IntroductionOff-site manufacturing (OSM) refers to the construction method of assembling building components in a factory and transporting them to the construction site for final installation (Goodier and Gibb 2007). Compared with traditional construction, OSM can significantly improve productivity and speed up project delivery through achieving a higher level of resource utilization and allowing the off-site production and on-site construction works to be conducted concurrently (Boyd et al. 2013; Hanna et al. 2017; Ko and Wang 2010; Panjehpour and Ali 2013; Tam et al. 2007). OSM has been recognized as a promising solution to address the shortfall of affordable housing demand globally (Thompson 2019). With the rapid development of advanced information technology (IT) in recent years, numerous efforts started employing building information modeling (BIM), which refers to the collaborative process of creating, sharing and utilizing information of the building life cycle (Eastman et al. 2011), in OSM projects. The integration of BIM and OSM brings benefits such as improving information exchange and modeling (Nawari 2012), addressing schedule delay problems (Li et al. 2017), and managing production flows (Arashpour et al. 2018).In response to the increasing housing demand in New Zealand (NZ), the Ministry of Business, Innovation and Employment (MBIE) has set policies and plans to prioritize the development and use of OSM (MBIE 2018). However, the benefit of speedy delivery of OSM projects cannot be fully realized due to current bottlenecks with manual compliance checking processes, which are labor intensive, time consuming, and error prone (Dimyadi and Amor 2013). Furthermore, unlike conventional processes, OSM requires the preapproval of various functional components before the final installation. The performance-based NZ regulatory framework can support the unique compliance requirements of OSM. The NZ Building Code (NZBC) enables innovative design, engineering, and construction processes to be explored and implemented without the need to follow rigid and often overly conservative prescriptive rules (Dimyadi et al. 2020). However, the performance-based design presents its own challenges due to the iterative peer-review process that can take weeks to months to complete, particularly if there are differences of opinion among peer reviewers, which may add uncertainties to the project delivery timing. Undesired iteration cycles can be a major cause of project delays and cost increases in construction planning (Preidel and Borrmann 2016). Additionally, OSM is a nonlinear construction process that shifts complex compliant design and construction tasks to the early stages, thus preventing design changes downstream. It also involves early site preparation for storage of modular components, simultaneously running of logistics, and both off- and on-site work (PrefabNZ 2018b). Consequently, OSM needs to not only meet the performance outcomes of the NZBC, but must also satisfy a wider range of requirements, including those in the Manufactured Modular Component Guidance in New Zealand (Auckland Council 2020) and the Handbook for the Design of Modular Structures in Australia (James et al. 2017).BIM enables automated compliance checking (ACC) of building designs (Choi and Kim 2008) by sharing machine-readable building data to support automated compliance decisions (Martins and Monteiro 2013). To date, most modern ACC approaches rely on BIM as the essential data input to supply geometric and semantic information with adequate level of details (Costin et al. 2018). A common methodology is to convert proprietary BIM models into the international BIM standard (Sadrinooshabadi et al. 2020) format, namely, Industry Foundation Class (IFC), and then to check this model using predefined rules (Malsane et al. 2015). According to Eastman et al. (2009), modern ACC approaches often follow a four-stage process, namely (1) rule interpretation, translation, and logic structuring; (2) building model preparation with the required level of details; (3) rule execution and checking; and (4) reporting of the results. In recent years, the industry has seen the emergence of novel ACC approaches and the start of promising commercial implementations.Integrating ACC into OSM workflows has the potential to improve productivity and expedite project delivery. However, the OSM industry is generally not familiar with ACC processes, and little is known about how well ACC technology can serve the OSM industry. Because OSM has a unique set of workflows that is different from traditional construction methods, there may be challenges in adopting ACC technologies in OSM projects. Specifically, this study addresses the following research questions (RQs): •RQ1: What is the current status of BIM adoption in the NZ OSM industry?•RQ2: To what extent are OSM stakeholders aware of the potential of ACC?•RQ3: What actions can boost the adoption of ACC technology in the NZ OSM industry?The rest of this article is organized as follows. The next section reviews the literature on the integration of OSM and BIM, regulatory compliance processes, and the general adoption of ACC technologies. This is followed by the overall research design and methods, which are then followed by the results. The final two sections present discussions and conclusions of the research findings.Background and Literature ReviewTo provide context for the research reported in this paper and support the design of the survey questionnaire, this section briefly reviews relevant literature from the following aspects: (1) OSM and BIM, (2) the current regulatory compliance checking process, and (3) adoption of ACC technologies.OSM and BIMDue to an increased demand for the speedy delivery of new buildings, OSM has experienced steady growth in NZ since the beginning of the twenty-first century. According to PrefabNZ (2018b) and Kennerley (2019), there are five types of OSM in NZ, namely (1) components, (2) panels, (3) volume, (4) hybrid, and (5) complete buildings. Components and panels are two-dimensional (2D) prefabricated units that do not enclose usable spaces (Bertram et al. 2019). Components are small-scale items assembled off-site such as structural components. Panels refer to planar units that include windows, doors, and integrated services. Volume, hybrid, and complete buildings are three-dimensional (3D) prefabricated units that enclose usable spaces, such as building modules, pods, and complete building units, which are typically fully finished internally and can be directly installed on-site (Kennerley 2019; PrefabNZ 2018b).Although the application of different OSM types is not limited to any specific building types, it was found that components and panels are best suitable for residential construction, modular prefabrication is ideal for highly serviced areas, and complete buildings are most suited for portable or temporary applications (Shahzad et al. 2014). BIM aligns with the core integration concept of OSM, which enhances the design processes through early stage decision-making, detail optimization, clash detection, better coordination, and effective communication (Bonenberg et al. 2018; Ramaji and Memari 2015; Samarasinghe et al. 2015; Sharma et al. 2017; Singh et al. 2015; Solnosky et al. 2014); facilitates seamless and timely information exchange between designers and manufacturers; and minimizes design errors and discrepancies between the design and final products and enhances mass customization (Mostafa et al. 2020; Singh et al. 2015).The Current Regulatory Compliance Checking ProcessThe performance standard of all NZ buildings is legislated by a three-tier building control framework [i.e., Building Act, Building Regulations, and Building Code (MBIE 2014)]. The NZBC is part of Building Regulations and stipulates detailed provisions that all building works must comply with. Typically, all construction projects in NZ are required to comply with regulations from eight sections or technical clauses of NZBC, which are (1) general provisions, (2) stability, (3) protection from fire, (4) access, (5) moisture, (6) safety for users, (7) services and facilities, and (8) energy efficiency (MBIE 2014). NZBC is a performance-based code and sets out functional and performance objectives that every building must achieve. Each technical clause in the NZBC is accompanied by a set of prescriptive compliance documents known as the Acceptable Solutions (AS) and Verification Methods (VM), which represent industry best practice minimum requirements and compliance solutions for a range of scenarios. Satisfying the full extent of any AS or VM is deemed to comply with relevant performance objectives of NZBC. Given the performance-based nature of the NZBC, building designers can decide to propose innovative alternative solutions, subject to formal justifications, a peer-review process, and sometimes judicial rulings.A building consent is typically required before any physical construction works can commence (PrefabNZ 2018b). It is a formal approval issued by the Building Consent Authority (BCA), confirming that the proposed design and construction solution complies with the building code and relevant normative standards. The evidence of compliance is generally provided in the form of design drawings, calculations, and supporting documentation. For building projects involving OSM, both off- and on-site works must be included in the building consent application. In addition to the overall mandatory compliance with the NZBC, OSM projects also need to demonstrate componentry compliance that must align with the project execution, which adds another level of complexity for compliance checking. Particularly, there is a need to manage the iterative process of specifying building component details by integrating information from suppliers, contractors, and subcontractors at different stages of the process (Gbadamosi et al. 2020). Tolerance of parts should be carefully considered in the design for manufacture and assembly (DFMA) process, in which standardized tolerance values learned from previous projects can be used as references to check the buildability for similar construction scenarios in new OSM projects (Shahtaheri et al. 2017). As suggested by Manufactured Modular Component Guidance in NZ, internal fixtures and fittings (e.g., toilet, shower, cabinets and doors, bed, wardrobe, and desk) should be fastened to avoid any potential damage during transit (Auckland Council 2020). Such information should ideally be proposed and checked in the design drawings or models and inspected at the site of manufacture. The Handbook for the Design of Modular Structures (James et al. 2017), a guide for OSM and DFMA in Australia, specifies both regulatory and nonregulatory compliance requirements in the aspects of structure, building services, fire, acoustics, sustainability, facades, architecture, materials and manufacture, durability, safety, transportation, erection, temporary works, inspection, verification, disassembly, and recyclability.Conventional approaches to demonstrating building code compliance in construction projects rely much on manual undertakings (Eastman et al. 2009; Malsane et al. 2015; Nawari 2019; Nguyen and Kim 2011; Preidel and Borrmann 2016; Tan et al. 2010; Zhong et al. 2012). Normative (legislative, regulatory, and contractual) provisions are all conventionally conveyed in natural language subject to human interpretation. The inevitable variations in the interpretation of normative provisions among different people are a common problem. Although the official interpretation of NZBC in the form of a handbook is available, there are still gray areas that may arise from time to time depending on the project. This has posed a challenge, particularly when different experts from different disciplines use inconsistent or nonstandard terminologies when assessing compliance of a given design (İlal and Günaydın 2017). The undesirable iteration cycle of modifications among different evaluators can be a significant factor for project delays and cost escalation in construction planning (Preidel and Borrmann 2016). Moreover, the manual compliance checking practice usually demands face-to-face meetings, which can be considered inefficient due to the overwhelmingly huge volume of project information and design criteria to discuss and negotiate (Nguyen and Kim 2011). The process requires designers and evaluators to have a reasonably high level of skills as well as familiarity with the relevant regulations (Tan et al. 2010; Zhong et al. 2012). In later stages of the construction projects, errors in building code compliance checking can potentially cause design changes that induce high and long-term costs of rework (Nguyen and Kim 2011), and sometimes even loss of life.Adoption of ACC TechnologiesSome of the earlier ACC implementations include Construction and Real Estate Networks (CORENET’s) e-PlanCheck in Singapore, the Solibri Model Checker (SMC) in Europe, SMARTcodes in the US, and DesignCheck in Australia (Ding et al. 2006; Khemlani 2005; Nawari 2011; Solibri 2020). However, most have not served the industry as intended, and some have not stood the test of time. For example, the CORENET e-PlanCheck was considered relatively successful since government agencies as well as industry stakeholders were involved in achieving digitalization of the building plan submission and the checking and approval processes (Goh 2007). Unfortunately, it has not been fully utilized for various reasons. DesignCheck aimed to automate the compliance checking process with the Australian accessibility building code in the early 2000s, but it was not taken up by the industry, and no further development has been undertaken.In recent years, the construction industry has seen the emergence of novel ACC approaches and the start of promising commercial implementations. The timeline of the development of various ACC approaches over the last half of the twentieth century has been summarized by Dimyadi and Amor (2013). These ACC approaches follow different technical routes, for example, language-based rule interpretation (Dimyadi and Amor 2017; Dimyadi et al. 2017; Lee et al. 2015, 2016; Park et al. 2016; Preidel and Borrmann 2015, 2016, 2017; Solihin and Eastman 2016), linked-data and semantic technology (Beach et al. 2015; Bouzidi et al. 2012; Bus et al. 2018; Dimyadi et al. 2016; Jiang et al. 2019; Lu et al. 2015; Yurchyshyna et al. 2007; Zhong et al. 2012), rule engines (Beach et al. 2013; Kasim et al. 2013; Lu et al. 2015), and natural language processing (Zhang and El-Gohary 2014, 2017, 2019). Additionally, although most ACC approaches rely heavily on BIM data as input (Costin et al. 2018), a number of construction projects, especially in developing countries, still use 2D drawings. It was observed that there are efforts trying to extract essential information from 2D drawings and establish 3D semantic understanding of the construction project (Elyan et al. 2020; Zhao et al. 2021), which can then support ACC purpose (Wang et al. 2021) [e.g., an artificial intelligence-based ACC system for 2D drawings by Vanyi Technology Ltd. (2021)]. In NZ, a novel human-guided automation employing a workflow-driven approach, known as the Automated Compliance Audit of Building Information Models (ACABIM) approach, has recently been implemented commercially. ACABIM was used successfully in a pilot project on BIM-enabled consenting by a BCA (Amor and Dimyadi 2021).Currently, ACC is usually the task of designers and BCAs. ACC brings direct benefits to designers and BCAs through checking design solutions against regulatory requirements and suggesting any identifiable inconsistencies and noncompliance (Lee 2021). This is further facilitated by a global transition from paper-based documents to digital data [e.g., Computer aided design (CAD) drawings, BIMs, and digital documents] for checking and approving designs online. For example, the Korean government has funded the development of a BIM-based electronic-submission system to support their national building permitting processes (Kim et al. 2020). The local governments in China have been collaborating with technology firms to develop and online systems for checking building designs against building codes (Wang et al. 2021). Similar attempts have been reported in Norway and Singapore (Hjelseth 2015b). ACC has applications in all stages of a project life cycle [e.g., automatic identification of fall hazards through checking BIM against the rules from Occupational Safety and Health Administration (OSHA) (Zhang et al. 2013), and checking of construction operation plans (Salama Dareen and El-Gohary Nora 2013)].To date, ACC systems have not been broadly used in the construction industry (Beach et al. 2020). Although previous studies (Amor and Dimyadi 2021; Dimyadi and Amor 2013; Eastman et al. 2009; Hjelseth 2015a; Krijnen and Van Berlo 2016) reviewed ACC software development and implementation, they were all technology-focused and did not provided insights into other nontechnological challenges. For example, Amor and Dimyadi (2021) summarized that ACC development has focused on “addressing challenges in sharing digital architectural and engineering design information, formalizing normative provisions as computable rules, and methods of processing them for compliance.” Despite the technology development, literature (Lee et al. 2003; Tornatzky et al. 1990) has revealed factors such as human perception and policies significantly contribute to any successful adoption of new technology. A recent survey study by Beach et al. (2020) ascertained a set of obstacles that prevented the wide adoption of ACC in the whole built environment and proposed a vision for future ACC development and implementation. However, this research focused on the wider built environment in the United Kingdom (UK) context and was limited by only surveying industry professionals who might not be familiar with ACC. This paper aims to narrow this gap that no existing studies measured the NZ OSM industry’s readiness for ACC, learned lessons from global efforts on ACC adoption, and explained a strategic roadmap toward wider ACC adoption for NZ OSM industry.Research Design and MethodsGiven the abstract nature of the research topic, this study adopted a qualitative approach (Creswell 2009) and collected data through literature review, expert interviews, questionnaire surveys, and focus groups. The research was carried out in three main stages, as presented in Fig. 1.Stage 1: Understanding ACC Adoption from LiteratureIn the first stage, a comprehensive literature review of ACC technology was conducted, and its results were used to design a preliminary version of the questionnaire. The questionnaire was semistructured and consisted of a total of 22 questions in four sections. Section “Introduction” aimed to collect the participants’ personal information regarding their specialization and experience with OSM projects. Section “Background and Literature Review” was about the NZBC and existing compliance checking processes. The shortcomings in the current practice of building code compliance were explored through questions about the most challenging sections of NZBC, and the specific tasks or aspects of the building code compliance process that need to be improved. The participants were then invited to provide a number of problems that they believed could be resolved by ACC technology. In this section, the participants were also asked to provide an estimate of their time and effort spent on the manual building code compliance processes and any alternative (semi)automated solutions they are using. Section “Research Design and Methods” was designed to answer RQ1, which investigated the current state of the BIM uptake in the NZ OSM industry because BIM is highly relevant and essential for modern ACC approaches. The participants were asked to rate the use of BIM in their design processes, the significance of the benefits brought by BIM, how much they use BIM in code compliance checking, and the most critical barriers to BIM use in OSM projects. Section “Research Findings” aimed to answer RQ2 through investigating the participants’ perception of integrating ACC into their existing practices and collecting their suggested actions to promote the adoption of the ACC technology for OSM projects. They were asked whether they saw a need to automate the process and whether they thought that the automated compliance with NZBC could benefit OSM projects, their business, and the whole NZ OSM industry. This section also asked the participants what key stakeholders and governments should do in order to promote the adoption of ACC technology for OSM projects.The questionnaire was designed for industry professionals with experience in defining compliance requirements, designing OSM products in accordance with regulatory building code and nonregulatory requirements, or assessing OSM projects against compliance requirements. Since not all respondents were expected to have knowledge and experience in all three areas (BIM, ACC, and OSM), most of the key survey questions were set as optional to ensure that the respondents could provide input to the questions they had the confidence to answer. Selectable options were summarized from the comprehensive literature review. For example, in Section “Introduction,” the selectable options for the question “What type(s) of OSM are included in your company’s business scope?” were supported by the “Capacity and Capability Report” of PrefabNZ (2018a). In Section “Research Design and Methods,” the selective options for the question “What do you think are the most critical barriers that limit your adoption of BIM in OSM projects?” were summarized from Ahmed (2018), BAC (2019a, b), Ghaffarianhoseini et al. (2017), Pezeshki and Ivari (2018), Sun et al. (2017), and Vass and Gustavsson (2017). Most questions also provided the option of other to allow respondents to express their own views through additional comments, thus improving the quality of the survey results. In particular, before the respondents were invited to answer the questions in terms of ACC, a visual workflow was added into the survey to assist their understanding on how ACC technology works.Stage 2: Understanding the Awareness and Readiness for ACC TechnologyIn the second stage, a pilot survey was conducted first. Since the questionnaire was semistructured, a pilot study was critical for the preparation of data collection (Yin 2011) and can ensure the reliability and validity of the final questionnaire survey. Eight industry experts (Table 1) with good knowledge in BIM, OSM, and NZBC were invited to complete the preliminary questionnaire, and their responses were then carefully analyzed to find out (1) the inconsistency in the survey design, (2) any flaws in specific questions, and (3) any missing questions or predefined answers. The same experts were then invited to participate in semistructured interviews (each lasted around 1.5 h) to provide additional information and comments related to their answers. The interviews had two purposes. First, they helped the research team understand the rationale and gain in-depth knowledge about their responses to further improve the questionnaire. Second, they provided in-depth insights that complemented the final questionnaire survey. Each interview was recorded properly and then transcribed.Table 1. Interviewee profile (survey study)Table 1. Interviewee profile (survey study)Interviewee No.PositionIndustry segmentArea of expertise1AaDirectorArchitectNational leading architect with >10  years of experience in both traditional and OSM projects1BDirectorArchitectNational leading architect with >15  years of experience in both traditional and OSM projects1CDirectorArchitectNational leading architect with >10  years of experience in both traditional and OSM projects1DSenior architectArchitectA senior architect with >5  years of industry experience1EaDirectorEngineering consultancyNational expert with >15  years of experience as civil/structural engineer1FaDirectorManufacturerInternational and national expert in NZBC and OSM. Held responsibilities for delivering many large OSM projects in NZ1GPrincipal urban plannerBCANational leading expert and practitioner in NZBC relating to town planning1HaBCA officerBCANational expert in NZBC and BIM, with nearly 10 years of experience in assessing building consent applicationsThe questionnaire was then refined and distributed to the NZ OSM industry. Purpose-based convenience sampling strategy (Etikan et al. 2016; Javid et al. 2022) was employed to control the quality of the data collection. Participants were selected based on the following two criteria: (1) all participants are working in the OSM industry in NZ; and (2) they are OSM professionals who also have good knowledge in digital design and construction (e.g., BIM, ACC). A total of 160 OSM professionals from Off-siteNZ, a professional OSM association in NZ, were invited by email for the questionnaire survey and a total of 45 respondents completed the survey. The experience, roles, and backgrounds of the respondents had a reasonably even distribution, as shown in Fig. 2. Among the 45 respondents, 16% were from the government (including BCAs); 18% were clients; 23% were architects and designers; 14% were engineers; 27% were manufacturers, fabricators, suppliers, subcontractors, and builders; and 2% were real estate agents. After removing one response from a real estate agent, 44 valid responses remained with a valid response rate of 27.5%. This is higher than the general response rate of surveys (10%–15%) in Singapore (Teo et al. 2007), which has similar population size to NZ. The sample size and response rate were comparable to a previous study (Beach et al. 2020) that received 66 responses in the UK (with 10 times the population of NZ). Therefore, the sample size was considered satisfactory for the analysis.The survey results were analyzed using the SPSS Statistics version 27.0 software (IBM 2021) and displayed as tables or charts. Nominal data obtained from multiple-choice and checkbox questions were analyzed by descriptive analysis such as percentages and frequencies. Ordinal data could be interpreted by assigning integers to the response categories to represent the level of agreement to certain statements and taking the median of the integers to show the overall trend (Harpe 2015). The qualitative answers to open questions were grouped based on respondents’ perspectives on the problem. For questions in which the qualitative answers had very clear categories, semiquantitative analysis was performed to interpret the responses. The summary of the qualitative responses provides supportive evidence for the quantitative results.Stage 3: Developing a Strategic Roadmap to Facilitate ACC AdoptionStage 3 aimed to answer RQ3. It was conducted to learn about international efforts on ACC adoption and transfer evidence-based knowledge and experience to NZ to develop a strategic ACC adoption roadmap for the OSM industry, including (1) interviews, (2) conceptual roadmap development, and (3) focus groups (FG).Purposeful sampling (Palinkas et al. 2015) was used to identify and select interviewees who had rich knowledge and experience related to ACC adoption. To ensure the interview data could be situated within the context of this research, the selection of interviewees was governed by the following three sampling criteria: (1) experts should have direct experience in the development or testing of at least a functional ACC prototype system that can fully or partly automate the regulatory compliance processes; (2) experts should have real ACC adoption experience (e.g., the ACC system was tested in a pilot project); and (3) ACC adoption experience shared by the experts must have the involvement of multiple key stakeholders. A total of 16 individual interviews (each lasting around 1 h) was conducted through video conference with ACC experts from Australia, China, Denmark, Netherlands, NZ, Norway, Singapore, South Korea, and the United Kingdom. The profile of interviewees and key interview questions can be found in Tables 2 and 3, respectively. The interview transcripts were sent back to the interviewees for checking, which is a critical technique for building credibility in qualitative research (Lincoln and Guba 1985). No major modifications were suggested. These interviews were grouped based on respondents’ countries because each country has its unique characteristics in terms of policy, building code, regulation system, building typology, building consent processes, stakeholder requirements, and so forth. The data for each country was initially studied separately such that the data can be refined using content analysis in two cycles of coding. The first cycle of coding was structural coding, which resulted in defined codes from the data matrix being associated with multiple subcodes. The second cycle of coding was focused coding. Based on the results of the first coding, the most outstanding codes were identified, and themes were developed (Saldaña 2021). Once the data for each country was analyzed and refined, a cross-country analysis took place following the recommendations of Miles et al. (2014).Table 2. Interviewee profile (roadmap development)Table 2. Interviewee profile (roadmap development)Interviewee No.ProfessionCountryACC experience2AAcademic researcherAustraliaInternational leading ACC expert who was involved in the development of an early ACC system in Australia2BDesignerChinaDesign engineer who was involved in a major ACC pilot project in China2CBCA officerChinaBCA officer who was involved in a major ACC pilot project in China2DAcademic researcherChinaEmerging researcher with >3  years of ACC research experience2EACC technologistChinaNational leading ACC expert who was involved in the development of ACC software in China2FAcademic researcherDenmarkEmerging researcher with >4  years of ACC research experience2GACC technologistEstoniaNational leading ACC expert who was involved in the development of ACC software in the Netherlands/Estonia2HACC technologistEstoniaNational leading ACC expert who was involved in the development of ACC software in Netherlands/Estonia2IBCA officerNZBCA officer who was involved in a major ACC pilot project in NZ and conducted a research project on ACC at master level2JStandard expertNZNational leading standardization expert2KStandard expertNZNational leading standardization expert2LaAcademic researcherNZInternational leading expert with >30  years of ACC research experience2MOSM expertUKOSM expert who had project experience in both the UK and NZ2NAcademic researcherNorwayInternational leading expert with >15  years of ACC research experience2OAcademic researcherSingaporeInternational leading expert who was recently involved in a major ACC development project in Singapore2PACC technologistSingaporeInternational leading expert with >20  years of ACC research and development experience2QAcademic researcherSouth KoreaInternational leading expert with >14  years of ACC research and development experience2RAcademic researcherUKInternational leading expert with >10  years of ACC research and development experienceTable 3. Key interview questions (roadmap development)Table 3. Key interview questions (roadmap development)No.Questions1What were the specific reasons motivating the development/use of ACC technology?2What were the challenges in promoting the use of ACC? How did you solve the problems?3What technology improvements will enhance the ACC adoption?4What were the top factors to the success of ACC uptake?5What were the main barriers that prevented ACC uptake?Based on the content analysis of the interview data obtained from the previous step, a conceptual roadmap was proposed to improve the understanding of lessons learned from global ACC adoption. The roadmap specifically attempted to describe key actions in a timeline for facilitating wider ACC adoption.To validate and refine the proposed roadmap, nine industry experts in the positions of BCA officer, design directors, project manager, and BIM specialist attended a FG. Five out of the nine experts participated in interviews in previous stages, and the rest of the experts were identified and invited for their good knowledge in BIM, OSM, and NZBC. The FG was held online through video conference for around 3 h and focused on (1) finding missing and inappropriate items, and (2) improving time-sequential relationship of suggested actions to finalize the roadmap. The experts were also asked to comment if there was any customization needed to the roadmap for NZ OSM industry. The discussion was recorded properly and then transcribed. All suggestions were extracted from the transcribed data and used to improve the roadmap. For instance, Interviewee 2L suggested extending the action (technology firms improve ACC maturity) to be included in all stages because technology is never perfect and always needs improvement. Interviewee 1H recommended removing the action (BCA to simplify building consent assessment) since this is more like an outcome rather than a prerequisite for ACC adoption. The improved roadmap was then emailed to all FG experts who were asked to check the roadmap and confirm no further changes were needed.References Abd Samad, S., A. N. Harun, M. N. M. Nawi, and N. A. Haron. 2018. “The potential use of BIM through an electronic submission: A preliminary study.” Malaysian Constr. Res. J. 3 (1): 82–96. Ahmed, S. 2018. “Barriers to implementation of building information modeling (BIM) to the construction industry: A review.” J. Civ. Eng. Constr. 7 (2): 107–113. Aksenova, G., A. Kiviniemi, T. Kocaturk, and A. Lejeune. 2019. “From Finnish AEC knowledge ecosystem to business ecosystem: Lessons learned from the national deployment of BIM.” Construct. Manage. Econ. 37 (6): 317–335. Arashpour, M., Y. Bai, V. Kamat, R. Hosseini, and I. Martek. 2018. “Project production flows in off-site prefabrication: BIM-enabled railway infrastructure.” In Proc., 35th Int. Symp. on Automation and Robotics in Construction (ISARC), 80–87. Berlin, Germany: International Association for Automation and Robotics in Construction. Auckland Council. 2016. Auckland unitary plan. Auckland, New Zealand: Auckland Council. Auckland Council. 2020. Manufactured modular component guidance. Auckland, New Zealand: Auckland Council. (BAC) BIM Acceleration Committee. 2019a. BIM in New Zealand—An industry-wide view 2019. Wellington, New Zealand: Building Research Association of New Zealand. (BAC) BIM Acceleration Committee. 2019b. The New Zealand BIM handbook—A guide to enabling BIM on built assets. Wellington, New Zealand: Building Research Association of New Zealand. Beach, T. H., J.-L. Hippolyte, and Y. Rezgui. 2020. “Towards the adoption of automated regulatory compliance checking in the built environment.” Autom. Constr. 118 (Oct): 103285. Beach, T. H., T. Kasim, H. Li, N. Nisbet, and Y. Rezgui. 2013. “Towards automated compliance checking in the construction industry.” In Proc., Int. Conf. on Database and Expert Systems Applications, 366–380. Berlin: Springer. Beach, T. H., Y. Rezgui, H. Li, and T. Kasim. 2015. “A rule-based semantic approach for automated regulatory compliance in the construction sector.” Expert Syst. Appl. 42 (12): 5219–5231. Bertram, N., S. Fuchs, J. Mischke, R. Palter, G. Strube, and J. Woetzel. 2019. Modular construction: From projects to products. New York: McKinsey & Company. Bonenberg, W., X. Wei, and M. Zhou. 2018. “BIM in prefabrication and modular building.” In Proc., Int. Conf. on Applied Human Factors and Ergonomics, 100–110. Orlando, FL: Springer. Bouzidi, K. R., B. Fies, C. Faron-Zucker, A. Zarli, and N. L. Thanh. 2012. “Semantic web approach to ease regulation compliance checking in construction industry.” Future Internet 4 (3): 830–851. Bus, N., A. Roxin, G. Picinbono, and M. Fahad. 2018. “Towards french smart building code: Compliance checking based on semantic rules.” In Proc., 6th Linked Data in Architecture and Construction Workshop, edited by M. Poveda-Villalón, P. Pauwels, and A. Roxin, 6–15. Aachen, Germany: CEUR-WS Team. Choi, J., and I. Kim. 2008. “An approach to share architectural drawing information and document information for automated code checking system.” Tsinghua Sci. Technol. 13 (S1): 171–178. Choi, J., and I. Kim. 2013. “Development of check-list for BIM based architectural design quality check.” Korean J. Comput. Des. Eng. 18 (3): 177–188. Ciribini, A., S. M. Ventura, and M. Paneroni. 2016. “Implementation of an interoperable process to optimise design and construction phases of a residential building: A BIM pilot project.” Autom. Constr. 71 (Nov): 62–73. Costin, A., A. Adibfar, H. Hu, and S. S. Chen. 2018. “Building information modeling (BIM) for transportation infrastructure–Literature review, applications, challenges, and recommendations.” Autom. Constr. 94 (Oct): 257–281. Creswell, J. W. 2009. Research design: Qualitative, quantitative and mixed methods approaches. Thousand Oaks, CA: SAGE. Dimyadi, J., and R. Amor. 2013. “Automated building code compliance checking. Where is it at?” In Proc., CIB World Building Congress 2013 and Architectural Management & Integrated Design and Delivery Solutions, 172–185. Brisbane, Australia: Queensland Univ. of Technology. Dimyadi, J., and R. Amor. 2017. “Automating conventional compliance audit processes.” In Proc., Int. Conf. on Product Lifecycle Management, 324–334. Seville, Spain: Springer. Dimyadi, J., S. Fernando, K. Davies, and R. Amor. 2020. “Computerising the New Zealand building code for automated compliance audit.” In Proc., 6th New Zealand Built Environment Research Symp., 39–46. Auckland, New Zealand: Massey Univ. Dimyadi, J., W. Solihin, C. Eastman, and R. Amor. 2016. “Integrating the BIM rule language into compliant design audit processes.” In Proc., 33rd Int. Conf. of CIB W78, 1–10. Delft, Netherlands: International Council for Research and Innovation in Building and Construction. Dimyadi, J., G. Thomas, and R. Amor. 2017. “Enabling automated compliance audit of architectural designs.” In Proc., 51st Int. Conf. of the Architectural Science Association (ANZAScA), edited by M. A. Schnabel, 387–396. Sydney, Australia: Architectural Science Association. Ding, L., R. Drogemuller, M. Rosenman, D. Marchant, and J. Gero. 2006. “Automating code checking for building designs-DesignCheck.” In Clients driving construction innovation: Moving ideas into practice, edited by K. Brown, K. Hampson, and P. Brandon, 113–126. Brisbane, Australia: Cooperative Research Centre for Construction Innovation. Doan, D. T., A. Ghaffarianhoseini, N. Naismith, A. Ghaffarianhoseini, T. Zhang, and J. Tookey. 2019. “Examining green star certification uptake and its relationship with building information modelling (BIM) adoption in New Zealand.” J. Environ. Manage. 250 (Nov): 109508. Eastman, C., P. Teicholz, R. Sacks, and K. Liston. 2011. BIM handbook: A guide to building information modeling for owners, managers, designers, engineers and contractors. Hoboken, NJ: Wiley. Gbadamosi, A.-Q., L. Oyedele, A.-M. Mahamadu, H. Kusimo, M. Bilal, J. M. Davila Delgado, and N. Muhammed-Yakubu. 2020. “Big data for design options repository: Towards a DFMA approach for offsite construction.” Autom. Constr. 120 (Dec): 103388. Ghaffarianhoseini, A., J. Tookey, A. Ghaffarianhoseini, N. Naismith, S. Azhar, O. Efimova, and K. Raahemifar. 2017. “Building information modelling (BIM) uptake: Clear benefits, understanding its implementation, risks and challenges.” Renewable Sustainable Energy Rev. 75 (Aug): 1046–1053. Goh, B.-H. 2007. “E-government for construction: The case of Singapore’s CORENET project.” In Proc., of Research and Practical Issues of Enterprise Information Systems II, 327–336. New York: Springer. GSA. 2015. GSA BIM guide 02—Spatial program validation. Washington, DC: US General Services Administration. Hjelseth, E. 2015a. “BIM-based model checking (BMC).” In Building information modeling: Applications and practices, edited by R. Issa and S. Olbina, 33–61. Reston, VA: ASCE. Hjelseth, E. 2015b. “Public BIM-based model checking solutions: Lessons learned from Singapore and Norway.” In Building information modelling (BIM) in design, construction and operations, edited by L. Mahdjoubi, C. A. Brebbia, and R. Laing, 421–436. Southampton, UK: Wessex Institute of Technology Press. Hong, Y., A. W. Hammad, S. Sepasgozar, and A. Akbarnezhad. 2019. “BIM adoption model for small and medium construction organisations in Australia.” Eng. Constr. Archit. Manage. 26 (2): 154–183. Hosseini, M. R., S. Banihashemi, N. Chileshe, M. O. Namzadi, C. Udeaja, R. Rameezdeen, and T. McCuen. 2016. “BIM adoption within Australian small and medium-sized enterprises (SMEs): An innovation diffusion model.” Constr. Econ. Build. 16 (3): 71–86. James, M., B. Yu, and B. Martin. 2017. Handbook for the design of modular structures. Melbourne, Australia: Monash University Press. Javid, M. A., N. Ali, M. Abdullah, T. Campisi, S. A. H. Shah, and S. Suparp. 2022. “Analysis of driver’s socioeconomic characteristics relating to speeding behavior and crash involvement: A case study in Lahore.” Infrastructures 7 (2): 18. Jiang, S., Z. Wu, B. Zhang, and H. S. Cha. 2019. “Combined MvdXML and semantic technologies for green construction code checking.” Appl. Sci. 9 (7): 1463. Kasim, T., H. Li, Y. Rezgui, and T. Beach. 2013. “Automated sustainability compliance checking process: Proof of concept.” In Proc., 13th Int. Conf. on Construction Applications of Virtual Reality, 30–31. Middlesbrough, UK: Teesside Univ. Kennerley, T. 2019. Planning barriers for prefabricated housing. Porirua, New Zealand: BRANZ. Kim, I., J. Choi, E. A. L. Teo, and H. Sun. 2020. “Development of K-BIM e-Submission prototypical system for the openBIM-based building permit framework.” J. Civ. Eng. Manage. 26 (8): 744–756. Krijnen, T., and L. Van Berlo. 2016. “Methodologies for requirement checking on building models: A technology overview.” In Proc., 13th Int. Conf. on Design and Decision Support Systems in Architecture and Urban Planning, 1–11. Eindhoven, Netherlands: Eindhoven Univ. of Technology. Lam, T. T., L. Mahdjoubi, and J. Mason. 2017. “A framework to assist in the analysis of risks and rewards of adopting BIM for SMEs in the UK.” J. Civ. Eng. Manage. 23 (6): 740–752. Lee, H., J.-K. Lee, S. Park, and I. Kim. 2016. “Translating building legislation into a computer-executable format for evaluating building permit requirements.” Autom. Constr. 71 (Nov): 49–61. Lee, H. M. 2021. “Assessing information-input standardisation for automated compliance checking efficiency.” Master’s dissertation, Wellington School of Architecture, Victoria Univ. of Wellington. Lee, J.-K., C. M. Eastman, and Y. C. Lee. 2015. “Implementation of a BIM domain-specific language for the building environment rule and analysis.” J. Intell. Rob. Syst. 79 (3–4): 507–522. Lee, Y., K. A. Kozar, and K. R. Larsen. 2003. “The technology acceptance model: Past, present, and future.” Commun. Assoc. Inf. Syst. 12 (1): 50. Li, C. Z., R. Y. Zhong, F. Xue, G. Xu, K. Chen, G. G. Huang, and G. Q. Shen. 2017. “Integrating RFID and BIM technologies for mitigating risks and improving schedule performance of prefabricated house construction.” J. Cleaner Prod. 165 (Nov): 1048–1062. Lincoln, Y. S., and E. G. Guba. 1985. Naturalistic inquiry. Thousand Oaks, CA: SAGE. Malsane, S., J. Matthews, S. Lockley, P. E. Love, and D. Greenwood. 2015. “Development of an object model for automated compliance checking.” Autom. Constr. 49 (Jan): 51–58. MBIE. 2014. New Zealand building code handbook. Wellington, New Zealand: Ministry of Business, Innovation & Employment. MBIE. 2018. Annual report 2017/18. Wellington, New Zealand: Ministry of Business, Innovation & Employment. Miles, M. B., A. M. Huberman, and J. Saldana. 2014. Qualitative data analysis: A methods sourcebook. Thousand Oaks, CA: SAGE. Mostafa, S., K. P. Kim, V. W. Tam, and P. Rahnamayiezekavat. 2020. “Exploring the status, benefits, barriers and opportunities of using BIM for advancing prefabrication practice.” Int. J. Constr. Manage. 20 (2): 146–156. Nawari, N. O. 2011. “Automating codes conformance in structural domain.” In Proc., 2011 ASCE Int. Workshop on Computing in Civil Engineering. Reston, VA: ASCE. Nguyen, T.-H., and J.-L. Kim. 2011. “Building code compliance checking using BIM technology.” In Proc., 2011 Winter Simulation Conf., 3395–3400. Phoenix, Arizona: IEEE. Palinkas, L. A., S. M. Horwitz, C. A. Green, J. P. Wisdom, N. Duan, and K. Hoagwood. 2015. “Purposeful sampling for qualitative data collection and analysis in mixed method implementation research.” Administration Policy Mental Health 42 (5): 533–544. Panjehpour, M., and A. A. A. Ali. 2013. “A review of prefab home and relevant issues.” Constructii 14 (1): 53–60. Park, S., Y.-C. Lee, and J.-K. Lee. 2016. “Definition of a domain-specific language for Korean building act sentences as an explicit computable form.” J. Inf. Technol. Constr. 21 (2016): 422–433. Piroozfar, P., E. R. Farr, A. H. Zadeh, S. T. Inacio, S. Kilgallon, and R. Jin. 2019. “Facilitating building information modelling (BIM) using integrated project delivery (IPD): A UK perspective.” J. Build. Eng. 26 (Nov): 100907. Preidel, C., and A. Borrmann. 2015. “Automated code compliance checking based on a visual language and building information modeling.” In Proc., 32nd Int. Symp. on Automation and Robotics in Construction (ISARC), 1–8. Oulu, Finland: International Association for Automation and Robotics in Construction. Preidel, C., and A. Borrmann. 2016. “Towards code compliance checking on the basis of a visual programming language.” J. Inf. Technol. Constr. 21 (25): 402–421. Preidel, C., and A. Borrmann. 2017. “Refinement of the visual code checking language for an automated checking of building information models regarding applicable regulations.” In Proc., ASCE Int. Workshop on Computing in Civil Engineering 2017, 157–165. Reston, VA: ASCE. Ramaji, I. J., and A. M. Memari. 2015. “Information exchange standardization for BIM application to multi-story modular residential buildings.” In Proc., AEI 2015, 13–24. Reston, VA: ASCE. Sadrinooshabadi, S., A. Taheri, I. Yitmen, and R. Jongeling. 2020. “Requirement management in a life cycle perspective based on ISO 19650-1 and CoClass as the new classification system in Sweden.” Eng. Constr. Archit. Manage. 28 (9): 2736–2753. Salama Dareen, A., and M. El-Gohary Nora. 2013. “Automated compliance checking of construction operation plans using a deontology for the construction domain.” J. Comput. Civ. Eng. 27 (6): 681–698. Saldaña, J. 2021. The coding manual for qualitative researchers. Thousand Oaks, CA: SAGE. Samarasinghe, T., P. Mendis, T. Ngo, and W. Fernando. 2015. “BIM software framework for prefabricated construction: Case study demonstrating BIM implementation on a modular house.” In Proc., 6th Int. Conf. on Structural Engineering and Construction Management, 154–162. Moratuwa, Sri Lanka: Univ. of Moratuwa. Shahtaheri, Y., C. Rausch, J. West, C. Haas, and M. Nahangi. 2017. “Managing risk in modular construction using dimensional and geometric tolerance strategies.” Autom. Constr. 83 (Nov): 303–315. Shahzad, W., J. Mbachu, and N. Domingo. 2014. “Prefab content versus cost and time savings in construction projects: A regression analysis.” In Proc., 4th New Zealand Built Environment Research Symp. (NZBERS), 1–17. Auckland, New Zealand: Massey Univ. Solihin, W., and C. M. Eastman. 2016. “A knowledge representation approach in BIM rule requirement analysis using the conceptual graph.” J. Inf. Technol. Constr. 21: 370–401. Solnosky, R. L., A. M. Memari, and I. J. Ramaji. 2014. “Structural BIM processes for modular multi-story buildings in design and construction.” In Proc., 2nd Residential Building Design & Construction Conf., 201–215. State College, PA: Pennsylvania State Univ. Sun, C., S. Jiang, M. J. Skibniewski, Q. Man, and L. Shen. 2017. “A literature review of the factors limiting the application of BIM in the construction industry.” Technol. Econ. Dev. Econ. 23 (5): 764–779. Thompson, J. 2019. “Modular construction: A solution to affordable housing challenges.” Cornell Real Estate Rev. 17 (1): 90–97. Tornatzky, L. G., M. Fleischer, and A. K. Chakrabarti. 1990. Processes of technological innovation. Lexington, MA: Lexington Books. Vanyi Technology Ltd. 2021. “An artificial intelligence-based ACC system for 2D drawings.” Accessed March 3, 2022. Wang, S., Z. Liu, Q. Hao, Q. Zhao, and X. Wu. 2021. “A survey on the development of data-driven compliance checking and government’s purchasing AI for compliance checking in China.” [In Chinese.] China Eng. Consulting 2: 68–79. Yin, R. K. 2011. Applications of case study research. Thousand Oaks, CA: SAGE. Yurchyshyna, A., C. F. Zucker, N. Thanh, C. Lima, and A. Zarli. 2007. “Towards an ontology-based approach for conformance checking modeling in construction.” In Proc., 24th Int. Conf. of CIB W78. Delft, Netherlands: International Council for Research and Innovation in Building and Construction. Zhang, J., and N. El-Gohary. 2014. “Automated reasoning for regulatory compliance checking in the construction domain.” In Proc., Construction Research Congress 2014: Construction in a Global Network, 907–916. Reston, VA: ASCE. Zhang, J., and N. El-Gohary. 2017. “Integrating semantic NLP and logic reasoning into a unified system for fully-automated code checking.” Autom. Constr. 73 (Jan): 45–57. Zhang, R., and N. El-Gohary. 2019. “A machine learning-based method for building code requirement hierarchy extraction.” In Proc., 2019 Canadian Society for Civil Engineering Annual Conf., 157930. Montreal: Canadian Society for Civil Engineering. Zhang, S. J., J. Teizer, J. K. Lee, C. M. Eastman, and M. Venugopal. 2013. “Building information modeling (BIM) and safety: Automatic safety checking of construction models and schedules.” Autom. Constr. 29 (Jan): 183–195. Zhong, B., L. Ding, H. Luo, Y. Zhou, Y. Hu, and H. Hu. 2012. “Ontology-based semantic modeling of regulation constraint for automated construction quality compliance checking.” Autom. Constr. 28 (Dec): 58–70.

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