• Vol 9, No 7 (2018)
  • Architecture

The Spatial Distribution Patterns of the Catering Trade in Nanchang based on Internet Public Reviews

Xiong He, Zijiang Yang, Kun Zhang, Ping Yang, Shuai Zhang

Corresponding email: 617837796@qq.com


Published at : 21 Dec 2018
IJtech : IJtech Vol 9, No 7 (2018)
DOI : https://doi.org/10.14716/ijtech.v9i7.2485

Cite this article as:
He, X., Yang, Z., Zhang, K., Yang, P., Zhang, S., 2018. The Spatial Distribution Patterns of the Catering Trade in Nanchang based on Internet Public Reviews. International Journal of Technology. Volume 9(7), pp. 1319-1328
166
Downloads
Xiong He School of Architecture and Urban Planning, Yunnan University, Kunming 650504, Chinaanning
Zijiang Yang School of Architecture and Urban Planning, Yunnan University, Kunming 650504, China
Kun Zhang School of Architecture and Urban Planning, Yunnan University, Kunming 650504, China
Ping Yang School of Architecture and Urban Planning, Yunnan University, Kunming 650504, China
Shuai Zhang School of Architecture and Urban Planning, Yunnan University, Kunming 650504, China
Email to Corresponding Author

Abstract
image

The spatial distribution characteristics and patterns of the catering industry in Nanchang were studied to determine the spatial laws of the local urban catering organizations. To establish a word-of-mouth evaluation system, the evaluation data of selected catering merchants were used to calculate comprehensive word-of-mouth scores and rankings for each merchant using principal component analysis. A nuclear density analysis of the spatial distribution of the catering industry was also carried out. The study results showed that Nanchang catering merchants can be divided into three groups of which high-consumption (the total amount of money spent by each customer at a single sitting) merchants accounted for 2.8%, middle-consumption merchants accounted for 37%, and low-consumption merchants accounted for 60.2%. The catering industry’s overall development level was further found to be low. Moreover, the high-consumption merchants were predominantly clustered in Honggutan, while the low-to-medium consumption merchants were mainly located in Zhongshan City. There was also a correlation between merchant distribution and merchant word-of-mouth: The distribution of catering chambers determined the level of word-of-mouth, and the degree of word-of-mouth determined the direction of catering development. Additionally, it was established that the internal business form and activity patterns of a city could affect the spatial distribution trends of catering merchants. Importantly, the study of network data combined with urban physical spaces could play a significant role in urban planning.

Catering merchants; Nanchang; Public reviews; Spatial pattern

Introduction

People’s daily lives and the internal organization of city spaces have changed enormously alongside the rapid development of information technology. To adapt to this trend, the theory of urban planning, the main aim of which is to study urban spatial organization and its changes, should seek to innovate its paradigms and methods. Such innovation is predominantly evident in the wide application of information technology in urban and regional research, the connections between network spaces and urban physical spaces, and discussions on the future of urban development (Zhen et al., 2007). Remote sensing, geographic information systems (GIS), and thermodynamic charts can be used to study urban spaces on a macro level (Wu & Ye, 2016; Du et al., 2018). The data found in messages, blogs, locations, and people’s daily lives can also be applied to study the behavioral characteristics of urban residents in microcosmic terms (Xiao et al., 2013; Ding et al., 2015; Li et al., 2016). Overall, paradigms and methods utilizing both network spaces and urban physical spaces are gradually increasing. The application of the big data of cities and their residents to urban network spaces is also becoming mainstream. However, the study of spatial organization and the structure of urban physical spaces is relatively lacking.

Scholars are paying increasing attention to the spatial distribution patterns of urban service industries, with their research scope covering commercial (Wu et al., 2003; Zhou & Ji, 2009) and production services (Zhen et al., 2008; Xue et al., 2011). The catering trade is not only an important branch of commercial services, but also a necessary link in urban spatial organization. Diet, the environment, and culture merge to form a culture with a history. The catering trade is undoubtedly an extremely important feature of city life. Furthermore, the spatial distribution of the catering trade and its driving factors are greatly significant in guiding future urban construction. However, the study of the spatial distribution of the catering trade, which is proportional to the speed of a city’s growth, is obviously not sufficient (Lu, 2007).

Foreign scholars have previously analyzed the spatial distribution of the catering trade from the perspective of tourism and transportation (Wall et al., 1985). They found that the catering trade is most concentrated in a city’s central business district or in well-developed transportation areas. It was also established that there is a close connection between the urban catering trade and transportation, and a catering development model has therefore been proposed with roads and traffic as guides.

Domestic research started comparatively late and has focused primarily on the analysis of star-rated hotels and hotel management (Hu & Zhang, 2002; Wen, 2004). The volume of research concentrating on the spatial distribution of the catering trade is however low, and tended to be based on a single-subject design (Lu, 2007).

Based on previous works, Nanchang was chosen as the sample study area in this paper and was evaluated using Statistical Product and Service Solutions (SPSS) with data from the review website Dianping. GIS was initially used to explore the spatial distribution of the catering trade in Nanchang.

Conclusion

With the rapid development of the Internet, catering consumption models combined with Internet data will surely become the new development models for the catering industry. This will undoubtedly play a positive role in promoting the development of the catering industry. Through the use of network data, this study analyzed the spatial distribution patterns of the catering industry and their influencing factors, which not only provides a useful reference for the development of the catering industry, but also for city planning. Secondly, the combination of network data and urban geospatial information changes the research paradigm of traditional urban space to a certain extent. It is gradually becoming a new method or a new direction in urban planning that can also be utilized in even larger disciplines.

References

Ding, L., Niu, X.Y., Song, X.D., 2015. Urban Spatial Studies with Big Data of Mobile Location: A Progress Review. Urban Planning International, Volume 30(4), pp. 53–58

Du, P., Bai, X.Y., Luo, J.Q., Li, E.Z., Lin, C., 2018. Advances of Urban Remote Sensing. Journal of Nanjing University of Information Science & Technology (Natural Science Edition), Volume 10(1), pp. 16–29

Hu, Z.Y., Zhang, Z.G., 2002. An Analysis about the Spatial Distribution of Hotels in Urban Area: Take Nanjing as a Case. Economic Geography, Volume 22(1), pp. 106–110

Lu, L., 2007. The Distribution in Space of Urban Catering and its Factors: Xi?an as an Example. Journal of Northwest University (Natural Science Edition), Volume 37(6), pp. 925–930

Li, Z.F., Yu, L., Gao, Y., Wu, Y.Z., Gong, D.P., Song, G.H., 2016. Extraction Method of Temporal and Spatial Characteristics of Residents’ Trips based on Cellular Signaling Data. Transportation Standardization, Volume 2(1), pp. 51–57

Xiao, Q., Feng, Z., Lifang, X., Shoujia, Z., 2013. Methods in Urban Temporal and Spatial Behavior Research in the Big Data Era. Progress in Geography, Volume 32(9), pp. 1352–1361

Wall, G., Dudycha, D., Hutchinson, J., 1985. Point Pattern Analysis of Accommodation in Toronto.  Annals of Tourism Research, Volume 12(4), pp. 603–618

Wang, J.F., Liao, Y.L., Liu, X., 2010. Spatial Data Analysis Tutorial. Science Press, Beijing, pp. 273–277

Wen, J., 2004. On Chinese Star-Hotels’ Spatial Distribution. Commercial Research, Volume 21, pp. 154–159

Wu, Z.Q., Dai, X.Z., Wei, X.H., 2003. Review and Prospects for Study on Spatial Structure of Urban commercial Activity. Economic Geography, Volume 23(3), pp. 327–332

Wu, Z.Q., Ye, Z.N., 2016. Research on Urban Spatial Structure based on Baidu Heat Map: A Case Study on the Central City of Shanghai. City Planning Review, Volume 40(04), pp. 33–40

Xue, D.Q., Shi, N., Gong, X.X., 2011. Spatial Features and Agglomeration of Producer Services in Xi'an City, China. Scientia Geographical Sonica, Volume 31(10), pp. 1195–1201

Zhen, F., Liu, H., Zheng, J., 2008. Spatial Distribution of Urban Producer Service: A Case Study of Nanjing. World Regional Studies, Volume 17(1), pp. 24–31

Zhen, F., Liu, X.X., Liu, H., 2007. Regional Urban Network Influenced by Information Technology: New Directions of Urban Studies. Human Geography, Volume 2, pp. 76–80

Zhou, S.-Y., Ji, L.-M., 2009. Commercial Space Succession in Old City of Beijing Case of Survey Line of Inner City in Beijing from 1996 to 2006. Scientia Geographical Sinica, Volume 29(4), pp. 493–499