Developing a model for the implementation of designing out waste in construction

Figures & data

Table 1. Barriers and enablers of waste minimisation in construction.

Category	Variable	Reference
Barriers	Design changes	(Ajayi et al., 2016; Doust et al., 2021; Ekanayake & Ofori, 2004; Laovisutthichai et al., 2020; Liu et al., 2015; Llatas & Osmani, 2016; Olanrewaju & Ogunmakinde, 2020; Osmani et al., 2008a; Salgin, Cosgun, Ipekci, & Karadayi, 2020; Wang, Li, & Tam, 2014)
	Change in processes and practices of design	(Ajayi & Oyedele, 2018; Osmani et al., 2008a; Osmani, Price, & Glass, 2005; Xu & Lu, 2019)
	Poor design	(Liu et al., 2015; Llatas & Osmani, 2016; Osmani et al., 2008a; Osmani et al., 2008b)
	Design complexity	(Ajayi & Oyedele, 2018; Ajayi et al., 2017; Laovisutthichai et al., 2020; Liu et al., 2015; Llatas & Osmani, 2016; Osmani, 2013; Osmani et al., 2008a; Osmani et al., 2008b; Osmani et al., 2005; Wang et al., 2014)
	Contract does not specify reducing waste during the design phase	(Akinade et al., 2018; Doust et al., 2021; Llatas & Osmani, 2016; Osmani, 2013; Osmani et al., 2005)
	Lack of interest of the client in reducing waste	(Olanrewaju & Ogunmakinde, 2020; Osmani, 2013; Osmani et al., 2008a; Osmani et al., 2008b; Wang, Yu, Tam, Li, & Xu, 2019)
	Project constraints (e.g. no sufficient time or resources to review the design)	(Olanrewaju & Ogunmakinde, 2020; Osmani, 2013; Osmani et al., 2008a; Osmani et al., 2008b; Salgin et al., 2020)
	Lack of information, documentation, and drawings	(Ajayi & Oyedele, 2018; Akinade et al., 2018; Jaques, 2000; Osmani, 2013; Salgin et al., 2020; Wang et al., 2014); (Olanrewaju & Ogunmakinde, 2020)
	Lack of collaboration among professionals from different disciplines	(Ajayi et al., 2016); Ajayi & Oyedele, 2018; Ipsen, Pizzol, Birkved, & Amor, 2021; Laovisutthichai et al., 2020; Liu et al., 2015; Osmani, 2013; Ajayi et al., 2017; Mohammed et al., 2022)
	Lack of DoW tools such as ICT tools	(Akinade et al., 2018; Li et al., 2015; Llatas & Osmani, 2016; Wang et al., 2014; Wong, Wu, & Chi-Sun, 2021)
	Designers’ negative perception (behaviour and attitude) towards DoW	(Ajayi et al., 2016; Liu et al., 2015; Wang et al., 2014; Wang et al., 2019)
	Lack of experience and skills in implementing DoW	(Ajayi et al., 2016; Osmani et al., 2008a; Salgin et al., 2020; Wang et al., 2014)
	Lack of awareness	(Ajayi et al., 2016; Liu et al., 2015; Llatas & Osmani, 2016; Olanrewaju & Ogunmakinde, 2020; Osmani, 2013)
	Lack of knowledge about standardisation (e.g. material size in the market)	(Ajayi & Oyedele, 2018; Ajayi et al., 2017; Ajayi et al., 2016; Alshboul & Abu Ghazaleh, 2014; Banihashemi, Tabadkani, & Hosseini, 2018; Ekanayake & Ofori, 2004; Jaques, 2000; Liu et al., 2015; Llatas & Osmani, 2016; Olanrewaju & Ogunmakinde, 2020; Osmani, 2013; Osmani et al., 2008a; Osmani et al., 2005; Salgin et al., 2020; Wang et al., 2014, 2015; Xu & Lu, 2019)
	Designers’ limited knowledge of construction processes	(Ajayi et al., 2016; Ipsen et al., 2021; Olanrewaju & Ogunmakinde, 2020)
Enablers	Prefabrication, precast and 3D printing	(Ajayi & Oyedele, 2018; Ajayi et al., 2017; Ajayi et al., 2016; Doust et al., 2021; Jaques, 2000; Laovisutthichai et al., 2020; Llatas & Osmani, 2016; Osmani et al., 2008a; Osmani et al., 2008b; Wang et al., 2014)
	Education or training	(Ajayi et al., 2016; Jaques, 2000; Olanrewaju & Ogunmakinde, 2020; Osmani et al., 2008a; Wang et al., 2014)
	Good communication and coordination	(Ajayi & Oyedele, 2018; Ajayi et al., 2016; Akinade et al., 2018; Jaques, 2000; Liu et al., 2015; Llatas & Osmani, 2016; Osmani, 2013; Osmani et al., 2008a; Salgin et al., 2020)
	Material selection or alternative products	(Ajayi et al., 2016; Ajayi & Oyedele, 2018; Akinade et al., 2018; Doust et al., 2021; Ekanayake & Ofori, 2004; Jaques, 2000; Laovisutthichai et al., 2020; Li et al., 2015; Llatas & Osmani, 2016; Olanrewaju & Ogunmakinde, 2020; Osmani, 2013; Osmani et al., 2005; Salgin et al., 2020; Wang, Li, & Tam, 2015)
	Legislation, regulations, government requirements	(Doust et al., 2021; Laovisutthichai et al., 2020; Li et al., 2015; Olanrewaju & Ogunmakinde, 2020; Osmani, 2013; Osmani et al., 2008a; Osmani et al., 2008b; Osmani et al., 2005; Wang et al., 2014; Wang et al., 2019; Wong et al., 2021)
	Financial incentive or cost-saving	(Ajayi et al., 2016; Ajayi et al., 2017; Ajayi & Oyedele, 2018; Akinade et al., 2018; Jaques, 2000; Laovisutthichai et al., 2020; Olanrewaju & Ogunmakinde, 2020; Osmani, 2013; Wang et al., 2014, 2015; Wong et al., 2021)
	Using Building Information Modelling (BIM)	(Akinade et al., 2018; Liu et al., 2015; Llatas & Osmani, 2016; Mohammed et al., 2022)
	Modular construction	(Ajayi et al., 2017; Ajayi & Oyedele, 2018; Akinade et al., 2018; Banihashemi et al., 2018; Wang et al., 2015; Wang et al., 2019; Wong et al., 2021)

Table 2. Background information of respondents.

Category	Item	Percentage
Occupation	Construction Project Manager	22.37
	Engineering Manager	18.42
	Civil Engineer	15.79
	Sustainability Manager	10.53
	Builder / Contractor	6.58
	Architect	6.58
	Mechanical Engineer	3.95
	Others (electrical engineers, graphic designers, interior designers)	15.79
Qualification	Project or Construction Management	28.26
	Civil Engineering	27.17
	Engineering Management	19.57
	Architecture	7.61
	Mechanical Engineering	7.61
	Others (building design, electrical engineering, interior design)	9.78
Years of Experience	Over 15 years	32.89
	Between 10–14 years	25.00
	Between 5–9 years	21.05
	Between 1–4 years	19.74
	Less than 1 year of experience	1.32
Project type	Infrastructure (Roads, Bridges, Airports, …)	32.63
	Residential Building	16.84
	Mixed Development	25.26
	Energy Facilities (Oil and Gas, Solar Energy, …)	14.74
	Intuitional and Office Buildings	6.32
	Others (e.g. places of worship, transportation, and aged care facilities)	4.21

Table 3. Result of ANOVA of DoW factors.

Construct	Code	Factor	Sum of squares	Mean square	F	Sig.
DoW Practice	Q13_1	My company has a strategy or policy to support DoW practice for all construction projects	8.159	1.166	0.790	0.598
	Q13_2	In my company, we conduct waste meetings to discuss ways to optimise the design and reduce waste	19.397	2.771	1.976	0.071
	Q13_3	My company adopts the following local standards of waste management; ‘Better Practice Guidelines for Waste Management and Recycling in Commercial and Industrial Facilities’	7.209	1.030	0.937	0.484
	Q13_4	My company adopts the following local standards of waste management; ‘Standards for managing construction waste in NSW’	8.561	1.223	1.195	0.318
	Q13_5	My company practices international standers, such as ISO 14001	6.763	0.966	0.776	0.609
	Q13_6	My company practices international standers, such as BS 8895: Designing for material efficiency in building projects	13.179	1.883	1.493	0.185
	Q13_7	My company practices the following guidelines: ‘Design for material optimisation’	4.449	0.636	0.565	0.781
	Q13_8	My company practices the following guidelines: ‘Design for recovery and reuse’	4.551	0.650	0.582	0.768
	Q13_9	My company practices the following guidelines: ‘Design for waste-efficient procurement’	6.303	0.900	0.820	0.574
	Q13_10	My company practices the following guidelines: ‘Design for off-site construction’	8.922	1.275	0.910	0.504
	Q13_11	My company practices the following guidelines: ‘Design for deconstruction and flexibility’	4.856	0.694	0.535	0.805
DoW Barriers	Q10_1	Design changes	5.502	0.786	1.235	0.296
	Q10_2	Poor design	9.805	1.401	2.089	0.056
	Q10_3	Complex design	4.498	0.643	0.697	0.674
	Q10_4	Change in processes and practices of design	5.936	0.848	1.100	0.373
	Q10_5	Contract does not specify reducing waste during the design phase	2.027	0.290	0.274	0.962
	Q10_6	Lack of interest of the client in reducing waste	7.031	1.004	1.073	0.390
	Q10_7	Project constraints (e.g. no time to change design)	6.069	0.867	1.121	0.361
	Q10_8	Designers’ negative perception towards DoW	3.016	0.431	0.628	0.731
	Q10_9	Lack of ICT tools	7.446	1.064	0.962	0.466
	Q10_10	Lack of experience and skills in implementing DoW	4.407	0.630	0.824	0.571
	Q10_11	Lack of awareness of DoW	6.374	0.911	0.905	0.508
	Q10_12	Lack of knowledge about standardisation (e.g. material size in the market)	2.881	0.412	0.569	0.779
	Q10_13	Lack of information, documentation, and drawings from the design stage	3.907	0.558	0.657	0.707
	Q10_14	Designers’ limited knowledge about construction processes	3.618	0.517	0.496	0.834
	Q10_15	Lack of collaboration among professionals from different disciplines	7.296	1.042	1.263	0.282
DoW Enablers	Q11_1	Utilisation of prefabrication, precast and 3D printing	2.926	0.418	0.779	0.607
	Q11_2	Utilisation of modular construction	2.178	0.311	0.454	0.864
	Q11_3	Education and training in DoW	4.646	0.664	1.038	0.413
	Q11_4	Good communication and coordination	8.362	1.195	1.736	0.115
	Q11_5	Appropriate material selection or alternative products	0.882	0.126	0.293	0.954
	Q11_6	Government legislation and regulations	2.571	0.367	0.710	0.663
	Q11_7	Financial incentives (i.e. cost-saving)	3.444	0.492	0.948	0.476
	Q11_8	Using Building Information Modelling (BIM)	6.646	0.949	1.756	0.111

Table 4. Result of the rotated component matrix of DoW barriers.

Variable^a	Component^b
	1	2	3	4	5
Lack of experiences and skills in implementing DoW	0.783
Lack of ICT tools	0.762
Lack of awareness of DoW	0.752
Lack of knowledge about standardisation (e.g. material size in the market)	0.570	0.548
Designers’ negative perception towards DoW	0.566
Lack of information, documentations, and drawings from the design stage		0.820
Designers’ limited knowledge about construction processes		0.773
Lack of collaboration among professionals from different disciplines		0.762
Change in processes and practices of design			0.835
Design changes			0.723
Complex design			0.642
Poor design				0.761
Project constraints (e.g. no time to review the design)				0.709
Lack of interest of the client in reducing waste					0.798
Contract does not specify reducing waste during the design phase					0.723

^a Extraction Method: Principal Component Analysis.

^b Rotation Method: Varimax with Kaiser Normalisation.

Figure 1. Full model of DoW in construction (algorithm result).

Table 5. Construct reliability, convergent validity, and discriminant validity.

Construct	Reliability and convergent validity				Discriminant validity (HTMT)
	Cronbach's alpha	Composite reliability (rho_a)	Composite reliability (rho_c)	Average variance extracted (AVE)	Client-related Barriers	Design-related Barriers	DoW	Enablers	Knowledge-related Barriers	Lack of Experience and Skills
Client-related Barriers
Design-related Barriers	0.651	0.685	0.803	0.578	0.210
DoW	0.911	0.922	0.928	0.620	0.233	0.554
Enablers	0.645	0.723	0.794	0.566	0.201	0.506	0.569
Knowledge-related Barriers	0.826	0.898	0.862	0.616	0.220	0.349	0.233	0.487
Lack of Experience and Skills	0.785	0.838	0.856	0.599	0.454	0.282	0.329	0.352	0.693
Project-related Barriers	0.549	0.582	0.812	0.685	0.301	0.498	0.133	0.464	0.492	0.589

Table 6. Predictive power result (PLSpredict).

Item	Q²predict	PLS-SEM_RMSE	LM_RMSE
Q13_11	0.170	1.019	1.159
Q13_3	0.020	1.045	1.243
Q13_4	0.068	0.992	1.139
Q13_5	0.084	1.062	1.083
Q13_6	0.115	1.085	1.219
Q13_7	0.070	1.009	1.071
Q13_8	0.115	0.985	1.130
Q13_9	0.048	1.023	1.066

Q² predict (DoW) = 0.149.

RMSE (DoW) = 0.953.

MAE (DoW) = 0.721.

Figure 2. Path coefficients results (bootstrapping results).

Table 7. Path coefficients, F-square, and collinearity (VIF) results.

Relationships	Original sample	Sample mean	Standard deviation	T statistics	p-values	f-square	VIF
Client-related Barriers -> DoW	0.171	0.155	0.163	1.049	0.294	0.039	1.367
Design-related Barriers -> DoW	0.338	0.307	0.149	2.264	0.024	0.151	1.368
Enablers -> DoW	0.411	0.376	0.125	3.283	0.001	0.210	1.448
Knowledge-related Barriers -> DoW	−0.132	−0.082	0.186	0.709	0.478	0.019	1.680
Lack of Experience and Skills -> DoW	0.300	0.301	0.148	2.026	0.043	0.075	2.171
Project-related Barriers -> DoW	−0.199	−0.118	0.148	1.344	0.179	0.049	1.464
Enablers x Project-related Barriers -> DoW	0.027	0.091	0.176	0.156	0.876	0.001	1.938
Enablers x Design-related Barriers -> DoW	−0.036	−0.087	0.149	0.241	0.810	0.001	1.825
Enablers x Client-related Barriers -> DoW	0.185	0.169	0.174	1.063	0.288	0.029	3.034
Enablers x Knowledge-related Barriers -> DoW	−0.085	−0.054	0.19	0.448	0.654	0.005	2.150
Enablers x Lack of Experience and Skills -> DoW	0.037	−0.028	0.136	0.274	0.784	0.002	2.600

Figure 3. IPMA results of exogenous constructs.

Table 8. IPMA results of indicators’ total effects and performance.

Item code	Item name	Performance	Importance
Q11_4	Good communication and coordination	77.632	0.179
Q10_5	Contract does not specify reducing waste during the design phase	75	0.171
Q10_10	Lack of experience and skills in implementing DoW	72.697	0.08
Q10_4	Change in processes and practices of design	72.697	0.173
Q10_7	Project constraints (e.g. no time to change design)	71.711	−0.137
Q10_15	Lack of collaboration among professionals from different disciplines	71.382	0.002
Q10_2	Poor design	71.382	−0.101
Q10_12	Lack of knowledge about standardisation (e.g. material size in the market)	71.053	−0.029
Q10_1	Design changes	70.724	0.085
Q10_11	Lack of awareness of DoW	70.724	0.063
Q10_3	Complex design	68.092	0.176
Q10_14	Designers’ limited knowledge about construction processes	67.105	−0.052
Q10_13	Lack of information, documentation and drawings from the design stage	65.789	−0.074
Q10_8	Designers’ negative perception towards DoW	65.789	0.102
Q11_1	Utilisation of prefabrication, precast and 3D printing	61.842	0.091
Q11_8	Using Building Information Modelling (BIM)	61.842	0.254
Q10_9	Lack of ICT tools	60.855	0.138

Ajayi, S. O., Oyedele, L. O., Kadiri, K. O., Akinade, O. O., Bilal, M., Owolabi, H. A., & Alaka, H. A. (2016). Competency-based measures for designing out construction waste: task and contextual attributes. Engineering, Construction, and Architectural Management, 23(4), 464–490. doi:10.1108/ECAM-06-2015-0095

 Web of Science ®Google Scholar

Doust, K., Battista, G., & Rundle, P. (2021). Front-end construction waste minimization strategies. Australian Journal of Civil Engineering, 19(1), 1–11. doi:10.1080/14488353.2020.1786989

 Web of Science ®Google Scholar

Ekanayake, L. L., & Ofori, G. (2004). Building waste assessment score: design-based tool. Building and Environment, 39(7), 851–861. doi:10.1016/j.buildenv.2004.01.007

 Web of Science ®Google Scholar

Laovisutthichai, V., Lu, W., & Bao, Z. (2020). Design for construction waste minimization: guidelines and practice. Architectural Engineering and Design Management, 18(3), 279–298. doi:10.1080/17452007.2020.1862043.

 Web of Science ®Google Scholar

Liu, Z., Osmani, M., Demian, P., & Baldwin, A. (2015). A BIM-aided construction waste minimisation framework. Automation in Construction, 59, 1–23. doi:10.1016/j.autcon.2015.07.020

 Web of Science ®Google Scholar

Llatas, C., & Osmani, M. (2016). Development and validation of a building design waste reduction model. Waste Management (Elmsford), 56, 318–336. doi:10.1016/j.wasman.2016.05.026

 PubMed Web of Science ®Google Scholar

Olanrewaju, S. D., & Ogunmakinde, O. E. (2020). Waste minimisation strategies at the design phase: Architects’ response. Waste Management, 118, 323–330. doi:10.1016/j.wasman.2020.08.045

 PubMed Web of Science ®Google Scholar

Osmani, M., Glass, J., & Price, A. D. (2008a). An investigation of design waste causes in construction. WIT Transactions on Ecology and the Environment, 109, 491–498. doi:10.2495/WM080501

 Google Scholar

Salgin, B., Cosgun, N., Ipekci, C. A., & Karadayi, T. T. (2020). Turkish Architects’ View on Construction and Demolition Waste Reduction in the Design Stage. Environmental Engineering and Management Journal, 19(3), 439–452. doi:10.30638/eemj.2020.042

 Web of Science ®Google Scholar

Wang, J., Li, Z., & Tam, V. W. Y. (2014). Critical factors in effective construction waste minimization at the design stage: A Shenzhen case study, China. Resources, Conservation and Recycling, 82, 1–7. doi:10.1016/j.resconrec.2013.11.003

 Web of Science ®Google Scholar

Ajayi, S., & Oyedele, L. (2018). Critical design factors for minimising waste in construction projects: A structural equation modelling approach. Resources, Conservation and Recycling, 137, 302–313. doi:10.1016/j.resconrec.2018.06.005

 Web of Science ®Google Scholar

Osmani, M., Price, A. D. F., & Glass, J. (2005). Potential For construction waste minimisation through design. WIT Transactions on Ecology and the Environment, 84), doi:10.2495/SPD050561

 Google Scholar

Xu, J., & Lu, W. (2019). Design for construction waste management. In Konstantinos Papadikis, Chee S. Chin, Isaac Galobardes, Guobin Gong, & Fangyu Guo (Eds.), Sustainable buildings and structures: Building a sustainable tomorrow (pp. 271–276). Suzhou, China: CRC Press.

 Google Scholar

Osmani, M., Glass, J., & Price, A. D. F. (2008b). Architects’ perspectives on construction waste reduction by design. Waste Management (Elmsford), 28, 1147–1158. doi:10.1016/j.wasman.2007.05.011

 PubMed Web of Science ®Google Scholar

Ajayi, S., Oyedele, L., Akinade, O., Bilal, M., Alaka, H., Owolabi, H., & Kadiri, K. (2017). Attributes of design for construction waste minimization: A case study of waste-to-energy project. Renewable and Sustainable Energy Reviews, 73, 1333–1341. doi:10.1016/j.rser.2017.01.084

 Web of Science ®Google Scholar

Osmani, M. (2013). Design waste mapping: a project life cycle approach. Proceedings of the Institution of Civil Engineers - Waste and Resource Management, 166(3), 114–127. doi:10.1680/warm.13.00013

 Google Scholar

Akinade, O. O., Oyedele, L. O., Ajayi, S. O., Bilal, M., Alaka, H. A., Owolabi, H. A., & Arawomo, O. O. (2018). Designing out construction waste using BIM technology: Stakeholders’ expectations for industry deployment. Journal of Cleaner Production, 180, 375–385. doi:10.1016/j.jclepro.2018.01.022

 Web of Science ®Google Scholar

Wang, J., Yu, B., Tam, V. W. Y., Li, J., & Xu, X. (2019). Critical factors affecting willingness of design units towards construction waste minimization: An empirical study in Shenzhen, China. Journal of Cleaner Production, 221, 526–535. doi:10.1016/j.jclepro.2019.02.253

 Web of Science ®Google Scholar

Jaques, R. (2000). Construction site waste generation-the influence of design and procurement. Architectural Science Review, 43(3), 141–145. doi:10.1080/00038628.2000.9696897

 Google Scholar

Ipsen, K. L., Pizzol, M., Birkved, M., & Amor, B. (2021). How lack of knowledge and tools hinders the eco-design of buildings—A systematic review. Urban Science, 5(1), 20. doi:10.3390/urbansci5010020

 Google Scholar

Mohammed, M., Shafiq, N., Al-Mekhlafi, A.-B. A., Al-Fakih, A., Zawawi, N. A., Mohamed, A. M., … Al-Nini, A. (2022). Beneficial effects of 3D BIM for Pre-empting waste during the planning and design stage of building and waste reduction strategies. Sustainability, 14(6), 3410. doi:10.3390/su14063410

 Web of Science ®Google Scholar

Li, J., Tam, V. W. Y., Zuo, J., & Zhu, J. (2015). Designers’ attitude and behaviour towards construction waste minimization by design: A study in Shenzhen, China. Resources, Conservation and Recycling, 105, 29–35. doi:10.1016/j.resconrec.2015.10.009

 Web of Science ®Google Scholar

Wong, I., Wu, Z., & Chi-Sun, P. (2021). Strategies for effective waste reduction and management of building construction projects in highly urbanized cities—A case study of Hong Kong. Buildings, 11(5), 214. doi:10.3390/buildings11050214

 Web of Science ®Google Scholar

Alshboul, A. A., & Abu Ghazaleh, S. (2014). Consequences of design decisions on material waste during construction survey of architects': Point of view, the case of Jordan. Jordan Journal of Civil Engineering, 159(3269), 1–12.

 Google Scholar

Banihashemi, S., Tabadkani, A., & Hosseini, M. R. (2018). Integration of parametric design into modular coordination: A construction waste reduction workflow. Automation in Construction, 88, 1–12. doi:10.1016/j.autcon.2017.12.026

 Web of Science ®Google Scholar

Wang, J., Li, Z., & Tam, V. W. Y. (2015). Identifying best design strategies for construction waste minimization. Journal of Cleaner Production, 92, 237–247. doi:10.1016/j.jclepro.2014.12.076

 Web of Science ®Google Scholar