Technology acceptance model for Augmented Reality and Building Information Modeling integration in the construction industry

The digitalization of the construction industry has immense potential for dramatically improving the industry’s practices. Concerning current measures in construction project management, the industry is still dependent on traditional construction methods. However, the application of fully automated techniques within the construction industry has not yet been a widespread practice. Thus, this may explain why there is a slow adaption of digital growth within the construction industry and specifically in developing countries. This study is aiming to investigate the acceptance of Building Information Modeling (BIM) and Augmented Reality (AR) integration in the construction industry. To achieve this aim, Technology Acceptance Model 3 (TAM3) was utilized. The scope was narrowed down to four developing counties (Malaysia, Egypt, Saudi Arabia, and Turkey) and a questionnaire survey was developed and distributed between construction professionals in those countries for data collection purposes. Exploratory Factor Analysis (EFA) was used to develop the TAM, and a regression analysis is used to validate it. The developed TAM3 showed that users control over BIM-AR and perception of easiness of use has the highest influence on their perception of the system usefulness, which would positively affect their intention to use the system. Additionally, unlike the findings of the original TAM3, three variables of Image, Perception of External Control, and Voluntariness illustrate new relations which can be considered as a novel outcome. The outcomes of this study can be used to evaluate the acceptance of BIM-AR Integration in the construction industry context, and the developed TAM3 can be used for the development of new BIM-AR applications in developing countries as it can predict the BIM and AR users’ acceptance.

[1]  Xiangyu Wang,et al.  Design, strategies, and issues towards an augmented reality-based construction training platform , 2007, J. Inf. Technol. Constr..

[2]  I. Ajzen,et al.  Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research , 1977 .

[3]  C. Heckler A Step-by-Step Approach to Using the SAS™ System for Factor Analysis and Structural Equation Modeling , 1996 .

[4]  Oh-Seong Kwon,et al.  A defect management system for reinforced concrete work utilizing BIM, image-matching and augmented reality , 2014 .

[5]  Diana Adler,et al.  Using Multivariate Statistics , 2016 .

[6]  Xiangyu Wang,et al.  Application of Collaborative Mobile System in AR-Based Visualization, Data Storage and Manipulation , 2013, CDVE.

[7]  Weisheng Lu,et al.  RFID-enabled Management System Adoption and Use in Construction: passing through the labyrinth with an Improved Technology Acceptance Model , 2018 .

[8]  Seul-Ki Lee,et al.  Discriminant model of BIM acceptance readiness in a construction organization , 2017 .

[9]  Charles M. Eastman,et al.  BIM Handbook: A Guide to Building Information Modeling for Owners, Managers, Designers, Engineers and Contractors , 2008 .

[10]  José Bravo,et al.  Ambient Intelligence for Health: First International Conference, AmIHEALTH 2015, Puerto Varas, Chile, December 1-4, 2015, Proceedings , 2015, AmIHEALTH.

[11]  Hung-Lin Chi,et al.  Development of user interface for tele-operated cranes , 2012, Adv. Eng. Informatics.

[12]  Seulki Lee,et al.  Comparative Study of BIM Acceptance between Korea and the United States , 2016 .

[13]  B. Tabachnick,et al.  Using multivariate statistics, 5th ed. , 2007 .

[14]  Peter E.D. Love,et al.  BIM + AR: A Framework of Bringing BIM to Construction Site , 2012 .

[15]  M. C. tom Dieck,et al.  A theoretical model of mobile augmented reality acceptance in urban heritage tourism , 2018 .

[16]  Matthew D. Griffith Review of A Step-by-Step Approach to Using SAS for Factor Analysis and Structural Equation Modeling (2nd ed.), by Norm O’Rourke and Larry Hatcher , 2016 .

[17]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[18]  Maslin Masrom,et al.  Technology Acceptance Model and E-learning , 2007 .

[19]  Ruoyu Jin,et al.  The application of Augmented Reality (AR) in the Architecture Engineering and Construction (AEC) industry , 2018 .

[20]  Karen Kensek Building Information Modeling , 2014 .

[21]  Viswanath Venkatesh,et al.  Technology Acceptance Model 3 and a Research Agenda on Interventions , 2008, Decis. Sci..

[22]  Jun Wang,et al.  Comparative analysis on the adoption and use of BIM in road infrastructure projects , 2016 .

[23]  Vineet R. Kamat,et al.  Geospatial Databases and Augmented Reality Visualization for Improving Safety in Urban Excavation Operations , 2010 .

[24]  Sai On Cheung,et al.  Understanding Intention to Use Alternative Dispute Resolution in Construction Projects: Framework Based on Technology Acceptance Model , 2018 .

[25]  Peter E.D. Love,et al.  Augmented Reality in built environment: Classification and implications for future research , 2013 .

[26]  S H Hong,et al.  Identification of external variables for the Technology Acceptance Model(TAM) in the assessment of BIM application for mobile devices , 2018 .

[27]  Sara Shirowzhan,et al.  A Scanner Technology Acceptance Model for Construction Projects , 2017 .

[28]  David Greenwood,et al.  Mobile augmented reality applications for construction projects , 2018 .

[29]  Fred D. Davis,et al.  A Model of the Antecedents of Perceived Ease of Use: Development and Test† , 1996 .

[30]  Ying Wang,et al.  Integrating Augmented Reality with Building Information Modeling: Onsite construction process controlling for liquefied natural gas industry , 2014 .

[31]  C-W. Kim,et al.  The Adoption of Building Information Modeling in the Design Organization: An Empirical Study of Architects inKorean Design Firms , 2014 .

[32]  Thomas Froese,et al.  Impact of Emerging Information Technology on Information Management , 2005 .

[33]  Timothy Jung,et al.  A Theoretical Model of Augmented Reality Acceptance , 2014 .

[34]  Fred D. Davis Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[35]  Javier Irizarry,et al.  BIM2MAR: An Efficient BIM Translation to Mobile Augmented Reality Applications , 2015 .

[36]  Xiangyu Wang,et al.  Using Augmented Reality to Facilitate Piping Assembly: An Experiment-Based Evaluation , 2015, J. Comput. Civ. Eng..

[37]  Weisheng Lu,et al.  Extended Technology-Acceptance Model to Make Smart Construction Systems Successful , 2018, Journal of Construction Engineering and Management.

[38]  Giuseppe Riva,et al.  Ambient Intelligence in Health Care , 2003, Cyberpsychology Behav. Soc. Netw..

[39]  A. N. Zainab,et al.  Collection security management at university libraries: assessment of its implementation status , 2011, ArXiv.

[40]  Viswanath Venkatesh,et al.  Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model , 2000, Inf. Syst. Res..

[41]  Peter E.D. Love,et al.  Integrating mobile Building Information Modelling and Augmented Reality systems: An experimental study , 2018 .

[42]  Fred D. Davis User Acceptance of Information Technology: System Characteristics, User Perceptions and Behavioral Impacts , 1993, Int. J. Man Mach. Stud..

[43]  Andy P. Field,et al.  Discovering Statistics Using SPSS , 2000 .

[44]  Xiangyu Wang,et al.  Research trends and opportunities of augmented reality applications in architecture, engineering, and construction , 2013 .

[45]  An Gie Yong,et al.  A Beginner's Guide to Factor Analysis: Focusing on Exploratory Factor Analysis , 2013 .

[46]  Geoff Zeiss,et al.  Building Information Modeling , 2021, Wendehorst Bautechnische Zahlentafeln.

[47]  Sara Rankohi,et al.  Review and analysis of augmented reality literature for construction industry , 2013 .