about protecting what they considered to be the intellectual property component of the BIM model and feared that their original model might be repurposed or reused (Arensman & Ozbek, 2012). Client and contractor had significantly different views on three pre-adoption barriers: the high cost of staff training and upskilling, the client’s lack of understanding of BIM and the complicated change process with p-values of .022, .050 and .010, respectively. The participants from the client organization had higher group means for these three barriers. A plausible explanation is that clients, especially public sector clients, usually have more complicated change management processes than contractors. Similarly, the lack of existing BIM expertise and awareness in client organizations could be the reason for more weightage attached to the importance of lack of knowledge and training cost barriers.

Post-adoption barriers to BIM implementation

Table 4 shows the ranking of 21 post-adoption barriers to BIM implementation in construction organizations. The top five barriers are the high ongoing cost (license renewal, training cost, etc.) (RII = .772), skill shortages (RII = .760), unclear benefit evaluation (RII = .754), client’s lack of understanding (RII = .744), and user resistance (RII = .742). In addition, it can be observed that unclear benefit evaluation continues to affect BIM implementation. It received a higher ranking in the post-adoption phase than the pre-adoption phase, as organizations questioned their return on investment in BIM after its implementation.

Table 4. Ranking and independent t-test results - post-adoption barriers

Rank	Post-adoption barriers	RII	Standard deviation	Independent t-test results at significance level .05, p-value
				Client-Contractor	Contractor-Consultant	Consultant-Client
1	Ongoing high cost of implementation (license renewal, training cost, etc.)	0.772	1.003	0.332	0.020*	0.303
2	Shortage of skills and expertise	0.760	1.078	0.245	0.563	0.510
3	Lack of BIM benefits evaluation	0.754	1.033	0.864	0.195	0.382
4	Client’s lack of understanding of BIM	0.744	1.126	0.696	0.526	0.874
5	User resistance (Attachment to conventional methods, e.g. 2D drafting or paper drawings)	0.742	1.054	0.385	0.489	0.205
6	Lack of standards and comprehensive framework for BIM implementation	0.740	1.041	0.375	0.953	0.378
7	Variations in client’s demand	0.736	1.013	0.669	0.984	0.677
8	Cost and time associated with employee training and upskilling	0.736	1.082	0.149	0.279	0.605
9	Interoperability concerns (Integration of BIM with the existing software)	0.732	1.031	0.833	0.791	0.654
10	Communication issues with other project participants/supply chain partners	0.728	1.027	0.244	0.087	0.020*
11	Contract conditions concerning the use of BIM	0.726	1.059	0.801	0.351	0.278
12	Low adoption across the supply chain	0.724	1.053	0.338	0.567	0.679
13	Reduced working efficiency during the change process	0.718	0.985	0.693	0.483	0.868
14	Lack of market support for BIM implementation	0.716	1.144	0.983	0.462	0.554
15	Complicated change process	0.694	1.111	0.540	0.727	0.705
16	Lack of top management support	0.682	1.158	0.532	0.976	0.488
17	Unsuitable for all types of projects (e.g. small building projects)	0.680	1.314	0.192	0.488	0.035*
18	Increased workload	0.676	1.141	0.530	0.484	0.173
19	Difficulties in learning and using BIM (lack of ease of use)	0.668	1.151	0.348	0.750	0.425
20	Data security concerns	0.652	1.239	0.877	0.975	0.844
21	Poor internet connectivity	0.648	1.208	0.758	0.722	0.532

*Mean difference significant at the .05 level.

The ongoing high cost of implementation was identified as the most significant post-adoption barrier to BIM implementation. Ongoing costs associated with BIM implementation include license renewal costs, software upgrading costs, ongoing maintenance fees and staff training expenses. Furthermore, there are additional costs of employing a BIM technician over a CAD technician and other BIM-specialized roles. Training and education in BIM are fundamental to the successful implementation of BIM. Therefore, expenses incurred in training staff in BIM competency can also be very high. Moreover, the “downtime” ensuing from individual and organizational learning results in significant costs to organizations implementing BIM (Rogers et al., 2015). Furthermore, the cost of acquiring and maintaining an up-to-date IT infrastructure is a bottleneck to BIM implementation (Rogers et al., 2015).

The respondents placed shortage of skills and expertise in the second position (Table 4). Staff’s BIM capability refers to the existing staff’s capability in operating and maintaining BIM tools and models. A lack of experienced technicians in using BIM tools has also been highlighted in previous studies as one of the main barriers to BIM adoption (Gilligan & Kunz, 2007). Seaden et al. (2003) pointed out that smaller construction organizations are generally less likely to hire experienced employees compared to larger organizations. The lack of appropriately trained staff, rather than the technology itself, is an ongoing issue for most organizations (Eastman et al., 2011; Ademci & Gundes, 2018). Similarly, the present study found that clients’ insufficient understanding of BIM benefits and limited technical knowledge affect post-adoption BIM usage in construction projects. Clients play a significant role in deciding which technology will be used in a project and for what purposes. Therefore, the lack of client knowledge concerning BIM is among the key barriers to the continued use of BIM in various projects. Finally, user resistance was placed in the fifth position by the respondents as staff may continue entrenching themselves in the traditional CAD approach or paper drawings due to their poor BIM skills or psychological resistance to change. The cultural shift of modifying the conventional or standard processes presents significant challenges (Hasan, Ahn, Baroudi, et al., 2021).

All the p values higher than .05 for each item among client and contractor groups suggested that their perceptions toward post-adoption barriers to BIM implementation did not differ significantly. However, contractors and consultants seemed to differ in their perception of high ongoing cost as a post-adoption barrier to BIM implementation, with a p-value of .020. Consultants gave more weight to the high ongoing cost associated with BIM as they might be using BIM more regularly than contractors, whose usage might be limited to specific projects only. Also, consultants and clients had significantly different views on the post-adoption barriers: communication issues with other project participants and supply chain partners and BIM’s suitability for all types of projects with p-values of .020 and .035, respectively. Consultants considered these barriers more important than clients, which could possibly be related to the higher usage of BIM in design and engineering consultancies than client organizations in the Indian construction industry.

Discussion and implications

BIM implementation is an effort-intensive and expensive process for construction organizations, especially in developing countries. Therefore, understanding the factors affecting its post-adoption usage in addition to its adoption is necessary to ensure the long-term success of BIM implementation and associated productivity gains. Moreover, a holistic understanding of pre- and post-adoption barriers could help potential BIM adopters work toward addressing post-adoption barriers or challenges they are likely to encounter after adoption.

The study found that cost considerations are a critical barrier during the pre- and post-adoption stages. BIM implementation is not limited to one time-off investment for construction organizations but may incur substantial ongoing costs. These findings contradict Rogers et al. (2015), who found that hardware and software costs were not major barriers to BIM adoption. However, it supports the results of Hall et al. (2023) that the high cost of acquiring the software and licensing required to use BIM is a significant barrier. In many countries, such as India, most construction organizations are small and medium-sized enterprises (SMEs) with limited financial capacity to invest in new technologies. Gajendran and Perera (2017) found that SMEs are generally cost-conscious regarding investments in new technologies. Previous studies also show that BIM implementation in SMEs is challenging due to a lack of in-house skills and high implementation expenses (Hong et al., 2019; Vidalakis et al., 2020). Consequently, reducing the implementation cost would be crucial to increase BIM adoption in developing countries. Furthermore, organizations must consider the costs associated with the continued BIM usage and the whole implementation process rather than just initial investment in its adoption.

The study also found that a perceived lack of understanding of BIM benefits or unclear evaluation affects BIM adoption and usage decisions. The results show that construction organizations are skeptical about the tangible benefits of BIM implementation, though various BIM benefits are documented in the literature. Yang and Chou (2019) also argued that many benefits of BIM are generally anticipated rather than tangible in the absence of an appropriate and easy-to-use benefit evaluation model, especially for immature BIM-enabled stakeholders. At the same time, previous studies found that developing a standard calculation methodology or framework to quantify the benefits of BIM adoption could be challenging due to variations in project scopes, BIM applications and stakeholders (Barlish & Sullivan, 2012). Therefore, developing standard calculation methodologies or frameworks that can be applied to different contexts is crucial for increasing BIM adoption and usage. For construction markets that are yet to achieve the mature stage of BIM adoption, it is suggested that business cases on cost-benefit analysis covering various construction projects, BIM applications and stakeholders should be conducted to evaluate the implications of BIM for projects and organizations and justify the investments required in pre- and post-adoption phases of BIM implementation.

The study also found that while low adoption across the supply chain and lack of market support affect the pre-adoption decision, the client’s lack of knowledge, skill shortage and user resistance affect post-adoption usage of BIM. Therefore, the clients and supply chain partners in developing countries can play an important role in driving the adoption and use of BIM in construction projects. The lack of market demand has been recognized as the key impediment to BIM adoption (Doan et al., 2021). If a client mandates the use of BIM in a project, other project participants use it due to the influence of the client’s decision or contractual conditions of BIM use (Hetemi et al., 2020). Previous studies on BIM implementation also suggest that incentives from the government could accelerate BIM adoption and diffusion (Marzouk et al., 2022). Unfortunately, there has not been a push from the government in developing countries such as India, Egypt and Nigeria to mandate BIM in public projects (Marzouk et al., 2022; Olanrewaju et al., 2020).

However, some developing countries and Latin American countries, such as Brazil, Chile, Mexico, and Peru, have endorsed using BIM in public projects (Machado et al., 2020). Moreover, government policies and strategies have played an essential role in driving BIM adoption in the AEC industry of developed countries such as Denmark, Finland, the United Kingdom and the United States (Chan et al., 2019; Lee et al., 2014). For instance, the Finnish government developed a clear vision for BIM implementation at governmental and operational levels (Wong et al., 2010). Norway has an active research community and governmental building authorities focusing on national BIM development (Silva et al., 2016). Policies and strategies that have successfully driven the industry to adopt and use BIM in some countries can be adopted in developing countries such as India, where BIM adoption is low.

The study also found the differences in the ranking or relative importance of barriers common during the pre-and post-adoption phases of BIM implementation. For instance, lack of market support is perceived as one of the top five pre-adoption barriers to BIM implementation (Table 3). In contrast, it is not perceived as an equally high-ranked post-adoption barrier, as indicated by its 14th ranking (Table 4). It could be because the organizations that have already adopted BIM responded to the market demand for BIM implementation or are using BIM in projects. In contrast, non-adopters are still looking for favorable market conditions to initiate BIM adoption. The findings also show that the unavailability of industry-approved BIM standards and a comprehensive framework becomes a more important barrier during the post-adoption stage as organizations struggle to implement BIM.

Furthermore, BIM adopters perceive the client’s lack of understanding of BIM as one of the significant barriers (4th rank) during the post-adoption phase. Conversely, it is not perceived as a strong barrier by potential adopters during the pre-adoption stage, as evidenced by the 14th rank (Table 3). Similarly, lack of management support ranked higher as a pre-adoption barrier than a post-adoption barrier. It can be argued that the initial BIM adoption decision requires approval and higher support from the top management. However, in the post-adoption phase, most employees become familiar with the technology and changes in the work processes and, therefore, may require less support from the management. Nonetheless, management support remains relevant for successful BIM implementation in both pre- and post-adoption phases. The findings support studies that suggest management support is critical for successful BIM implementation (Gu & London, 2010).

While potential adopters perceived a lack of skilled staff as not a very critical barrier during the pre-adoption stage, as shown by the 11th ranking of this factor (Table 3), BIM adopters considered it as one of the top five post-adoption barriers (Table 4). It indicates that the actual shortage of skilled BIM professionals could be more acute than the perceived shortage, and BIM adopters find it challenging to recruit skilled staff. Competent BIM talent is in high demand globally on both the technical and managerial levels (Abdirad & Dossick, 2016). Still, very few universities and technical institutes in India offer training programs and courses on BIM, though their numbers are slowly increasing. Moreover, previous studies have found that current BIM curricula do not cover the needs of the AEC industry. Elias et al. (2023) found that continuous collaboration and partnership with the industry are crucial for educational institutions to graduate BIM-ready professionals. BIM education should teach students how to extract information effectively from building models, implement BIM in projects and organizations, and collaborate with others (Huang, 2018). Moreover, students must be equipped with the latest BIM skills required by the AEC industry (Wang et al., 2020). Shojaei et al. (2023) discuss construction companies’ strategies to tackle BIM skill shortages in the UK construction industry. They suggest that organizational focus on upskilling their employees and training supplier network partners using in-house and tailored training is crucial for successful BIM implementation.

Additionally, other stakeholders such as professional groups, training providers and educational institutions can work with the government and the industry to help bridge the skill gaps in successful BIM implementation. Malaysia has a National BIM library and a government mandate to transition to construction 4.0. The Malaysian government has collaborated with the research center (MyBIM) to facilitate training and consultation for AEC industry players through seminars and workshops (Ibrahim et al., 2021). Similarly, many enablers of BIM innovation in China are driven by government institutions. For instance, the Shanghai Municipal People’s Government issued the strategic objectives for BIM implementation. Furthermore, the China State Council issued prefabricated design codes, technical standards, and construction methods (R. Jin, C. M. Hancock, et al., 2017). Charef et al. (2019) discuss several initiatives, mainly from Europe, implemented in the last few years to foster BIM adoption. Some examples are national programs to facilitate BIM adoption, an international BIM implementation guide, a BIM handbook, standards and guidelines, a BIM training tool, educational institutions’ curriculum changes and BIM training programs.

Therefore, BIM education in college curricula, training centers by the government and professional bodies, updated course material to meet the industry needs and practices, BIM implementation guide, standards, frameworks and tools, in-house BIM training for employees and supply chain partners, and collaboration with foreign institutes and organizations to implement the best practices are some of the initiatives that can be taken in developing countries such as India to address the skill and competency gaps in BIM implementation. Moreover, lessons learned in BIM from different countries should be incorporated into BIM training and educational courses to inform practitioners about best BIM implementation and usage practices (Georgiadou, 2019). For instance, Mostafa et al. (2020) offered practical insights into using BIM for prefabrication in the housing sector.

Surprisingly, the present study found that data security concerns are perceived as less critical barriers during the pre- and post-adoption stages. This finding contradicts Hasan, Ahn, Rameezdeen, et al. (2021), who reported that data security matters associated with using information and communication technologies are significant concerns among construction organizations in Australia. Moreover, although considered the most significant BIM adoption barrier for SMEs in New Zealand (Hall et al., 2023), interoperability concerns were not perceived as a severe barrier during the pre- and post-adoption stages of BIM implementation in the Indian construction industry. Similarly, the findings contradict Chien et al. (2014), who found complicated change processes to be one of the significant barriers to BIM adoption. In contrast, this barrier was ranked 15th during both the pre- and post-adoption stages. Furthermore, the finding of this study contradicts Lam et al. (2017), who found the unsuitability of BIM for all types of projects to be a significant barrier to BIM adoption. The present study shows that BIM adopters do not perceive it as a very important post-adoption barrier, as indicated by the 17th ranking of this factor (Table 4). The low level of BIM maturity could explain these contradictions, as BIM adoption and use is still at an infant stage in the Indian construction industry. The data security, usability and process change concerns may become more important as construction organizations in India advance their BIM maturity by integrating BIM with other software or systems and using it more extensively during the project lifecycle and facility management.

Though the data was collected from the Indian construction industry, findings from this empirical study can be interpreted and applied by construction organizations from other countries, especially countries with similar working environments, BIM maturity and other socio-economic conditions. Moreover, the study’s findings are expected to be useful for policymakers, government departments, construction organizations, and other stakeholders in their quest to increase the current uptake of BIM in the construction industry. The study recommends that organizations take a holistic approach to BIM implementation, as overcoming pre-adoption barriers would not necessarily translate into successful BIM usage due to several post-adoption barriers. It is not that construction organizations will only face challenges while adopting BIM; several challenges concerning successful BIM implementation exist in the post-adoption phase. Therefore, a comprehensive understanding of the factors affecting BIM implementation is critical for its successful adoption and use.

Conclusion

The present study evaluated BIM implementation barriers construction organizations face in the pre- and post-adoption phases in the Indian construction industry. It identified and ranked 23 pre-adoption and 21 post-adoption barriers affecting BIM implementation in construction organizations. The top five barriers associated with BIM implementation in construction organizations during the pre-adoption stage were high hardware costs, high software costs, low adoption across the supply chain, low market support, and unclear benefit evaluation. Conversely, the top five significant barriers during the post-adoption phase were high ongoing costs, shortage of skills and expertise, unclear benefit evaluation, client’s lack of understanding, and user resistance. The findings show that organizations continue to face several barriers after initial BIM adoption that may prevent them from realizing the full benefits of BIM implementation.

The independent t-test results indicate that clients, contractors, and consultants had similar perceptions of pre- and post-adoption barriers except for significant differences between the group means concerning a few barriers, as indicated by p-values. The findings could help organizations develop a holistic understanding of the initial and ongoing barriers to BIM implementation and enable them to identify measures to overcome these barriers. As discussed in the previous section, many barriers identified in the study would require a collaborative effort from all stakeholders, including government and education institutions. The study also offers important practical implications for organizations planning to implement BIM in the future, as ongoing cost, and a lack of BIM expertise, client understanding, and suitable frameworks and guidelines could prevent them from realizing the full potential and benefits of BIM in the post-adoption phase.

However, the findings must be considered within the study’s limitations. Construction organizations that participated in the survey used BIM mainly in building projects. A similar study can be performed for construction organizations that use BIM in infrastructure projects such as road and railway projects and facility management. The inclusion of multiple respondents from some organizations, although working on different projects, is another limitation because of the potential for competing information and potential biases. Due to the use of self-administered questionnaires to collect the data, the findings are based on participants’ perceptions. More detailed investigations using the case study method could provide deeper insights into the barriers and their root causes. Also, future studies could analyze the reasons behind similarities and differences in the perceptions concerning some of the barriers influencing BIM implementation in more detail. Finally, this empirical research was conducted in the Indian construction industry; therefore, the findings may not directly apply to other regions. However, despite these limitations, the study enriches our understanding of the perceptions of BIM adopters and non-adopters, as well as different project stakeholders, concerning pre- and post-adoption barriers to BIM implementation in construction organizations.

Disclosure statement

No potential conflict of interest was reported by the author(s).