1 HYPERMARKET AND MARKET INTERACTION: APPLICATION OF GRAVITI MODEL AND GEOGRAPHIC INFORMATION SYSTEM (GIS) Jamal Aimi Jamaludin Department of Town and Regional Planning, Built Environment Faculty, Universiti Teknologi Malaysia, Skudai, 2009, E-mail: [email protected]ABSTRACT: Gravity model had been widely used in the area of transportation planning, business and trade, and in allocating public amenities. Beginning from the outstanding Newton Gravitation Law, gravity model had evolved and modified to fit various purposes and applications. However, there are too many types and variant of variables had been use especially various type of distance variables, until viability of gravity model to explain an ongoing phenomena and predict future condition had been put into question and issued by several scholars. For that reason, this research compares accuracy of four gravity model variants using either Euclidean distance or actual distance, each with and without parameter, in predicting market share of each Giant hypermarket in Johor Bahru. The predicted portion then compare with the actual market share and each hypermarket’s customer origin survey data to evaluate accuracy of each gravity model variant. Result shows that, the variant that use Euclidean distance without parameter come out with the most accurate market share explanation. Huff Model generate by using spatial analyst capability in geographical information system then show a bit more and visualize the gravitation surface of each hypermarket, compare to its rivals, and even successfully explain the spatial interaction between each hypermarket and their market. Thus, prove the capability of gravity model to explain existing interaction phenomena and forecast future interaction pattern. BUSINESS PLANNING AND GRAVITY MODEL Urban planning is an attempt to come out with the best idea or series of action required in future to create better urban environment (Harris, 1965 in Samat, 2008). Before making any decision regarding future development, planners must be able to foresee and predict future condition or phenomenon. In order to predict the future, planner must first understand the pattern and reason of ongoing phenomena. For so long, models have been used to explain and help us understand phenomenon (Wheeler, 1993), and used to assist
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HYPERMARKET AND MARKET INTERACTION:
APPLICATION OF GRAVITI MODEL AND
GEOGRAPHIC INFORMATION SYSTEM (GIS)
Jamal Aimi Jamaludin
Department of Town and Regional Planning, Built Environment Faculty, Universiti Teknologi Malaysia, Skudai, 2009, E-mail: [email protected]
ABSTRACT: Gravity model had been widely used in the area of transportation planning, business and trade, and in allocating public amenities. Beginning from the outstanding Newton Gravitation Law, gravity model had evolved and modified to fit various purposes and applications. However, there are too many types and variant of variables had been use especially various type of distance variables, until viability of gravity model to explain an ongoing phenomena and predict future condition had been put into question and issued by several scholars. For that reason, this research compares accuracy of four gravity model variants using either Euclidean distance or actual distance, each with and without parameter, in predicting market share of each Giant hypermarket in Johor Bahru. The predicted portion then compare with the actual market share and each hypermarket’s customer origin survey data to evaluate accuracy of each gravity model variant. Result shows that, the variant that use Euclidean distance without parameter come out with the most accurate market share explanation. Huff Model generate by using spatial analyst capability in geographical information system then show a bit more and visualize the gravitation surface of each hypermarket, compare to its rivals, and even successfully explain the spatial interaction between each hypermarket and their market. Thus, prove the capability of gravity model to explain existing interaction phenomena and forecast future interaction pattern.
BUSINESS PLANNING AND GRAVITY MODEL
Urban planning is an attempt to come out with the best idea or series of action required in future to create better urban environment (Harris, 1965 in Samat, 2008). Before making any decision regarding future development, planners must be able to foresee and predict future condition or phenomenon. In order to predict the future, planner must first understand the pattern and reason of ongoing phenomena. For so long, models have been used to explain and help us understand phenomenon (Wheeler, 1993), and used to assist
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planner predict certain future phenomenon. As the result, planners make better planning decisions. Among of the most used prescriptive and predictive model used in urban planning is the gravity model.
Been widely used for applications in various field such social science, business and facilities allocation (Ediwan, 2006); the gravity model had been undertaken vast evolution and enhancement to adapt and fit its various application needs. This gravity model origin from the Newton Gravitation Law introduced by Sir Isaac Newton in 1687 (Katiman, 1988). Isaac says interaction between two entities or objects is coincide by their mass and invert by their distance. This means, bigger entities produce more interaction, while far distance make entities interact less.
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Newton Gravitation Law, 1687, Source: Modified from Katiman, (1988)
Fij represent degree or value of interaction between the i and j entities. Mi is mass for item or entity i. Mj represent the mass of entity j. Dij is distance between i and j, while G is the gravity constant for interaction between i and j.
In 1929 Prof. Reilly revolutionaries the use of Newton Gravitation Law (NGL). He applies the main principals of NGL for economic and business application (Katiman, 1988). For economic purpose, gravity model assume that probability for a consumer to choose a facility, in this case a retail outlet, is parallel to the facility attraction force and invert to distance between the facility and consumer (Reilly, 1929). Later, Reilly’s Retail Gravitation Law was modified and popularize by Converse (1949 in Chasco & Vincens, 1999). He introduced the concept of breaking point and identified the inertia factors that visualize unwillingness of consumer to travel beyond certain distance for shopping purpose (Skogster, 2006).
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Reilly’s Retail Gravitation Law. Source: Modified from Katiman (1988)
B is sale value of a shopping outlet in area a or b. P represent population of area a or b. While D is distance between a shopping outlet with area a and b.
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Converse Gravity Model. Source: Modified from (Ghosh et. a., 1987 in Chasco & Vicens, 1999)
DA is distance of town A to breaking point. DAB is distance between town A and ton B while P is population of town A and town B.
Town BTown A
Breaking Point
Source: Modified from (Ghosh et. a., 1987 in Chasco & Vicens, 1999)
Figure 1 Modification of Reilly’s Retail Gravitation Law and Concept of Breaking
Point by Converse (1949).
However, the Reilly model had been criticize as too dependent on distance factor alone and only considering conmpetiton or interaction of two retail outlets (Eppli dan Shilling, 1996). While in real situation, there are multiple ways interaction between several number of retail outlets with their market within an area. For that reason, Huff upgrade the Reilly and Converse models based on Luce opinion on consumer discrete choice which say that consumer will only choose a facility with most optimal benefit and interest, in comparison to the other alternative facilities within their reach.
In 1963, Huff said that when a consumer had plenty of alternative to go shopping, they probably may chose to stop by several shopping malls rather than just stick to one nearest shopping mall. That mean every shopping mall within consumers’ willingness distance to travel had certain percentage of probability to be visit by consumer. Huff Model use travel time distance and shopping malls’ retail floor area as variables to determine probability of a consumer to shop at certain retail entity. This model also say that market is complex, aggregate and based on spending probability. The Huff Model is the most applied gravity model as it is widely accepted and used in many fields.
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Spatial interaction model by Huff say, bigger shopping outlet has higher chance or probablility to attract more shoppers. While a distant shopping mall had smaller chance to be visited, compare to a nearer shopping mall. This model introduces the use of travel time, rather than distance as its distance variable to improve the Reilly Model and also suggest the use of variable parameter in order to explain different interaction, and different travel purposes. Later Lakshmanan and Hansen used retail floor space to determine attractiveness a a shopping mall compare to its competitors. Thus allowing overlapping of market catchment area and competition or interaction of every shopping malls in an area (Skogster, 2006).
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Huff Model. Source: Modified from Chasco & Vicens (1999)
Pij is probability percentage consumer in i to shop at outlet j. Sj is the attractive level or size of outlet j on consumer in area i while Dij is distance between area i and outlet j. b is parameter of distance base on travel purpose.
Most empirical finding admit that Huff model is capable to predict market share of each retail outlet within acceptable accuracy (Riza, 1994). However, several scholar mention that to make its prediction even more accurate, geo-psycology factors must be taken into account to support the influence of size, population and distance factors. Since Huff model only concern about the influence of outlets size and distance, without counting on physical and consumer psychology factors that related to Consumer Behaviours Theory, in determining consumer shopping area selection, Nakkanishi and Cooper (1974) insert and manipulate several retail store attraction factors such environment, facilities level, image, service level and brand affect inside their graviti model which later known as Multiplicative Competitive Interaction Model (MCI). Later, Okoruwa, Nourse and Terza (1988 in Lee, 2002) add another factors such outlets age, type, economy and consumer social status obtain through survey, to determine interaction between shopping outlets and consumer.
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Multiplicative Competitive Interaction Model (MCI). Source:Modified from Chasco and Vicens, 1999
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MCI, Pij is probability of consumer from zone i to shop at outlet j. Where, Uij represent attraction value of outlet j toward consumer in i, which is defined by a set of the outlet
SSUES REGARDING GRAVITY MODEL PREDICTION VIABILITY
ispite numbers of application and modification made, there are still unresting issues regarding the viability of gravity model prediction or even capability to explain an on
lter (1971 in Pace & Lee, 2003) remarked that size of shopping outlets did not significantly related toward prediction of their total sale value. While, Stanley and Seewal
everal researcher such Nakanishi and Cooper (1974), include various social economic variables that are too subjective and abstract to be valued with hope they may simulate or
IN
attributes or even external factor that attract consumer in i to shop in j. β is parameter of each attribute that represent consumer sensitivity toward that certain outlet attribute k.
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D
going phenomenon. Todes (1981 in Riza, 1994) observed that Huff model used in Chicago was unable to explain travel distribution in Cape Town as there is constraint of Aperthied Law, while Riza (1994) observed the same weakness when he applied gravity model to explain travel trend of people in Kota Bharu. Pace and Lee (2003) in the other hand find out that the uses of parameter in gravity model most of the time resulted in unsatisfactory prediction.
Ko
(1976 in Pace & Lee, 2003) agreed that gravity model capability to explain and predict interaction between a shopping entities with its market is very limited. In contra, Eppli and Shilling (1996) doubted the importance of distance factor in determining outlets attraction level. While, Brown (1989 in Skogster 2006) quoted to agreed that basic gravity model with distance and population variable with parameter will not always performed well whenever applied.
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imitate the real world phenomenon. For that purpose, they required many data, complex calculation and evaluation of abstracts elements in order to determine interaction between a shopping outlets and its market. However, consumer shopping location choice most of the time may not be influence by that entire factor. According to Clarke (1998 in Samat 2008) one of gravity model weaknesess is that it required numerous numbers of households within market catchment area, social economy and travel data. For that reason, it is so difficult to obtain such data, especially in developing contry where availability of those data is limited and unorganized to be used for gravity model application whih need a lot of data (Samat, 2008).
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For all the issues, emerge question whether we can just use simple or basic gravity model that only used size and distance viariables only without including complex social –
odel in explaining and predicting a enomenon regarding urban commercial landuse, this research manipulate spatial
fferent distance variable; Euclidean distance without parameter, Euclidean distance with parameter power of two, actual distance without any parameter, and actual distance with
HYPERMARKET AND MARKET INTERACTION ANALYSIS
In order to deter accuracy level of each four basic gravity model variant, this research use uff Gravity Model, modified to fulfill this research objective (refer to formula 6).
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economy, geo-physical and consumer psychology factors in predicting consumer shopping location. This research will show whether the usage of only distance and entity size factor is adequate or not in helping to explain shopping phenomenon, and predicting consumer behavior in choosing their shopping location. If it is prove that simple or basic gravity model are capable to explain and predict those phenomenons well, then the gravity model may be used as planning support device for planner to produce better development, as precise prediction may help planner to understand future phenomena better and help planner to make ample alternative decisions.
In oder to evaluate capability of basic gravity mphanalysis capability inside geographic information system (GIS) to generate Huff model and visualize gravitation surface of each sampled hypermarkets, compare to its business competitor. Gravitationsurface of each hypermarket show interaction pattern and level of each sample hypermarket with its market and competitors. In order to evaluate viability or precision of the gravity model, output of the model will be compared with each sample hypermarket customer origin data, surveyed in each sampled hypermarket.
This research evaluate prediction precision of four variants of gravity model. Each used di
parameter power of two. For comparing purpose, three Giant hypermarket in Johor Bahru District were selected to be this research entities. Selection of hypermarket from the same franchise aim to reduce the effect of different price, variety of product, facilities, environment, consumer perception and effect of hypermarket promotion factor in influencing interaction level between a shopping entity with its market and competitors.
H
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IHR(%) is probability percentage dwellers in R opt to visit or shop in hypermarket H compare to its competitors. S(H) is the retail floor space area of hypermarket, while S(R) is number of house in market area R. is distance of hypermarket H
).
FFECT OF EUCLIDEAN DISTANCE AND ACTUAL DISTANCE
Table 1.0 Rectification Comparison and Accuracy of Each Gravity Model Variant.
from residential R.
The rectification between surveyed hypermarket customer origin allocation and percentage of customer origin allocation for each sampled hypermarket predict by of each gravity model, will be used to determine prediction accuracy of each variant (refer to formula 7
From tion using 6 and 7 ch found out that in overall, the using of Euclidean distance without parameter produce the most ate predictio h its total average rectify value just 3.395, comp d to the other three distance variant (refer
table 1 and graph 1). Usage of parameter for both Euclidean and actual distance also seem not helping to make prediction for hypermarket and market interaction phenomena
intensive road network, which made the use of Euclidean istance adequate and even more significant than using actual distance. Furthermore, there re only small different or range between Euclidean distance and actual distance travelled
calcula formula , this resear raccu n wit
areto
to be even more accurate.
In addition to that, it is also observed in this research result, by using Euclidean distance, prediction will be even more accurate compared if we use actual distance. Maybe because Johor Bahru has vast anddaby each hypermarket visitor to went to their preferred hypermarket (refer table 2). Another factor that may contribute toward this condition is the high social-economic factor of Johor Bahru citizen which allowed them to have their own vehicle. Thus it is
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even easier for them to travel and since they earn high wages, they are more willing to travel distances just to get preferred daily good at more reasonable prize, without really concerning about their travel cost. Thus the use of Euclidean distance is even more significant to explain this phenomenon.
Graph 1.0 Prediction Accuracy of Each Four Gravity Model Variant.
Table 2.0 Average Distance Travelled by Customer to Reach Giant Skudai, Plentong and Southern City.
Customer Distance Giant Skudai Giant Plentong Giant Southern City
Travelled to Average Euclidean
Distanc ) 4,699 6,691 3,271
e (mAverage Actual Distance
(m) 5,804 417 3,774 8,
Different (m) 1,105 1,726 503
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HUFF MODEL CAPABILITY IN EXPLAINING AND PREDICTING INTERACTION BETWEEN HYPERMARKETS WITH ITS MARKET AND
OMPETITORS C
Table 3.0 Residents’ Shopping Location.
Resident Shopping Location
Preferable Percentage – Based on Survey (%)
Preferable Percentage – Based on Huff Model (%)
Skudai Plentong Skudai Plentong Kg. Melayu Majidee
65 4.55 95.45 35
Taman Daya 20.00 80.00 30 70 Pangsapuri Bukit Saujana
14.29 85.71 33 67
Southern City Plentong Southern City Plentong Bandar Baru Permas Jaya
43.75 56.25 14 86
Taman Desa Harmoni
42.86 57.14 15 85
Taman Johor Jaya 3.70 96.30 8 92 Taman Saujana 27.78 72.22 7 93 Skudai Southern City Skudai Southern City Kampung Pasir 66.67 33.33 80 20 Putih
In overall, Huff Model t e Euclidea nce variable without any para er had ccessfully predict pro of s ion pr by dw t
tial areas or Bahru ( ). After had been applied by using analyst capability in geographic info ation system
patially help to explain and visualize interaction between competing hypermarkets.
onsider interaction between two competing hypermarket that compete on the same
market. This was done because of limitation of surveyed data.
hat us n dista metsu bability hopping locat eferred ellers in eighselected residenspatial
in Joh refer table 3rm (GIS), Huff model also
s
The spatial model generated help to show the more dominant hypermarket compared to its competing hypermarket, clearly referred to its higher probability percentage to be visited by dwellers in certain area within its market range (refer figure 1, 2, and 3). In order to compared survey result with the predicted result, generation of this Huff model onlyc
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Figure 1.0 Dual-way Interaction Between Giant Skudai and Giant Plentong with Their Market Catchment
Figure 2.0 t Southern City and Giant Plentong with Their Market Catchment
Figure 3.0 Dual-way Interaction Between Giant Southern City and Giant Skudai with Their Market Catchment
Dual-way Interaction Between Gian
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From comparison of survey result and the predicted result obtained using Huff Model, prediction related to Taman Daya and Taman Johor’s residents preferable shopping location prove that gravity model are able to predict and explain interaction between a shopping outlet against its competitor and its market in almost accurate manner. For the other six customer origin area surveyed, even though basic gravity model are unable to precisely predict percentage of consumer allocation, the model still able to predict and explain which hypermarket is even more dominant hypermarket comparatively to its competitors. May be this would be the affect of this research not considering other factors such traffic congestion, local customer perception toward each hypermarket, familiarity of customer with each hypermarket, dwellers daily activities routine, promotion and even other excluded competition from other hypermarket, supermarket, shopping mall and local e hfactor, still, the basic gravity redict and explain interaction phenomenon between a hypermarket with its petitors successfully.
Figure 4.0 Resident Probability to Shops at Giant Skudai.
xisting shop ouses in their respective residential area. In spite of the entire excluded model is capable to p
market and com
Since basic gravity model that use Euclidean distance had been prove to fruitfully explain and predict interaction between two hypermarket with their market, this research generate a Huff Model to visualize interaction between three sampled hypermarket and their markets area (refer to figure 4,5 and 6). It is obvious from gravitation surface of each hypermarket generated, Giant Plentong receive largest cake portion or catch biggest market segment compared to Giant Skudai, and While Giant Southern City is the one with smallest market share. Which also visualize how Giant Plentong and Skudai may probably attract more population to their store. However, the income or profit generate by Giant Southern maybe higher than Giant Plentong And Giant Skudai since, the social-economic and income level of residents living within Southern City market share area are higher, as it is located near Johor Bahru City core area.
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Figure 5.0 Resident Probabilities to Shops at Giant Southern City.
Figure 6.0 Resident Probabilities to Shops at Giant Plentong.
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SUMMARY
Base on this research analysis, it is notice that basic gravity model that use Euclidean distance without any parameter variable in average produce the most accurate prediction, with rectify value of only 3.395. In overall, this research analysis prove that prediction by using Huff gravity model are capable and reliable in predicting consumer shopping location and explaining interaction between hypermarket with their market and competitors. Form eight customer origin place, basic gravity model successfully determine each hypermarket that was more preferred by customer in those eight areas, compared to its competing hypermarket.
In conclusion, basic gravity model does reliable in producing ample and accurate prediction and capable to visualize and help explain interaction phenomenon between a hypermarket with its markets and competitors clearly. For the reason, gravity model can be use as planning support device for planners, to plan urban commercial and trad land use. Thus cre ble
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