Consumer Behavior
Authors: Veena Chattaraman (Auburn University) , Wi-Suk Kwon (Auburn University) , Kassandra Ross (Auburn University) , Jihyun Sung (Auburn University) , Juan E. Gilbert (University of Florida) , Kiana Alikhademi (University of Florida) , Brianna Richardson (University of Florida)
In this paper, we examine the effects of an artificially intelligent, mobile, conversational decision aid’s strategy (attribute-/alternative-based) and consumers’ need for cognition (low/high) on decision elaboration, decision aid evaluations (perceived usefulness, enjoyment, attitude) and reuse intentions in a semi-realistic store. Based on consumer decision-making theory, the decision aid developed employed four decision strategies that consumers commonly use, two attribute-based (lexicographic, elimination-by-aspects) and two alternative-based (satisficing, weighted adding) differentiated by whether the decision support began by having consumers think about key attributes or alternatives (brands) for their choice. A total of 100 consumers were recruited for the consumer experiment employing a between-subjects design. The results demonstrated that attribute-based mobile decision aids are perceived to be more beneficial and lead to greater reuse intent in a physical retail store than alternative-based decision aids. Mobile decision aids are also evaluated more positively with respect to enjoyment and attitude by low-NFC (vs. high-NFC) consumers.
Keywords: conversational AI, decision aids, need for cognition
How to Cite: Chattaraman, V. , Kwon, W. , Ross, K. , Sung, J. , Gilbert, J. E. , Alikhademi, K. & Richardson, B. (2022) “Consumer Evaluations of Mobile, Conversational Decision Aids for In-Store Shopping: Effects of Decision Strategy Implemented and Consumer Need for Cognition”, International Textile and Apparel Association Annual Conference Proceedings. 78(1). doi: https://doi.org/10.31274/itaa.13832
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