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Characteristics and Dynamics of BIM Adoption in China: Social Network Analysis

June 2022
Journal of Construction Engineering and Management 148(6)

June 2022
148(6)

DOI:10.1061/(ASCE)CO.1943-7862.0002276

Authors:

Harbin Institute of Technology

Building information modeling (BIM) can integrate multi-stage resources and promote multi-agent collaboration. As a key information technology in the architecture, engineering and construction field, BIM has attracted increasing attention worldwide. Existing research mainly focuses on influencing factors or project-based applications of BIM, lacking a macroscopic and quantitative measurement. This study quantitatively explores the macro characteristics and dynamics of BIM adoption. A total of 4,591 BIM-related patents were collected, and the current BIM adoption status was clarified. The evolution process of BIM adoption from 2011 to 2020 was revealed using social network analysis, and the development trend was predicted based on a Barrat, Barthelemy, Vespignani (BBV) model. The results indicate that BIM adoption in China presents significant regional imbalances and scale-free network features, with low connectivity as a whole and a significant island effect locally, and is entering a stage of rapid development and active evolution. This study provides an overview of actual BIM adoption and its potential causes, which is a breakthrough in existing research. The conclusions will contribute to the government issuing evidence-based policies to promote BIM at large.

BIM-related patents from 2011 to 2020.

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Provincial distribution of BIM enterprises engaged in patent cooperation.

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Key technology classification of cooperative patents over time.

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Distribution of various fields and the corresponding subfields of cooperative patents.

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Geographical distribution of evolution of BIM enterprises.

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Content uploaded by Qingwen Bo

Content may be subject to copyright.

Characteristics and Dynamics of BIM Adoption

in China: Social Network Analysis

Yudan Dou1and Qingwen Bo2

Abstract: Building information modeling (BIM) can integrate multi-stage resources and promote multi-agent collaboration. As a key

information technology in the architecture, engineering and construction field, BIM has attracted increasing attention worldwide. Existing

research mainly focuses on influencing factors or project-based applications of BIM, lacking a macroscopic and quantitative measure-

ment. This study quantitatively explores the macro characteristics and dynamics of BIM adoption. A total of 4,591 BIM-related patents

were collected, and the current BIM adoption status was clarified. The evolution process of BIM adoption from 2011 to 2020 was revealed

using social network analysis, and the development trend was predicted based on a Barrat, Barthelemy, Vespignani (BBV) model. The

results indicate that BIM adoption in China presents significant regional imbalances and scale-free network features, with low connec-

tivity as a whole and a significant island effect locally, and is entering a stage of rapid development and active evolution. This study

provides an overview of actual BIM adoption and its potential causes, which is a breakthrough in existing research. The conclusions will

contribute to the government issuing evidence-based policies to promote BIM at large. DOI: 10.1061/(ASCE)CO.1943-7862.0002276.

Author keywords: Building information modeling (BIM); Adoption; Characteristics; Dynamics; Social network.

Introduction

Information technologies continue to rapidly develop, leading to

need to upgrade systems for many domains around the world

(Merig´o et al. 2018). The construction industry has long been faced

with labor-intensive input, extensive management, and high con-

sumption, creating an urgent need for change (Ma et al. 2018).

Building information modeling (BIM) can integrate various types

of construction information throughout the life cycle, including de-

sign, procurement, scheduling, and costs, and promote efficient col-

laboration among developers, designers, suppliers, contractors, and

operators, to shorten the schedule, reduce costs, improve quality, and

achieve other sustainable and lean construction goals (Bryde et al.

2013;Chen and Tang 2019). BIM has tremendous potential in the

field of architecture, engineering and construction (AEC) and has

received global attention in academia. Notable achievements in

this area include: “BIM+ Innovation”(Du et al. 2013;Irizarry et al.

2013), “BIM+ Life Cycle Project Management”(Kang et al. 2016;

Ma et al. 2018;Marzouk et al. 2018), “BIM+ Prefabricated

Buildings/Green Buildings”(Ji et al. 2020;Lu et al. 2017;Wan g

et al. 2018), “BIM+ lean concept”(Herrera et al. 2021;Mahalingam

et al. 2015), and “BIM+ Education”(Becerik-Gerber et al. 2012;

Bosch-Sijtsema et al. 2019), to name but a few examples.

However, the practical adoption of BIM in many countries

is limited, with poor effects (Howard et al. 2017;Prabhakaran

et al. 2021), which does not match the vigorous development of

theoretical research, active governmental policy support, and indus-

try expectations (Murguia et al. 2021;Wen et al. 2021). This diffi-

culty in promotion is in large part due to the lack of an overview

about BIM adoption (Succar and Kassem 2015), which leads to in-

sufficient theoretical guidance to inform governments as they de-

velop policies to promote BIM. Measuring the characteristics and

dynamics of BIM adoption is conducive to clarifying its current

and future situation macroscopically, and for interpreting underlying

causes, to provide evidence-based policy suggestions for government

and to improve the overall performance of BIM promotion. Hence,

the following issues urgently need to be addressed: What are the

holistic characteristics of BIM adoption (now)? Why are there such

characteristics (past)? What is the evolutionary trend (future)?

Existing literature mainly uses case studies, expert interviews,

and questionnaire surveys to analyze various factors influencing

BIM adoption (especially obstacles such as legal and contract is-

sues) and the behaviors of enterprises adopting BIM (Ahmed and

Kassem 2018;Howard et al. 2017;Van Roy and Firdaus 2020).

This hinders their practical implications due to the inadequate ob-

jectivity of the data and its limited application to specific projects,

enterprises or regions (Ma et al. 2020). Moreover, most studies fo-

cus on qualitative descriptions of BIM adoption (Azhar 2011) and

lack quantitative measurement, resulting in challenges for policy

improvements. In addition, extant research pays more attention

to static analysis than to the evolution of BIM adoption, and thus

cannot explain the causes of contemporary issues.

Some studies have utilized diffusion models, such as BASS [a

widely used overall model in technology diffusion theory proposed

by BASS (1976)], to predict the trend of BIM adoption (Gholizadeh

et al. 2018), or have applied evolutionary game theory to explore its

adoption mechanisms (Du et al. 2019;Zheng et al. 2017). However,

diffusion models are based on large samples and are more suitable

for studying technology diffusion in mature markets (Bass 1976);

for the promotion of BIM in most regions, especially in develop-

ing countries, prediction results are unreliable when using diffusion

models. Meanwhile, game theory has limited practical applications

due to its strict assumptions and the lack of empirical payoff data

1Assistant Professor, Dept. of Construction Management, Dalian Univ.

of Technology, Dalian 116024, China. ORCID: https://orcid.org/0000

-0002-2654-6322. Email: douyudan@dlut.edu.cn

2Ph.D. Student, School of Management, Harbin Institute of Technology,

Harbin 150001, China (corresponding author). ORCID: https://orcid.org

/0000-0001-8560-4417. Email: 18B910062@stu.hit.edu.cn

Note. This manuscript was submitted on August 25, 2021; approved on

January 18, 2022; published online on March 17, 2022. Discussion period

open until August 17, 2022; separate discussions must be submitted for

individual papers. This paper is part of the Journal of Construction En-

gineering and Management, © ASCE, ISSN 0733-9364.

J. Constr. Eng. Manage., 2022, 148(6): 04022025

(Yuan and Yang 2020). By contrast, social network analysis (SNA)

can characterize technology adoption and reveal its evolutionary

processes, and has produced many meaningful results in multiple

fields (Alkemade and Castaldi 2005;Han et al. 2018). While SNA

is suitable for analyzing BIM adoption and its evolution, it has rarely

been applied in past studies.

Therefore, this study applies the SNA method, based on the co-

operative patent data of BIM in China, to quantitatively explore the

macro characteristics and dynamics of BIM adoption, and provide

evidence-based guidance for the government to issue effective pol-

icies. The research logic constructed by this paper can be used for the

evolution research of technology adoption in other fields, such as

prefabricated construction technology. The conclusions and policy

suggestions proposed, which are unavailable from research at the

micro region or project level, are applicable to other developing

countries that face comparable challenges with China. The remainder

of this study provides a literature review, describes the methodology,

presents the results, and finishes with a discussion and conclusion.

Literature Review

BIM-Related Research

As defined by the American National Standards Institute, BIM is a

shared knowledge resource that covers information throughout the

whole process of a project. All participants can insert, extract, up-

date, and modify the information in BIM software at different

stages in order to achieve collaborative work (Xu et al. 2018).

An important topic of BIM-related research is its integration

with lean construction. Lean concepts focus on achieving a con-

tinuous workflow, and include tools such as concurrent engineer-

ing, just-in-time production, and partnering (Al Hattab and Hamzeh

2015). A lean project delivery system (LPDS), as an operational

strategy of lean construction, can address the fragmentation issues

that are represented by design changes and rework, so as to improve

the efficiency of project construction (Aslam et al. 2021). BIM is a

carrier for storing information and a tool for information exchange

and transmission, which integrates multi-source and heterogeneous

information, and coordinates the multiple disciplines, agents, and

stages of the entire project construction process (Xu et al. 2018). As

such, BIM provides technical support for the advancement of lean

construction. Hence, the requirements of lean construction facilitate

BIM application; meanwhile BIM adoption contributes to lean

management throughout the life of a project (Bryde et al. 2013;

Mahalingam et al. 2015). Researchers have agreed on the necessity

and advantages of integrating BIM and lean concept to improve

project performance (Herrera et al. 2021;Schimanski et al. 2021).

Existing BIM-related studies also pay close attention to techni-

cal issues, such as BIM system development, BIM function opti-

mization, and BIM technology compatibility (Shirowzhan et al.

2020;Tang et al. 2020b), and integration with other digital tech-

nologies, such as VR (Meng et al. 2020), to achieve comprehensive

improvements in project performance (Ji et al. 2020;Wang et al.

2018). Examples of such research include strategy comparisons,

conflict checks, energy consumption analysis, and environmental

simulations in the design stage (Hao et al. 2020;Liu et al. 2017;

Tang et al. 2020a); collision detection, 4D schedule simulation, and

5D cost control in the construction stage (Deng et al. 2019;Park

et al. 2017;Wang et al. 2016); and equipment maintenance, emer-

gency evacuation, and green building evaluation in the operational

stage (Ismail 2020;Lu et al. 2017).

Theoretical research of BIM has provided meaningful achieve-

ments, and BIM has also attracted increasing attention in the AEC

field. The practical application effects, however, remain unclear,

even though some countries have adopted BIM as a national plan

(Liao et al. 2020;Othman et al. 2021). Most existing studies propose

qualitative or fragmented descriptions, and evaluations are of specific

projects, enterprises, or regions rather than the whole industry (Cao

et al. 2017a), and lack a quantitative overview for measuring macro

BIM adoption (Prabhakaran et al. 2021). In addition, while BIM

facilitates the coordination of multi-stakeholders, multi-disciplines

and multi-stages in the project construction process, the synergy

among different BIM enterprises is not explicit (Xu et al. 2018).

These factors are significant for promoting BIM, but they are rarely

discussed in existing research.

BIM Adoption Research

BIM has great practical value, such as software integration, infor-

mation and data sharing, collaborative work, and three-dimensional

visualization, which is widely agreed upon in both academia and

the industry. Nevertheless, BIM also has disadvantages, such as

high software and hardware requirements, complex stakeholder re-

lationships, potential information security risks, and unclear legal

boundaries (Tan et al. 2019;Zhou et al. 2019). These issues are the

main barriers to BIM adoption in those countries where the devel-

opment of BIM is immature (Van Roy and Firdaus 2020).

Unsound technology standard systems and low technology

maturity of BIM lead to poor interoperability and compatibility be-

tween various BIM software applications, high technical complexity

and adoption investment, and uncertain expected benefits, which in-

crease the difficulty for enterprises to apply BIM (Siebelink et al.

2021). Legal risk is another obstacle. BIM necessarily provides high

integration, with strong interdependence between multiple disci-

plines, which can promote disputes about the ownership of intellec-

tual property rights and unclear boundaries of responsibilities;

simultaneously, data security is challenged due to information shar-

ing between multiple stakeholders, which further exacerbates issues

concerning rights and responsibilities (Ragab and Marzouk 2021).

While contracts can define the rights and responsibilities of the par-

ticipants in a project, and thus can achieve reasonable risk allocation,

currently-favored contract terms and conditions do not well support

BIM adoption, though some legal terms have been improved (Chong

et al. 2017a). Contract issues remain a main barrier to adoption of

BIM, in most cases.

BIM-related policy is regarded as an important driver for pro-

moting BIM worldwide, although both policy instruments and

supervision effects are differentiated under various regional con-

texts (Babatunde et al. 2020;Yuan and Yang 2020). For instance,

in many developing countries, such as China, current policies cov-

ering the lifespan of a project and the incentives for training multi-

level BIM talents are insufficient. To potential adopters, especially

small and medium-sized enterprises (SMEs), who lack perception,

motivation, capability, and experience with BIM, there exists much

resistance to BIM adoption under existing policies (Saka and Chan

2021). Consequently, BIM adoption in many countries remains

slow, with poor adoption effects, despite much governmental effort

(Liao et al. 2020;Prabhakaran et al. 2021).

Various drivers and obstacles are involved in the adoption of

BIM (Ahmed and Kassem 2018;Howard et al. 2017;Van Roy

and Firdaus 2020). At different stages of BIM promotion, the influ-

encing factors and their relationships change, and an enterprise’s

behaviors will be dynamic and subject to the interactions of multiple

factors (Du et al. 2019;Zheng et al. 2017). As such, a static analysis

of influencing factors, using case studies, expert interviews and ques-

tionnaire survey methods (Arayici and Coates 2012;Cao et al. 2016;

Linderoth 2010), deviates from reality. Previous research used the

J. Constr. Eng. Manage., 2022, 148(6): 04022025

evolutionary game theory method to reveal the dynamic adoption

mechanisms (Du et al. 2019;Zheng et al. 2017), but the practical

applications are limited due to a lack of empirical payoff data (Yua n

and Yang 2020). Researchers have also adopted diffusion models,

such as the BASS model, to predict the diffusion trend of BIM

(Gholizadeh et al. 2018). Nevertheless, diffusion models have strict

assumptions and require a large sample (Bass 1976), and are thus

more suitable for research regarding the adoption of mature technol-

ogies, than research in countries where BIM adoption is in an ex-

ploratory stage.

Research that looks at the dynamic evolution of BIM adoption

needs to first clarify historical evolution features and explain its

underlying process, so as to accurately predict the evolution trend.

Although SNA has only very infrequently been applied in existing

BIM adoption research, it possesses the possibility of addressing

the various previously-described issues.

Social Network Research

Social networks exist throughout our social and economic lives

(Barabasi and Albert 1999;Watts and Strogatz 1998). SNA bridges

micro subject behaviors and macro evolutionary characteristics,

and has been widely applied in many fields, including the AEC

industry (Han et al. 2018;Tang et al. 2018). Keast and Hampson

(2007) proposed that the social network formed by construction

enterprises has significant advantages in promoting trust and com-

munication among stakeholders. Park et al. (2011) found that large

construction enterprises tend to form large and dense network re-

lationships, while SMEs are more inclined to maintain long-term

and targeted network relationships. Dou et al. (2020) constructed a

two-stage evolution framework and analyzed the evolution mecha-

nism of an inter-organizational diffusion network of prefabricated

construction technology.

Enterprises decide whether to adopt BIM and interact with each

other under influencing factors. That an increasing number of enter-

prises’applying BIM software urges them to form diverse partner-

ships, which makes BIM adoption to present network features, with

high upgradability and expandability (Linderoth 2010). As such,

there exists embeddedness in a BIM adoption network, as the co-

operation between BIM enterprises evolves (Cao et al. 2014). Cao

et al. (2017b) discussed the impact of social network macrostruc-

ture based on a specific project for BIM adoption, verifying the

importance of the network in promoting BIM. Linderoth (2010)

explored the formation mechanism that promotes and restricts BIM

adoption by regarding it as the interconnection between actors in

construction projects. Existing research has attached increasing im-

portance to the application of SNA in BIM adoption. However, the

practical applications are limited due to a concentration on specific

projects or regions rather than the whole industry. In addition, little

in-depth analysis has been performed on the evolution process and

development trends for BIM adoption.

To conclude, SNA offers an applicable method to explore the

characteristics and dynamics of BIM adoption, while the current

literature is restricted in providing evidence-based guidance for

governments to promote BIM in a broader scope.

Methodology

Research Design

First, this study collected BIM-related patents, and cooperative pat-

ents (applied for by two or more enterprises) were screened out

after data cleaning. Then, the fundamental theories and concepts

of SNA, i.e. , BIM adoption network construction and BBV model

of BIM adoption network evolution, were demonstrated. Next, a

descriptive statistical analysis was conducted on the processed pat-

ents, to clarify the basic situation of current practical BIM adoption.

Then, the characteristics and evolution process of BIM adoption

were illustrated using the SNA method, through UCINET 6.0

and its embedded [i.e., NetDraw, Analytic Technologies, Lexing-

ton, Kentucky (Butts 2008)]. Subsequently, the development trend

for BIM adoption was predicted by programming in MATLAB

version R2020a (MathWorks, Natick, Massachusetts) based on

the Barrat, Barthelemy, Vespignani (BBV) model. Policy sugges-

tions were further proposed. The research framework of this study

is presented as shown in Fig. 1.

Data Collection

China is a representative developing country, with leading

BIM publications (Wen et al. 2021). The characteristics and dy-

namics research of BIM adoption in China is important due to its

market size and can be applied in many comparable regions. After

the issuance of the 2011–2015 Construction Industry Information

Development Outline (Ministry of Housing and Urban-Rural

Development of China 2011), BIM-related theoretical research

has grown rapidly (Wen et al. 2021), and BIM practice has been

a key focus in the AEC industry. Therefore, this study selects

2011–2020, the ten key years, as the time range of data acquisition

for BIM adoption.

Intellectual property laws protect innovative technologies

through patents, which are important outputs of technology inno-

vation, as agreed by most researchers (Kogan et al. 2017). Patent

data is valid because it is issued by government authorities, with a

strict patent filing process, high application cost, and little subjec-

tive interference. Many studies of technology innovation based on

patent data have achieved reasonable and reliable conclusions (Boh

et al. 2020). Generally, enterprises apply for patent protection for

their innovative BIM technologies (Mao et al. 2015). Accordingly,

the patents can well describe the BIM adoption level of each enter-

prise, and the joint application of patents reflects to a certain extent

the cooperation among enterprises (Yu and Zhang 2019). There-

fore, cooperative patent data is adopted in this study, and BIM

adoption weighted networks are formed based on the partnerships

between enterprises involved with each patent.

The State Intellectual Property Office (SIPO) website is an

authoritative and publicly available channel for obtaining patent data

in China. This study collected data by performing a search of the

SIPO website with a time range for the patent publication day of

January 1, 2011 to December 31, 2020, and search keywords “BIM”

or “building information modelling.”This resulted in 4,609 items for

BIM-related patents in the AEC field. After the patent data of indi-

vidual applicants was filtered out, 4,591 patents of applicants repre-

senting enterprises or institutions (government agencies or research

institutes) remained. This data was further screened to retain just

patents applied for by two or more enterprise/institution applicants,

resulting in a data set of 4,004 individually applied patents and 587

cooperatively applied patents.

Social Network Analysis

Fundamental Theories and Concepts

Social networks are collections of multiple social actors (includ-

ing individuals, groups, and organizations) and their links (Burt

et al. 2013). The “strong-weak ties”and “embeddedness”are two

representative theories of social networks, which provide solid

foundations for this research (Phelps et al. 2012). The strong-

weak ties theory believes that interpersonal relationship networks

J. Constr. Eng. Manage., 2022, 148(6): 04022025

can be divided into strong ties and weak ties (Brooks 2019;Jack

2005). Strong ties indicate the convergence of individual attributes

and information in the network, with close relationships between

individuals within the groups or organizations (Tortoriello et al.

2012). The information obtained in strong tie networks is often

highly repetitive. Weak ties imply large differences in individual

attributes and information in the network, with loose connections

between individuals. Weak ties can establish links between groups

and organizations, crossing their social boundaries to obtain diverse

information and resources (Brooks 2019). The embeddedness theory

proposes a tendency to stay in a certain social network and to con-

tinuously create, update, and expand network links over time (Dacin

et al. 1999). Embedded social networks are more energetic than

common ones, due to a high level of trust and frequent information

interaction between network actors.

Weighted network theory is an important branch of social net-

work research. It can reflect both the existence and the strength of

connections between nodes and characterize the differences

between information involved in nodes (Barrat et al. 2004a,b).

A BIM adoption network is denoted by G¼ðN;WÞ,where

Nis the network size and Wðwij Þdenotes the edge weight matrix

of the network, i;j¼1;2;:::;N.wij indicates the cooperation fre-

quency between BIM enterprises iand j, which is calculated by

wij ¼ki=PΓikj.kiand kjare the numbers of direct partners for

enterprises iand j, respectively. In a BIM adoption network, a

greater edge weight between two nodes indicates a closer connection

between the enterprises. Node degree and node average degree

(number of direct partners), and node strength and average strength

(cooperation frequency with partners) are fundamental attributes of

a BIM adoption network (Barabasi and Albert 1999;Watt s and

Strogatz 1998), which can be calculated according to Table 1.

In particular, the connected components (number of connected

subgroups in the network), graph density (closeness of the connec-

tions between nodes in the network), and modularity (reflecting the

Characteristics

Descriptive statistics Network features

Dynamics

Historical Evolution

Characteristics and Dynamics of BIM Adoption Network

Evolution prediction

Data Collection

China SIPO

website

BIM-related

patents

Time:

2011-2020

Keywords: Building

information model or BIM

Scope:

AEC field

Social Network Analysis

Fundamental theory

and concepts

BIM adoption

network construction

555 BIM enterprises

Strong-weak ties theory

Embeddedness theory 493 cooperative links

Cooperative

patents

BBV

model

Node degree and strength

Applicants information

Patents classification

Fields distribution

Network

topology

Network

attributes

Geographical distribution

Network attributes

Network topology

555*555 strength matrix

Network

topology

Network

attributes

Fig. 1. Research framework.

Table 1. Calculation of the fundamental attributes of BIM adoption network

Attribute Code Calculation Parameter meaning

Node degree kiki¼Pli, where lidenotes a partner directly

connected to enterprise i.

The total number of partners directly connected to

enterprise iin BIM adoption network G.

Node average degree KK¼1

i¼1

ki, where kidenotes the partners directly

connected to enterprise i.

The average of partners of all enterprises in BIM

adoption network G.

Node strength sisi¼Pj∈Γiwij, where jdenotes a neighbor partner of

enterprise i;Γiindicates the set of all existing

neighbor partners of enterprise i.

The total cooperation frequency of enterprise i.

Node average strength SS¼1

i¼1

si, where sidenotes the cooperation

frequency of enterprise i.

The average of cooperation frequency of all

enterprises in BIM adoption network G.

J. Constr. Eng. Manage., 2022, 148(6): 04022025

pros and cons of the division of network communities) are key

indicators used to present the multi-agent collaboration characteris-

tics in social networks (Barabasi and Albert 1999;Watts and Strogatz

1998). They therefore will be our next focus.

BIM Adoption Network Construction

First, a total of 555 BIM enterprises, along with their 493 connec-

tions, corresponding to the retrieved 587 cooperative patents, were

indexed from 1 to 555. Then, an adjacency matrix of size 555 by

555 was constructed to represent the BIM adoption network, in

which a BIM enterprise is the node, the enterprise partnership in-

volved in a cooperative patent is the edge, and the number of patent

cooperation frequencies between enterprises is the edge weight.

Because the partnerships between enterprises are bidirectional, the

adjacency matrix is symmetric, and the diagonal elements are zero.

BIM adoption networks for each year of the study period were con-

ducted according to these procedures.

BBV Model of BIM Adoption Network Evolution

The social network theory proposes that the evolution of weighted

networks is a coupled evolution of network topology and weight

distribution (Barrat et al. 2004c;Yook et al. 2001). When new

nodes are added to the network, they will preferentially connect

to existing nodes with high strength and node degree (Barabasi

and Albert 1999). Hence, the evolution process of the BBV model

(Barratetal.2004c) for a BIM adoption network satisfies growth

and preferential link rules. The specific procedures utilized in this

study are summarized as follows.

Step I: Initial network. Given the initial BIM adoption network,

there are m0(555) enterprises with their e0(493) cooperative links.

The cooperation frequency between BIM enterprises in the initial

network is denoted by the weight matrix W0(555 * 555).

Step II: Growth. Suppose that a new enterprise nenters the BIM

adoption network at each time unit, and connects with the existing

menterprises in the network to form mcooperative links. minflu-

ences the new enterprise’s partner selection. It is assumed that the

new BIM enterprise selects one potential partner in the existing net-

work at each time, i.e., m¼1. The selection by nof partners from

mis conducted according to the weight priority. The probability of

an existing enterprise ibeing selected by nis (Barrat et al. 2004c):

n→i

¼si

Pjsj

ð1Þ

This indicates that BIM enterprises with greater cooperation

strength in the network are more likely to be selected by the newly

entered enterprises.

Step III: The dynamic evolution of cooperation frequency. An

initial cooperation frequency W0is assigned to each newly formed

link ðn;iÞ. The new cooperative link will only locally cause the

readjustment of the cooperation frequencies of enterprise iand

its partners j∈τðiÞ. This adjustment is implemented according

to Eqs. (2) and (3):

wij →wij þΔwij ð2Þ

Δwij ¼δi

wij

ð3Þ

where δiis an additional increment in the BBV model. Different

additional increments of nodes indicate differentiated cooperation

effects of BIM enterprises in the network. For example, when the

node’s additional increment is greater than its initial strength, the

current partnership of a BIM enterprise produces a multiplier effect,

i.e., there exist other cooperation opportunities in addition to the

connection between BIM enterprise and its current partner. As a

result of this process, the BIM adoption network will evolve to

present specific network characteristics.

Results

Descriptive Statistics

The number of BIM-related patents, including independently ap-

plied patents and cooperatively applied patents, increased from

2011 to 2020, as shown in Fig. 2.

In 2010, 2011, and 2012, the number of BIM patent applications

did not exceed five per year. However, 80.7% of the total patents

were applied for in 2018, 2019, and 2020. Specifically, the top line

in Fig. 2shows the rapidly growing trend of independently applied

patents, and the bottom line depicts the tendency of the cooperative

patents. In the first three years, there was but one cooperative pat-

ents issued (in 2012). In contrast, 544 of all patent applications

were submitted in the last four years, and in 2020 alone, the num-

bers of patents exceeded 200. In sum, the number of cooperative

patents for BIM is growing, although the growth rate is lower than

that of the independently applied patents. BIM’s collaboration and

synergies are increasingly valued by enterprises.

1. Applicants of the Cooperative Patents

The 587 cooperative patents obtained in the section “Data

Collection”correspond to 555 applicants (i.e., BIM enterprises).

The characteristics of these enterprises are analyzed from four

dimensions: years in business, enterprise type, main business,

and geographic location, as provided in Table 2.

First, enterprises with the largest share have been established

for 1 to 10 years, accounting for 30.4%, while the smallest pro-

portion are those founded more than 40 years ago, at only 9.2%.

This indicates that BIM patent output is based on a particular

type of engineering experience, and also that fresh thinking that

keeps pace with the times is useful.

Second, current BIM enterprises are mainly classified into

five types: limited liability companies, corporations, universities,

research institutes, and government departments. Limited liability

companies, typically SMEs, account for the largest share (80.2%).

This indicates that SMEs have a greater need for cooperation

when they adopt BIM.

Third, enterprises in the consulting and technical services

(26.7%) and construction (25.8%) sectors account for the most

patents. This is related to the high research and development

Fig. 2. BIM-related patents from 2011 to 2020.

J. Constr. Eng. Manage., 2022, 148(6): 04022025

capabilities of the former and the rich engineering site experi-

ence of the latter. Such entities usually are quite open to BIM

adoption.

BIM enterprises engaged in patent cooperation are distrib-

uted throughout different regions, with the largest proportion

in eastern China. The provincial distribution of BIM enterprises

is visualized in Fig. 3.

The colors from dark to light indicate the number of enterprises

in a region, from more to less. Beijing, Shanghai, and Guangdong

have the largest number of enterprises with cooperative patents.

There are no patent cooperation records among BIM enterprises in

Qinghai, Xinjiang, and Hainan. The main reason is that there are

more BIM enterprises in economically developed regions, and

there are greater opportunities for cooperation to produce patents

there.

2. Classification of Cooperative Patents

A text analysis was done on the 587 cooperative patents. The

main four classifications are summarized in Table 3, which indi-

cates that BIM-related patents focus on fixed structures, mechani-

cal engineering, physics, and electricity. Enterprises often adopt

BIM for the construction and engineering components of various

buildings and infrastructures, or the performance development

and optimization of BIM itself, or the application of an electric

communication technique. The top six technology classifications

are presented in Fig. 4. Almost half of the data is classified G06.

This indicates that most patents focus on technical issues, such as

BIM system development, BIM function optimization, and BIM

technology compatibility, which are also given the most attention

in academia. Moreover, the distribution tendency of these key

technology classifications (Fig. 4) shows that the number of pat-

ents in each classification has a rising trend, especially G06 and

E04. Over time, the classification Other accounts for an increas-

ing proportion, indicates that the development of BIM technol-

ogies is diversified.

3. Field Distribution of Cooperative Patents

This study further filtered the 587 cooperative patents man-

ually and divided them into four categories: Software and

systems (F1), construction methods (F2), equipment and devi-

ces (F3), and application evaluation (F4). F1 includes improve-

ments to BIM modeling methods or software performance, and

using BIM to improve production and construction efficiency,

reduce cost and time, and optimize design and operation effects.

F2 refers to the methods or systems that apply BIM to optimize

on-site construction techniques, processes, construction tools,

etc. F3 includes equipment for surveying, mapping, monitoring,

and construction management, or a device that integrates BIM

and other digital technologies such as VR and GIS. F4 refers to a

method or system of measuring risk and quality, or BIM appli-

cation value evaluation.

F1 is the category with the largest number of cooperative

patents (51%); followed by F2 and F3 (32% and 14%, respec-

tively); the smallest category is F4 (3%). F1 is divided into seven

subfields: cost (F11), schedule (F12), model optimization (F13),

design (F14), production (F15), construction (F16), and opera-

tion and maintenance (F17), of which the largest proportion

(22%) is F16. The distribution of the various fields and subfields

is visualized in Fig. 5. Notably, F2 is different than F16: The

former emphasizes optimizing construction methods, while the

latter focuses on construction management.

At this stage in China, the cooperative BIM patents focus

on F1, which is consistent with the existing research that “BIM

has the highest research frequency in systems and models”

(Chong et al. 2017b;Zhao 2017). This indicates that although

the BIM adoption lags behind the theoretical research (Ding

et al., forthcoming), BIM modeling methods, BIM software per-

formance, and BIM-based cost and schedule optimization sys-

tems are viewed by both academia and industry as having great

importance. However, most of these software and systems of

BIM are standalone, with inadequate compatibility and interop-

erability. Therefore, strengthening the integration between BIM

software and promoting the establishment of BIM system stan-

dards need to be addressed, for both theory and practice.

Network Characteristics

1. Network Topology

The BIM adoption network has 555 enterprises and 493 con-

nections, as shown in Fig. 6. The network is displayed according

to the size of the nodes.

Fig. 6indicates that Enterprise 31 is the core node in the

network, which corresponds to the State Grid Corporation of

China. This indicates that state-owned enterprises are more en-

thusiastic about BIM adoption, and that power engineering is an

important application domain for BIM. Overall, the connectivity

of the network is weak, with little cooperation between enter-

prises. Moreover, most BIM partnerships are single (one edge

between two nodes). This indicates that the current network is

characterized by weak ties. Most BIM enterprises in the network

are loosely connected, with large individual differences, and the

information is diversified. Hence, the BIM adoption network at

this point is actively evolving.

2. Attribute Characteristics

The average node degree and average node strength of the

BIM adoption network were calculated to be 1.777 and 3.632,

respectively. The distributions of node degrees and node strengths

are visualized in Figs. 7(a and b), respectively.

As shown in Fig. 7, both node degree and node strength are

power-law distributed, which indicates the scale-free feature of a

BIM adoption network (Barabasi and Albert 1999), and implies

that a small proportion of BIM enterprises have a large number

of collaborative ties, whereas the majority have only a few ties.

Table 2. Characteristics of cooperative patent applicants

Dimension Category Number Percentage (%)

Years in

business

1–10 years 169 30.4

11–20 years 142 25.6

21–30 years 128 23.1

31–40 years 65 11.7

More than 40 years 51 9.2

Enterprise

type

Limited liability company 445 80.2

Corporation 38 6.8

University 40 7.2

Research institute 20 3.6

Government sector 12 2.2

Main

business

Consulting and technical services 148 26.7

Construction 143 25.8

Integrated services 74 13.3

Reconnaissance and design 41 7.4

Building material equipment 30 5.4

Other 119 21.4

Geographic

location

Eastern China 200 36

North China 132 23.8

Southern China 76 13.7

Southwest China 54 9.7

Central China 52 9.4

Northwest China 21 3.8

Northeast China 20 3.6

J. Constr. Eng. Manage., 2022, 148(6): 04022025

Hence, diverse partnerships and rational resource allocations are

limited.

The edge weight of the network represents the patent co-

operation frequency between BIM enterprises. According to the

network analysis, the edge weights between Enterprises 49, 50,

and 51, and those of 81 and 122 are the largest, indicating that

the patent collaborations between these enterprises are the most

frequent.

In addition, Enterprises 47, 93, 97, 110, and 111 have formed

a subgroup with the largest edge weights. Enterprise 47 is Jiax-

ing Wuzhen Yingjia Qianzhen Technology Co.; 93 is Shenzhen

Qianhai Yingjia Data Service Co.; 97 is Shenzhen Yingjia

Internet Technology Co.; 110 is Yingjia Internet (Beijing) Tech-

nology Co.; and 111 is Yingjia Internet (Shanghai) Construction

Technology Co. These enterprises are subsidiaries or branch en-

terprises of the same group. This indicates that there are strong

ties in the local world of the BIM adoption network. BIM enter-

prises maintain their close connections within the group through

convergent information and resources. In other words, closer

cooperation is more likely to occur in existing subgroups of

a BIM adoption network.

In summary, the current BIM adoption network is character-

ized weak ties as a whole, while strong local ties are significant.

Evolution Process

1. Evolution of Geographical Distribution

In the ten years from 2011 to 2020, the number of provinces

where BIM enterprises are located has gradually. The geo-

graphical distribution evolution of BIM enterprises is visualized

in Fig. 8.

In 2015 and before, BIM was in an exploratory stage. BIM

enterprises were mainly distributed in the provinces of Beijing,

Shanghai, Jilin, Zhejiang, Guangdong, and Sichuan. Their num-

bers were small, and their geographic locations were scattered.

During this period, BIM-related theoretical research had just

Fig. 3. Provincial distribution of BIM enterprises engaged in patent cooperation.

Table 3. Main classifications of BIM-related patents

Section Code Description

Fixed structure E Construction of a road, railway, or bridge; constructions or buildings

Mechanical engineering F Ventilating, use of air currents for screening; engineering components

Physics G Measuring, testing, computing, calculating, counting

Electricity H Electric communication technique

J. Constr. Eng. Manage., 2022, 148(6): 04022025

begun to gain attention (Wen et al. 2021). After 2016, BIM enter-

prises began to appear in the central regions, and the total number

of BIM enterprises has continued to increase, mainly in the eastern

and central provinces. Although there were BIM enterprises in

the northeast, their number had always been low. Not until

2020 did BIM enterprises begin to appear in Inner Mongolia and

northwestern China, and their numbers remain very small.

Current BIM adoption presents a significant imbalance in

geographical distribution, which is closely related to China’s

unbalanced regional economic development (Dou et al. 2020).

To achieve a broader promotion of BIM as a whole, it is neces-

sary to explore the differences in influencing factors and formu-

late development policies tailored to local conditions.

2. Evolution of Network Attributes

Table 4lists the evolution of five key attributes of the BIM

adoption network during the period from 2011 to 2020. The

average degree ranges between 1.46 and 1.71. Hence, on aver-

age, BIM enterprises in the network have fewer than two part-

ners, and their cooperative relationship is single. The increase in

network size hardly leads to any diversified partnerships. How-

ever, the average strength has been increasing year by year,

i.e., the cooperation frequency between enterprises has in-

creased. From this, we can conclude that BIM collaborative in-

novation continue to increase, based on trust.

The connected components of BIM adoption network in-

crease yearly, but the graph density is small and is gradually

decreasing. This indicates that the growth rate of the cooperative

links between enterprises is less than that of the number of enter-

prises. As such, the connectivity of the BIM adoption network is

poor, which leads to “innovation islands”(Chen et al. 2018).

A greater modularity indicates a higher connection between

BIM enterprises within the community and a clearer boundary

between communities. The modularity of BIM adoption net-

work has increased yearly, indicating that the community struc-

ture has become more significant and there are many subgroups

within the network. Hence, the current BIM adoption network

presents a significant “island effect”(Chen et al. 2018), which is

harmful to information sharing and resource allocation within

the network.

The connected components of BIM adoption network in-

crease yearly, but the graph density is small and is gradually

decreasing. This indicates that the growth rate of the cooperative

links between enterprises is less than that of the number of enter-

prises. As such, the connectivity of the BIM adoption network is

poor, which leads to “innovation islands”(Chen et al. 2018).

A greater modularity indicates a higher connection between

BIM enterprises within the community and a clearer boundary

between communities. The modularity of BIM adoption net-

work has increased yearly, indicating that the community struc-

ture has become more significant and there are many subgroups

within the network. Hence, the current BIM adoption network

presents a significant “island effect”(Chen et al. 2018), which is

harmful to information sharing and resource allocation within

the network.

3. Evolution of Network Topology

From 2011 to 2020, the size of the BIM adoption network

has continued to expand, enterprises’connections have in-

creased, and the network has become denser. The topology evo-

lution process of the network is visualized in Fig. 9, which

shows that, in 2015 and before, the number of BIM enterprises

was small, and their connections were weak, and they had not

yet presented obvious network characteristics. From 2016 to

2018, the number of BIM enterprises increased, and the network

characteristics gradually became significant. Core enterprises

and subgroups dominated by core enterprises began to appear,

and there was an island effect. During this period, most of

the inter-enterprise connections were one-to-one, i.e., the co-

operative relationship was single, and the network density was

low. After 2019, the network size has increased significantly,

and the cooperative relationship between BIM enterprises, es-

pecially their existing partnerships, has become closer. In addi-

tion, the scale-free characteristics of the network have become

more significant, with multiple core enterprises dominating.

However, the overall network connectivity and the collaboration

between enterprises remain low, and the issue of innovation is-

lands still exists.

Evolution Prediction

Analysis of the network’s historical evolution process indicates that

it is in an active stage of evolution. The topology prediction of the

network after evolution stabilization is visualized in Fig. 10(a)

(1,000 enterprises) and Fig. 10(b) (2,000 enterprises), and the co-

ordinates are used to distinguish the relative node positions. The

larger and darker nodes indicate those enterprises with significant

resource superiority; that is, the leaders in BIM adoption network.

Over time, the number of core enterprises and the scale of

subgroups in the network increases, and the size and connectivity

of the network greatly increases. The distributions of node degrees

after evolution stabilization are shown in Fig. 11, which charac-

terize the increasingly significant scale-free property. To accelerate

Fig. 4. Key technology classification of cooperative patents over time.

14%

32%

F11

F12

F13

10%

F14

F15

3% F16

22%

F17

51%

Fig. 5. Distribution of various fields and the corresponding subfields of

cooperative patents.

J. Constr. Eng. Manage., 2022, 148(6): 04022025

application, the government can guide core enterprises to promote

their subsidiaries or technology alliance members to adopt BIM.

Discussion

Island Effect of BIM Adoption

Many countries have achieved fruitful results in BIM research,

especially China, which has a large number of BIM-related publi-

cations (Wen et al. 2021). However, its practical adoption has been

slow. Researchers have explored the main obstacles to the adoption

of BIM and put forward corresponding policy suggestions (Ahmed

and Kassem 2018;Howard et al. 2017;Van Roy and Firdaus 2020),

but with little success. The overall connectivity of the Chinese BIM

adoption network remains low, with insufficient trust and co-

ordination between BIM enterprises, resulting in a significant is-

land effect.

“Island effect”is an ecological term, originally referring to the

lack of necessary materials or energy exchange between subsys-

tems and other components in an ecosystem, leading to a closed

phenomenon of incompatible development (Qin 2015). The island

Fig. 6. Topology of BIM adoption network (2011–2020).

-50

100

150

200

250

300

350

0 5 10 15 20 25 30

Count

Value

(a) (b)

-50

100

150

200

250

01020304050

Count

Value

Fig. 7. (a) Distribution of node degree of BIM adoption network; and (b) distribution of node strength of BIM adoption network.

J. Constr. Eng. Manage., 2022, 148(6): 04022025

effect and its path dependence for BIM adoption mainly result from

enterprises seeing themselves as isolated entities and in competition

with each other (Chen et al. 2018). Many differences exist between

BIM enterprises, especially for inter-regional enterprises, in terms of

innovation policy environment and resource allocation, among other

factors, resulting in a lack of trust and coordination (Eadie et al.

2013). As a result, close cooperation happens more often between

subgroups of a parent company, or between the parent and its

branches, leading to many islands in the network. In this scenario,

it is difficult for innovation and experience to achieve market-oriented

diffusion, restricting the establishment of common software interfa-

ces and standard technical systems and adversely affecting the incen-

tive for enterprises to adopt BIM. Therefore, the island effect of BIM

adoption (i.e., the multi-agent collaboration dilemma), is a key issue

that needs to be urgently addressed to promote BIM with high

efficiency.

Reduction in the island effect is to a certain extent conducive to

alleviate the barriers to BIM adoption, such as legal disputes and

contract management. For instance, the temporary nature of proj-

ects construction causes participants to lack trust and be unwilling

to share their information, leading to complex rights and respon-

sibilities issues, which seldom exists among BIM enterprises in

the same subgroup.

Judging from the history of BIM in some developed countries,

BIM adoption is characterized by slow initial exploration, but rapid

advancement after policy guidance from the government (NBS

2013). Hence, the formulation of BIM-related policies for solving

the dilemma of multi-agent collaboration deserves more attention.

Policy Limitations and Suggestions

In 2011, China listed BIM to the informatization standards for

construction. In subsequent years, various BIM-related policies

were issued, but the number was small, and the attention paid was

insufficient. Prior to 2017, the central and local governments high-

lighted BIM adoption using various policies and standards, and

listed BIM as the top information technology in the 10 New Tech-

nologies in Construction Industry (Ministry of Housing and Urban-

Rural Development of China 2017). In 2018, the State Council

adopted the promotion of BIM as a national strategy, and specific

policy instruments have been proposed in many regions, which

characterizes preliminary inter-regional and industry-level diffu-

sion of BIM. This is in line with the evolution process of BIM adop-

tion reflected in Figs. 8and 9.

However, existing BIM-related polices are still of limited value

in coping with the multi-agent collaboration dilemma. First, most

BIM-related policies focus on the macro and qualitative guidance

of multi-discipline integration and multi-agent collaboration, such

as the Guiding Opinions on Promoting the Collaborative Develop-

ment of Intelligent Construction and Building Industrialization in

China (Ministry of Housing and Urban-Rural Development of

China 2020), and lack detailed regulations and definite measures

addressing multi-agent collaboration issues. Furthermore, the ex-

tant policy instruments are mainly targeted for individual stages

or fragmented links of BIM projects, such as design and construc-

tion, while the supervision needed for coordinating multiple stages

and stakeholders throughout to the entire construction process is

scarce. In addition, existing policies lack effective incentives for

transforming BIM-related research into practice, and pay insuffi-

cient attention to the cultivation of multi-level BIM talents.

Fig. 8. Geographical distribution of evolution of BIM enterprises.

Table 4. Evolution of key attributes of BIM adoption network

Attribute

2015 and

before 2016 2017 2018 2019 2020

Average degree 1.46 1.71 1.68 1.47 1.64 1.63

Average strength 3.23 4.5 4.64 5.49 5.4 5.62

Connected components 11 17 30 51 76 98

Graph density 0.06 0.04 0.02 0.01 0.01 0.01

Modularity 0.848 0.806 0.902 0.924 0.963 0.943

J. Constr. Eng. Manage., 2022, 148(6): 04022025

Hence, this study proposes some suggestions for the government:

1. Detailed policy measures and tools to strengthen multi-

discipline integration and multi-agent collaboration need to

be issued. For example, the government can establish demon-

stration projects, bases and cities for applying BIM, to promote

BIM in stages and levels. Encouraging the benchmarking enter-

prises to play a leading and radiating role for their affiliates and

followers is another feasible way. This is conducive to break

path dependence from the island effect, so as to form a positive

industry atmosphere for adopting BIM.

2. General standards for multi-agent collaboration should be

adopted. For instance, the government can invite industry lead-

ers, such as major enterprises, universities, and research insti-

tutions, to participate in establishing BIM-related standards.

It is also necessary to support diversified enterprises in forming

BIM technology alliances, by which they can synergistically

develop BIM platforms and systems that are compatible and

interoperable, and are applicable to the entire life of project

construction.

3. Both the theoretical achievements and the multilevel talent train-

ing of BIM should be highlighted. BIM theoretical research

should be recognized for its guiding role in BIM practice. More

policy incentives, such as special funds and subsidies, for trans-

forming BIM-related research into operational technologies and

equipment, need to be provided by the government. In addition,

the integration of scientific research, university education, and

corporate training should be strengthened, in order to collabo-

ratively cultivate BIM talents at different levels.

2015 and before 2015 2016

2017 2018

2019 2020

Fig. 9. Topology evolution of BIM adoption network.

J. Constr. Eng. Manage., 2022, 148(6): 04022025

Conclusions

This study reveals the characteristics and dynamics of BIM adop-

tion using SNA. Our conclusions are summarized as follows:

•Currently, BIM adoption in China is limited and promotional

efforts are ineffective. However, BMI it is entering the stage

of rapid development and active evolution.

•BIM adoption presents significant regional unbalances, as the

effects of promotional campaigns are closely related to local

development.

•In recent years, the BIM adoption network has gradually be-

come denser and its scale-free characteristics have become more

significant; however, the overall connectivity of the network

remains low, presenting an island effect.

This study quantitatively explored the current status of BIM adop-

tion, and revealed its evolution process and development trend, from

a macro perspective rather than a regional or project level. This is an

important breakthrough, addressing the evolutionary characteristics

of BIM adoption (when and what) and the underlying causes (why

and how). The conclusions and suggestions provided by this study

provides scientific guidance for the government to issue effective

policies to promote BIM throughout the AEC industry. However,

this study has some limitations. For instance, its prediction regarding

the evolution of the BIM adoption network was conducted using the

BBV model directly, without considering how influencing factors

interact with BIM adoption. This limitation will be addressed in

future research.

Data Availability Statement

Some or all of the data, models, or code that support the findings

of this study are available from the corresponding author upon

reasonable request.

Fig. 10. Topology predictions for BIM adoption network: (a) n ¼1,000; and (b) (n ¼2,000).

Fig. 11. Distribution of node degree for BIM adoption network: (a) n ¼1,000; and (b) (n ¼2,000).

J. Constr. Eng. Manage., 2022, 148(6): 04022025

Acknowledgments

This research was supported by the National Natural Science Foun-

dation of China (NSFC) (Nos. 72101044 and 72071027) and the

Fundamental Research Funds for the Central Universities [No.

DUT20RC (3)092].

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Building information modeling (BIM) is a key approach for the digitization of the sector. Therefore, states worldwide put BIM at the center of their construction digitalization strategies. However, strategies vary significantly, and so does BIM implementation and its adoption over time, thus making the comparison between countries considerably challenging. Therefore, the first part of this article provides a comprehensive review of available publications in the field of BIM adoption at the national and international level. BIM adoption in Slovakia is systematically analyzed based on an anonymous online BIM survey that focuses on various areas of BIM. The focus of the BIM survey was on the assessment of the readiness of experts who work with BIM methodology, their maturity, skillsets, and BIM adoption motivation, along with the means of communication and collaboration using Common Data Environment (CDE). Furthermore, we focused on the project management perspective, which covers the existence and compliance with BIM execution plan (BEP) evaluation. In the concluding part, requirements, barriers, and future developments are discussed in detail. The BIM survey provides an insight in the current state of the art of BIM in the industry that allows for a better understanding of its potential and a more informed development and implementation of BIM strategies. This study is an important contribution to BIM and digitalization benchmarking that provides valuable information to digitalization policy makers at the governmental and business levels.

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Jul 2023

BIM has played an important role in promoting sustainable development in the construction industry. The lack of an effective system for evaluating BIM application performance has become a major obstacle to BIM application. Therefore, this study develops an indicator evaluation framework that includes benefit factors and cost factors to systematically evaluate the BIM application performance. The evaluation indicators are determined through a scientometric literature review and expert evaluations, and the AHP method is employed to assess the weights of each indicator. A performance index is established and measured through a cost–benefit measurement. The developed evaluation framework and index are applied in a case study of a grid information modeling (GIM) system implemented in a specific UHV substation project. The sensitivity of the evaluation index is further examined. Finally, the recommendations for developing BIM applications like GIM are discussed. Accordingly, this research mainly contributes to developing the BIM application performance evaluation framework and index, which can be used to assess the application performance of digital technologies in the construction industry worldwide. The case experience and recommendations could promote BIM application in the power generation construction industry.

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May 2024
Construct Innovat

Purpose-Building information modelling (BIM) implementation in the design, construction and operations (DCO) industry is increasingly becoming essential. While BIM has been adopted on a larger scale in many developed economies, its acceptance is still in the embryonic phases for developing nations in the DCO industry. This study aims to identify the inhibitors to BIM implementation through the social network theoretical lens, intending to understand the associations among the barriers in the Indian context. Subsequently, recommend strategies to mitigate the barriers from the academic practitioner's perspective. Design/methodology/approach-A mixed methods research was adopted, commencing with comprehensive literature reviews to recognise various inhibitors to BIM implementation. These identified barriers were further examined through the questionnaire survey (n ¼ 71). BIM implementation barrier network (BIBN) was created using University of California at Irvine Network (UCINET) is a powerful social network analysis software that functions on the principle of social network theory. The experts' opinions were captured through the BIBN network through interviews. Network properties such as eigen vector centrality, betweenness centrality, degree centrality, in-degree and out-degree and clustering coefficient were computed, and the metrics were analysed further. Findings-Twenty-six BIM implementation barriers were initially identified. A questionnaire survey was conducted. The chain reaction can be minimised by prioritising and regulating these barriers. The issues were categorised into fourfold clusters (standardisation, policy and process, cultural and human resources, change management and operational) issues were generated from the exploratory factor analysis (EFA). The obstacles and barriers resulting from the other main barriers associated with it can be minimised by reducing the challenges with high eigenvector centrality but low betweenness importance. Practical implications-This study proves to accelerate sustainable BIM implementation growth in developing nations; this research study assists BIM stakeholders in developing coping mechanisms to monitor and remove BIM implementation barriers. Originality/value-Analysing the associativity of the BIM implementation barriers through sociograms for developing nations is a novel concept with this research.

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Jan 2024

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Sep 2023

Countless efforts were conducted worldwide to obtain the BIM position of markets. Yet, a gap in the contemporary literature to comprehensively assess construction markets’ BIM adoption status (CMBAS) exists. A comprehensive assessment will assist decisionmakers in making insightful decisions regarding the wide adoption of BIM in order to make appropriate strategic decisions. The authors designed a tool to detect the BIM adoption status of construction markets comprehensively to ensure a complete understanding of CMBAS when designing BIM initiatives. The tool was applied to Egypt as an example of a developing market and verified and validated through experts’ reviews. A comparative analysis was performed to benchmark the BIM status of this market throughout the years. Appropriate research methods, sampling techniques, and descriptive and inferential analyses were deployed. It was concluded that BIM professionals in Egypt can play an essential role in spreading BIM to the construction market. The market is changing from the use of AutoCAD 2D to other BIM tools; however, more than half the market reached high BIM levels mostly through self-training, particularly with the deficiency of relevant university courses. A CMBAS tool will facilitate benchmarking BIM status among countries to assist in closing technological gaps with the evolving digital transformation.

An investigation into Macro BIM Maturity and Its impacts: A comparison of Qatar and the United Kingdom

Article

Full-text available

May 2021
Architect Eng Des Manag

Emerging frameworks of BIM implementation have proposed several attributes as measures of macro-scale BIM maturity within countries. Such macro-scale BIM maturity indicators determine the policy and institutional imperatives for BIM diffusion at the national and market levels. Although macro-scale initiatives are enacted to ultimately drive micro-scale (organisational) BIM adoption, it remains unclear whether they have been effective in practice. To ascertain this, the macro-scale BIM maturity of two countries (Qatar and the United Kingdom) are examined in order to identify the influence of the key macro-scale maturity factors on implementation at the micro-scale. Based on expert BIM maturity evaluation and interviews (n=16), the maturity of both countries was ascertained and compared. Subsequently, a survey (n=73) of construction businesses was used to solicit opinions about the relevance of macro-BIM maturity factors to implement at the micro-level. The study further identifies peculiarities with respect to the maturity levels of both countries. The findings indicate that both Qatar and UK have generally comparable levels of macro-BIM maturity, although, in some areas, both countries failed to meet the expectations of organisations in terms of facilitating their BIM adoption at the micro-level. Qatari organisations were of the opinion that further maturity is required in relation to champions and drivers, as well as regulatory frameworks. Similarly, in the UK, organisations were of the view that there was a need for more in terms of champions and drivers as well as noteworthy publications in order to facilitate micro-scale adoption.

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Full-text available

Feb 2021

Lean project delivery system (LPDS) has proven to be an effective productivity improvement method. Despite enormous benefits, the construction industry is struggling with effective implementation of LPDS especially in achieving Lean construction (LC) principles like improving the visualization and maintaining effective flow of information. Concurrently Virtual design and construction (VDC) has opened new windows of opportunities for the construction industry through multidisciplinary integration of design, and construction processes and improving automation through visualization. Using the potentials of VDC to effectively implement LPDS is an area scarcely examined in the current body of knowledge. This study identifies implementation potential of LPDS integrated with VDC, and develops implementation steps to effectively utilize VDC functionalities within the Lean environment using a systematic literature review (SLR) process. The common links between VDC and LDPS are identified through review of academic and practice-based literature. Using a matrix in which potential benefits of VDC are analyzed based on their synergistic impact on Lean principles, a total of 351 positive hypothetical interactions were found between LC and VDC, displaying a strong synergy between them. Moreover, based on the literature, 65 opportunities associated with VDC that support LPDS implementation are identified. Apart from the support by VDC, six (6) areas where Lean intervention can mitigate the challenges faced by VDC are identified. In the end, proposed implementation steps for utilizing VDC within the LPDS environment have been developed. This novel study will help the construction industry improve performance through simultaneous application of LPDS and VDC.

Building Information Modelling in Indonesia: Knowledge, Implementation and Barriers

Article

Full-text available

Dec 2020

This article aims to identify the status of construction industry practitioners in Indonesia in terms of their knowledge and current practices as well as the barriers for implementing Building Information Modelling (BIM). This study utilises a questionnaire survey, aimed at the construction industry practitioners in Indonesia. The result shows that BIM is still a novelty for the construction practitioners in Indonesia. This is backed with the finding that more than 60% of the respondents was not familiar with BIM terminology or did not have proper knowledge of BIM terminology. More than 70% of the respondents' projects have implemented BIM Level 1, mostly in transportation service, energy production and distribution, roads and bridges, and the building infrastructure category. The five highest ranks of barriers to BIM implementation are lack of BIM training, lack of BIM experience and capability, no client demand, high cost in software and hardware acquisition, and inadequate information technology (IT) facilities. The recommended strategy should be initiated by the government, by conducting a comprehensive familiarisation programme covering BIM knowledge, BIM advantages and BIM implementation in the industry. At the same time, the government should prepare regulations and standards as guidance to BIM implementation in Indonesia.

Integrating BIM with Lean Construction approach: Functional requirements and production management software

Article

Dec 2021
AUTOMAT CONSTR

“BeaM!” is a production management system that aims at supporting a BIM-integrated application of Lean Construction Management methods on construction sites. In particular, an advanced variant of the Last Planner System is integrated with BIM information on data processing level. This paper transfers the theoretical concepts of the “BeaM!” production management system into functional requirements for software implementation. The functional requirements are introduced along with a set of use cases and actors. Furthermore, a first prototype built using these functional requirements is presented. The prototype has been demonstrated to and evaluated by a total of 20 domain experts from practice to evaluate the prototype and its underlying functional requirements. Following a Design Science Research approach, the evaluation is focused on practical utility and applicability of the prototype. Findings as obtained from the demonstrations and expert interviews are presented and future development directions are outlined in this paper.

BIM research vs BIM practice: a bibliometric-qualitative analysis from China

Article

Aug 2021

Purpose Understanding the frontier difference between building information modeling (BIM) research and practice is a top priority to guarantee the engineering significance and feasibility of academic achievements, yet such research gap has not been well-explored. The purpose of this paper is to provide an objective and accurate analysis of BIM knowledge using 551 published BIM-related papers and 68 documents of frontier BIM projects in China. Design/methodology/approach This paper adopts the mixed method, combining the bibliometrics method with the qualitative method. Bibliometrics was used to analyze 551 BIM-related literatures from China with Citespace 5.0. Qualitative research was used to analyze 68 project documents from China with Nvivo. Finally, the analysis results are compared to obtain the final conclusion. Findings The analysis results of the collected BIM-related papers, given by bibliometrics analysis, show that the subject categories of engineering, civil engineering, and construction and building technology, and 8 key research clusters are extremely important for development of BIM knowledge. The analysis results of the collected project documents, given by qualitative analysis, indicate that visualization, aided management, intelligent construction, simulation and analysis are the hot applications of BIM practice. Originality/value Through comparison, certain research gaps between the research and practice community in China was identified, which are useful for identification of research trends and practice frontier in BIM community. This study offers useful and new insights to summarize the status quo of BIM and can be used as a reference to integrate future BIM developments.

BIM Adoption in Construction Contracts: Content Analysis Approach

Article

Aug 2021

Building Information Modeling (BIM) is rapidly restructuring the construction industry offering major enhancements in project outcomes. Although the emerging demands for BIM adoption is developing to become an industry norm, yet there are uncertainties concerning the ability of the existing legal paradigm to fully incubate and promote BIM. The existing conventional construction contracts do not cope with the collaborative approach of BIM causing potential contractual aspects to arise. These contractual aspects may become obstacles in the sufficient implementation of BIM and achieving anticipated productivity gains. This research aims to identify the provisions in the contract that should be addressed when BIM is utilized in the project. The research highlights the main contractual issues associated with BIM and explains the current treatment of BIM in contractual documents from standard form of contracts and BIM Protocols. Directed Content analysis method is used to analyze three main standard forms of contracts that adopts BIM and are of different approach of drafting, covering multiparty agreement, partnering agreement and standard bi-party agreement. A comparative study is held between the contracts under investigation, which are PPC2000: Project Partnering Contract, NEC4 ECC: Engineering and Construction Contract and JCT CE: Constructing Excellence Contract. The research presents and assesses the extent to which these standard forms of contracts deal with the contractual issues identified and accordingly the research proposes a drafting structure and framework for provisions that should be included in a BIM based contract.

Systemic BIM Adoption: A Multilevel Perspective

Article

Apr 2021

Systemic innovations require multiple interdependent actors to change their practices simultaneously in order to realise the benefits of the innovation. Building Information Modelling (BIM) has been classified as a systemic innovation that is adopted by building projects, firms, and users. However, the slow diffusion of BIM in the Architecture, Engineering, and Construction (AEC) sector has maintained the gap between BIM visions and actual BIM practice. Some governments are planning to enact policies to promote BIM adoption in construction. However, in some countries, BIM adoption has already started with large construction organisations (i.e., the middle-out diffusion approach). To learn from previous experience and before enacting top-down interventions, policymakers require a model to stimulate systemic BIM adoption for entire supply chains with fragmented project and organisational structures. The current paper investigates systemic adoption of digital innovations in construction and is aimed at formulating a model of systemic BIM adoption (MSBA). Three primary datasets consisting of 133 BIM users, 30 chief executive officers, and 20 project managers were collected in Peru and collectively analysed using cross-classified multilevel modelling (CCMM). It was found that MSBA has five user-, three firm-, and two project-level factors, explaining 28%, 75% and 50% of variance in users’ BIM adoption respectively. The proposed model would provide useful guidance for corporate decision-makers and government policymakers to develop BIM-diffusion policies to accelerate adoption. It would also provide a useful practical implementation framework as the industry progresses towards a digital mode of working and could underpin further digitalisation of the sector worldwide.

The progress and trend of BIM research: A bibliometrics-based visualization analysis

Article

Apr 2021
AUTOMAT CONSTR

As a new and important technology in architecture, engineering, and construction (AEC), Building Information Modeling (BIM) has witnessed a decade of rapid development. It is highly necessary to analyze the research progress and development trend of BIM. Based on 1369 relevant literatures published and the core database “Web of Science”, this study used co-citation analysis, co-word analysis, and cluster analysis to analyze the data and drew the mapping knowledge domains with Citespace software. The results show that BIM research is still in the rapid growth stage. And BIM research is mainly distributed in nine fields. In terms of time sequence, the development of BIM in the past decade developed from data collection to information integration and to knowledge management. The research hotspots are mainly concentrated in eleven directions, which can be further classified into three levels. This paper will provide valuable theoretical and practical reference for the future research of BIM.

Analyzing the Association between Lean Design Management Practices and BIM Uses in the Design of Construction Projects

Article

Jan 2021

Downloaded 26 times Technical Papers Analyzing the Association between Lean Design Management Practices and BIM Uses in the Design of Construction Projects Rodrigo F. Herrera, Ph.D., S.M.ASCE; Claudio Mourgues, Ph.D.; Luis F. Alarcón, Ph.D., M.ASCE; and Eugenio Pellicer, Ph.D., M.ASCE Abstract There is a beneficial effect when integrating Building Information Modeling (BIM) with lean practices to identify and reduce waste in the construction industry. According to experts, it is possible to improve the design process through waste reduction by implementing lean practices and BIM. An unexplored perspective on these synergies concerns the relationship between the specific uses of BIM and lean practices. Therefore, this study analyzed the relationships between Lean Design Management (LDM) practices and BIM uses in the planning and design phases of the infrastructure lifecycle. To achieve this objective, the research was organized into three stages: (1) the explanation of LDM practices and BIM uses; (2) the characterization of sample projects and data collection strategies; and (3) data exploration, including reliability analysis, descriptive statistics, association analysis, and a causal analysis of LDM practices and BIM uses. The analysis of the relationship between LDM practices and BIM uses generated empirical evidence of the implementation of BIM uses and lean management practices at the design phase. LDM practices from the categories planning and control and problem-solving and decision-making were more related to BIM uses than LDM practices from the category stakeholder management. Additionally, it was concluded that if a project applies a higher proportion of BIM uses, it will tend to apply a higher proportion of LDM practices; however, this relationship is not as clear in the other way around.

Obtaining advantages from technology revolution: A patent roadmap for competition analysis and strategy planning

Article

Aug 2019
TECHNOL FORECAST SOC

This paper aims to propose a new kind of patent roadmaps, including a roadmapping method and application directions. The patent roadmap is used to analyze patent competition and develop a patent strategy. In the patent roadmap, patent analysis, patent maps and a generic technology roadmap are used. By using these three methods in combination, two concepts, patent information and patent strategies, are linked. Further, the patent roadmap provides theoretical and informational support for companies, allowing them to learn about the current patent competition situation, and perform corresponding patent layout planning. Compared to previous research on technology and patent roadmaps, this study illustrates the patent competition situation in some industries, and provides a new method for patent strategy planning and its applications. In a case study, this paper presents the patent roadmap of the high-speed railway track (HSRT) industry, specifying the whole roadmapping process and an application in patent planning. Finally, conclusions are drawn that, in applications, the proposed patent roadmap not only plays an important role in helping companies to find new technology opportunities, avoiding duplicate R&D investments, preventing patent infringement risks, and so on, but also has important significance for guiding the overall industry development.

Characteristics and Dynamics of BIM Adoption in China: Social Network Analysis

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