發(fā)布時(shí)間：2018-03-26 10:27

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

【摘要】：網(wǎng)約車是“互聯(lián)網(wǎng)+”時(shí)代下的產(chǎn)物,其通過(guò)依托移動(dòng)互聯(lián)網(wǎng)建立的打車軟件服務(wù)平臺(tái),實(shí)現(xiàn)了乘客與司機(jī)之間的信息溝通,從而使司機(jī)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(jì)的典型代表。在網(wǎng)約車市場(chǎng)新興之時(shí),圍繞網(wǎng)約車市場(chǎng)規(guī)范發(fā)展的理論及應(yīng)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(yùn)用問(wèn)卷調(diào)查、數(shù)據(jù)挖掘等統(tǒng)計(jì)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(chǎng)的科學(xué)發(fā)展提供建議。本文的重點(diǎn)、創(chuàng)新之處,主要表現(xiàn)在以下三點(diǎn):第一、通過(guò)問(wèn)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(chǔ)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(duì)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(luò)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(duì)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(luò)建立分類判別模型,將約車頻率作為衡量網(wǎng)約車忠實(shí)客戶的特征,探討影響網(wǎng)約車忠實(shí)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(duì)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(xué)位授予單位】：首都經(jīng)濟(jì)貿(mào)易大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：F724.6;F572

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 侯登華;;共享經(jīng)濟(jì)下網(wǎng)絡(luò)平臺(tái)的法律地位——以網(wǎng)約車為研究對(duì)象[J];政法論壇;2017年01期

2 鮑一鳴;;基于互聯(lián)網(wǎng)平臺(tái)的網(wǎng)約車動(dòng)態(tài)補(bǔ)貼策略[J];現(xiàn)代商業(yè);2016年34期

3 吳明禮;楊雙亮;;用戶畫像在內(nèi)容推送中的研究與應(yīng)用[J];電腦知識(shí)與技術(shù);2016年32期

4 王漢斌;岳帥;;網(wǎng)約車指導(dǎo)定價(jià)模型研究[J];價(jià)格月刊;2016年10期

5 張燁楠;;網(wǎng)約車行業(yè)的監(jiān)管完善以及展望[J];企業(yè)改革與管理;2016年17期

6 周詩(shī)蜜;張華明;;滴滴打車軟件顧客滿意度評(píng)價(jià)研究[J];信息系統(tǒng)工程;2016年08期

7 王茹;;“十三五”時(shí)期如何推動(dòng)“互聯(lián)網(wǎng)+”促進(jìn)轉(zhuǎn)型升級(jí)[J];經(jīng)濟(jì)研究參考;2016年07期

8 韓中庚;杜劍平;;“互聯(lián)網(wǎng)+”時(shí)代的出租車資源配置問(wèn)題評(píng)析[J];數(shù)學(xué)建模及其應(yīng)用;2015年04期

9 包希璐;;南京滴滴打車滿意度研究——基于顧客感知價(jià)值[J];管理觀察;2015年18期

10 尹劍;陸程敏;楊貴軍;;判別分析與Logistic回歸組合分類[J];數(shù)理統(tǒng)計(jì)與管理;2014年02期

相關(guān)碩士學(xué)位論文 前2條

1 周茜;基于多項(xiàng)Logit模型的居民幸福感研究[D];南京大學(xué);2016年

2 茅群霞;缺失值處理統(tǒng)計(jì)方法的模擬比較研究及應(yīng)用[D];四川大學(xué);2005年

，

本文編號(hào)：1667511