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Analyzing Online Reviews to Measure Technology Acceptance at the Point of Scale: The Case of IKEA
(2015)
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. newfurniture) 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.
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 modelling 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.