网络品牌视角下个性化推荐对消费者购买意愿的影响研究—以大学生为例
摘 要
互联网技术的成熟推动了电子商务的高速发展，网络购物逐渐成为大多数老百姓首选的购物方式。同时，信息过载严重影响了消费者的决策效率，成为了主流电子商务网站亟待解决的难题。在此背景下，个性化推荐系统应运而生。本文将梳理中外学者的相关文献，将个性化推荐系统定义为个性化、信息编排、推荐时机和推荐方式四个维度。以上述四个维度为自变量，消费者的购买意愿为因变量，网络品牌为调节变量建立研究模型。根据研究模型设计问卷，并向高校大学生发放问卷。通过线上和线下两种方式进行数据的收集。运用SPSS22软件对数据进行多元回归分析和层次回归分析，根据分析结果得出如下结论：个性化推荐系统从四个不同的维度对消费者的购买意愿产生了不同程度的正相关影响；网络品牌仅在推荐时机维度与消费者的购买意愿间起调节作用。最后，根据研究结论向电商网站提出完善网站个性化推荐系统建设的针对性意见，具有一定的参考价值。
关键词：个性化推荐；购买意愿；网络品牌；回归分析法
Research on the Influence of Personalized Recommendations on Consumers#39; Purchase Intention from the Perspective of Internet Brands--A Case Study of College Students
ABSTRACT
The maturity of Internet technology has promoted the rapid development of e-commerce, and online shopping has gradually become the preferred shopping method for most ordinary people. Meanwhile, information overload has seriously affected the decision-making efficiency of consumers and has become an urgent problem for mainstream e-commerce websites. In this context, a personalized recommendation system came into being. This paper will sort out the relevant literature of Chinese and foreign scholars, and define the personalized recommendation system as four dimensions: personalization, information layout, recommendation timing and recommendation method. Taking the four dimensions of personalized recommendation system as independent variables, consumers#39; purchasing intention as dependent variables, and network brands as regulatory variables, a research model was established. The questionnaire was designed based on the research model and questionnaires were distributed to college students. Data collection is done both online and offline. SPSS22 was used to perform multiple regression analysis and hierarchical regression analysis on the data. Based on the analysis results, the following conclusions were drawn: The personalized recommendation system has positive correlation effects on consumers#39; purchase intention from four different dimensions; the network brand only plays a regulatory role between the recommendation timing dimension and the purchase intention. Finally, according to the conclusions of the research, the author puts forward targeted suggestions for improving the personalized recommendation system for e-commerce websites, which has certain reference value.
Key words: personalized recommendation; purchase intention; network brand; regression analysis
文献综述
电子商务网站的个性化推荐系统，某种意义上缓解了数据信息过载的现象，为网站用户节省了盲目浏览的时间成本，提高了决策效率。它作为一种新型营销手段，从不同的维度影响着消费者购买过程中的主观意愿。且本文将网络品牌视作重要的外部因素，并假设它在上述影响关系中起一定的调节作用。以下，将从个性化推荐、消费者购买意愿和网络品牌的角度进行综述，并以此作为本文的理论基础。
1.1 个性化推荐
二十世纪九十年代，互联网技术的发展带动了世界范围内电子商务的迅速繁荣，这种繁荣意味着各大线上购物网站的商品数据量也在短时间内不断攀升。为防止消费者被淹没在商品信息的海洋中而造成的消费者流逝，推荐系统的雏形--解决用户处理过载信息的搜索引擎开始出现。一般认为，推荐系统是指购物网站向消费者提供商品推荐服务并为其购买行为提供参考建议的技术。而个性化荐系统能在各式各样的推荐系统中脱颖而出，究其根本是因为它以海量的数据挖掘作为基础，模拟现实场景中的销售人员，根据消费者当前所处的情景以及购物需求为他们提供因人而异的个性化推荐服务，帮助他们做出合理的消费决策。
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