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
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 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 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 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, 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
·
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.
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 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 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.
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.
Figure
1: Hierarchical decision making structure using target levels, benchmarks and
options
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 (C11) |
13/ 0 |
Liquidity
ratios (C1) |
8 |
055/ 0 |
Instantaneous
ratio (C12) |
||
10 |
047/ 0 |
Cash
ratio (C13) |
||
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 (C31) |
136 /0 |
Activity
ratios (C3) |
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 (C5) |
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:
Table 2: production companies ranked one and two and three in 2013
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 |
Table 2 shows
Sufian Cement, Khash, and Artavirbil production companies ranked one and two
and three in 2013, respectively, indicating that the three 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
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 |
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:
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.
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 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 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
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 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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