Chatbots represent a viable interaction layer between online retailers and customers, however, when it comes to online purchases in the form of conversational commerce, customers’ resistance could turn out to be a big challenge for marketers. This study provides a deeper understanding of how consumers perceive chatbots and their intention to use them for online purchases. Based on an extended Technology Acceptance Model, the study examines whether and how the original TAM’s exogenous constructs combined with trust, compatibility, and perceived enjoyment predict a positive attitude and, consequently, a higher intention to use chatbots for online shopping. A total of 208 respondents participated in an online survey and Structural Equation Modeling (SEM-PLS) was applied to test the hypotheses. Moreover, a qualitative textual analysis of participants’ answers was performed to dig deeper into users’ motives for developing positive, neutral/ambivalent, or negative attitudes toward the chatbot. In doing so, the study provides useful information to online businesses in electronic retail activities, as the results highlight the importance of designing chatbots that fit both consumer’s cognitive needs and affective desires.
Understanding Users' Acceptance of Chatbots: An Extended TAM Approach
Roberta De Cicco
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2022
Abstract
Chatbots represent a viable interaction layer between online retailers and customers, however, when it comes to online purchases in the form of conversational commerce, customers’ resistance could turn out to be a big challenge for marketers. This study provides a deeper understanding of how consumers perceive chatbots and their intention to use them for online purchases. Based on an extended Technology Acceptance Model, the study examines whether and how the original TAM’s exogenous constructs combined with trust, compatibility, and perceived enjoyment predict a positive attitude and, consequently, a higher intention to use chatbots for online shopping. A total of 208 respondents participated in an online survey and Structural Equation Modeling (SEM-PLS) was applied to test the hypotheses. Moreover, a qualitative textual analysis of participants’ answers was performed to dig deeper into users’ motives for developing positive, neutral/ambivalent, or negative attitudes toward the chatbot. In doing so, the study provides useful information to online businesses in electronic retail activities, as the results highlight the importance of designing chatbots that fit both consumer’s cognitive needs and affective desires.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
