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DOI: 10.14807/ijmp.v10i2.859
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512
Analysis of Financial Performance of Cement Industry
Manufacturing Companies in Tehran Stock Exchange Using the
FAHP Technique and the TOPSIS Method
Sahar Omrani
Zanjan Soufi University, Iran, Islamic Republic of
E-mail: Saharomrani69@yahoo.com
Mostafa Jafari
University of Zanjan, Iran, Islamic Republic of
E-mail: Strategy2000ir@yahoo.com
Ali Mansori
University of Zanjan, Iran, Islamic Republic of
E-mail: Mansori.ali@znu.ac.ir
Submission: 06/08/2018
Revision: 22/08/2018
Accept: 18/09/2018
ABSTRACT
Objetive: The aim of this study was to provide a fuzzy model for
evaluating the performance of cement industry manufacturing
companies listed in Tehran Stock Exchange in 2013, 2014 and 2015
using financial ratios and considering the preferences of different
decision makers.
Methodology: This study was based on FAHP and TOPSIS, in which
the FAHP was used to determine the weight of different criteria of the
decision makers. Finally, the cement industry companies were
ranked using the TOPSIS approach. In this study, different financial
ratios such as liquidity ratios, leverage ratios, activity ratios,
profitability ratios, and growth ratios were used for evaluation.
Results & Findings: Eleven findings and nineteen results were
presented that three Soufian Cement Company, Ghadir Capital and
Industry Development Cement Company, and Hegmatan Cement
Company from Three East Azarbaijan, Tehran, and Hamedan
provinces and from three different geographic regions of Iran have
had the most similarity with the ideal solution in the
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ranking of options (alternatives) by the TOPSIS method. Also, in the light of core
values and by maintaining their market share and competent corporate governance,
they have gained the highest output of the cement industry by obtaining the first rank
respectively in 2013, 2014, and 2015, which, in turn, can be a good representative of
the country's cement industry. By modeling the top companies and with the help of
science along with analyzes in other sectors of the cement industry, the firms with
weaker performance can strengthen their performance. This can become a strong
strength for the Iranian cement industry.
Keywords: Performance measurement, Financial Ratios, Cement Industry, FAHP,
TOPSIS
1. INTRODUCTION
The corporate performance measurement has long been considered as an
important issue. Measurement the companies' performance is nowadays one of the
most important financial issues for them. Using the corporate performance
evaluation methods, the issues such as the following can be addressed appropriately
(BACIDORE, 1997):
• How much the companies have struggled to raise the interests of their
shareholders?
• What indicators are considered by banks and credit institutes in providing
facilities to the companies?
• What aspects are considered by the owners of the companies in giving
rewards to the managers?
• Ultimately, what points are considered by the government entities due to legal
requirements in relation to companies?
Most economics scholars have recognized capital formation as the most
important factor for economic development. Economic development in today's
progressive world is owed to stock markets and capital market activities
(GHALIZADEH; HASSAN, 2004).
The investors are always looking for the best investment to gain further
interest. To this end, they seek to separate successful and unsuccessful companies
and rank them. Considering the poor performance of ranking methods used in
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Tehran Stock Exchange, it appears crucial to provide a method that can facilitate the
issue meanwhile being highly reliable. Making decisions by considering a number of
criteria, each of which has a special place, can be possible only by using multi-
criteria decision-making models. Various indicators tailored to the type of ranking are
used in these methodS (IRAQI, 2008).
Therefore, financial evaluation and ranking the companies can be done by
considering financial ratios as indicators, Stock Exchange companies as options and
the use of multi-criteria decision-making methods. The aim of this research was to
provide a decision-making model to investigate and evaluate the financial
performance of the stock market companies by using their financial ratios and also to
achieve the decision makers' thematic judgments.
To do so, a combined method (Fuzzy Analytical Hierarchical Process (FAHP)
and TOPSIS) was used. These two methods are recognized as the most important
and most widely used decision-making methods and their combination is expected to
deliver optimal results. Nowadays, following the competitiveness of the global
economy and increased public awareness of financial and investment issues, the
capital market has drawn the attention more than ever.
On the other hand, to capture the attention of investors, most companies are
trying to produce high quality goods and services with lower costs. Meanwhile, a
number of companies try to show a favorable image of their company status by
providing unrealistic and misleading information to keep themselves at the
competition scene in attracting the investors. Hence, measuring the performance of
companies with appropriate and diverse indicators as well as rating them based on
these indices seem to be important and beneficial to the investors.
The performance appraisal with respect to the development of capital markets
is among the major issues regarded by the stakeholders, creditors, governments and
managers. The investors always tend to be informed of the success of managers in
using their capitals (MAHMOOD; SHAHABDIN; JAFAR, 2010). Financial ratios are
the most useful indicator for the performance and the financial status of the company
(ÍRFAN; NILSEN, 2007).
However, ranking by considering several criteria that each have a special
place only can occur by applying the multi-criteria decision-making models. Various
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indicators are used tailored to the type of ranking in these methods (MASOUMEH;
ZERR, 2009). Hence, using five financial ratios as indicators and employing the
multi-criteria decision making methods, we can financially evaluate and rate the
companies listed on the Stock Exchange. Accurate assessment of companies in the
industries can be a full mirror of the status of different companies compared to their
competitors, revealing their internal strengths and weaknesses as well as their
external opportunities and threats (KASHAN, et al. 2004).
The evaluation of companies plays a major role in the industry. Introducing
industry-leading companies specifies their position in a competitive environment
based on various indicators or variables. This, on the one hand, makes the weak
companies to distinguish their distance from the top ones to develop an appropriate
strategy to reach them. On the other hand, the top companies will strengthen their
superiority by defining their proper plans and strategies.
The capital formation is assumed the most important factor in economic
development from the perspective of most economic thinkers and stock and capital
market is one of the most important sources of providing capital. The total of these
factors leads to increased competition in the market, and increasing competition will
also ultimately leads to the development of the society (MAHMOUD, et al. 2006).
Financial information is one of the most important factors in most decision
makings. More complex decision-making environment with higher uncertainty will
add the difficulties of the decision-making process. In this regard, the financial
statements are designed to help users identify the key relationships and predictions
and investors use such information to evaluate the investment decisions and
prioritize them (SASAN; KAVEH; GHOLAMREZA, 2004).
In such an environment, an absence of criteria and methods for evaluating
companies and helping the investors in the Tehran Stock Exchange cannot be
ignored. There is also a void of methods to help the companies listed on the Tehran
Stock Exchange to know what a score they need to obtain for getting more efficient
and closing to the level of efficiency.
2. RESEARCH LITERATURE AND BACKGROUND
Investing in stocks seems to be one of the most important factors by using
which a country can be developed. Investment in equity can achieve the
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predetermined target if it has been done properly and optimally. To this end,
appropriate models need are needed for measurement of stock efficiency or
productivity. There are several different models in this regard, including Fuzzy
Analytical Hierarchical Process (FAHP) and TOPSIS.
Using this technique, the success rate of a share can be measured at a time
section; however, the performance measurement at a time section is not sustainable
enough according to environmental, social and economic conditions. On the other
hand, if there is a model to be used to measure the stocks growth (regression) in
several periods, a proper context will be provided for the investors' decision making.
Given that the cement industry is one of the influential industries of Tehran
Stock Exchange with many member companies, we designed this research to
evaluate and rank the companies of the cement industry listed in Tehran Stock
Exchange using the combined method (FAHP & Topsis).
Cement industry plays a highly important role in promoting the country's
development goals as a strategic commodity and is of particular importance as one
of the conversion industries in Iran. It has been also considered in the path of self-
reliance In terms of currency savings. Hence, economical measurement and
comparison of active units in this industry within the country appears to be important
and considerable in terms of efficiency and productivity with a managerial attitude.
Currently, 5 cement companies are operating in Iran and the number of units
increases annually. The main advantage of this research is to compare these units
with each other meanwhile evaluating their efficiency. In addition to illustrating the
distribution of the functional structure of the cement industry within the country, this
domestic comparison also compares each unit with the whole domestic units; thus,
units operating in a similar political-economic structure are compared with each
other.
Using the FAHP, TOPSIS approach, we tried to identify the major cement
production units inside the country and compare their efficiencies. Accordingly, we
could separate more efficient units and compare them meanwhile considering the
specific power of each unit. With the help of this analysis, we would be able
eventually help the decision makers change the efficiency elements of each unit to
move toward higher levels of efficiency. Also, using the FAHP -TOPSIS approach,
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the companies can be assessed with the aim to maximize profits by considering the
composition and optimal allocation of resources.
A brief explanation of some multi-criteria decision-making methods is provided
for the reader to clarify the two methods of hierarchical process and topsisization and
other multi-criteria multi-criteria methods.
2.1. SAW
A simple weighting model is one of the easiest methods for multi-index
decision making. By calculating the weights of indicators, it is easy to use this
method. The steps to use this method are as follows:
• Decrease the decision matrix
• Non-linear scaling of decision matrix values
• Multiplication of non-scale matrices in weights of indicators
• Choose the best option using the countermeasure criterion:
2.2. ELECTRE
This model was introduced in the late 1980s and was considered as one of
the best multi-indicator decision-making techniques. The basis of this concept is
"non-ranked relationships", which does not necessarily lead to ranking of options, but
may also eliminate options.
2.3. TOPSIS
This model was proposed by Huang and Yun in 1981 and is one of the best
multi-index decision-making models. This technique is based on the notion that the
choice option should have the least distance with the ideal ideal solution (best
possible) and the maximum distance with the ideal negative solution (the worst
possible condition).
The problem solving steps using this method are:
• Calculation of soft-scale non-scale matrix
• Compute the weights matrix with one of the weighing methods W
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• Calculation of V-Scale Non-scale Matrix
• Ideal positive solution Vj +: the largest value for the positive indicators and the
smallest value for the negative index. In other words, we compile the vector of
the best values for each index.
• Ideal negative solution Vj-: the largest value for negative indicators and the
smallest value for positive indicators. In other words, we compose the vector
of the worst values for each index.
• Calculates the Euclidean distance of each option to positive and negative
ideals.
• Determine the relative proximity of an option to the ideal solution:
• Ranking options based on larger CL.
2.4. Analytical hierarchy process
Hierarchical Analytic Process (AHP) is one of the most well-known multi-
dimensional decision-making techniques developed by Thomas A. Lee in the 1970s
(Haynes, et al. 1993). This method is used when decision-making practice with
multiple options And the decision maker is useful, indexes can be quantitative or
qualitative, the basis of this method lies in the comparison of the pair.
Wang (2008) used Gray Relations Analysis method in categorizing financial
ratios to assess the financial performance of the airlines in Taiwan and employed the
fuzzy multi-criteria decision making in the final ranking of these companies (WANG,
2008). Oortagul and Karakasoglu used the FAHP and TOPSIS to evaluate the
financial performance. They used the first method to determine the weights of the
studied financial ratios.
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Then, using these weights and the second method, they ranked 15 companies
active in the Turkish cement industry (WANG, 2008). By combining the FAHP and
TOPSIS methods, Wang (2008) initially determined the importance of decision-
making criteria and finally ranked the suppliers by employing the fuzzy TOPSIS
approach.
Using the FAHP, Kuo, Yang and Huang (2008) evaluated the performance of
the Turkish cement industry companies and employed the TOPSIS approach to rank
the studied companies. Rezaie, et al. (2014) ranked the Cement companies active in
the stock market during the two consecutive years of 2008 and 2009 using the
financial ratios and utilizing the Integrated Fuzzy Analytical Hierarchical Process and
Vikor method. Based on the results obtained in 2008, the companies of Qaen, Fars
and Khuzestan had the best performance, respectively.
In 2009, the companies of Hormozgan, Ardebil and Qaen had respectively the
best performance (REZAIE, et al., 2014). Chang, et al. (2010) ranked the cement
companies active in the stock market using the financial ratios and Analytical
Hierarchy Process and Topsis methods. According to their results, the cement
companies of Fars, Ardebil and Qaen obtained the first to third ranks of financial
performance, respectively (MASOUMEH; ZERR, 2009).
In another research, Yalcin, Bayrakdaroglu and Kahraman (2012) evaluated
the performance of the Turkish banking sector. Considering a variety of financial
ratios in this study, they initially extracted the weights of ratios using the FAHP
approach. Then, the banks were ranked by TOPSIS method. They showed that the
banks more successful in practice had obtained better rating in this study as well
(YALCIN; BAYRAKDAROGLU; KAHRAMAN, 2012).
In a research entitled as "Evaluation of the performance of joint venture capital
investment firms using the developed TOPSIS method with a different distance
approach", Chang et al. evaluated the performance of joint venture funds in the
structure of multi-index planning analysis (2010) using the Treynor ratio, Sharpe
ratio, Jensen alpha and the ratio of information, and each of these criteria was also
used for the final ranking. In this study, 82 joint investment funds in Taiwan were
evaluated for 34 consecutive months by using the TOPSIS method (CHANG; LIN;
LIN; CHIANG, 2010).
Using the FAHP, TOPSIS & VIKOR approaches, Ho, Cheung and Cheung,
(2009) ranked three reputable banks of Taiwan based on the Balanced Scorecard
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method and showed that the methods of fuzzy decision making models are suitable
methods for performance evaluation (HO; CHEUNG; CHEUNG, 2009).
Using the FAHP & TOPSIS methods, Mahmood, Shahabdin and Jafar (2010) ranked
5 credible banks in Turkey and acknowledged that the non-financial criteria should
also be considered along with financial criteria to evaluate the performance.
Masoumeh and Zerr (2009) provided a fuzzy model for evaluating the performance
of Turkish cement companies using the developed financial ratios, an approach
based on the FAHP and TOPSIS methods (MASOUMEH; ZERR, 2009).
In a research entitled as "The use of Gray Relations Analysis to solve the
problems of multi-criteria decision making", Wang (2008) described this model. In
this study, two case studies were solved by Gray Relationship Analysis method and
the resulting answers were compared with the answers obtained from solving these
problems by data envelopment analysis, TOPSIS and the simple total weight
methods. The ranking of options by Gray Relationship Analysis method is more
similar to the results obtained by the TOPSIS and the Simple Harmonic Mean
methods (KUO; YANG; HUANG, 2008).
3. RESEARCH METHODOLOGY
3.1. Type of research
As the subject of this research was related to the present time in terms of time
section and we sought to acquire a better and more comprehensive understanding of
the status quo by gathering data and information about the current situation, the
research methodology could be seen as a surveying one. In terms of objective it was
a descriptive of an applied type. Regarding the research design, it could be
categorized as a post-event research. Since this research was aimed at assessing
the financial performance of the entire cement manufacturing industry companies
listed in the stock exchange using FAHP and TOPSIS methods, then, no hypothesis
was presented.
3.2. Research Methodology
In terms of information gathering method, for the introduction and background
of the research, reliance on library studies and the study of previous research in the
field is studied, and then data collection to determine the coefficients of preferences
of criteria from the pairwise comparison of the hierarchical process of fuzzy
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questionnaire, which is between 20 experts Includes financial professors and stock
brokers and financial experts who downloaded the data from the questionnaire using
online bukletti software, weighted financial ratios and raw data from the cement
producing companies in the stock exchange from the site. Online Stocks
Organization Securities Iraq, Iran Capital Market Information Center, site analysis of
financial data and collecting new RhAVrd software is used.
3.3. Data validity
The validity implies that the measurement tool can measure the examined
attribute and not another attribute. Thus, one of the main goals in designing any test
or questionnaire is its high validity. In this research, due to the use of standard
variables extracted from various articles, the research variables benefited from
content validity.
3.4. Data reliability
In this research, the reliability of questionnaires was measured using the
matrices inconsistency rate. Based on the experience, the inconsistency rate lower
than 0.1 indicates the validity of comparisons; otherwise, the comparisons should be
revised (MEHREGAN, 2014). Reliability also refers to the stability of the research
findings. Thus, a measurement tool is valid if the measurement results of an attribute
by the same tool under the same conditions would be similar to the previous
measurement (ZOHREH; ABBAS, 2005). The inconsistency rates obtained for all the
comparisons in this study were less than 0.1, which indicates the validity of the
questionnaire.
3.5. Target population
The statistical population of this research included all the cement industry
companies listed in in Tehran Stock Exchange, which covered all cement companies
that were active from the beginning of 2013 to the end of 2015.
3.6. Sample community: The method and reason for choosing the sample
community
The sampling methods were not used and we employed a screening model to
select the cement companies. Thus, the companies from the statistical community
with necessary and sufficient information were selected and the rest were excluded.
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3.7. Data Analysis
After collecting data, a new phase of the research process, known as the data
analysis stage, was begun. Certainly, all the issues discussed in the previous section
would matter if the information and data gathered are analyzed accurately and
properly and the results of data analysis are properly interpreted. In this section,
according to the research methodology, the results of the questionnaires, data
analysis, and the paired comparisons of matrices were presented using the Macro
Excel software.
After evaluating the questionnaires completed by the experts (financial
experts and stockholders active in the stock exchange), the consistency rate of the
pairwise comparisons of matrices was calculated, which was lower than 0.1 for each
of the matrices, revealing the consistency of the comparisons. Then, the criteria
evaluated in this research were weighted using the FAHP method and ranked by the
TOPSIS method with the Online Buckley software. The logic principle of this model
defines the ideal positive solution and the ideal negative solution. The ideal solution
(positive) is a solution that increases the profit criterion and reduces the cost
criterion.
The optimal option is the one with the smallest distance from the ideal positive
solution and the farthest distance from the ideal negative solution at the same time.
In other words, in the ranking of options by TOPSIS method, the options with the
highest similarity to the ideal solution will get a higher rank. Figure (1) shows the
research model, while Table 1 provides the weights of main criteria and the sub-
criteria.
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Figure 1: Hierarchical decision making structure using target levels, benchmarks and
options
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Table 1: provides the weights of main criteria and the sub-criteria
Criteria weight
ranking
Weight of sub criteria
sub criteria
weight of
the main
criteria
main criteria
16
021 /0
Current ratio) C
11
(
13 /0
Liquidity ratios
(C1)
8
055 /0
Instantaneous ratio
)C12(
10
047 /0
Cash ratio) C
13
(
9
055 /0
Debt ratio) C21(
239 /0
Leverage ratios
(C2)
5
059 /0
Equity to Total
Assets ratio) C22(
4
065 /0
Fixed asset to Equity
ratio) C23(
11
045 /0
Fixed asset ratio to
long-term debt) C24(
15
031 /0
Inventory ratio) C
31
(
136 /0
Activity ratios (C
3
)
7
059 /0
Total asset turnover
ratio) C32(
14
036 /0
Current asset
turnover ratio) C33(
2
136 /0
Net margin margin
ratio) C41(
324 /0
Profitability ratios
(C4)
1
171 /0
Equity return ratio
)C42(
6
059 /0
Sales growth ratio
)C51(
233 /0
Growth ratios (C
5
)
3
092 /0
Operating profit
growth ratio) C52(
13
037 /0
Equity growth ratio
)C53(
12
043 /0
Asset growth ratio
)C54(
As you can see in Table 1, the weights of the main criteria and the sub-criteria
show that the profit ratios and liquidity ratios with the lowest weights are 0.324 and
0.13, which indicates that the profit ratios The effect of measuring the effect of
cement companies on liquidity ratios has the least effect on the measurement of
cement companies. Among the sub-criteria, the return on shareholders' equity is
related to the profit margin of 0.171 with the highest impact and current trend related
The ratio of liquidity to 0.021 has a lower impact on the measurement of cement
producing companies in the stock exchange.
The results of evaluation of financial performance of cement industry
companies using topsis method are as follows:
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Table 2: production companies ranked one and two and three in 2013
Table 2 shows Sufian Cement, Khash, and Artavirbil production companies
ranked one and two and three in 2013, respectively, indicating that the three
Ranking )2015(
Ranking
)2014(
Ranking
)2013(
Ci
(2015)
Ci
(2014)
Ci
(2013)
Options
20
6
18
0/4465
0/5628
0/4756
Behbahan Cement
29
34
20
0/4221
0/4846
0/4418
Bojnord cement
25
21
9
0/4322
0/5013
0/5392
Darab cement
11
20
15
0/4589
0/5014
0/4983
Dashtestan Cement
14
5
14
0/4545
0/5640
0/5106
Isfahan cement
22
14
24
0/4423
0/5342
0/4343
Ilam Cement
13
18
34
0/4564
0/5184
0/2734
Fars new cement
10
15
32
0/4602
0/5275
0/3418
Fars cement
36
4
35
0/2984
0/5651
0/2702
Qaen Cement
27
25
21
0/4254
0/4980
0/4401
Garb cement
1
24
17
0/5129
0/4991
0/4857
Hegmatan Cement
35
19
7
0/3784
0/5114
0/5464
Hormozgan Cement
15
26
5
0/4534
0/4972
0/5557
shomal cement
24
27
26
0/4384
0/4927
0/4215
khazar cement
34
22
29
0/4096
0/5010
0/3868
Kerman Cement
23
13
2
0/4399
0/5381
0/5892
Khash Cement
33
8
12
0/4109
0/5587
0/5164
Kurdistan Cement
32
33
8
0/4165
0/4847
0/5419
Karoon cement
7
10
11
0/4708
0/5463
0/5259
Mazandaran Cement
21
28
25
0/4445
0/4921
0/4300
Shahrood Cement
6
32
23
0/4754
0/4858
0/43645
Sepahan cement
28
3
6
0/4251
0/5819
0/5494
Sharg cement
26
12
30
0/4276
0/5387
0/3670
Sefid nay riz cement
8
30
1
0/4622
0/4878
0/5911
Sufi cement
16
16
4
0/4493
0/5229
0/5604
Tehran cement
18
29
10
0/4479
0/4914
0/5316
Urmia Cement
9
36
13
0/4612
0/4666
0/5113
Bageran Cemen
2
17
22
0/5127
0/5207
0/4397
Larsabsevar Cement
4
2
31
0/5039
0/5957
0/3575
Larestan cement
12
7
27
0/4566
0/5609
0/4038
Majd Khaf Cement
3
23
33
0/5042
0/4996
0/2846
Momtazan Kerman
cement
19
35
28
0/4478
0/4683
0/3976
Khorramabad Cement
5
11
36
0/4828
0/5456
0/2306
Drood cement
31
1
19
0/4169
0/6361
0/4438
Toseye sarmaye and
sanate ghader cement
30
31
16
0/4188
0/4859
0/4914
Khuzestan Cement
17
9
3
0/4481
0/5563
0/5833
Arta Ardabil Cement
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companies had the highest financial performance in 2013 and had a profitable profit.
have been.
Ghadir, Larestan and East Cement Industries Development Cement
Companies ranked one and two and three in 2014, respectively, indicating that these
three companies had the highest financial performance in 2014 and profitable Have
been huge.
Hegmatan, Larsbevshire, and Momtazan Cement manufacturing companies
ranked one and two dozen in 2015 respectively, indicating that the three companies
had the highest financial performance in 2015 and had high profits. have been.
Figure 2: the financial performance of cement companies
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In Figure 2, the financial performance of cement companies clearly shows in
three years, 2013,2014 and 2015, with three colors of green and blue, respectively.
Table 3: Average 3 years, 2013, 2014 and 2015
Ratings are based on an average of 3 years
)2013،2014،2015(
Average 3 years )2013،2014،2015(
Options
12
0/028924337
Behbahan Cement
28
0/026345903
Bojnord cement
13
0/028826566
Darab cement
16
0/028557922
Dashtestan Cement
7
0/02982368
Isfahan cement
22
0/027491098
Ilam Cement
35
0/024399985
Fars new cement
30
0/025865186
Fars cement
36
0/021710072
Qaen Cement
26
0/026617269
Garb cement
9
0/029384253
Hegmatan Cement
20
0/028035347
Hormozgan Cement
8
0/029533442
shomal cement
27
0/026417124
khazar cement
32
0/025259653
Kerman Cement
2
0/030659472
Khash Cement
11
0/028940578
Kurdistan Cement
18
0/028264922
Karoon cement
5
0/030161007
Mazandaran Cement
25
0/026704673
Shahrood Cement
23
0/027319566
Sepahan cement
4
0/03016777
Sharg cement
29
0/025899616
Sefid nay riz cement
3
0/030272158
Sufi cement
6
0/03000057
Tehran cement
14
0/028827423
Urmia Cement
19
0/028252452
Bageran Cemen
15
0/028826566
Larsabsevar Cement
17
0/028303203
Larestan cement
21
0/027643651
Majd Khaf Cement
33
0/025125855
Momtazan Kerman
cement
31
0/025694373
Khorramabad Cement
34
0/024399985
Drood cement
10
0/028962781
Toseye sarmaye and
sanate ghader cement
24
0/027309951
Khuzestan Cement
1
0/03130981
Arta Ardabil Cement
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Table3 shows the average cement manufacturing companies for the three
consecutive years of 2013, 2014 and 2015, which ranked Artha, Ardebil, Khash and
Sufian companies, respectively.
Figure 3: shows the average cement manufacturing industry
Figure 3 shows the average cement manufacturing industry for the three
consecutive years of 2013, 2014 and 2015.
3.8. Research Findings
As seen in Table (2) and Figure (1), the cement manufacturing companies
listed in Tehran Stock Exchange were ranked using the TOPSIS method with the
following findings:
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Finding 1: Soufian Cement Company, with the closeness ratio of 0.5911, was
ranked the first with simultaneously the minimum distance from the ideal solution and
the farthest distance from the ideal negative solution in 2013. In other words, in the
ranking of options by TOPSIS method, the options with the highest similarity to the
ideal solution will earn a higher rating.
Finding 2: Khash Cement Company, with the closeness ratio of 0.5892, was
ranked the second with simultaneously the minimum distance from the ideal solution
and the farthest distance from the ideal negative solution in 2013.
Finding 3: Arta Ardebil Cement Company, with the closeness ratio of 0.5833,
was ranked the third with simultaneously the minimum distance from the ideal
solution and the farthest distance from the ideal negative solution in 2013.
Finding 4: Ghadir Capital and Industry Development Cement Company, with
the closeness ratio of 0.6361, was ranked the first with simultaneously the minimum
distance from the ideal solution and the farthest distance from the ideal negative
solution in 2014.
Finding 5: Larestan Cement Company, with the closeness ratio of 0.5957, was
ranked the second with simultaneously the minimum distance from the ideal solution
and the farthest distance from the ideal negative solution in 2014.
Finding 6: Shargh (East) Cement Company, with the closeness ratio of
0.5819, was ranked the third with simultaneously the minimum distance from the
ideal solution and the farthest distance from the ideal negative solution in 2014.
Finding 7: Hegmatan Cement Company, with the closeness ratio of 0.5129,
was ranked the first with simultaneously the minimum distance from the ideal
solution and the farthest distance from the ideal negative solution in 2015.
Finding 8: Lar Sabzevar Cement Company, with the closeness ratio of 0.5127, was
ranked the second with simultaneously the minimum distance from the ideal solution
and the farthest distance from the ideal negative solution in 2015.
Finding 9: Momtazan Kerman Cement Company, with the closeness ratio of
0.5042, was ranked the third with simultaneously the minimum distance from the
ideal solution and the farthest distance from the ideal negative solution in 2015.
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Finding 10: Soufian Cement Company, Ghadir Capital and Industry
Development Cement Company, and Hegmatan Cement Company were ranked the
first respectively in 2013, 2014 and 2015.
Table 3 and Figure 2 show the average of three years (2013, 2014 and 2015),
based on which:
Finding 11: Arta Ardebil Cement Company, Khash Cement Company, and
Soufian Cement Company were ranked the first, the second, and the third,
respectively.
4. DISCUSSION & CONCLUSION
Performance measurement and evaluation has drawn the attention of man
from the very past. The aim of performance assessment is to identify weaknesses
and strengths, and consequently modify, improve, and promote the performance.
Nowadays, given the increasing growth and importance of organizations in the
community, the evaluation of the performance of organizations and managers has
come to focus of attention and various indicators have been introduced as the
criteria measurement of the organizations' performance.
Productivity, efficiency, and effectiveness are examples of these assessment
criteria. Performance appraisal is not limited to the individuals' evaluation, but any
system or organization can be evaluated based on their goals to measure their
success rate in achieving those objectives.
In this regard, the assessment of the companies listed in the capital market
(stock market) is of particular importance since it has a crucial impact in guiding the
investors to choose stocks on one hand, and also helping the managers to identify
the current status of the company and taking measures to prevent the crisis as well
as initiatives for productivity growth on the other hand. It is especially essential for
industries such as the cement industry, which is considered among the strategic
industries.
Therefore, sufficient care should be made in choosing the best method from
different methods of evaluating the performance of companies. In this regard, given
the advantages of the TOPSIS method, the cement industry companies were
compared in different years with the same industry companies and ranked by the
proposed model. Unlike other studies, we used the Fuzzy Analytical Hierarchical
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Process Method in this study to reduce uncertainty and ambiguity in this study. We
also employed the TOPSIS approach to rank companies.
In addition, since the weights used were obtained by groups that besides
benefiting from academic knowledge had practical experience in the field of
investment, training of credit and investment providing methods and were also well
familiar with Tehran Stock Exchange environment, the methodology had a relative
validity, which is another feature of this study. The results obtained from this study
were as follows:
Conclusion 1: Three Soufian, Khash, and Arta Ardebil Cement Companies
from three provinces of East Azarbaijan, Sistan and Baluchestan, and Ardebil, which
have different geographical area and climatic conditions, have had the best
performance in 2013. Thus, one can say that they have earned the highest profit in
this year.
Conclusion 2: Three Tehran, Shomal (North), and Shargh (East) Cement
Companies from Tehran Province, which have the same geographical area and
climatic conditions, have had a better performance in the second place in 2013.
Conclusion 3: Three Ghadir Capital and Industry Development, Larestan, and
Shargh (East) Cement Companies from three provinces of Tehran, Fars, and
Tehran, which have different geographical area and climatic conditions, have had the
best performance in 2014. Thus, one can say that they have earned the highest
profit in this year.
Conclusion 4: Three Qaen, Isfahan, and Behbahan Cement Companies from
three provinces of South Khorasan, Isfahan, and Khuzestan, which have different
geographical area and climatic conditions, have had a better performance in the
second place in 2014.
Conclusion 5: Three Hegmatan, Lar Sabzevar, and Momtazan Kerman
Cement Companies from three provinces of Hamedan, South Khorasan, and
Kerman, which have different geographical area and climatic conditions, have had
the best performance in 2015. Thus, one can say that they have earned the highest
profit in this year.
Conclusion 6: Three Larestan, Dorood, and Sepahan Cement Companies
from three provinces of Fars, Lorestan, and Isfahan, which have different
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geographical area and climatic conditions, have had a better performance in the
second place in 2015.
Conclusion 7: Three Fars Nou, Qaen, and Dorood Cement Companies from
three provinces of Shiraz, South Khorasan, and Lorestan, which have different
geographical area and climatic conditions, have had the weakest performance in
2013 and have earned a very little profit in this year.
Conclusion 8: Three Bojnourd, Khorramabad, and Bagheran Cement
Companies from three provinces of North Khorasan, Lorestan, and Isfahan, which
have different geographical area and climatic conditions, have had the weakest
performance in 2014 and have earned a very little profit in this year.
Conclusion 9: Three Kerman, Hormozgan, and Qaen Cement Companies
from three provinces of Kerman, Hormozgan, and South Khorasan, which have
different geographical area and climatic conditions, have had the weakest
performance in 2015 and have earned a very lower profit in this year.
Conclusion 10: Three Behbahan, Ghadir Capital and Industry Development,
and Bojnourd Cement Companies from three provinces of Khuzestan, Tehran, and
North Khorasan, which have different geographical area and climatic conditions,
have had a modest performance in 2013.
Conclusion 11: Three Fars Nou, Hormozgan, and Dashtestan Cement
Companies from three provinces of Shiraz, Hormozgan, and Bushehr, which have
different geographical area and climatic conditions, have had a modest performance
in 2014.
Conclusion 12: Three Urmia, Khorramabad, and Behbahan Cement
Companies from three provinces of West Azarbaijan, Lorestan, and Khuzestan,
which have different geographical area and climatic conditions, have had a modest
performance in 2015.
Conclusion 13: Out of 36 manufacturing companies in the cement industry,
Soufian Cement Company has had the best performance in 2013, 2014, and 2015
with a closeness ratio of 0.036, which has gained the highest most profits and
market share.
5. BASED ON THE RESEARCH LITERATURE AND BACKGROUND
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Conclusion 13: Danesh Shakib and Fazli ranked the cement companies active
in the stock industry using the financial ratios and employing the Analytical Hierarchy
Process and TOPSIS methods in 2009. Based on the results of this research, Fars,
Ardebil and Qaen cement companies obtained the first to third rankings of financial
performance respectively.
In comparison with the current research, in which the financial performance of
the manufacturing companies of the cement industry in Tehran Stock Exchange was
assessed using the FAHP and TOPSIS methods for 3 years of 2013, 2014, and
2015, the average of these 3 years shows that the Arta Ardebil Cement Company,
Khash Cement Company, and Soufian Cement Company have been ranked the first,
the second, and the third, respectively.
Conclusion 15: Rezaei, Saeedi Ramiani, Nazari Shirkoohi and Badizadeh
(2014) ranked the Cement companies active in the stock market using the financial
ratios and utilizing the Integrated Fuzzy Analytical Hierarchical Process and Vikor
method during the two consecutive years of 2008 and 2009.
Based on the results obtained in 2008, the companies of Qaen, Fars and
Khuzestan had the best performance, respectively. In 2009, the companies of
Hormozgan, Ardebil and Qaen had respectively the best performance. As a result,
Arta Ardebil Cement Company has a better financial performance than other
companies in the cement industry.
Conclusion 16: In the proposed approach, the mental judgments of decision
makers in the paired comparison process and financial tables of companies were
used in the performance appraisal. The proposed decision making model was used
to rank the cement industry companies in Tehran Stock Exchange. Through
comparing the results of this research and the conventional rankings provided, the
strengths of this model became clear.
Conclusion 17: One of the important results of this research was the
demonstration of the superiority of the detection power of the combined approach
compared to the non-combined TOPSIS approach (as one of the common ranking
methods). Due to the comparisons made, the use of the conceptual model of this
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research for companies as well as investors will be highly constructive in making
better decisions.
Conclusion 18: The companies at the first rank need to develop a proper
strategy to maintain their position. Meanwhile, weaker corporations have to focus on
lowering their gap with stronger firms and try to improve their position in the ranking.
Conclusion 19: The decision making model of the present research was used
in the ranking of companies according to the financial information. This model can be
used in all decision makings regarding financial and non-financial ranking as well as
in choosing a proper option.
Finally, we suggest to use the proposed method in the later studies for
evaluating other industries. In addition, other financial ratios can be used instead of
the financial ratios utilized here. Future studies can use the proposed model to rank
the top 100 companies (presented by the Industrial Management Organization) and
compare the results with each other.
Also, the ANP and TOPSIS integration method should be used for
prioritization. In addition, with the help of decision makers from all the different
groups active in Tehran Stock Exchange, taking into account each decision maker
based on its importance (weighting decision makers), comparisons can be made and
thus more reliable results. Comparison of this model with accounting methods and
other performance evaluation methods (Prometheus, Electro) is another suggestion
for future research.
Also, in terms of its application, taking into account the results of this
research, it is recommended that companies with inappropriate performance be
offered a solution Appropriate and use of modern scientific and applied methods
improve their position among companies active in this industry and it is suggested to
investors to invest in companies in order to reduce their investment risk in
companies with better performance and performance.
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