服裝數(shù)字媒體消費(fèi)行為分析及實(shí)證研究
發(fā)布時(shí)間：2019-03-31 14:40
【摘要】：隨著互聯(lián)網(wǎng)技術(shù)的發(fā)展，數(shù)字媒體逐漸轉(zhuǎn)變成主流媒體，讓媒體真正成為消費(fèi)者生活的一部分?jǐn)?shù)字媒體時(shí)代讓消費(fèi)者購(gòu)物的選擇更加自主，也讓網(wǎng)絡(luò)營(yíng)銷面臨著更大的機(jī)會(huì)和競(jìng)爭(zhēng)服裝——作為日常生活必需品，其快速增加的網(wǎng)絡(luò)購(gòu)買(mǎi)量，而日益受到企業(yè)管理者和研究學(xué)者們的關(guān)注所以，研究基于數(shù)字媒體的服裝消費(fèi)行為具有重要的現(xiàn)實(shí)意義 本文選取B2C網(wǎng)絡(luò)購(gòu)物模式，以服裝網(wǎng)絡(luò)銷售為研究對(duì)象，在服裝電子商務(wù)企業(yè)實(shí)地搜集數(shù)據(jù)，采取靜態(tài)問(wèn)卷調(diào)查和動(dòng)態(tài)數(shù)據(jù)挖掘相結(jié)合的方法，分析和研究網(wǎng)絡(luò)購(gòu)物環(huán)境下的消費(fèi)者的購(gòu)買(mǎi)服裝時(shí)，消費(fèi)者因素服裝企業(yè)因素營(yíng)銷因素網(wǎng)絡(luò)因素以及感知風(fēng)險(xiǎn)因素對(duì)其消費(fèi)行為的影響用數(shù)據(jù)挖掘技術(shù)的關(guān)聯(lián)規(guī)則算法分析了消費(fèi)經(jīng)常網(wǎng)購(gòu)的服裝產(chǎn)品之間的組合營(yíng)銷利用聚類算法對(duì)有著不同消費(fèi)行為的消費(fèi)者進(jìn)行分類，并針對(duì)每一類型提出相應(yīng)的營(yíng)銷策略，最后在服裝企業(yè)進(jìn)行實(shí)證分析 通過(guò)消費(fèi)行為的靜態(tài)測(cè)試發(fā)現(xiàn)，，性別年齡學(xué)歷和服裝網(wǎng)絡(luò)消費(fèi)行為兩者之間無(wú)顯著差異，職業(yè)收入計(jì)算機(jī)使用年數(shù)每日使用網(wǎng)絡(luò)時(shí)間對(duì)服裝網(wǎng)絡(luò)消費(fèi)者的消費(fèi)行為有顯著差異消費(fèi)者因素服裝企業(yè)因素營(yíng)銷因素網(wǎng)絡(luò)因素與服裝網(wǎng)絡(luò)消費(fèi)有顯著的正相關(guān)性感知風(fēng)險(xiǎn)因素與服裝網(wǎng)絡(luò)消費(fèi)行為有顯著負(fù)相關(guān)靜態(tài)問(wèn)卷分析將消費(fèi)者分為4類分別是理性謹(jǐn)慎型沖動(dòng)享受型個(gè)性時(shí)尚型追求品牌型 在消費(fèi)行為的動(dòng)態(tài)測(cè)試中，以一家知名服裝企業(yè)的電子商務(wù)部的消費(fèi)者購(gòu)買(mǎi)服裝的部分歷史數(shù)據(jù)，選擇具有代表性能夠反映消費(fèi)者個(gè)人信息以及網(wǎng)絡(luò)消費(fèi)特性的變量，制作成本課題需要的數(shù)據(jù)庫(kù)最后根據(jù)數(shù)據(jù)挖掘分析將消費(fèi)者分為8個(gè)群組，每一群組所反映出的個(gè)人特征和消費(fèi)行為均有明顯區(qū)別 基于以上動(dòng)靜態(tài)的測(cè)試結(jié)果，整合后得出全新的分類結(jié)果，并提出相應(yīng)的營(yíng)銷建議同時(shí)，通過(guò)數(shù)據(jù)挖掘分析，發(fā)現(xiàn)不同產(chǎn)品間組合銷售的規(guī)律，T恤和牛仔褲無(wú)論是休閑裝還是正裝均能搭配出很好的效果，正裝中，正式的襯衫，西裙，褲子也會(huì)被消費(fèi)者與風(fēng)衣短西裝一起組合購(gòu)買(mǎi)，由于包和絲巾在平時(shí)被單獨(dú)購(gòu)買(mǎi)的幾率不高，所以建議實(shí)證服裝企業(yè)對(duì)這幾種產(chǎn)品進(jìn)行組合銷售，提高包和絲巾的購(gòu)買(mǎi)幾率該研究結(jié)果將有助于服裝網(wǎng)絡(luò)營(yíng)銷企業(yè)提高營(yíng)銷的針對(duì)性和有效性，促進(jìn)組合營(yíng)銷的應(yīng)用和發(fā)展，提高企業(yè)的銷售額和利潤(rùn)空間
[Abstract]:With the development of Internet technology, digital media has gradually become the mainstream media, so that media really become part of consumer life in the digital media era so that consumers shopping more independent choice. E-marketing is also faced with greater opportunities and competition for clothing-as a necessity of daily life, its rapid increase in the volume of online purchases, and increasingly attracted the attention of business managers and researchers so, It is of great practical significance to study clothing consumption behavior based on digital media. This paper chooses B2C network shopping mode, taking clothing network sales as the research object, and collects data on the spot in clothing e-commerce enterprises. Using the method of static questionnaire survey and dynamic data mining, this paper analyzes and studies the purchase of clothing by consumers under the environment of online shopping. Consumer factor, clothing enterprise factor, marketing factor, network factor and perceived risk factor influence their consumption behavior. The association rule algorithm of data mining technology is used to analyze the combination camp among clothing products which are often purchased online. Marketing uses clustering algorithm to classify consumers with different consumption behaviors. And put forward the corresponding marketing strategy for each type, finally, through the empirical analysis of clothing enterprises through the static test of consumption behavior, found that there is no significant difference between gender, age, education and clothing online consumption behavior. There is a significant difference between the consumption behavior of clothing network consumers and the consumption behavior of clothing network consumers. There is a significant positive correlation between the marketing factors of clothing enterprises and the network factors of clothing network consumption and the network factors of clothing network consumption. The static questionnaire analysis of the negative correlation between sexy knowledge risk factors and clothing online consumption behavior divides consumers into four categories: rational, prudent, impulse-enjoyment-style, personality-style, brand-seeking type, in the dynamic test of consumption behavior. Taking part of the historical data of consumers' purchase of clothing from the electronic commerce department of a well-known clothing enterprise, we choose variables that are representative of consumers' personal information and the characteristics of online consumption. In the end, according to the data mining analysis, consumers are divided into 8 groups. The individual characteristics and consumption behavior reflected in each group are obviously different based on the above dynamic and static test results. At the same time, through the analysis of data mining, we find that the rule of combination sale between different products, T-shirt and jeans can match very well, no matter whether they are casual wear or formal dress. In formal clothes, formal shirts, western skirts, and trousers will also be purchased by consumers and short suits of windbreaker. Since the chances of bags and scarves being purchased separately in ordinary times are not high, it is suggested that empirical clothing enterprises should combine these products to sell these products. The results of this study will help garment network marketing enterprises to improve the pertinence and effectiveness of marketing, to promote the application and development of combined marketing, and to improve the sales and profit space of enterprises.
【學(xué)位授予單位】：西安工程大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：F724.6;F426.86
本文編號(hào)：2451005
[Abstract]:With the development of Internet technology, digital media has gradually become the mainstream media, so that media really become part of consumer life in the digital media era so that consumers shopping more independent choice. E-marketing is also faced with greater opportunities and competition for clothing-as a necessity of daily life, its rapid increase in the volume of online purchases, and increasingly attracted the attention of business managers and researchers so, It is of great practical significance to study clothing consumption behavior based on digital media. This paper chooses B2C network shopping mode, taking clothing network sales as the research object, and collects data on the spot in clothing e-commerce enterprises. Using the method of static questionnaire survey and dynamic data mining, this paper analyzes and studies the purchase of clothing by consumers under the environment of online shopping. Consumer factor, clothing enterprise factor, marketing factor, network factor and perceived risk factor influence their consumption behavior. The association rule algorithm of data mining technology is used to analyze the combination camp among clothing products which are often purchased online. Marketing uses clustering algorithm to classify consumers with different consumption behaviors. And put forward the corresponding marketing strategy for each type, finally, through the empirical analysis of clothing enterprises through the static test of consumption behavior, found that there is no significant difference between gender, age, education and clothing online consumption behavior. There is a significant difference between the consumption behavior of clothing network consumers and the consumption behavior of clothing network consumers. There is a significant positive correlation between the marketing factors of clothing enterprises and the network factors of clothing network consumption and the network factors of clothing network consumption. The static questionnaire analysis of the negative correlation between sexy knowledge risk factors and clothing online consumption behavior divides consumers into four categories: rational, prudent, impulse-enjoyment-style, personality-style, brand-seeking type, in the dynamic test of consumption behavior. Taking part of the historical data of consumers' purchase of clothing from the electronic commerce department of a well-known clothing enterprise, we choose variables that are representative of consumers' personal information and the characteristics of online consumption. In the end, according to the data mining analysis, consumers are divided into 8 groups. The individual characteristics and consumption behavior reflected in each group are obviously different based on the above dynamic and static test results. At the same time, through the analysis of data mining, we find that the rule of combination sale between different products, T-shirt and jeans can match very well, no matter whether they are casual wear or formal dress. In formal clothes, formal shirts, western skirts, and trousers will also be purchased by consumers and short suits of windbreaker. Since the chances of bags and scarves being purchased separately in ordinary times are not high, it is suggested that empirical clothing enterprises should combine these products to sell these products. The results of this study will help garment network marketing enterprises to improve the pertinence and effectiveness of marketing, to promote the application and development of combined marketing, and to improve the sales and profit space of enterprises.
【學(xué)位授予單位】：西安工程大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：F724.6;F426.86
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