IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v124y2017icp306-319.html
   My bibliography  Save this article

How augmented reality apps are accepted by consumers: A comparative analysis using scales and opinions

Author

Listed:
  • Rese, Alexandra
  • Baier, Daniel
  • Geyer-Schulz, Andreas
  • Schreiber, Stefanie

Abstract

Increasingly, retailers rely on interactive technologies to improve consumers' shopping experiences. On the one side, interactive kiosks and smart mirrors make use of dedicated devices and software to explain, configure, and recommend products. On the other side, computer programs – so-called apps – are installed on the consumer's own device for the same purpose. They can be used at home, or – if installed on a mobile device – in retail outlets or on the move. In all cases, augmented reality (AR) can support these purposes by placing virtual content (e.g. new furniture) in a real environment (the consumer's home). The overall perception and acceptance toward such interactive technologies are discussed in this paper. Users' perceptions and experiences are measured by applying a modified technology acceptance model (TAM). Four experiments, two with marker-based and two with markerless AR apps are presented to support the generalization of the results, the measurement models and the measurement approach. The results are satisfactory with regard to the robustness of the TAM model. However, the relative importance of hedonic (enjoyment, pleasure, fun) and utilitarian (information) aspects varies for different kinds of AR apps and has to be considered for improvement to occur. From a measurement point of view the acquiescence bias has to be dealt with when developing scale items.

Suggested Citation

  • Rese, Alexandra & Baier, Daniel & Geyer-Schulz, Andreas & Schreiber, Stefanie, 2017. "How augmented reality apps are accepted by consumers: A comparative analysis using scales and opinions," Technological Forecasting and Social Change, Elsevier, vol. 124(C), pages 306-319.
  • Handle: RePEc:eee:tefoso:v:124:y:2017:i:c:p:306-319
    DOI: 10.1016/j.techfore.2016.10.010
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162516304528
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.techfore.2016.10.010?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Viswanath Venkatesh, 2000. "Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model," Information Systems Research, INFORMS, vol. 11(4), pages 342-365, December.
    2. Ha, Sejin & Stoel, Leslie, 2009. "Consumer e-shopping acceptance: Antecedents in a technology acceptance model," Journal of Business Research, Elsevier, vol. 62(5), pages 565-571, May.
    3. Barbara H. Wixom & Peter A. Todd, 2005. "A Theoretical Integration of User Satisfaction and Technology Acceptance," Information Systems Research, INFORMS, vol. 16(1), pages 85-102, March.
    4. Fred D. Davis & Richard P. Bagozzi & Paul R. Warshaw, 1989. "User Acceptance of Computer Technology: A Comparison of Two Theoretical Models," Management Science, INFORMS, vol. 35(8), pages 982-1003, August.
    5. Porter, Constance Elise & Donthu, Naveen, 2006. "Using the technology acceptance model to explain how attitudes determine Internet usage: The role of perceived access barriers and demographics," Journal of Business Research, Elsevier, vol. 59(9), pages 999-1007, September.
    6. Hausman, Angela V. & Siekpe, Jeffrey Sam, 2009. "The effect of web interface features on consumer online purchase intentions," Journal of Business Research, Elsevier, vol. 62(1), pages 5-13, January.
    7. Heshan Sun & Ping Zhang, 2008. "An exploration of affect factors and their role in user technology acceptance: Mediation and causality," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 59(8), pages 1252-1263, June.
    8. Chong, Alain Yee-Loong, 2013. "Mobile commerce usage activities: The roles of demographic and motivation variables," Technological Forecasting and Social Change, Elsevier, vol. 80(7), pages 1350-1359.
    9. Domina, Tanya & Lee, Seung-Eun & MacGillivray, Maureen, 2012. "Understanding factors affecting consumer intention to shop in a virtual world," Journal of Retailing and Consumer Services, Elsevier, vol. 19(6), pages 613-620.
    10. Chen, Lei-Da & Tan, Justin, 2004. "Technology Adaptation in E-commerce:: Key Determinants of Virtual Stores Acceptance," European Management Journal, Elsevier, vol. 22(1), pages 74-86, February.
    11. Zaichkowsky, Judith Lynne, 1985. "Measuring the Involvement Construct," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 12(3), pages 341-352, December.
    12. Pantano, Eleonora & Servidio, Rocco, 2012. "Modeling innovative points of sales through virtual and immersive technologies," Journal of Retailing and Consumer Services, Elsevier, vol. 19(3), pages 279-286.
    13. Demirkan, Haluk & Spohrer, Jim, 2014. "Developing a framework to improve virtual shopping in digital malls with intelligent self-service systems," Journal of Retailing and Consumer Services, Elsevier, vol. 21(5), pages 860-868.
    14. Javornik, Ana, 2016. "Augmented reality: Research agenda for studying the impact of its media characteristics on consumer behaviour," Journal of Retailing and Consumer Services, Elsevier, vol. 30(C), pages 252-261.
    15. Gurtner, Sebastian & Reinhardt, Ronny & Soyez, Katja, 2014. "Designing mobile business applications for different age groups," Technological Forecasting and Social Change, Elsevier, vol. 88(C), pages 177-188.
    16. Pan, Yue & Zhang, Jason Q., 2011. "Born Unequal: A Study of the Helpfulness of User-Generated Product Reviews," Journal of Retailing, Elsevier, vol. 87(4), pages 598-612.
    17. Choi, Jaewon & Lee, Hong Joo & Sajjad, Farhana & Lee, Habin, 2014. "The influence of national culture on the attitude towards mobile recommender systems," Technological Forecasting and Social Change, Elsevier, vol. 86(C), pages 65-79.
    18. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    19. Pantano, Eleonora & Naccarato, Giuseppe, 2010. "Entertainment in retailing: The influences of advanced technologies," Journal of Retailing and Consumer Services, Elsevier, vol. 17(3), pages 200-204.
    20. Kim, Jiyeon & Forsythe, Sandra, 2008. "Adoption of Virtual Try-on technology for online apparel shopping," Journal of Interactive Marketing, Elsevier, vol. 22(2), pages 45-59.
    21. Hyunae Lee & Namho Chung & Timothy Jung, 2015. "Examining the Cultural Differences in Acceptance of Mobile Augmented Reality: Comparison of South Korea and Ireland," Springer Books, in: Iis Tussyadiah & Alessandro Inversini (ed.), Information and Communication Technologies in Tourism 2015, edition 127, pages 477-491, Springer.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pantano, Eleonora & Rese, Alexandra & Baier, Daniel, 2017. "Enhancing the online decision-making process by using augmented reality: A two country comparison of youth markets," Journal of Retailing and Consumer Services, Elsevier, vol. 38(C), pages 81-95.
    2. Rese, Alexandra & Schreiber, Stefanie & Baier, Daniel, 2014. "Technology acceptance modeling of augmented reality at the point of sale: Can surveys be replaced by an analysis of online reviews?," Journal of Retailing and Consumer Services, Elsevier, vol. 21(5), pages 869-876.
    3. Holdack, Eric & Lurie-Stoyanov, Katja & Fromme, Harro Fabian, 2022. "The role of perceived enjoyment and perceived informativeness in assessing the acceptance of AR wearables," Journal of Retailing and Consumer Services, Elsevier, vol. 65(C).
    4. Domina, Tanya & Lee, Seung-Eun & MacGillivray, Maureen, 2012. "Understanding factors affecting consumer intention to shop in a virtual world," Journal of Retailing and Consumer Services, Elsevier, vol. 19(6), pages 613-620.
    5. Yang, Byunghwa & Kim, Youngchan & Yoo, Changjo, 2013. "The integrated mobile advertising model: The effects of technology- and emotion-based evaluations," Journal of Business Research, Elsevier, vol. 66(9), pages 1345-1352.
    6. Pillai, Rajasshrie & Sivathanu, Brijesh & Dwivedi, Yogesh K., 2020. "Shopping intention at AI-powered automated retail stores (AIPARS)," Journal of Retailing and Consumer Services, Elsevier, vol. 57(C).
    7. Julian M. Müller, 2019. "Comparing Technology Acceptance for Autonomous Vehicles, Battery Electric Vehicles, and Car Sharing—A Study across Europe, China, and North America," Sustainability, MDPI, vol. 11(16), pages 1-17, August.
    8. Maria Tsourela & Dafni-Maria Nerantzaki, 2020. "An Internet of Things (IoT) Acceptance Model. Assessing Consumer’s Behavior toward IoT Products and Applications," Future Internet, MDPI, vol. 12(11), pages 1-23, November.
    9. Kerstin Pezoldt & Jana Schliewe, 2012. "Akzeptanz von Self-Service-Technologien: State of the Art," Schmalenbach Journal of Business Research, Springer, vol. 64(2), pages 205-253, March.
    10. Verma, Pranay & Sinha, Neena, 2018. "Integrating perceived economic wellbeing to technology acceptance model: The case of mobile based agricultural extension service," Technological Forecasting and Social Change, Elsevier, vol. 126(C), pages 207-216.
    11. Kang, Hyo Jeong & Shin, Jung-hye & Ponto, Kevin, 2020. "How 3D Virtual Reality Stores Can Shape Consumer Purchase Decisions: The Roles of Informativeness and Playfulness," Journal of Interactive Marketing, Elsevier, vol. 49(C), pages 70-85.
    12. Sohn, Stefanie, 2017. "A contextual perspective on consumers' perceived usefulness: The case of mobile online shopping," Journal of Retailing and Consumer Services, Elsevier, vol. 38(C), pages 22-33.
    13. Hsu, Sheila Hsuan-Yu & Tsou, Hung-Tai & Chen, Ja-Shen, 2021. "“Yes, we do. Why not use augmented reality?†customer responses to experiential presentations of AR-based applications," Journal of Retailing and Consumer Services, Elsevier, vol. 62(C).
    14. Morgan-Thomas, Anna & Veloutsou, Cleopatra, 2013. "Beyond technology acceptance: Brand relationships and online brand experience," Journal of Business Research, Elsevier, vol. 66(1), pages 21-27.
    15. Han, Sang-Lin & An, Myounga & Han, Jerry J. & Lee, Jiyoung, 2020. "Telepresence, time distortion, and consumer traits of virtual reality shopping," Journal of Business Research, Elsevier, vol. 118(C), pages 311-320.
    16. Al-Qeisi, Kholoud & Dennis, Charles & Alamanos, Eleftherios & Jayawardhena, Chanaka, 2014. "Website design quality and usage behavior: Unified Theory of Acceptance and Use of Technology," Journal of Business Research, Elsevier, vol. 67(11), pages 2282-2290.
    17. Garaus, Marion & Wolfsteiner, Elisabeth & Wagner, Udo, 2016. "Shoppers' acceptance and perceptions of electronic shelf labels," Journal of Business Research, Elsevier, vol. 69(9), pages 3687-3692.
    18. Natarajan, Thamaraiselvan & Balasubramanian, Senthil Arasu & Kasilingam, Dharun Lingam, 2017. "Understanding the intention to use mobile shopping applications and its influence on price sensitivity," Journal of Retailing and Consumer Services, Elsevier, vol. 37(C), pages 8-22.
    19. Junic Kim, 2018. "Platform Adoption Factors in the Internet Industry," Sustainability, MDPI, vol. 10(9), pages 1-12, September.
    20. Poncin, Ingrid & Garnier, Marion & Ben Mimoun, Mohammed Slim & Leclercq, Thomas, 2017. "Smart technologies and shopping experience: Are gamification interfaces effective? The case of the Smartstore," Technological Forecasting and Social Change, Elsevier, vol. 124(C), pages 320-331.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:tefoso:v:124:y:2017:i:c:p:306-319. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.