With the advent of large language models, a spotlight has been turned onto chatbots. Utilizing the Technology Acceptance Model (TAM), we investigated whether whatsappization of the chatbot – making the conversation more resemble a WhatsApp conversation – improves Perceived Ease of Use, Perceived Usefulness, and Attitude Toward Using. In today's world, given that WhatsApp conversations sometimes substitute for face-to-face communication, borrowing this format for use in another framework was reasonable. Participants, assigned a drive-sharing task, communicated with a textual chatbot via WhatsApp and had to decide whether to take a lift to college with a driver suggested by the chatbot. Whatsappization of the chatbot was done in two ways: Through a dialog-style conversation (Dialog versus No Dialog), and by adding WhatsApp indicators – “Last Seen”, “Connected”, “Read Receipts”, and “Typing …” (Indicators versus No Indicators). The research was full factorial, with a 2 by 2 design. 120 participants were randomly assigned to one of the four groups, with 30 participants in each group. The results, using one-way ANOVAs, demonstrated that the interaction with the chatbot was longer under the Dialog compared to the No Dialog condition, and participants in the Dialog condition had a lower rating for Attitude Toward Using. In addition, both for the Perceived Ease of Use and Perceived Usefulness constructs, participants' ratings were lower under the Indicators compared to the No Indicators condition. Our findings signal that whatsappization of the chatbot decreased user's motivation to use the system. Hence, the current study suggests that a non-human agent should not try to imitate a WhatsApp conversation.
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