Evaluation Based on the Distance from the Average Solution Approach: A Derivative Model for Evaluating and Selecting a Construction Manager

Abstract

In the current market of integration and globalization, the competition between engineering and construction companies is increasing. Construction contractors can improve their competitiveness by evaluating and selecting qualified personnel for the construction engineering manager position for their company’s civil engineering projects. However, most personnel evaluation and selection models in the construction industry rely on qualitative techniques, which leads to unsuitable decisions. To overcome this problem, this paper presents evaluation criteria and proposes a new model for selecting construction managers based on the evaluation based on the distance from the average solution approach (EDASA). The research results showed that EDASA has many strengths, such as solving the problem faster when the number of evaluation criteria or the number of alternatives is increased.

1. Introduction

Resource management is just as critical as challenging engineering project management themes such as schedule management, time management, cost management, quality management, and risk management [1,2,3,4]. In resource management, evaluating and recruiting personnel for engineering projects are always given top priority. Any project’s success may be attributed to the fundamental human principle of selecting the appropriate personnel, delivering the correct product, and delivering the product at the right time [5,6,7,8,9,10]. Therefore, appropriate candidate evaluation criteria are needed for evaluating and selecting personnel for the position of construction manager in civil engineering projects [11,12,13,14,15,16,17,18]. A new scientific and objective selection method is needed for the company to select a qualified candidate. However, a portion of the currently used models for personnel selection relies on qualitative methods, often resulting in inappropriate decisions [19,20]. The goal of this study is to present evaluation criteria and propose a new method for choosing a construction manager using an EDASA to address this issue.

Next, this paper presents a literature review on personnel competence in construction projects to provide the foundation for identifying basic criteria for selecting a construction manager for civil engineering projects.

Competence is the ability to use skills, knowledge, and personal characteristics to improve efficiency in work performance, increasing the likelihood of project success [21]. According to the Project Management Institute (PMI), there are three types of project management competencies: knowledge, performance, and personal competence [22]. When a project manager applies methods, tools, and techniques to project activities, they are said to have knowledge competency. The project manager’s ability to implement their project management expertise to complete the project’s needs is performance competence. Finally, personal competencies, in addition to attitudes and fundamental personality qualities, describe how project managers perform when engaging in activities within the context of a project. The capacity framework identifies ten management implementation capacities, including managing project (1) integration, (2) scope, (3) time and schedule, (4) cost, (5) quality, (6) resource, (7) risk, (8) procurement, (9) communication, and (10) stakeholders. The six personal competencies include (1) communication, (2) leadership, (3) management, (4) cognitive ability, (5) efficiency, and (6) professionalism.

Construction managers have an important role in projects. Knowledge and skills are two core factors for construction managers [23]. The development and implementation of personnel training methods in the enterprise will help the management apparatus be flexible in assigning personnel, permitting maximum project efficiency. This benefits the construction manager and helps the company, which has a key human resource for long-term development. El-Sabaa [24] identifies the characteristics and skills of an effective construction manager. The author considers communication skills as the top criterion of project managers, while technical skills were less influential. In addition, the authors also highlight the difference between a project manager and a construction company executive. While both require resourcefulness, a construction manager requires extensive, broad knowledge to make the best use of resources. In addition, construction managers must have soft skills, accept change, and be proactive in their work. The construction manager should be the leader throughout the project lifecycle. In that role, the construction manager must be the individual who knows how to plan and monitor the entire project for the best efficiency.

Gharehbaghi and McManus [17] explore the necessary leadership qualities for successful construction projects. They depend on the task, team, work environment, resources, schedule, and budget. The author also suggests four important criteria that construction management engineers need, including (1) knowing other people, (2) knowing yourself well, (3) being able to communicate, and (4) decisiveness. A good leader must know and understand the wishes of their subordinates and demonstrate concern for their lives. In other words, understand personnel at the construction site, share experiences, and unite to accomplish individual goals. Construction managers must understand themselves and continue to learn and develop. A good leader must communicate well and be decisive in all situations. In addition, a construction manager must possess good general knowledge and skills and thoroughly understand the company culture and the construction site. These conditions require construction companies to equip themselves with the necessary additional knowledge through training, including short-term training courses.

Dainty, et al. [25] identify the core competencies related to the construction manager’s role and deploy a predictive model to make selection decisions and train personnel for construction managers for large construction companies. The authors reveal that many project manager candidates participate in surveys in which their employees are asked to recount problems and solutions. This practice allows managers to understand their capabilities. The authors provide a logistic regression model for assessing candidate competence, and their results show that self-control and team leadership are the dominant factors determining a construction manager’s competence. In addition to 12 performance-related abilities important for project managers, the study identified 10 additional competency characteristics: accomplishment orientation, initiative, information seeking, attention, impact, and efficacy in meeting client needs, direction, teamwork and collaboration, analytical and conceptual thinking, and agile execution.

Based on interviews with 13 project leaders, civil engineers, and construction managers, as well as 7 team leaders, in 13 construction projects in Sweden, Styhre and Josephson [26] find the importance of specific roles in project success. The authors also show that, although they are required to manage a substantial amount of work in their projects, most construction management engineers are satisfied with their work. The authors have shown that the position of construction engineers is indispensable to ensuring the project’s success. Construction enterprises should establish training courses for construction engineers and consider core skills for advanced training according to job characteristics. Technical skills alone are insufficient to create a successful project manager. Fisher [27] suggests six soft skills necessary for human resource management and corresponding behaviors for an effective construction manager, including (i) understanding employee behavioral characteristics, (ii) the ability to lead the team, (iii) the ability to influence, (iv) committing clear and honest actions, (v) the ability to resolve conflicts, and (vi) perceiving personality differences of project team members.

Zulch [28] recognizes essential characteristics that a construction manager must possess for successful communication. The managers should know that all leadership styles will have varying degrees of influence on the success of a project. Knowledge of leadership will help managers flexibly solve work problems according to specific situations, permitting project success. Evaluation of the capacity of the construction manager cannot be complete without assessing their experience because, without experience, competence cannot be demonstrated or improved [29]. Moreover, experience is considered an important factor for successful personal growth. To successfully fulfill their assigned role, individuals need to accumulate the necessary experience and thus complement their potential.

According to the APM Competence Framework, project managers’ competencies include 20 technical competencies, 15 behavioral competencies, and 11 contextual competencies [30]. Construction project managers must have both technical knowledge and proficiency and abilities to coordinate and communicate effectively with various stakeholders. To ensure project success, construction managers must possess technical expertise, people skills, and a work ethic. Nuwan, et al. [11] discover management development approaches. The authors use the Delphi method, including 12 experts and 44 respondents, to develop 20 factors of specialized knowledge, soft skills, and working attitude that are meaningful for construction engineers. The most important of these are planning and managing progress. The most important soft skills regarding working attitude are time management and leadership.

Based on the list of capacity assessment criteria surveyed above, construction experts in Vietnam have selected the 15 most important criteria (within three groups) to select construction managers in

Table 1. Criteria for the evaluation and selection of a construction manager.

Code	Criteria for the Evaluation and Selection of a Construction Manager
CE	Construction Expertise
CE1	Construction technical knowledge
CE2	Knowledge of construction organization and management
CE3	Knowledge of the construction schedule
CE4	Knowledge of occupational safety and environmental sanitation
CE5	Understanding of construction quality and volume management
SS	Soft Skills
SS1	Communication and presentation skills
S2	Construction problem-solving skills
S3	Ability to lead and guide construction workers
S4	Information management skills (documents, construction records)
S5	Creative innovation ability
WE	Work Experience
WE1	Similar projects and works completed
WE2	Experience working with owner, project management unit, and supervisory unit
WE3	Experience working with contractors, project teams, and construction suppliers
WE4	Professional degrees and certificates in construction
WE5	Ability to use construction specialized software

.

The rest of the paper is organized as follows. Section 2 provides the EDASA research method employed in Section 3. This section describes the empirical results and discusses the EDASA application. The final section concludes the study.

2. Methodology

Keshavarz et al. invented the distance from the average solution approach EDASA method in 2015 [31,32]. The best alternative is selected using EDASA by measuring the distance of each choice from the ideal value. This method is especially useful in situations with contradicting attributes or conflicting criteria. EDASA has been applied in the evaluation of airline services [33], solving air traffic problems [34], personnel selection [35], green supplier selection [36], material selection [37], and hospital site selection [38]. Using this method, suppose there are n construction manager candidates and m evaluation and selection criteria. The steps for using the proposed method are presented as follows [31,32,33,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60]:

Step 1: Calculate the weight of each criterion.

Step 2: Create a decision-making matrix, shown as follows:

$$X=\left[\begin{array}{cccc}{x}_{11}& x_{12}& \dots & x_{1n}\\ x_{21}& x_{21}& \dots & x_{2n}\\ ⋮& ⋮& & ⋮\\ x_{1n}& x_{2n}& \dots & x_{mn}\end{array}\right]; i=1, 2, \dots , m; j=1, 2, \dots , n$$

(1)

where

x_ij denotes the performance value of the i^th alternative on the j^th criterion. Moreover, the assessor weight of the criteria w = [w₁, w₂, …, w_n].

Step 3: Identify the average solution based on each of the following criteria:

$${\overline{x}}_j=(x_1, x_2,\dots ,x_n),$$

(2)

where

$${\overline{x}}_j=\frac{{\displaystyle \sum _{i=1}^m{x}_{ij}}}{m}; j=1, 2,\dots , n.$$

Step 4: Determine the positive and negative distances from the average solution.

The positive distances from the average (PDA) and the negative distances from the average (NDA) are dependent on the type of criteria (benefit and cost), calculated as follows:

$$d_{ij}^{+}=\{\begin{array}{l}\frac{\max (0,(x_{ij}-{\overline{x}}_j))}{{\overline{x}}_j},j\in {\mathsf{\Omega }}_{\max }\\ \frac{\max (0,({\overline{x}}_j-x_{ij}))}{{\overline{x}}_j},j\in {\mathsf{\Omega }}_{\min }\end{array}.$$

(3)

and

$$d_{ij}^{-}=\{\begin{array}{l}\frac{\max (0,({\overline{x}}_j-x_{ij}))}{{\overline{x}}_j},j\in {\mathsf{\Omega }}_{\max }\\ \frac{\max (0,(x_{ij}-{\overline{x}}_j))}{{\overline{x}}_j},j\in {\mathsf{\Omega }}_{\min }\end{array}.$$

(4)

where

$d_{ij}^{+}$ and $d_{ij}^{-}$ denote the positive and negative distance of i^th candidates from the average solution of j^th factors, respectively;

${\mathsf{\Omega }}_{\max }$ and ${\mathsf{\Omega }}_{\min }$ are positive real numbers that represent the set of benefit criteria and the cost criteria, respectively.

Step 5: Determine the weighted sum of PDA, and the weighted sum of NDA, for all alternatives, shown as follows:

$$Q_i^{+}={\displaystyle \sum _{j=1}^n{w}_j}{d}_{ij}^{+}; i=1, 2, \dots , m$$

(5)

$$Q_i^{-}={\displaystyle \sum _{j=1}^n{w}_j}{d}_{ij}^{-}; i=1, 2, \dots , m$$

(6)

where

w_j denotes the nonnegative weight of the criterion j.

Step 6: Normalize the values of the weighted sums of PDA and NDA for each of the candidates, as shown below:

$$S_i^{+}=\frac{Q_i^{+}}{\underset{k}{\max }{Q}_k^{+}}.$$

(7)

$$S_i^{-}=1-\frac{Q_i^{-}}{\underset{k}{\max }{Q}_k^{-}}.$$

(8)

where

$S_i^{+}$ and $S_i^{-}$ denotes the normalized weighted sum of the PDA and the NDA, respectively.

Step 7: The appraisal scores S_i for all project managers are computed as follows:

$$S_i=\frac{S_i^{+}+S_i^{-}}{2}.$$

(9)

where

$0\le S_i\le 1$; i = 1, 2, …, m

The appraisal scores for construction manager candidates are listed in descending order. Among the applicants, the one with the highest S_i is the best option.

3. Results

We applied the EDASA through a case study in one construction project in Vietnam. The recruitment committee consists of five professionals who must evaluate and select one of three candidates (A1, A2, A3) for the construction manager position. First, construction experts used Saaty’s scale of 1–9 to make a pairwise comparison of evaluation and selection criteria for construction managers. The results of the weight calculation of these criteria are presented in

Table 2. The weight of criteria for the evaluation and selection of a construction manager.

Code	Criteria for the Evaluation and Selection of a Construction Manager	Weight
CE	Construction Expertise
CE1	Construction technical knowledge	0.1760
CE2	Knowledge of construction organization and management	0.0920
CE3	Knowledge of the construction schedule	0.0630
CE4	Knowledge of occupational safety and environmental sanitation	0.2900
CE5	Understanding of construction quality and volume management	0.0380
SS	Soft Skills
SS1	Communication and presentation skills	0.0070
SS2	Construction problem-solving skills	0.0500
SS3	Ability to lead and guide construction workers	0.0300
SS4	Information management skills (documents, construction records)	0.0110
SS5	Creative innovation ability	0.0170
WE	Work Experience
WE1	Similar projects and works completed	0.0270
WE2	Experience working with owner, project management unit, and supervisory unit	0.1040
WE3	Experience working with contractors, project teams, and construction suppliers	0.0580
WE4	Professional degrees and certificates in construction	0.0230
WE5	Ability to use construction specialized software	0.0140

.

Second, five construction experts created the decision-making matrix and calculated the average solution using Equation (2) according to all selection criteria, as shown in

Table 3. The average solution of criteria for the evaluation and selection of a construction manager.

Code	Criteria for Evaluation and Selection of Construction Manager	A1	A2	A3	${\overline{\mathit{x}}}_{\mathit{j}}$
CE	Construction Expertise	75	60	82	72.3333
CE1	Construction technical knowledge	83	62	74	73.0000
CE2	Knowledge of construction organization and management	84	71	64	73.0000
CE3	Knowledge of the construction schedule	72	62	82	72.0000
CE4	Knowledge of occupational safety and environmental sanitation	62	84	71	72.3333
CE5	Understanding of construction quality and volume management	71	85	63	73.0000
SS	Soft Skills	73	62	82	72.3333
SS1	Communication and presentation skills	82	73	63	72.6667
SS2	Construction problem-solving skills	74	81	61	72.0000
SS3	Ability to lead and guide construction workers	62	83	71	72.0000
SS4	Information management skills (documents, construction records)	84	60	74	72.6667
SS5	Creative innovation ability	72	63	81	72.0000
WE	Work Experience	63	73	80	72.0000
WE1	Similar projects and works completed	83	62	74	73.0000
WE2	Experience working with owner, project management unit, and supervisory unit	64	81	71	72.0000
WE3	Experience working with contractors, project teams, and construction suppliers	75	60	82	72.3333
WE4	Professional degrees and certificates in construction	83	62	74	73.0000
WE5	Ability to use construction specialized software	84	71	64	73.0000

.

The positive and negative distances from the average solution are calculated using Equations (3) and (4), as shown in

Table 4. Values of the positive distances from the average (PDA).

Code	Criteria for the Evaluation and Selection of a Construction Manager	A1	A2	A3
CE1	Construction technical knowledge	0.0369	0.0000	0.1336
CE2	Knowledge of construction organization and management	0.1370	0.0000	0.0137
CE3	Knowledge of the construction schedule	0.1507	0.0000	0.0000
CE4	Knowledge of occupational safety and environmental sanitation	0.0000	0.0000	0.1389
CE5	Understanding of construction quality and volume management	0.0000	0.1613	0.0000
SS1	Communication and presentation skills	0.0000	0.1644	0.0000
SS2	Construction problem-solving skills	0.0092	0.0000	0.1336
SS3	Ability to lead and guide construction workers	0.1284	0.0046	0.0000
SS4	Information management skills (documents, construction records)	0.0278	0.1250	0.0000
SS5	Creative innovation ability	0.0000	0.1528	0.0000
WE1	Work experience	0.1560	0.0000	0.0183
WE2	Similar projects and works completed	0.0000	0.0000	0.1250
WE3	Experience working with owner, project management unit, and supervisory unit	0.0000	0.0139	0.1111
WE4	Experience working with contractors, project teams, and construction suppliers	0.1370	0.0000	0.0137
WE5	Professional degrees and certificates in construction	0.0000	0.0000	0.0000

and

Table 5. Values of the negative distances from the average (NDA).

Code	Criteria for the Evaluation and Selection of a Construction Manager	A1	A2	A3
CE1	Construction technical knowledge	0.0000	0.1705	0.0000
CE2	Knowledge of construction organization and management	0.0000	0.1507	0.0000
CE3	Knowledge of the construction schedule	0.0000	0.0274	0.1233
CE4	Knowledge of occupational safety and environmental sanitation	0.0000	0.1389	0.0000
CE5	Understanding of construction quality and volume management	0.1429	0.0000	0.0184
SS1	Communication and presentation skills	0.0274	0.0000	0.1370
SS2	Construction problem-solving skills	0.0000	0.1429	0.0000
SS3	Ability to lead and guide construction workers	0.0000	0.0000	0.1330
SS4	Information management skills (documents, construction records)	0.0000	0.0000	0.1528
SS5	Creative innovation ability	0.1389	0.0000	0.0139
WE1	Work experience	0.0000	0.1743	0.0000
WE2	Similar projects and works completed	0.0000	0.1250	0.0000
WE3	Experience working with owner, project management unit, and supervisory unit	0.1250	0.0000	0.0000
WE4	Experience working with contractors, project teams, and construction suppliers	0.0000	0.1507	0.0000
WE5	Professional degrees and certificates in construction	0.0000	0.0000	0.0000

.

The weighted sum and the weighted normalized sum of PDA and NDA for the candidates are calculated using Equations (5)–(8). Finally, the appraisal score of each construction manager candidate is calculated using Equation (9). All results are shown in

Table 6. The weighted normalized sum of PDA and NDA and the appraisal score.

	A1	A2	A3
$Q_i^{+}$	0.0406	0.0122	0.0920
$Q_i^{-}$	0.0152	0.1142	0.0153
$S_i^{+}$	0.4410	0.1326	1.0000
$S_i^{-}$	0.8666	0.0000	0.8657
$S_i$	0.6538	0.0663	0.9329

.

The calculation results in Table 6 show that candidate A3 has the highest appraisal score (0.9329). Therefore, this person is prioritized to be selected as the construction manager. The research results showed that EDASA has many strengths. First, some qualitative attributes could be converted into quantitative attributes. Second, compared with traditional assessment methods (e.g., AHP), EDASA can consider conflicting criteria in the same problem. Third, the time to apply EDASA to solve the problem was faster when the number of evaluation criteria or the number of alternatives increased. Finally, this method can be combined with other theories such as fuzzy logic or grey system theory to reflect the complexity or uncertainty of the real world because it has a solid mathematical basis [39,43,61].

4. Conclusions

The fundamental human principle of choosing the right personnel, delivering the right product, and delivering the product on time is necessary for the success of any engineering and construction project. This paper presents fifteen evaluation criteria for selecting a construction manager and proposes a new quantitative methodology for this selection utilizing EDASA. This method is practically applied through a case study of the evaluation and selection of construction managers, demonstrating its effectiveness, especially in the event of the evaluation of many construction manager candidates. In addition, in some situations where the selection problem is complex or has more selection criteria, the EDASA deterministic approach should be combined with another method or theory (such as fuzzy logic theory or grey system theory) to reflect the uncertainty in the judgment of the decision maker.