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  本文選題：網(wǎng)約車　切入點：出行方式　出處：《首都經(jīng)濟貿(mào)易大學》2017年碩士論文

【摘要】：網(wǎng)約車是“互聯(lián)網(wǎng)+”時代下的產(chǎn)物,其通過依托移動互聯(lián)網(wǎng)建立的打車軟件服務平臺,實現(xiàn)了乘客與司機之間的信息溝通,從而使司機快速接單,乘客快速打車,有效地提高打車效率,成為共享經(jīng)濟的典型代表。在網(wǎng)約車市場新興之時,圍繞網(wǎng)約車市場規(guī)范發(fā)展的理論及應用研究是十分必要的。本文圍繞網(wǎng)約車用戶出行方式選擇展開研究,運用問卷調(diào)查、數(shù)據(jù)挖掘等統(tǒng)計方法,調(diào)查了網(wǎng)約車用戶的分布狀況和行為信息,就網(wǎng)約車用戶出行方式選擇行為表現(xiàn)出的群體差異性展開探討,最終刻畫出影響網(wǎng)約車用戶約車方式以及約車頻率的主要特征,從而為網(wǎng)約車市場的科學發(fā)展提供建議。本文的重點、創(chuàng)新之處,主要表現(xiàn)在以下三點:第一、通過問卷調(diào)查收集網(wǎng)約車用戶的基本信息以及行為信息,把握網(wǎng)約車用戶基本信息以及行為信息,在此基礎上利用列聯(lián)分析以及交叉分析研究網(wǎng)約車用戶在約車方式以及約車頻率方面存在的群體差異性,結(jié)果表明收入、職業(yè)、年齡、約車原因、安全滿意度等群體特征對約車方式選擇以及約車頻率具有顯著影響。第二、圍繞網(wǎng)約車用戶約車方式利用決策樹、logistic、神經(jīng)網(wǎng)絡建立分類判別模型,探討影響網(wǎng)約車用戶不同約車方式的主要特征,結(jié)果表明網(wǎng)約車用戶的年齡、頻率、約車原因、安全滿意度、收入對網(wǎng)約車用戶不同的約車方式存在顯著影響。第三、圍繞網(wǎng)約車用戶約車頻率利用決策樹、logistic、神經(jīng)網(wǎng)絡建立分類判別模型,將約車頻率作為衡量網(wǎng)約車忠實客戶的特征,探討影響網(wǎng)約車忠實用戶選擇行為的特征,結(jié)果表明,選車方式、選車原因、收入、年齡等對其有顯著影響。
[Abstract]:Ride-hailing is the product of the era of "Internet". By relying on the mobile Internet, the ride-hailing software service platform has realized the communication of information between passengers and drivers, so that drivers can pick up orders quickly, and passengers can take a taxi quickly. Effectively improve the efficiency of ride-hailing, become a typical representative of the sharing economy. It is very necessary to study the theory and application of the development of the network car market standard. This paper focuses on the choice of the travel mode of the ride-hailing users, and applies the statistical methods such as questionnaire survey, data mining and so on. This paper investigates the distribution and behavior information of the network ride-hailing users, probes into the group differences in the behavior of the car-ride-sharing users, and finally depicts the main characteristics that affect the car-sharing modes and the ride-sharing frequency of the ride-hailing users. The key points and innovations of this paper are as follows: first, collecting the basic information and behavior information of ride-hailing users through questionnaires. To grasp the basic information and behavior information of ride-hailing users on the basis of the analysis and cross-analysis of network ride-hailing users in terms of car-sharing patterns and ride-sharing frequency, the results show that the income, occupation, age, and age of car-hailing users are different from each other. Group characteristics such as car-sharing reasons, safety satisfaction and so on have a significant impact on the choice of ride-hailing mode and the frequency of ride-hailing. Second, a classification and discrimination model is built around the decision tree of ride-hailing users using the decision tree logistic-neural network. This paper discusses the main characteristics that affect the different car-sharing modes of the net-ride-hailing users. The results show that the age, frequency, reasons, safety satisfaction and income of the net-ride-hailing users have significant influence on the different car-sharing modes of the net-ride-hailing users. According to the decision tree of ride-sharing frequency of ride-hailing users, the neural network is used to establish a classification and discriminant model. The frequency of ride-hailing is regarded as the characteristic to measure the loyal customers, and the characteristics that affect the behavior of network-ride-sharing loyal users are discussed. The results show that, Car selection, car selection reasons, income, age and so on have a significant impact on it.
【學位授予單位】：首都經(jīng)濟貿(mào)易大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：F724.6;F572

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本文編號：1667511