Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/78462
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dc.contributorDepartment of Land Surveying and Geo-Informatics-
dc.creatorZhu, JW-
dc.creatorXu, Y-
dc.creatorFang, ZX-
dc.creatorShaw, SL-
dc.creatorLiu, XJ-
dc.date.accessioned2018-09-28T01:16:37Z-
dc.date.available2018-09-28T01:16:37Z-
dc.identifier.urihttp://hdl.handle.net/10397/78462-
dc.language.isoenen_US
dc.publisherMolecular Diversity Preservation International (MDPI)en_US
dc.rights© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).-
dc.rightsThe following publication Zhu, J., Xu, Y., Fang, Z., Shaw, S. -., & Liu, X. (2018). Geographic prevalence and mix of regional cuisines in chinese cities. ISPRS International Journal of Geo-Information, 7(5), 183 is available at https://doi.org/10.3390/ijgi7050183-
dc.subjectFood geographyen_US
dc.subjectRegional cuisineen_US
dc.subjectSpatial analyticsen_US
dc.subjectChinaen_US
dc.titleGeographic prevalence and mix of regional cuisines in Chinese citiesen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume7-
dc.identifier.issue5-
dc.identifier.doi10.3390/ijgi7050183-
dcterms.abstractPrevious research on the geographies of food put a considerable focus on analyzing how different types of food or ingredients are consumed across different places. Little is known, however, about how food culture is manifested through various cooking traditions as well as people's perceptions over different culinary styles. Using a data set captured from one of the largest online review sites in China (www.dianping.com), this study demonstrates how geo-referenced social review data can be leveraged to better understand the geographic prevalence and mix of regional cuisines in Chinese cities. Based on information of millions of restaurants obtained in selected cities (i.e., provincial capitals and municipalities under direct supervision of the Chinese central government), we first measure by each city the diversity of restaurants that serve regional Chinese cuisines using the Shannon entropy, and analyze how cities with different characteristics are geographically distributed. A hierarchical clustering algorithm is then used to further explore the similarities of consumers' dining options among these cities. By associating each regional Chinese cuisine to its origin, we then develop a weighted distance measure to quantify the geographic prevalence of each cuisine type. Finally, a popularity index (POPU) is introduced to quantify consumers' preferences for different regional cuisines. We find that: (1) diversity of restaurants among the cities shows an east-west contrast that is in general agreement with the socioeconomic divide in China; (2) most of the cities have their own unique characteristics, which are mainly driven by a large market share of the corresponding local cuisine; (3) there exists great heterogeneity of the geographic prevalence of different Chinese cuisines. In particular, Chuan and Xiang, which are famous for their spicy taste, are widely distributed across the mainland China and (4) among the top-tier restaurants ranked by the consumers in a city, the local cuisine is not usually favored, while other cuisines are favored by consumers in many different cities. This study demonstrates the use of social review data as a cost-effective approach of studying urban gastronomy and its relationship with human activities.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationISPRS international journal of geo-information, May 2018, v. 7, no. 5, 183-
dcterms.isPartOfISPRS international journal of geo-information-
dcterms.issued2018-
dc.identifier.isiWOS:000435194700023-
dc.identifier.eissn2220-9964-
dc.identifier.artn183-
dc.identifier.rosgroupid2017001902-
dc.description.ros2017-2018 > Academic research: refereed > Publication in refereed journal-
dc.description.validate201809 bcrc-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
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