Assessing the innovative skills and competencies required of construction management graduates
Article Category: Research Paper
Published Online: Sep 14, 2023
Page range: 90 - 106
Received: Aug 01, 2022
Accepted: Apr 16, 2023
DOI: https://doi.org/10.2478/otmcj-2023-0002
Keywords
© 2023 James Olaonipekun Toyin et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
In this study context, ‘construction management graduates’ are also called ‘building graduates’. Construction management (CMt) is the discipline that entails managing a construction project or projects as effectively as possible (Arditi and Alavipour 2019). Construction Manager (CM) duties entail and are not limited to making the best use of available finances; efficient project scheduling; controlling the scope of work; avoiding delays, revisions and conflicts; improving project design and construction quality; and contracting and procurement flexibility (Arditi et al. 2009). The revolution in the construction industry has resulted in a tremendous amount of skill being demanded of the construction management graduate (CMG). Moreover, the need for construction managers arose centuries ago – in fact, such a need has probably been prevailing ever since the time when humans first created shelters to protect themselves from threats such as weather and animals. Since then, construction process management has been of such a vital importance that it cannot be neglected, regardless of how rudimentary or modest the structures requiring to be constructed might be. We have arrived in the 21st century (4th industrial revolution [IR]) because of this progress.
Besides, Yogeshwaran et al. (2018) and Yap et al. (2021) noted the need to evaluate the expected skills and competencies of quantity surveyors (QS). Similar research (Wang and Cheng 2022) was reported in China, and Abdullah et al. (2017) researched in Australia, focusing on construction managers. However, all indication shows that the current IR entails incorporating information technology (Toyin and Mewomo 2023) in the management of construction activities. Thus, this has left the construction industry with no option but to adopt such innovative technology that is capable of managing information throughout the lifecycle of the construction process. Building information modelling (BIM) technology has been seen, tested and proven as an innovative technology that can function perfectly well in the construction industry (Dossick et al. 2014; Kolarić et al. 2018; Toyin and Mewomo 2021). Notwithstanding, several researchers highlighted the ‘need for BIM skills’ (Hodorog et al. 2019) in the built environment. For example, Mohd and Latiffi (2013), Wang et al. (2020), Hodorog et al. (2019) and Toyin and Mewomo (2023) stated that using a BIM workforce aids in cost savings and enhanced time management through clash detection.
Innovation in construction is defined as changes that lead to an improved input–output relationship for products and processes, as well as changes within the technical, management or legal organisation of a project that can be monetised (Brockmann et al. 2016). Thus, the construction industry is still faced with the challenges of getting innovatively skilled professionals with the required competencies to manage the construction lifecycle process. These have remained difficult to find. The construction managers (CM) are under tremendous pressure as most struggle to align themselves with the evolving innovative technology in the construction industry (Demirdoven and Arditi 2014a). Based on their good degree of familiarity with this emerging technology, a few fresh CMG could secure employment offers in reputable construction companies; in contrast, some old construction managers are being retrenched (Torres-Machí et al. 2013; Abdullah et al. 2017) since they cannot meet the evolving innovative technology trends in the construction industry. Such innovative trends in construction include but are not limited to BIM, robotics, digital twin technology, artificial intelligence (AI), augment reality (AR), the use of drone, etc. (Brockmann et al. 2016; Hodorog et al. 2019; Toyin and Mewomo 2022; Wang and Cheng 2022).
Therefore, construction industry employers now seek to employ CMG who are academically sound as well as possess necessary construction-related innovative skills and competencies in related technological software or tools, such as ‘BIM’, Microsoft Project (MSP), etc., that can be used to manage the project throughout its lifecycle. Although very few studies focus on this area, none have tried to conduct such related research in Nigeria. Therefore, this study investigates the expected core skills and competence required of CMG in the Nigerian construction industry. The specific objectives are to: (a) ‘identify and appraise the critical competencies needed to keep pace within the revolving industry’; and (b) ‘examine the core innovative skills expected of CMG’.
CM is both a demanding and challenging profession. The responsibilities of a construction manager include the following, as documented in the literature (Baharudin 2006; Arditi et al. 2009; Yaman et al. 2015; Maina 2018):
Supervise and direct construction projects from start to finish Review the project in-depth to schedule deliverables and estimate costs Coordinate and direct construction workers and subcontractors Select tools, materials and equipment and track inventory Prepare internal and external reports about job status Negotiate terms of agreements, draft contracts and obtain permits and licences Ensure quality construction standards and the use of proper construction techniques
As a result of these responsibilities, being relentless and prudent in achieving goals is a key attribute of a construction manager; as such, they need to be informed of everything that happens during the project. Thus, determining the precise truth is also necessary for them to work successfully (Pellisé Tintoré 2014).
Competency is defined by GWA (2022) as the combination of behavioural qualities, skills, abilities and knowledge required to generate adequate results on the job. Buvik and Rolfsen (2015) see competence as ‘the abilities, skills, and capabilities that a person has in a particular domain’. Yap et al. (2021) agreed with Wao and Flood (2016), who refer to competency as the major criterion utilised to improve the performance of professionals in their different occupational sectors.
Based on the preceding definition, competence may be understood as the capacity to use a specific characteristic of knowledge, skills, talent or personal qualities to accomplish/deliver critical activities or tasks effectively. Turner (2017), Arditi et al. (2013) and Mühlbacher et al. (2013) see leadership characteristics, technical knowledge, behaviours and competence in strategic and corporate management as part of the critical skill sets for good project managers. Torres-Machí et al. (2013) conducted a study focussing on CMG in Spain; their opinion was sought to understand why the unemployment rate among young graduate of CMt professionals is very high. The main reasons given were lack of adequate communication (due to the mixed nature of professionals in their industry), inadequate university program design (lack of BIM knowledge), lack of eagerness to work, a refusal to relocate, inadequate master’s degree to meet market demands, an economic crisis and too many universities offering similar graduate degrees.
The study by Wang and Cheng (2022) in China identified 40 general competencies expected of CMG. The author’s findings reflected that the current academic curriculum of tertiary institutions in China could not cater for the construction industry’s expectations. Moreover, it tends to be too theoretical and lacks practicality. The industry expected the graduates to be able to ‘write a comprehensive technical report, to analyse the technical issues and to provide ongoing feedback to the teams’. Vaz-Serra and Mitcheltree (2021) conducted research in Australia; the aim was to understand the competencies expected of project management graduates as required by the industry. Their study reveals that more significance is laid on interpersonal skills, competencies within core technical knowledge, sustainability and life cycle analysis, and knowledge of environmental waste management systems. The study of Mitcheltree et al. (2019) concluded that good communication; commitment to personal development; emotional intelligence; resilience and persistence; and commitment to professional development are the top five traits the construction industry looks out for when recruiting graduates. Table 1 shows the competencies gathered from various published articles on construction managers. The variables documented in this table was used to elicit respondent opinion towards the study objective on expected competency.
Critical competencies expected of CMG
CMC, construction management competencies; CMG, construction management graduates.
The CMG must possess special skills that allow them to face complex constructability difficulties, as well as the ability to visualise a finished product in an empty three-dimensional (3D) space (Martin-Gutierrez et al. 2012; Ahmed et al. 2014; McCuen 2015; Kim and Irizarry 2021). Ahmed et al. (2014) submit that the CMG that possess these skills are likely to meet up with the innovative evolving needs of the industry when they join the workforce. However, Williamson and Andrew (2018) point out ‘spatial skill’ as one of the terms used to describe core skills construction practitioners use to make informed decisions. These assist them in transforming abstract images into the finished creation. Dennis and Tapsfield (2013) state that spatial ability is ‘the ability to generate, retain, retrieve, and transform well-structured visual images’.
As discussed in the introduction section, construction managers require basic skills in innovative technology. BIM is one of these revolutionised technologies evolving in the construction industry. Nevertheless, individual BIM core skills are the personal characteristics, technical talents and professional expertise required to perform a BIM activity or deliver a BIM-related output. These capabilities, achievements or actions should be quantifiable in performance standards and might be obtained or improved through education, development and training (Succar et al. 2013; Plawgo and Ertman 2021). According to Hodorog et al. (2019), traditional analytic approaches cannot capture the dynamic process of BIM. The expanding required number of new roles, such as BIM manager, BIM director and BIM technician, demonstrates the growing demand for BIM experts (Yalcinkaya 2013). Construction managers are more likely to pick up the role of BIM managers. BIM managers act as intermediaries between other construction professionals, working with architects, designers, engineers and clients to gather specifications and overseeing the creation of detailed structural plans (Construction 2021). Looking at the role of a construction manager on a project, it is immediately perceptible that they are expected to deal with the management of the entire resources on a construction project, and they act as an intermediary among all construction teams. Thus, they are close to being the BIM manager. They only need to obtain little knowledge in the coordination of BIM. However, according to Rahman et al. (2016), construction managers and BIM managers require distinct skill sets. Various scholars also emphasise the importance of skills such as collaboration and effective communication in the curricula. According to Dossick et al. (2014), a BIM syllabus should include an understanding of computer application principles and BIM procedures. Individual qualities such as aptitude, credentials, skills/abilities, knowledge and attitude are examined by Barison and Santos (2011). They note the professional necessity for the role in both fundamental and functional aspects. Rahman and Ayer (2017) assessed the capabilities of BIM in an organisation; the authors highlighted the following skills as required from construction managers: information and communication technology (ICT) skills, teamwork, a basic understanding of the BIM process, and analytical and problem-solving skills.
In addition, feedback and critical thinking are also essential skills set for a CMG. Nevertheless, an intelligent construction manager may have sufficient industry experience, but it does not mean they no longer need feedback. Experienced field workers see problems that even the smartest construction managers may overlook (Turner 2017). Thus, a construction manager should be open to feedback from clients, supervisors and professional peers (Benhart and Shaurette 2013; Mitcheltree et al. 2019). Furthermore, because the work comprises significant obligations, being a construction manager necessitates a wide range of skills and characteristics. As construction projects get larger and more sophisticated, it is up to the employer to hunt for qualified candidates who are willing to be trained to acquire these skills. Table 2 shows the identified core innovative skills gathered from published articles on construction managers. The variables documented in this table were used to elicit respondents’ opinion towards the study objective on innovative core skill.
Core innovative skill
BIM, building information modelling; CMES, construction management expected skills; ICT, information and communication technology; VDC, virtual design and construction.
This study uses two distinct ways to source data. Firstly, secondary data were sourced from previously published literature. An extant review of the literature was conducted. The hypothesis that, in any study context, conducting a literature review would be an ideal means for obtaining a suitable contextual backdrop against which the present study’s findings might be evaluated, has been scientifically proven. Such a practice sheds more light on what has been done and is yet to be done and research trends for decades. Therefore, this study systematically reviews published articles sourced from the Scopus and Web of Science (WoS) databases. These databases were selected because they are two of the most credible and largest scientific databases; they ensure a high degree of quality control and encompass a broader range of research disciplines (Ullah et al. 2019; Toyin and Mewomo 2021). Lastly, the extant review yielded 27 competencies and 13 core skills. These can be seen in Tables 1 and 2. Thus, the identified variables are based mainly on competencies and skills that have received significant consideration in similar studies previously documented by scholars. Employing well-known variables for a research study is preferable since this allows respondents to react quickly. A questionnaire survey was constructed grounded on the identified 27 and 13 variables found during the extant literature review, and the snowball sample techniques method was used to locate respondents. As a result, the study presented in this article is quantitative. The questionnaire survey consists of two major processes to examine the questionnaire’s relevance and reliability. Firstly, the questionnaire was reviewed by five construction-related personnel. This comprises of two real estate human resource managers, two contractors with over 10 years of practising experience and one registered graduate member of the Nigerian Institute of Building (NIOB), confirming that unclear expressions were not contained in the survey. Suitable technical terms were used, and the questionnaire covered the expected competencies and skills required of CMG. Secondly, before the questionnaire was widely distributed, a pilot study with 20 respondents was done to examine its comprehensibility and design. The expected BIM competencies and skills were measured on a 5-point Likert scale from 1 (‘not significant’) to 5 (‘strongly significant’).
One reliable method to validate quantitative questionnaire reliability is the use of Cronbach’s α technics (Vaz-Serra and Mitcheltree 2021; Toyin and Mewomo 2022). These technics are used to determine the average relationship or internal regularity amongst factors/variables in a questionnaire. The Cronbach’s α result will determine if the instrument used in collecting data is reliable and if the collected data can be suitable for further descriptive and inferential analysis. A Cronbach’s α of 0.7 or above is deemed suitable for conducting inferential statistical analysis (Yap et al. 2021). The 20 pilot test respondents were excluded from the primary data before continuing with further analysis. Thus, 330 valid responses were employed for the analyses. Principal component analysis (PCA) and Relative Important Index (RII) were used to analyse the findings of the survey data. Subsequently, the conclusions were comprehensively discussed, and conclusive closing remarks were drawn. Firstly, the survey results were tested using the Cronbach’s α reliability analysis test. This was used to validate the respondents’ opinion on the 5-point Likert scale used in terms of its applicability and suitability for this study context, a process adopted in the study of Isa et al. (2020). Table 3 sets out the minimum criteria guide used in this study for the conduction of PCA. These have also been adopted in multiple studies in the literature (Joseph et al. 2010; Nilashi et al. 2015; Kapsoulis et al. 2018; Isa et al. 2020).
Criteria guide for EFA
| S. No. | Criteria | Parameter |
|---|---|---|
| 1. | Factor loading value | ≥0.35 |
| 2. | Eigen factor value | >1 |
| 3. | KMO test | ≥0.5 |
| 4. | Correlation matrix of variables | ≥0.05 |
| 5. | Test of sphericity anti-image | <0.05 |
| 6. | Percentage of variance | ≥50% |
| 7. | Variable communality value ≥0.05 | Variable communality value ≥0.05 |
| 8. | Parallel analysis test | Real eigenvalue factor > random order eigenvalue factor |
KMO, Kaiser–Meyer–Olkin.
Typically, when an opinion is required to be sought from a larger number of respondents, employing a web-based snowballing data generation approach would be a better option. This is because having a small number of valid responses may result in reliability issues involving the value of the relationship between variables. The valid response rate for this study was
Guide for factor loading selection based on response rate
| S. No. | Value of factor loading | Response rate |
|---|---|---|
| 1. | 0.75 | 50–59 |
| 2. | 0.70 | 60–69 |
| 3. | 0.65 | 70–99 |
| 4. | 0.55 | 100–119 |
| 5. | 0.50 | 120–149 |
| 6. | 0.45 | 150–199 |
| 7. | 0.40 | 200–249 |
| 8. | 0.35 | 250–349 |
| 9. | 0.30 | 350 and above |
The results, shown in Figures 1 and 2, present respondents’ data according to their gender, wherein 70% were male and 30% female, categories of respondents and years of experience.
Fig. 1:
Categories of respondents.
Fig. 2.
Years of experience.
Table 5 shows Cronbach’s test. The -value ranges from 0 to 1. According to Vaz-Serra and Mitcheltree (2021), the greater the -value, the more reliable the output result or scaling becomes. The measuring scale is reasonable if the -value ranges from 0.7 to 1. A Cronbach’s α of ≥0.7 means that the measuring scale has comparatively great internal reliability. Using SPSS 27.0 (IBM), Table 5 shows that the 27 variables have an α-value of 0.881, and the 13 variables 0.813. These indicated that the measurement is reliable at a 5% significance level based on the 5-point Likert scale. These imply that the Cronbach α coefficient of all the 27 and 13 variables (competencies and skills) at 0.881 and 0.813 is above 0.7, as suggested by Pallant (2005). The author stated that all the variables had high internal consistency and reliability.
Cronbach’s α test
| Reliability statistics | |||
|---|---|---|---|
| Cronbach’s α | Cronbach’s α based on standard-ised items | ||
| Expected competency | 0.881 | 0.880 | 27 |
| Expected skills | 0.813 | 0.813 | 13 |
Tables 7 and 8 list the results of the 27 and 13 variables for competencies and skills, respectively, in descending order based on their mean item score (MIS) and RII, which enables a presentation of the descriptive statistics of the questionnaire data. The expression in Table 6 was used to rate the significance level. Thus, all 27 and 13 variables (100%) are deemed statistically highly significant at 0.81 ≤ RII ≤ 1, wherein lies the range from 0.85 to 0.95 as perceived by the respondents. Therefore, all the variables are highly significant.
Significance level
| RII values | Significance level | |
|---|---|---|
| 0.81 ≤ RII ≤ 1.00 | High | H |
| 0.61 ≤ RII ≤ 0.80 | High-medium | H-M |
| 0.41 ≤ RII ≤ 0.60 | Medium | M |
| 0.21 ≤ RII ≤ 0.40 | Medium-low | M-L |
| 0.00 ≤ RII ≤ 0.20 | Low | L |
Construction manager competencies variable analysis
| Descriptive statistics (variables = 27; |
||||
|---|---|---|---|---|
| Coding | Mean | Std. deviation | RII | Ranking |
| CMC27 | 4.73 | 0.466 | 0.95 | 1st |
| CMC5 | 4.71 | 0.528 | 0.94 | 2nd |
| CMC23 | 4.68 | 0.615 | 0.93 | 3rd |
| CMC18 | 4.62 | 0.599 | 0.92 | 4th |
| CMC21 | 4.59 | 0.657 | 0.91 | 5th |
| CMC1 | 4.55 | 0.657 | 0.91 | 6th |
| CMC26 | 4.52 | 0.685 | 0.90 | 7th |
| CMC14 | 4.50 | 0.694 | 0.90 | 8th |
| CMC20 | 4.50 | 0.672 | 0.90 | 9th |
| CMC17 | 4.49 | 0.681 | 0.90 | 10th |
| CMC13 | 4.42 | 0.702 | 0.88 | 11th |
| CMC24 | 4.42 | 0.694 | 0.88 | 12th |
| CMC15 | 4.40 | 0.722 | 0.88 | 13th |
| CMC25 | 4.40 | 0.659 | 0.88 | 14th |
| CMC12 | 4.39 | 0.720 | 0.87 | 15th |
| CMC11 | 4.39 | 0.676 | 0.87 | 16th |
| CMC6 | 4.38 | 0.701 | 0.87 | 17th |
| CMC22 | 4.38 | 0.648 | 0.87 | 18th |
| CMC19 | 4.37 | 0.716 | 0.87 | 19th |
| CMC4 | 4.35 | 0.707 | 0.87 | 20th |
| CMC16 | 4.35 | 0.691 | 0.87 | 21st |
| CMC2 | 4.34 | 0.739 | 0.86 | 22nd |
| CMC10 | 4.33 | 0.762 | 0.86 | 23rd |
| CMC8 | 4.30 | 0.793 | 0.86 | 24th |
| CMC3 | 4.30 | 0.722 | 0.86 | 25th |
| CMC7 | 4.27 | 0.789 | 0.85 | 26th |
| CMC9 | 4.26 | 0.836 | 0.85 | 27th |
CMC, construction management competencies; RII, relative importance index.
Construction manager competencies expected skills variable analysis
| Descriptive statistics (variables = 13; |
||||
|---|---|---|---|---|
| Coding | Mean | Std. deviation | RII | Ranking |
| CMES5 | 4.68 | 0.567 | 0.93 | 1st |
| CMES1 | 4.51 | 0.681 | 0.90 | 2nd |
| CMES13 | 4.41 | 0.693 | 0.88 | 3rd |
| CMES12 | 4.38 | 0.727 | 0.87 | 4th |
| CMES6 | 4.37 | 0.686 | 0.87 | 5th |
| CMES11 | 4.37 | 0.650 | 0.87 | 6th |
| CMES10 | 4.33 | 0.746 | 0.86 | 7th |
| CMES2 | 4.33 | 0.733 | 0.86 | 8th |
| CMES4 | 4.33 | 0.694 | 0.86 | 9th |
| CMES3 | 4.30 | 0.789 | 0.86 | 10th |
| CMES8 | 4.28 | 0.721 | 0.85 | 11th |
| CMES7 | 4.26 | 0.776 | 0.85 | 12th |
| CMES9 | 4.25 | 0.824 | 0.85 | 13th |
RII, relative importance index.
Tables 7 and 8 show the MIS and RII ranking results for the variables identified under the expected competencies and skills of construction manager graduates. These were obtained from the survey data and analysed using SPSS 27.0. The input of clients, students and contractor/consultant perspectives summarises these data. The use of MIS and RII enabled the calculation of the ranking for selecting the significantly essential competencies and skills. All the variables have a high significance level ranging from MIS from 4.25 to 4.73 and RII from 0.85 to 0.95. However, due to the high ranking of the MIS, which is far above the minimum recommendation of 3.50, previous scholars have considered ranking the criticality or importance of a variable in a data set. This study, therefore, proposed an RII rating of 0.90 to select the most critically important competencies and skills. Thus, this proposal may be considered for subsequent findings related to such a high rating. Based on it, 10 competencies and 2 skills have been assessed as meeting this threshold.
Thus, the competencies would be the following: CMC 27 – Good communication; CMC 5 – Honesty and integrity; CMC 23 – Understanding and application of ICT knowledge; CMC 18 – Labour and resource management; CMC 21 – Ability to prepare schedules of work and project progress reports; CMC 1 – Team leadership and management; CMC 26 – Computer skills; CMC 14 – Basic understanding of construction drawing interpretation; CMC 20 – Knowledge and understanding of project specifications; and CMC 17 – Maintenance and quality management competency. The two skills that are perceived as most critical are: CMES 5 – Teamwork skills and CMES 1 – Critical thinking and openness to feedback. These competencies and skills are critically important for CMG and managers to embrace, considering the high significant mean weight. These will keep them relevant and productive in the construction industry.
PCA and principal axis factoring (PAF) are the two common reductions and rotated grouping factor analyses used by scholars, which can be conducted with SPSS. In PCA, it is assumed that the total variance in the data equals the shared variance between the items. In PAF, the assumption is that the total variance in the data equals two things: common variance and unique variance. However, unique variance does not exist in PCA, making it slightly different. Moreover, this study met the assumption of conducting PCA. Furthermore, correlation matrix, unrotated factor solution and eigenvalue greater than 0.35 were selected based on the criteria in Table 4, as recommended in the studies of Bujang and Baharum (2017) and Isa et al. (2020). Therefore, the PCA approach is deemed sufficient to conduct the inferential analysis. Malhotra and Birks (2006) reported that in FA, Bartlett’s test of sphericity and the Kaiser–Meyer–Olkin (KMO) test are commonly used in measuring sample adequacy. ‘When Bartlett’s test of sphericity significant is (
Data reliability test
| KMO and Bartlett’s test | |||
|---|---|---|---|
| Competencies variables 27 | Skills variables 13 | ||
| KMO measure of sampling adequacy | 0.892 | 0.893 | |
| Bartlett’s test of sphericity | Approx. chi-square | 2006.213 | 775.901 |
| Df | 351 | 78 | |
| Sig. | 0.000 | 0.000 | |
KMO, Kaiser–Meyer–Olkin.
The PCA conducted encompasses three phases, namely: (a) to generate a correlation matrix across all variables involved to discover elements in clusters that have the most in common with one another; (b) to extract factors to establish the numbers of created factors and the qualities represented by each factor, and (c) to rotate the factors for them, in such a way that they become clearer, by clustering them into a component group (Isa et al. 2020; Babaie et al. 2022; Duras 2022). Therefore, highly correlated variables were grouped within the same component since they seem to measure the same perception. In contrast, variables in different components correlate less with each other as they measure perceptions differently. Furthermore, PCA was used to reduce the variables and group them into more manageable clusters. Factor rotation and extraction were executed using SPSS 27.0 software. Figure 3 shows the total variance calculated for the 27 variables.
Fig. 3:
Competencies variable extraction.
Figure 3 shows the extracted seven components with eigenvalues greater than 1. Only items with a factor loading of ≥0.35 were included in each component (factor). This seven-component factor clustering solution explained the 27 variables of expected competencies in the Nigerian construction industry, which accounted for 51.57% of the overall variance. Isa et al. (2020) suggested that an acceptable percentage of commutative variance allowable should not be less than 50% since this is deemed required for practical importance. Therefore, it may be concluded that the model’s reliability is acceptable. Figure 4 shows that the seven-component factor described the overall variance, with the first component clustering amounting to 24.788% of the variance involving four variables. The second component comprises five variables, which contribute to 5.96%. The third component includes four variables contributing 4.60%; and the fourth component contains five variables contributing 4.38%. The fifth component has four variables contributing to 4.26%; and the sixth and seventh components contain two and one items contributing 3.87% and 3.72%, respectively. Also, Figure 4 displays the 27 remaining variables’ results in the seven factors, together with their connected factor loadings, eigenvalues and explained variances of the seven factors.
This section discusses and interprets the factors extracted in Table 10. It is required to check the appropriate FA rotation method to use before proceeding. The available two types in SPSS are Oblique rotation (Direct Oblimin or Promax) and Orthogonal rotation (Varimax or Quartmax or Equamax). It is best to start with direct oblimin to conduct a rotated solution. For conducting a rotated solution, starting with direct oblimin would be an ideal approach. After the result of this study revealed that orthogonal rotation is appropriate, the researchers adopted orthogonal rotation using the varimax method. The same method has been adopted in management-related studies (Aluko and Mewomo 2021). However, to interpret factor loading, the variables factor loading matrix is rotated to bring the smallest loadings to nearly zero and its largest loading towards unity (Enshassi et al. 2018). Isa et al. (2020) claimed that an apparent component structure is usually revealed when a variable’s factor loading is significantly based on the number of valid responses received for the study, as seen in Table 3. However, the factor value with a loading of 0.35 and above was retained and used to suitably name the component cluster. Furthermore, Table 11 shows the interpretation of the required data generated from Table 10.
Component clustering (competencies)
| Rotated component matrix | |||||||
|---|---|---|---|---|---|---|---|
| Component | |||||||
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | |
| CMC7 | 0.659 | ||||||
| CMC19 | 0.641 | ||||||
| CMC16 | 0.596 | ||||||
| CMC22 | 0.469 | ||||||
| CMC2 | 0.708 | ||||||
| CMC3 | 0.6200 | ||||||
| CMC20 | 0.496 | ||||||
| CMC4 | 0.495 | ||||||
| CMC8 | 0.405 | ||||||
| CMC18 | 0.657 | ||||||
| CMC21 | 0.566 | ||||||
| CMC17 | 0.534 | ||||||
| CMC24 | 0.424 | ||||||
| CMC5 | 0.733 | ||||||
| CMC14 | 0.564 | ||||||
| CMC13 | 0.423 | ||||||
| CMC12 | 0.423 | ||||||
| CMC6 | 0.358 | ||||||
| CMC9 | 0.640 | ||||||
| CMC11 | 0.593 | ||||||
| CMC10 | 0.468 | ||||||
| CMC1 | 0.459 | ||||||
| CMC15 | |||||||
| CMC26 | 0.751 | ||||||
| CMC23 | 0.550 | ||||||
| CMC25 | |||||||
| CMC27 | 0.820 | ||||||
CMC, construction management competencies.
Rotated component factor loading interpretation of the 25 retained variables
| Component | Component naming | Competencies | Code | Factor loading |
|---|---|---|---|---|
| 1 | Project management and planning-related component | Analysing design solutions | CMC7 | 0.659 |
| Ability for managing project variations, cash flow forecasting and monitoring | CMC19 | 0.641 | ||
| Competency in the reviewing and selection of qualified subcontractors | CMC16 | 0.596 | ||
| Basic understanding of construction code and regulation | CMC22 | 0.469 | ||
| 2 | Pre-contract planning and hazard management | Knowledge of the biding and tendering process | CMC2 | 0.708 |
| Risk management | CMC3 | 0.620 | ||
| Knowledge and understanding of project specifications | CMC20 | 0.496 | ||
| Pre-contract planning and programming | CMC4 | 0.495 | ||
| Basic knowledge of procurement | CMC8 | 0.405 | ||
| 3. | On-site construction management component | Tool and machine maintenance and quality management competency | CMC17 | 0.534 |
| Labour and resource management | CMC18 | 0.657 | ||
| Ability to prepare the schedule of work and project progress and technical report | CMC21 | 0.566 | ||
| Knowledge of sustainability in construction | CMC24 | 0.424 | ||
| 4 | Basic construction management component | Honesty and integrity | CMC5 | 0.733 |
| Site survey and analysis of construction site | CMC6 | 0.358 | ||
| Ability to set up an expediting log and procurement, submittal of log | CMC12 | 0.423 | ||
| Basic knowledge of health and safety in construction practice | CMC13 | 0.423 | ||
| Basic understanding of construction drawing interpretation | CMC14 | 0.564 | ||
| 5 | Peace-making and management-related component | Team leadership and management. | CMC1 | 0.459 |
| Client care | CMC9 | 0.640 | ||
| Basic knowledge of various forms of building and construction contracts | CMC10 | 0.468 | ||
| Conflict avoidance and management or interpersonal understanding | CMC11 | 0.593 | ||
| 6 | ICT-related component | Computer skills – Excel, MS Office, Adobe, Internet-based, etc. | CMC26 | 0.751 |
| Understanding and application of construction-related software knowledge | CMC23 | 0.550 | ||
| 7 | Communication component | Good communication | CMC27 | 0.820 |
CMC, construction management competencies; ICT, information and communication technology.
The results presented in Table 10 indicated that 25 out of the 27 surveyed variables meet the significant (0.35) level for the PCA-rotated component grouping for this study. These, are the critical expected competencies to be attributed by intending CMG in the Nigerian construction industry, from which components 2 and 4: ‘Pre-contract planning and hazard management’ and ‘Basic construction management component’ contained five variables each; components 1, 3 and 5: ‘Project management and planning-related component’; ‘On-site construction management component’ and ‘Peace-making and management-related component’ contained four each; component 6: ‘ICT-related component’ contained two; and component 7: ‘Communication component’ had only one. Overall, component 7 has the highest factor loading of 0.820 and CMC26 has 0.751, and CMC8 has the least factor loading of 0.405.
These clustered variables, referred to as the project management and planning-related component, are the required competencies that deal with understanding the drawing, the capability of noticing and identifying additional work and the ability to bring it to booking by notifying the QS, and the ability to know the competencies to look out for in selecting a sub-contractor, labour requirements, etc. (Jabar et al. 2013; Wang and Cheng 2022). Thus, possessing this attribute will go a long way in improving the company or organisation’s productivity and quality of work done and also increase the employability of construction managers (Benhart and Shaurette 2013). Moreover, construction managers are expected to have substantial knowledge in evaluating work done based on the bill of quantity (BOQ) (Abdullah et al. 2017). In this group, CMC7 has the highest factor loading with 0.659; at the same time, CMC22 had 0.469, which is the least factor loading.
Pre-contract planning and hazard management refer to the competencies associated with understanding the activities involved in getting set for the project. The construction managers are expected to have in-depth knowledge in reviewing tender drawings and documents to check for discrepancies (Dainty et al. 2004; Wang and Cheng 2022) and to cross-check the quoted quantity of works against the proposed volume to be executed. Also, they need to understand what is expected before moving to the site to discharge their duties, such as coordinating materials required for procurement (Male et al. 2010; Torres-Machí et al. 2013) and arrangement of skilled and unskilled labour planning charts. In addition, the construction manager is expected to understand the building process throughout the construction phase (Ying et al. 2015; Turner 2017). Thus, it is required of them to prepare a programme of work to be executed during this phase. Hazard management cannot be left out in the pre-contract planning phase. The earlier the possible hazard is identified and planned for, the better it will be mitigated or prevented from occurring. Therefore, the CMG is expected to know about all the classes of hazards that could occur on-site, such as: falling due to unstable work surfaces, unavailability of fall protective equipment, slipping and tripping, excessive noise, possible electric incidents, etc. These will enable risk management and avoid disrupting the working pace and process.
The activities expected to be performed at this stage are the construction manager’s primary core anticipated duties. The level and quality at which these activities are managed will predict whether or not the project will succeed. Therefore, a CMG is expected to possess competencies in labour and resources management (Ahmed et al. 2014; Mitcheltree et al. 2019). The management of labour and resources is vital in every construction site, as they are the driving force of on-site construction activities. Labour and materials costs could amount to around 90% of the project construction costs. If not well managed, it could result in waste of materials, capital, workforce, etc.; a CMG is expected to be up to date with the labour laws, regulations and procedures, to ensure that the working hours allowable in accordance with labour legislation are complied with. The accomplishment of a construction project depends on getting all the right resources for every task on-site. The proper management of construction resources will help the contractor achieve the project’s main goal with maximum quality and efficiency. A CMG’s ability to prepare a work schedule is essential as this would assist in adequately organising tasks to be carried out on-site, thereby improving resource and labour management. A basic understanding of construction drawing interpretation is essential. Weekly progress report writing competencies are important. It will enable the construction manager to know if there is substantial progress; if not, the management could easily identify the cause of the delay to ensure that this cause is promptly eliminated as well as prevented from occurring again, at least in the near future.
CMG are expected to have a basic knowledge of the preventive maintenance of tools and machines, such as making provisions for machine consumables (oil/grease) and quick identification of faulty tools. In addition, most are versatile in quality management and possess adequate knowledge of sustainable construction processes. Honesty and integrity are core personal competencies any firm or company is looking out for in their employee. For a CMG to thrive in the industry, these personal attributes are essential and their importance cannot be understated. Nevertheless, the quality of being truthful and sincere is regarded as honesty, while integrity is the value of doing the right thing at all times. A CMG is expected to know health and safety practices and first aid administration processes. These will help to prevent possible fatality on-site.
These component elements refer to the peaceable management and coordination of construction team workers, and their aim is the prevention of occurrence of serious disputes in the construction site between the labour force and the management representatives, since such an eventuality can be expected to exercise an adverse impact on the construction workflow. The client’s needs must be met based on the available allocated fund. It is imperative to be on the same page with the client and construction professional teams involved in the project. It will strengthen the relationship between the client and construction firm and may lead to the client referring such firm to friends. As a construction manager, one of the primary responsibilities is the coordination and management of all team members involved in the project. As such, the ideal characteristic of a good leadership is that the leader must present at all times a portrait of being reasonable and receptive to all parties involved, and this can be accomplished concomitant with the adoption of an approach by the leader wherein, to verify compliance with schedule, feedback regarding the work progress is collected on a regular basis, together with inadequate compliance or non-compliance being promptly investigated.
ICT in construction involves communication through computers and hardware, cell phones, satellite systems, etc., through which the construction teams can collaborate successfully and communicate the actual message. Computer-based documentation is essential for running day-to-day site work smoothly, using the following software or applications: Microsoft Office power pack, Adobe and construction-related CAD software (Auto card, Archicad, Orion, etc.). Therefore, it is crucial for a CMG to understand and be able to apply ICT knowledge. These will enhance fast decision-making.
In the context of the construction industry, communication encompasses any mode of imparting or exchanging information, including but not limited to the mediums of writing, speaking or virtual display. These could be subdivided into active listening, written, oral, nonverbal, visual and contextual communication (Mexico 2022). All these communication forms are required to be well understood by a CMG. Such an effective understanding would enable a CMG to function proficiently during the course of discharging of duties. The manner in which a construction manager communicates with others to present and receive ideas makes a lasting impact on the parties with whom the manager interacts, and also significantly influences the mental image that people form of the construction firm on the whole. In Nigeria, where there are diverse languages, it would be imperative for a CMG to understand the country’s unified language (English) (Quora 2022).
This research investigated the innovative skills and competencies expected of CMG in the discharge and management of their professional responsibilities within the Nigerian built environment. Globally, CMG employment is increasingly coming to be characterised by the exhibition of a highly demanding tendency by the construction firm or employer, and Nigeria is no exception to this phenomenon. Moreover, the influx of innovative technology in the industry keeps evolving. For the upcoming CMG to remain employable in a reputable construction firm or industry, they need to know what core skills and competencies are being demanded from the industry. A thorough examination of related literature revealed 13 innovative skills and 27 expected core competencies. A survey questionnaire was developed to collect primary data for the study. The survey data were analysed using descriptive and inferential statistics.
MIS and standard deviation were conducted on the data to statistically rank the variables associated with the innovative skills and expected core competencies, while the RII was used to rate their significance level. Nevertheless, all the 13 and 27 variables were perceived to be significantly important, with MIS ranging from 4.25 to 4.73 and RII from 0.85 to 0.95. This shows that the industry is unwilling and not ready to employ half-baked graduates, possibly due to the project’s highly intensive capital and the construction process’s sophisticated nature. The findings of the survey result with regard to skills indicate that a significant emphasis is manifest for the following aspects: (a) Teamwork skills – it is mandatory for CMG to possess this skill, as it plays an indispensable and major role in the coordination of activities during the construction stage. (b) Critical thinking and openness to feedback – the construction manager is expected to be a fast thinker; the ability on the manager’s part to take swift technical decisions based on the feedback received from time to time speeds up the work concomitant with good quality being maintained. Additionally, other skill variables are also important.
The PCA was conducted, which reduced the 27 variables to 25 and grouped them into seven-component clusters.
Based on this study’s findings, we can conclude that the current demand and expectations of the industry from recent and upcoming graduates are high; these could reflect that the industry does not give room for low-skilled graduates. Consequently, for construction managers or CMG to remain employable or relevant in the industry, they must embrace the innovative skills and competencies essential for the project’s current and future success in the built environment. In addition, they must familiarise themselves with the innovative technology evolving in the industry and possess a high level of personal capability to tackle the core professional task ahead of them. According to the survey report, all the previously identified innovative core competencies in the literature, considered to be revolutionaries’ competencies expected of the CMG, are significantly critical in the Nigerian construction industry. The PCA eliminated ‘Contract administering and managing subcontracts’ and ‘Knowledge of project brief preparation’ from the required competencies peculiar to Nigeria, as perceived by the respondents. This implies that the two eliminated variables are not necessarily crucial for construction managers in the Nigerian construction industry, but may be considered very relevant for other construction professionals. Although this study is limited to the Nigerian construction industry, the identified variables could be modified and used in other regions to generate a comprehensive result using a mixed method of data collection approach.