An integrated Building Information Modelling, Integrated Project Delivery and Lean Construction Maturity Model

ABSTRACT

Construction scholars and professionals have recognized the integration of Building Information Modelling (BIM), Integrated Project Delivery (IPD), and Lean Construction (LC) as an effective way to increase collaboration and deliver construction projects. However, construction organizations cannot identify the transitional management steps required to achieve BIM-IPD-LC (BIL) implementation maturity. This paper presents a roadmap, introducing a BIL Maturity Model (MM) through iterative rounds of semi-structured interviews, model validation through a survey, and model implementation.

The research defined the maturity characteristics of construction organizations applying BIL across five levels, namely: ad hoc (individual), repeatable (project), defined (organization and project), quantitatively managed (full organization awareness), and optimizing (cross-organization integration) encompassing five major attributes including, ‘Customer Focus’, ‘Culture & People’, ‘Workplace Standardization’, ‘Waste Minimization’, and ‘Continuous improvement’ as well as 23 sub-attributes. The proposed integrated BIL MM will attract and assist industry practitioners and relevant stakeholders in identifying their position in BIL implementation maturity. The identified interdependencies between BIM, IPD, and LC will also serve as the basis for future academic studies respecting the collaboration of these three in an integrated manner.

KEYWORDS:

• Maturity Models
• Building Information Modelling
• Lean Construction
• Integrated Project Delivery

Introduction and research background

In the construction industry, large-scale projects involve a complex process of exchanging datasets among various disciplines (Ika, 2009). This challenge has resulted in the emergence of collaborative innovations aimed at minimizing data fragmentation (Aslam, Gao, & Smith, 2020). Building Information Modelling (BIM), Integrated Project Delivery (IPD), and Lean Construction (LC) are among these innovations in scholarly literature for their role in enhancing smoother information exchange and supporting collaborative decision-making (Ghosh & Lee, 2021).

BIM is mainly known as a technology that allows for more integrity, exchange, and retrieval of the building data among the stakeholders (Ahankoob, Manley, Hon, & Drogemuller, 2021). The most frequently cited functionalities of BIM include 3D visualization, design review, clash detection, program and space validation, engineering analysis, 4D scheduling, 5D cost estimation, logistics planning, safety analysis, energy analysis, shop drawing, documentation, and facility management (El Hajj, Martínez Montes, & Jawad, 2021).

IPD is a contract type and project delivery method that integrates all participants’ legal and cultural presence in complex projects to optimize project results and minimize waste, eventually meeting LC goals (Ma, Zhang, & Li, 2018). The foundational principles of IPD include ‘mutual respect and trust’, ‘early involvement of key participants’, as well as ‘continued involvement of key participants’, ‘risk and reward sharing’, ‘collaborative decision-making’, ‘early project goals definition’, ‘intensified planning’, ‘open communication’, a ‘no blame culture’, and adoption of the ‘appropriate technology’ (AIA, 2007).

LC is commonly known as a philosophy, culture or construction approach that serves two main goals with LC tools: to minimize process waste and to generate value for the construction supply chain (Killian, Abdallah, & Clevenger, 2020).

While BIM, IPD, and LC can function independently, their integration is recommended for enhancing project performance (Evans, Farrell, Elbeltagi, & Dion, 2021). As one of the early recognitions of integrating BIM, IPD, and LC (BIL), Sacks et al. (2010) hypothesize that ‘the full potential for improvement of construction projects can only be achieved when these three elements are adopted in an integrated manner’. Additionally, based on AIA (2007), ‘Sacks et al. (2010) argue that while it is possible to achieve IPD without BIM, BIM is essential for efficiently achieving the collaboration required for IPD ‘. In a subsequent 2012 study, the AIA report on IPD case studies underscores BIM and LC as the core strategies for IPD, highlighting that the synergies among BIM, IPD, and LC are instrumental in achieving more transparent data exchange and enhancing project delivery efficiency.

According to a study by Fakhimi et al. (2016), organizations can fully benefit from BIM implementation when they couple it with IPD and LC. In another study, Piroozfar et al. (2019) state that even though BIM can be adopted in any procurement system, the best result comes from coupling it with IPD.

Several theoretical and practical models are developed to incorporate BIM and LC techniques in IPD, and they are evaluated in real-world projects. These studies find that the BIL enables an innovative project delivery method to optimize costs, quality, and time across the construction project's life cycle (Rankohi et al., 2022; Machado et al., 2020).

According to Langston and Zhang (2021), Miettinen and Paavola (2014), and AIA C191 (2008), BIM, in this synergy, serves as a platform for shared data exchange and technological integration, while IPD facilitates early engagement among stakeholders by addressing legal and cultural aspects. Furthermore, LC fosters a culture of integration within the construction supply chain.

Organizations embracing BIL encounter a significant challenge in identifying the transitional management stages necessary to maximize integration benefits (Evans, Farrell, Elbeltagi, & Dion, 2022). Those adopting BIL or aiming to enhance their current practices must pinpoint areas for improvement and monitor progress. Additionally, they require a comprehensive tool to define goals and establish a roadmap for improving technology, infrastructure, policies, and processes (Succar, 2009).

According to Nesensohn et al. (2014) and Wendler (2012), Maturity Models (MMs) offer these transitional management roadmaps. Additionally, MMs provide a robust tool enabling organizations to assess their current maturity levels and strategically plan for future performance improvement (Alankarage, Chileshe, Samaraweera, Rameezdeen, & Edwards, 2022). Current MMs are based on the first widely used MM, the Software Engineering Institute's Capability Maturity Model (CMM), designed by the Software Engineering Institute in 1986. CMM is a novel concept that has emerged in numerous disciplines, including construction, focusing on monitoring Continuous Improvement using a stepwise approach (Omotayo, Boateng, Osobajo, Oke, & Obi, 2019). Standardized Process Improvement for Construction Enterprises (SPICE) is a recontextualization of the CMM for construction processes (Amaratunga, Sarshar, & Baldry, 2002). The SPICE framework comprises five maturity levels, serving as a foundational framework for assessing and improving construction processes, and subsequent MMs often build upon its principles and methodologies.

Among all the MMs developed in the construction field, several attempts inside and outside the academic literature aim to assess the level of maturity in organizations when adopting BIM in collaboration with IPD and/or LC (Rashidian, Drogemuller, & Omrani, 2022a). However, these efforts reveal the existence of two significant gaps. Firstly, according to a literature review by Rashidian, Drogemuller, and Omrani (2023a), relevant BIM, IPD, and LC MMs are predominantly categorized into four distinct assessment scopes: BIM, BIM-LC, IPD-LC, and LC. As a result, the absence of an integrated BIL MM has motivated this research to develop a comprehensive assessment tool.

Secondly, a recurring theme in related research is the lack of an articulated process for developing MMs (Rashidian, Drogemuller, & Omrani, 2022b). Many published materials on MMs fall short in detailing methodologies for creating distinct levels, leading to reliance on subjective judgments in their application. This paper, however, seeks to develop a BIL MM with well-defined attributes, a clear maturity level design, and a robust validation process. It also aims to offer clarity and guidance to construction organizations on implementing BIL systematically.

Literature review

MMs are structured into attributes and sub-attributes, typically including four to six maturity levels (Paulk, 1995). As a result, a well-defined MM should consist of a scheme outlining maturity attributes, levels, and level descriptors, reflecting a transparent theoretical and sound design process (Hoseini, Hertogh, & Bosch-Rekveldt, 2019). In recognizing the importance of such a scheme, Becker, Knackstedt, and Pöppelbuß (2009) has introduced a systematic approach to MM development, encompassing key steps such as problem statement, analyzing existing related MMs, iteratively developing and designing the model, and validating and implementing the model through case studies. This systematic approach is commonly observed in similar studies (Caiado et al., 2021; Das, Perera, Senaratne, & Osei-Kyei, 2023). In alignment with this scheme, Rashidian et al. (2022a) and Rashidian et al. (2023a) have conducted two studies comparing relevant BIM, IPD, and LC MMs. Furthermore, Rashidian, Drogemuller, Omrani, and Banakar (2023b) have identified a comprehensive set of attributes and sub-attributes for a BIM, IPD, and LC MM confirmed through two Delphi studies (Table 1). The present study incorporates the findings of Rashidian et al. (2023a, 2023b) and the BIL maturity attributes, given their relevance and recent publication.

Table 1. BIL maturity attribute definitions adopted from Rashidian et al. (2023a).

Attribute	Sub-Attribute
Customer focus	Flexible resources	Availability of multi-skilled staff to change the direction to meet the customer's needs by generating various alternatives without losing much time or money.
	Optimizing value	Maximizing the outcome of the project by understanding the customer's requirements. If the company clearly understands the customer's needs, it can plan accordingly and meet those needs efficiently.
	Recognition of the entire supply chain as the client	Taking everyone into account as a client.
Culture and people	Contribution by staff at all levels	Employees share their ideas/points of view to improve the company's processes and reduce waste. The organization hears all voices. Last Planner System and Pull Planning are valuable techniques for engaging the team members.
	Organization training support	Organizing and sponsoring the team in order to develop their BIM, IPD, and LC competencies and skills.
	Upper-level management buy-in	The company's managers’ willingness and support to implement an integrated BIM, IPD, and Lean in the organization.
	Early goal definition	Project goals are developed early, agreed upon and respected by all participants, and insight from each participant is valued.
	Open communication	Open, direct, and honest communication exists among all participants using shared platforms, e.g. BIM model, Lean techniques, & IPD contract-There is no blame culture since the responsibilities are fully communicated among the parties in an IPD contract.
	Leadership	Leaders are coaches instead of controllers. A leader is the most competent person who sets an example and walks the talk.
Workplace standardization	Visual management	The application of visual devices that communicate job status and requirements on schedule, quality, safety, and productivity to everyone (e.g. Kanban).
	5S implementation	5S is about creating visual order, organization, cleanliness, and standardization. This leads to better safety, more space, better teamwork, and constant improvement.
	Organization updates about the BIM Model	BIM information-sharing management requirements include model ownership, interoperability, IFC, the Common Data Environment (CDE), the Model Editor, and Federated Model Specification and Management.
	Just in time	Providing the right materials or information in the right quantities and quality when it is needed to reduce waste and provide maximum value.
	Big Room	Co-location and integrated meetings
Waste minimization	Defect	Incorrect work that needs to be repaired, replaced, or redone
	Over-Production	Producing more material or information than is required or earlier than is necessary
	Waiting	When any construction party is left waiting for labor, materials, equipment, or Requests for Information (RFI) responses to complete the preceding activity.
	Transportation and motion	Unnecessary movements of materials, equipment, or people can be avoided using collaborative decision-making techniques and BIM 4D and LC.
	Inventory	Providing information, supplies, or items beyond what the various disciplines require.
	Extra processing (Rework)	Coordination and administrative workflows on a construction project, leading to double data entry.
Continuous improvement	Metric	Metrics are used to monitor and improve all project processes, which must be consistent throughout time and simple for all staff to read and understand.
	Responses to defects	It refers to the effective management of problems and retention and documentation of the identified solutions for future use.
	Error proofing	Process of proactively eliminating errors from work. These precautions, by their nature, are proactive instead of reactive.
	PDCA implementation	Plan-Do-Check-Act to solve both unit-functional and cross-functional problems in their activities.

In response to Becker's scheme, the iterative design of the MM should not only encompass attributes but also extend to maturity levels, as these levels serve as integral components of the MMs. A maturity level is a well-defined evolutionary plateau leading to the development of mature processes (Sarshar et al., 2000). The construction-related MMs that have demonstrated a well-defined process for developing levels have often borrowed the structure of either the CMM or SPICE (Succar, 2009). The five levels of CMM are initial, planned, defined, managed, and optimizing. The SPICE framework also outlines the evolutionary progression into five maturity levels, including ad hoc, repeatable, defined, managed, and optimizing for construction processes (Akunyumu et al., 2020). According to SPICE, an organization can only be at one maturity level at any stage and move to the next level only if its main processes are deemed capable at the current level (Sarshar et al., 2000). As outlined in the CMM document provided by Team (2002), businesses perform best when they concentrate their process improvement efforts on a reasonable number of process areas at a time, and these areas demand greater sophistication as the organization's maturity grows to higher maturity levels. Notably, both CMM and SPICE have exhibited significant similarities in their characteristics, forming the foundation for developing the BIL maturity level descriptors (Figure 1).

Figure 1. Common themes derived from CMM (Paulk, 1995) and SPICE (Sarshar et al., 2000) Maturity levels.

In MM development, it is equally important to establish a set of metrics to increase their reliability and usability (Succar, Sher, & Williams, 2012). A similar strategy is utilized by Rodegheri and Serra (2020) and Yilmaz, Akcamete, and Demirors (2019). These metrics are determined mainly by analyzing the existing MM's characteristics, strengths, and limitations. Likewise, in the BIL MM development process, these criteria from the literature are extracted according to their limitations and strengths identified by Rashidian et al. (2023b). The characteristics are listed as ‘the ease of use and being intuitive’, being ‘adaptive’, ‘inclusive (Hard and Soft attributes)’, ‘holistic’, ‘having detailed attribute division’, ‘comprehensive reporting presentation’, ‘a clear description of the attributes’, ‘free self-assessment template’, and ‘availability of guidelines’ (Rashidian et al., 2023b). Consistently, studies by Sebastian and Van Berlo (2011) and Das et al. (2023) have underscored the importance of these criteria in MM development and implementation.

The literature review highlights the critical role of a structured approach in developing MMs, with iterative development and validation central to enhancing model reliability. Building on this foundation and guided by the principles of established frameworks such as CMM and SPICE, this study leverages these insights to develop a nuanced BIL MM.

Methodology

To address Becker et al.'s (2009) systematic approach to MM development, both qualitative and quantitative methods were essential. The structure of the BIL MM was developed based on attributes identified by Rashidian et al. (2023a). Subsequently, the maturity levels within the BIL MM were defined, drawing inspiration from established MMs such as CMM and SPICE. After the initial development phase, the BIL MM and its defined levels were introduced to participants through semi-structured interviews. In addition, the research team engaged in continuous literature reviews following each interview. This process was aimed at identifying additional evidence to further solidify the basis of the expert recommendations incorporated into the BIL MM.

Human Research Ethics Committee (HREC) approvals for human subjects were obtained from Queensland University of Technology, Australia, under the ethics approval number LR 2021-4623-5600. The recruitment approach for the entire study was evaluated by the HREC, receiving approval due to negligible risk to participants. Strategies were outlined to mitigate potential risks, including ensuring voluntary participation and the option for participants to withdraw at any time without consequence. Also, to de-identify the participants, they were assigned a unique code that was used consistently throughout the data collection and analysis process.

The purposive sampling technique was employed to extract substantial information regarding a BIL from a small number of well-selected participants. The objective was to ensure that the selected participants would offer valuable insights regarding the maturity level descriptors. Due to the COVID-19 pandemic or geographical distance, the interviews were conducted via Zoom video communications from June 2022 to November 2022 with the BIM, IPD, LC and MMs experts.

The respondents were top managers from a range of construction stakeholder companies across the world. Additional qualifying criteria included having about ten years of working experience in BIM, IPD, or LC implementation and, ideally, knowledge of the application of MMs. Potential experts were engaged through LinkedIn, events, and conferences, and additional experts were included through snowball sampling based on initial expert recommendations.

Out of 70 potential participants contacted, 13 individuals agreed to participate in the research study (Table 2). According to Creswell (2007), a sample size ranging from 12 to 30 participants for a heterogeneous group of interviewees is sufficient to ensure a wide spectrum of perspectives and experiences. This is in line with similar studies conducted by Aziz and Zainon (2022), Lamptey et al. (2021), and Babatunde, Perera, and Zhou (2016).

Table 2. Background of participants – Interview.

Participants	Profession	Years of Experience	Location	Expertise Area	Type of Organization
P1	Mechanical engineer	30	Australia	Lean, IPD	L
P2	Project manager	20	India	BIM, LC	L
P3	Quantity surveyor/ academic	30	Australia	BIM, LC, IPD	L
P4	Lean construction consultant	11	Hungary	BIM, MM	L
P5	Academic/architect	40	Australia	BIM, IPD, LC	L
P6	Civil engineer	40	Australia	BIM, IPD	L
P7	Civil engineer	37	Peru	BIM, LC	S
P8	Academic/ Construction manager	18	Australia	BIM, IPD/LC	L
P9	Construction manager	10	Brazil	BIM	L
P10	Architect/ IPD consultant	24	Canada	BIM, LC, IPD	S
P11	Architect	12	Australia	BIM	L
P12	Continuous Improvement/ Innovation manager	18	Australia	BIM, IPD, LC	L
P13	Construction management professor/Lean Construction consultant	42	Brazil	BIM, IPD, LC	L

P = Participant, S = Small enterprises, 10–49 employees, M = Medium-sized enterprises, 50–249 employees, L = Large enterprises employ 250 or more

Before initiating the semi-structured interview, the preliminary BIL MM was piloted through three intensive group discussions with the research team. The model was refined to best describe the levels for each attribute. The pilot study achieved the framework's verification and refinement and was then shared with participants. Each interview lasted approximately 1.5–2 hours. The researchers obtained respondents’ permission to record the interviews, and ethical principles were followed to ensure the privacy of respondents. During the interviews, experts evaluated the practices, tools, techniques, and processes detailed in each sub-attribute descriptor aimed at facilitating maturity progression at each level. Participants were also allowed to suggest modifications to the proposed attributes within the BIL MM.

Following the completion of the interviews, qualitative analysis was conducted using NVivo 11, as it allowed for efficient data organization (Das et al., 2023). After analyzing the interview data and refining the model, the updated BIL MM was distributed to the interviewees for further revisions. The feedback collected during the second round of interviews underwent thorough analysis to identify any elements that may have been overlooked during the initial round. These identified elements were then integrated into the model, enhancing its overall comprehensiveness. The framework validation and implementation are recommended phases of MM development to ensure its suitability for use in the relevant market and to ensure the quality of the research outcomes (Babatunde et al., 2016). A total of 47 new experts, comprising top managers from relevant organizations and academic specialists, were invited to participate in the survey. Of these, 13 experts responded to the survey. The decision to rely on a smaller group of experts is consistent with similar studies in the field, such as those by E Silva et al. (2024) and Babatunde et al. (2016). These studies indicate that smaller panels of highly qualified experts, particularly those with substantial experience and expertise, can provide reliable and relevant insights (Table 3). To validate the model, a questionnaire survey was carried out, utilizing criteria from Rashidian et al.'s (2023b) study. These criteria were refined to enhance precision and clarity for the participants. This involved revising the wording of the criteria, such as changing ‘inclusive (hard and soft attributes)’ to ‘Hard & soft criteria inclusion’. Lastly, two organizations (an Architecture company and a BIM consultant company) were requested to implement the BIL MM within their entities and evaluate their organizational performance in BIL implementation. To ensure unbiased evaluations, two managerial staff from each organization were selected to provide insights. This deliberate selection process highlights the significance of incorporating multiple viewpoints and managerial experiences within the organization, thereby mitigating the potential for project-specific biases. Before the evaluation commenced, the authors provided detailed guidance on interpreting the BIL MM, addressing any questions in a one-hour meeting to ensure participants were well-prepared.

Table 3. Background of participants – Validation.

			Validation – Survey participants
Participants		Profession	Years of Experience	Location	Expertise Area	Type of Organization
P1		Architect – project leader	12	Australia	BIM	M
P2		Quantity surveyor	35		Lean, IPD	S
P3		Consulting manager	5		BIM, IPD, LC	L
P4		Architect	20		BIM, LC, IPD	L
P5		Digital project manager	8		BIM, MM, IPD, LC	L
P6		Project manager – electrical engineer	20		BIM, MM, LC	L
P7		Construction manager/ academic	11		BIM, LC, MM	L
P8		Civil engineer	40		BIM, IPD	L
P9		BIM manager	13		BIM, IPD	L
P10		Postdoctoral research associate	5		BIM, IPD, LC	L
P11		Digital project manager	5		BIM, IPD	L
P12		Steel detailer / structural	30		BIM	M
P13		Digital engineering lead	15		BIM, IPD, LC, MM	L
BIL MM implementation participants
Company X	P1	BIM coordinator/ architect	10	Australia	BIM, IPD, LC	L
	P2	Senior architect /Team leader	13		BIM, LC	L
Company Y	P1	Digital project manager	5		BIM, IPD	L
	P2	BIM coordinator	5		BIM, IPD	L

P = Participant, S = Small enterprises, 10–49 employees, M = Medium-sized enterprises, 50–249 employees, L = Large enterprises employ 250 or more

According to Eadie, Perera, and Heaney (2011), achieving a higher maturity level in a specific attribute necessitates fulfilling all requirements of the preceding levels. Following this principle, participants were advised to consider advancing to higher maturity levels only when their organizations had met all criteria of the current level. To ensure confidentiality, the participating organizations were anonymized as X and Y; also, relevant details about the participants from those companies are provided in Table 3.

Results

This section presents the findings from semi-structured interviews and validation analysis, aiming to develop and confirm the characteristics of each sub-attribute's maturity level. The identified BIL Maturity levels included ad hoc, repeatable, defined, quantitatively managed, and optimizing. Maier, Moultrie, and Clarkson (2012) stressed the crucial importance of precision, emphasizing the need for clearly defined maturity levels accompanied by detailed descriptions to ensure clarity for users. This was achieved in the study by using well-defined terms and providing examples, thereby eliminating any ambiguity in the organizational assessment process.

After completing the interviews, recommendations were categorized and coded in NVivo. The initial category of comments offered insights into the overall characteristics of the BIL MM. For example, interviewees suggested adding more prescriptive descriptors to provide a roadmap for implementing BIL within an organization. According to Participant 1, ‘This could be effectively achieved by outlining a clear pathway for organizations to progress from the lowest to the highest level of maturity, ensuring a clear distinction between each level’. Interviewees also provided examples of LC techniques to clarify the benefits associated with each maturity level. Specifically, it was highlighted that LC tools like ‘Pull Planning’ (a collaborative scheduling method), ‘Just in Time (JIT)’ (for optimizing inventory timing and scheduling), and ‘Kanban’ (a visual task management system) could effectively reduce ‘Transportation and Motion’ waste within the ‘Waste Management’ attribute. Consequently, these techniques were incorporated into the ‘Transportation and Motion’ attribute.

In response to suggestions for enhanced specificity, certain attributes underwent refinement. For instance, the ‘Flexible Resources’ attribute was updated to ‘Adaptive Resources’ to better capture the ability of resources to adjust to the fluctuating demands of construction projects. This refinement led to the categorization of resources into ‘People’, ‘Tools’, ‘Technologies’, ‘Physical spaces’, and ‘Budget’, following the definitions provided by the CMM in 1993. Through this iterative process of refinement, the attributes were elaborated to include ‘Adaptive Multi-Skilled Personnel’, ‘Adaptive Hardware’, ‘Adaptive Software and Networks’, ‘Adaptive Physical Facilities’, and ‘Adaptive Budget’, resulting in a more detailed and comprehensive set of sub-attributes.

In the refinement process, several attributes of the initial model were combined following expert guidance to achieve an optimal balance between the total number of attributes and the model's granularity. Specifically, the ‘Big Room’ – a designated space for integrated meetings among project participants – was initially categorized as a sub-attribute of ‘Workplace Standardization’. The importance of the ‘Big Room’ adaptability to accommodate various work scopes was also highlighted as a crucial factor. This feedback led to the redefinition of this attribute, resulting in its integration into the ‘Adaptive Resources-Physical Places’ attribute within the BIL MM.

Additionally, it was underscored by Participant 3 that ‘ the effective adoption of integrated meetings and close collaboration in the “Big Room” necessitates staff training on cultural and behavioral aspects. Establishing clear expectations and guidelines for participation is essential, including the need for full engagement and availability during relevant discussions’. These insights further contributed to the comprehensive re-evaluation of the ‘Big Room’ attribute, ensuring its alignment with the broader objectives of ‘Adaptive Resources’ and ‘Workplace Standardization’ within the BIL MM.

Similarly, the ‘Recognition of the Entire Supply Chain as the Client’ sub-attribute was recommended to be integrated into ‘Optimizing Value’. As a result, only two primary sub-attributes were selected under the ‘Customer Focus’ attribute, namely ‘Adaptive Resources’ and ‘Optimizing Value.’

Additionally, there was a suggestion to introduce new terms for maturity levels 1–5 alongside the primary terms derived from CMM and SPICE. Consequently, the terminology was revised to include ad hoc (individual), repeatable (project), managed (organization and project), quantitatively managed (full organization awareness), and optimizing (cross-organization integration). It was also pointed out that the phrase ‘problems are identified through their root causes, and solutions are revisited continuously’ should be included in level 5 to emphasize the nature of optimization, which involves continuous improvement.

The review of individual attributes by the participants revealed additional interdependencies among attributes that were identified in Rashidian et al.'s (2023a) study. These interdependencies were incorporated into the maturity level descriptors to enhance clarity. For example, ‘VM’ was initially considered a separate attribute in the BIL MM; however, Participant 4 emphasized the importance of establishing visual metrics for ‘VM’ implementation within an organization. ‘The metrics’ visualization, such as job status or progress, facilitates clear communication channels and, as a result, increases transparency among the involved stakeholders, thus addressing the IPD principles’. The participants also recommended combining ‘VM’ tools with the ‘Big Room’ to facilitate more efficient and informative communication. As a result, these tools were utilized to enhance the description levels of the ‘VM’ attribute, with the interdependencies being directly integrated into it.

The ‘5S’ methodology, incorporated as an attribute for ‘workplace Standardization’ in the BIL MM, has traditionally been linked with the construction activities on site. However, interviews from this study revealed its potential in information management practices within organizations. This highlighted the versatility of the ‘5S’ approach and its potential applicability across different disciplines. Notably, the findings emphasized the role of ‘Management Buy-in’ as crucial for successfully implementing the ‘5S’ technique in information management practices. Additionally, the establishment of protocols and the assignment of leadership roles to oversee these protocols were recommended to ensure the successful implementation of ‘5S’.

By connecting ‘scheduling to 4D BIM’, the waiting time can also be reduced (Pérez & Bastos Costa, 2021). According to Participant 4, ‘utilizing this technique allows for a clear understanding of the network of commitments and eventually active management of the waiting time’.

In the initial BIL MM, ‘Defect Identification’ was categorized under ‘Waste Minimization’ attributes. This was later refined to ‘Construction Defect Identification’ to address constructability issues in projects more accurately. According to Participant 5, ‘The adoption of a visualized BIM model, with its extensive range from 3D to nD functionalities, is crucial for detecting defects early within the virtual model’. ‘Recognizing construction defects as a common occurrence in projects, it's essential for organizations to document these defects for future reference’. ‘Leveraging BIM's advanced data storage and sharing capabilities facilitates the precise documentation of construction defects, reducing rework and minimizing time and resource wastage’.

Upon completing the refinement of the BIL MM, the final version was presented to the same interviewees for additional feedback, resulting in minor adjustments. Figure 2 reflects the finalized attributes’ structure. An example of the BIL MM is also provided in Table 4.

Figure 2. BIL attributes’ structure.

Table 4. BIL Maturity Model structure example – Customer Focus.

Customer Focus
	Description	Initial (individuals)	Repeatable (project)	Defined (organization – project)	Quantitatively Managed (full organization awareness)	Optimizing (cross-organization integration)
Adaptive Multi-skilled people	The availability of multi-skilled staff to a) generate alternative solutions and b) respond to information flow requirements such as: OIR – Organizational Information Requirements PIR – Project Information Requirements EIR – Exchange Information Requirements AIR – Asset Information Requirements	Staff skills do not comply with customer requirements in the projects. Chaotic responses are in place to generate alternative solutions and respond to information flow requirements. During crises, projects typically abandon planned procedures. Success depends entirely on individuals.	Multi-skilled individuals are employed in a project with the ability to generate alternative solutions and respond to information flow requirements. The same crew of skilled staff is employed on similar projects.	Hiring policies are established in the organization to employ multi-skilled staff with BIM and LC skills to generate alternative solutions and respond to OIR, EIR, AIR, and PIR.	The performance of the multi-skilled staff in responding to customer requirements and generating alternative solutions to customer requirements is revisited and measured through the established metrics. Results are analyzed quantitatively. The actual results and the customer requirements are compared quantitatively to find the gaps in the organization.	IPD coordinators ensure the IPD hiring policy employs multi-skilled staff to respond to the dynamic nature of IPD contracts using BIM and LC techniques. Staff are chosen based on their adaptability and ability to work in a collaborative and dynamic environment. Continuous collaboration of all involved parties in an IPD contract results in quick analysis across all disciplines and evaluation of conformance to client requirements using BIM and LC techniques. Gaps are identified, root causes are communicated, and solutions are provided.

Validation stage

Following the distribution of the questionnaire, 13 individuals responded to the survey. Table 5 presents the mean scores obtained from the participants’ questionnaire responses. The significance of the nine validity statement criteria was examined in relation to the interpretation of the scale intervals including (1) ‘not important’ (mean score ≤ 1.5); (2) ‘fairly important’ (1.51 ≤ mean score ≤ 2.5); (3) ‘important’ (2.51 ≤ mean score ≤ 3.5); (4) ‘very important’ (3.51 ≤ mean score ≤ 4.5); and (5) ‘extremely important’ (mean score ≥ 4.51) (Li et al., 2013). This classification scheme for factors proposed by Li et al. (2013) was also adopted by studies comparable to this study, such as Olawumi and Chan (2020).

Table 5. BIL MM validation results.

Validation Criteria	Respondents													Mean
	1	2	3	4	5	6	7	8	9	10	11	12	13
Clear design process	5	5	4	3	4	5	4	5	5	4	5	4	4	4.38
Detailed attributes division	5	4	5	5	4	4	5	5	5	5	5	3	4	4.56
Hard & soft criteria inclusion	5	3	5	5	5	4	5	5	5	4	4	4	4	4.46
Ease of use and interpretation	5	5	5	2	4	5	5	5	5	4	4	3	3	4.23
Appropriate assessment scope	5	5	5	4	4	4	4	5	5	3	4	4	4	4.31
Broad stakeholders’ targets (Client, Designer, Constructor) (holistic)	5	5	5	4	5	5	4	5	4	3	5	4	4	4.46
A clear description of the attributes	5	5	5	4	5	5	5	5	5	4	4	4	4	4.62
Adaptive (different phases and work scope)	5	4	4	4	5	4	4	5	5	4	5	4	4	4.38
Appropriate reporting presentation	5	4	5	3	4	4	5	5	4	4	4	4	3	4.15

Questionnaires must be statistically analyzed to confirm their reliability and validity (Yusof and Aspinwall, 2000; Ghanbaripour, Langston, Tumpa, & Skulmoski, 2023). The reliability analysis was conducted using Cronbach's alpha, and the obtained value for the questionnaires in this study was 0.88, which exceeded the recommended minimum Cronbach's alpha value of 0.7, indicating that the questionnaire was reliable.

The ‘detailed attributes division’ scored the highest, with a mean of 4.56 among the nine validation criteria used for the framework’s evaluation. This indicates its comprehensiveness in capturing the nuances of BIM, IPD, and LC integrations. Furthermore, experts rated most validation criteria as very important, with mean scores ranging from 3.5–4.5, underscoring the framework's detailed approach. Therefore, these results affirmed the tool's effectiveness in robustly assessing BIL implementation.

Figures 3 and 4 present organization X and Y assessment results in spider diagrams, which are widely recognized as the preferred method for displaying results in MMs (Anthony & Antony, 2021). It should be emphasized that the organizations were not compared against each other; instead, their performance was assessed based on their individual results.

Figure 3. Company X – BIL MM implementation and evaluation results.

Figure 4. Company Y – BIL MM implementation and evaluation results.

Discussion

The BIL MM described in this paper is a further development of the Rashidian et al. (2023a) research, where the interdependencies of the BIL are determined through a Delphi study. This study takes a further step by using these interdependencies to develop the structure of BIL MM.

In this study, the BIL attributes and sub-attributes obtained from the Rashidian et al. (2023a) paper were restructured according to the interviewees’ recommendations. This restructuring led to the developing of a model consisting of 5 main attributes and 23 sub-attributes, which aligns with the recommended number of assessment criteria for the MMs in the Kaplan and Norton (2004) study.

This research addresses a significant gap by operationalizing BIM, IPD, and LC interdependencies within a practical MM. BIL MM is intended to be multidimensional and covers contractual, process, cultural, and technical attributes, overcoming the limitations of existing MMs that often approach these aspects in isolation. Given the emergence of new paradigms, such as Artificial intelligence (AI) and Industry 4.0, and their integration into the construction field for enhanced project delivery efficiency (Zhang, Chan, Darko, Chen, & Li, 2022), further research is recommended to identify relevant attributes and incorporate them into similar MMs.

The BIL MM is distinguished by applying a systematic method for defining maturity levels, drawing on the structure of the SPICE and CMM models. Unlike numerous existing MMs that often lack a solid theoretical foundation and uniform structuring of maturity levels, BIL MM provides organizations with a structured pathway to elevate their practices to a higher level of maturity.

A further feature distinguishing the BIL MM is its detailed focus on the ‘Customer Focus’ attribute, specifically addressing the roles of construction parties and their requirements, aspects that have received limited emphasis in past research. In this MM, the concept of a customer extends beyond the traditional view of just being the project client. Instead, it follows the Lean concept that the customer is any party receiving the outcomes of other parties. In this context, and over the restructuring process, the concept of ‘Recognizing the Entire Supply Chain as the Clients’, recommended by Rashidian et al. (2023a), is incorporated into the ‘Optimizing Value’ attribute of BIL. This integration ensures that all resources can optimize the supply chain's value and address their specific requirements. These requirements encompass various information needs, including Organizational Information Requirements (OIR), Project Information Requirements (PIR), Exchange Information Requirements (EIR), and Asset Information Requirements (AIR). These requirements, absent in other relevant MMs, have been integrated into the refined BIL MM version within the ‘Customer Focus’ description. This inclusion aims to provide users clarity and enhance the model's comprehensiveness.

The study reveals that the BIL MM's attributes, particularly ‘VM’, ‘Contributions by all staff’, ‘Just-In-Time’, and ‘Adaptive resources’, are key in building trust and collaboration in projects and effective IPD implementation.

In the BIL MM, an unexpected result emerged regarding the ‘Non-Utilized Talent’ attribute. Initially included but subsequently removed in the original Rashidian et al. (2023a) study, this attribute was reconsidered following recommendations from interview participants. The suggestion was to incorporate aspects of this attribute into the ‘Roles and Responsibilities’ sub-attributes associated with the ‘People and Culture’ attribute. This integration strategically defines and assigns responsibilities among staff, ensuring optimal utilization of talent and minimizing instances of non-utilized waste.

The successful implementation of the BIL MM requires assembling a team with expertise in BIM coordination, IPD, and LC execution. This team's collective expertise is crucial for an accurate organizational assessment. This group should make decisions on each attribute collaboratively, with the outcomes typically displayed in a spider diagram.

Conclusion

The Building Information Modelling-BIM, Integrated Project Delivery-IPD, and Lean Construction-LC (BIL) Maturity Model (MM) presented in this study addresses a significant gap in existing MMs by providing a comprehensive and multidimensional assessment tool. It supports organizations engaged in IPD projects by fostering informed, data-driven decision-making. This enables these organizations to define their standpoint and also understand the maturity level of selected parties, fostering a better comprehension of areas of compatibility.

Prior to this paper, there was no evidence regarding the maturity level required by construction organizations for effective BIL implementation. This lack of information resulted in a deficiency in understanding the necessary transitional steps toward the BIL implementation. This study, however, has positioned the BIL MM not only as a tool for analyzing an organization's current capabilities in BIL implementation but also as a step-by-step guide for organizations to identify their limitations and strengths and plan for future performance improvement. This is especially necessary in the constantly evolving construction industry, where adaptation and forward planning are critical to maintaining competitiveness and attaining sustainable growth. BIL also enables organizations to effectively communicate performance to internal and external stakeholders and respond continuously to the needs of all concerned parties.

BIL MM predominantly utilized the methodology Becker et al. (2009) employed when developing the MMs to ensure scientific rigor and practical applicability. The designed BIL MM, its attributes, and maturity levels were examined through iterative semi-structured interviews with experts.

BIL MM comprises five principal attributes: ‘Customer Focus’, ‘Culture and People’, ‘Workplace Standardization’, ‘Waste Minimization’, and ‘Continuous Improvement’, and includes both technical and human-related aspects. Each attribute further includes a range of sub-attributes, evaluated against five maturity levels: initial (individuals), repeatable (project), defined (organization-project), quantitatively managed (Organization Full awareness), and optimizing (cross-organization integration). The BIL MM comprehensively explains attributes, sub-attributes, and maturity levels, aiming to mitigate the inherent subjectivity commonly observed in existing MMs in the literature.

The development of the BIL MM also involved a validation survey and implementation in two organizations, addressing previous critiques regarding the absence of well-defined MM design processes and validation. This rigorous approach underpinned the reliability and applicability of the BIL MM in real-world settings, ensuring that industry practitioners can effectively utilize it. The results from the validation survey indicated that the BIL MM could be applicable to a wide range of stakeholders, including clients, designers, and constructors.

As with any research, this paper also has some limitations. The critical role of macro-level factors and their contribution to the micro-level implementation of BIL has been outside the scope of this study. It can be addressed according to the market characteristics worldwide to determine whether there are substantial differences in BIL maturity in different contexts.

This paper is based on the published English MM literature. Future research can include MMs with other languages in their investigations.

This study highlights that BIL MM is primarily intended for the essential IPD stakeholders: the client, designer, and builder. During the validation phase, a BIM consultant party utilized the BIL MM as well and found it highly advantageous for their specific requirements. In order to enhance the overall applicability of the suggested model, it is imperative to conduct further studies on the implementation of BIL, thereby evaluating its applicability for a wide range of stakeholders.

This study primarily utilized data from Australian participants due to their willingness to participate while engaging experts worldwide. Future research should encompass a more diverse range of locations to enhance generalizability. It is essential to acknowledge that expert experiences may have influenced the data, potentially affecting result interpretation, and researcher biases may have played a role in study analysis. Also, the proposed BIM, IPD, and LC practices in the BIL MM are examples of existing practices. With a wide range of interchangeable options available, future studies can adopt similar practices as appropriate and applicable to their specific contexts.

This study also suggests future research to investigate more detailed subdivisions of the proposed attributes, which could include emerging technologies and concepts such as Artificial Intelligence (AI) and related techniques with the ability to facilitate automation.

Disclosure statement

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

Additional information

Funding

This research is supported by Building 4.0 CRC and an Australian Government Research Training Program (RTP) Scholarship. Ethics approval for this study was granted by the Queensland University of Technology University Human Research Ethics Committee (UHREC) reference number: LR 2021-4623-5600.