| 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). Amazon’s "Flow" feature and the SnapShop Showroom system offer organic combinations of online shopping and AR. 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 B2C system platform, which has been studied using various research methods (behavioral experiments, brain-computer connection technology, and psychological measurement), has created a realistic large-scale environment using AR technology. Studies of this platform have led to an original technology acceptance model and have systematically advanced a technology acceptance mental model of online shopping.This study was divided into four sub-studies. Study 1 was a comparative study of two shopping modes (a normal online shopping platform and an AR online shopping platform). Based on both domestic and foreign online shopping systems, the study used behavioral experiments and a brain-computer interface to investigate the following issues:(1) differences in the consumer’s attitudes toward the two shopping modes; (2) differences in consumer concentration and emotional human factors between the two shopping modes; and (3) differences in consumer purchase intention between the two shopping patterns. Study 2 considered AR technology while conducting market segmentation research based on online shopping lifestyles. First, the researcher created an online shopping lifestyle scale. Second, the survey participants conducted market segmentation according to their online shopping styles. Finally, the participants were classified according to aspects of their online shopping style using cluster analysis. The study determined two AR online shopping lifestyles. The researchers examined the two shopping styles in terms of their market segment-specific factors. Study 3 used the technology acceptance model of online shopping as the foundation for a proposed technology acceptance mental model (TAMM) based on AR. First, the researcher constructed an experimental AR online shopping platform with two conditions: marker-tracking AR shopping and markerless-tracking AR shopping. Second, the researcher verified the AR-based TAMMs. Finally, the researcher established the AR TAMMs for the two types of lifestyles. Using these models as marketing research, study 4 conducted market analyses, consumer analyses, competitor analyses, and psychological planning of advertising and marketing.The results showed that (1) Consumers have a good implicit attitude toward AR online shopping. The shopping mode affects consumers’attention and concentration: their attention and concentration are higher when using the AR online mode than when using the ordinary online mode. The shopping mode also affects the Delta indicator of nervous human factors. The Delta for the AR online mode is lower than the Delta for the ordinary online mode. Furthermore, the shopping mode also affects purchase intention. The purchase intention for the AR online mode is higher than the purchase intention for the ordinary online mode. (2) There are two types of consumers who use AR online shopping:the loyalty lifestyle consumer and the random lifestyle consumer. The loyalty lifestyle consumer is characterized by greater deep psychological motivation, psychological comparison effects, influence and dominance of scenario and influence and dominance of psychological inducement. The loyalty lifestyle consumer is likely to reside in a prefecture-level city and work or study in the provincial capital city (or another big city). He or she shops online frequently, and their online shopping process often involves some specific business. The significant features of this type of consumer are as follows:1) They have a higher self-concept regarding AR online shopping; 2) They show different behaviors during AR online shopping compared with other shopping modes; 3) They pay more attention to after-sales, express delivery, financing, and shopping relationships, and they become addicted to online shopping more easily than other consumers; 4) They enjoy shopping online, and they show a high degree of consumer involvement. These consumers think that this mode of shopping has become a consumption trend, and they derive self-satisfaction from the shopping process. In comparison, the random lifestyle consumer is characterized by lower deep psychological motivation and a reduced psychological comparison effect, nfluence and dominance of scenario and influence and dominance of psychological inducement. The random lifestyle consumer is likely to reside in a town or village and work or study in a prefecture-level city. This consumer type has a low frequency of online shopping, and their online shopping process does not often involve a specific business. The significant features of this type of consumer are as follows:1) They have a lower self-concept regarding AR online shopping; 2) They do not show different behaviors during AR online shopping compared with other shopping modes. This type of consumer shopping methods does not vary according to the shopping mode; 4) They do not pay attention to after-sales, express delivery, financing, or shopping relationships, and they do not easily become addicted to online shopping; 4) They do not experience online shopping as fun, and they show a low degree of consumer involvement. (3) Based on an invariance inspection, the researcher established the relevant TAMMs for the loyalty lifestyle consumer and the random lifestyle consumer. 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. (4) Through the market investigation and the previous analysis, this study found that the three types of consumers (A, B, and C) require different marketing strategies. Experiential marketing, entertainment marketing, event marketing, systems for consumer evaluations of products, combinations of online and offline marketing, and the marketing of popular elements become effective integrated marketing methods.The theoretical significance of the study is reflected in two ways:(1) The study is a blend of management, psychology, consumer behavioral science and computer science and technology. The shopping-related psychological cognition and the emotions associated with B2C e-commerce are explored in an interdisciplinary manner; (2) This study tentatively puts forward a technology acceptance mental model (TAMM) for AR technology. The practical significance of the study is embodied in two ways:(1) The study examines the technological and psychological advantages of AR-based online shopping; (2) The study provides Internet marketing paths based on psychological cognition and emotion, performance-price ratio and online shopping addiction to inform the "fourth retail revolution". The study of Cyber-Physical System based on AR online shopping is important pathway to connect flexible manufacturing and personalized customization. |
PDF Full Text Request