Barriers to sustainable procurement in the Nigerian construction industry: an exploratory factor analysis

Figures & data

Table 1. Definition of potential barriers factors for sustainable procurement.

Variable no	Variable Name
HSP01	Lack of awareness of sustainability concepts
HSP02	Reluctance of the contractor side to adopt sustainability practices in procurement
HSP03	Lack of motivation for the implementation staff
HSP04	Lack of capacity in required human resources
HSP05	Perceived high cost of adopting sustainable solutions
HSP06	Failure to match project needs to procurement options
HSP07	Failure of Government to establish National Council for Public Procurement
HSP08	Lack of commitment to National Development Plan
HSP09	Inadequate time for the pre-contract phase
HSP10	Lack of regulatory framework for sustainable construction procurement
HSP11	Lack of enforcement and implementation of relevant laws
HSP12	Lack of monitoring and control on projects
HSP13	Corruption
HSP14	Political interference
HSP15	Non availability of sustainable materials
HSP16	Failure to adhere to quality management processes
HSP17	Reluctance in embracing new knowledge
HSP18	Lack of confidence in local contractors
HSP19	Delays in payment of contractors

Sources: (Belfitt et al., 2011; Meehan and Bryde, 2011; Mensah and Ameyaw, 2012: 874; McMurray et al. 2013; Olanrewaju, et al. 2014; Ruparathna and Hewage, 2015; Ogunsanya, et al. 2016; Renukappa et al. 2016; Faremi, et al. 2017; United Nations, 2017).

Table 2. Respondents’ demographic characteristics.

Demographic characteristics	Percentage	n
Gender
Male	79.7	255
Female	20.3	65
Age
21–25	2.5	8
26–30	9.4	30
31–35	12.9	41
36–40	13.5	43
41–45	22.3	71
46–50	18.2	58
51–55	13.2	42
56–60	7.5	24
61–65	0.3	1
Highest qualification
National Diploma	1.9	6
Higher National Diploma	21.5	68
Bachelor’s degree	51.4	163
Master’s degree	24.3	77
Doctorate	0.9	3
Professional qualification
Architect	17.7	56
Builder	12.6	40
Civil engineer	30.6	97
Electrical engineer	6.3	20
Mechanical engineer	5.0	16
Structural engineer	3.2	10
Procurement officer	5.0	16
Quantity surveyor	18.0	57
Project manager	1.6	5
Years of Experience in the Construction Industry
1–5	16.5	52
6–10	21.2	67
11–15	19.0	60
16–20	19.6	62
20–25	13.0	41
26–30	7.3	23
Above 30	3.5	11
Sector of the Construction Industry
Government agency	53.6	171
Contractor	18.2	58
Consultant	14.4	46
Other: private	13.8	44

Table 3. KMO and Bartlett’s test.

Kaiser-Meyer-Olkin Measure of Sampling Adequacy.		0.893
Bartlett's Test of Sphericity	Approx. Chi-Square	2757.429
	Df	171
	Sig.	0.000

a. Cronbach’s alpha = 0.913.

Table 4. Communalities.

Communalities
	Initial	Extraction
HSP01 Lack of awareness of sustainability concepts	1.000	0.713
HSP02 Reluctance of the contractor side to adopt sustainability practices in procurement	1.000	0.712
HSP03 Lack of motivation for the implementation staff	1.000	0.680
HSP04 Lack of capacity in required human resources	1.000	0.684
HSP05 Perceived high cost of adopting sustainable solutions	1.000	0.564
HSP06 Failure to match project needs to procurement options	1.000	0.702
HSP07 Failure of government to establish National Council for Public Procurement	1.000	0.655
HSP08 Lack of commitment to the National Development Plan	1.000	0.609
HSP09 Inadequate time for the pre-contract phase	1.000	0.403
HSP10 Lack of regulatory framework for sustainable construction procurement	1.000	0.638
HSP11 Lack of enforcement and implementation of relevant laws	1.000	0.677
HSP12 Lack of monitoring and control of projects	1.000	0.685
HSP13 Corruption	1.000	0.768
HSP14 Political interference	1.000	0.572
HSP15 Non-availability of sustainable materials	1.000	0.606
HSP16 Failure to adhere to quality management processes	1.000	0.613
HSP17 Reluctance in embracing new knowledge	1.000	0.667
HSP18 Lack of confidence in local contractors	1.000	0.682
HSP19 Delays in payment of contractors	1.000	0.544

Extraction Method: Principal Component Analysis.

Table 5. Rotated component matrix.

	Component
	1	2	3	4
HSP01 Lack of awareness of sustainability concepts	0.802
HSP03 Lack of motivation for the implementation staff	0.770
HSP04 Lack of capacity in required human resources	0.768
HSP02 Reluctance of the contractor side to adopt sustainability practices in procurement	0.761
HSP09 Inadequate time for the pre-contract phase	0.501
HSP13 Corruption		0.833
HSP14 Political interference		0.704
HSP11 Lack of enforcement relevant laws		0.645
HSP12 Lack of monitoring and control of projects		0.641
HSP10 Lack of regulatory framework for sustainable construction procurement		0.559
HSP06 Failure to match project needs to procurement options			0.807
HSP07 Failure of government to establish National Council for Public Procurement			0.766
HSP05 Perceived high cost of adopting sustainable solutions			0.693
HSP08 Lack of commitment to the National Development Plan			0.621
HSP18 Lack of confidence in local contractors				0.790
HSP17 Reluctance in embracing new knowledge				0.753
HSP16 Failure to adhere to quality management processes				0.622
HSP15 Non-availability of sustainable materials				0.621
HSP19 Delays in payment of contractors				0.594

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

Rotation converged in 7 iterations.

Table 6. Total variance explained.

Component	Initial eigenvalues			Extraction sums of squared loadings			Rotation sums of squared loadings
	Total	% of Variance	Cumulative %	Total	% of Variance	Cumulative %	Total	% of Variance	Cumulative %
1	7.575	39.868	39.868	7.575	39.868	39.868	3.654	19.232	19.232
2	1.804	9.496	49.363	1.804	9.496	49.363	2.941	15.481	34.713
3	1.612	8.484	57.847	1.612	8.484	57.847	2.872	15.116	49.829
4	1.184	6.229	64.076	1.184	6.229	64.076	2.707	14.247	64.076
5	0.905	4.765	68.841
6	0.821	4.319	73.160
7	0.740	3.893	77.054
8	0.612	3.221	80.274
9	0.527	2.776	83.050
10	0.460	2.419	85.470
11	0.423	2.227	87.696
12	0.380	2.000	89.697
13	0.348	1.829	91.526
14	0.327	1.722	93.248
15	0.309	1.628	94.876
16	0.281	1.477	96.353
17	0.261	1.373	97.726
18	0.234	1.231	98.956
19	0.198	1.044	100.000

Extraction Method: Principal Component Analysis.

Figure 1. Scree plot for factor analysis.

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