Capella University Designing a Decision-Making Model Paper

Description

Designing a Decision-Making ModelWhen designing a model with a diagrammatic depiction, the designer first considers a process, theory, idea, concept, factors, or combinations of these. In this case, read the course readings for this unit. Consider the multiple types and options of decision-making tools described in the readings. Similar to the Rahmen and de Feis (2009) examples, reflect on a publicized decision from the past two years made by a business with which you are familiar. This can be any decision, major or minor, but must have enough information published that you can make an informed critique of the decision made. (For example, Ford’s 2018 decision to stop building cars, and to focus on SUVs.)For this draft of the paper, review the decision-making tools described in Rahmen and de Feis (2009), Zakeri et al. (2018), and Cabrerizo et al. (2018). Based on the literature’s descriptions of the types of decision making involved, and the tools and processes suggested for use, do the following:Describe the decision made by the business and cite the publicized information about the decision. (These do not have to be scholarly sources, but should be from the past 2 years.) Pick any two decision-making tools from the readings in this unit, explain how they are typically used, and make a case for why these tools would be best for making the decision described in part A.Explain how you could combine those two tools or processes into a better tool or process, which would increase the likelihood of a solid, reasoned, and informed decision. You can eliminate pieces of either tool to fit them together, creating your own unique tool or process.Create a diagram or flowchart depicting the resulting new process or tool. Include a list of all references used. Use at least 4: the three required readings, and one supporting your information about your selected business’s decision.Use APA 6th edition and submit a paper free from errors and of high academic quality. Number your diagram as a Figure, as per APA.You will work on this in the discussions as well.ReferencesCabrerizo, F. J., Chiclana, F., Al-Hmouz, R., Morfez, A., Balamash, A. S., & Herrera-Viedma, E. (2015). Fuzzy decision making and consensus: Challenges. Journal of Intelligent & Fuzzy Systems, 29(3), 1109–1118.Rahman, N., & de Feis, G. L. (2009). Strategic decision-making: Models and methods in the face of complexity and time pressure. Journal of General Management, 35(2), 43–59.Zakeri, S., Yang, Y, & Hashemi, M. (2018). Grey strategies interaction model. Retrieved from https://www.dora.dmu.ac.uk/xmlui/bitstream/handle/…Journal of Strategy and Management
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Grey Strategies Interaction Model
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Journal:
Manuscript ID
Journal of Strategy and Management
JSMA-06-2018-0055.R4
St
Manuscript Type:
SWOT analysis, Strategies interaction model (SIM), Grey systems,
Shannon’s Entropy
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Keywords:
Research Paper
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Page 1 of 24
Grey Strategies Interaction Model
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Abstract
Purpose – This paper aims to implement the strategies selection process in a proposed formulated mathematical framework to prioritize selected
strategies with the interaction of other groups of strategies, known as the strategies interaction model (SIM).
Design/methodology/approach – SWOT analysis is a popular useful strategic planning tool, which analyzes organizations internal and external
factors. The traditional SWOT procedure lists internal and external factors and derives four groups of strategies based on the organization’s
strategic position. SWOT is easy to use as a business analyzing tool, while it is not competent enough for strategic formulation. With the
emergence of the economy’s vicissitudes, undulations in the markets and multiple changes, and various variables in the industrial competitive
environment, selection of the organization strategies confront uncertainty in decision-making. The SIM framework presents a solution to select
alternative strategies for organizations in unpredictable situations.
Findings – The findings show that SIM is a reliable approach to evaluate, select and rank organization’ strategies. SIM proposes alternative
strategies due to the uncertainty of the organization’ environment with respect to the four strategic positions. The SIM’ proposed ranking process
is in accordance with the highest impact of each strategy on each other. Furthermore, it possesses advantages of AHP, ANP and other applied
MCDM techniques in SWOT analysis.
Practical implications – In this paper SIM is applied within a dairy company located in the north of Iran.
Originality/value – SIM has the advantages of the classic SWOT and fills the gaps of MCDM methods application in the SWOT analysis.
Moreover, it provides a formulated algorithm for the organizations to face the uncertainty of the environment. SIM philosophy can be widely
used in the decision and managerial implications.
Keywords: SWOT analysis; Strategies interaction model (SIM); Grey systems; Shannon’s Entropy
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1. Introduction
Strategic planning is a management tool that enables employees to canalize the organization’s targets and helps to identify long-term goals,
current status, and future plans of the organization via identifying root causes of problems at all levels of the entire organization (toklu, et
al.2016). Franham (1999) set out three stages in the strategic management process: strategy formulation, strategy implementation, and strategy
evaluation. As he stated, strategy formulation includes developing a business mission; identifying an organization’s external opportunities and
threats; determining internal strengths and weaknesses; establishing long-term objectives; generating alternative strategies, and choosing
particular strategies to pursue. Strategy formulation also includes ‘deciding what new businesses to enter, what businesses to abandon, how to
appropriate resources, whether to expand operations or diversify, whether to enter international markets, whether to merge or form a joint venture
and how to avoid a hostile takeover’.
The first step of the strategic planning process is to define the organization’s strength and weaknesses as internal factors and the specification of
an organization’s opportunities and environmental threats as the organization’s external factors. For analyzing and identifying internal and
external factors, organizations use the SWOT matrix. By determination of these factors, the developed strategies may be built on the strengths, or
they eliminate the weaknesses, exploit the opportunities, or counter the threats (Wang et al.,2014; Zhang and Feng, 2013; Dyson,2004).
Learned (1969) first described SWOT analysis. SWOT analysis has been grown as a key tool for addressing complex strategic situations by
reducing the quantity of information to improve decision-making. SWOT analysis is one of the most recognized and established strategic
formulation techniques. It has been used in various fields of the current and emerging issues (Syazwan and Bakar, 2014; He and Liao,2012;
Helms et al., 2011; Panagiotou, 2003; Glaister and Falshaw,1999). SWOT analysis can be utilized in a wide range of topics. For instance, Yan et
al. (2015) proposed a national strategic planning framework for land consolidation, with a focus on the clarification of internal strength and
weakness strategies and external opportunity and threat strategies involved in the land consolidation process. In an analytical framework, Fertel et
al. (2013) used SWOT analysis on the themes of energy security, energy efficiency, technology, and innovation.
With defying the organization’s mission and vision, the original SWOT analysis starts with identification of internal factors (strengths and
weaknesses) and external factors (opportunities and threats). The evaluation of the aforementioned factors is performed in the IFE (internal
factors evaluation) and EFE (external factors evaluation) matrices. The evaluation specifies the organization’s strategic position. SWOT matrix
includes four strategic groups. These groups are the result of four combination processes as: strengths and opportunities as aggressive strategies
( -maxi- maxi), strengths and threats as competitive strategies ( -maxi-mini), weaknesses and opportunities as conservative strategies ( maxi-mini), and weaknesses and threats as defensive strategies ( -mini-mini). Aggressive (offensive) strategies represent maximum
exploitation of the synergy effect present between the organization’s strengths and opportunities generated by the environment (Krzysztof, 2007).
Competitive strategies refer to prevailing opportunities in the environment and denote domination of the weaknesses over strengths; this group of
strategies reduces weaknesses with the application of opportunities. Conservative strategies attempt to overcome the threats with utilization of the
opportunities as external factors. The survival arena is in the defensive position. Without any opportunities or strength factors, the package of
these strategies leads organizations to minimize threats and weaknesses. The resultant of IFE and EFE matrices determines organization position
within the above-mentioned four classes. Indeed, in a typical SWOT analysis process, strategic position, and selected strategies of the
organization are inextricably bound together.
Strategy formulation is based on the derived strategic position from SWOT analysis process. As a decision-making stage, the final step of the
original SWOT analysis, the strategies are selected through quantitative strategic planning (QSPM). In fact, the concept of QSPM matrix is based
on the relation matrix, which evaluates and prioritizes the selected strategies through internal and external factors. As discussed earlier, QSPM
only evaluates the selected strategies, while it ignores other groups of strategies, regardless of their importance or environmental uncertainties.
Therefore, the output of QSPM is a crisp answer that only embraces a certain world whereby it technically avoids uncertainty or other strategic
positions.
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Journal of Strategy and Management
Journal of Strategy and Management
In the real world, the impacts of unpredictable conditions on businesses are an integral part of businesses life cycle, where there are many
variables hidden behind factors which seem completely irrelevant to the business, but they are not. In SWOT analysis, the derived strategies from
the typical procedures do not follow the vagueness of an organization’s environment such as market, political, economic and environmental
conditions or social and technical conditions (PEST). In the business, for the strategic decision making of the progress, conservation or survival, a
clear and direct answer is essential. This answer which is built on the internal factors encompasses all environmental factors. Hence, to address
these problems a framework is needed that contains the possible strategic positions, elucidates environmental uncertainties, and offers alternative
strategies. In this paper, we proposed an algorithm called strategies interaction model (SIM); SIM data structure evaluates interactions of
strategies of each strategic position. Moreover, SIM suggests alternative strategies for selection for each organization strategic position. To
eliminate vagueness, subjectivity, and imprecision with the application, we developed a grey form of SIM. With the proposition of SIM, this
paper aims to solve the following problems:
1. Strategic position ignorance in the hybrid methodologies of MCDM and SWOT.
2. Lack of an integrated model for the selection of an organization strategies and also alternative strategies in accordance with the organization
strategic position.
3. In respect of the shared resources for implementation and operation of strategies, there is no framework to assess the interaction of strategies
due to their budget requirement.
4. Lack of a formulated framework to support the assessment of the interaction of possible unselected strategies on the prioritization of the main
selected strategies.
The paper is structured as follows: various SWOT applications, and also the application of MADAM methodologies in SWOT analysis has been
described in section 2. In section 3, the methodologies and concepts which are utilized in the proposed framework have been defined. SIM and its
steps have been demonstrated in section 4. The fifth section is devoted to the case study, and SIM application and results. The results discussion
of SIM and the conclusion of the research have been located in section 6. Finally, future work are exposed in section 7.
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2. Literature review
In this section, we provide a literature review of SWOT applications, then MCDM applications inSWOT analysis have been described. There are
four conventional strategic tools including SWOT analysis, PESTEL (Yüksel, 2012), gap analysis (Brown and Swartz, 1989), and five forces
analysis (Grundy, 2006) used by organizations to conduct analyses and make strategic decisions. Amongst strategic tools, SWOT is the most
popular strategic management tool. As a strategic tool, the concept of SWOT analysis utilized in the various fields of research. The following
table shows the recent application of SWOT in research and studies.
Table 1
Literature review of application of SWOT
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Topic
Author
Year
Environment and
energy
Szulecka
and Zalazar
2017
With an AHP-SWOT analysis combined
method, they found 36 factors that
influence plantation establishment in
rainy forest of Paraguay
Shi
2016
This study used SWOT to review
internal and external factors of green
energy using in Association of Southeast
Asian Nations (ASEAN)
Syazwan &
Bakar
2014
Suh
2014
Çelik et al
2013
Topic
Author
Year
Focus
logistic
Tavana et
al
2016
In a fuzzy environment, with a hybrid
method of Fuzzy AHP and SWOT
analysis, this study evaluated strategic
factor in an outsourcing reverse logistics.
2015
With a comparative analysis of
microbiological quality and safety
aspects, this research compared short
food supply chain and conventional food
supply chain in Belgium through SWOT
analysis.
To identify SWOT in the Halal logistics
environment, this study focused Halal
logistics industry in Malaysia.
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Agriculture and
foods
Focus
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supply chain
and services
With using expert elicitation method,
this study used SWOT analysis for case
of the integrated rice–duck farming in
South Korea, Malaysia and Vietnam.
`
health
Van Durme
et al
Li et al
2016
2011
This research evaluated the feasibility of
adopting cloud computing model in
healthcare by SWOT analysis.
t
With and data collection from literature
review, prefabrication-related
regulations, interviews with experts, and
government reports, this study deal with
SWOT analysis to facilitate a more indepth understanding of the management
of prefabrication housing production
development status in housing
This study proposed a methodoogy for
identification of problematic domains in
the health system for people living with
chronic conditions by SWOT analysis
through thematic analysis of the
transcripts.
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Production
2014
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Kuo et al
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This study deal with SWOT analysis to
find strengths and weaknesses, and
threats and opportunities of the Turkish
fishery sector through a workshop with
the fishery companies.
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Page 3 of 24
production in Hong Kong.
Nagara et
al
2015
This paper applies SWOT (strengths,
weaknesses, opportunities and threats)
analysis to examine the suitability of
virtual water trading, desalination,
groundwater extraction and wastewater
reuse as alternative water solutions to
alleviate water scarcity.
Organization
and
Marketing
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AbdelBasset
2018
David et al
2017
This paper employed an AHP-SWOT
analysis approach in neutrosophic
environment with the case of Starbucks
Company.
This paper discussed about QSPM
application in marketing
Decision making is the important part of the SWOT analysis process which has good capability to integrate and combine with MCDM methods.
In general, MCDM refers to multi-attributes decision-making (MADM) and multi-objective decision making (MODM). Widely, multiple criteria
decision making (MCDM) methods have been employed in SWOT to solve strategic decision-making problem. These studies have transferred
SWOT procedures into MCDM algorithms and made various solution frameworks with the proposed hybrid models. In this section, the
application of TOPSIS , AHP , ANP , VIKOR , Entropy, GRA , DEMATEL , DEA, and the Goal Programming as the most popular MCDM
methods in SWOT analysis have been described. Review of application of the aforementioned techniques is expressed in (Table 2) in the specific
areas.
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Table 2
Review of the literature. Combination of MCDM methodologies with SWOT analysis
Technique
Author(s) & Year
Application & Specific Area
TOPSIS
Azimi, Yazdani-Chamzini, Fouladgar, Zavadskas and Basiri
Ying
Ghorbani, Velayati, Ghorbani
Nejad, Pouyan and Shojaee
Hatami Marbini and Saati
Alptekin
Ozkok and Cebi
SHAMSODDINI and AMIRI
Mohamad, Afandi and Kamis
Forghani and Izadi
Shakerian Dehnavi and Ghanad
Nejatbakhsh and Bahremand
2011
2010
2011
2011
2009
2013
2014
2015
2015
2013
2016
2015
AHP





2000
2004
2010
1995
2011
2011
2007
2012
2007
2013
2008
2012
2009
2009
2011
2013
2014
2010
2012
2013

Forest
Agriculture (South central florida)
Tourism Marketing (Sri Lanka)
Marketing strategies
Examination of sport marketing outsourcing decision-making
Forest economy (China, Yichang City in Hubei Province)
Information systems ( Turkey, e-government
Manufacturing (Turkey)
Medical service (VWL Medical Services)
Supply Chain
E-Government (Turkey)
Marketing ( consumer – Turkish electronics firm)
Maritime (Turkey)
Geographical systems ( implementation of GIS in developing country)
Cattle recording systems (Animal Husbandry in Kenya)
Geoscience (Mining; Iranian dimensional stone mines)
Environmental ( relocation of the firm for air pollution)
Forest
Forest (Agroforestry – Rwanda)
Applied AFS (axiomatic fuzzy set theory) and implemented in the case of
(Yuksel &deviren.2007).

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Yüksel and Dagdeviren
Shahabi, Basiri, Kahag and Zonouzi
Sevkli, Oztekin, Uysal, Torlak, Turkyilmaz and Delen
Azimi, Yazdani-Chamzini, Fouladgar, Zavadskas and Basiri
Wang, Du and Lu
2007
2014
2012
2011
2011
Catron, Stainback, Dwivedi, and Lhotka
Görener
Ostrega, De Felice and Petrillo,
Grošelj, P., & Stirn
Zhao, Yang, Liang, and Gu,
Shojaei, Abbaszade and Aghaei
Heidari, Ashari, Farahbakht and Parvaresh
Hejazi, & Lak
Choi
Rahnamaie, Poorahmad and Ashrafi
Lee
2013
2012
2011
2015
2016
2013
2014
2014
2014
2011
2015
Textile firm
Steel scrap industry strategies
Airline Industry
Mining sector
Environmental (the cumulative effect of pollution in the atmospheric
environment)
Bio energy (Kentucky)
Compared Application of AHP and ANP
Environmental and mining
Environmental management (Slovenia)
Resource (China)
Medical equipment’s industry
Tourism destination (Kish Island)
Medical equipment producer industry
Water Market
Urban management ( Iran, Maraghe)
Location selection for a second tier city in China
Ghorbani, Arabzad and Bahrami
Tang, Atkinson and Zou
Chen
Yuan, Zhang, Wu and Yang
2012
2012
2013
2015
Supply Chain
International marketing (UK consulting company)
Textile Industry
Food and Supply chain

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Entropy
Mining sector
Integrated model for strategic decision making
Financial and economics (prioritization of strategies)
Iran’s stock market
Cosmetics organization
Furniture firm
Shipyard production system
Environmental (rural land )
Local authority in the east coast of Malaysia
Contractor Selection
Human Resource
Iranian dairy Company
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ANP
Kurttila, Pesonen, Kangas and Kajanus.
Shrestha, Alavalapati and Kalmbacher.
Wickramasinghe, V., & Takano, S. E.
Jiansheng
Lee and Walsh
Jiancheng
Kahraman, Demirel and Demirel
Görener, Toker and Uluçay
Osuna and Aranda
Bas
Kahraman, Demirel, Demire l and Ateş
Şeker and Özgürler
Arslan and Turan,
Taleai, Mansourian and Sharifi
Wasike, Magothe, Kahi and Peters
Tahernejad, Khalokakaie and Ataei
Eslamipoor and Sepehriar
Margles, Masozera Rugyerinyange and Kaplin
Stainback, Masozera, Mukuralinda and Dwivedi
Bonzo and Liu
Hybrid
Model
gy
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Journal of Strategy and Management


Journal of Strategy and Management
MA, ZHOU and WANG
2009
Traffic
Ghorbani, Bahrami and Arabzad
2012
Supply Chain
Nikjoo and Saeedpoor
Saeedpoor, Kazzazi, Kashani and Nikjoo
Yang-tian, Wei-zhong, Yi-feng,, Hong-sheng and Center
2014
2012
2013
Insurance industry (Iran)
A combination of Grey theory and DEMATEL
lightning protection and disaster mitigation situation
DEA
ABZARI, BALOUEI, KHAZAEI, and POOR
2013
Governmental
Linear
Programming
Amin, Razmi and Zhang
Ghorbani, Arabzad and Bahrami
2011
2012
Supply chain
Supply Chain


Ghorbani, Bahrami and Arabzad
2012
Supply Chain

DEMATEL
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With evaluation of strategies as the alternative against internal and external factors as the criteria, TOPSIS plays the role of decision-making tool
in SWOT analysis. Due to the hierarchy structure of SWOT, a lot of research have dealt with AHP and ANP in SWOT analysis process (see
Table 2). Integration process of AHP (or ANP) with SWOT analysis in a hierarchy structure is as follows: SWOT factors (Weaknesses,
Strengths, Threats, and Opportunities) as criteria, SWOT sub-factors as the sub-criteria and the strategies as alternatives are placed in descending
order of hierarchy structure (Shahabi et al, 2014). In this process, at first all strategies (ST, SO, WT and WO) are determined in SWOT matrix,
then they prioritize as the output of AHP or ANP process. Like combination of TOPSIS method and SWOT analysis, there is no clear paradigm
for attention to the organization strategic position and the above approaches ignore organization strategic position practically, while it is the first
factor for evaluation of strategies.
For operation and implementation of the selected strategies, organizations have to allocate the resources. Due to the shared resources, strategies
affect each other. Therefore, according to the strategic position of the organization, that strategy which has the highest impact on other strategies
needs more resources than the others do. Hence, as long as SWOT procedure is based on scores and importance of internal and external factors,
the strategy with the highest effect on other strategies must reach the higher rank because the basis of interaction is indirectly according to the
importance. Thus, in one hand, there are algorithms, which rank strategies due to an organization’s internal and external factors and suggest the
selected strategies without consideration of the organization’s strategic position. On the other hand, there is a missing framework for the
calculation of interaction between strategies. As a result of these shortfalls, a comprehensive framework is needed that attends an organization’s
strategic position and also embraces interactions.
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3. Method and Tools
The original SWOT analysis procedure does not offer extra strategies to cover all strategic positions . Extra strategies are the alternatives of the
main output of the decision-making part of SWOT analysis to propose a plan for actions due to other strategic positions. Likewise, the original
SWOT procedure does not support a framework for the assessment of the interaction of possible unselected strategies on the ranking of the main
selected strategies. The nature of SWOT analysis is the decision making for “what strategy is more suitable for the current strategic position?”,
but by integration with MCDM methods, it ignores other strategic positions of the organization. Turning to the description, we proposed the SIM
algorithm. The basis of SIM is the calculation of interaction between each strategy of the strategic positions. The key of SIM is the value of
interaction ( ). In the real world applications and decision-making, the vagueness increases due to inappropriate human judgements and
imprecise information (Çelikbilek and Tüysüz, 2016; Tseng, 2009), and SIM data structure and algorithm basics are based on decision-maker’s
(DM) decisions. As the human judgments, DM(s) decisions face with uncertainty, incomplete information, vagueness, partial ignorance, and nonobtainable information. Thus, to handle uncertainty, all SIM functions deal with the grey numbers and the grey operations. Grey systems theory
was first introduced by Professor Deng (1982; 1985). Grey concepts have been developed to apply in many subjects (Deng. 1989; 1990). Like
fuzzy set theory (Zadeh, 1965), grey systems theory is an effective tool to enable integration of uncertainty and ambiguity into the evaluation
process (Çelikbilek and Tüysüz, 2016).
3.1. Grey Operations
The basic element of grey systems theory is the grey numbers which describe vagueness and uncertain information. The relationship between the
grey number and grey systems theory is analogous with the relationship between a fuzzy number and fuzzy mathematics (Xie and Liu, 2010). The
exact value of a grey (⊗ G) number is unknown, while it lies between two bounds of a numerical interval. Hence, the grey number is defined as a
numerical interval with two known upper and lower bounds as (⊗ G = , ). Such a method supplements the expression of system uncertainties
whenever the probability density and membership functions cannot be fully identified (Memon, et al. 2015). Following equations Eq.(1-10)
address the grey number operations:
If⊗ = , , ⊗ = , then > and > therefore
(1)
gy
−⊗
3)
4)
Grey number subtraction:
Grey number multiplication:
6)

×⊗

/⊗
# ×⊗
= ,
⊗&*
+
+
⊗&*
&* &
= , *
&* &*
= +
,
,

× %& , & ( =
,
)
× ,
The possibility degree of⊗

+
⊗ −⊗ =⊗ + − ⊗
,
+ +
+ +
=% , (
,
+⊗

, max
(2)

= −
,
,
)
= [
,
,
)
,

(3)

(4)
]
)
,

(5)
(6)
)
,

)
, max
(8)
≤⊗
(9)
:
)
,
)
,

)
,

)
]
t
8)
= [
= [# , # ]
Grey number division
(7)
7)

en
5)
= − , −
Grey number addition:
m
2)
1)
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-.⊗
/ =
≤⊗
012 3,4∗ )012 3,&* )&’
4∗
, ℎ7#7 8∗ = 8 ⊗
+ 8 ⊗

(10)
The grey linguistic variables utilized for the rating attributes are: very poor (abbrivated to VP), poor (P), medium Poor (MP), fair (F), medium
good (MG), good (G), and very good (VG), where their corresponding grey values are [0, 1], [1, 3], [3, 4], [4, 5], [5, 6], [6, 9], and [9, 10]
respectively. On the flip side, [0.0, 0.1], [0.1, 0.3], [0.3, 0.4], [0.4, 0.5], [0.5, 0.6], [0.6, 0.9], [0.9, 1.0] are the grey values assigned for the very
low (VL), low (L), moderate low (ML), moderate (M), moderate high (MH), high (H), very high (VH) as the weighting attributes linguistic
variables.
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3.2. Shannon’s Entropy
One of the major results of information theory is the Shannon’s entropy (Laurenza et al.2012; Shannon.2001). This method is using to weight the
criteria. The grey entropy can be found in Eq. (11; 12) in accordance to (Sachdeva et al., 2009; Das et al., 2014) where (7&9: and7&: ) expresses
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entropy of each criteria, and (;&9: and ;&9 ) defines weight of each criteria in an interval.
7&9: = −
9
@D
C
B
@A ln
B
@A
1
?
E
B
@A E
@D
B
@A
of
7& : = −
C
1
?
ln
al
With respect to Eq. (11; 12), computation of weight of GHℎ criterion is as Eq. (13; 14):
J
;&9: = 1 − 7&9: . ? 1 − 7&9: )
AD
C
)
@A N
@A N
)
.
@A
.
B
@A is normalized form of ⊗
A =
@A ,
@A
gy
B
@A = M?
@D
C
B
@A = M?
@D
B
B
A = @A ,
@A
9
11
12
13
14
te
Where ⊗
AD
ra
J
;&9 = 1 − 7&9 . ? 1 − 7&9 )
St
15
16
In another form of equation, let (QA ) be an added value such as DMs decisions, thus the Entropy formula will be as following equations:
Let (QA ) be a crisp number therefore:
J
an
;&9: = QA 1 − 7&9: . ? QA 1 − 7&9: )
AD
J
;&9 = QA 1 − 7&9 . ? QA 1 − 7&9 )
AD
And if (QA = QA , QA ) then
J
;&9: = QA 1 − 7&9: . ? QA 1 − 7&9: )
J
;&9 = QA 1 − 7&9 . ? QA 1 − 7&9 )
Entropy algorithm for the crisp numbers in certain environment is as follow as Eq. (21,22):
@D
J
)
)
22
AD
The normalization process is in accordance to Eq.(23):
C
@D
. [@A
23
en
#A = M? [@A N
21
m
;V9 = W1 − 7V9 X . Y? W1 − 7V9 XZ
e
ag
C
19
20
AD
1
? #@A ln #@A
ln
18
an
AD
7V9 = −
17
dM
3.3. Proposed Grey WPM (WPM-G)
For the ranking procedure, we proposed a transformed methodology which is called (WPM-G). WPM-G steps are in accordance with the
weighted product model (WPM) process (Wang et al., 2010; Triantaphyllou, 2000). The proposed WPM-G equation is as follows (Eq.24) where

B
@A ,
=
@A ,
@A , ⊗
B
= @AB ,
B
@A , and with respect to the value of
B
@A is normalized form of ⊗
A =
@A ,
@A pursuant Eq.(15,16):
B
C , alternatives arrange in their descending order, where ⊗
B
A =
t
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
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22
23
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33
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Journal of Strategy and Management
Journal of Strategy and Management

B
J
C = ]^ @A +
AD
@A _
`9
@A _
W`9 a`9 X
24
If (;A be a grey number then
u
Jo

B
J
C = ]^ @A +
AD
25
Where ;A = ;A , ;A
rn
4. Strategies interaction model
In the real world business, for strategic planning, there is no certain strategic position for an organization. In the external environment, there are
variables that organizations are not capable to control them, such as competition rules, globalization, government policies, technological changes,
natural forces, economic fluctuations, social and cultural forces, and demographic factors. These factors make the unpredictable impacts on the
strategic decision making as well as the strategic decisions. It changes the previously approved strategies of a specific strategic position. For this
reason, organizations have to face with every four strategic positions of SWOT matrix. Thus, in one hand, there is an algorithm, which proposes
plans for actions in a certain strategic position, and on the other hand, there is no certain strategic position for organizations to make plans for
their actions to achieve the long-term goals. Therefore, a comprehensive algorithm is needed to cover all strategic positions. As mentioned in
(Table 2) TOPSIS, AHP and ANP are the most popular MCDM methods for integration with SWOT to make an algorithm to analyze SWOT for
prioritization and selection of the best strategies, whereas these techniques do not consider organizations strategic positions. The core of SIM is to
offer alternative strategies for each strategic position. Furthermore, SIM ranks strategies according to their interactions.
The workflow of SIM methodology procedure has been illustrated in Fig.1 to solve the mentioned problems (see introduction section). In the
proposed procedure, there are two main areas: the evaluation, and the selection. The evaluation and all computation activities will be progressed
in the evaluation area and the results will be processed in the selection area.
al
of
ra
St
Evaluation
Selection
Analysis of
Internal
Factors
gy
te
Analysis of
External
Factors
Construction of
SWOT matrix
Start
End
Selection of
the Alternative
Strategies
Evaluation of
the alternative
strategies
Fig 1. The Proposed methodology procedure workflow of SIM
en
m
e
ag
Ranking of the
Selected
Strategies
Selection
of the
Strategies
an
Computation of
VI
Selection of the
Strategies (All
strategic positions)
dM
Determination of
Strategic Position
an
The procedure includes five phases as they are mentioned below respectively. The first two phases follow the same algorithm that SWOT
analysis does.
Phase I. Analysis of internal and external factors
The analysis process performs in the internal factors evaluation (IFE) and external factors evaluation (EFE) matrices. The strengths and
weaknesses of the organization are listed in the IFE matrix as internal factors. Generally, IF analysis is based on financial statements (sales, cost,
revenue, productivity and etc). Also, the basis of EF analysis is GPESTEL (globalization, political, economic, social, technical, environmental
and legal) indicators analysis.
t
1
2
3
4
5
6
7
8
9
10
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Page 6 of 24
Page 7 of 24
Phase II. Construction of SWOT matrix.
SWOT matrix is constructed on internal and external factors platform. Typically, organization strategies are assessed in the SWOT matrix. As
mentioned, there are four strategic positions. Each position has its original nature and strategies. The derived strategies are the resultant of
external and internal factors.
Phase II.I. Selection of the Strategies (All strategic positions)
In the SWO analysis original process, at first, the algorithm assesses the strategic position, then strategies are determined according to the
strategic position. In this step, regardless of organization’s strategic position all strategies (ST, SO, WT, WO) are determined.
Phase II.II. Determination of strategic position and selection of the strategies in accordance to the strategic position
Strategic position assessment is a formulated process. The intersection of IEEM and IFEM total scores expresses the organization strategic
position.
Phase III. Computation of (VI)
The main core of the proposed framework is the computation of VI. VI is a value extracted from a mathematical algorithm based on entropy that
describes the range of interaction of strategies on each other. VI model has been displayed in the following figure.
rn
u
Jo
al
of
ST Strategies
WT Strategies
SO Strategies
St
Relation Matrix
te
ra
WO Strategies
gy
Fig 2. The Proposed Strategies Interaction Model (SIM)
Phase IV. Ranking of the selected Strategies
With the impact of VI as the coefficient of alternatives, the selected strategies will be prioritized.
Phase V. Evaluation and selection of the alternative strategies
an
5. Real world application and results
In this section, we discuss a real-world application of SIM’ model to consider a project of strategic planning and SWOT analysis the case of a
large-scale dairy enterprise, which has a turnover in excess of 100 million dollars. The employees are more than 1200 , and it is located in the
north of Iran.
5.1. Case study: an overview
With an effective R&D department and innovative approaches to production and processes, also with the supplying of high-quality raw material,
this company produces various groups of products. The mentioned processes must be transferred into a fiscally disciplined platform. In this
company, there is no standard software platform for the integration of business processes and resources (ERP). The company lacks the
businesslike marketing research, branding, and the developed distribution planning that is required for the domestic and export markets
penetration. For the DSR1 (where demand exceeds supply) and attractive dairy markets for exporting of products such as Iraq, Russia, and
Afghanistan, the dairy industry is an attractive opportunity for investment. In recent years, the economic issues, sanctions, and fluctuations in
international political relations have affected domestic legislation, domestic political context, cash flows, and finally on the purchasing power of
the public.
5.2. Data Collection
With a short introduction about the company and its industrial environment, the strengths and weaknesses are provided in (Table 3). The goals of
applying SIM are to select the best strategies and determine the best alternative strategies. The proposed model has been already implemented in
the company as its one of the strategic planning parts (FY2 2017).
Table 3
Synthesis of SWOT analysis
Weaknesses
Opportunities
Threats
S1
High quality products
W1
Market research
O1
Untapped domestic markets
T1
Fluctuations in the economic and
governmental laws
S2
Usage of high quality raw
materials
W2
Branding
O2
Untapped markets for
exportation
T2
Strong competitors (newcomers)
S3
Innovation and variety
W3
ERP Software
O3
orientation of society healthy
products
T3
Fluctuations in international political
relations
Demand to Supply Ratio
Fiscal Year
t
2
Strengths
en
1
m
e
ag
an
dM
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
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Journal of Strategy and Management
Journal of Strategy and Management
S4
Fiscal discipline (revenues,
expenses and obligations)
S5
Flexible production
W4
Distribution
T4
Fluctuations in the purchasing power
of the people
T5
SUBSTITUTE GOODS
u
Jo
5.3. SIM application and results
5.3.1. Analysis of internal and external factors
To evaluate internal and external factors and also for calculating the score (weighted rank), there is a typical formula which is based on the
multiplication of importance with the weight and rank. In this paper, a developed form of Delphi panel has been utilized for evaluation of internal
and external factors.
5.3.1.1. Delphi panel and analysis
The objective of the Delphi group in this study is the achievement of a consensus based on the discussion among experts (Párraga, et al. 2014).
According to the selection process, the expert panel has been composed into the theoretical and practical experts, where the theoretical experts are
the company consultants (consultants of economic and finance, strategic and systems, and marketing and sales) and executive vice presidents of
(strategy and HR); Experts on practical matters are executive vice presidents (production and QC), (sales and operations), (production groups and
marketing) and (finance, IT and investment). The numerical scale of the questionnaire is portrayed in Fig.3.
rn
al
of
2
1
1.5
3
4
Very Low
7
6
5
8
9
3.5
2.5
5.5
4.5
St
6.5
7.5
8.5
Very High
Moderate
Fig 3. Numerical scale of weighting and rating; the scale includes three ranges of very low, moderate high and very high. Other groups of linguistic variables such as
low, moderate low, high and moderate high have not been specified and DM chooses the numbers between very low, moderate and very high as his/her option.
ra
To analyze the obtained data from the questionnaire, this paper proposed a developed Delphi analysis. The proposed method foundation is the
weight of decision makers (WDMs). According to the WDMs, with respect to each group members’ decisions, a special importance weight is
tagged on the groups of theoretical and practical experts. The weights of expert groups are in accordance with the entropy of their decisionmaking. In a numerical space, the proposed algorithm of Delphi computes WDMs using the entropy (Eq.17-19) of decisions. The final results of
the panel have been demonstrated in (Table 4).
gy
te
Table 4
Integration of ( bcdA and ( bcd) of importance weight. ” bcd” has been calculated by sum of simple averages (SA) of each expert group’s decisions.
bcd i
jklmn9
bcd
e
ef
0.0847
0.1497
0.9649
0.1562
0.339
0.1826
0.1025
0.0018
0.1562
0.111
0.670

0.1860
0.1133
0.0083
0.1353
0.111

0.0577
0.1663
0.0069
0.1219
0.088
Practical Experts
f
g
0.1294
0.1025
0.0052
0.0881
0.081
dM
bcd i
bcd i
bcd i
e
0.1839
0.1133
0.0056
0.1353
0.110
Theoretical Experts
an
h
0.0901
0.1497
0.0051
0.1036
0.087
0.0856
0.1025
0.0022
0.1036
0.073
0.330
5.3.2. Construction of the SWOT matrix
This section includes two parts as 1.selection of the strategies through resulatant of the internal and external factors; and 2. Determination of
strategic position and selection of the strategies in accordance to the strategic position.
5.3.2.1. Selection of the Strategies
As mentioned, the derived four strategies groups from SWOT are the resultants of the strengths and opportunities, strengths and threats,
weaknesses and opportunities, and the weaknesses and threats. Thus, regardless of the strategic positions, they have been determined as: 1. The
aggressive strategies (SO group), which are the resultant of strengths and opportunities include the domestic market development ( f ),
export market development ( f ), and the development of healthy and probiotic products ( f h f ) abbreviated to ( , , f )
respectively; 2. in regard to the company’s strengths and environmental threats, as competitive strategies, the competitive price by reducing
product costs ( h g ), and the diversification ( h h ) abbreviated to the ( and ) have been determined as the (ST) group of strategies;
3. To cover the weaknesses with environmental opportunities, the marketing mix development ( g f ), and the increasing number
of the DCs ( g ) which are assigned to the ( , ). These strategies are selected as the conservative strategies, abbreviated as (WO)
group of strategies.; and finally The increasing brand equity ( h ), and the product development by investment on R&D ( g h )
abbreviated as ( , ) have been specified as the defensive strategies in the group of (WT) strategies, where marketing mix is the single
statement of combination of marketing four “P(s)” including product, place, promotion, and price. Moreover, DC denotes a distribution center
and R&D mentions research and development processes.
5.3.2.2. Determination of strategic position and selection of the strategies in accordance to the strategic position
To find what strategy plays the pathfinder role to lead the company policies and resources for the current and future situations, the strategic
position of the company must be determined. There is a classic methodology for calculation of the company strategic position. In the classic
version, the weights of importance multiply in rank and the score specifics the strategic position. While in this paper we introduced ( bcd),
which multiplies in the weights of importance and the results will be multiplied in the rank. The following equations show the mentioned
procedure, where ( ) is the weight of importance and (o klmn×k ) is the normalized number of ( bcdA . ) with respect to the Eq.(19),
bcd is for theoretical and bcd is for practical experts and ( ), ( ) mentioned to the theoretical experts decisions and practical experts
respectively.
t
en
m
e
ag
an
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2
3
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8
9
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17
18
19
20
21
22
23
24
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30
31
32
33
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Page 8 of 24
Page 9 of 24
pq#7 = W^o klmn* .k* + o klmn’ .k’ _ × #r s + #r s X × 4 )
21
Calculation process of scores is shown in (Table 5,6).
u
Jo
Table 5
Scores of internal factors where the weights of importance and rankings are the SA of DMs in each experts group.
Theoretical experts
Practical experts
Rank
bcd

o
bcd

3.75
0.330
8.88
0.118
4.00
0.45
Usage of high quality raw materials
0.670
7.50
0.103
3.00
0.330
8.00
0.107
3.25
0.33
Innovation and variety
0.670
8.25
0.113
4.00
0.330
8.38
0.112
3.75
0.43
Fiscal discipline ((revenues,
expenses and obligations))
0.670
8.63
0.118
3.75
0.330
8.50
0.113
3.25
0.40
Flexible production
0.670
7.25
0.099
3.00
0.330
7.88
0.105
3.25
0.32
Market research
0.670
8.50
0.116
2.00
0.330
8.25
0.110
2.00
0.23
0.670
8.38
0.115
1.75
0.330
8.50
0.113
1.50
0.19
0.670
7.50
0.103
1.00
0.330
7.88
0.105
1.25
0.12
8.63
0.118
2.00
0.330
8.75
0.117
1.75
Total Score
0.22
2.69
Branding
ERP Software
Distribution
St
Weaknesses
score
0.116
of
0.670
o
rank
score
0.670
8.5
0.141
4
0.330
8.625
0.143
4
0.57
Untapped markets for exportation
0.670
8.125
0.135
3.5
0.330
8.25
0.137
3.25
0.46
0.670
6.75
0.112
3
0.330
7.125
0.118
3.25
0.35
Fluctuations in the economic and
governmental laws
0.670
7.625
0.127
1.75
0.330
7.375
0.122
2
0.24
Strong competitors (newcomers)
0.670
7.75
0.129
1.25
0.330
7.875
0.130
1.75
0.19
0.670
8.25
0.137
1
0.330
7.625
0.126
1.5
0.17
0.670
8.625
0.143
2
0.330
8.875
0.147
2
0.29
0.670
4.5
0.075
1
0.330
4.625
0.077
1
0.07
orientation of society to healthy
products
SUBSTITUTE GOODS
dM
Fluctuations in international
political relations
Fluctuations in the purchasing
power of the people
gy
Untapped domestic markets
an
te
ra
Opportunities
rank
8.50
Table 6
Scores of external factors where the weights of importance and rankings are the SA of DMs in each experts group.
Theoretical experts
Practical experts
rank
bcd

o
bcd

Threats
o
0.670
al
Strengths
High quality products
rn
Total Score
2.34
According to Fig.4, the resultant of two total scores of internal and external factors specify the company’s strategic positions.
2.69
1
WO
2.5
SO
an
4
2.5
1
WT
ST
Fig 4. Graphical structure: determination of strategic position.
t
en
2.34
m
e
ag
1
2
3
4
5
6
7
8
9
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Journal of Strategy and Management
Journal of Strategy and Management
As portrayed in Fig.4, strategic position of the company is the ( ). Thus, competitive strategic position must be selected as the result of this
phase. Consequently, two strategies of “competitive price by reducing product costs, and diversification” are the selected strategies.
5.3.3. Computation of VI
As shown in Fig.2, is the value of interaction between two groups of strategies. ( ) structure is built on the entropy concept which describes
how much strategies affect each other. In ( ) mathematical framework, the impact of all groups of strategies on the selected strategies are
investigated due to the strategic position determination. As mentioned earlier, the grey functions are employed to avoid imprecision and
uncertainty of DMs decisions. In this paper, all computations are performed in the grey environment. Following phases show the ( ) calculation
algorithm.
Phase I. Construction of a decision matrix.
First, all groups of strategies are considered as alternatives, and the selected strategies are assumed as criteria. Then, in the next constructed
decision matrix, selected strategies are considered as alternatives and other groups of strategies which includes selected groups of strategies are
considered as criteria. In the decision matrix, decisions are based on DMs assessment about the relation between members of two groups of the
strategies; In fact, the decision matrix is a relation matrix. In this paper, the relation matrices are not the same as the pairwise comparison
matrices and they follow the classical MCDM algorithm. DMs decisions are the linguistic variables which they have been discussed earlier. The
transformation illustration of linguistic variables to grey numerical variables in a relation matrix is as follows in Fig.5.
rn
u
Jo
al
of
Very low
importance relation
0
2
1
Moderate low
importance relation
Moderate high
importance relation
3
5
4
St
Low importance
relation
Very high
importance relation
6
10
9
8
7
High importance
relation
Moderate
importance relation
ra
Fig 5. Numerical scale for relation matrix: linguistic variables and their corresponding numerical variables
Phase II. Normalization of decision matrix with respect to the Eq.(15,16).
Phase III. Computation of Entropy according to the Eq.(11-14).
Phase IV. Computation of weight of each criterion: The weights denote range of interaction of criteria on alternatives.
5.3.3.1. Interaction between strategies
Calculation process of interactions is in the grey environment. As mentioned, a grey number is a numerical interval that includes lower and upper
bounds. In decision-making processes, In other words, DM’s decision is located somewhere between these two bounds. In this paper, there are
eight DMs who provided their decisions as the organizational experts. We proposed a simple approach to select the interval, which supports the
most likely existence probability of the right number that all DMs mention. In the proposed approach, the smallest lower bound and the highest
upper bound of DM’s decisions have been selected. The constructed interval by those two bounds is the basis of the computing process. The
concept of the mentioned interval computation has been portrayed in Fig.6:
gy
te
an
Moderate high
importance relation
0
2
1
3
5
4
Moderate
importance relation
dM
6
7
10
9
8
High importance
relation
Fig 6. Graphical concept of the mentioned interval computation: for instance, let suppose DMs decisions are the intervals of [4,5], [5,6] and [6,9], the right interval for
computation of interaction is [4,9] where the DMs decisions are between the lowest and the highes intervals (red line).
Moreover, the interval can be computed as following equations.
)
J
J
B
=
?
t
.
M?
t
N
@A
@A
@D
@D
J
)
B
B
@A = @A ,
B
@A , ⊗
@A = @A ,
@A and (t) is the number of each upper and lower bound of ⊗
23
@A in the experts decision matrix. In
m
where ⊗
22
e
ag
J
B
B
@A = ? t @A . M? t N
@D
@D
an
this paper, the first approach has been utilized to compute the intervals.
The final step is the calculation of VI. This procedure subtends following phases:
Phase I. Computation of each strategies score
As discussed earlier, each strategy is a resultant of the internal and external factors. According to the (Table 5,6), the scores are the result of the
sum of the strengths, threats, opportunities, and threats in each strategy. Hence, the derived scores are ( : f : 1.45; : f : 1.34;
en
f : f h f : 1.21) as the scores of the (SO) group strategies, ( : h g: 0.71; : h h: 0.58) as the scores of the (ST) group strategies, ( : g
f :2.02; : g : 0.79) as the scores of the (WO) group strategies, and ( : h: 0.62; : g h: 0.78) as the scores of the (WT) group
strategies.
t
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
Page 10 of 24
Phase II. Computation of VI
As desplayed in (Table 7), for compution of ( ), decision matrix needs to be constructed which the derived normalized scores from (phase 1) are
the (QA ) and the numbers in the decision matrix are the set of ( A . Following Eq.(19,20), is the weight of each strategy as the criteria.
Page 11 of 24
Table 7
Computation of

Score
1.34
(QA )
0.1411
u
Jo
1.45
0.1526
0.000
0.187
0.009
0.082
0.389
0.052
0.022
0.017
0.000
0.678
0.496
0.788
f

1.21
0.71
0.1274
0.000
0.896
0.320
0.492
1.000
0.135
0.496
0.129
(QA )
0.0747
0.611
0.052
0.658
0.492
0.877
0.375
0.765
1.000

0.58
2.02
Score
0.955
0.500
0.958
0.968
0.0611
0.123
0.625
0.235
0.000
Score
(QA )
0.2126
0.046
0.500
0.042
0.032
0.009
0.006
0.270
0.009
0.052
0.024
0.024
0.024

0.79
0.62
0.0832
0.991
0.994
0.730
0.991
(QA )
0.0653
0.948
0.976
0.976
0.976
0.893
0.710
0.218
0.880

Score
0.969
0.500
0.948
0.991
0.78
0.0821
0.107
0.290
0.782
0.120
0.031
0.500
0.052
0.009
0.4838
0.5323
0.7291
0.7799
0.8585
0.7694
0.9775
0.9610
0.5062
0.6421
0.9507
0.2677
0.9999
0.9943
0.9769
0.9274
0.4143
0.7689
0.34709
0.21213
0.16847
0.09228
0.07942
0.08730
0.00740
0.00865
0.13296
0.06499
0.04617
0.46268
0.00002
0.00141
0.00665
0.01409
0.21191
0.05638
al
SO
ST
WO
WT
7A
A
rn
5.3.4. Ranking of the selected Strategies
According to (Table 15), with the construction of the decision matrix, ( ) is ranked. In the decision matrix, ( ) of ( , , ) strategies are
the weight of criteria as A and ( @ ) is the weight of alternatives which affects on ranking. In regard to to (Table 15), ( , ,
f , , , , ) are the criteria and ( , ) are as the alternatives. In Accordance with Eq.(25), for the ranking of strategies, grey
WPM has been employed. For an instance, following tables (Table 8,9) show the ranking procedure of ST group strategies. The numbers of
decision matrix are based on experts decisions which are extracted from tables of interactions computation. The weights of ( strategies are not
normalized.
of
St
Table 8
Ranking of strategies with application of @ on the normalized decision matrix (where ( A have been normalized as the weights of criteria) as the weight of
criteria, regarding to the proposed grey WPM formula.
A
0.19434
0.11877
0.09433
0.05167
0.04447
0.04888
0.02585
0.25906
0.00001
0.00079
0.00372
0.00789
0.11865
0.03157
@A

@A
@A
@A
@A
0.500
0.600
0.500
0.500
0.333
0.500
0.400
0.500
0.500
0.667
f
@A

@A
@A
@A

@A
@A X @
= 1,2 , i = 1,2;
1.000
0.667
0.000
0.375
0.143
0.375
6.9963
1
0.000
0.333
1.000
0.625
0.857
0.625
6.9814
2
6.9963
6.9814
Score
Rank
0.112291
1.381968
2
1
AD
24
dM
J
Rank
0.474
As exhibited in (Table 9), the larger value of u@ is expected. In the process, score has been calculated as following equation:
pq#7A = ? W @A +
u@
0.526
u@
0.00865
0.06499
@A
0.455
@A
0.00740
0.13296
@A
0.546
an

@
@A
@A

0.625
Table 9
Ranking of strategies with application of A as the weight of alternatives.
Strategies
@A

0.375
gy

te

ra
5.3.5. Evaluation and selection of the alternative strategies
The basis of alternative strategies selection is the larger value of A in each strategies group. As it is noted before, A is a grey number and
for computation of A , this paper proposed a transferring equation (Eq.27), called the grey importance value ( ). Let us consider ⊗ @ =
@,
@ and (w) is a random variable where (w < @ are Where ( ⊗ @)y ≤⊗ ⊗ ⊗ @ay = W @ + wX , ^ @ + w_ @)y = W @ − wX , ^ @ − w_ @ay ≥⊗ @ ) and (⊗ 25 @) @ + ^ @ + w_X @ + ^ @ + w_ 26 Z −  ‚W @ − wX + W @ − wX + @ + W @ + wXƒ @ + ^ @ − w_ ‡ ‡ „† † † ) 27 en = €   }  } W^ @ − w_ + | |Y |   ^ @ − w_ + {~ { ); m Therefore ( ) is as Eq.(27): ) and (w < e ag Then, The neighbor numbers of ⊗ an ( )s of each strategies in strategies groups of ( , , ) are shown in (Table 10) where (wˆ‰ = 0.01, wkŠ = 0.001 and wk‰ = 0.00001). t 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Journal of Strategy and Management Selection of (ξ) follows a simple order. In the proposed process, the smallest number needs to be chosen between the bounds of each grey number in groups. Then it needs to the number of (1) must be left instead of the last number of the bounds. For instance, following equations ilustrate the selection of (ξ) for strategy group of (WO). Journal of Strategy and Management = [0.04617, 0.46268] 28 = [0.00002, 0.00141] 29 And u Jo The smallest number between four bounds (two lower, and two upper bounds) of the grey numbers is (0.00002) thus according to the selection of (w) instruction it just need to leave number of (1) instead of the last number of the (0.00002). Therefore the (w =0.00001). Table 10 Grey value importance for each strategy Strategies A rn [0.34709, 0.21213] [0.16847, 0.09228] al [0.07942, 0.08730] f A [0.00665, 0.01409] Strategies 359.877 61.449 186.506 [0.21191,0.05638] Strategies 28.974 1710.811 A [0.04617, 0.46268] [0.00002, 0.00141] 10765544 2.334 Therefore, in respect of (Table 10), alternative strategies are ( , , ), where ( = 10765544 > = 2.334), ( =
1710.811 > = 28.974) and ( = 359.877 > f = 186.506 , = 61.449). In addition to ( ) strategies, the company can
implement them as well. The Selection of alternative strategies is in accordance with the larger value of ( )
of
6. Discussion and conclusions
A strategy is a concept that shows how an organization must move from the current position to the next planned position. It is like a canvas,
which organization major goals, policies, and action plans are portrayed on. Strategic planning is a part and parcel of strategy. It is a statistical
conformation a decision-making based tool to define the organization’s mission, goals, strategy, direction, and audience to allocate the resources
due to the strategy (mission and goals). Moreover, strategic planning has been described as a process of strategies selection and definition, an
alignment of strategies and decision making for the resource allocation. For planning of the goals and allocating the resources, typically strategic
planning deals with the STEER analysis (Socio-cultural, Technological, Economic, Ecological, and Regulatory factors), PEST analysis (Political,
Economic, Social, and Technological analysis), PESTEL analysis (Political, Economic, Social, Technological, Environmental and Legal),
EPISTEL analysis (Environment, Political, Informatics, Social, Technological, Economic, and Legal), and the SWOT analysis (Strengths,
Weaknesses, Opportunities, and Threats).
SWOT is one of the most popular business and strategic analysis tools, which widely used to identify the strengths and weaknesses of the
organization as internal factors, and determination of the opportunities and threats of the organization environment as the external factors.
Internal factors indicate strengths and weaknesses of the organization and external factors explain opportunities and threats, which impact the
organization behavior frequently. The strategies are the result of internal and external factors. The derived strategies from the SWOT analysis
process play the role of minimizing threats by focusing on strengths and maximizing possible available advantages via opportunities.
As denoted heretofore, the traditional SWOT process identifies internal and external factors and integrates them into a matrix, then offers four
strategies groups of SO, ST, WO, and WT strategies. however, it is not effective for strategy formulation and planning. In the strategic planning
process, the classic SWOT analysis procedure combines five phases including 1. Identification of internal and external factors, then construction
of IFE and EFE matrices; 2. Making SWOT matrix; 3. SWOT matrix analysis; 4. Construction of quantitative strategic programming matrix
(QSPM matrix); 5. Ranking the identified strategies to propose organization operational strategies. The QSPM matrix evaluates selected
strategies groups (ST, SO, WT or WO) against internal and external factors, while it ignores other groups of possible strategies and does not offer
a framework to choose alternative strategies. Furthermore, it ignores the impact of strategies on each other. In this paper, we aimed to cover the
gap of classic SWOT analysis, and also the ignorance of the organization strategic position in the hybrid MCDM-SWOT methodologies. The
decision-making stage of SWOT analysis is the area where the authors proposed MCDM-based methodologies to select organization strategies.
For the selection of the strategies in the SWOT analysis procedure, this paper presented a proposed model calls strategies interaction model
(SIM). This paper comprehends eight sections including Literature review, method and tools, proposed methodology, data collection, application
and result, discussion and conclusion, and future works. In the paper, we described the SWOT analysis procedure and reviewed the literature on
hybrid model of MCDM-SWOT analysis. Application of TOPSIS, AHP, ANP, Entropy, DEMATEL, DEA and linear programming are
investigated in the literature review section. As discussed in the literature section, there is no paradigm to designate the organization strategic
position in the MCDM-SWOT hybrid frameworks. Moreover, they ignore organization strategic position in the process of the strategiies
selection. To solve the aforementioned gaps, we proposed an interaction model, which is described in the proposed methodology section. The
output of SIM offers alternative strategies for each strategic positions. The ranking procedure is in accordance with the strategies interactions. For
the comparison, the following figures show the strategies selection process of the studied company in AHP method and SIM model.
gy
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Strategies Selection

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Fig 7. AHP structure: the case study strategies selection procedure
Strategies Selection

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of

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te
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`

f
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ST
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WT

Fig 8. SIM structure: the case study strategies selection procedure

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St
As exposed in (Fig 7), with only proposition of the strategies ranking process and without consideration of the strategic positions, AHP selects
strategies in accordance to the internal and external factors, while after determination of strategic positions, SIM procedure selects strategies
based on the interaction of strategies (see Fig 8).
Strategic planning starts with the determination of the strategic positions and SIM is a useful tool for the strategic planning projects. SIM is
proposed in two areas of evaluation and selection (see Fig 1). The section of evaluation contains following steps: analysis of internal factors and
analysis of external factors (simultaneously), construction of SWOT matrix, determination of strategic position, computation of , ranking the
selected strategies and evaluation of the alternative strategies respectively. The selection area includes the selection of the strategies (all strategic
positions), selection of the strategies, and selection of the alternative strategies. SIM is implemented in the grey environment to harness realworld uncertainty. The key tool of the proposed methodology is Shannon’s Entropy that is stated in the method and tools section. In addition, we
proposed a grey form of the weighted product model, which is called GWPM (see Eq. 24,25).
In this paper, SIM has been applied in a case of dairy company. The company is a large-scale enterprise, which has a turnover in excess of 100
million dollars. The employees are more than 1200 , and it is located in the north of Iran. Internal and external factors of the company provided in
(Table 3). With respect to the company’s SWOT, “domestic market development, export market development, development of healthy and
probiotic products” are selected as SO strategies, “competitive price by reducing product costs, diversification”, “marketing mix development,
increasing number of DCs”, and “increasing brand equity, product development by investment on R&D” have been extracted as ST, WO, and
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Journal of Strategy and Management
Journal of Strategy and Management
WT strategies respectively. As illustrated in (Fig 4), the competitive strategic position with ST strategies has been selected as the result of
strategic position determination. The main core of the SIM is the value of interaction ( ). is a mathematical Entropy-based approach that
describes the interaction range of strategies on each other (See Fig 2).
This paper proposed a developed form of Delphi panel as the base of group decision-making process for analysis of the obtained data from the
questionnaire of the SIM. The panel includes the theoretical expert’s category containing consultants (consultants of economic & finance,
strategic & systems, and marketing & sales) and executive vice presidents of (strategy and HR). Moreover, the executive vice presidents
(production and QC), (sales and operations), (production groups and marketing) and (finance, IT and investment) have been hired as the expert of
the practical matters. Also, the proposed math-based process uses a numerical scales of the questionnaires (see Fig 3). As shown in (Table 4),
The procedure of the developed expert panel is in accordance with the weight of each DM. The proposed method deals with VI. It expresses how
much strategies affect each other. In pursuant to the ranking of the selected strategies, increasing “brand equity” stands up the first place and “the
product development by investment in R&D” is in the second priority. Furthermore, marketing mix development and domestic market
development are selected as the alternative strategies.
This paper attempts to solve the following problems: 1. Strategic position ignorance in combined methodologies of MCDM and SWOT. 2. Lack
of an integrated model for selecting organization strategies and alternative strategies due to organization strategic position. 3. In respect of shared
resource of implementation and operation of strategies, lack of the framework to assess the interaction of strategies because of their budget
requirement. 4. Lack of formulating a framework for the effective assessment of organization’s unselected possible strategies interaction on the
prioritization pocess of selected strategies. SIM is a developed form of classic SWOT analysis. Like classic SWOT analysis and strategies
selection process, SIM determines company strategic position (see Fig 4). Additionally, with a formulated process, SIM algorithm contains the
selection of the main strategies and the alternative strategies, and also it assess organizations unselected possible strategies interaction on the
ranking of selected strategies (see phase 6.4).
In this paper, we proposed two procedures to compute the numerical intervals of DMs decisions in the calculation process of the interactions (see
rn
u
Jo
al
of
St
Fig 6 and Eq. 22, 23). As portrayed in (Fig 6), the numerical interval of (⊗
@A = @A ,
@A ) is calculated in accordance with the lowest value of
the lower bounds and the highest value of the upper bounds in the decision making process as the ( @A ) and ( @A ) respectively. In addition, two
ra
equations of (Eq 22,23) are presented for calculation of the mentioned interval. Furthermore, to compare between two grey numbers, this paper
introduced an equation (see Eq 27), called grey importance value (GIV). Xie and Liu (2010), Cakır (2013), and Kong (2015) proposed other
equations to compare two grey numbers.
SIM is a reliable approach for the evaluation, selection, and prioritization of the organizations strategies. Traditional SWOT analysis and SIM
follows the same algorithm, while SIM proposes alternative strategies due to the uncertainty of the organization environment based on each four
strategic positions. In addition, SIM offers a ranking process in accordance with the highest impact of each strategy on each other. Furthermore,
SIM possesses advantages of AHP, ANP and other applied MCDM techniques in SWOT analysis. SIM structure is based on the comparison of
impact of each strategy on each other by employing the entropy method to calculate the coefficient of alternative in a standard MCDM problem
structure.
gy
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7. Future Work
The SIM flexible algorithm has a great potential to develop and integrate with MCDM methodologies. The SIM philosophy can be applied in
many decision-making problems such as suppliers evaluation and selection, facility location selection, material selection problems and so on.
Implementation of SIM in the fuzzy environment would be our first proposition for the future work. as it mentioned in the paper, the is proposed
SIM algorithm is based on the grey numbers to handle the uncertainty of organizations environment. Like grey systems theory, fuzzy systems
theory offers solutions for the uncertainty of environment. We also suggest integration of MCDM methods with SIM to rank the alternative
strategies and integration with AHP, ANP, and BWM due to their hierarchy comparison structures. As the coefficient of alternatives,
philosophy can be utilized to make a bridge between two irrelevance decision-making matrices. For instance, in the cases of evaluation and
selection of suppliers, material selection, market segmentation, and market selection in line with the organizations strategies for making a
strategic decision. Moreover, employing policy for computation of the attributes weights in the decision matrix, and using philosophy in
the group decision-making can be considered as an interesting topic for the future research. is a transferring method of grey numbers to the
white numbers. Not only it can be used in grey systems applications, but also we suggest the development of other forms of . In the Delphi
panel, we used weights of decision makers. This policy can be developed in the group decision-making work.
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Figures
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Evaluation
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Analysis of
Internal
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Selection of the
Strategies (All
strategic positions)
Selection
of the
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Construction of
SWOT matrix
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Selection of
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Fig 1. The Proposed methodology procedure workflow of SIM
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Relation Matrix
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Analysis of
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Fig 2. The Proposed Strategies Interaction Model (SIM)
Journal of Strategy and Management
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Fig 3. Numerical scale of weighting and rating; the scale includes three ranges of very low, moderate high and very high. Other groups of linguistic variables such as
low, moderate low, high and moderate high have not been specified and DM chooses the numbers between very low, moderate and very high as his/her option.
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Fig 4. Graphical structure: determination of strategic position.
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importance relation
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Moderate high
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Fig 6. Graphical concept of the mentioned interval computation: for instance, let suppose DMs decisions are the intervals of ሾ4,5ሿ, ሾ5,6ሿ and ሾ6,9ሿ, the right interval for
computation of interaction is ሾ4,9ሿ where the DMs decisions are between the lowest and the highes intervals (red line).
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Strategies Selection
ܵଵ
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ܵଷ
ܵସ
ܵܶଶ
ܵܶଵ
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ܵହ
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ܵܶଷ
ܹଷ
ܹଶ
ܹସ
ܱଵ
ܵܶ଺
ܵܶହ
ܵܶସ
ܱଶ
ܶଵ
ܱଷ
ܶଶ
ܶଷ
ܶହ
ܵܶଽ
଼ܵܶ
ܵܶ଻
ܶସ
of
Fig 7. AHP structure: the case study strategies selection procedure
St
ܵଶ
ܵସ
ܱܵଵ
ܱܵଶ
ܱܵଶ
ܱܵଷ
ܵܶଵ
ܹଷ
ܵܶଶ
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SO
ܱܵଷ
ܹଵ
ܵܶଵ
ܵܶଶ
ST
an
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ܹଶ
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Strategies Selection
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`
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ܹܱଵ
ܹܱଵ
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ܱଶ
ܹܱଶ
ܹܱଶ
ܹܶଵ
ܹܶଵ
ܶଵ
ܱଷ
ܶଵ
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ܹܶଶ
ܹܶଶ
ܶଷ
ܶସ
ܶହ
ܶହ
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ܶସ
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ܶଶ
ܱଵ
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Journal of Strategy and Management
Fig 8. SIM structure: the case study strategies selection procedure
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Tables
Table 1
Literature review of application of SWOT
u
Jo
Topic
Author
Year
Focus
Topic
Author
Year
Focus
Environment and
energy
Szulecka
and Zalazar
2017
With an AHP-SWOT analysis combined
method, they found 36 factors that
influence plantation establishment in
rainy forest of Paraguay
logistic
Tavana et
al
2016
In a fuzzy environment, with a hybrid
method of Fuzzy AHP and SWOT
analysis, this study evaluated strategic
factor in an outsourcing reverse logistics.
2016
This study used SWOT to review
internal and external factors of green
energy using in Association of Southeast
Asian Nations (ASEAN)
supply chain
and services
Verraes et
al
2015
With a comparative analysis of
microbiological quality and safety
aspects, this research compared short
food supply chain and conventional food
supply chain in Belgium through SWOT
analysis.
Van Durme
et al
2014
This study proposed a methodoogy for
identification of problematic domains in
the health system for people living with
chronic conditions by SWOT analysis
through thematic analysis of the
transcripts.
Kuo et al
2011
This research evaluated the feasibility of
adopting cloud computing model in
healthcare by SWOT analysis.
rn
Shi
al
Agriculture and
foods
Syazwan &
Bakar
2014
Suh
2014
Çelik et al
2013
of
To identify SWOT in the Halal logistics
environment, this study focused Halal
logistics industry in Malaysia.
St
With using expert elicitation method,
this study used SWOT analysis for case
of the integrated rice–duck farming in
South Korea, Malaysia and Vietnam.
`
ra
This study deal with SWOT analysis to
find strengths and weaknesses, and
threats and opportunities of the Turkish
fishery sector through a workshop with
the fishery companies.
health
gy
te
Production
With and data collection from literature
review, prefabrication-related
regulations, interviews with experts, and
government reports, this study deal with
SWOT analysis to facilitate a more indepth understanding of the management
of prefabrication housing production
development status in housing
production in Hong Kong.
Nagara et
al
2015
This paper applies SWOT (strengths,
weaknesses, opportunities and threats)
analysis to examine the suitability of
virtual water trading, desalination,
groundwater extraction and wastewater
reuse as alternative water solutions to
alleviate water scarcity.
Organization
and
Marketing
AbdelBasset
2018
David et al
This paper employed an AHP-SWOT
analysis approach in neutrosophic
environment with the case of Starbucks
Company.
e
ag
2016
an
Li et al
dM
an
2017
This paper discussed about QSPM
application in marketing
Table 2
Review of the literature. Combination of MCDM methodologies with SWOT analysis
TOPSIS
Azimi, Yazdani-Chamzini, Fouladgar, Zavadskas and Basiri
Ying
Ghorbani, Velayati, Ghorbani
Nejad, Pouyan and Shojaee
Hatami Marbini and Saati
Alptekin
Ozkok and Cebi
SHAMSODDINI and AMIRI
Mohamad, Afandi and Kamis
Application & Specific Area
2011
2010
2011
2011
2009
2013
2014
2015
2015
Mining sector
Integrated model for strategic decision making
Financial and economics (prioritization of strategies)
Iran’s stock market
Cosmetics organization
Furniture firm
Shipyard production system
Environmental (rural land )
Local authority in the east coast of Malaysia
Hybrid
Model


t
Author(s) & Year
en
Technique
m
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
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57
58
59
60
Journal of Strategy and Management

Journal of Strategy and Management
Forghani and Izadi
Shakerian Dehnavi and Ghanad
Nejatbakhsh and Bahremand
2013
2016
2015
Contractor Selection
Human Resource
Iranian dairy Company


2000
2004
2010
1995
2011
2011
2007
2012
2007
2013
2008
2012
2009
2009
2011
2013
2014
2010
2012
2013
Forest
Agriculture (South central florida)
Tourism Marketing (Sri Lanka)
Marketing strategies
Examination of sport marketing outsourcing decision-making
Forest economy (China, Yichang City in Hubei Province)
Information systems ( Turkey, e-government
Manufacturing (Turkey)
Medical service (VWL Medical Services)
Supply Chain
E-Government (Turkey)
Marketing ( consumer – Turkish electronics firm)
Maritime (Turkey)
Geographical systems ( implementation of GIS in developing country)
Cattle recording systems (Animal Husbandry in Kenya)
Geoscience (Mining; Iranian dimensional stone mines)
Environmental ( relocation of the firm for air pollution)
Forest
Forest (Agroforestry – Rwanda)
Applied AFS (axiomatic fuzzy set theory) and implemented in the case of
(Yuksel &deviren.2007).

u
Jo
AHP
Kurttila, Pesonen, Kangas and Kajanus.
Shrestha, Alavalapati and Kalmbacher.
Wickramasinghe, V., & Takano, S. E.
Jiansheng
Lee and Walsh
Jiancheng
Kahraman, Demirel and Demirel
Görener, Toker and Uluçay
Osuna and Aranda
Bas
Kahraman, Demirel, Demire l and Ateş
Şeker and Özgürler
Arslan and Turan,
Taleai, Mansourian and Sharifi
Wasike, Magothe, Kahi and Peters
Tahernejad, Khalokakaie and Ataei
Eslamipoor and Sepehriar
Margles, Masozera Rugyerinyange and Kaplin
Stainback, Masozera, Mukuralinda and Dwivedi
Bonzo and Liu
rn
al
of
St
ANP
Yüksel and Dagdeviren
Shahabi, Basiri, Kahag and Zonouzi
Sevkli, Oztekin, Uysal, Torlak, Turkyilmaz and Delen
Azimi, Yazdani-Chamzini, Fouladgar, Zavadskas and Basiri
Wang, Du and Lu
2007
2014
2012
2011
2011
Catron, Stainback, Dwivedi, and Lhotka
Görener
Ostrega, De Felice and Petrillo,
Grošelj, P., & Stirn
Zhao, Yang, Liang, and Gu,
Shojaei, Abbaszade and Aghaei
Heidari, Ashari, Farahbakht and Parvaresh
Hejazi, & Lak
Choi
Rahnamaie, Poorahmad and Ashrafi
Lee
2013
2012
2011
2015
2016
2013
2014
2014
2014
2011
2015

Textile firm
Steel scrap industry strategies
Airline Industry
Mining sector
Environmental (the cumulative effect of pollution in the atmospheric
environment)
Bio energy (Kentucky)
Compared Application of AHP and ANP
Environmental and mining
Environmental management (Slovenia)
Resource (China)
Medical equipment’s industry
Tourism destination (Kish Island)
Medical equipment producer industry
Water Market
Urban management ( Iran, Maraghe)
Location selection for a second tier city in China

2012
2012
20…
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