Selection of Retail Store in Kingdom of Saudi Arabia Using Analytic Hierarchy Process _ahp

International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online),

Volume 6, Issue 3, March (2015), pp. 08-15 © IAEME

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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.

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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



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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.



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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 the��technical requirement with that of

the��.

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 eigenvalue�� , i.e.

�� =∑ ��,�� , (2)

Where��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):

�. �. = ��

��, (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



12

Step 5: Random Inconsistency Index (R.I.) is then determined for each of the square matrix using

Equation (4):

!. �. = �."#� �$

, (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



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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



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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.

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Selection of Retail Store in Kingdom of Saudi Arabia Using Analytic Hierarchy Process _ahp