Impacts of building information modeling (BIM) implementation on design and construction performance: a resource dependence theory perspective

doi:10.15302/J-FEM-2017010

摘要
图/表
参考文献
相关文章
多维度评价

全文: PDF(462 KB) HTML
导出: BibTeX | EndNote | Reference Manager | ProCite | RefWorks

摘要

利用资源依赖理论，本文构建并实例验证了一个模型以解释在建设项目中建筑信息模型（BIM）的应用是如何通过提高组织间协作能力从而对不同项目参与方绩效产生影响的。基于从来自中国应用BIM的建设项目的设计师和总承包商处收集到的两组调查数据，偏最小二乘的结果分析和自助中介效应测试明确表明，基于BIM的信息共享和协同决策功能作为一个整体在提高设计师和总承包商两方的基于BIM的效率和效果方面发挥着重要的作用。研究结果进一步表明，设计师和总承包商在项目BIM实施活动中受益并非等同，而这种非等价关系与在基于BIM的跨组织资源交换过程中设计者和总承包商所扮演的不同角色密切相关。这些发现验证了BIM作为管理建设项目中的跨组织资源依赖性的跨界工具的资源依赖理论视角，并且有助于加深理解如何以及为何项目参与方会不同程度的受益于像BIM这样的组织间信息技术的应用。

Abstract：

Drawing on resource dependence theory, this paper develops and empirically tests a model for understanding how the implementation of building information modeling (BIM) in construction projects impacts the performance of different project participating organizations through improving their interorganizational collaboration capabilities. Based on two sets of survey data collected from designers and general contractors in BIM-based construction projects in China, the results from partial least squares analysis and bootstrapping mediation test provide clear evidence that BIM-enabled capabilities of information sharing and collaborative decision-making as a whole play a significant role in determining BIM-enabled efficiency and effectiveness benefits for both designers and general contractors. The results further reveal that designers and general contractors benefit from project BIM implementation activities significantly non-equivalently, and that this non-equivalence closely relates to the different roles played by designers and general contractors in BIM-enabled interorganizational resource exchange processes. The findings validate the resource dependence theory perspective of BIM as a boundary spanning tool to manage interorganizational resource dependence in construction projects, and contribute to deepened understandings of how and why project participating organizations benefit differently from the implementation of interorganizational information technologies like BIM.

Keywords building information modeling interorganizational collaboration construction project performance resource dependence theory partial least squares modeling

通讯作者: 曹冬平 E-mail: dongping.cao@connect.polyu.hk

在线预览日期: 发布日期: 2017-04-19

	服务

	推荐给朋友
	免费邮件订阅
	RSS订阅
	作者相关文章

	Dongping CAO
	Heng LI
	Guangbin WANG

引用本文:

Dongping CAO,Heng LI,Guangbin WANG. Impacts of building information modeling (BIM) implementation on design and construction performance: a resource dependence theory perspective[J]. Front. Eng, 2017, 4(1): 20-34.

网址:

https://journal.hep.com.cn/fem/EN/10.15302/J-FEM-2017010 OR https://journal.hep.com.cn/fem/EN/Y2017/V4/I1/20

Fig.1 Research model

Construct	Code	Items	Factor loadings
Construct	Code	Items	Designer	Contractor
BIM-enabled information sharing capability (ISC)	ISC1	Based on BIM models, our team has been enabled to share information with other related participants in a timely manner	0.916	0.890
	ISC2	Based on BIM models, our team has been enabled to share information with other related participants in a complete manner	0.933	0.926
	ISC3	Based on BIM models, our team has been enabled to share information with other related participants in an accurate manner	0.943	0.920
	ISC4	Based on BIM models, our team has been enabled to share information with other related participants in a consistent manner	0.844	0.857
BIM-enabled collaborative decision-making capability (CDC)	CDC1	Based on BIM models, our team has been enabled to regularly collaborate with other related participants to jointly formulate design/construction plans	0.857	0.897
	CDC2	Based on BIM models, our team has been enabled to regularly collaborate with other related participants to jointly compare and select design/construction solutions	0.906	0.916
	CDC3	Based on BIM models, our team has been enabled to regularly collaborate with other related participants to jointly adjust and optimize design/construction solutions	0.870	0.933
	CDC4	Based on BIM models, our team has been enabled to regularly collaborate with other related participants to jointly solve emergent design/construction problems	0.911	0.875
BIM-enabled task efficiency improvement (TEY)	TEY1	BIM implementation has enabled a faster execution of our team's design/construction activities	0.898	0.927
	TEY2	BIM implementation has increased our team's productivity in related design and construction processes	0.941	0.946
	TEY3	BIM implementation has saved time for our team to conduct related design/construction activities	0.945	0.887
BIM-enabled task effectiveness improvement (TES)	TES1	BIM implementation has reduced errors and rework in our team's design/construction activities	0.850	0.813
	TES2	BIM implementation has helped our team to explore better design/construction solutions with higher quality and less cost	0.884	0.897
	TES3	BIM implementation has enabled our team's design/construction outcomes to more satisfactorily fulfill the client/owner's needs	0.901	0.867

Tab.1 Measurement items

Tab.2 Demographic information

Tab.3 Measurement validity and construct correlations: Designer sample

Tab.4 Measurement validity and construct correlations: General contractor sample

Fig.2 Results of PLS analyses for the research model

Tab.5 Mediation effects of BIM-enabled interorganizational collaboration capabilities

Tab.6 Comparisons of construct values for designer and general contractor samples

1	Allred C R, Fawcett S E, Wallin C, Magnan G M (2011). A dynamic collaboration capability as a source of competitive advantage. Decision Sciences, 42(1): 129–161 https://doi.org/10.1111/j.1540-5915.2010.00304.x
2	Barlish K, Sullivan K (2012). How to measure the benefits of BIM–A case study approach. Automation in Construction, 24: 149–159 https://doi.org/10.1016/j.autcon.2012.02.008
3	Bernstein H M (2015). The Business Value of BIM in China. Dodge Data and Analytics, Bedford, MA
4	Bryde D, Broquetas M, Volm J M (2013). The project benefits of building information modelling (BIM). International Journal of Project Management, 31(7): 971–980 https://doi.org/10.1016/j.ijproman.2012.12.001
5	Cao D, Li H, Wang G (2014). Impacts of isomorphic pressures on BIM adoption in construction projects. Journal of Construction Engineering and Management, 140(12): 04014056 https://doi.org/10.1061/(ASCE)CO.1943-7862.0000903
6	Cao D, Li H, Wang G, Zhang W (2016). Linking the motivations and practices of design organizations to implement building information modeling in construction projects: empirical study in China. Journal of Management Engineering, 32(6): 04016013 https://doi.org/10.1061/(ASCE)ME.1943-5479.0000453
7	Cao D, Wang G, Li H, Skitmore M, Huang T, Zhang W (2015). Practices and effectiveness of building information modelling in construction projects in China. Automation in Construction, 49: 113–122 https://doi.org/10.1016/j.autcon.2014.10.014
8	Cao M, Zhang Q (2011). Supply chain collaboration: impact on collaborative advantage and firm performance. Journal of Operations Management, 29(3): 163–180 https://doi.org/10.1016/j.jom.2010.12.008
9	Chopra S, Meindl P (2001). Supply Chain Management: Strategy, Planning and Operation. Prentice Hall, Upper Saddle River, NJ
10	Ding L, Zhou Y, Akinci B (2014). Building information modeling (BIM) application framework: the process of expanding from 3D to computable nD. Automation in Construction, 46: 82–93 https://doi.org/10.1016/j.autcon.2014.04.009
11	Dossick C S, Neff G (2010). Organizational divisions in BIM-enabled commercial construction. Journal of Construction Engineering and Management, 136(4): 459–467 https://doi.org/10.1061/(ASCE)CO.1943-7862.0000109
12	Eastman C, Teicholz P, Sacks R, Liston K. (2011). BIM Handbook: A Guide to Building Information Modeling for Owners, Managers, Designers, Engineers and Contractors (2nd ed.). Hoboken: John Wiley and Sons
13	Emerson R M (1962). Power-dependence relations. American Sociological Review, 27(1): 31–41 https://doi.org/10.2307/2089716
14	Fornell C, Larcker D F (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1): 39–50 https://doi.org/10.2307/3151312
15	Francom T C, El Asmar M (2015). Project quality and change performance differences associated with the use of building information modeling in design and construction projects: Univariate and multivariate analyses. Journal of Construction Engineering and Management, 141(9): 04015028 https://doi.org/10.1061/(ASCE)CO.1943-7862.0000992
16	Froese T M (2010). The impact of emerging information technology on project management for construction. Automation in Construction, 19(5): 531–538 https://doi.org/10.1016/j.autcon.2009.11.004
17	Gao J, Fischer M (2008). Framework and Case Studies Comparing Implementations and Impacts of 3D/4D Modeling across Projects. Center for Integrated Facility Engineering, Stanford University Stanford, CA
18	Gattiker T F, Goodhue D L (2005). What happens after ERP implementation: understanding the impact of interdependence and differentiation on plant-level outcomes. Management Information Systems Quarterly, 29(3): 559–585
19	Giel B K, Issa R R A (2013). Return on investment analysis of using building information modeling in construction. Journal of Computing in Civil Engineering, 27(5): 511–521 https://doi.org/10.1061/(ASCE)CP.1943-5487.0000164
20	Hair J F, Sarstedt M, Ringle C M, Mena J A (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science, 40(3): 414–433 https://doi.org/10.1007/s11747-011-0261-6
21	Hartmann T, Gao J, Fischer M (2008). Areas of application for 3D and 4D models on construction projects. Journal of Construction Engineering and Management, 134(10): 776–785 https://doi.org/10.1061/(ASCE)0733-9364(2008)134:10(776)
22	Hoegl M, Gemuenden H G (2001). Teamwork quality and the success of innovative projects: a theoretical concept and empirical evidence. Organization Science, 12(4): 435–449 https://doi.org/10.1287/orsc.12.4.435.10635
23	Karimi J, Somers T M, Bhattacherjee A (2007). The impact of ERP implementation on business process outcomes: A factor-based study. Journal of Management Information Systems, 24(1): 101–134 https://doi.org/10.2753/MIS0742-1222240103
24	Lamming R C (1996). Squaring lean supply with supply chain management. International Journal of Operations & Production Management, 16(2): 183–196 https://doi.org/10.1108/01443579610109910
25	Lee G, Lee J, Jones S A (2012). The Business Value of BIM in South Korea. McGraw Hill Construction, Bedford, MA
26	Li H, Lu W, Huang T (2009). Rethinking project management and exploring virtual design and construction as a potential solution. Construction Management and Economics, 27(4): 363–371 https://doi.org/10.1080/01446190902838217
27	Lopez R, Love P E (2012). Design error costs in construction projects. Journal of Construction Engineering and Management, 138(5): 585–593 https://doi.org/10.1061/(ASCE)CO.1943-7862.0000454
28	Lu W, Fung A, Peng Y, Liang C, Rowlinson S (2014). Cost-benefit analysis of Building Information Modeling implementation in building projects through demystification of time-effort distribution curves. Building and Environment, 82: 317–327 https://doi.org/10.1016/j.buildenv.2014.08.030
29	Pfeffer J (1982). Organization and Organizational Theory. Pitman, Boston, MA
30	Pfeffer J, Salancik G R (1978). The External Control of Organizations: A Resource Dependence Perspective. New York: Harper & Row
31	Podsakoff P M, Organ D W (1986). Self-reports in organizational research: problems and prospects. Journal of Management, 12(4): 531–544 https://doi.org/10.1177/014920638601200408
32	Poirier E A, Staub-French S, Forgues D (2015). Measuring the impact of BIM on labor productivity in a small specialty contracting enterprise through action-research. Automation in Construction, 58: 74–84 https://doi.org/10.1016/j.autcon.2015.07.002
33	Preacher K J, Hayes A F (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods, Instruments, & Computers, 36(4): 717–731 https://doi.org/10.3758/BF03206553 pmid: 15641418
34	Preacher K J, Hayes A F (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, Instruments, & Computers, 40(3): 879–891 https://doi.org/10.3758/BRM.40.3.879 pmid: 18697684
35	Rai A, Patnayakuni R, Seth N (2006). Firm performance impacts of digitally enabled supply chain integration capabilities. Management Information Systems Quarterly, 30(2): 225–246
36	Sacks R, Barak R (2008). Impact of three-dimensional parametric modeling of buildings on productivity in structural engineering practice. Automation in Construction, 17(4): 439–449 https://doi.org/10.1016/j.autcon.2007.08.003
37	Sahin F, Robinson E P Jr (2005). Information sharing and coordination in make-to-order supply chains. Journal of Operations Management, 23(6): 579–598 https://doi.org/10.1016/j.jom.2004.08.007
38	Scheer L K, Kumar N, Steenkamp J B E (2003). Reactions to perceived inequity in US and Dutch interorganizational relationships. Academy of Management Journal, 46(3): 303–316 https://doi.org/10.2307/30040624
39	Shen F Y, Chang A S (2011). Exploring coordination goals of construction projects. Journal of Management Engineering, 27(2): 90–96 https://doi.org/10.1061/(ASCE)ME.1943-5479.0000046
40	Smits W, van Buiten M, Hartmann T (2016). Yield-to-BIM: impacts of BIM maturity on project performance. Building Research and Information (in press)
41	Ian Stuart F, McCutcheon D (1996). Sustaining strategic supplier alliances. International Journal of Operations & Production Management, 16(10): 5–22 https://doi.org/10.1108/01443579610130664
42	Succar B (2009). Building information modelling framework: a research and delivery foundation for industry stakeholders. Automation in Construction, 18(3): 357–375 https://doi.org/10.1016/j.autcon.2008.10.003
43	Taylor J E (2007). Antecedents of successful three-dimensional computer-aided design implementation in design and construction networks. Journal of Construction Engineering and Management, 133(12): 993–1002 https://doi.org/10.1061/(ASCE)0733-9364(2007)133:12(993)
44	Volk R, Stengel J, Schultmann F (2014). Building information modeling (BIM) for existing buildings—Literature review and future needs. Automation in Construction, 38: 109–127 https://doi.org/10.1016/j.autcon.2013.10.023
45	Winch G M (2010). Managing Construction Projects: An Information Processing Approach (2nd ed.). Oxford: Wiley-Blackwell
46	Won J, Lee G (2016). How to tell if a BIM project is successful: a goal-driven approach. Automation in Construction, 69: 34–43 https://doi.org/10.1016/j.autcon.2016.05.022
47	Wong C W, Lai K H, Cheng T C E, Lun Y H V (2015). The role of IT-enabled collaborative decision making in inter-organizational information integration to improve customer service performance. International Journal of Production Economics, 159: 56–65 https://doi.org/10.1016/j.ijpe.2014.02.019
48	Yalcinkaya M, Singh V (2015). Patterns and trends in building information modeling (BIM) research: a latent semantic analysis. Automation in Construction, 59: 68–80 https://doi.org/10.1016/j.autcon.2015.07.012
49	Yan T, Dooley K (2014). Buyer-supplier collaboration quality in new product development projects. Journal of Supply Chain Management, 50(2): 59–83 https://doi.org/10.1111/jscm.12032
50	Zhang W, Cao D, Wang G (2008). The construction industry in China: Its bidding system and use of performance information. Journal for the Advancement of Performance Information and Value, 1(1): 6–19
51	Zhu K, Kraemer K L, Xu S (2006). The process of innovation assimilation by firms in different countries: a technology diffusion perspective on E-Business. Management Science, 52(10): 1557–1576 https://doi.org/10.1287/mnsc.1050.0487

No related articles found!

Viewed

Full text

Abstract

Cited

Shared

Discussed