Augmented reality shopping application usage: The influence of attitude, value, and characteristics of innovation
Introduction
The rapid growth of online retail has provided consumers with more conveniences. However, the service experience is limited because consumers can neither interact with nor form realistic expectations of the products. Therefore, simulating the shopping experience of real products or environments is particularly important (Fan et al., 2020).
Augmented reality (AR) is a new interactive technology (Poushneh, 2018). It can superimpose virtual 3D models of real products into the real world such as human bodies or objects, and people can manipulate these virtual 3D models by rotating, shifting, and enlarging them (Poushneh and Vasquez-Parraga, 2017). Consequently, many e-commerce platforms have begun to invest in the development of various forms of AR shopping applications (ARSAs) using AR technology (Fan et al., 2020).
Due to the current COVID-19 pandemic, countries all over the world have adopted necessary anti-epidemic measures and recommendations such as “closed isolation” and “maintaining social distance”, and consumer behavior is undergoing tremendous changes (Donthu and Gustafsson, 2020). Therefore, the academic community has conducted research on consumer buying behavior. Most scholars have made corresponding research contributions mainly to consumers' panic buying behavior (Laato, 2020; Prentice et al., 2020, 2021; Naeem, 2021; Islam et al., 2021; Omar et al., 2021). At the same time, because of the pandemic, consumers' consumption in physical stores has been severely affected. Thus, more consumers are switching from brick-and-mortar stores to online consumption (Pantelimon et al., 2020). As a result, some researchers have conducted related research in the field of online consumption such as e-retail and e-commerce, and mobile meal ordering programs (Jafarzadeh et al., 2021; Tran, 2021; Guthrie et al., 2021; Dirsehan and Cankat, 2021). Consequently, ARSAs are showing extremely important value (Kirk and Rifkin, 2020). They can confer convenience, functionality, sociality, and other benefits to consumers, which are becoming more prominent considering the COVID-19 pandemic.
Although ARSAs can provide various benefits to the online shopping market, the actual adoption of ARSAs has not yet reached expectations and not been widely used (Yim and Park, 2019). One reason is that ARSA is an application tool for innovative technologies, and potential adopters still have concerns about its use. Other researchers also highlighted that problems such as digital fatigue, installation difficulties, slow response speed, and privacy security caused the slow application of ARSAs (Feng and Xie, 2019; Yim and Park, 2019). More importantly, these benefits can only be achieved if consumers are willing to adopt ARSAs. This view agrees with the “critical mass” theory proposed by Markus (1994); that is, individual choices must be considered in the context of their community or organization. As an increasing number of individuals adopt innovative technologies (tools) in the system (organization), such innovation will be considered more and more beneficial to adopters and potential buyers (Van Slyke et al., 2007).
Recently, to understand consumers' acceptance intention of AR technology and ARSAs, much academic research has been conducted. Some researchers have adopted the technology acceptance model and its extended theory to understand. Moreover, they have examined the following factors influencing consumers' adoption of AR technology and ARSAs: perceived ease of use, perceived usefulness (Huang and Liao, 2015; Pantano et al., 2017; Plotkina and Saurel, 2019; Rese et al., 2017; Holdack et al., 2020; Hinsch et al., 2020; Qin et al., 2021), expanded entertainment, fun, aesthetics, visual imagery, and multifaceted quality attributes (Li and Fang, 2020; Park and Yoo, 2020; Chiu et al., 2021; Jung et al., 2021), technical anxiety, privacy security and perceived risk (Kim and Forsythe, 2009; Zhang et al., 2019; Yoo, 2020; Bonnin, 2020). In addition, some scholars have studied the influence of factors related to hedonic and utilitarian attributes on consumer participation in AR applications and AR technology application products, brand attitudes, use intentions or decision-making behaviors (Rauschnabela et al., 2019; Hinsch et al., 2020; Bonnin, 2020; Qin et al., 2021; Nikhashemi, 2021). Other researchers based their studies on the situated cognition theory to explain consumers' attitudes, intentions, and loyalty to AR technology and its applications (Chylinski et al., 2020; Fan et al., 2020; Hilken et al., 2020; Sung, 2021).
This study extends the current understanding of consumers' intentions of using ARSAs by introducing innovation diffusion, attitude, and perceived value theories. These theories are selected because they address the key concerns of consumers when adopting new technology. First, innovation diffusion theory focuses on explaining how innovative technologies are accepted and spread among consumers (Plotkina and Saurel, 2019; Yuen et al., 2018). The spread of innovation is influenced by the following features or characteristics of ARSAs: (1) relative advantages compared with existing alternatives, (2) compatibility with users, (3) complexity in users' adoption, (4) trialability, and (5) observability, which reflects the ease of identifying the benefits and learning how to use ARSAs from others. Second, perceived value is a predictor of customer adoption behavior (Yang et al., 2016). This theory explains a consumer's intention to use ARSAs from a utility perspective. If ARSAs can provide consumers with good value (i.e., economic, functional, social, and hedonic utility) compared with existing channels, then the consumer intention to adopt ARSAs will be stronger. Finally, we explore the attitude theory. Attitude is a determinant of individual behavioral intentions (Van Slyke et al., 2007). The theory of reasoned action (Fishbein and Ajzen, 1975) states that one's behavioral intentions are largely affected by one's attitude.
This study enriches existing scholarship by synthesizing and applying innovation diffusion theory, perceived value theory, and attitude theory, and introduced various paradigm theories (such as customer utility, social psychology and innovation acceptance). At the same time, this study not only includes the similar attributes of some influencing factors investigated by previous studies, such as complexity (ease of use), relative advantages (usefulness), and attitude to use, but also introduces new variables such as compatibility, observability and trialability, and value attributes. Therefore, this research enriches the existing academic research and explores the key issues when consumers adopt AR shopping application technology. In addition, this study provides a logical causal structure, i.e., based on the “belief-attitude-intention” relationship and further introduces perceived value, thereby further expanding this causal relationship. In this regard, this study can better explain how innovative technologies are accepted and spread among consumers as compared to previous studies. Especially when the COVID19 epidemic is still on-going and escalating in many countries, the application value of ARSAs is more prominent, and further exploration of the factors and methods that can more effectively promote the use and spread of ARSAs by consumers confers more academic significance and practical value.
Section snippets
Theories and model
This study uses innovation diffusion, attitude, and perceived value theories to explore the determinants of consumers' intention to use ARSAs, propose a research model, and determine the relationship between structural factors in each theory and their relationships. Table 1 summarizes the applied theories.
We designed a model through the explanation of the three theories (Fig. 1). The model depicts the determinants of consumers' adoption of ARSAs and explains their relationship.
This study
Measurement items
Table 2 shows the measurement items using a 5-point Likert scale and related references used to develop and operationalize the constructs.
Survey administration
The subjects of this study are shoppers in China. The measurement items in survey questionnaire were developed with reference to the literature. The study first translated the English questionnaire into Chinese, and then translated it back into English. After that, this study compared the two English versions and checked for differences. This is to ensure the
Confirmatory factor analysis
Confirmatory factor analysis is conducted to ascertain the model's goodness-of-fit, reliability, and validity. The fit indices at the bottom of Table 4 demonstrate a good model fit.
The factor loadings (λ) and the composite reliabilities (CRs) of the constructs demonstrate reliability because they are higher than the recommended critical values of 0.70 and 0.80, respectively (Hair et al., 2009). This research also performed reliability analysis. The Cronbach's α values are all higher than the
Conclusion, limitations and future research
This study enriches existing scholarship by synthesizing and applying innovation diffusion theory, perceived value theory, and attitude theory, and by introducing various paradigm theories to expand existing research. In addition, this study introduces perceived value on the basis of the “belief-attitude-intention” relationship, thereby further expanding this causal relationship. The academic contribution and significance of this research are as follows.
First, by synthesizing and applying
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