本文選題：社交媒體　切入點：貿(mào)易區(qū)域　出處：《武漢大學》2017年碩士論文　論文類型：學位論文

【摘要】：在市場分析中,最重要的一步是定義商業(yè)設施的貿(mào)易區(qū)域。城市商業(yè)設施的優(yōu)化配置對于國民經(jīng)濟的發(fā)展和人們生活質(zhì)量的提升具有重要意義。傳統(tǒng)界定商業(yè)設施貿(mào)易區(qū)域的數(shù)據(jù)源主要來自問卷調(diào)查所收集的顧客信息,但是問卷調(diào)查非常耗費人力,物力且回饋率較低,并且涉及的對象有限,獲取的樣本對象具有局限性。人們在使用社交媒體的過程中,產(chǎn)生了海量的帶有地理位置信息的數(shù)據(jù)。社交媒體數(shù)據(jù)時空屬性豐富,反映了人們的生活方式和移動規(guī)律,為我們在大數(shù)據(jù)時代下界定商業(yè)設施的貿(mào)易區(qū)域提供了新的機遇和途徑。本文基于社交媒體點評數(shù)據(jù),提出一種利用改進的Huff模型界定貿(mào)易區(qū)域的方法。通過對不同界定貿(mào)易區(qū)域的模型進行比較分析發(fā)現(xiàn)本文提出的改進Huff模型具有一定優(yōu)勢。本文所做主要工作如下:(1)設計利用點評網(wǎng)站頁面結(jié)構(gòu)的網(wǎng)絡爬蟲搜集商業(yè)設施的評分和用戶點評數(shù)據(jù)的方案,并按照研究需求,提出數(shù)據(jù)預處理的方法,包括地理編碼和數(shù)據(jù)提取。(2)設計利用改進的Huff模型界定貿(mào)易區(qū)域的方法。該方法首先獲取顧客樣本數(shù)據(jù);然后計算Huff模型中的三個變量:商業(yè)吸引力,行程距離與顧客光臨概率;之后對研究區(qū)域進行不同尺度格網(wǎng)劃分,提取不同簽到數(shù)的格網(wǎng),選擇不同因素作為商業(yè)設施吸引力變量,進行Huff模型校正,選擇出最佳的Huff模型參數(shù);最后基于改進的Huff模型,界定購物中心的貿(mào)易區(qū)域,并利用ArcGIS桌面工具對結(jié)果進行可視化。(3)將基于改進的Huff模型得出的貿(mào)易區(qū)域與基于無顧客數(shù)據(jù)的Voronoi圖、空間可達性模型得出的貿(mào)易區(qū)域進行對比,相比于其它方法,Huff模型能更好地界定商業(yè)設施的貿(mào)易區(qū)域。該研究是首次基于帶有地理位置信息的社交媒體點評數(shù)據(jù),利用改進的Huff模型進行貿(mào)易區(qū)域界定的嘗試。該研究為商業(yè)設施的貿(mào)易區(qū)域界定研究探討了一種新型大規(guī)模數(shù)據(jù)源的可能性。貿(mào)易范圍確定之后,商業(yè)管理和經(jīng)營者就可以利用這個范圍來識別顧客的來源和分布,估計客流量,有針對性地發(fā)布廣告,制定營銷活動等,這對于研究城市的商業(yè)發(fā)展和服務功能有重要意義。
[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.
【學位授予單位】：武漢大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：F724;F274;P208

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