本文選題：互聯網金融 + 互聯網理財產品��； 參考：《天津大學》2014年碩士論文

【摘要】：隨著信息技術的提高,電子商務及網絡社群等新興商業(yè)模式應運而生,互聯網引領的各種商業(yè)模式正悄然改變著人們的生活方式。網絡的深入應用,使互聯網進入了各個行業(yè),并給人們的生活帶來了革命性的改變。近幾年,互聯網牽手傳統金融行業(yè),一個新興的金融模式——互聯網金融相伴而生。互聯網金融在技術的浪潮中得到快速的發(fā)展。時下,“余額寶”、“百發(fā)百賺”等互聯網理財產品的不斷涌現,使得互聯網理財行業(yè),甚至是傳統理財行業(yè)的競爭變得日益加劇。面對激烈的市場競爭,如何真實地了解互聯網理財者的購買需求,利用有針對性的策略來提高互聯網理財產品競爭力,從而更加有效地影響理財者的購買意愿,促進理財者購買是十分值得研究和探討的。盡管國內外學者已從對傳統金融的影響、商業(yè)模式創(chuàng)新、風險及監(jiān)管等角度,對互聯網理財產品進行了一些有價值的探索,但是有關互聯網理財產品購買行為的研究多是描述性分析,研究的理論視角也不夠清晰,而關于互聯網理財產品購買意愿的實證研究更是少之又少,有鑒于此,為使學術界和實務界更準確地了解互聯網理財產品購買意愿的影響因素的構成及重要性程度,本文在確定互聯網理財產品購買意愿的影響因素之后,采用RBF神經網絡評價方法來模擬互聯網理財產品的購買過程,并根據實證結果對互聯網理財產品的競爭力提升方面提出全面系統的合理化建議。具體而言,本研究的主要內容如下:第一章在介紹互聯網金融及互聯網理財相關理論的基礎上提出本文的研究問題,指出本研究的研究意義和目的,并介紹本研究的主要內容、研究方法及本文創(chuàng)新點。第二章梳理關于互聯網理財、購買意愿、RBF神經網絡的相關理論文獻。第三章詳述本文理論研究的方法、問卷的設計情況、調研數據的整理,并對問卷樣本做描述性統計分析,進而得出關于問卷采樣效果的結論。第四章選用因子分析及信度效度檢驗方法,驗證數據的有效性,考量各影響因素之間的相關性,進而驗證因素選取的適用性。第五章基于RBF神經網絡模型,來模擬互聯網理財產品的購買過程,進而得出各因素的重要性排序結果,并通過對互聯網理財產品各影響因素的深入分析,為互聯網理財產品在競爭力提升方面提出相關合理化建議。第六章為全文的總結與展望。
[Abstract]:With the improvement of information technology, new business models such as e-commerce and network community emerge as the times require, and various business models led by the Internet are quietly changing people's way of life. With the deep application of Internet, the Internet has entered various industries and brought revolutionary changes to people's lives. In recent years, the Internet hand in hand with the traditional financial industry, a new financial model-Internet finance accompanies. Internet finance is developing rapidly in the tide of technology. Nowadays, the continuous emergence of Internet financial products such as Yu'e Bao and Baifa hundred profit makes the competition between the Internet financing industry and even the traditional financial management industry more and more intense. In the face of fierce market competition, how to truly understand the purchase needs of Internet financial managers and use targeted strategies to improve the competitiveness of Internet financial products, so as to more effectively affect the willingness of financial managers to buy, It is worth studying and discussing to promote the money manager purchase. Although scholars at home and abroad have made some valuable explorations on Internet financial products from the perspectives of influence on traditional finance, innovation of business model, risk and supervision, etc. However, the research on the purchase behavior of Internet financial products is mostly descriptive analysis, and the theoretical perspective is not clear enough, and the empirical research on the purchase intention of Internet financial products is rare. In order to make the academic and practical circles understand more accurately the composition and importance of the factors influencing the purchase intention of Internet financial products, this paper determines the influencing factors of the intention of purchase of Internet financial products. The RBF neural network evaluation method is used to simulate the purchase process of Internet financial products, and based on the empirical results, a comprehensive and systematic rationalization proposal is put forward to enhance the competitiveness of Internet financial products. Specifically, the main contents of this study are as follows: the first chapter introduces the related theories of Internet finance and Internet financing, points out the significance and purpose of this research, and introduces the main contents of this study. Research method and innovation of this paper. The second chapter combs the related theoretical literature about Internet financing, purchase intention and RBF neural network. In the third chapter, the methods of theoretical research, the design of the questionnaire, the arrangement of the survey data, and the descriptive statistical analysis of the questionnaire samples are described in detail, and then the conclusion about the sampling effect of the questionnaire is obtained. In the fourth chapter, factor analysis and reliability validity test are used to verify the validity of the data and the correlation between the factors, so as to verify the applicability of the selection of factors. The fifth chapter is based on RBF neural network model to simulate the purchase process of Internet financial products, and then get the ranking results of the importance of each factor, and through the in-depth analysis of the impact factors of Internet financial products. For the Internet financial products in the competitiveness of the relevant rationalization of the recommendations. The sixth chapter is the summary and prospect of the full text.
【學位授予單位】：天津大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：F724.6;F832.2

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