本文選題：大數(shù)據(jù) + C2C模式��； 參考：《上海工程技術(shù)大學(xué)》2015年碩士論文

【摘要】：隨著互聯(lián)網(wǎng)技術(shù)的發(fā)展,如今越來(lái)越多的人選擇在網(wǎng)上進(jìn)行購(gòu)物,近年來(lái)以淘寶網(wǎng)為代表的C2C購(gòu)物模式發(fā)展迅速,然而,C2C模式占領(lǐng)主導(dǎo)地位的同時(shí),大數(shù)據(jù)的到來(lái)對(duì)其提出了挑戰(zhàn),如大數(shù)據(jù)挖掘的隱私安全問(wèn)題,大數(shù)據(jù)甄別的C2C模式質(zhì)量問(wèn)題等,這些問(wèn)題的存在都會(huì)影響著消費(fèi)者的行為。所以,研究大數(shù)據(jù)環(huán)境下C2C模式的消費(fèi)者行為是大數(shù)據(jù)時(shí)代C2C網(wǎng)絡(luò)市場(chǎng)發(fā)展的迫切需要。本研究以大數(shù)據(jù)時(shí)代為社會(huì)背景,以消費(fèi)者行為理論為基礎(chǔ),圍繞大數(shù)據(jù)自身的概念、特征及影響,結(jié)合C2C模式的特點(diǎn)及發(fā)展現(xiàn)狀,建立了大數(shù)據(jù)環(huán)境下C2C模式的消費(fèi)者行為模型,并通過(guò)實(shí)證對(duì)理論進(jìn)行驗(yàn)證,得出結(jié)論并對(duì)C2C模式提出相關(guān)建議。在理論部分,基于大數(shù)據(jù)的特點(diǎn)和C2C模式的特點(diǎn),提出了大數(shù)據(jù)驅(qū)動(dòng)的精準(zhǔn)營(yíng)銷,大數(shù)據(jù)甄別的網(wǎng)站質(zhì)量,大數(shù)據(jù)挖掘的隱私安全三個(gè)影響大數(shù)據(jù)環(huán)境下消費(fèi)者行為的外部因素,將大數(shù)據(jù)驅(qū)動(dòng)的精準(zhǔn)營(yíng)銷分為信息檢索、推薦系統(tǒng)、虛擬體驗(yàn)三個(gè)變量;將大數(shù)據(jù)甄別的網(wǎng)站質(zhì)量分為信息質(zhì)量、服務(wù)質(zhì)量、系統(tǒng)質(zhì)量三個(gè)變量;將大數(shù)據(jù)挖掘的隱私安全分為隱私泄露、安全關(guān)注、信息公開(kāi)三個(gè)變量;并以感知有用、信任、感知風(fēng)險(xiǎn)作為中間變量,結(jié)合SOR和TAM模型的理論基礎(chǔ)建立了大數(shù)據(jù)環(huán)境下C2C模式消費(fèi)者行為的理論模型。在實(shí)證部分,以淘寶網(wǎng)購(gòu)物者作為調(diào)研對(duì)象,進(jìn)行預(yù)調(diào)研和正式調(diào)研,運(yùn)用SPSS19.0和AMOS17.0數(shù)據(jù)分析軟件進(jìn)行信度效度分析、因子分析、結(jié)構(gòu)方程模型檢驗(yàn)等,得出結(jié)論:大數(shù)據(jù)驅(qū)動(dòng)的信息檢索、推薦系統(tǒng)、虛擬體驗(yàn)通過(guò)影響消費(fèi)者在C2C購(gòu)買(mǎi)的感知有用性進(jìn)而對(duì)消費(fèi)者購(gòu)買(mǎi)意愿產(chǎn)生影響;大數(shù)據(jù)甄別的信息質(zhì)量、服務(wù)質(zhì)量通過(guò)影響消費(fèi)者對(duì)C2C的信任進(jìn)而對(duì)消費(fèi)者購(gòu)買(mǎi)意愿產(chǎn)生影響;大數(shù)據(jù)挖掘的隱私泄露、安全關(guān)注通過(guò)影響消費(fèi)者對(duì)C2C的感知風(fēng)險(xiǎn)進(jìn)而對(duì)消費(fèi)者購(gòu)買(mǎi)意愿產(chǎn)生影響。最后,分析和總結(jié)研究結(jié)果,并根據(jù)研究結(jié)論對(duì)C2C模式的發(fā)展提出建議,并指出本文研究的不足之處與未來(lái)的研究展望。
[Abstract]:With the development of Internet technology, more and more people choose to shop online. In recent years, the C2C shopping model, represented by Taobao, has developed rapidly. However, C2C mode occupies the leading position at the same time. The arrival of big data has challenged him, such as the privacy security problem excavated by big data, the quality of C2C model identified by big data, and so on. The existence of these problems will affect the behavior of consumers. Therefore, to study the consumer behavior of C2C model under big data environment is the urgent need for the development of C2C network market in big data era. This study is based on the social background of big data's time, on the theory of consumer behavior, on the concept, characteristics and influence of big data itself, combined with the characteristics and development status of C2C model. This paper establishes the consumer behavior model of C2C model under big data environment, and verifies the theory by demonstration, draws a conclusion and puts forward some relevant suggestions to C2C model. In the theoretical part, based on the characteristics of big data and the characteristics of C2C model, the paper puts forward the accurate marketing driven by big data and the quality of website identified by big data. Big data excavates the privacy security three influence consumer behavior external factor under the big data environment, the accurate marketing driven by big data is divided into three variables: information retrieval, recommendation system, virtual experience; The quality of the website identified by big data is divided into three variables: information quality, service quality and system quality; the privacy security excavated by big data is divided into three variables: privacy disclosure, security concern, and information disclosure; and the three variables are perceived usefulness and trust. Perceived risk as an intermediate variable, combined with the theoretical basis of SOR and TAM models, a theoretical model of consumer behavior in big data's C2C model is established. In the empirical part, we take Taobao shoppers as the research objects, carry out pre-survey and formal investigation, use SPSS19.0 and AMOS17.0 data analysis software to analyze reliability and validity, factor analysis, structural equation model test, etc. Conclusion: big data driven information retrieval, recommendation system, virtual experience affect consumers' perceived usefulness in C2C purchase and then affect consumers' willingness to buy. Service quality affects consumers' confidence in C2C and then consumers' willingness to buy. Big data divulges privacy and security concerns affect consumers' perceived risks to C2C and then to consumers' willingness to buy. Finally, the research results are analyzed and summarized, and suggestions for the development of C2C model are put forward according to the research conclusions, and the shortcomings of this study and the future research prospects are pointed out.
【學(xué)位授予單位】：上海工程技術(shù)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：F713.55;F724.6

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本文編號(hào)：1859504