Identifying critical factors that affect the application of information technology in construction management: A case study of China

Abstract

The new mode for managing construction projects with information technology (IT) has attracted worldwide attention because it can help managers and workers perform tasks and bring potential benefits, such as high-quality products and accident-free production, effectively. However, the application of IT in site have not achieved expected results because it is faced with many constraints caused by internal factors from enterprises and projects and external factors from the government and environment. Although many relevant studies have discussed the constraints of implementing different IT and devices in the construction industry or site, few articles have specifically focused on identifying and analyzing the indicator system. In this work, we took China as the background, scientifically identified 23 influential factors that affect the implementation of IT in construction management through literature review and expert interviews. Subsequently, questionnaires were issued, and Delphi method was used to obtain empirical data that aimed at four different management fields. Then, an efficient and convenient method called DEMATEL was used to deal with these data. Afterward, the factors were divided into four categories, namely, core, diving, independent, and impact factors. Finally, the similarities and differences of the analysis results from the four fields were compared, and the key factors were identified. Results show that the cross-domain talent ability, concept and value cognition, and organization structure are core factors in all management fields that should be managed first along with the IT innovation ability in the enterprise. The formulation of technical standards and related device and training input are also critical in specific fields. Strategic planning plays a role in macro control and promotion. Data management and application, platform construction, solution, and collaboration have direct impacts on information management. The research results provide suggestions not only for the government to formulate effective policies for IT application and promotion in construction industry, but also for enterprises to take measures in improving management efficiency in the construction site and realizing its substantial benefits.

Graphical abstract

Keywords

information technology / construction manage-ment / influential factors / empirical study / DEMATEL

References

[1] Asgari Z, Rahimian F P (2017). Advanced virtual reality applications and intelligent agents for construction process optimisation and defect prevention. Procedia Engineering, 196: 1130–1137

[2] Azhar S (2011). Building Information Modeling (BIM): Trends, benefits, risks, and challenges for the AEC industry. Leadership and Management in Engineering, 11(3): 241–252

[3] BIM Committee (2012). AEC (UK) BIM Protocol, version 2.0

[4] Blayse A M, Manley K (2004). Key influences on construction innovation. Construction Innovation, 4(3): 143–154

[5] Cheng C, Shen K C, Li X D, Zhang Z H (2017). Major barriers to different kinds of prefabricated public housing in China: The developers’ perspective. In: ICCREM—Prefabricated Buildings, Industrialized Construction, and Public-Private Partnerships, 79–88

[6] Chien K F, Wu Z H, Huang S C (2014). Identifying and assessing critical risk factors for BIM projects: Empirical study. Automation in Construction, 45: 1–15

[7] Cinite I, Duxbury L E (2018). Measuring the behavioral properties of commitment and resistance to organizational change. Journal of Applied Behavioral Science, 54(2): 113–139

[8] Ding X H, Feng J G (2019). Construction and application of intelligent safety supervision system. Building Economy, 40(7): 12–15 (in Chinese)

[9] Ding X, Li Z, Lu B (2019a). Study on the problems and countermeasures in the government’s promotion of intelligent construction site. Construction Safety, 34(2): 58–62 (in Chinese)

[10] Ding Z K, Liu S, Liao L H, Zhang L (2019b). A digital construction framework integrating building information modeling and reverse engineering technologies for renovation projects. Automation in Construction, 102: 45–58

[11] Eadie R, Browne M, Odeyinka H, McKeown C, McNiff S (2013). BIM implementation throughout the UK construction project lifecycle: An analysis. Automation in Construction, 36: 145–151

[12] Gan Y Y, Shen L Y, Chen J D, Tam V, Tan Y, Illankoon I (2017). Critical factors affecting the quality of industrialized building system projects in China. Sustainability, 9(2): 216–228

[13] General Office of the State Council (2017). Opinions on promoting the sustainable and healthy development of the construction industry (in Chinese)

[14] GOV.UK: Department for Business, Energy & Industrial Strategy (2013). Construction 2025. Industrial Strategy: Government and industry in partnership

[15] Guan S C, Zhu M R (2010). Identification of the influence factors of enterprise informatization construction and empirical study basing on grey relational theory. In: Proceedings of 17th International Conference on Management Science & Engineering. Melbourne: IEEE, 240–246

[16] Hammad A, Vahdatikhaki F, Zhang C, Mawlana M, Doriani A (2012). Towards the smart construction site: Improving productivity and safety of construction projects using multi-agent systems, real-time simulation and automated machine control. In: Proceedings of the Winter Simulation Conference (WSC). Berlin: IEEE, 1–12

[17] Hardie M, Newell G (2011). Factors influencing technical innovation in construction SMEs: An Australian perspective. Engineering, Construction, and Architectural Management, 18(6): 618–636

[18] Jung Y, Joo M (2011). Building information modelling (BIM) framework for practical implementation. Automation in Construction, 20(2): 126–133

[19] Kang T W, Hong C H (2015). A study on software architecture for effective BIM/GIS-based facility management data integration. Automation in Construction, 54: 25–38

[20] Koolwijk J S J, Vanoel C J, Waelink J W F, Vrijhoef R (2018). Collaboration and integration in project-based supply chains in the construction industry. Journal of Management Engineering, 34(3): 34–42

[21] Kuenzel R, Teizer J, Mueller M, Blickle A (2016). SmartSite: Intelligent and autonomous environments, machinery, and processes to realize smart road construction projects. Automation in Construction, 71: 21–33

[22] Lam P T, Chan E H, Poon C S, Chau C K, Chun K P (2010). Factors affecting the implementation of green specifications in construction. Journal of Environmental Management, 91(3): 654–661

[23] Lee S, Yu J, Jeong D (2015). BIM acceptance model in construction organizations. Journal of Management in Engineering, 31(3): 04014048

[24] Li C Z D, Xue F, Li X, Hong J, Shen G Q (2018). An Internet of Things-enabled BIM platform for on-site assembly services in prefabricated construction. Automation in Construction, 89: 146–161

[25] Li R Y M (2015). Construction safety knowledge sharing via smart phone Apps and technologies. In: Zhang Y, Cristol D, eds. Handbook of Mobile Teaching and Learning. Heidelberg: Springer, 261–273

[26] Liu H, Wang M J, Skibniewski M J, He J S, Zhang Z S (2014). Identification of critical success factors for construction innovation: From the perspective of strategic cooperation. Frontiers of Engineering Management, 1(2): 202–209

[27] Liu J, Li G C, Zhang B B (2019). Research on intelligent site management system based on general integration methodology. Journal of Luoyang Institute of Science and Technology (Natural Science Edition), 29(1): 25–29 (in Chinese)

[28] Mao Z B (2017). Promote the construction of smart sites to facilitate the sustainable and healthy development of the construction industry. Journal of Engineering Management, 31(5): 80–84 (in Chinese)

[29] McClary S (2011). Two go at RICS after “improper behaviour”. Estates Gazette, 11/26/2011-1147-33

[30] MOHURD (2016). Informatization development outline in construction industry (2016–2020) (in Chinese)

[31] MOHURD (2017a). The 13th Five-Year Plan for scientific and technological innovation in urban and rural housing development(in Chinese)

[32] MOHURD (2017b). 10 new technologies in the construction industry (in Chinese)

[33] MOHURD (2018). Technical standard for supervision information system in construction site (in Chinese)

[34] Nguyen P T, Vo K D, Phan P T, Nguyen T A, Cao T M, Huynh V D B, Nguyen Q L H T T (2018). Construction project quality management using Building Information Modeling 360 Field. International Journal of Advanced Computer Science and Applications, 9(10): 228–233

[35] Nitithamyong P, Skibniewski M J (2006). Success/Failure factors and performance measures of web-based construction project management systems: Professionals’ viewpoint. Journal of Construction Engineering and Management, 132(1): 80–87

[36] Niu Y H, Lu W S, Chen K, Huang G G, Anumba C (2016). Smart construction objects. Journal of Computing in Civil Engineering, 30(4): 04015070

[37] Ren J, Lützen M, Rasmussen H B (2018). Identification of success factors for green shipping with measurement of greenness based on ANP and ISM. In: Lee P W, Yang Z, eds. Multi-Criteria Decision Making in Maritime Studies and Logistics, International Series in Operations Research & Management Science. Cham: Springer, 260: 79–103

[38] Rossi A, Vila Y, Lusiani F, Barsotti L, Sani L, Ceccarelli P, Lanzetta M (2019). Embedded smart sensor device in construction site machinery. Computers in Industry, 108: 12–20

[39] Rowe G, Wright G (2013). The Delphi technique as a forecasting tool: Issues and analysis. International Journal of Forecasting, 15(4): 353–375

[40] Sargent K, Hyland P, Sawang S (2012). Factors influencing the adoption of information technology in a construction business. Australasian Journal of Construction Economics and Building, 12(2): 72–86

[41] Saurin T A (2016). Safety inspections in construction sites: A systems thinking perspective. Accident Analysis & Prevention, 93: 240–250

[42] Seyed-Hosseini S M, Safaei N, Asgharpour M J (2006). Reprioritization of failures in a system failure mode and effects analysis by decision making trial and evaluation laboratory technique. Reliability Engineering & System Safety, 91(8): 872–881

[43] Shi J H, Liang L, Shi T L (2019). The discussion of application of intelligent site system in construction process. China Southern Agricultural Machinery, 50(11): 203–253 (in Chinese)

[44] Silverio-Fernández M, Renukappa S, Suresh S (2019).Evaluating critical success factors for implementing smart devices in the construction industry: An empirical study in the Dominican Republic. Engineering, Construction and Architectural Management, 7(1): 15–29

[45] Teizer J (2015). Status quo and open challenges in vision-based sensing and tracking of temporary resources on infrastructure construction sites. Advanced Engineering Informatics, 29(2): 225–238

[46] The Japanese Cabinet (2013). Japan Revitalisation Strategy

[47] Wang J, Yuan H (2011). Factors affecting contractors’ risk attitudes in construction projects: Case study from China. International Journal of Project Management, 29(2): 209–219

[48] Xu G, Dai Z T, Cui X J (2019). Research and implementation of whole-process quality and safety supervision platform for intelligent construction sites. Urban Geotechnical Investigation & Surveying, (1): 37–40 (in Chinese)

[49] Zhang L, Sun X, Xue H (2019). Identifying critical risks in Sponge City PPP projects using DEMATEL method: A case study of China. Journal of Cleaner Production, 226: 949–958

[50] Zhang Y C (2018). Discussion on construction demand and information integration application on smart site. Intelligent Building and Smart City, (5): 86–88 (in Chinese)

[51] Zhou D, Zhang L, Li H (2006). A study of the system’s hierarchical structure through integration of DEMATEL and ISM. In: International Conference on Machine Learning and Cybernetics. Dalian: IEEE, 1449–1453

[52] Zhou H T, Wang H W, Zeng W (2018). Smart construction site in mega construction projects: A case study on island tunneling project of Hong Kong–Zhuhai–Macao Bridge. Frontiers of Engineering Management, 5(1): 78–87

[53] Ziarnik J P, Bernstein G S (1982). A critical examination of the effect of inservice training on staff performance. Mental Retardation, 20(3): 109–114

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