基于增强现实网络购物的技术接受心理模型:互联网+的生活型态研究
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摘要
互联网+是互联网领域信息物理系统研究的一种新生力量,它体现的是心理学应用领域基于互联网新兴技术的创新机制和生活型态。在"互联网+"的依托下,增强现实(Augmented reality,AR)作为一种新型技术已经迅速拓展到管理学、心理学、消费者行为学等领域,而且增强现实技术也被列入改变未来购物方式的三大技术之一(分别为QR码,增强现实和移动支付)。目前,在这些系统中,对于技术的研发正在加速成型,但相关的内部心理机制研究却显得相对滞后,人们对整个购物过程的心理因素也非常重要,而不仅仅在对设备和技术的感知。研究者确认了B2C增强现实网络购物的心理优势效应并且主要从两个层面初步构建了增强现实网购实验平台:有标识的增强现实购物系统和无标识的增强现实购物系统。首先,基于增强现实技术,研究主要进行了网购生活型态的市场细分研究。在自编的网购生活型态量表的基础上,研究者将调查对象按不同的网购生活型态进行市场细分,采用聚类分析将参与调查的对象以生活型态因子作为变量进行分类,获得两个网购生活型态聚类类型。其次,研究者检验了基于增强现实技术的技术接受心理(TAMM)模型,并且建立了两种生活型态下的增强现实TAMM模型。忠诚型网购者TAMM模型是由AR系统可用性、AR网购心理性价比、AR网购成瘾倾向、网购消费者卷入程度、网购消费者自我概念、网购消费者风险感知、网购消费者决策风格和AR网购购买意向构成的非递归模型。随机型网购者TAMM模型是由AR系统可用性、AR网购成瘾倾向、网购消费者风险感知和AR网购购买意向构成的非递归模型。忠诚型和随机型消费者的TAMM模型拟合良好。在忠诚型网购者的TAMM模型中,AR网购系统可用性、心理性价比、网购消费者卷入程度、网购消费者风险感知在购物过程中起了核心作用。在随机型网购者的TAMM模型中,AR网购系统可用性、网购消费者风险感知在购物过程中起了核心作用。该研究对于B2C电子商务心理研究具有积极的借鉴意义。
Internet+ is a kind of new force in the field of Internet Cyber-Physical System. It reflects innovation mechanism and lifestyle based on Internet emerging technology in applications of psychology. Based on "Internet +", the new technology of augmented reality(AR) has extended rapidly to management, psychology, consumer behavior, and other areas. AR technology is one of three major technologies that were identified as likely to change the future of shopping(the others are QR codes and mobile payment). At present, technology research and development are accelerating rapidly to shape these systems, but relevant research into the internal psychological mechanisms associated with such systems is lagging behind. Information about the psychological aspects of the entire shopping process and not just the shopper's perceptions of the equipment and technology involved are also very important. The researcher confirmed psychological advantage effect of augmented reality based on online shopping of B2C and constructed an experimental AR online shopping platform with two conditions, namely marker-tracking AR shopping and markerless-tracking AR shopping. First, the study considered AR technology while conducting market segmentation research based on online shopping lifestyles. Based on online shopping lifestyle scale, the survey participants conducted market segmentation according to their online shopping styles. The participants were classified according to aspects of their online shopping style using cluster analysis. The study determined two AR online shopping lifestyles. Secondly, the researcher verified the AR-based technology acceptance mental model(TAMM), and established the AR TAMMs for the two types of lifestyles. The TAMM for the loyalty lifestyle consumer is a non-recursive model involving in the AR system availability, the AR psychological cost performance, the AR online addiction tendency, consumer involvement in online shopping, the online consumer's self-concept, the online consumer's risk perception, the online consumer's decision-making style and the online purchase intention. The TAMM for the random lifestyle consumer is a non-recursive model involving the AR system availability, the AR online addiction tendency, the online consumer's risk perception and the online purchase intention. The respective TAMMs' fits are good for both the loyalty lifestyle consumer and the random lifestyle consumer. For the TAMM of the loyalty lifestyle consumer, the AR system availability, the AR psychological cost performance, consumer involvement in online shopping, the online consumer's risk perception play a central role in the process of shopping. For the TAMM of the random lifestyle consumer, the AR system availability, the online consumer's risk perception play a central role in the process of shopping. The research has positive significance for e-commerce psychological research of B2C.
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