基于社交媒体的贸易区域界定研究

发布时间：2018-03-20 05:19

本文选题：社交媒体　切入点：贸易区域　出处：《武汉大学》2017年硕士论文　论文类型：学位论文

【摘要】：在市场分析中,最重要的一步是定义商业设施的贸易区域。城市商业设施的优化配置对于国民经济的发展和人们生活质量的提升具有重要意义。传统界定商业设施贸易区域的数据源主要来自问卷调查所收集的顾客信息,但是问卷调查非常耗费人力,物力且回馈率较低,并且涉及的对象有限,获取的样本对象具有局限性。人们在使用社交媒体的过程中,产生了海量的带有地理位置信息的数据。社交媒体数据时空属性丰富,反映了人们的生活方式和移动规律,为我们在大数据时代下界定商业设施的贸易区域提供了新的机遇和途径。本文基于社交媒体点评数据,提出一种利用改进的Huff模型界定贸易区域的方法。通过对不同界定贸易区域的模型进行比较分析发现本文提出的改进Huff模型具有一定优势。本文所做主要工作如下:(1)设计利用点评网站页面结构的网络爬虫搜集商业设施的评分和用户点评数据的方案,并按照研究需求,提出数据预处理的方法,包括地理编码和数据提取。(2)设计利用改进的Huff模型界定贸易区域的方法。该方法首先获取顾客样本数据;然后计算Huff模型中的三个变量:商业吸引力,行程距离与顾客光临概率;之后对研究区域进行不同尺度格网划分,提取不同签到数的格网,选择不同因素作为商业设施吸引力变量,进行Huff模型校正,选择出最佳的Huff模型参数;最后基于改进的Huff模型,界定购物中心的贸易区域,并利用ArcGIS桌面工具对结果进行可视化。(3)将基于改进的Huff模型得出的贸易区域与基于无顾客数据的Voronoi图、空间可达性模型得出的贸易区域进行对比,相比于其它方法,Huff模型能更好地界定商业设施的贸易区域。该研究是首次基于带有地理位置信息的社交媒体点评数据,利用改进的Huff模型进行贸易区域界定的尝试。该研究为商业设施的贸易区域界定研究探讨了一种新型大规模数据源的可能性。贸易范围确定之后,商业管理和经营者就可以利用这个范围来识别顾客的来源和分布,估计客流量,有针对性地发布广告,制定营销活动等,这对于研究城市的商业发展和服务功能有重要意义。
[Abstract]:In market analysis, The most important step is to define the trade area of commercial facilities. The optimal allocation of urban commercial facilities is of great significance to the development of national economy and the improvement of people's quality of life. According to the sources, they are mainly from the customer information collected by the questionnaire, But the questionnaire is very labor, material and feedback rate is low, and the object involved is limited, the sample has limitations. People in the process of using social media, Social media data are rich in space-time attributes, reflecting the way people live and how they move. It provides us with new opportunities and ways to define the trading area of commercial facilities under big data's time. This paper presents a method of defining trade regions by using improved Huff model. By comparing and analyzing the models of different defined trade regions, it is found that the improved Huff model proposed in this paper has some advantages. The main work done in this paper is as follows:. (1) Design a scheme to use the web crawler structure of a review site to collect ratings of commercial facilities and user rating data. According to the research requirements, a method of data preprocessing is proposed, including geo-coding and data extraction. (2) the method of using the improved Huff model to define the trade area is designed. Firstly, the customer sample data are obtained by this method. Then we calculate the three variables in the Huff model: commercial attractiveness, travel distance and customer presence probability, and then divide the study area with different scale grid to extract the grid with different number of sign-ins. Choosing different factors as the attractive variables of commercial facilities, the Huff model is corrected to select the best Huff model parameters. Finally, based on the improved Huff model, the trade area of the shopping center is defined. Using the ArcGIS desktop tool to visualize the results, the trade area based on the improved Huff model is compared with the trade area based on the Voronoi map and the spatial reachability model without customer data. The Huff model is a better way to define the trading areas of commercial facilities than other methods. The study is the first to be based on social media review data with geographic information. This study explores the possibility of a new type of large-scale data source for the study of regional definition of trade in commercial facilities. Business management and operators can use this range to identify the source and distribution of customers, estimate passenger flow, publish advertisements, formulate marketing activities, etc., which is of great significance to the study of the commercial development and service functions of the city.
【学位授予单位】：武汉大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F724;F274;P208

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