Testing a Measurement Model of BIM Potential Benefits in Iraqi Construction Projects
Vol. 3 No. 12 (2017): December
Research Articles
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Building Information Modeling (BIM) is an integrated and comprehensive system for all that related to the construction project, which includes a set of effective policies, procedures, and computer applications that increase the performance of the project during its life cycle. The objective of this research develops a clear concept about the BIM adoption in Iraq through investigating potential benefits that can be obtained through its application in construction projects also build a measurement model for these benefits. The research methodology was based on quantitative approach which adopted by conducting a questionnaire directed to professionals in the field of construction projects in the public and private sectors supported by personal interviews with respondents either individually or in groups. Three hundred copies of the forms were distributed to the companies, firms and engineering departments of the various ministries of the state. After the data was obtained, two software (SPSS and SmartPLS) was used for analyzing the data and constructing the measurement model. The results showed of all the benefits constructed within three key components. The first is knowledge support for management in term of (costs, data, processes), the second is effective design performance and the third is effective construction performance and all these components were modeled as a measurement model.
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[2] Azhar, S., et al. Building Information Modeling (BIM): A new Paradigm for Visual Interactive Modeling and Simulation for Construction Projects. in Proc., First International Conference on Construction in Developing Countries. 2008.
[3] Succar, B., Building Information Modelling Framework: A Research and Delivery Foundation for Industry Stakeholders. Automation in construction, 2009. 18(3): p. 357-375.doi: 10.1016/j.autcon.2008.10.003.
[4] Chan, C.T., Barriers of Implementing BIM in Construction Industry from the Designers' Perspective: A Hong Kong Experience. Journal of System and Management Sciences, 2014. 4(2): p. 24-40.
[5] Azhar, S., M. Khalfan, and T. Maqsood, Building Information Modelling (BIM): Now and Beyond. Construction Economics and Building, 2015. 12(4): p. 15-28.doi: 10.5130/ajceb.v12i4.3032.
[6] Eastman, C.M., et al., BIM handbook: A Guide to Building Information Modeling for Owners, Managers, Designers, Engineers and Contractors. 2nd Edition ed. 2011, United States: John Wiley & Sons. doi: 10.5130/ajceb.v12i3.2749.
[7] Arayici, Y., C. Egbu, and S. Coates, Building Information Modelling (BIM) Implementation and Remote Construction Projects: Issues, Challenges, and Critiques. Journal of Information Technology in Construction, 2012. 17(Management of remote construction sites and the role of IT Systems): p. 75-92.
[8] Memon, A.H., et al., BIM in Malaysian Construction Industry: Status, Advantages, Barriers and Strategies to Enhance The Implementation Level. Research Journal of Applied Sciences, Engineering and Technology, 2014. 8(5): p. 606-614.doi: 10.19026/rjaset.8.1012.
[9] Chen, L. and H. Qu, Evaluation for "Economics and Legislative Factors Influence the Design Team and Contractor Throughout a Building Project From Inception to Completion". Journal of System and Management Sciences, 2011. 1(6): p. 94-108.
[10] Nagalingam, G., H.S. Jayasena, and K. Ranadewa. Building Information Modelling and Future Quantity Surveyor's Practice in Sri Lankan Construction Industry. in The Second World Construction Symposium. 2013.
[11] CRC Construction Innovation, Adopting BIM for Facilities Management: Solutions for Managing The Sydney Opera House, in Cooperative Research Center for Construction Innovation. 2007: Brisbane, Australia.
[12] Kekana, C.O. Aigbavboa, and W.D. Thwala. Building Information Modelling (BIM): Barriers in Adoption and Implementation Strategies in the South Africa Construction Industry. in International Conference on Emerging Trends in Computer and Image Processing. 2014. Thailand.
[13] Smith, D.K. and M. Tardif, Building Information Modeling: A Strategic Implementation Guide for Architects, Engineers, Constructors, and Real Estate Asset Managers. 1st Edition ed. 2009, United States: John Wiley & Sons. doi: 10.1002/9780470432846.
[14] Ahmad, M.A., Peter Demian , and Andrew D.F Price. BIM Implementation Plans: A Comparative Analysis. in In: Smith, S. D., (Ed). 28th Annual ARCOM Conference, 3-5 September 2012, Edinburgh, UK: Association of Researchers in Construction Management. 2012.
[15] Yamazaki, Y., et al., 3D/BIM applications to large-scale complex building projects in Japan. International Journal of High-Rise Buildings, 2014. 3(4): p. 311-323.
[16] Azhar, S., Building Information Modeling (BIM): Trends, Benefits, Risks, and Challenges for the AEC Industry. Leadership and Management in Engineering, 2011. 11(3): p. 241-252.doi: 10.1061/(asce)lm.1943-5630.000012.
[17] Schade, J., T. Olofsson, and M. Schreyer, Decision"making in a model"based design process. Construction management and Economics, 2011. 29(4): p. 371-382.doi: 10.1080/01446193.2011.552510.
[18] Nawari, N.O. and M. Kuenstle, Building information modeling: Framework for structural design. 2015: CRC Press. doi: 10.1201/b18355.
[19] Hergunsel, M.F., Benefits of Building Information Modeling for Construction Managers and BIM Based Scheduling. 2011.
[20] Holness, G., Building Information Modeling: Future Direction of the Design and Construction Industry. ASHRAE Journal, August 2006, 2006. 48(8): p. 38-46.
[21] Nassar, K. The Effect of Building Information Modeling on the Accuracy of Estimates. in The sixth annual AUC research conference. Cairo: The American University. 2010. Retrieved from http://ascpro.ascweb.org/chair/paper/CPRT155002010.pdf.
[22] Arayici, Y., et al., Technology adoption in the BIM implementation for lean architectural practice. Automation in Construction, 2011. 20(2): p. 189-195.doi: 10.1016/j.autcon.2010.09.016.
[23] Barlish, K. and K. Sullivan, How to Measure the Benefits of BIM”A Case Study Approach. Automation in construction, 2012. 24: p. 149-159.doi: 10.1016/j.autcon.2012.02.008.
[24] Linderoth, H.C., Understanding Adoption and Use of BIM as the Creation of Actor Networks. Automation in construction, 2010. 19(1): p. 66-72.doi: 10.1016/j.autcon.2009.09.003.
[25] Sebastian, R., Changing Roles of the Clients, Architects and Contractors Through BIM. Engineering, Construction and Architectural Management, 2011. 18(2): p. 176-187.doi: 10.1108/09699981111111148.
[26] Forbes, L.H. and S.M. Ahmed, Modern construction: lean Project Delivery and Integrated Practices. 1st Edition ed. 2010, United States: CRC Press. doi: 10.1201/b10260.
[27] Love, P.E., et al., From Justification to Evaluation: Building Information Modeling for Asset Owners. Automation in construction, 2013. 35: p. 208-216.doi: 10.1016/j.autcon.2013.05.008.
[28] Likert, R., A Technique for the Measurement of Attitudes. Archives of psychology, 1932. 144(55): p. 1-55.
[29] Field, A., Discovering Statistics Using SPSS. 4th Edition ed. 2009, United States: SAGE Publications. doi: 10.1002/bjs.7040.
[30] Tabachnick, B.G. and L.S. Fidell, Using Multivariate Statistics. 5th Edition ed. 2013, United Kingdom: Pearson Education.
[31] Pallant, J., SPSS Survival Manual: A Step by Step Guide to Data Analysis Using IBM SPSS. 6th Edition ed. 2016, Australia: Allen & Unwin. doi: 10.1111/1753-6405.12166.
[32] Norris, M. and L. Lecavalier, Evaluating the Use of Exploratory Factor Analysis in Developmental Disability Psychological Research. Journal of autism and developmental disorders, 2010. 40(1): p. 8-20.doi: 10.1007/s10803-009-0816-2.
[33] Yong, A.G. and S. Pearce, A Beginner's Guide to Factor Analysis: Focusing on Exploratory Factor Analysis. Tutorials in quantitative methods for psychology, 2013. 9(2): p. 79-94.doi: 10.20982/tqmp.09.2.p079.
[34] Mertler, C.A. and R.V. Reinhart, Advanced and Multivariate Statistical Methods: Practical Application and Interpretation. 6th Edition ed. 2016, United Kingdom: Routledge. doi: 10.4324/9781315266978.
[35] Baggio, R. and J.E. Klobas, Quantitative Methods in Tourism: A handbook. 1st Edition ed. Vol. 48. 2011, United Kingdom: Channel View Publications. doi: 10.21832/baggio6195.
[36] Brown, T.A., Confirmatory Factor Analysis for Applied Research. 2nd Edition ed. 2014, United States: Guilford Publications. doi: 10.1198/tas.2008.s98.
[37] Schumacker, R.E. and R.G. Lomax, A Beginner's Guide to Structural Equation Modeling. 4th Edition ed. 2015, United Kingdom: Taylor & Francis. doi: 10.1080/10705511.2011.607726.
[38] Hair, J.F., et al., A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). 2nd Edition ed. 2014, United States: SAGE. doi: 10.1080/1743727x.2015.1005806.
[39] Henseler, J., C.M. Ringle, and M. Sarstedt, A New Criterion for Assessing Discriminant Validity in Variance-Based Structural Equation Modeling. Journal of the Academy of Marketing Science, 2015. 43(1): p. 115-135.doi: 10.1007/s11747-014-0403-8.
[40] Hair, J.F., et al., A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). 3rd Edition ed. 2016, United States: SAGE. doi: 10.1108/IMDS-04-2016-0130.
[41] Joseph, F., et al., Multivariate Data Analysis: A Global Perspective (7th (Global Edition) ed.). 7th Edition ed. 2010, United States: Prentice Hall.
[42] Afthanorhan, W., A comparison of partial least square structural equation modeling (PLS-SEM) and covariance based structural equation modeling (CB-SEM) for confirmatory factor analysis. International Journal of Engineering Science and Innovative Technology, 2013. 2(5): p. 198-205.
[43] Wilson, B. and J. Henseler. Modeling reflective higher-order constructs using three approaches with PLS path modeling: a Monte Carlo comparison. 2007. ANZMAC. Retrieved from https://research.utwente.nl/en/publications/modeling-reflective-higher-order-constructs-using-three-approache.
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