Table 1.

Summary of recent studies on AR adoption in the retail and marketing domain

ArticlePurposeMethodsTheory usedFindings
Pantano et al. (2017) To investigate the effect of AR technologies on consumer behavior within online retail environmentsExperiment (sample size = 318)TAMTechnology characteristics directly impact perceived ease of use, perceived enjoyment, and perceived usefulness. Technology impacts consumers’ online shopping experience and purchase decision-making process in terms of collecting information and interacting with the accessible information. The importance of entertainment varies in different cultures
Chandra and Kumar (2018) To identify various factors that influence the adoption intention of AR from an organizational perspectiveSurvey (sample size = 107)Technology–organization–environment frameworkTechnology competence, relative advantage, top management support and consumer readiness play significant roles in influencing an organization’s adoption intention of AR for e-commerce
Rauschnabel et al. (2018) To investigate the factors driving the adoption of augmented reality smart glasses (ARSGs)Mixed method (experiment followed by qualitative research)TAM and gratifications theoryExpected utilitarian, hedonic, and symbolic benefits drive consumers’ reactions to ARSGs. Users are less concerned about how ARSG impacts their privacy compared to ARSG’s impact on the privacy of other people
Fan et al. (2020) To investigate the influence of AR adoption on online consumers’ product attitudesExperiment (sample size = 493)Cognitive load and fluencyAR characteristics (environmental embedding and simulated physical control) reduce consumers’ cognitive load, enhance their cognitive fluency, and improve their product attitude. Product type (search vs experience) moderates these relationships
Perannagari and Chakrabarti (2020) To examine the impact of AR on retailingNon-empirical (literature review)Technology acceptance model (TAM)The study identified eight themes from extant literature, arranged into a conceptual framework to explain the consumers’ decision-making process
Berman and Pollack (2021) To develop a process of successful AR implementationConceptualNonePlanning and implementing AR successfully involves executing six integrated steps
Yavuz et al. (2021) To investigate the factors influencing the usage of mobile AR applicationsMixed method (interviews followed by experiments)NoneThe study identified five constructs that influence the usage of mobile AR applications. The two most important factors are security and privacy. These two are followed by ease of learning, visual quality of the application’s 3D model and ease of use
Lee et al. (2022) To investigate consumers’ adoption intention toward augmented reality-enhanced virtual Try-Ons (VTOs)Survey (sample size = 352)SOR frameworkThe technology attributes of AR-enhanced VTOs exert significant positive influences on adoption intention. The personality traits (sensation-seeking tendency and technology anxiety) moderated the proposed relationships among technology attributes, perceived values, and adoption intentions
Khashan et al. (2023) To comprehend the dynamics of AR adoption in retail in low-income countriesSurvey (sample size = 398)Task-Technology Fit and Unified Theory of Acceptance and Use of Technology2Task-technology fit, performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation and customer innovativeness positively affect shoppers’ behavioral intentions to adopt AR apps in retail. On the other hand, perceived risk negatively affects shoppers’ behavioral intentions to adopt AR apps in retail
von der Au et al. (2023) To investigate the impact of context (the location of AR use) on consumers’ evaluation and judgment of AR-enabled marketingExperimentsNarrative and local presenceContext has a significant impact on plausibility. While plausibility and local presence both are impactful, plausibility has a stronger effect on utilitarian benefits than local presence. On the other hand, local presence has a stronger effect on perceived physical tangibility than plausibility
Rauschnabel et al. (2024) To develop a framework that takes into account AR’s primary characteristics, integrating virtual content into the real worldNon-empirical (conceptual)NoneThe study proposes a 4C framework (consumer, content, context and computing devices) that highlights the importance of and interplay among these four factors
Schultz and Kumar (2024) To identify consumption values determining the use of ARSurvey (sample size = 250)Consumer value theory and TAMMonetary value and social value have no significant effect on consumers’ perception of the usability of an AR app. Hedonic value matters to females only. Informational and convenience values are found to be most important
Current studyTo develop an integrated framework that incorporates both positive factors and negative barriers to explain the usage of AR-enabled mobile applicationsSurvey (sample size = 478)SDT and IRTAR and technology attributes (aesthetics, usefulness, enjoyment, and informativeness) positively impact AR usage intention. Among the barriers, value and risk barriers significantly impact adoption intention. While image and usage barriers do not significantly impact adoption intention. Occupational differences also moderate the influence of these determinants (motivations and barriers) on consumers’ behavioral intentions
Source(s): Authors’ creation

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