Exploring Behavioral Mechanisms of BIM Outsourcing in Construction Enterprises: A TPB-Based Empirical Study from China

Abstract

Building Information Modeling (BIM) is an innovative and effective solution to transform the Architecture, Engineering, and Construction (AEC) sector, offering advantages that extend across the entire lifecycle of project management. Nonetheless, several obstacles hinder the comprehensive implementation of BIM. As a result of these obstacles, construction enterprises opt to delegate the development and utilization of BIM models to specialized outsourcing providers that focus on BIM services. Since limited research focused on examining the formation mechanisms behind BIM outsourcing process, this paper elucidates the mechanisms that underpin BIM outsourcing behavior by applying Ajzen’s theory of planned behavior (TPB) and integrating transition costs along with institutional pressures theory. The behavioral model underwent empirical validation through the application of partial least squares structural equation modeling (PLS-SEM) on survey data collected from construction engineers working for construction enterprises in China. The results indicated that (1) BIM outsourcing degree is motivated by an organization’s BIM outsourcing intention and BIM application capability; (2) behavioral attitudes, especially external production cost advantage, contributes the most toward achieving a high BIM outsourcing intention, followed by normative pressures; (3) transition cost contributes the most toward achieving a low BIM outsourcing intention. This research expands the theoretical framework of the TPB and provides insight into BIM outsourcing behavior in construction enterprises.

1. Introduction

BIM is a widely used digital technology within construction enterprises [1]. It has demonstrated significant effectiveness in lean project management, including better visualization, reduced project costs, and enhanced collaboration among project stakeholders, improving the efficiency in lifecycle project management [2,3]. Due to these benefits, many construction enterprises have realized that in order to maintain industry competitiveness, it is necessary to implement BIM throughout the project lifecycle to achieve benefits. The implementation of BIM is a critical determinant for organizations’ sustainability within the competitive marketplace. Consequently, a significant number of construction enterprises have begun to establish their own BIM professional teams to accelerate BIM adoption. However, BIM adoption has its own barriers, including higher investment at the initial stages of implementation, unexpected return on investment, and behavioral resistance [4,5,6,7]. These challenges are impeding holistic BIM adoption among construction enterprises.

Given the various advantages and challenges linked to comprehensive BIM adoption, construction firms have investigated diverse BIM implementation strategies to address their specific needs. Within different BIM implementation strategies, BIM outsourcing has been proven as an effective strategy. Transaction cost theory indicates enterprises should focus on their core competencies to achieve more business objectives with minimal resource consumption [8]. Construction enterprises possess distinct identities and primary objectives, which may lead them to allocate limited resources to the maintenance of in-house BIM professional teams responsible for executing all BIM-related functions. [9]. Meanwhile, two primary barriers—including significant investment in BIM software (e.g., Revit, Navisworks, Lumion) and infrastructures, as well as continuous efforts for skilled BIM professionals—prevent in-house BIM use [10]. Consequently, there is a growing demand for BIM outsourcing within the construction industry. Fountain and Langar [10] defined BIM outsourcing as “an organization outsource the creation and use of BIM models in a project to a third party specializing in BIM processes”. They suggested that BIM outsourcing can help enterprises save costs and leverage the resources and capabilities of BIM outsourcing vendors to relieve the in-house BIM use burdens. The survey revealed that 45% of general contractors in the United States have participated in BIM outsourcing. Hence, BIM outsourcing has emerged as a prevalent strategy in BIM implementation. The rationale behind the decision of construction firms to outsource BIM functions has garnered considerable interest from both scholarly research and industry practitioners.

The majority of existing research on BIM has predominantly concentrated on the adoption and dissemination of BIM technologies, which unfolds across three levels: organizational-level BIM diffusion [11], project-level BIM diffusion [12], and individual-level BIM diffusion [13]. Thus far, this body of empirical research has predominantly concentrated on elucidating the attitudes and behaviors associated with the implementation of BIM across various levels. [14]. Researchers have explored how technical, organizational, and individual factors influence the motivations and behaviors of construction engineers across different stages of BIM implementation [14]. The theory foundation of the previous literature primarily focused on Technology Acceptance Model (TAM), Expectation–Confirmation Model (ECM), Technology–Organization–Environment framework (TOE) and innovation diffusion theory, which has been proven to be effective in information technology (IT) adoption and diffusion [15,16,17,18]. Researchers deem that BIM implementation is based on BIM software and has certain similarities with IT adoption. It seems reasonable to draw on existing IT adoption theory. However, Cao et al. [19] has proven that compared to IT, BIM has its own uniqueness. BIM represents a multifaceted and systemic advancement; the adoption process frequently encompasses not only modifications to project procedures, substantial financial investments, and intangible benefits, but it may also exert significant social impact.

Due to BIM uniqueness, BIM outsourcing also has its own uniqueness compared to IT outsourcing. While previous IT outsourcing studies indicated that economic requirements played the key role in determining IT outsourcing, Chen et al. [9] has indicated that the decision-making process regarding BIM outsourcing is highly complex, necessitating the consideration of various economic, strategic, technical, and social factors. The justification for information technology outsourcing is grounded in the principles of economies of scale and scope, which provide immediate financial advantages to the organization that delegates certain tasks [20]. However, commercial exploitation is the key reason for BIM outsourcing. This involves the establishment of partnerships between the company and the BIM outsourcing firm, aimed at mitigating risks and distributing the associated benefits [19]. These relationships are characterized less by traditional buyer–seller dynamics associated with economies of scale and more by collaborative alliances that emphasize joint strategic initiatives. Therefore, BIM outsourcing tends to be more easily impacted by institutional pressures. In the construction sector, the practice of outsourcing BIM occurs concurrently with the execution of projects. Thus, BIM functions vary from stakeholder to stakeholder in construction projects, making more complexity in scope.

Previous studies have indicated BIM should not be simply treated as IT and discussed BIM outsourcing in IT outsourcing field. And they have presented motives of BIM outsourcing which included technical, business performance, and capability [20]. To further investigate BIM outsourcing in behavioral lens, Chen et al. constructed a model to assist contractors’ BIM outsourcing behavior, which included selective outsourcing, total outsourcing, and total insourcing [9]. Their model reveals that financial, customer, internal operations, company learning, and growth are the main factors for predicting BIM outsourcing behavior. Based on these prior studies, outsourcing BIM presents a complex alternative for construction firms seeking to adopt BIM methodologies. In the context of BIM outsourcing behavior, it is essential to investigate whether such outsourcing can yield both immediate financial gains and long-term competitive advantages, such as opportunities for commercial exploitation [21]. Meanwhile, it is essential for them to assess their internal experiences with BIM and to estimate the demand for BIM professionals resulting from outsourcing initiatives [20]. It is necessary to internally evaluate the risks associated with Building Information Modeling (BIM) utilization in comparison to those associated with outsourcing. Consequently, a variety of factors must be taken into account throughout the BIM outsourcing process. These factors cover not only the economic aspects but the strategic, technical, and social ones [22]. However, scant study is devoted to investigating factors influencing BIM outsourcing behavior in a more comprehensive perspective. Moreover, this deepen understanding toward BIM outsourcing behavior will aid in the formulation of more effective guidelines for the adoption of BIM [10]. There is a necessity to elucidate the mechanisms underlying the BIM outsourcing behavior of construction enterprises and to analysis the interactions among the associated variables. Nevertheless, there has been a paucity of research focused on investigating BIM outsourcing through the lens of behavioral aspects and the mechanisms underlying their formation. This represents a significant gap in the current body of research that warrants further investigation.

In this study, BIM outsourcing behavior was conceptualized as BIM outsourcing degree. In TPB, attitude, subject norms, and perceived behavioral control are determinants of intention and behavior. TPB has gained significant recognition as a comprehensive and effective framework for elucidating human intentions and behaviors [22]. Moreover, BIM outsourcing behavior is likely to be influenced not only by strategic motivations and beliefs but also by BIM capability, TPB can provide a more comprehensive perspective for this. Thus, TPB was deemed the most appropriate theoretical framework for this research.

In order to fill these gaps, the objective of this paper was to elucidate the behavioral rationale underlying the BIM outsourcing behavior of construction enterprises. The primary aim of this paper was to investigate the effects of various motivators and influencing pathways that drive BIM outsourcing behavior within construction enterprises. In order to accomplish their goal, the authors initially conducted a comprehensive review of the pertinent literature concerning the outsourcing of BIM. Drawing on the TPB, a theoretical model was then proposed, combined with TCT and institutional theory, and seven hypotheses were examined to reveal the motivators of BIM outsourcing behavior. This paper assessed the proposed model utilizing data gathered from construction engineers within construction enterprises in China. The findings of the analysis are thoroughly presented and examined in the Discussion and Conclusion sections of this paper, respectively. This paper extends the explanatory context of TPB, as well as providing insight into BIM outsourcing behavior in construction enterprises.

2. Literature Review and Hypothesis Development

2.1. Literature Review

2.1.1. BIM Outsourcing

The practice of outsourcing IT functions is prevalent across various industries and is not limited to the construction sector. Transaction cost theory (TCT) and resource-based view (RBV) are the two leading examples to explain the decision of IT outsourcing. TCT suggests that organizations pursue cost reductions and financial advantages through the practice of information technology outsourcing. The primary motivations for information technology outsourcing are the realization of economies of scale and the attainment of immediate financial advantages [9]. Besides these economic benefits, outsourcing can also bring strategic outcomes. From the perspective of RBV, commercial exploitation has been found as a primary strategy for IT outsourcing. Organizations can obtain competitive advantages through outsourcing by integrating the resources and technologies from the service companies. Meanwhile, the collaborative network stemming from outsourcing can also reduce risks.

BIM outsourcing has become the main way for contractors to apply BIM technology. Based on the transaction cost theory and the resource-based view, whether for cost–benefit considerations or resource strategy reasons, BIM outsourcing will become the main choice for contractors [9]. BIM outsourcing enables contractors to benefit from advanced technical knowledge in a relatively short period of time [20]. By providing the latest BIM tools and technologies from external suppliers and integrating them with information technologies such as VR, RFID, and GIS [23], they empower contractors to solve BIM-related issues in the short term [21]. Additionally, contractors face various obstacles in adopting and implementing BIM. The high initial costs of software, hardware, and training have significantly increased the uncertainty of cost-effectiveness [24]. By reducing the initial BIM investment such as in BIM infrastructure and team building investment [10], immediate financial benefits can be enjoyed merely through BIM outsourcing. At the same time, BIM outsourcing can also share the “uncertain risk of cost-effectiveness” mentioned earlier with the outsourcing supplier [25]. It is especially attractive to small- and medium-sized enterprises.

Research has demonstrated that BIM outsourcing behavior can be accurately anticipated through various motivators identified within the TPB framework, such as attitude toward BIM outsourcing [10], BIM capability [9], as well as short- and long-term benefit attitudes [10]. In recent years, the TPB has been employed as a robust framework for understanding IT outsourcing behavior [26,27]. Drawing upon the findings of these studies, the TPB has been chosen as the foundational framework for this research, aimed at examining the psychological factors that influence the outsourcing behavior of BIM within construction enterprises.

2.1.2. Theory of Planned Behavior

The theory of planned behavior (TPB) fundamentally serves as a comprehensive framework reflecting social psychological principles, widely employed to explain human intentions and predict behaviors, particularly at the individual decision-making level. This theoretical framework incorporates the concept of perceived behavioral control alongside the Theory of Reasoned Action [28], proposing that behavioral intentions, which directly drive behavior enactment, are influenced by three core factors: attitude (AT), subjective norms (SNs), and perceived behavioral control (PBC) [29]. Attitude denotes an individual’s positive or negative evaluation of engaging in a specific behavior [30]. This dimension captures both emotional sentiments and cognitive rationales an individual associates with a particular action [31]. For example, it assesses whether an individual views a behavior, such as purchasing prefabricated housing, as positive, valuable, or beneficial [31]. Subjective norms reflect an individual’s perception of social pressures from significant others or institutions to perform a behavior. Perceived behavioral control refers to an individual’s assessment of the ease or difficulty associated with performing a particular behavior, along with their confidence in their own abilities and the availability of necessary resources and is closely linked to self-efficacy as described in Social Cognitive Theory [32]. Norisnita and Indriati observed that self-efficacy often serves as a proxy for perceived behavioral control [33], encapsulating an individual’s belief in their capacity to accomplish tasks. In Zheng’s paper [34], PBC was conceptualized as relational competence, encompassing knowledge, ability, and control in fostering interorganizational relationships.

In recent years, TPB has been extensively applied across interdisciplinary research. For instance, Rich et al. [35] conducted a meta-analysis, robustly demonstrating TPB’s predictive validity for treatment adherence among chronic disease patients. Vafaei-Zadeh et al. [36] extended the TPB model to investigate purchase intentions for hybrid vehicles. The theory has also been utilized in diverse contexts, such as citizens’ travel choices during pandemics [37], credit usage in rural areas [38], prediction of green product consumption and purchase intentions [39], and patients’ medication use intentions [40]. Although TPB was initially developed to predict individual behaviors, its application has gradually expanded to organizational-level behavior prediction. For example, Tsai et al. [41] extended TPB to explain behavioral choices of employees within service organizations. Bulgurcu et al.’s paper illustrated TPB’s utility in predicting employee compliance behaviors based on rationality and security awareness [42]. Additionally, Venkatesh et al. integrated TPB with the Technology Acceptance Model (TAM) to explore technology adoption within structured organizations [43].

In the construction sector, numerous scholars have leveraged TPB to examine organizational intentions and behaviors. For instance, Zhou et al. [31] integrated the Norm Activation Model (NAM) with TPB to investigate the intentions of citizens regarding the purchase of prefabricated housing. Zhai et al. [44] expanded upon the TPB by integrating the concepts of moral identity and corporate green culture to formulate the Extended TPB model, which investigates large-scale contractors’ intentions to engage in environmentally responsible behavior. Xie et al. [45] constructed a TPB-based framework to predict environmentally responsible behavior among participants in large-scale construction projects. The theory’s explanatory power and applicability have also been demonstrated in studies on construction organizations’ willingness to participate in electronic bidding [46], dispute resolution among project organizations [47], and contractors’ construction and demolition waste management [48].

Recent research has been conducted, leading to the identification of two significant research gaps. First, the extant literature on BIM outsourcing mainly focuses on its motives and influence factors but seldom considers the formation mechanisms. Second, previous research has primarily focused on external drivers and motivators to elucidate the behavior associated with BIM outsourcing, while neglecting the potential impact of psychological factors that may intrinsically affect this behavior, including factors such as attitude and intention, particularly within a comprehensive framework. To fill these gaps, the authors suggest employing the TPB as a comprehensive framework that integrates both psychological and social factors to investigate the intentions and behaviors related to BIM outsourcing within construction enterprises.

2.2. Research Model and Hypotheses Development

2.2.1. Behavioral Attitudes and BIM Outsourcing Intention

In the TPB, behavioral attitude pertains to the assessment made by an individual or organization regarding a specific behavior. It is typically formed during the decision-making process when comparing different alternatives and based on their relative advantages or value [49]. Recent papers have shown that approximately 70% of BIM models are developed by external consultants or contractor teams, indicating a trend that companies are increasingly relying on outsourcing to cope with technical and staffing limitations [20,50]. BIM outsourcing enables enterprises to avoid long-term investments in software, training, and personnel [51], utilize the advanced technologies, expertise, and infrastructure of external suppliers, reduce initial costs, immediately obtain economic benefits [20], achieve external production cost advantages, and thereby encourage enterprises to make the decision of outsourcing.

During the bidding process for construction projects, the presence of information asymmetry may lead to opportunistic behavior from contractors. This forces the owner to invest additional time and effort to evaluate outsourcing vendors, resulting in an increase in transaction costs [52]. High transaction costs may make construction enterprises more cautious toward outsourcing, reducing the degree of outsourcing. Furthermore, BIM models usually involve collaboration across multiple specialties and require the signing of multiple contracts. Consequently, in the outsourcing process, contract negotiation costs may also become a significant factor influencing outsourcing decisions. If the contract negotiation costs are too high, the construction enterprises may choose not to engage in large-scale BIM outsourcing. Based on these analyses, the following hypotheses are proposed:

H1: 

The external production cost advantage brought by BIM outsourcing has a positive impact on the BIM outsourcing intention of construction enterprises.

H2: 

The transaction cost in the BIM outsourcing process has a negative impact on the BIM outsourcing intention of construction enterprises.

2.2.2. Subjective Norms and BIM Outsourcing Intention

Existing research have indicated that IT outsourcing is influenced not only by transaction attributes but also by institutional factors [53]. In the TPB, subjective norm refers to the social pressures or the opinions of important groups that influence a decision-maker. These pressures mainly include mimetic pressure and normative pressure [19,49]. In construction projects, the decision-making behavior of construction enterprises is influenced not only by rational decision-making but also by the influence of upstream enterprises or other firms involved in the project [54]. Through collaboration with colleagues, industry rivals, and outsourcing partners, managers within the company acquire a more comprehensive understanding of the advantages associated with BIM outsourcing. If majority of industry peers choose to outsource BIM services, BIM outsourcing reduces their investments in hardware and human resources, making significant economic benefits and positive industry reputations. Company managers would be more likely to imitate these successful cases and choose to outsource BIM services on a large scale [55].

Institutional theory suggests that organizations or individuals are influenced by institutional pressures when making decisions, forcing decision-makers to adhere to established norms and practices [56]. Studies confirm that in outsourcing decisions, normative pressure facilitates the decision to outsource technology [57]. Within the construction sector, the utilization of BIM is often a prerequisite in project bidding processes, thereby increasing the propensity to engage in outsourcing [58]. This phenomenon is notably evident in the public domain, where deficiencies in internal capabilities lead governmental bodies to impose outsourcing mandates for BIM implementation, ensuring adherence to stringent project specifications [20]. These institutional factors consequently strengthen the strategic decision to capitalize on specialized expertise via outsourcing arrangements. Based on this, this paper formulated the following hypotheses:

H3: 

The levels of mimetic pressure are positively associated with the BIM outsourcing intention of construction enterprises.

H4: 

The levels of normative pressure are positively associated with the BIM outsourcing intention of the construction enterprises.

2.2.3. Perceptual Behavioral Control and BIM Outsourcing Intention

In the framework of the TPB, perceived behavioral control pertains to the extent to which an individual believes they possess the capability to execute a particular behavior, whether with relative ease or with considerable difficulty. This concept encompasses the individual’s self-awareness of the various factors that may either support or hinder the execution of that behavior [49]. For construction enterprises, there are significant differences in BIM application capabilities across enterprises. When an enterprise’s technological application capabilities fail to meet its strategic needs, it may choose to outsource in order to acquire external resources and address capability gaps [9]. In contrast, for enterprises that already possess high BIM application capabilities, the enterprise’s technical strength is sufficient to support the smooth implementation of projects. Therefore, construction enterprises are more likely to rely on internal resources rather than outsourcing BIM-related tasks to third parties [9]. Consequently, the inherent capabilities of BIM applications within construction enterprises significantly influence the decision-making process regarding outsourcing, either facilitating or obstructing it. Hence, this study hypothesized the following:

H5: 

BIM application capability of the construction enterprises has a negative impact on its BIM outsourcing intention.

2.2.4. Perceptual Behavioral Control and BIM Outsourcing Degree

Although some construction enterprises have recognized that BIM technology can bring benefits and enhance industry reputation, the improvement of BIM application capabilities depends not only on purchasing advanced hardware but also on the accumulation of BIM experience within the companies [59]. Based on the enterprise’s own resource conditions and BIM application experience, construction enterprises can choose different outsourcing models. When enterprises lack BIM experience and managers perceive lower costs and risks, they tend to pursue conservative strategies such as outsourcing most or all BIM-related tasks to meet project requirements while minimizing risk exposure [22]. Recent evidence suggests that cost-sensitive managers may adopt outsourcing as a transitional strategy—reducing the financial burden of full in-house adoption while progressively building internal BIM capacity [22]. This logic refines our hypotheses by linking cost perceptions, risk considerations, and managerial attitudes more explicitly to outsourcing intentions and behaviors. As BIM application experience accumulates, the company gradually improves its ability to apply BIM technology, enabling it to manage BIM projects more efficiently. At this stage, the company only needs to outsource the parts of the project that require BIM application, reducing its dependence on external contractors. When a company has strong BIM application capabilities, it can rely on internal resources to complete more BIM tasks without relying on outsourcing. Therefore, this study hypothesized the following:

H6: 

BIM application capability of the construction enterprises has a negative impact on its BIM outsourcing degree.

2.2.5. BIM Outsourcing Intention and BIM Outsourcing Degree

The impact of behavioral intention on actual behavior has been extensively corroborated within the disciplines of sociology and psychology. The TPB asserts that the intention to participate in a particular behavior, whether by an individual or an organization, serves as a necessary precursor for the actual execution of that behavior. research have demonstrated that behavioral intention exerts a positive effect on actual behavior [60,61]. BIM outsourcing intention reflects the extent to which construction enterprises are willing to outsource BIM tasks to third-party companies and the effort they are willing to invest in achieving this goal. BIM outsourcing is a common phenomenon, but the extent of outsourcing varies significantly. This variation is because of the enterprise’s outsourcing intention reflects its level of trust in external collaboration. Enterprises with higher outsourcing intention generally have greater trust in the capabilities and reputation toward third-party companies, making them more willing to delegate more work to external teams [62]. This trust encourages companies to loosen their control during the outsourcing process, thereby further increasing the extent of outsourcing. Conversely, enterprises with lower outsourcing intention often have doubts about the BIM application capabilities and reputation of third-party companies, resulting in a lower scope and depth of BIM outsourcing. Drawing upon the prior analysis and the conducted interviews, this paper posits the following hypothesis:

H7: 

BIM outsourcing intention has a positive impact on the degree of BIM outsourcing.

In conclusion, this research employed the TPB as a comprehensive framework that integrates both transactional and institutional factors to investigate the intentions and behaviors related to BIM outsourcing within construction firms. Based on the previous analyses, the authors have proposed the following research model, as depicted in Figure 1.

3. Research Method

3.1. Measurement Development

A questionnaire survey was utilized as the primary method for data collection in order to evaluate the previously proposed research model and its associated hypotheses. The development of variables measurement commenced with a thorough examination of both theoretical and empirical literature pertaining to IT outsourcing and BIM outsourcing. Additionally, a semi-structured interview was conducted in March 2025 with four professionals from academia and industry. Following the initial development of the measurement items, a pretest was administered utilizing the online survey platform wjx.cn. This pretest aimed to identify any ambiguous expressions and to conduct a preliminary assessment of the validity of the associated constructs. Following the input from these participants, certain wording of the measurement items was modified. For instance, the phrase “have economic benefits” in the mimetic pressures item, “many of the enterprise’s peers outsource BIM services to benefit the company significantly”, was adjusted to “benefit”.

The completed questionnaire was made up of three sections. The initial section gathers general information pertinent to project engineers, including variables such as gender, ownership type, educational background, experience in the construction industry, experience in BIM implementation, and position. The second section assesses the intention and extent of BIM outsourcing among the engineers surveyed in relation to the implementation of BIM. The third section includes inquiries regarding the five contextual factors that were analyzed. The questionnaire assessed a total of seven dependent or independent variables: external production cost advantage (PRODCOST), transaction cost (TRCOST), normative pressures (NP), mimetic pressures (MP), BIM application capability (BAC), BIM outsourcing intention (BI) and BIM outsourcing degree (BOD).

The measurement items employed for the constructs were predominantly derived from established scales within the existing literature, which have demonstrated reliability, and were subsequently adapted to align with the context of BIM outsourcing.

Table 1. Measurement items.

Dimension	Constructs	Measurement Question Items	Item Source
PRODCOST	PRODCOST1	Compared with the enterprise’s own BIM application services, outsourcing BIM services can reduce the enterprise’s hardware input cost.	Ang et al. [63] Kessler et al. [64] Jaumandreu et al. [65]
	PRODCOST2	Compared with the enterprise’s own BIM application services, outsourcing BIM services can reduce the enterprise’s software input cost.
	PRODCOST3	Compared with the enterprise’s own BIM application services, outsourcing BIM services can reduce the enterprise’s human resource input cost.
	PRODCOST4	Compared with the BIM service outsourcing method, the project management cost generated by the enterprise’s independent completion of BIM application services is lower.
TRCOST	TRCOST1	Companies need to spend a lot of time to find a BIM service outsourcing enterprise to meet the needs of project BIM application.	Ang et al. [63] Espino-Rodriguez et al. [66] Bean et al. [67]
	TRCOST2	When negotiating a contract with a BIM service outsourcing enterprise, the enterprise needs to spend a lot of time and labor costs.
	TRCOST3	Enterprises spend a lot of time and labor costs monitoring the work of BIM service outsourcing enterprises to ensure that their results meet project and contract requirements.
	TRCOST4	Once a contract is finalized, it can be difficult for an enterprise to fine-tune a BIM service contract for project needs.
NP	NP1	Enterprise’s outsourcing vendors strongly advocate BIM outsourcing.	Ang et al. [63] Cao et al. [19] Wang et al. [68]
	NP2	Enterprise’s partners strongly advocate BIM outsourcing.
	NP3	Enterprise’s competitors strongly advocate BIM outsourcing.
MP	MP1	Many of the enterprise’s peers outsourced BIM services to save project costs.	Ang et al. [63] Cao et al. [19] Wang et al. [68]
	MP2	Many of the enterprise’s peers outsource BIM services to benefit the company significantly.
	MP3	Many of the enterprise’s peers outsourced BIM services, which were perceived favorably by others in the industry.
	MP4	Many of the enterprise’s peers outsourced BIM services, and its service quality was well received by customers.
BAC	BAC1	Our enterprise has extensive experience in BIM applications.	Son and Benbasat [69] Cao et al. [70] Mahamadu et al. [71]
	BAC2	Our enterprise is capable of solving the technical problems related to BIM.
	BAC3	Our enterprise has the necessary expertise to apply BIM in projects.
	BAC4	Our enterprise has a strong BIM application planning ability.
BI	BI1	Our enterprise now wants to outsource its BIM business.	Ajzen [49] Zheng et al. [34] Murguia et al. [72]
	BI2	Our enterprise intends to outsource its own BIM business in the future.
	BI3	Our enterprise wants to outsource its BIM business all the time.
BOD	BOD1	BIM visual drawing review.	Eastman et al. [1] Gao et al. [62] Cao et al. [19]
	BOD2	BIM-based collision inspection.
	BOD3	Mechanical and electrical deepening design based on BIM.
	BOD4	BIM-based fine decoration deepening design.
	BOD5	BIM-based curtain wall deepening design.
	BOD6	BIM-based steel structure deepening design.
	BOD7	Simulation of special construction scheme based on BIM.
	BOD8	Construction site layout based on BIM.
	BOD9	BIM-based visual disclosure.
	BOD10	BIM-based project security management.
	BOD11	BIM-based project schedule management.
	BOD12	Project quality management based on BIM.
	BOD13	BIM-based project cost management.

delineates all the constructs, along with the associated scales and their respective source citations. The particular measurement items utilized in this research are outlined in Table 1.

The measurement items for PRODCOST were adapted from the papers of Ang et al. [63], Kessler et al. [64], and Jaumandreu et al. [65], and rephrased to fit the context of BIM outsourcing. The four adopted items specifically reflect the perceived benefits by employing BIM inside the enterprises compared to buying BIM applications in the market. The measurement items of TRCOST were based on Ang et al. [63], Espino-Rodriguez et al. [66], and Bean et al. [67], and were subsequently adapted to align with the context of BIM outsourcing. A total of four items were ultimately utilized to assess this construct, focusing on the costs associated with identifying appropriate BIM outsourcing vendors and ensuring the quality of their services. The operationalization of NP and MP was primarily informed by the works of Ang et al. [63], Cao et al. [19], and Wang et al. [68]. The construct of NP was operationalized to illustrate the influence of various professional organizations on the standards governing BIM outsourcing within construction firms. Three distinct items were employed to assess the normative influences exerted by outsourcing vendors, partners, and competitors, respectively. MP was defined in relation to the perceived advantages and effectiveness of BIM outsourcing as experienced by comparable organizations, utilizing four metrics to assess the degree to which these peer enterprises had derived significant benefits. The items of the BCA were modified based on the works of Son and Benbasat [69], Cao et al. [70], and Mahamadu et al. [71]. Four items reflect the knowledge, experience and capability in the implementation of BIM. The measurement items of BI were adapted from Ajzen [49], Zheng et al. [34], and Murguia et al. [72]. Three items reflect the intention toward BIM outsourcing. Based on the previous discussions, these measurement items (i.e., PRODCOST, TRCOST, NP, MP, BCA, BI), were assessed utilizing a five-point Likert scale, which spans from strong disagreement to strong agreement.

The degree of BIM outsourcing (BOD) was assessed using a combined index that reflects BIM outsourcing in various construction application areas. The detailed BIM outsourcing applications were based on Eastman et al. [1], Gao et al. [62] and Cao et al. [19], as well as the findings derived from the initial interviews conducted. Following additional revisions informed by the feedback from the pilot study, the questionnaire ultimately included 13 BIM outsourcing applications. The degree of BIM outsourcing was assessed using a two-point scale of 0 (not outsource), and 1 (outsource). To enhance the thoroughness of the adoption measurement, a principal component analysis (PCA) was conducted to combine the BIM outsourcing across 13 different applications into a single aggregated factor [19,73,74,75]. The resulting factor scores were then utilized to assess the overall level of BIM outsourcing. The internal consistency assessment of the aggregated factor yielded a satisfactory Cronbach’s Alpha coefficient of 0.815.

3.2. Sampling and Data Collection

The survey questionnaire was administered to construction engineers who are currently involved in BIM-based construction projects on the Chinese mainland. As one of the largest construction markets globally, China’s construction output value reached RMB 32.65 trillion (approximately USD4.59 trillion based on the 2024 exchange rate). In recent years, the Chinese government has implemented a series of initiatives to promote the adoption of BIM; however, the development of BIM within the construction industry remains unevenly distributed. Consequently, a completely random sampling method was deemed inappropriate for gathering respondents. Instead, participants representing a diverse array of BIM-based construction projects across various regions were identified through multiple strategies, including searches within BIM communication communities and outreach to professionals attending industry seminars. The chosen participants were subsequently requested to participate in the survey, reflecting on their most recent engagement in a construction project utilizing BIM.

Before administering a comprehensive questionnaire survey, in-depth interviews were carried out with four experts who have significant theoretical understanding and practical expertise in BIM. Among the interviewees, two were academic scholars specializing in BIM, who exhibited a thorough comprehension of the adoption of BIM within the industry. The other two participants were professionals from construction firms with active involvement in BIM practices. The experts were queried regarding the existence of BIM outsourcing, provided examples of BIM outsourcing in practice, and identified the factors contributing to this phenomenon. Following this, experts were solicited to evaluate the questionnaire in order to ascertain the face validity of the survey instrument and to verify that the measurements were relevant within the framework of BIM outsourcing. Each interview lasted between 45 min to one hour.

Subsequently, a comprehensive questionnaire survey was administered to gather data. Responses were solicited via email and the wjx.cn online survey platform from April 2025 to June 2025. Approximately 327 construction engineers from various regions were approached through wjx.cn, email and WeChat, resulting in the collection of 252 responses. Following the removal of low-quality data—characterized by responses that predominantly favored a single option, excessive neutral responses, unanswered items, and questionnaires completed in under 150 s—the final sample size was reduced to 200 for further analysis, yielding an effective response rate of 79.4%. Demographic analysis was conducted by IBM SPSS Statistics 22.0, and characteristics of these 200 construction engineers are shown in

Table 2. Sample characteristics.

Variable	Category	Number	Percentage
Gender	Male	143	71.50%
	Female	57	28.50%
Educational background	Junior college and below	36	18.00%
	Undergraduate	116	58.00%
	Master’s degree	44	22.00%
	PhD	4	2.00%
Experience in BIM implementation	0–3 years	51	25.50%
	4–5 years	130	65.00%
	6 years and above	19	9.50%
Ownership type	State-owned	136	68.00%
	Private	64	32.00%
Experience in the construction industry	0–5 years	48	24.00%
	6–10 years	87	43.50%
	11 years and above	65	32.50%
Position	Middle-level management or above	59	29.50%
	Junior management	102	51.00%
	Front-line staff	39	19.50%

. The data indicates that 74.5% of the participants possess over three years of experience in BIM. Furthermore, it is apparent that the engineers surveyed exhibit a variety of backgrounds concerning gender, professional roles, and levels of experience in BIM.

4. Data Analyses and Results

4.1. Measurement Validation

Based on the collected data, this paper used partial least squares structural equation modeling (PLS-SEM) to explore the mechanism of the BIM outsourcing behavior by conducting path analysis among variables. SmartPLS 4.0 was used as the specific PLS analysis program. PLS-SEM handles non-normal datasets and smaller sample sizes [76]. In relation to the sample size necessary for conducting PLS analyses, it is advisable that the sample size be at least ten times greater than the number of structural paths linked to the latent construct exhibiting the highest quantity of incoming paths [77]. In the current paper, the construct exhibiting the highest number of incoming paths is the degree of BIM outsourcing, which has a total of six incoming paths, and the sample size (N = 200) satisfactorily meet the “10 times” requirement. Prior to employing the Partial Least Squares (PLS) technique to evaluate the proposed hypotheses, the measurement instruments for the variables associated with the hypotheses were initially subjected to a validation process.

The validation of the measurements for PRODCOST, TRCOST, NP, MP, BAC, and BI was conducted by evaluating internal consistency, convergent validity, and discriminant validity. The internal consistency of the constructs was evaluated by calculating composite reliability. As indicated in

Table 3. Measurement validity and construct correlations.

Variable	CR	Cronbach’s α	AVE	BAC	BI	MP	NP	PRODCOST	TRCOST
BAC	0.938	0.938	0.842	0.918
BI	0.935	0.934	0.885	−0.588	0.941
MP	0.912	0.907	0.783	−0.481	0.513	0.885
NP	0.886	0.884	0.812	−0.475	0.542	0.358	0.901
PRODCOST	0.877	0.858	0.701	−0.440	0.564	0.445	0.421	0.837
TRCOST	0.903	0.898	0.765	0.494	−0.490	−0.285	−0.380	−0.222	0.875

Notes: SD (standard deviation) = ${\displaystyle \frac{1}{\mathrm{N}}}\sum _{i=1}^N{\left(x_i-\mu \right)}^2$; CR (composite reliability) = ${\displaystyle \frac{{\left(\sum \mathsf{\lambda }\right)}^2}{{\left[\right(\sum \mathsf{\lambda })}^2+\sum \mathsf{\theta }]}}$; AVE (average variance extracted) = ${\displaystyle \frac{{\sum }_{\mathrm{i}=1}^{\mathrm{n}}{\mathsf{\lambda }}_{\mathrm{i}}^2}{{\sum }_{\mathrm{i}=1}^{\mathrm{n}}{\mathsf{\lambda }}_{\mathrm{i}}^2+{\sum }_{\mathrm{i}=1}^{\mathrm{n}}{\mathsf{\theta }}_{\mathrm{i}}}}$. PRODCOST (external production cost advantage); TRCOST (transaction cost); NP (normative pressures); MP (mimetic pressures); BAC (BIM application capability); BI (BIM outsourcing intention). a. Bold values on the diagonal represent the square root of AVE.

, the composite reliability coefficients for the constructs under investigation all surpass the established threshold of 0.7 [76], demonstrating that all constructs possess adequate internal consistency. Convergent validity reflects the extent to which the items underlying a particular construct actually refer to the same conceptual variable. This was evaluated by calculating the average variance extracted (AVE) values in conjunction with the factor loadings of the measurement items. Table 3 demonstrates that the average variance extracted (AVE) values for all constructs exceed the recommended threshold of 0.5 [76]. The square root of the average variance extracted (AVE) for each variable exceeds the absolute values of the inter-construct correlations, suggesting that the constructs exhibit sufficient discriminant validity. As demonstrated in

Table 4. Factor loadings for multi-item constructs.

Construct	Items	Mean	SD a	Factor Loadings b	T-Value
PRODCOST	PRODCOST1	0.997	0.025	0.841	22.165
	PRODCOST2	0.955	0.024	0.886	32.704
	PRODCOST3	1.000	0.026	0.878	30.641
	PRODCOST4	1.052	0.025	0.737	12.627
TRCOST	TRCOST1	0.973	0.036	0.856	27.328
	TRCOST2	1.010	0.030	0.890	33.585
	TRCOST3	1.027	0.027	0.893	37.387
	TRCOST4	0.982	0.037	0.860	26.251
NP	NP1	1.037	0.027	0.913	37.867
	NP2	0.995	0.022	0.915	44.822
	NP3	0.968	0.028	0.875	34.953
MP	MP1	0.959	0.039	0.836	24.852
	MP2	0.956	0.031	0.887	30.464
	MP3	1.032	0.028	0.916	37.279
	MP4	1.054	0.028	0.899	37.052
BAC	BAC1	0.997	0.025	0.923	40.261
	BAC2	0.955	0.024	0.913	39.354
	BAC3	1.000	0.026	0.911	38.695
	BAC4	1.052	0.025	0.925	41.885
BI	BI1	1.015	0.024	0.944	41.687
	BI2	1.107	0.022	0.966	50.023
	BI3	0.893	0.027	0.911	33.295

Notes: The bold values indicate the standardized factor loadings of the items associated with their respective constructs, while the T-values correspond to these loadings. PRODCOST (external production cost advantage); TRCOST (transaction cost); NP (normative pressures); MP (mimetic pressures); BAC (BIM application capability); BI (BIM outsourcing intention). _a SD = standard deviation. _b All factor loadings are significant at the 0.1% level.

, the majority of items display standardized factor loadings on their corresponding constructs that surpass the threshold of 0.7 [76]. This indicates that the measured variables demonstrate considerable explanatory capacity for their corresponding latent variables.

4.2. Hypothesis Testing

A bootstrapping procedure involving 5000 resamples was conducted to assess the statistical significance of the path coefficients within the research model. The outcomes of the PLS analyses, which were derived using the bootstrapping method, are illustrated in Figure 2. The R² value of the dependent variable, BIM outsourcing intention to BIM outsourcing degree, is 0.317. This suggests that a significant portion of the variance in this construct is accounted for by the research model. As shown in Figure 2, the results indicated that external production cost advantage (β = 0.278, p < 0.001), mimetic pressure (β = 0.169, p < 0.01), and normative pressure (β = 0.194, p < 0.01) positively affect BIM outsourcing intention; thus, Hypotheses H1, H3, and H4 are all supported. Meanwhile, the influences of transaction costs (β= −0.215, p < 0.01) and BIM application capability (β = −0.188, p < 0.01) on BIM outsourcing intention are all negative and statistically significant; thus, Hypotheses H2 and H5 are all supported. The influences of BIM application capability (β = −0.219, p < 0.01) on BIM outsourcing degree is negative and statistically significant, hence Hypotheses H6 is supported, whereas the influences of BIM outsourcing intention (β = 0.406, p < 0.001) on BIM outsourcing degree is positive and statistically significant, hence Hypotheses H7 is supported.

Table 5. Hypothesis standard path coefficient and test results.

Hypothesis	Path	Standard Path Coefficient	p-Value	Test Result
H1	External production cost advantage—BIM outsourcing intention	0.278	0.000	support
H2	Transaction cost—BIM outsourcing intention	−0.215	0.002	support
H3	Mimetic pressures—BIM outsourcing intention	0.169	0.006	support
H4	Normative pressures—BIM outsourcing intention	0.194	0.002	support
H5	BIM application capability—BIM outsourcing intention	−0.188	0.005	support
H6	BIM application capability—BIM outsourcing degree	−0.219	0.002	support
H7	BIM outsourcing intention—BIM outsourcing degree	0.406	0.000	support

presents the path coefficients of the structural model discussed in this paper, along with their corresponding significance levels.

5. Discussion

Based on TPB and integrating TCT and institutional theory, this paper proposed a research model with PRODCOST and TRCOST as behavioral attitudes, NP and MP as subjective norms, BAC as a behavioral control variable, BI as an intention variable, and BOD as a behavioral variable. The empirical results suggested that all the 7 hypotheses passed the test (Table 5).

5.1. Key Findings

5.1.1. The Influence of Behavioral Attitude on BIM Outsourcing Intention

The findings suggest that an external production cost advantage serves as a predictor for the intention to outsource BIM (H1 in Table 5), which supports Ang et al. [63] and Dibbern et al. [78], who argued that the production cost advantages of outsourcing vendors facilitate owners’ intention to engage in large-scale IT outsourcing. A construction enterprise with a strong external production cost advantage is willing to outsource BIM functions. Additionally, in the measurement of external production cost advantages in this paper, construction enterprises perceived hardware cost advantages from BIM outsourcing to be lower than software cost advantages, and the average level of the perception of reduced human resource costs is relatively high. This may be because hardware and software costs are generally considered as a one-time expense. For construction enterprises, hardware procurement and maintenance tend to be more fixed and manageable, making the advantage of hardware costs less obvious. In addition, the advantage of human resource costs reduction is relatively high. The construction enterprise is more willing to concentrate on reduction in human resource costs because these costs are long-term, ongoing expenditures, which are characterized as greater fluctuations and being more difficult to control internally. Furthermore, these findings also indicated that human resource is the key barrier in BIM implementation, which is consistent with the barriers of BIM adoption literature.

Transaction costs have an negative effect on BIM outsourcing intention (H2 in Table 5), which is consistent with the findings of Ang et al. [63] and Espino-Rodriguez et al. [66], who reported that transaction costs discourage the intention of IT outsourcing due to the additional cost and time involved in finding the suitable IT outsourcing vendors. The findings also indicated that the average level of perceived cost of searching for BIM outsourcing companies is relatively low. This may be because, due to the rapid development and widespread adoption of BIM, the number of BIM outsourcing and consulting companies has reached a considerable scale. Construction enterprises can easily and quickly find suitable BIM outsourcing companies, which reduced the cost of searching for appropriate companies. Taking the China State Construction Engineering Corporation as an example, the unified bidding platform enables BIM outsourcing companies that cooperate with internal companies to automatically register, providing convenience for construction enterprises. Additionally, other contractors can also access similar online platforms to query relevant information, reducing the difficulty in finding suitable BIM outsourcing companies and decreasing transaction costs. Furthermore, BIM application has a higher market share in public and residential construction projects, which typically have more standardized technical requirements and lower asset specificity. Therefore, it is easier for construction enterprises to find BIM outsourcing companies that meet the requirements for these projects, further lowering the perceived costs. On the other hand, the transaction cost perception related to supervising the BIM outsourcing company’s work to ensure that their results meet project and contract requirements is relatively high. This might be explained that BIM applications involve more complex technology and outcomes in the construction phase, which are not always clearly defined, particularly for some phase-specific BIM application results. The delivery standards for these results may not be as clear as in the design phase, which means general contractors must invest more time and resources to supervise and verify the work.

5.1.2. The Influence of Subjective Norms on BIM Outsourcing Intentions

The empirical results indicate that both mimetic pressure and normative pressure promote BIM outsourcing intention (H3, H4 in Table 5), validating the findings of Vitharana et al., who demonstrated that, in the process of IT outsourcing, the decision to outsource is not always solely based on the benefit-prioritization principle, while institutional pressures are also an important factor influencing outsourcing behavior [58]. However, the results of this paper confirmed that both institutional theory and TCT directly influence BIM outsourcing degree. However, these findings, in part, contradict the studies of Ang et al., who explored how institutional pressures affect the degree of IT outsourcing under different transaction costs and used transaction cost variables as moderating factors in their theoretical model [79]. This may be because, with the widespread adoption of BIM, the driving forces behind outsourcing behavior are no longer limited to a simple cost–benefit analysis but are increasingly influenced by the institutional environment and external norms. Indeed, owners from the public sectors in many countries (e.g., China, UK, Singapore) are progressively requiring the implementation of BIM in their projects. Construction enterprises have no choice but to adopt BIM by themselves or outsource BIM functions. Construction companies, which have successfully implemented BIM through outsourcing, creatied industry-wide mimetic effects, effecting outsourcing decisions. The construction industry predominantly operates under a project-based model, wherein construction enterprises are embedded in intricate collaborative networks at the industry level. These networks are formed based on project-specific collaborative relationships that vary across different project contexts [80]. Project-based networks may serve as significant conduits for construction enterprises to navigate institutional pressures arising from collaborative relationships established in previous projects. This may subsequently influence their behaviors, including the outsourcing of BIM in forthcoming projects.

This paper also revealed that the influence of mimetic pressures and normative pressures on the intention to outsource BIM varies. Indeed, normative pressures exhibited higher positive effects. This aligns with the conclusions drawn by Vitharana et al. [57], who reported that normative pressure will spread collective expectations among organizations through various channels, promoting the IT outsourcing degree. Construction projects provide a communication channel for the various stakeholders, such as BIM professionals and BIM outsourcing vendors. Although the project is regarded as temporary organization, different general contractors and BIM subcontractors may collaborate again, forming relatively closer project-based collaborative networks. The networks can act as important channels for construction enterprises to conduct project-based learning, which have the potential to substantially impact the attitude toward BIM outsourcing [80]. The attitudes that organizations develop from their experiences with networks in previous projects may further influence their behaviors regarding BIM outsourcing. Therefore, BIM outsourcing intentions of construction enterprises are more likely to be influenced by normative pressure.

5.1.3. The Influence of Perceived Behavioral Control on BIM Outsourcing Intention and Behavior

The empirical data in this paper shows that BIM application capability negatively impacts BIM outsourcing intention (H5 in Table 5), which is consistent with the findings of Cheon et al. [81], who indicates that organizations will fill the gap between strategic needs and their own IT capabilities by large-scale IT outsourcing. However, the effect is relatively low. It supports the findings of Fountain et al. [10], who argue that the primary strategic motivation for BIM outsourcing is not to alleviate the lack of BIM application capabilities. Instead, many general contractors already have strong BIM application capabilities, and BIM outsourcing is used to reduce the excessive workload of BIM tasks. Among the favorable factors influencing the intention to outsource BIM, the advantage of reduced external production costs demonstrates the most significant impact. This indicates that construction enterprises tend to prioritize savings in production and labor costs when making BIM outsourcing decisions. This finding highlights the fact that cost control is a key factor in BIM outsourcing decisions in construction projects.

This paper also found that BIM application capability negatively impacts BIM outsourcing degree (H6 in Table 5). It indicates that when construction enterprises possess strong and sufficient BIM application capabilities, they are less willing to engage in large-scale BIM outsourcing.

In the context of BIM application, when general contractors believe they can fully master and control BIM tasks, they are more likely to complete the tasks in-house rather than relying on outsourcing. On the other hand, if they feel that BIM tasks exceed their capabilities, outsourcing becomes an effective solution. Therefore, the impact of BIM application capability on outsourcing degree is direct, while its impact on outsourcing intention may be indirect, depending on the company’s perceived and actual capabilities.

5.1.4. The Influence of Behavioral Intention on BIM Outsourcing Behavior

Consistent with TPB-based studies in other fields, behavioral intention acted as a significant motivator for organizational behaviors. It indicates that the stronger the BIM outsourcing intention of construction enterprises, the more likely they are to engage in large-scale BIM outsourcing (H7 in Table 5). Furthermore, the empirical data in this paper reveals significant differences in the proportion of BIM-related applications outsourced. BIM visualization review (58%), BIM-based clash detection (39%), and BIM-based MEP (Mechanical, Electrical, and Plumbing) design (35%) are the most commonly outsourced BIM applications. In contrast, BIM-based project management, such as quality management, schedule management, and especially cost management (15%), have the lowest degree of outsourcing. These findings are consistent with the findings of Fountain et al. [10]. When organizations internally trust that BIM outsourcing is beneficial and are willing to execute it, it can promote large-scale BIM outsourcing behavior. These BIM applications have the highest outsourcing proportion, mainly because their benefits represent the most intuitive and can be easily perceived. BIM-based project management exhibited low outsourcing proportion, mainly because of communication barriers, high management costs, and poor quality in service. Indeed, these BIM applications involve complex specialized knowledge and technical requirements. It requires not only high-level technical support but also requires outsourcing vendors to quickly respond to specific project requirements in on-site conditions, ensuring the timely delivery of information. This process may increase communication costs, which prevented the large-scale outsourcing.

5.2. Theoretical Contributions

Two theoretical contributions on TPB are made. Initially, although the TPB has delineated the determinants that forecast behaviors, it does not explicitly acknowledge the impact of contextual factors on the behavior of BIM outsourcing within the TPB framework. In this paper, the authors argue that within the specific context of BIM outsourcing, transaction costs and institutional pressures are critical factors influencing the correlation between the intention to outsource BIM and the degree of BIM outsourcing. In contrast to the traditional TPB model, which conceptualizes attitude as a unified construct, this study deconstructs attitude into two separate components: benefit perception attitude and risk perception attitude. These components collectively influence the intention to outsource BIM. The results corroborate prior research on IT outsourcing, indicating that the benefit-oriented attitude has a positive impact on outsourcing intention, whereas the risk-oriented attitude does not exhibit a significant effect. Additionally, while earlier studies have identified various motivations and patterns associated with BIM outsourcing, they have not provided a comprehensive framework that integrates contextual motivators to forecast BIM outsourcing behavior. This research expands the application of the TPB to elucidate the BIM outsourcing behavior of construction firms within the situation of BIM-enabled construction projects.

5.3. Practical Implications

This research offers various practical implications.

Firstly, the empirical findings underscore the necessity of viewing BIM outsourcing as a multifaceted social activity that is not solely driven by transaction costs but is also shaped by institutional pressures. Consequently, while institutional forces can be leveraged to promote the outsourcing of BIM for vendors, it is imperative to exercise caution to prevent indiscriminate BIM outsourcing that does not take into account the unique requirements of enterprises. Moreover, based on the comparison of two institutional pressures, the results suggest normative pressures have more important role in determining BIM outsourcing intention. For large state-owned enterprises, to enhance the efficacy of their impact, BIM outsourcing providers ought to sustain the collaborative networks established during previous construction projects. For small and medium private enterprises, providers of BIM outsourcing services ought to prioritize the enhancement of BIM products and services, as this can contribute to greater client satisfaction and trust, thereby facilitating the acquisition of additional project opportunities in the future. Second, results indicate that external production cost advantage plays the most significant role in promoting BIM outsourcing intention. For large state-owned enterprises, they may focus on more flexibility and agility in BIM. Thus, BIM outsourcing providers should propose innovative BIM solutions to meet whenever they need, especially when integrated with other sophisticated information technologies, such as AI, RFID, GIS, and Robotics. For small and medium private enterprises, they may concentrate on financial benefit brought by BIM outsourcing. Thus, BIM outsourcing providers should offer fundamental and important BIM functions. Moreover, BIM outsourcing vendors can provide ROI analysis and success cases to present the value of BIM outsourcing service during the market searching process. Third, BIM outsourcing vendors should increase BIM service quality in contracts to avoid transaction costs, leading to the reduction of clients’ BIM outsourcing intention, especially for large state-owned enterprises. This is because the organizational structure of large enterprises is more complex, and the review procedures for contracts are more elaborate. Once there are problems with the contracts, it is more likely to lead to increased transaction costs. Finally, both large state-owned enterprises and small and medium private enterprises should learn from BIM outsourcing providers, as these providers can introduce advanced BIM knowledge and technologies that enhance their capabilities in BIM management. Simultaneously, collaboration with experienced BIM outsourcing providers can facilitate the establishment of direct BIM learning mechanisms for employees, potentially enhancing their BIM proficiency.

6. Conclusions

This paper aims to explore the behavioral rationale behind the outsourcing of BIM by construction firms, as well as to examine the factors and mechanisms that contribute to this behavior. To achieve this objective, a model has been developed that integrates TCT with institutional theory. A theoretical model grounded in the TPB was formulated, incorporating seven proposed hypotheses related to transaction cost predictors and institutional predictors. Subsequently, a sample of 200 construction engineers from Chinese construction enterprises was collected and analyzed using PLS-SEM.

The empirical study showed all the hypotheses were supported, and the results indicated that construction enterprises’ BIM outsourcing behavior can be driven and predicted by both BIM application capability and BIM outsourcing intention, which can be significantly predicted by external production cost advantage, transaction cost, normative pressures, mimetic pressures, and BIM application capability. In particular, the BIM outsourcing degree was confirmed to be positively influenced by BIM outsourcing intention directly and negatively influenced by BIM application capability. External production cost advantage was found to be the strongest predictor of BIM outsourcing intention, followed by normative pressures and mimetic pressures. As such, in order to ensure the effective implementation of BIM applications, construction enterprises need to allocate hardware, software, and human resources, which incurs significant internal production costs. BIM outsourcing can effectively reduce these costs, and the more pronounced the reduction in internal production costs due to outsourcing, the greater the construction enterprises’ willingness to engage in BIM outsourcing. The reduction in production costs, resulting from BIM outsourcing, is the primary driving factor influencing BIM outsourcing intention for construction enterprises. During the process of searching, negotiating, supervising, and managing service contracts with BIM outsourcing vendors, construction enterprises incur significant communication costs. The higher these transaction costs, the less likely the construction enterprises are to outsource BIM tasks. Construction enterprises will form BIM outsourcing intention under the combined effect of mimetic pressure and normative pressure. Among these, normative pressure has a more significant driving effect on BIM outsourcing intention. The BIM outsourcing intention and behavior of construction enterprises are influenced by their own BIM application capabilities. The stronger the BIM application capability, the less likely they are to engage in large-scale BIM outsourcing behavior. BIM outsourcing intention is the most important factor driving construction enterprises to engage in large-scale BIM outsourcing.

The findings confirmed earlier IT outsourcing research. Transaction costs are the significant motivators for predicting IT outsourcing intention. While prior research has indicated BIM cannot be simply treated as IT due to its characteristics, such as complex and radical innovations, BIM outsourcing can be influenced by changes in transaction costs. This finding also indicated BIM possesses some features and characteristics of IT, but is not completely equivalent to IT. Indeed, compared with other IT outsourcing, BIM outsourcing also exerts considerable social influence, such as normative pressures, mimetic pressures. Consequently, subsequent research should consider BIM outsourcing as a multifaceted social activity that is not solely driven by transaction costs but is also shaped by institutional pressures.

There are several limitations that warrant further investigation. First, the data utilized in this paper were exclusively sourced from construction enterprises within China, and the research methodologies were confined to specific sociological approaches, including semi-structured interviews and questionnaires. Furthermore, the data is mainly from state-owned enterprises. Thus, future research endeavors could consider employing alternative data collection techniques to assess the generalizability of the model across diverse cultural and market contexts. Meanwhile, qualitative comparative study between state-owned and private enterprises could been conducted to further reveal the effects of different institutional pressures on BIM outsourcing behavior. Second, this study focuses on examining the influences of related factors on BIM outsourcing behavior from a static perspective. Taking into account the evolutionary nature of behavior, future studies could conduct longitudinal investigations on BIM outsourcing behavior from a dynamic perspective in the future. Third, although this study found that TPB has proved an effective framework to investigate BIM outsourcing behavior, the moderating factor is missing. Considering the singularity of data sources, there is a need to investigate the cultural moderators that may later influence mechanisms between BIM outsourcing intention and BIM outsourcing behavior.