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dc.contributor.authorSozen, Cenk
dc.contributor.authorDevrani, Tulay
dc.date.accessioned2021-06-30T12:54:53Z
dc.date.available2021-06-30T12:54:53Z
dc.date.issued2020
dc.identifier.issn0263-7472en_US
dc.identifier.urihttp://hdl.handle.net/11727/6181
dc.description.abstractPurpose The purpose of this study is to suggest an unusual method that may help researchers to examine from the real-time movements of consumers among stores located on any kind of shopping location. We assumed shopping behavior of individuals as a complicated network representing their interactions with multiple types of stores - brands. Shopping malls were chosen to test this alternative method. Closely located stores in these organizations give researchers a chance to investigate patterns of interactions of customers in relation to brands. Therefore, we decided to develop an unusual method to examine customers' behavior in these organizations. Design/methodology/approach This study suggests that circulation patterns of customers in a shopping location may provide valuable information to decision makers. The applicability of this technique was tested on 700 consumers visiting stores of a supper-regional shopping mall, located in Ankara, Turkey. Paths of the customers in a specific type of mall were determined, and their interactions with the stores were analyzed by using social network analysis techniques. The brands having key positions in the network were compared with the brand configuration of high- and low-performer malls serving to similar markets. Findings The results of the network analyses were used to understand whether this method could be beneficial for the ideal tenant mix problem of shopping malls. Findings suggest that the performance of malls depends on fitness to customer paths, and the malls, which didn't have the key brands at the initial stage, could not adapt themselves later. Findings of the case study verified that this technique might offer a solution to this well-known dilemma of the retailing sector and may have several implications. Originality/value These types of data are very valuable, especially for retailing research and the industry, because very critical knowledge such as traffic among retail stores, key central brands, ideal location of stores, consumption tendencies of different customer groups and symbiotic or competitive relations among retailers can be obtained. This method may also have broad implications in other fields of research such as location analysis, decision support systems and property management as well as marketing and retailing.en_US
dc.language.isoengen_US
dc.relation.isversionof10.1108/PM-09-2019-0049en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectInvestmentsen_US
dc.subjectConsumer behavioren_US
dc.subjectNetwork theoryen_US
dc.subjectTenant mixen_US
dc.titleIntroduction of a new method for retailing and marketing research: the case of shopping mallsen_US
dc.typearticleen_US
dc.relation.journalPROPERTY MANAGEMENTen_US
dc.identifier.volume38en_US
dc.identifier.issue3en_US
dc.identifier.startpage365en_US
dc.identifier.endpage381en_US
dc.identifier.wos000522236800001en_US
dc.identifier.scopus2-s2.0-85082593806en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergien_US


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