Selection of retail store in kingdom of saudi arabia using analytic hierarchy process ahp

1. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online),
Volume 6, Issue 3, March (2015), pp. 08-15 © IAEME
8
SELECTION OF RETAIL STORE IN KINGDOM OF SAUDI
ARABIA USING ANALYTIC HIERARCHY PROCESS
(AHP)
Mwafak M. Shakoor
Industrial Engineering Department, King Khalid University,
Abha, Saudi Arabia
ABSTRACT
Retailing store plays an important role in fulfilling the daily needs of customers/consumers.
Retailing business has grown up in multi fold in last decade because of the fruitful changes
incorporated in the business model. The significant features like easiness and comfort in shopping
under one roof has really played a great role in success of retailing store in western countries,
however the same success has not been accrued in Asian countries wherein cost cutting mind set still
plays a vital role in shopping. This moderate success of the retailing business is owing to the wide
spectrum of selection criteria that customer/consumer is looking for which are meaningfully met by
retail managers in a retail stores.
The aims of the present study is to provide comprehensive criteria that have been used by
customer in making retail selection and to prioritize them using Analytic Hierarchy Process (AHP).
The prioritized criteria will help both customers and retail managers to decide their buying and
selling strategy respectively. A case problem of retail store selection using the prioritized criteria in
Aseer region of Kingdom of Saudi Arabia (KSA) has been illustrated.
Keywords: Analytic hierarchy process (AHP), Customer preference, Organized retailing, Retailing,
Kingdom of Saudi Arabia
INTRODUCTION
On the verge of globalization, traditional retailing has been changed tremendously. More and
more malls, supermarket and retailing chains are seen in major cities across the globe. The changes
in the shopping mode has been possible because of the 24×7×365 hour worldwide shopping and
billing ease enabled by the complex software, revolution in digital technology and development of
fast electronic gadgets that are making the buying and selling process without any hustle and bustle
in the least time possible.
INTERNATIONAL JOURNAL OF MANAGEMENT (IJM)
ISSN 0976-6502 (Print)
ISSN 0976-6510 (Online)
Volume 6, Issue 3, March (2015), pp. 08-15
© IAEME: http://www.iaeme.com/IJM.asp
Journal Impact Factor (2015): 7.9270 (Calculated by GISI)
www.jifactor.com
IJM
© I A E M E

2. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online),
Volume 6, Issue 3, March (2015), pp. 08-15 © IAEME
9
People like hassle free shopping and prefer to spend more on quality buying. However there
is a large section of people who still prefers to wait for the right opportunity to maximize their saving
by opting for discounts and offers. More and more offers from supermarkets lure them to shop at the
malls. Consumers now days prefer their routine requirement through shopping malls thus encourages
mall owners to expand their business in various sections. However, on the other hand, due to
changing taste of the customer, it has become very difficult for the mall owners to keep pace with
them.
Even after offering discount and offers, retail managers are always keeping their fingers
crossed for the turn-over because of the changing preference and habits of their customers. However
they try to consolidate their turn-over positions by offering super duper offers clubbed with customer
loyalty. Retail managers try strategic moves from time to time. Their attempt to keep their customers
happy pays back in maintaining the steady pace of business. Retail managers always look for long
term buyer-seller relationship to avert any business uncertainty arising due to ever changing attitude
of customers.
Looking to the above premises, it has become indispensable for the retail managers to keep
their customers happy by offering right quality of goods, at right cost and right time in right quantity.
Whereas on the other hand, customers need to select right malls in order to optimize their shopping
by getting maximum quality at minimum cost. Thus the present research is aimed for the following
multi-objectives:
1. To provide comprehensive survey of various criteria influencing the selection of retail store.
2. To identify and rank the significant criteria influencing the selection of retail store.
3. To provide AHP based modeling for the selection of retail store.
The present paper provides the decision making model using AHP for the selection of retail
store which has been organized as follows: section 1 deals with the introduction to the present
research. In-depth literature review is presented in section 2, which is followed by the framework for
criteria selection for retail store in section 3. Section 4 deals with the AHP methodology whereas
section 5 illustrates AHP modeling for retail store selection. Section 6 presents the results of the
present research followed by a brief discussion in section 7 and finally the paper ends with
conclusion in section 8.
2. LITERATURE REVIEW
Retailing remains the most important business model for decades. Large business groups
divert their business to retailing because of the huge profit potential. Many researchers have carried
out the research in the area of retailing store site selection to exploit the available business
opportunity in the nearby proximity. Various researchers also employed the AHP methodology in
site selection for retail store for instance; Craig et al. (1984) presented models of the retail location
process. Kuo et al. (2002) employed a decision support system (DSS) for selecting convenience store
location through integration of fuzzy AHP and artificial neural network. Singh and Agarwal (2011)
studied the consumer preference shifting from unorganized retailing to organized retailing in India.
Turhan et al. (2013) carried out literature review on the selection criteria of store location based on
performance measures. Akalin et al. (2013) used the AHP Approach for evaluating location selection
elements for retail store using a case of clothing store. Koç and Burhan(2015) used AHP in a real
world problem of store location selection.
Many researchers studied the process of selecting retailing store by carrying out extensive
study of customer/consumer preferences, store attributes, cost, convenience of shopping etc (Brand
and Leonard, 2001; Ergün, 2013). Liisa (1990) studied the consumer preferences for environmental
quality and other social goals. Mitchell and Kiral (1998) studied the primary and secondary store
loyal customer perceptions of grocery retailers. Arora and Greg (1999) measured the influence of

3. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online),
Volume 6, Issue 3, March (2015), pp. 08-15 © IAEME
10
individual preference structures in group decision making. Philippi is and Hubbard (2003) modeled
hierarchical consumer preferences for the global food markets selection and later on Bianchi (2009)
investigated consumer expectations of convenience store attributes in emerging markets a presented
the case of Chile. Finally, Kim et al. (2012), studied the usefulness of analytic hierarchy process
(AHP) to determinants win-win growth factor for retailing industry in Korea.
3. FRAMEWORK FOR RETAIL STORE CRITERIA SELECTION
Selecting a retail store is an important strategic decision now becoming complex issue because
more and more retail stores are coming up in same or nearby proximity. Selecting a retail store thus
becomes difficult for the customer/consumer. Customer preferring a particular retail store depends
upon a wide choice spectrum. Many criteria like fast checkout, importance of store cleanliness,
convenience of parking, closeness to residence, courteous and friendly employees, availability of
generic products, reputation or brand of retail store, transparency in product related information,
wide selection of national brands, wide selection of ethnic foods, wide selection of store private
labels, low priced advertised specials (discounts),desserts and pastries section, quality of meat cuts,
high quality of fruits and vegetables, quality bakery under single roof, service deli, availability of
health and personal care products, large selection of fruits and vegetables, fresh seafood on display,
electrical equipment availability, availability of household equipments etc.; are considered to be
playing an important role in retail store selection.
Figure 1. Modeling Framework for Retail Shopping using AHP
As shown in Figure 1, 22 criteria were identified from the in-depth literature review. Initial
survey was carried out to identify the most preferable criteria that influence the retail shopping. As a
result, 22 criteria identified from the literature review were reduced to nine. The nine most criteria
preferred are ‘fast checkout, cleanliness of store, convenience of parking, low priced advertised
specials (discounts), high quality fruits and vegetables, quality bakery in the store, service deli, large
selection of fruits and vegetables, and courteous, friendly employees’.
4. ANALYTIC HIERARCHY PROCESS
AHP is a decision-support procedure developed by Saaty (1988) for dealing with complex,
unstructured and multiple-criteria decisions. AHP can be applied in a wide variety of decision areas.
The three basic steps of AHP are:
1. Describing a complex decision-making problem as a hierarchy;
2. Using pair wise comparison techniques in estimating the relative priority of the various
elements on each level of the hierarchy;
3. Integrating these priorities for developing an overall evaluation of decision alternatives.

4. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online),
Volume 6, Issue 3, March (2015), pp. 08-15 © IAEME
11
For assigning the weights to each of the technical criteria as well as to the suppliers’
alternatives in order to construct the decision matrix and pair wise comparison matrices, phrases such
as ‘much more important’ are used to extract the decision maker’s preferences. Saaty (1988)
produced an intensity scale of importance as shown in Table 1.
Table 1.Nine-point scale of pair-wise comparison
Intensity of relative importance Definition
1 Equally preferred
3 Moderately preferred
5 Essentially preferred
7 Very strongly preferred
9 Extremely preferred
2, 4, 6, 8 Intermediate importance between two adjacent judgments
4.1 Traditional AHP models (Saaty, 1988; Winston, 1994) use the following steps:
Step 1: A technical requirement factor comparison matrix ‘D’ is constructed. This is known as a
decision matrix. Each element of the ‘D’ matrix is based on Saaty’s nine-point scale. The element of
the ‘D’ matrix,݀௣௤, compares the level of importance of theܲ௧௛
technical requirement with that of
the‫ݍ‬௧௛
.
Step 2: The geometric means (GM) of each of the rows for both the decision matrix and pairwise
comparison matrices are calculated. The priority vector (PV) values follow the normalization of each
GM value.
Step 3: An overall summation of the product of sum of each vector column for both the decision
matrix and pairwise comparison matrices with the PV values of each row is carried out to obtain the
principal eigenvalueሺߣ௠௔௫ሻ, i.e.
ߣ௠௔௫ = ∑ ‫ܥ‬௝ܸܲ௜
௞
௜,௝ୀଵ , (2)
Where‫ܥ‬௝is the sum of each column vector.
Step 4: The level of inconsistency in both the decision and pairwise comparison matrices is checked
using Equation (3):
‫.ܫ‬ ‫.ܫ‬ =
ఒ೘ೌೣିே
ேିଵ
, (3)
Where I.I. is the Inconsistency Index, and N is the number of elements in each matrix.
( )
11 12 1
21 22 2
1 2
D 1
k
k
k k kk
d d d
d d d
d d d
 
 
 =
 
 
 
K
K
M M O M
K

5. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online),
Volume 6, Issue 3, March (2015), pp. 08-15 © IAEME
12
Step 5: Random Inconsistency Index (R.I.) is then determined for each of the square matrix using
Equation (4):
ܴ. ‫.ܫ‬ =
ଵ.ଽ଼ሺேିଶሻ
ே
, (4)
Step 6: The Inconsistency Ratios (I.R.) for each of the square matrices are obtained dividing I.I
values by R.I. values. Further revision in the elements of the matrices is necessary if I.R.>10%.
Step 7: Pairwise comparison matrices for each supplier’s alternatives are
constructed. Table 1 is used to assign weight to these matrices. The principal eigen values (PI) I.I.
and I.R. are then computed using the same logic as in steps 2–6.
5 ANALYTIC HIERARCH PROCESS MODELING A RETAIL STORE SELECTION
A case study was undertaken for the selection of retailing store in Aseer region, Kingdom of
Saudi Arabia (KSA). Questionnaire using Saaty’s scale was administered to 350
customers/consumer preferring retail shopping to identify the most preferred criteria of their choice.
Later on these most preferred criteria were used in another questionnaire to identify the best malls
amongst the A1, A2 and A3 (Disguised malls).
Table 2. Comparison of 22 Criteria using AHP Methodology
Group
Code
Sr. No. Criteria Final
Weightage
M1
1 Fast checkout 0.053075
2 Cleanliness of store is important for me. 0.054922
3 Convenience of parking 0.052604
4 Close to where you live 0.04325
5 Courteous, friendly employees 0.05056
6 Offers generic products 0.044861
7 The reputation of retail store 0.043211
8 Provides nutritional information about products 0.043604
9 Wide selection of national brands 0.042661
M2
10 Wide selection of ethnic foods 0.033504
11 Wide selection of store private labels 0.035822
12 Low priced advertised specials (Discounts) 0.049695
M3
13 Quality of meat cuts 0.045844
14 High quality fruits and vegetables 0.05449
15 Has quality bakery in the store 0.049931
M4
16 Desserts and pastries section 0.04215
17 A service deli 0.046944
18 A variety of health and personal care products 0.045805
19 Large selection of fruits and vegetables 0.050914
20 Sells fresh seafood 0.039242
21 Offers electrical equipment 0.037552
22 Offers household equipment 0.039359
( , 1,2, , )iA i n= K

6. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online),
Volume 6, Issue 3, March (2015), pp. 08-15 © IAEME
13
Legend: M1: Shopping comforts, M2: Friendly environment shopping, M3: Cost & quality
parameters and M4: Facilities under single roof
Table 3: Prioritization of Criteria using General Weightage Calculation
Sr.
No.
Code
Criteria
General
Weight Rank
1 S1 Fast checkout 0.1228 3
2 S2 Cleanliness of store is important for me. 0.3614 1
3 S3 Convenience of parking 0.0597 5
5 S4 Courteous, friendly employees 0.0203 8
12 S5 Low priced advertised specials (Discounts) 0.1176 4
15 S6 High quality fruits and vegetables 0.2368 2
16 S7 Has quality bakery in the store 0.0261 7
17 S8 A service deli 0.0054 9
19 S9 Large selection of fruits and vegetables 0.0494 6
22 Criteria were classified under four sub-headings as M1, M2, M3, and M4. Table 2 indicates
the 22 criteria and its respective weightage obtained through questionnaire survey whereas Table 3
shows prioritization of criteria using general weightage calculation. Table 4 indicates the
comparison of four groups to decide their customer preference whereas Table 5 indicates the
comparison of various alternatives A1, A2 and A3 based on the prioritized alternatives. Finally Table
6 indicates the weightage of various alternatives for the selection of retailing store.
Table 4: Mean Weight Calculation of Criteria
M1 M2 M3 M4 Geometric Mean Weightage
M1 1 5 3 7 3.201086 0.564423
M2 0.2 1 0.33 3 0.667062 0.117618
M3 0.33 3 1 5 1.491596 0.263002
M4 0.14 0.33 0.2 1 0.311688 0.054958
Legend: M1: shopping comforts, M2: friendly environment shopping, M3: cost & quality
parameters and M4: facilities under single roof
Table 5: Comparison of Various Alternatives based on Prioritized Criteria
Sr.No. Criteria A1 A2 A3 C.R.
1 Fast checkout 0.0968 0.7009 0.2021 0.13
2 Cleanliness of store 0.3333 0.3333 0.3333 0
3 Convenience of parking 0.4738 0.4738 0.0522 0
4 Courteous, Friendly employees 0.2961 0.61819 0.0857 0.13
5 Low priced advertised specials
(Discounts)
0.3079 0.6428 0.0491 0.12
6 High quality fruits and
vegetables
0.6497 0.2782 0.0720 0.06
7 Has quality bakery in the store 0.6008 0.1995 0.1995 0
8 A service deli 0.4289 0.4289 0.1420 0
9 Large selection of fruits and
vegetables
0.2577 0.6377 0.1045 0.03

7. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online),
Volume 6, Issue 3, March (2015), pp. 08-15 © IAEME
14
Table 6: Weightage of Various Alternative Retailing Store
Alternatives
M1 M2 M3 M4
Weightage
S1 S2 S3 S4 S5 S6 S7 S8 S9
A 1 0.1562 0.3333 0.4738 0.4055 0.4738 0.4545 0.3333 0.3333 0.25773 0.3547
A 2 0.6590 0.3333 0.4738 0.4808 0.4738 0.4545 0.3333 0.3333 0.63776 0.4700
A 3 0.1846 0.3333 0.0523 0.1136 0.052 0.0909 0.3333 0.3333 0.10451 0.1752
6 RESULTS
This research has accumulated 22 criteria for the retail selection. Out of the initial 22 criteria,
nine criteria were shortlisted through questionnaire survey based on AHP scale. The final ranking of
nine criteria is derived as follows:
S2>S6>S1>S5>S3>S9>S7>S4>S8
Wherein ‘>’ means preferred.
Pairwise comparison was also carried out among three potential alternatives A1, A2and A3.
Relationship among the three given alternative is derived as A2> A1>A3, where ‘>’ means preferred.
Thus relationship indicates that retail ‘A2’is preferred over retail ‘A1 and A3’.
7 DISCUSSION
The results obtained in the present research indicates that criteria of ‘Cleanliness of store is
important for customer/consumer’. This criteria is preferred over the other criteria like ‘High quality
fruits and vegetables’, ‘Fast checkout’, ‘Low priced advertised specials (Discounts)’, ‘Convenience
of parking’, ‘Large selection of fruits and vegetables’, ‘Has quality bakery in the store’, ‘Courteous,
friendly employees’ and ‘A service deli’. The ranking of criteria would help customers/consumers to
decide the best retail store suiting to their requirement. On the other hand it will also help retail
managers to know which criteria their customers/consumers prefer in selecting a retail store. Thus
retail managers can deploy the available resources more meaningfully and optimizes the profit.
8 CONCLUSION
The present research provides AHP based decision making model for the selection of retail
store. Selection of retail store is a significant issue influences the survival and growth of a retail store
in particular and retail business as a whole. This model provide win-win situation for the
customers/consumers and retail managers. Customers/consumers may fulfill their need with great
customer satisfaction whereas retail managers will find their business rolling.
REFERENCES
1. Craig C., et al. (1984), “Models of the retail location process: A review”, Journal of Retailing,
Vol. 60, No.1, pp.5-36.
2. Kuo R. J., et al. (2002), “A decision support system for selecting convenience store location
through integration of fuzzy AHP and artificial neural network”, Computers in Industry,
Vol.47, pp.199-214.
3. Singh A.K. and AgarwalP.K. (2011), “Study on Shifting Consumer Preferences from
Unorganized Retailing to Organized Retailing in Noida”, International Journal of Accounts,
Economics & Business Management, Vol. 1, No.2,pp.69

8. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online),
Volume 6, Issue 3, March (2015), pp. 08-15 © IAEME
15
4. Turhan G., et al. (2013), “Literature Review on Selection Criteria of Store Location Based on
Performance Measures”, Procedia - Social and Behavioral Sciences,Vol. 99, pp.391 – 402
5. Akalin M., et al. (2013),“The Application of AHP Approach for Evaluating Location
Selection Elements for Retail Store: A Case of Clothing Store”, International Journal of
Research in Business and Social Science, Vol. 2, No 4.
6. Koç E. and Burhan H. (2015), “An Application of Analytic Hierarchy Process (AHP) in a
Real World Problem of Store Location Selection”, Advances in Management & Applied
Economics, Vol. 5, No.1, pp.41-50.
7. Brand M.H. and Leonard R.L. (2001), “Consumer Product and Service Preferences Related to
Landscape Retailing”, HortScience, Vol.36, No.6, pp.1111-1116.
8. ErgünE. (2013),“Factors affecting consumer preferences for retail industry and retailer
selection using analytic hierarchy process”, Kafkas University Journal of Economics and
Administrative, Sciences Faculty, Vol. 4, No.6, pp. 43-57.
9. LiisaU. (1990), “Consumer preferences for environmental quality and other social goals”,
Journal of Consumer Policy, Vol.13, No.3, pp.231.
10. Mitchell V.W. and Kiral R.H.(1998), “Primary and secondary store loyal customer
perceptions of grocery retailers”, British Food Journal, Vol.100, No.7, pp.312-319.
11. Arora N. and Greg M.A. (1999), “Measuring the influence of individual preference structures
in group decision making”, Journal of Marketing Research, Vol.36, pp:476-487.
12. Philippidis G. and Hubbard L.J. (2003), “Modeling hierarchical consumer preferences: An
application to global food markets”, Applied Economics, Vol. 35, pp. 1679-1687.
13. Bianchi C. (2009), “Investigating Consumer Expectations of Convenience Store Attributes in
Emerging Markets: Evidence in Chile”, Journal of International Consumer Marketing,
Vol.21, No.4, pp.178.
14. Kim W., et al. (2012), “Usefulness of analytic hierarchy process (AHP) to determinants win-
win growth factor for retailing industry in Korea”, African Journal of Business Management,
Vol.6, No.14, pp. 4824-4834.
15. Saaty T. L. (1988), “The Analytic Hierarchy Process: Planning, Priority Setting, Resource
Allocation”, (RWS Publications: Pittsburgh, PA).
16. Winston W. L. (1994), “The analytic hierarchy process in Operations Research: Applications
and Algorithms”, edited by B. Wadsworth, pp. 798–806, (Duxbury Press: Belmont,CA).
17. Dr. Bidyut jyoti gogoi, “Antecedents of Customer Satisfaction In A Retail Store Environment
and Its Impact on Time Spent and Impulse Buying” International Journal of Management
(IJM), Volume 4, Issue 1, 2013, pp. 157 - 162, ISSN Print: 0976-6502, ISSN Online: 0976-
6510.
18. M. Mohamed Riaz and Dr. D. Mahesh, “A Study on Customer Preference towards Accord
Advertising Agencies, Chennai” International Journal of Management (IJM), Volume 6, Issue
1, 2015, pp. 19 - 26, ISSN Print: 0976-6502, ISSN Online: 0976-6510.