A GIS approach to shopping mall location selection

Cheng, Eddie W.L.; Li, Heng; Yu, Lei

doi:10.1016/j.buildenv.2005.10.010

Cited by 103 publications

(57 citation statements)

References 28 publications

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“…Due to modernization, the shopping habits have changed from small independent stores or discount stores to large regional shopping malls. In this modern era, people have more positive views towards large shopping malls, due to the fact that people find buying in shopping malls as a unique process that leads to rise of attractiveness of shopping malls [1]. Finn and Louviere, demonstrated that people have negative perceptions toward the quality of goods and services in discount stores [2].…”

Section: Introductionmentioning

confidence: 99%

“…The crucial importance of selecting the most suitable location is often undervalued, whereas this manner affects marketing and financial strategy of retailers who will be active in the shopping malls [1,5]. To retailing businessmen, how to attract customers and catch the opportunities of marketplace development are the two most noticeable issues in practice.…”

Section: Introductionmentioning

confidence: 99%

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Selecting Shopping Center Site Using MADM Techniques

2017

LHHSS-17, ICEELB-17, Jan. 1-2, 2017 Dubai (UAE)

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Abstract-Shopping malls are one of the glories of metropolises with their attractive shops and a wide variety people who are walking in order to purchase goods. Location selection decision making of these shopping malls is considered as a strategic decision, due to its noticeable impact on shopping malls profitability. Selection of an appropriate site requires consideration of multiple alternatives and assessment of attributes. Old solutions lack the ability to deal with linguistics variables (qualitative), on account of theirs ambiguity and imprecision. The aim of this paper is to integrate numbers of conflicting qualitative and quantitative variables for evaluating alternatives. Tehran is considered as a real example. Methodologically, Shannon Entropy is applied for assigning weights of each attribute. TOPSIS and VIKOR are utilized for ranking alternatives by computed weights. This model rectifies the deficits of old solutions with providing the grounds of decision making under uncertainty.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Selecting Shopping Center Site Using MADM Techniques

2017

LHHSS-17, ICEELB-17, Jan. 1-2, 2017 Dubai (UAE)

View full text Add to dashboard Cite

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“…To decide where to locate a new outlet, a retail firm needs a strategy (Li, Liu 2012). Cheng et al (2007) argue that geographic information systems (GIS), which rely on detailed digital maps and databases, will become essential tools for retail businesses to develop decision systems and select locations for new outlets. According to Clarke (1998), the use of GIS in retail location theory has become more widespread because of the importance of geodemographic characteristics.…”

Section: Introductionmentioning

confidence: 99%

Geomarketing Models in Supermarket Location Strategies

Baviera‐Puig

Buitrago‐Vera

Escribá-Pérez

2016

Journal of Business Economics and Management

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Abstract.Choosing where to open a new outlet is a critical decision for retail firms. Building on the multiplicative competitive interaction model from retail location theory, this paper develops a geomarketing model that can be used to devise supermarket location strategies. First, attributes that explain a supermarket's pull on consumers were determined. These attributes included objective (taken from databases and empirical observation) and subjective (based on managerial judgements) variables relating to the supermarket and its trade area. Then, geographic information system tools were used to analyse real data at a highly detailed level (road section). From a geomarketing viewpoint, the model shows that sociodemographic characteristics of the supermarket's trade area affect firms' location strategies. The paper also discusses improvements for calibrating and validating this model. Adding the spatial organization of supermarkets to the model yields a different consumer behaviour pattern. This geomarketing model can help managers to design supermarket location strategies according to shop features, competitors and environment, whilst estimating supermarket sales.

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“…Cheng et al (2007) suggested a GIS approach for selection of shopping mall locations. Chang et al (2008), combined GIS with fuzzy multi-criteria decision-making for location selection.…”

Section: Introductionmentioning

confidence: 99%

Selecting Location of Retail Stores Using Artificial Neural Networks and Google Places API

Satman

Altunbey

2014

IJSP

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Selection of locations of retail stores (similarly, facilities) is a kind of decision problem in which the researcher targets maximum profit or minimum cost by using statistical or judgmental forecasts. In many cases, statistical forecasts are based on survey data or data collected for an other store which are not reliable as the survey may not measure the potential demand or the other store that is used for comparison may not be similar enough. Addition to this, estimating the potential demand for a non-existing store can be expensive. Google Places API is a software library which provides a nearby search utility that is able to report several kinds of institutions, establishments and other objects placed in a circumferential area for a given radius. In this paper, we suggest a method which is based on estimating the relation between environmental properties of existing retail stores and their financial rankings. We remark that feed forward neural networks are capable to reveal such a relation as they permit using both integer, real and binary variables in the model and non-linearity. We apply our method on the location selection problem of a retail stores chain in Turkey (Note 1) which has 144 clients in its organization. Expert opinions in the organization show us applicability of this method is high in similar situations.

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A GIS approach to shopping mall location selection

Cited by 103 publications

References 28 publications

Selecting Shopping Center Site Using MADM Techniques

Selecting Shopping Center Site Using MADM Techniques

Geomarketing Models in Supermarket Location Strategies

Selecting Location of Retail Stores Using Artificial Neural Networks and Google Places API

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