Document Type : Research Paper
Authors
1
Ph.D Student of Operational Research, Ferdowsi University of Mashhad
2
Associate Professor, Ferdowsi University of Mashhad
Abstract
Extended Abstract
Tourism system of any location consists of segments, parts and complicated elements which are mutuallyconnected and have network, hierarchy, structure and application in a competitive market. In this regard, Mashhad, as a religious and tourism hub in Iran hosts millions of domestic and international pilgrims to the shrine of Imam Reza annually. Besides visiting its holy shrine, the pilgrims come to this city for medical, recreational and commercial affairs. Mashhad as religious and economic metro police has numerous shopping centers for tourists. The current study has a systematic view toward tourism, and tourists'interest shopping centers. It also aims to study this from a fuzzy c-mean and Genetic algorithm viewpoints which result in 4clusters named traditional, modern, famous and recreational-commercial centers. In order to investigate the significant difference between the two clustering methods, MANNOVA is used in order to show the significant difference between the two methods.
Introduction
In the present era, evolvement and development in various fields of business and tourism have become one of the main elements of trade economy in the world. In this context, regardless of the key goals such as tourism, pilgrimages, educationand meeting with friends and relatives, healthcare and safety objectives, commerce and trade.
Materials and Methods
The study follows a new procedure regarding previous studies, regarding tourism system elements. The survey analyses the main shopping centers as destinations of commercial tourists in the city of Mashhad (see table 1), which is known as biggest religious city of Iran. Regional planned shopping centers are clustered using fuzzy c-mean algorithm. In order to overcome the lack of local minimum in fuzzy c-mean method, the genetic algorithm is employed.
Table (1): the name of the shopping centers
Code
Shopping Center name
code
Shopping Center name
1
Almas-e-shargh
11
Be'sat
2
Khayyam grand mall
12
Markazy mall
3
Kaveh International bazaar
13
Hakim
4
PadidehShandiz
14
Ghadir
5
VesalShopping Center
15
Omid shopping center
6
PromaComplex
16
Alton Tower
7
Village Tourist
17
ZistKhavar Complex
8
Goharshad
18
Kian Center
9
JannatBazar
19
Salman Tower
10
Reza Bazaar
20
17 ShahrivarCommercial Zone
Following our objectives, the data collected are analyzed in the way specified in tourism system elements. In order to analyze the dimensionality of shopping center values we appliedexperts’ comments on each element. This study is mainly based on a questionnaire which was filled by experts about shopping centers. Then the valuesa wereimported to fuzzy c-mean method based on the similarity of centeral points in each cluster. Finally the findings of the two methods are compared with MANOVA method to show the credibility of clustering.
Discussion and Result
Fuzzy c-mean cluster analysis was used to segment shopping centers according to the tourism system attributes (demand, supply and facility). The number of segments was determined by the minimum function value coefficients in fuzzy c-mean method.
The findings showed that 20 shopping centersin Mashhad were clustered into 4 segments. The 4 segments are named according to the main criteria which were collected from experts' comments toward shopping centers in each element. The segments are named traditional, modern, famous and recreational-commercial. The shopping center has a degree of membership to each segment that provides an adequate view for managers to make a plan for tourism development in Mashhad.Tables 2 shows the 4 segments and the degree of membership of the centers.
Table (2): Segments and degree of membership
code
Center name
Segment
code
Center name
Segment
1
2
3
4
1
2
3
4
1
Almas-e-shargh
0/870
0/081
0/042
0/007
11
Besat
0/089
0/070
0/064
0/778
2
KhayyamgratMall
0/771
0/126
0/091
0/012
12
Markazi mall
0/072
0/058
0/862
0/008
3
Kaveh International Bazaar
0/892
0/066
0/036
0/006
13
Hakim
0/086
0/073
0/828
0/012
4
PadidehShandiz
0/054
0/046
0/036
0/864
14
Ghadir
0/069
0/060
0/862
0/008
5
VesalShopping Center
0/670
0/230
0/085
0/015
15
OmidShopping Center
0/199
0/147
0/636
0/019
6
Promacomplex
0/740
0/161
0/085
0/014
16
Alton Tower
0/064
0/899
0/032
0/005
7
Village Tourist
0/215
0/159
0/105
0/520
17
Zistkhavar
0/086
0/857
0/050
0/006
8
Goharshad
0/096
0/076
0/821
0/008
18
Kian Center
0/160
0/769
0/058
0/013
9
JannatBazaar
0/096
0/076
0/821
0/008
19
Salman Tower
0/137
0/799
0/054
0/010
10
Reza Bazaar
0/084
0/076
0/830
0/010
20
17 Shahrivar
0/238
0/300
0/444
0/018
Conclusion
The purpose of this study is to cluster shopping malls regarding tourism system. Regarding the determination of shopping mall important aspects, and using genetic and fuzzy c-mean method, the results revealed 4 segments, namely traditional, modern, famous and recreational-commercial. The findings of the present research have important managerial implications. Giventhe emphasis of Iranian customers on attractiveness of shopping motives and experiencesbesides visiting Imam Reza holy shrine in Mashhad, they make most of their purchases prior to their mall visits and marketing stimulation inside and outside of the shopping centers.Therefore, marketing campaigns should be focused on providing information aboutretailer’s offers and destination attractions. Social and recreational appeals for attracting consumers tothe mall may not work well and merchandise appeals may be more persuasive. Furthermore, consumers in order to staylonger at the shopping centermust be paid attention to. Marketingdirected at these centers should focus both inside and outside of the retail premises.
Keywords: Tourism, Shopping Center, Cluster Analysis, Fuzzy C-Mean, Genetic Algorithm
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Keywords
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