Motivations and barriers to embracing augmented reality: An exploratory study with Vietnamese retailers
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Received May 5, 2022;Accepted June 27, 2022;Published July 15, 2022
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DOIhttp://dx.doi.org/10.21511/im.18(3).2022.03
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Article InfoVolume 18 2022, Issue #3, pp. 28-37
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Cited by1 articlesJournal title: Procedia Computer ScienceArticle title: A systematic review on the use of augmented reality in management and businessDOI: 10.1016/j.procs.2023.10.073Volume: 225 / Issue: / First page: 861 / Year: 2023Contributors: Dorota Walentek, Leszek Ziora
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The most crucial key to successfully approaching customers is enhancing the interaction experience between customers and retailers. This study explores the motivations for adopting augmented reality (AR) in retailing small and medium-sized retailers in Vietnam. A structured questionnaire was delivered to a total sample of 302 Vietnamese retailers and got 215 clean and valid responses. The survey was conducted both online and offline for ten months, from February 2021 to December 2021. The chosen surveyors are retailing managers and owners of retailing firms. These firms sell fashion products, technology gadgets, and household products. The data were statistically analyzed using Smart PLS software and the partial least equation structural model. The findings indicate three direct, positive, and significant factors that influence the retailer’s AR adoption, including (1) organizational attitude toward AR, (2) organizational innovativeness, and (3) competition pressure in which organizational attitude toward AR and organization innovativeness are two critical motivational drivers. The competition pressure has been identified as the challenge barrier. The cost barriers affect organizational attitude toward AR but do not significantly influence AR adoption. Along with theoretical contributions, this paper also gave some theoretical and practical implications for retailers who have the intention to adopt AR and integrate AR into their current retailing system.
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JEL Classification (Paper profile tab)M15, M31, O33
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References37
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Tables4
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Figures2
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- Figure 1. Proposed research model
- Figure 2. Structural model
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- Table 1. Outer loadings, Cronbach’s alpha, composite reliability, and AVE
- Table 2. HTMT
- Table 3. R2, Q2, and SMRM
- Table 4. Hypotheses testing result
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Conceptualization
Hai Ninh Nguyen
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Data curation
Hai Ninh Nguyen
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Formal Analysis
Hai Ninh Nguyen
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Funding acquisition
Hai Ninh Nguyen
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Investigation
Hai Ninh Nguyen
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Methodology
Hai Ninh Nguyen
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Project administration
Hai Ninh Nguyen
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Resources
Hai Ninh Nguyen
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Software
Hai Ninh Nguyen
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Supervision
Hai Ninh Nguyen
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Validation
Hai Ninh Nguyen
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Visualization
Hai Ninh Nguyen
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Writing – original draft
Hai Ninh Nguyen
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Writing – review & editing
Hai Ninh Nguyen
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Conceptualization
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