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Technology acceptance modeling of augmented reality at the point of sale: Can surveys be replaced by an analysis of online reviews?

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  • Rese, Alexandra
  • Schreiber, Stefanie
  • Baier, Daniel

Abstract

Online reviews by users have become an increasingly important source of information. This is true not only for new users of goods or services, but also for their producers. They extend the insight into the acceptance of new goods and services, e.g. at the point of sale, from a mere sales and usage quantity oriented point of view to a cause and effect oriented one. Since online reviews by consumers of many goods and services are nowadays widespread and easily available on the internet, the question arises whether their analysis can replace the more traditional approaches to measure technology acceptance, e.g., using questionnaires with TAM (Technology Acceptance Model) items. This paper tries to answer this question using IKEA׳s mobile catalogue app as an example. For comparisons reasons, data on the acceptance of the current version of this catalogue is collected in four different ways, (1) as answers to batteries of TAM items, (2) as assignments to pre-defined adjective pairs, (3) as textual likes and dislikes of users (simulating online reviews), and (4) as publicly available (real) reviews by users. The source for (1)–(3) is a survey with a sample of respondents, the source for (4) an online forum. The data is analyzed using partial least squares (PLS) for TAM modeling and text mining for pre-processing the textual data. The results are promising: it seems that data collection via surveys can be replaced – with some reservations – by the analysis of publicly available (real) online reviews.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:joreco:v:21:y:2014:i:5:p:869-876
    DOI: 10.1016/j.jretconser.2014.02.011
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    References listed on IDEAS

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    1. 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.
    2. De Bruyn, Arnaud & Lilien, Gary L., 2008. "A multi-stage model of word-of-mouth influence through viral marketing," International Journal of Research in Marketing, Elsevier, vol. 25(3), pages 151-163.
    3. Saarijärvi, Hannu & Mitronen, Lasse & Yrjölä, Mika, 2014. "From selling to supporting – Leveraging mobile services in the context of food retailing," Journal of Retailing and Consumer Services, Elsevier, vol. 21(1), pages 26-36.
    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. 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.
    8. 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.
    9. 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.
    10. Bruner, Gordon II & Kumar, Anand, 2005. "Explaining consumer acceptance of handheld Internet devices," Journal of Business Research, Elsevier, vol. 58(5), pages 553-558, May.
    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.
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