Correlation

Data collected in Section 2 of the questionnaire were used to correlate to the characteristics of the participants as recorded in Section 1 of the questionnaire. The results of the Pearson correlation screening are presented in Table 4.7. Easterby-Smith et al. (2008) determined that the Pearson correlation is used to test associations for ordered category scales, ultimately indicate correlations between variables. Saunders et al. (2012) indicated that a deviation between zero and 0.2 positive or negative holds no significant correlation. From Table 4.6 it can be discovered that only weak correlations were identified in the current study and therefore not much time was spent to derive possible explanations for the correlations.

Table 4.6 Pearson correlation screening Pearson Correlation Screening

Barriers Rank Size of company Type of industry Level of Experience Lack of knowledge 1 0.12 -0.28 -0.14

The complexity of analytical tools

2 0.05 -0.22 0.04

The lack of sufficient budget

3 0.15 -0.25 -0.15

Lack of sufficient manpower

4 0.13 -0.10 -0.27

Lack of time

5 0.14 0.10 -0.13

Low profit margin

Pearson Correlation Screening Barriers Rank Size of company Type of industry Level of Experience

Lack of government legislation

7 0.14 -0.05 -0.14

The lack of potential benefits

8 0.02 0.04 0.14

Competition among small construction

firms 9 0.14 0.11 -0.14

It is not economical

10 -0.07 0.28 -0.07

General

The perception of risk management by key decision makers on project affect risk management implementation on

projects 0.07 0.18 -0.02

Contracts and contractual clauses are being used to manage most risks on

small construction projects. 0.24 0.03 -0.03

Impact of Key decision makers on RM

implementation 0.14 0.25 -0.14

Perception that RM impact on project

performance 0.02 -0.21 0.03

The first correlation is lack of knowledge, identified as a barrier to effective risk management, compared to the sector of industry that participants deliver construction projects within.

From the Table 4.7 it could be deduced by means of the central tendency that participants that performed construction projects only in the private or public sector viewed the lack of knowledge as a barrier to effective risk management more seriously than the participants that performed construction projects in both the public and private sector. This can be reasoned by observing the higher mean and median in Table 4.7. Participants that worked on construction projects in both sectors had a significantly lower mean value than the participants that worked in the public and private sectors. The difference in scoring by participants working in

both sectors, compared to the rest of the sample, is difficult to explain with the data available.

Table 4.7 Perception of the impact of lack of knowledge by industry sector

Type Mean Median Mode

Public 9.27 10 10

Private 9.42 10 10

Both 7.76 9 10

The second correlation observed was the degree to which available budget was perceived to be a barrier by participants working in different sectors of the industry.

It can be observed from Table 4.8 that participants working on construction projects in the public sector believe the lack of sufficient budget to be a more noteworthy barrier than participants that worked only on projects in the private sector or worked in both sectors.

Table 4.8 Perception of the impact of lack of budget by industry sector

Type Mean Median Mode

Public 8.2 9 10

Private 7.18 8 8

Both 6.28 7 10

The results depicted in Table 4.9 indicated that participants with less than five years experience scored the barrier, lack of manpower, higher than all the other participants. Moreover the participants with more than twenty years’ experience scored lack of manpower the lowest in terms of severity in the sample group. It may be an indication that less experienced participants believed more people will assist with risk management. The more experienced participants emphasise lack of skills and knowledge as a more severe barrier instead, as observed from the open ended questions in Annexure D.

Table 4.9 Perception of the impact of lack of manpower relative to participant experience.

Type Mean Median Mode

Less than 5 Years 7.88 9 10

5-9 Years 7.21 8 9

10-20 Years 7.26 8 10

More than 20

Years 5.55 6 9

The perception that risk management on small projects was not economical relating to the sector of industry participants worked in, was the next correlation observed. The participants that performed work in the public sector felt that whether it was economical to implement risk management was not a noteworthy barrier on small construction projects as depicted in Table 4.10.

Participants that performed work in the public sector gave a lower mean and median score compared to the rest of the sample group.

Table 4.10 Perception of risk management being economical to implement on projects relative to Industry Sector

Type Mean Median Mode

Public 2.09 2 1

Private 4.83 4,5 1

Both 4.73 4 1

The fifth correlation is that of using contracts as a tool to manage risk on projects and size of companies that use contracts as risk management tools. The correlation between the size of the company and contractual elements to manage risk is presented in Table 4.11. From the data captured from participants in the study there was an indication that participants in companies with 20 to 60 employees tended to use contract and contractual clauses more frequently to manage the risk on small construction projects.

Table 4.11 Perception that contracts are used to manage risk relative to the size of the company.

Size ID Average Median Mode

Less than 20 100 5.5 6 3

20 -60 200 6.44 7 10

60 -250 300 5.6 6 *

More than250 400 5.6 6 8

*The mode cannot be computed for this size company as none of the 4 participants scored the same number.

The last correlation observed gave an indication that participants working on construction projects in the private sector, and both the public and private sector, believed that the impact key stakeholders had on project risk management was more severe to that of the public sector as depicted in Table 4.12.

Table 4.12 Perception of the impact the attitude of key stakeholders have on risk management by industry sector

Type Mean Median Mode

Public 7.8 9 9

Private 8.75 10 9

Both 8.9 10 9