Study of the Sustainable Functioning of Construction Companies in the Conditions of Risk Factors

1. Introduction

The sustainable functioning of a construction company is ensured by its ability to withstand risk factors and achieve the final goals of construction.

Risk management in the implementation of investment and construction projects is necessary for companies operating in the construction sector, as it represents a clear and applicable strategy to ensure their survival in the market [1,2].

Construction companies need reliable and easy-to-implement procedures to achieve the goals of investment and construction projects (compliance with estimated cost standards, proper quality of the construction object, completion of construction and installation works on schedule). In most cases, construction companies are exposed to a large number of risk factors, which are often the result of incompetent management decisions, entailing uncertainty in achieving the final result of an investment and construction project and the loss of sustainable functioning [3,4,5]. The uncertainty that has appeared during the implementation of the investment and construction project creates the possibility that the final result of the project will exceed the desired expectations or the other way around [6].

The need to assess the effective functioning of construction companies is due to market competition, when each business entity strives to improve its performance. Development of algorithms for assessing the sustainability of construction companies in order to improve technical and economic indicators in conditions of risks and uncertainty should be carried out on the basis of system engineering principles for the construction and development of complex systems [4,7,8].

In modern theoretical studies, the issues of risks of the organization and management of construction are considered; methods of assessing and improving the efficiency of construction processes; the capacity of individual elements of construction production and the system as a whole; methods of identifying, assessing and managing risks in construction; problems of the effectiveness of the functioning of construction companies in conditions of uncertainty [9,10,11,12,13].

Algorithm for increasing the sustainability of construction companies in order to improve their technical and economic indicators in the implementation of investment and construction projects should include the following stages [14,15]:

- attracting the attention of participants of investment and construction projects to the problem of risks and uncertainty;

- Determination and assessment of the degree of influence of risk factors on the activities of companies implementing investment and construction projects;

- Development of a structure for the implementation of compensatory measures to exclude or reduce the impact of risk factors on the activities of construction companies;

- Providing contractors with a risk factor management structure and demonstrating the impact of these factors on achieving the goals of the investment and construction project.

Two types of risk factors were selected for the study:

1. Anthropogenic factors.

2. Natural factors.

The difference between anthropogenic and natural risk factors is that anthropogenic factors arise as a result of human actions, while natural factors arise as a result of various natural disasters [10,11,16,17,18,19,20,21,22]. The description of the considered risk factors is presented in Table 1.

2. Materials and Methods

During the analysis of scientific literature, data from various studies, factors influencing the sustainable functioning of construction companies were selected.

To assess the degree of influence of various risk factors on the activities of construction companies and identify the most significant factors, the expert survey method was used [23,24,25].

In order to conduct an expert survey, a questionnaire was developed. Each indicator of the impact of a specific risk factor was obtained by summing up the actual scores set by experts. The degree of influence of risk factors was assessed by experts on a scale from 1 to 18, where 1 point was assigned to the least influential factor, and 18 points to the most influential [26,27].

According to the applied methodology [28], it was determined that the minimum number of experts for the study is 4. However, in order to increase the reliability of the survey results, the authors decided to increase the number of experts to 5. Thus, the expert group consisted of 5 experts, including managers and specialists of construction companies.

To assess the consistency of the results of the expert survey using the concordance coefficient (W), the closeness of the relationship between the ranked factors was determined:

$$W=\frac{12\times S}{m^2.\left(n^3-n\right)-m\sum T_i} ,$$

(1)

where S is the summarization of the squared deviations of the sum of ranks from the arithmetic mean of the sum of ranks.

$$S=\frac{1}{n}{{\displaystyle \sum }}_{i=1}^n{\left(x_i-\mu \right)}^2,$$

(2)

$$T_i=\frac{1}{12}\sum \left(t_i^3-t_i\right),$$

(3)

where ${\mathrm{t}}_{\mathrm{i}}$is the number of repeating elements in the estimates i of one expert;

m is the number of experts;

n is the number of ranked factors;

μ is the arithmetic mean.

Table 2 shows the weight of each risk factor based on the opinion of 5 experts in the field of construction.

Figure 1 shows the ranking of risk factors, taking into account their significance, depending on the weight measured for each of them, according to an expert survey.

The consistency of the results of the expert survey is checked using the concordance coefficient (W), as in formula (1):

$$W=\frac{12\times 42166.5}{{\left(5\right)}^2. \left({29}^3-29\right)-5\times 53}=0.84$$

Since W > 0.5, the consistency of expert opinions exists. The coefficient value is 0.84, which indicates a high degree of consistency of expert opinions.

The degree of consistency is also estimated by calculating the Pearson correlation coefficient using the equation below:

$$X_p^2=w\times m\times \left(n-1\right)=0.84\times 5\times \left(29-1\right)=117.6$$

The calculated Pearson coefficient is compared with the tabular value for the number of degrees of freedom n - 1 = 28, at a given significance level α = 0.05.

Since $X_{p }^2$is calculated – 117.6 > tabular – 41.3, then W = 0.84 is not a random value, and therefore the results obtained by their degree of significance make sense and can be used in further research.

Risk factor management strategies.

The risk factors of construction projects are diverse in nature and causes of occurrence. However, in theory, four main strategies for managing them have been developed, which are often followed in practice [29,30,31]:

• Avoidance (exclusion) of the occurrence of risk factors.
• Transfer of risk factors.
• Reduction (reduction) of the influence of risk factors.
• Acceptance of the occurrence of risk factors.

After identifying and assessing risk factors, construction industry specialists can take the necessary decisions and possible administrative and technological measures. These procedures are designed to contain risk factors by reducing the likelihood of occurrence or minimizing their impact [32,33].

TOPSIS technology allows evaluating the effectiveness of construction companies depending on their chosen risk management strategies. The strategies listed above serve as criteria for reducing or limiting the impact of risk factors of construction companies. The sub-criteria that are taken for this assessment are identified in the process of analyzing data from various studies, interviews with specialists of construction companies. Using the results of the assessment, those who manage risk factors in the company can choose the most preferable solution from several alternatives [34,35,36,37], as shown in Figure 2.

The basic principle of the TOPSIS method is that the alternative should have the shortest distance from the positive ideal solution and the furthest distance from the negative ideal solution [38,39].

The study assessed the sustainability of the functioning of three construction companies depending on the application of different strategies for managing risk factors. To facilitate calculations, the first company was designated C1, the second – C2, the third – C3; criteria (applied measures) were designated as K1, K2, ..., Kp. Table 3 presents the results of the evaluation of each alternative for companies by criteria (applied measures) on a scale from 1 to 10, in accordance with the results of the expert survey[40,41].

Where AAA - is the highest rating for the criteria, which is 10 and so for the rest of the symbols.

If we assume that there is a solution to a multi-criteria problem with (m) alternatives and (n) criteria, then the matrix of solutions (mij) = m × n will have the following form:

$$\begin{array}{ccc}{k}_1& k_2& k_3\end{array}$$

$$\mathrm{M}=\begin{array}{c}{С}_1\\ {С}_2\\ \dots \\ {С}_m\end{array}\left[\begin{array}{ccc}{\mathsf{к}}_{11}& {\mathsf{к}}_{12}& {\mathsf{к}}_{13}\\ {\mathsf{к}}_{21}& {\mathsf{к}}_{22}& {\mathsf{к}}_{23}\\ \dots & \dots & \dots \\ {\mathsf{к}}_{m1}& {\mathsf{к}}_{m2}& {\mathsf{к}}_{mn}\end{array}\right],$$

(4)

The assessment of the effectiveness of the functioning of companies from the point of view of risk factors management is carried out using the TOPSIS method and consists of the following stages:

1. After summarizing the results of the survey of experts in accordance with Table 2 the importance of the criteria is calculated as follows:

$${\text{В}}_{\mathrm{ij}}=\frac{{\mathsf{к}}_{ij}}{{{\displaystyle \sum }}_{i=1}^m{\mathsf{к}}_{ij}},$$

(5)

where Bij is the relative importance of each criterion.

After that, the entropy value of each criterion is calculated using the following formula:

$${\text{е}}_{\mathrm{j}}=\frac{-1}{\ln m}{{\displaystyle \sum }}_{i=1}^m\mathrm{В}ij\ln \mathrm{В}ij,$$

(6)

where ej is the entropy value of each criterion from 0 to 1.

m is the number of alternatives.

Then the weights w1, w2, ..., wn for the evaluated criterion are calculated using the following formula:

$${\mathrm{W}}_{\mathrm{j}}=\frac{1-e_j}{{{\displaystyle \sum }}_{i=1}^n\left(1-e_j\right)},$$

(7)

2. The matrix of normalization solutions for criteria (Measures to reduce or limit the impact of risk factors) is calculated:

$$R_{\mathrm{ij}}=\frac{{\mathsf{к}}_{ij}}{\sqrt{{{\displaystyle \sum }}_{i=1}^m{\mathsf{к}}_{ij}^2}},$$

(8)

where Rij is a matrix of normalization solutions for criteria;

i – 1, 2, ..., m;

j – 1, 2, ..., n.

Then the weighted matrix of normalization solutions for the criteria is calculated as follows:

$$V_{ij}=w_{j }\ast R_{ij},$$

(9)

where (wj) is the weight of the criterion, and the sum of the weights of the criteria is 1 according to the following formula:

$${{\displaystyle \sum }}_{i=1}^n{w}_j=1,$$

(10)

3. Positive and negative ideal solutions are determined:

$${\mathrm{А}}^{+}=max{v}_{ij},j=1,2,\dots \dots ,n,$$

(11)

$${\mathrm{А}}^{-}=min{v}_{ij},j=1,2,\dots \dots ,n,$$

(12)

4. The distance of the alternative from the positive ideal solution is determined:

$$={\left(V_{ij }-v^{+}j\right)}^2,$$

(13)

5. The distance of the alternative from the negative ideal solution is determined:

$$={\left(V_{ij }-v^{-}j\right)}^2,$$

(14)

6. The distance scale (Oi+) is calculated using the Euclidean distance (n). The distance for each alternative of a positive ideal solution is determined by the following formula:

$$O{i}^{+}=\sqrt{\left\{{{\displaystyle \sum }}_{i=1}^n{\left(V_{ij }-v^{+}j\right)}^2\right\},}$$

(15)

7. The distance scale (Oi-) is calculated using the Euclidean distance (n). The distance for each alternative of a negative ideal solution is determined by the following formula:

$$O{i}^{-}=\sqrt{\left\{{{\displaystyle \sum }}_{i=1}^n{\left(V_{ij }–v^{-}j\right)}^2\right\}},$$

(16)

8. The relative proximity to the positive ideal solution is calculated using the following formula:

$$C_i=\frac{O{i}^{-}}{O{i}^{-}+O{i}^{+}} ,$$

(17)

9. The evaluation of tof the sustainable of the functioning of the studied companies from the point of view of risk factors management is carried out, depending on the value of the proximity coefficient (Ci) on the scale presented in Table 4 [42,43,44].

3. Results

The results of the survey conducted among experts of construction companies were analyzed in accordance with Table 5.

The importance of the criteria (applied measures) is calculated using formulas (5), (6) and (7) in accordance with Table 6, Table 7, Table 8 and Table 9.

Using data obtained at the stages of application of the TOPSIS method and formulas (8), (9), (10), (11), (12) and (13) a matrix of normalization solutions was calculated for the criteria (applied measures) to reduce or limit the influence of risk factors (Table 10, Table 11).

Using the obtained values (Wj) (see Table 9) and (Rij) (see Table 11) a weighted matrix of normalization solutions is calculated for the criteria (applied measures) (see Table 12).

Thus, we obtain the values of the positive ideal solution and the negative ideal solution:

А⁺ = 0.179, 0.160, 0087, 0.228,

А^- = 0.131, 0.119, 0.069, 0.159.

Then, the distance of the alternative from the positive ideal solution and the negative ideal solution is calculated (see Table 13, Table 14, Table 15, Table 16).

The coefficient of relative proximity to the optimal solution is calculated in accordance with Table 4 as follows:

Сi(company₁)= 0.071/ (0.071+0.063)= 0.53 (Satisfactorily);

Сi(company₂)= 0.079/ (0.079+0.024)= 0.77 (good);

Сi(company₃)= 0.036/ (0.036+0.077)= 0.32 (Bad).

4. Conclusions

Experts have assessed a large number of factors that can affect the sustainable functioning of a construction company. The results of the survey showed that financial, technical, legal, economic, managerial and natural factors have the greatest impact. When developing a risk management strategy, construction companies are recommended to take into account the significance of the identified factors.

The information obtained can be used by persons responsible for the sustainable functioning of the construction company in the development and planning of measures to counteract risk factors. This will ensure the timely adoption of balanced, well-thought-out decisions; identify specific responses aimed at resolving risky situations.

The sustainable functioning of a construction company is ensured by its ability to withstand risks and achieve the final goals of construction, in this regard, the heads of construction companies now often face the difficult task of choosing optimal solutions in the field of risk management. In such cases, it is necessary to resort to the use of special methods of multi-criteria analysis of decision-making, such as the TOPSIS method. With the help of this method, the stability of functioning was assessed depending on the application of different strategies for managing risk factors of three construction companies.

The study showed that the risk factor management programs developed in the analyzed construction companies do not take into account the influence of some significant factors and modern scientific data about them. Consequently, the measures provided for in such programs to minimize risks are not relevant and cannot lead to highly effective results in preserving such an important property of construction companies as sustainability.

It is recommended to include several important aspects in the plans for managing risk factors in a construction company:

• Conducting advanced training courses that teach participants of an investment and construction project the skills of managing risk factors at all stages of the project.
• Optimization of administrative and legal work related to obtaining licenses for construction activities (development of relevant instructions, regulations).
• Checking the quality of building materials and their compliance with specifications at each stage of the project.
• Study and application of ways to improve the effectiveness of the use of technical resources.

The development of an effective decision-making mechanism aimed at preventing or reducing the impact of risk factors significantly increases the stability of the functioning of construction companies, allowing them to respond in a timely manner to undesirable deviations from the normal course of implementation of investment and construction projects.