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International Journal of Civil Engineering and Technology (IJCIET) Volume 9, Issue 13, December 2018, pp. 1431-1445, Article ID: IJCIET_09_13_145

Available online at http://www.iaeme.com/ijciet/issues.asp?JType=IJCIET&VType=9&IType=13

ISSN Print: 0976-6308 and ISSN Online: 0976-6316

© IAEME Publication Scopus Indexed

USING THE FUZZY-AHP TECHNIQUE FOR

DETERMINING THE KEY PERFORMANCE

INDICATORS OF PUBLIC CONSTRUCTION

COMPANIES IN IRAQ

Ali S. Tofan and Hatem K. Breesam

Civil Engineering Department, University of Baghdad; Baghdad, Iraq

ABSTRACT

The fierce competition, the economic weakness and the openness that Iraq is going

through on international construction companies have put great pressure on the local

construction companies to develop their performance continuously. Most of the

researchers focused on measuring the performance and success of construction

projects, but a limited number of studies were done on performance measurement at

the level of the construction company, but these studies began to increase due to the

need for performance measures at the companies' level. Key Performance Indicators

are considered one of means for measuring performance and progress towards

objectives of the organization and help organizations and agencies to identify and

measure their progress toward specific objectives. The indicators are weights and

measures derived from strategic objectives through the translation of those objectives

into programs, procedures, and activities. Performance measurement includes four

operations, which are building standards, then assessment then evaluation and then

optimization. Key performance indicators KPIs typically have financial and non-

financial metrics, which is one of the success measurement techniques of the

performance of organizations. Organizations look to the performance indicators as a

strategy to achieve the objectives and results, and a strong indicator of the

organizational success. List of 58 KPIs in five perspectives (financial, customer, social

and environmental, internal business, and learning and growth) obtained from the

previous studies. Then, the questionnaire was developed for data collection to find the

most important KPIs for construction companies in Iraq. The results of the

questionnaire extracted 26 KPIs. The KPIs from the first questionnaire were included

in a second pairwise comparison questionnaire using the fuzzy analytic hierarchy

process (FAHP) technique to obtain the weights related to each KPIs. Finally, the study

obtained 15 KPIs for construction companies in Iraq divided into four perspectives,

financial, customer, internal business, and learning and growth.

Key words: Construction Companies, Fuzzy-AHP (FAHP), Key performance

indicators (KPI), Iraq



Cite this Article: Ali S. Tofan and Hatem K. Breesam, Using the Fuzzy-Ahp

Technique for Determining the Key Performance Indicators of Public Construction

Companies in Iraq, International Journal of Civil Engineering and Technology, 9(13),

2018, pp. 1431-1445

http://www.iaeme.com/IJCIET/issues.asp?JType=IJCIET&VType=9&IType=13

1. INTRODUCTION

High competitiveness and profound changes in the construction industry force executives to

continually improve the performance of their companies [1]. According to Luu 2008

performance measurement is the core of continuous improvement, application of the

measurement process within companies can identify strengths and weaknesses in performance

and thus use lessons learned to identify best practices that can lead to an outstanding

performance in the case of its adoption and implementation[2].

In order to measure performance, it is essential to select the appropriate key performance

indicators that are most important in determining the success of the construction process. Its

play an essential role in providing information on the performance of the construction tasks,

projects, and companies.

Many studies were conducted to identify the key performance indicators, most of which

focused on performance measurement at the project level, while studies at the company level

were limited[1].

In Iraq, few efforts to identify indicators that can be used to measure the performance of

construction projects carried out and did not focused on the performance of companies wholly

where interest only financial indicators. Thus the set of balanced performance indicators that

can be used to measure the organization's performance is non-existent. Therefore to fill this

gap, this research aims to identify the most critical performance indicators that can be used by

managers to measure the performance of construction companies in Iraq.

2. LITERATURE REVIEW

The literature review considered two specific subjects, construction company performance and

the importance of key performance indicators in the construction companies. Neely 1995

defined performance measurement as: ‘‘the process of quantifying effectiveness and efficiency

of actions.’’[3]. The previous studies addressed several aspects of construction companies'

performance, such as financial, process, customer, learning, and environmental, etc., by

adopting different approaches [4]. National Institute for Standards and Technology (NIST)

2018 defined indicators as: "numerical information used to quantify the input, output and

performance dimensions of processes, products, programs, projects, services and the overall

outcomes of an organization"[5]. The concept of (KPIs) generated an ever growing number of

indicators because each organization will choose the indicators that support the activities which

are critical and of best value for the organization[6]. To measure the performance of a company,

the first thing to do is to look for the Key Performance Indicators (KPIs). Measurement is the

heart of the performance management process as the information system[7]. Adhiprasangga

2016 confirmed that the first step to use the balanced scorecards is identifying the KPIs of the

company[8]. The creators of the balanced scorecards (BSC), Kaplan and Norton, began their

studies on the subject in the 80s, and published it in their article: "The BSC" of the Harvard

Business Review (1992), where they define the BSC as: "A set of indicators that provide top

management with a comprehensive view of the business." Over time, and to the extent that the

BSC is imposed on more organizations, it has become a comprehensive management system

Using the Fuzzy-Ahp Technique for Determining the Key Performance Indicators of

Public Construction Companies in Iraq


articulated with strategic planning[9]. Ali et.al. 2013 developed 10 key performance indicators

for construction companies in Saudi Arabia[1]. The authors found that the company

performance did not depend on the financial indicators only but also the non-financial

indicators. Yu 2007 developed a framework to evaluate the company performance[10]. The

author stressed on the need to develop an integrated method to measure the performance of the

project and the performance of the company simultaneously, because the construction industry

oriented towards the project.

3. METHODOLOGY

To identify the key performance indicators (KPIs) for public construction companies in Iraq,

we determines the KPIs from the literature studies to extract the initial KPIs list that related to

the construction companies. Also, personal interviews with the head or deputy of planning and

monitoring department or quality section manager because they are the most related to

performance measurement of the company. The interviews were made to identify the method

used to measure the performance of the company. Then, from the previous studies and

interviews, the first questionnaire was defined and finalized after the judgment of external

experts. The questionnaire has been distributed to experienced engineers working for the public

construction companies which related to the ministry of Construction, Housing, and

Municipalities. After that, the questionnaire was analyzed to find the KPIs with high

importance according to the relative mean of data collected. The important KPIs from the last

step has been included in the second questionnaire form for pair-wise comparison using the

fuzzy analytic hierarchy process (FAHP) approach to find the relative weight for each

perspective and each KPI. Taking in consideration checking the consistency ratio for the

medium and, lower and upper values of integrated comparison matrices which must be less

than 10%. Finally, identifying the metric for each KPI to measure it. These metrics will help to

Measure the performance of the company toward the objectives on periodical intervals. The

methodology steps is shown in (Figure 1).

3.1 Criteria Selection

The primary data collected from the previous studies in order to find the initial set of KPIs.

These KPIs were included in the first questionnaire to identify the relative importance of each

of them.

An interview is an essential tool in academic and scientific research. Therefore, we did

personal interviews with the head or deputy of planning and monitoring department or the

manager of a quality section of the public construction companies.

Interviews showed that there is a performance evaluation in the companies, but it is not

applied conscientiously, and the evaluation used routinely for employee promotion only.



Figure 1 Research methodology

3.2 Questionnaire

To determine the relative importance of performance indicators for construction companies,

we designed questionnaire form to collect the data. 88 questionnaires were distributed to

experienced engineers and number of heads of departments in 8 public construction contracting

companies (Table 1).

From the 88 forms, returned 84 forms. Also we canceled three forms due to incomplete

information and mistakes. Therefore, the number of questionnaires analyzed were 81 which

represent 92% of questionnaires distributed.

The questionnaires categorized into two parts: the first part is the personal information of

the participant where the second part contains the questions to identify the importance of KPIs

proposed.




Table 1 Questionnaire participants distribution according to the company

Company No. of Participants

Al-Mansour General Company for Constructional Contracts 11

Hammurabi General Company for Constructional Contracts 11

Al-Rasheed General Company for Constructional Contracts 11

Al-Farouq General Company for Constructional Contracts 11

Ashur General Company for Constructional Contracts 10

Saad General Company for Constructional Contracts 9

Al-FAO General Engineering Company 10

AL-Mutasim General Company for Constructional Contracts 8

Reliability of the scale is the extent to which the scale to give results close to each time it

is used, and the reliability of the questionnaire is measured in many different ways. We used

Guttman Split-Half Reliability coefficient and Cronbach's alpha coefficient.

The Guttman coefficient between the two split halves is 0.97, and this means excellent

stability of the questionnaire. Also, by using the alpha equation for the internal consistency of

the questionnaire, had obtained a scale (0.967) for the KPIs group and this mean high internal

consistency of the questionnaire.

The result will take a value from the range (1 to 5) due to the use of a five-point Likert

scale. The calculation has been done using Statistical Package for the Social Sciences (SPSS)

and Microsoft Excel spreadsheets.

After completion of the analysis, the KPIs with relative importance equal or greater than

4.00 were selected from each perspective to evaluate it with the fuzzy AHP pair-wise

comparisons to find the relative weight for each perspective and KPI. Therefore, the selected

KPIs with relative mean are shown in (Table 2) arranged by perspective in descending order.

Table 2 The selected KPIs for FAHP comparison

Perspective KPI Mean

Financial

Profitability 4.65

Financial stability 4.26

Cash flow 4.26

Completion within Budget 4.01

Capital 4.00

Customer

Quality of service and work 4.47

Competitive price 4.20

External customer satisfaction 4.02

Market share 4.01

Internal customer satisfaction 4.00

Social and

Environmental

Policy or law of government 4.02

Risk control 4.01

Competitors 4.00

Internal business

Business efficiency 4.41

Meet technical specification 4.40

Managers competency 4.23

On-time delivery 4.19

Meet predetermined goals 4.14



Effectiveness of planning 4.12

Safety 4.07

Quality control and rework 4.02

Learning and

Growth

Company's reputation 4.22

Organization competency in management human

resources 4.05

Continuous improvement 4.04

Motivation 4.04

Human resource training and development 4.00

3.3 Fuzzy analytic hierarchy process technique

Analytical hierarchy process (AHP) is a powerful decision-making methodology developed by

Saaty in the 1980s to simplify the decision-making process [11]. It includes qualitative and

quantitative techniques and makes it possible to decompose complex problems into simpler

sub-problems where each level shows a set of objectives or criteria relative to each sub-group

[11][12][13]. The nine-point scale simplifies the choice of criteria and provides information

regarding the dominance of each element over others concerning the importance of each

criterion of the higher levels of the hierarchy. Individual opinions of view are made in groups,

taking into account the pertinent decision maker and are handled as a foundation for the

analysis of the reasons for specific judgments; there is the one week spot that occurs during the

setup of comparisons matrixes [14][15]. When the number of characteristics is increasing in

the hierarchy, more matchings' between attributes need to be applied.

Furthermore, by increasing of criteria and sub/criteria, the experts are dealing with physical

and mental fatigue. As a result, the judgments are becoming unreliable, subjective and

imprecise. Therefore, the fuzzy triangular numbers is a valuable solution for handling the

subjective and inaccurate judgments. Zadeh developed the fuzzy set theory and had become a

critical methodology in pair-wise comparisons. The fuzzy number can be defined as triple M=

(l, m, u) where its membership function was defined as[16]:

�� = � �� − � , � ∈ �, ��,�� − �� , � ∈ ��, ��,�, ��, (1)

Where l ≤ m ≤u, l and u are lower and upper values, m is middle value of M. When all three

numbers are equal (l = m = u), then we are dealing with non-fuzzy numbers. The pairwise

comparisons linguistic scale used is shown in (Table 3):

Table 3 The linguistic scale, which used in pairwise comparisons (Salman)

The preference degree

(Intensity of the

importance) of one

activity over

another(linguistically

scale)

The preference degree

Dig

ital

val

ue

Explanations

Fuzzy

digital

value

Invert of the

fuzzy value

Equal importance

1 Two activities contribute

equally to the objective (1,1,1) (1,1,1)




Intermediate importance

between (Equal and

moderate)

2

One activity has (equal to

moderate importance) over

another

(1,2,3) (1/3,1/2,1)

Moderate importance 3

Experience and judgment

slightly prefer one activity

over another

(2,3,4) (1/4,1/3,1/2)


between (Moderate to

strong)

4 One activity has (moderate

to strong) over another (3,4,5) (1/5,1/4,1/3)

Strong importance 5

Experience and judgment

strongly prefer one activity

over another

(4,5,6) (1/6,1/5,1/4)


between (Strong and very

strong)

6 One activity has (strong to

very strong) over another (5,6,7) (1/7,1/6,1/5)

Very strong importance 7 An activity is preferred

very strongly over another (6,7,8) (1/8,1/7,1/6)


between (Very strong and

absolute)

8

One activity has (very

strong to absolute) over

another

(7,8,9) (1/9,1/8,1/7)

Absolute importance 9

The evidence preferring

one activity over another is

of the highest Possible

order of affirmation

(8,9,10) (1/10,1/9,1/8)

The procedure proposed for acquiring priority weights for KPIs can be illustrated in the

(Figure 2).

Figure 2 The proposed procedure for acquiring priority weights for KPIs

(Figure 3) illustrates the hierarchy tree for the pair-wise comparison.

Prioritization of sub-criteria (KPIs)

Evaluation of the weights of criteria and sub-criteria

Consistency check of the matrices (fuzzification of data)

Data collection from the expert group

Preparation of the matrices for data collection (pair-wise comparison)

Development of the hierarchy tree, based on the objective (Best KPIs for construction

company performance), criteria (Perspective), and sub-criteria (KPIs)



Figure 3 The hierarchy tree for pair-wise comparison

During the first step, the comparison on the first level between the main criteria

(Perspectives) was established. On the second level, the pair-wise comparison between sub-

criteria (KPIs) was performed. The pair-wise comparison was made by the expert group of 34

members who have over 15-years' experience in the field of planning and monitoring in the

construction companies.

3.3.1. The FAHP calculation of consistency ratio

We must be sure of the harmonic of the comparisons of every participant, to identify if the

comparisons are harmonic or assonant to be confident of the consistency and validity of sample

answers, Gogus and Boucher (1998) method is used to calculate the consistency ratio[17]. The

calculation completed using the procedure below:

Step 1: divide the integrated fuzzy triangular matrix into two matrices, the first matrix for

middle numbers and the second matrix resulted from the geometric mean of upper values and

lower values of triangular numbers.

Step 2: the vector weight is computed using Saaty method through the equations (2) and

(3) below: �� = �� = �� ∑ ��∑ �� !� (2)

�" = #��"$ �� " = �� ∑ %��∗��∑ %��∗�� !� (3)

Step 3: the largest eigenvalue for each matrix is calculated using the equations (4) and (5)

as follows: '�� = �� ∑ ∑ �� ⁄ � ��!��!� (4)




'��" = �� ∑ ∑ %�� ∗ �� )��" ��"* +��!��!� (5)

Step 4: Following Saaty's procedure, consistency indices (CI), which represent the

deviation from perfect consistency, are calculated using the equations (6) and (7) below: ,-� = �'�� (6)

,-" = .'��" �/�� (7)

Step 5: The ratio of consistency index to the average random index shown in (Table 4)

is called the consistency ratio as presented in equation (8), Following Saaty's rule[11][18],

a consistency ratio of 0.1 or less is considered acceptable for each matrix type. If the

consistency ratio of a pair-wise comparison matrix is greater than 0.1, then the participants

should be encouraged to re-evaluate their preferences. ,0 = ,-0- (8)

Table 4 Random indices [17][19][20]

Matrix Size RIm RIg Matrix Size RIm RIg

1 0 0 9 1.3793 0.4348

2 0 0 10 1.4095 0.4455

3 0.4890 0.1796 11 1.4181 0.4536

4 0.7937 0.2627 12 1.4462 0.4776

5 1.0720 0.3597 13 1.4555 0.4691

6 1.1996 0.3818 14 1.4913 0.4804

7 1.2874 0.4090 15 1.4986 0.4880

8 1.3410 0.4164

The FAHP calculation of consistency ratio was done using the programs proposed by Al-

dhaheri 2018 depending on Gogus and Boucher 1998 method[17][20]. After computing the

weights for each perspective and each KPI, the consistency ratios calculated for the new fuzzy

integration matrices. The results for the main matrix (perspectives) and sub-matrices (KPIs)

are shown in (Table 5). All the matrices achieved a permissible consistency ratio under 0.1.

Table 5 The consistency ratio for main and sub-matrices

The KPIs applied to measure the performance

of construction companies

Number of

criterions CRm CRg

The main matrix (perspectives) 5 0.0067 0.0115

Financial KPIs 5 0.0060 0.0128

Customer KPIs 5 0.0043 0.0075

Social and environment KPIs 3 0.0121 0.0222

Internal business KPIs 8 0.0044 0.0111

Learning and growth KPIs 5 0.0050 0.0110



3.3.2. The FAHP Priority Weights and Ranking of perspectives and key performance

indicators

As well, to obtain the priority weights of the perspectives and KPIs, the program proposed by

Al-dhaheri 2018 depending on Chang 1996 is used[16][20]. The relative weights and rank of

each perspective are shown in (Table 6):

Table 6 The relative weights and rank of each perspective

No. Perspective Weight Rank

1 Financial Perspective 0.413 1

2 Customer Perspective 0.180 3

3 Social and environment Perspective 0.000

4 Internal Business Perspective 0.237 2

5 Learning and Growth Perspective 0.170 4

As seen, the social and environment perspective obtain 0.000 weight which means that the

majority of experts opinion that this perspective does not affect the overall performance of the

construction company. The financial perspective obtains the highest weight with 0.413 due to

its high effect on the success of the company.

The results of relative weights and rank of financial KPIs are shown in (Table 7):

Table 7 The relative weights and rank of the financial KPIs

No. Financial KPI Weight Rank

1 Profitability 0.578 1

2 Financial stability 0.000

3 Cash flow 0.218 2

4 Completion within Budget 0.204 3

5 Capital 0.000

It is noted that the profitability has the highest effect on the financial perspective with 0.578.

Also, the experts decided that the financial stability and capital have 0.000 weight and this due

to that these companies are public supported by the government.

The relative weights and rank of customer KPIs are shown in (Table 8):

Table 8 The relative weights and rank of the customer KPIs

No. Customer KPI Weight Rank

1 Quality of service and work 0.438 1

2 Competitive price 0.052 4

3 External customer satisfaction 0.289 2

4 Internal customer satisfaction 0.189 3

5 Market share 0.032 5

It is evident that the Quality of service and work obtained the highest importance with 0.438

weight followed by the external customer satisfaction with 0.289 weight, which proves that

there is great importance to satisfy the customer to increase the performance of the company.

Although social and environmental indicators will not be adopted because the perspective

weights zero, the results of the pair-wise comparison between them will be explained in (Table

9) to identify the preferences of experts if the social and environment perspective is studied

alone.




Table 9 The relative weights and rank of the social and environment KPIs

No. Social and environment KPI Weight Rank

1 Policy or law of government 0.575 1

2 Risk control 0.425 2

3 Competitors 0.000

The experts consider that the competitors have no importance in comparison with policy or

law of government, and risk control to the social and environment perspective.

The relative weights and rank of internal business KPIs are illustrated in (Table 10), which

shows that the business efficiency is the highest in weight (0.227) followed by the effectiveness

of planning with 0.211 weight:

Table 10 The relative weights and rank of the internal business KPIs

No. Internal business KPI Weight Rank

1 Business efficiency 0.227 1

2 Meet technical specifications 0.021 7

3 Managers competency 0.159 5

4 On-time delivery 0.008 8

5 Meet pre-set targets 0.027 6

6 Effectiveness of planning 0.211 2

7 Safety 0.176 3

8 Quality control 0.171 4

The relative weights and rank of learning and growth KPIs is shown in (Table 11), which

shows that the motivation is the highest importance with 0.370 weight followed by reputation

with 0.284 weight:

Table 11 The relative weights and rank of the learning and growth KPIs

No. Learning and growth KPI Weight Rank

1 Reputation 0.284 2

2 Motivation 0.370 1

3 Organization competency in management human

resources 0.174 3

4 Continuous improvement 0.000

5 Human resource training and development 0.172 4

4. RESULTS ANALYSIS

Kaplan and Norton 1998 mentioned that the number of KPIs is 15-20 for the company[21],

while Ali 2013 stated that the suitable amount of KPIs is 8-12 [1]; also Yu 2007 identified 16

KPIs from 26 KPIs to apply it on construction companies[10]. Alarcon 2001 said that the

implementation of a performance measurement system (PMS) should begin with relatively few

KPIs[22], while Costa 2004 mentioned that high number of KPIs prevents the smooth

application of PMS[23]. Therefore, the KPIs with relative weight equal to or less than 0.100 is

not considered, and the relative weights for the remaining KPIs in the same perspective re-

normalized by sum the remaining KPIs and divide each KPI weight on the sum to obtain the

normalized weight in 100 percent. The final weights for the obtained 15 KPIs are presented in

(Table 12).



In conclusion, these 15 KPIs can be used to measure the performance of the construction

companies in Iraq.

4.1. KPI metrics

After determining the set of key performance indicators (KPIs) and the weights of each KPI

and perspective, these KPIs divided as explained on the perspectives to conclude the

mathematical equation that measures the performance of the construction company in a specific

period.

The weight for each KPI is obtained from the experts by the fuzzy analytic hierarchy

process (FAHP). (Table 13) illustrate the weights and measures of each KPI. The measures

obtained from the previous researches on this field.

Table 12 The final KPIs obtained with relative weights

Perspective Weight KPI Weight

Financial 0.413

Profitability 0.578

Cash flow 0.218

Completion within Budget 0.204

Internal Business 0.237

Business efficiency 0.241

Effectiveness of planning 0.224

Safety 0.186

Quality control 0.181

Managers competency 0.168

Customer 0.180

Quality of service and work 0.478

External customer satisfaction 0.315

Internal customer satisfaction 0.207

Learning and growth 0.170

Motivation 0.370

Reputation 0.284

Organization competency in management

human resources 0.174

Human resource training and development 0.172

Table 13 Weight, code and measure of each KPI

No. KPI Weight Measure or metric

1 Financial

perspective 0.413

1.1 Profitability[1] 0.578 123456 784328 69: 9;< 5;6828=6>369? 28@8;A8=

1.2 Cash flow[1] 0.218 B9=ℎ 4?3D 423E 3F829653;=BA228;6 ?5975?5658=

1.3 Completion

within Budget 0.204

GA<H868< B3=6IJ6A9? B3=6

2

Internal

business

perspective

0.237

2.1 Business

efficiency [1] 0.241

K:F8;=8=L8@8;A8=




2.2 Effectiveness

of planning[24] 0.224

>369? J3=6 34 Jℎ9;H8= 5; D32M=IJ6A9? 6369? J3=6 34 D32M=

2.3 Safety[1] 0.186 NAE782 34 28F32697?8 9JJ5<8;6=I@829H8 ;AE782 8EF?3O8<

2.4 Quality

control[25] 0.181

NAE782 34 <848J6= 5; F23P8J6=>369? ;AE782 34 F23P8J6=

2.5 Managers

competency 0.168

NAE782 34 69=M= J3EF?868<NAE782 34 69=M= 9==5H;8<

3 Customer

perspective 0.18

3.1

Quality of

service and

work [26]

0.478 >369? Q528J6 J3=6 34 R58?< L8D32MIJ6A9? J3;=62AJ653; Fℎ9=8 J3=6

3.2

External

customer

satisfaction

[24]

0.315 External Customer satisfaction Survey

3.3

Internal

customer

satisfaction[24]

0.207 internal Customer satisfaction Survey

4

Learning and

Growth

perspective

0.17

4.1 Motivation[6] 0.370 B3EF8;=9653;L8@8;A8=

4.2 Reputation [24] 0.284 Value of Company reputation Survey

4.3

Organization

competency in

management

human

resources

[27][25]

0.174 SAE9; L8=3A2J8 4A?? − 65E8 8TA5@9?8;6=>369? ;AE782 34 4A?? 65E8 8TA5@9?8;6=

4.4

Human

resource

training and

development[6]

0.172

NAE782 34 F9265J5F9;66= 5; 96 ?89=6 3;8 J3EF9;O F95< 6295;5;H 9J65@56ONAE782 34 8EF?3O88= 8?5H57?8 432 6295;5;H

After measuring each KPI, the progress toward targets then calculated using the linear

equations below:

1. When the trend of KPI is upward: U��V��W� = X��"�� − YU-X��"�� − Z��

2. When the trend of KPI is downward: U��V��W� = YU- − X��"��Z�� − X��"��

Furthermore, the Absolute performance is calculated by multiplying the performance by

the weight as shown below: [\�� ]��V��W� = ]��V��W� ∗ ��"��



Moreover, to find the performance of each perspective, the related KPIs absolute

performance are summed and multiplied by weight of perspective to find the perspective

absolute performance.

Finally, the total performance resulted from the summation of the perspectives absolute

performances.

5. CONCLUSION

After the study of hypotheses and the results analysis of the questionnaire and interviews

conducted, where the goal of this study is to develop the key performance indicators to measure

the performance of public construction companies in Iraq, where these indicators were divided

into four perspectives based on the Balanced Scorecard framework. We found that most

companies focus on financial indicators to measure its performance while other indicators were

neglected. We concluded that the financial indicators have the highest impact on the

performance of the construction companies. However, the financial indicators not reflect the

complete picture of the company's performance. It is worth mentioning that the four

perspectives are not separate from each other, where each affects the other, as by increasing

learning and growth indicators, this will lead to an improvement in the internal business

indicators, which in turn will improve the service provided to the customer and thus increase

his satisfaction, which will eventually increase Company profits,

The paper result can be considered as the first step to create an integrated framework to measure

the performance of construction industry in Iraq.

ACKNOWLEDGEMENTS

The authors thank the Ministry of construction, housing, and municipalities and the

construction companies related to it for support and participation in the questionnaire. Also,

we thank University of Baghdad for permission and encouragement to conduct such studies for

the benefit of science and society.

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