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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?

Alexandra Rese, Stefanie Schreiber and Daniel Baier

Journal of Retailing and Consumer Services, 2014, vol. 21, issue 5, 869-876

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.

Keywords: Technology acceptance; Technology acceptance model (TAM); Online reviews; Text mining; Partial least squares (PLS); Augmented reality (search for similar items in EconPapers)
Date: 2014
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