淘宝推荐策略对消费者购买意愿影响研究

发布时间：2018-12-07 21:15

【摘要】：如今情况下,网购已经成为普遍的购物方式,并且消费者在网购商品时的个性化特征也愈加明显。随着信息技术的日渐成熟,互联网也进入了飞速发展的阶段,消费者面临的也由原本的信息匮乏变成了信息过载。对于网购平台以及商家来讲,让自己的商品信息从海量信息中脱颖而出并被消费者获取是一件非常困难的事情。个性化推荐技术就是在这种现实情况下出现并逐渐发展,并已经被各大电商网站应用于向不同用户提供个性化的商品推荐。本文基于这样的背景,选取了我国最大的B2C购物平台淘宝网作为研究对象,选取淘宝最有代表性的四种推荐策略,探讨淘宝网提供的个性化推荐策略与消费者购买意愿之间的内部作用机制。本文对个性化推荐、感知推荐质量、感知风险、购买成本、购买意愿等概念的国内外研究情况进行了分析和梳理,提出了淘宝网个性化推荐策略促进消费者购买意愿的模型与假设,确定每一因素的测量维度。在此基础上,本文采用成熟量表进行问卷设计,并通过问卷法完成数据收集,使用统计学软件SPSS20.0进行了描述性分析、相关分析及回归分析,对模型假设进行了验证。数据分析结果表明,淘宝网提供的四种个性化推荐策略均对消费者购买意愿起到正向的促进作用,但达到的效果略有不同;购买成本起到了中介作用;感知成本起到了调节作用。最后,本文还在数据分析结果的基础上进行了讨论,并结合现实情况对淘宝网及网络零售商提出了营销管理建议,这将起到一定的现实启示意义。
[Abstract]:Nowadays, online shopping has become a common way of shopping, and consumers in the online shopping personalized features are increasingly obvious. With the maturing of information technology, the Internet has entered the stage of rapid development, consumers are facing from the original lack of information to information overload. For online shopping platforms and merchants, it is very difficult to make their commodity information stand out from the mass of information and be obtained by consumers. Personalized recommendation technology appears and develops gradually in this kind of reality, and has been used by various e-commerce websites to provide personalized product recommendation to different users. Based on this background, this paper selects Taobao, the largest B2C shopping platform in China, as the research object, and selects the four most representative recommendations of Taobao. This paper probes into the internal mechanism between the personalized recommendation strategy provided by Taobao and the consumer's willingness to buy. This paper analyzes and combs the concepts of personalized recommendation, perceived recommendation quality, perceived risk, purchase cost, purchase intention and so on at home and abroad. This paper puts forward the model and hypothesis of Taobao personalized recommendation strategy to promote consumers' willingness to buy, and determines the measurement dimension of each factor. On this basis, this paper designed the questionnaire with mature scale, completed the data collection by questionnaire method, and used the statistical software SPSS20.0 for descriptive analysis, correlation analysis and regression analysis to verify the hypothesis of the model. The results of data analysis show that the four personalized recommendation strategies provided by Taobao all play a positive role in promoting consumers' purchase intention, but the effect is slightly different, and the purchase cost plays an intermediary role. Perceived costs act as a regulator. Finally, this paper discusses the results of data analysis, and puts forward some suggestions on the marketing management of Taobao and online retailers, which will be of practical significance.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F724.6;F713.55

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