Adopting construction 4.0 to promote sustainability in the Mekong Delta of Vietnam: a fuzzy delphi study

References

• El Jazzar M. Integrating construction 4.0 technologies: a four-layer implementation plan. Front Built Environ. 2021;7. doi: 10.3389/fbuil.2021.671408
   Google Scholar
• Statsenko L, Samaraweera, A, Bakhshi, J, et al. Construction 4.0 technologies and applications: a systematic literature review of trends and potential areas for development. Constr Innov. 2023:23(5). doi: 10.1108/CI-07-2021-0135
   Google Scholar
• Hoang T-H, Nguyen NPP, Hoang N-YN, et al. Application of social media in supply chain 4.0 practices: a bibliometric analysis and research trends. Oper Manag Res. 2023;16(3):1–23. doi: 10.1007/s12063-023-00378-9
   Web of Science ®Google Scholar
• Bui LTC, Carvalho M, Pham HT, et al. Supply chain quality management 4.0: conceptual and maturity frameworks. IJQRM. 2022. doi:10.1108/IJQRM-07-2021-0251.
   Google Scholar
• Balasubramanian S, Shukla V, Islam N, et al. Construction industry 4.0 and sustainability: an enabling framework. IEEE Transactions on Engineering Management, 2021. doi: 10.1109/TEM.2021.3110427
   Google Scholar
• Pham HT, Pham T, Truong Quang H, et al. Supply chain risk management research in construction: a systematic review. Int J Constr Manag. 2023;23(11):1945–1955. doi: 10.1080/15623599.2022.2029677
   Google Scholar
• Fei W, Opoku A, Agyekum K, et al. The critical role of the construction industry in achieving the sustainable development goals (sdgs): delivering projects for the common good. Sustainability (Switzerland). 2021;13(16):9112. doi: 10.3390/su13169112
   Web of Science ®Google Scholar
• Ngo VM, Quang HT, Hoang TG, et al. Sustainability‐related supply chain risks and supply chain performances: the moderating effects of dynamic supply chain management practices. Bus Strat Env. 2024;33(2):839–857. doi: 10.1002/bse.3512
   Web of Science ®Google Scholar
• Duong TBA, Pham Tho, Truong Quang Huy, et al. Risk in sustainable construction supply chains: construct development and measurement validation. Constr Manage Eco. 2023;41(8):634–650.
   Web of Science ®Google Scholar
• Muerza V, Guerlain C. Sustainable construction logistics in urban areas: a framework for assessing the suitability of the implementation of construction consolidation centres. Sustainability (Switzerland). 2021;13(13):7349. doi: 10.3390/su13137349
   Web of Science ®Google Scholar
• Pham HT, Truong Quang H, Sampaio P, et al. The impact of global risks on supply chain performance. An empirical study on construction sector in the COVID-19 pandemic. Int J Qual Reliab Manage. 2023;40(4):1009–1035. doi: 10.1108/IJQRM-03-2022-0084
   Web of Science ®Google Scholar
• Pocock J, Steckler C, Hanzalova B. Improving socially sustainable design and construction in developing countries. Procedia Eng. 2016;145:288–295. doi: 10.1016/j.proeng.2016.04.076
   Google Scholar
• Ayarkwa J, Joe Opoku D-G, Antwi-Afari P, et al. Sustainable building processes’ challenges and strategies: the relative important index approach. Cleaner Eng Technol. 2022;7:7. doi: 10.1016/j.clet.2022.100455
   Google Scholar
• Boretti A. Implications on food production of the changing water cycle in the Vietnamese Mekong Delta. Glob Ecol Conserv. 2020;22:e00989. doi: 10.1016/j.gecco.2020.e00989
   Web of Science ®Google Scholar
• World Bank. For Mekong Delta Farmers, Diversification Is The Key To Climate Resilience. 2021 [cited 2023, Apr, 30]. Available from: https://www.worldbank.org/en/news/feature/2021/10/21/for-mekong-delta-farmers-diversification-is-the-key-to-climate-resilience.
   Google Scholar
• Tran TV, Tran DX, Myint SW, et al. Examining spatiotemporal salinity dynamics in the Mekong River Delta using Landsat time series imagery and a spatial regression approach. Sci Total Environ. 2019;687:1087–1097. doi: 10.1016/j.scitotenv.2019.06.056
   PubMed Web of Science ®Google Scholar
• Ishikawa A, Amagasa M, Shiga T, et al. The max-min delphi method and fuzzy delphi method via fuzzy integration. Fuzzy Sets Syst. 1993;55(3):241–253. doi: 10.1016/0165-0114(93)90251-C
   Web of Science ®Google Scholar
• Badea A, Prostean G, Goncalves G, et al. Assessing risk factors in collaborative supply chain with the analytic hierarchy process (AHP). procedia-social and behavioral sciences. Procedia Soc Behav Sci. 2014;124:114–123. doi: 10.1016/j.sbspro.2014.02.467
   Google Scholar
• Dogan O, Deveci M, Canitez F, et al. Acorridor selection for locating autonomous vehicles using an interval-valued intuitionistic fuzzy AHP and TOPSIS method. Soft Comput. 2020;24:8937–8953.
   Web of Science ®Google Scholar
• Jeng DJ-F. Generating a causal model of supply chain collaboration using the fuzzy DEMATEL technique. Comput Ind Eng. 2015;87:283–295. doi: 10.1016/j.cie.2015.05.007
   Web of Science ®Google Scholar
• Joshi K, Kant R. Decision making in effective supply chain collaboration: a fuzzy AHP approach. IJDSRM. 2012;4(3–4):197–216. doi: 10.1504/IJDSRM.2012.053371
   Google Scholar
• Mathiyazhagan K, Govindan K, NoorulHaq A, et al. An ISM approach for the barrier analysis in implementing green supply chain management. J Clean Prod. 2013;47:283–297. doi: 10.1016/j.jclepro.2012.10.042
   Web of Science ®Google Scholar
• Seleem SN, Attia E-A, Karam A, et al. A lean manufacturing road map using fuzzy-DEMATEL with case-based analysis. Int J Lean Six Sigma. 2020;11(5):903–928. doi: 10.1108/IJLSS-12-2017-0147
   Web of Science ®Google Scholar
• Shukla RK, Garg D, Agarwal A. An integrated approach of Fuzzy AHP and Fuzzy TOPSIS in modeling supply chain coordination. Prod Manuf Res. 2014;2(1):415–437. doi: 10.1080/21693277.2014.919886
   Google Scholar
• Wang M, Wang CC, Sepasgozar S, et al. A systematic review of digital technology adoption in off-site construction: Current status and future direction towards industry 4.0. Buildings. 2020;10(11):204. doi: 10.3390/buildings10110204
   Web of Science ®Google Scholar
• Olatunde NA, Gento AM, Okorie VN, et al. Construction 4.0 technologies in a developing economy: awareness, adoption readiness and challenges. Frontiers In Engineering And Built Environment. 2022;3(2):108–121. doi: 10.1108/FEBE-08-2022-0037
   Google Scholar
• Demirkesen S, Tezel A. Investigating major challenges for industry 4.0 adoption among construction companies. ECAM. 2022;29(3):1470–1503. doi: 10.1108/ECAM-12-2020-1059
   Google Scholar
• Franco JAB, Domingues AM, de Almeida Africano N, et al. Sustainability in the civil construction sector supported by industry 4.0 technologies: challenges and opportunities. Infrastructures. 2022;7(3):43. doi: 10.3390/infrastructures7030043
   Google Scholar
• Chen Y, Huang D, Liu Z, et al. Construction 4.0, industry 4.0, and building information modeling (BIM) for sustainable building development within the smart city. Sustainability (Switzerland). 2022;14(16):10028. doi: 10.3390/su141610028
   Web of Science ®Google Scholar
• Forcael E, Ferrari I, Opazo-Vega A, et al. Construction 4.0: a literature review. Sustainability (Switzerland). 2020;12(22):1–28. doi: 10.3390/su12229755
   PubMed Web of Science ®Google Scholar
• Pham HT, Pham T, Truong Quang H. Impact of transformational leadership on green learning and green innovation in construction supply chains. ECAM. 2023;30(5):1883–1901. doi: 10.1108/ECAM-05-2021-0379
   Google Scholar
• Duong ATB, Vo VX, Do Sameiro Carvalho M, et al. Risks and supply chain performance: globalization and COVID-19 perspectives. Int J Product Perform Manage. 2023;72(7):1962–1986. doi: 10.1108/IJPPM-03-2021-0179
   Web of Science ®Google Scholar
• Ngo-Thanh T. BIM applications for transportation infrastructure in Tra Vinh province. Ca Mau Department of Transportation; 2021.
   Google Scholar
• Ngo-Thanh T, Do Minh T, Huynh Xuan T, et al. Overview of BIM application for bridge-highway and infrastructure projects in Viet Nam. Vn. 2020;71(7):760–774. doi: 10.25073/tcsj.71.7.3
   Google Scholar
• Huynh TX. Digitalization of bridge, road and technical infrastructure projects using BIM technology for management and operation in Ca Mau province. Ca Mau Department of Transportation; 2022.
   Google Scholar
• Le TT. The effect of green supply chain management practices on sustainability performance in Vietnamese construction materials manufacturing enterprises. Uncertain Supply Chain Management. 2020;8(1):43–54. doi: 10.5267/j.uscm.2019.8.007
   Google Scholar
• Pham T, Pham H. Improving green performance of construction projects through supply chain integration: the role of environmental knowledge. Sustainable Prod Consumption. 2021;26:933–942. doi: 10.1016/j.spc.2021.01.004
   Web of Science ®Google Scholar
• Wang CN, Nguyen NAT, Dang TT. Solving order planning problem using a heuristic approach: the case in a building material distributor. Appl Sci (Switzerland). 2020;10(24):1–21. doi: 10.3390/app10248959
   Google Scholar
• Mok KY, Shen GQ, Yang J. Stakeholder management studies in mega construction projects: a review and future directions. Int J Project Manage. 2015;33(2):446–457. doi: 10.1016/j.ijproman.2014.08.007
   Web of Science ®Google Scholar
• Xue J, Shen GQ, Yang RJ, et al. Mapping the knowledge domain of stakeholder perspective studies in construction projects: a bibliometric approach. Int J Project Manage. 2020;38(6):313–326. doi: 10.1016/j.ijproman.2020.07.007
   Web of Science ®Google Scholar
• Duong ATB. Supply chain risk assessment in disruptive times: opportunities and challenges. J Enterp Inf Manage. 2023;36(5):1372–1401. doi: 10.1108/JEIM-02-2023-0104
   Web of Science ®Google Scholar
• Kramer MP, Bitsch L, Hanf JH. The impact of instrumental stakeholder management on blockchain technology adoption behavior in agri-food supply chains. J Risk Financial Manage. 2021;14(12):598. doi: 10.3390/jrfm14120598
   Web of Science ®Google Scholar
• Lebcir R, Hill T, Atun R, et al. Stakeholders’ views on the organisational factors affecting application of artificial intelligence in healthcare: ascoping review protocol. BMJ Open. 2021;11. doi: 10.1136/bmjopen-2020-044074
   PubMed Web of Science ®Google Scholar
• Doe JK, Van de Wetering R, Honyenuga B, et al. Extended contextual validation of stakeholder approach to firm technology adoption: moderating and mediating relationships in an innovation eco-system. SBR. 2022;17(4):506–540. doi: 10.1108/SBR-10-2020-0128
   Google Scholar
• Kujala J, Sachs S, Leinonen H, et al. Stakeholder engagement: Past, present, and future. Bus Soc. 2022;61(5):1136–1196. doi: 10.1177/00076503211066595
   Web of Science ®Google Scholar
• Pedrini M, Ferri LM. Stakeholder management: a systematic literature review. corporate governance. CG. 2019;19(1):44–59. doi: 10.1108/CG-08-2017-0172
   Google Scholar
• Li Y, Sun H, Li D, et al. Effects of Digital technology adoption on sustainability performance in construction projects: the mediating role of stakeholder collaboration. J Manage Eng. 2022;38(3):04022016. doi: 10.1061/(ASCE)ME.1943-5479.0001040
   Web of Science ®Google Scholar
• Duong ATB, Pham T, Truong Quang H, et al. Ripple effect of disruptions on performance in supply chains: an empirical study. Eng Construction Archit Manag. 2023;31(13):1–22. doi: 10.1108/ECAM-10-2022-0924
   Web of Science ®Google Scholar
• Cooper V, The critical success factor method: a review and practical example, in International Conference on Information Resources Management (CONF-IRM) 2008 Proceedings; Ontario, Canada. 2008. p. 53.
   Google Scholar
• Goyal S, Ahuja M, Guan J. Information systems research themes: a seventeen-year data-driven temporal analysis. Commun Assoc Inf Syst. 2018;43(1):23. doi: 10.17705/1CAIS.04323
   Google Scholar
• Rad FF, Oghazi P, Palmié M, et al. Industry 4.0 and supply chain performance: a systematic literature review of the benefits, challenges, and critical success factors of 11 core technologies. Ind Marketing Manage. 2022;105:268–293. doi: 10.1016/j.indmarman.2022.06.009
   Web of Science ®Google Scholar
• Howell MT. Critical success factors simplified: implementing the powerful drivers of dramatic business improvement. New York: Taylor & Francis; 2009.
   Google Scholar
• Wang K, Guo F. Towards sustainable development through the perspective of construction 4.0: systematic literature review and bibliometric analysis. Buildings. 2022;12(10):1708. doi: 10.3390/buildings12101708
   Web of Science ®Google Scholar
• Liu Z, Lu Y, Nath T, et al. Critical success factors for BIM adoption during construction phase: a Singapore case study. ECAM. 2022;29(9):3267–3287. doi: 10.1108/ECAM-12-2020-1072
   Google Scholar
• Oyedele A, Owolabi HA, Oyedele LO, et al. Big data innovation and diffusion in projects teams: towards a conflict prevention culture. Dev Built Environ. 2020;3:100016. doi: 10.1016/j.dibe.2020.100016
   Google Scholar
• Kumar V, Pandey A, Singh R. Can artificial intelligence be a critical success factor of construction projects?: project practitioners’ perspectives. Technol Innovation Manage Rev. 2022;11(11–12):17–32. doi: 10.22215/timreview/1471
   Web of Science ®Google Scholar
• Shafei H, Radzi AR, Algahtany M, et al. Construction 4.0 technologies and decision-making: a systematic review and Gap Analysis. Buildings. 2022;12(12):2206. doi: 10.3390/buildings12122206
   Web of Science ®Google Scholar
• Goel A, Ganesh LS, Kaur A. Sustainability integration in the management of construction projects: a morphological analysis of over two decades’ research literature. J Clean Prod. 2019;236:236. doi: 10.1016/j.jclepro.2019.117676
   Web of Science ®Google Scholar
• Famakin IO, Aigbavboa C, Molusiwa R, Comparative analysis of critical success factors for smart and sustainable developments between organizations and among construction professionals, in The Twelfth International Conference on Construction in the 21st Century (CITC-12); Amman, Jordan. 2022.
   Google Scholar
• Ozorhon B, Karahan U. Critical success factors of building information modeling implementation. J Manage Eng. 2017;33(3):04016054. doi: 10.1061/(ASCE)ME.1943-5479.0000505
   Web of Science ®Google Scholar
• Chinda T. Examination of factors influencing the successful implementation of reverse logistics in the construction industry: pilot study. Procedia Eng. 2017;182:99–105. doi: 10.1016/j.proeng.2017.03.128
   Google Scholar
• Srimathi S, Dinesh S, Sethuraman R. A review on critical success factors in construction project. International Journal Of Scientific Research In Science, Engineering And Technology. 2017;3(2):478–481.
   Google Scholar
• Williams T. Identifying success factors in construction projects: a case study. Project Management Journal. 2016;47(1):97–112. doi: 10.1002/pmj.21558
   Web of Science ®Google Scholar
• Zakaria IB, Hashim SZ, Ahzahar N. Critical success factor for sustainable facilities management: a review of literature. IJARBSS. 2018;8(7):469–480. doi: 10.6007/IJARBSS/v8-i7/4388
   Google Scholar
• Quang HT, Sampaio P, Carvalho MS, et al. An extensive structural model of supply chain quality management and firm performance. Int J Qual Reliab Manage. 2016;33(4):444–464. doi: 10.1108/IJQRM-11-2014-0188
   Web of Science ®Google Scholar
• Fernandes AC, Sampaio P, Sameiro M, et al. Supply chain management and quality management integration: a conceptual model proposal. Int J Qual Reliab Manage. 2017;34(1):53–67. doi: 10.1108/IJQRM-03-2015-0041
   Web of Science ®Google Scholar
• Duong BAT, Truong HQ, Sameiro M, et al. Supply chain management and organizational performance: the resonant influence. Int J Qual Reliab Manage. 2019;36(7):1053–1077. doi: 10.1108/IJQRM-11-2017-0245
   Web of Science ®Google Scholar
• Murray TJ, Pipino LL, Van Gigch JP. A pilot study of fuzzy set modification of delphi. HSM. 1985;5(1):76–80. doi: 10.3233/HSM-1985-5111
   Google Scholar
• Okoli C, Pawlowski SD. The delphi method as a research tool: an example, design considerations and applications. Inf Manage. 2004;42(1):15–29. doi: 10.1016/j.im.2003.11.002
   Web of Science ®Google Scholar
• Bouzon M, Govindan K, Rodriguez CMT, et al. Identification and analysis of reverse logistics barriers using fuzzy delphi method and AHP. ResouConserv Recycl. 2016;108:182–197. doi: 10.1016/j.resconrec.2015.05.021
   Web of Science ®Google Scholar
• Moktadir M. Examining barriers to reverse logistics practices in the leather footwear Industry; No. 0123456789. Boston, MA, USA: Springer US; 2019.
   Google Scholar
• Ma Z, Shao C, Ma S, et al. Constructing road safety performance indicators using fuzzy delphi method and grey delphi method. expert systems with applications. Expert Syst Appl. 2011;38(3):1509–1514. doi: 10.1016/j.eswa.2010.07.062
   Web of Science ®Google Scholar
• Hsu Y-L, Lee C-H, Kreng VB. The application of fuzzy delphi method and fuzzy AHP in lubricant regenerative technology selection. Expert Syst Appl. 2010;37(1):419–425. doi: 10.1016/j.eswa.2009.05.068
   Web of Science ®Google Scholar
• Deveci M, Özcan E, John R, et al. A study on offshore wind farm siting criteria using a novel interval-valued fuzzy-rough based Delphi method. J Environ Manage. 2020;270:110916. doi: 10.1016/j.jenvman.2020.110916
   PubMed Web of Science ®Google Scholar
• Saaty TL. How to make a decision: the analytic hierarchy process. Eur J Oper Res. 1990;48(1):9–26. doi: 10.1016/0377-2217(90)90057-I
   Web of Science ®Google Scholar
• Saaty TL. What is the analytic hierarchy process? Berlin, Heidelberg: Springer; 1988.
   Google Scholar
• Akkermans H, Bogerd P, Van Doremalen J. Travail, transparency and trust: a case study of computer-supported collaborative supply chain planning in high-tech electronics. Eur J Oper Res. 2004;153(2):445–456. doi: 10.1016/S0377-2217(03)00164-4
   Web of Science ®Google Scholar
• Le P-L, Nguyen D-T. Exploring lean practices’ importance in sustainable supply chain management trends: an empirical study in Canadian construction industry. Eng Manage J. 2023;1–26. doi: 10.1080/10429247.2023.2187608
   Google Scholar
• Bisht TS, Kumar D, Alappat BJ. Revised leachate pollution index (r-LPI): a tool to quantify the contamination potential of landfill leachate. Process SafEnviron Prot. 2022;168:1142–1154. doi: 10.1016/j.psep.2022.10.052
   Web of Science ®Google Scholar
• Kumar A, Zavadskas EK, Mangla SK, et al. When risks need attention: adoption of green supply chain initiatives in the pharmaceutical industry. Int J P Res. 2019;57(11):3554–3576. doi: 10.1080/00207543.2018.1543969
   Web of Science ®Google Scholar
• Spires EE. Using the analytic hierarchy process to analyze multiattribute decisions. Multivariate Behav Res. 1991;26(2):345–361. doi: 10.1207/s15327906mbr2602_8
   PubMed Web of Science ®Google Scholar
• Wang J. BIM-Enabled design collaboration for complex Building, in cooperative design, visualization, and engineering. Cham: Springer; 2014. pp. 238–244.
   Google Scholar
• Akkermans HA, Bogerd P, Yücesan E, et al. The impact of ERP on supply chain management: exploratory findings from a European delphi study. Eur J Oper Res. 2003;146(2):284–301. doi: 10.1016/S0377-2217(02)00550-7
   Web of Science ®Google Scholar
• Simmons DR, McCall C, Clegorne NA. Leadership competencies for construction professionals as identified by construction industry executives. J Constr Eng Manage. 2020;146(9). doi: 10.1061/(ASCE)CO.1943-7862.0001903
   PubMed Web of Science ®Google Scholar
• Shadid WK. A framework for managing organizations in complex environments. Constr Manage Eco. 2018;36(4):182–202. doi: 10.1080/01446193.2017.1343483
   Web of Science ®Google Scholar
• von der Gracht HA. Consensus measurement in delphi studies: review and implications for future quality assurance. Technol Forecasting Social Change. 2012;79(8):1525–1536. doi: 10.1016/j.techfore.2012.04.013
   Web of Science ®Google Scholar
• Hatefi SM, Tamošaitienė J. Construction projects assessment based on the sustainable development criteria by an integrated fuzzy AHP and improved GRA model. Sustainability. 2018;10(4):991. doi: 10.3390/su10040991
   Web of Science ®Google Scholar
• Wind Y, Saaty TL. Marketing applications of the analytic hierarchy process. Manage Sci. 1980;26(7):641–658. doi: 10.1287/mnsc.26.7.641
   Web of Science ®Google Scholar
• Zhang S, Liu J, Li C, et al. Evaluation of water resources utilization efficiency based on DEA and AHP under climate change. Water. 2023;15(4):718. doi: 10.3390/w15040718
   Web of Science ®Google Scholar
• Singh A, Kumari S, Malekpoor H, et al. Big data cloud computing framework for low carbon supplier selection in the beef supply chain. J Clean Prod. 2018;202:139–149. doi: 10.1016/j.jclepro.2018.07.236
   Web of Science ®Google Scholar
• Geng S, Hou H, Yang J. A hybrid decision support model for deploying humanitarian operations to respond to earthquakes. Eng Manage J. 2022;34(4):705–717. doi: 10.1080/10429247.2022.2027206
   Google Scholar
• Donegan HA, Dodd FJ. A note on saaty’s random indexes. MathComput Modell. 1991;15(10):135–137. doi: 10.1016/0895-7177(91)90098-R
   Google Scholar
• Abioye SO, Oyedele LO, Akanbi L, et al. Artificial intelligence in the construction industry: a review of present status, opportunities and future challenges. J Buil Eng. 2021;44:44. doi: 10.1016/j.jobe.2021.103299
   Web of Science ®Google Scholar
• Nguyen DT, Le PL. Twenty-year application of logistics and supply chain management in the construction industry. Constr Manage Eco. 2022;40(10):796–834. doi: 10.1080/01446193.2022.2110273
   Web of Science ®Google Scholar
• Lee JC, Chen CY. The moderator of innovation culture and the mediator of realized absorptive capacity in enhancing organizations’ absorptive capacity for SPI success. J Global Inform Manag. 2019;27(4):70–90. doi: 10.4018/JGIM.2019100104
   Web of Science ®Google Scholar
• Lee JC, Shiue YC, Chen CY. An integrated model of the knowledge antecedents for exploring software process improvement success. J Enterp Inf Manage. 2020;33(6):1537–1556. doi: 10.1108/JEIM-03-2019-0084
   Web of Science ®Google Scholar
• Miemczyk J, Luzzini D. Achieving triple bottom line sustainability in supply chains: the role of environmental, social and risk assessment practices. Int J Oper Prod Manage. 2019;39(2):238–259. doi: 10.1108/IJOPM-06-2017-0334
   Web of Science ®Google Scholar
• Yuan M, Li Z, Li X, et al. Proposing a multifaceted model for adopting prefabricated construction technology in the construction industry. ECAM. 2023;30(2):755–786. doi: 10.1108/ECAM-07-2021-0613
   Google Scholar
• Cai J. Understanding adoption of high off-site construction level technologies in construction based on the TAM and TTF. Eng Constr Archit Manag. 2022;30:10. doi: 10.1108/ECAM-05-2022-0439
   Web of Science ®Google Scholar
• Amuda-Yusuf G. Critical success factors for building information modelling implementation. CEB. 2018;18(3):55–73. doi: 10.5130/AJCEB.v18i3.6000
   PubMedGoogle Scholar
• Arya B, Lin Z. Understanding collaboration outcomes from an extended resource-based view perspective: the roles of organizational characteristics, partner attributes, and network structures†. J Manage. 2007;33(5):697–723. doi: 10.1177/0149206307305561
   Web of Science ®Google Scholar
• Prajogo D, Mena C, Chowdhury M. The role of strategic collaborations and relational capital in enhancing product performance – a moderated-mediated model. Int J Oper Prod Manage. 2021;41(3):206–226. doi: 10.1108/IJOPM-05-2020-0256
   Web of Science ®Google Scholar
• Lekan A, Clinton A, Fayomi OSI, et al. Lean thinking and industrial 4.0 approach to achieving construction 4.0 for industrialization and technological development. Buildings. 2020;10(12):221. doi: 10.3390/buildings10120221
   Web of Science ®Google Scholar
• Osunsanmi TO, Aigbavboa CO, Emmanuel Oke A, et al. Appraisal of stakeholders’ willingness to adopt construction 4.0 technologies for construction projects. BEPAM. 2020;10(4):547–565. doi: 10.1108/BEPAM-12-2018-0159
   Google Scholar
• Prebanić KR, Vukomanović M. Realizing the need for digital transformation of stakeholder management: a systematic review in the construction industry. Sustainability. 2021;13(22):12690. doi: 10.3390/su132212690
   Web of Science ®Google Scholar
• Shojaei RS, Burgess G. Non-technical inhibitors: exploring the adoption of digital innovation in the UK construction industry. Technol Forecasting Social Change. 2022;185:122036. doi: 10.1016/j.techfore.2022.122036
   Web of Science ®Google Scholar