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Can I read Speaking vs. listening? Balance conversation attributes of voice assistants for better voice marketing on EtoBox?

Speaking vs. listening? Balance conversation attributes of voice assistants for better voice marketing by Peng Hu; Yeming Gong; Yaobin Lu; Amy Wenxuan Ding is a Business, Management and Accounting article available to read on EtoBox.

What is Speaking vs. listening? Balance conversation attributes of voice assistants for better voice marketing about?

Artificial Intelligence (AI) is shaping marketing in an unprecedented way. Empowered by AI, voice assistants are increasingly capable of speaking and listening like humans, offering a great opportunity for a new marketing approach -voice marketing. This research examines how conversation attributes of voice assistants determine consumer trust and intention to engage in voice shopping. Using a sequential mixed-method design, three studies consistently show that consumers perceive the speaking attribute of voice assistants as more human-like than the listening attribute. We find that such incongruency between the two conversation attributes can undermine consumers' trust in voice assistants, leading to reduced willingness to accept product recommendations from voice assistants and shop via voice assistants, which would hamper the development of voice marketing. Accordingly, this research suggests that AI giants with strong technological strength and capital support should distribute more resources to advance the underlying technologies enabling human-like listening (e.g., natural language understanding and voice recognition). But for AI startups with limited financing ability and tec

Who reads Speaking vs. listening? Balance conversation attributes of voice assistants for better voice marketing?

It is typically read by researchers, students, and practitioners in Business, Management and Accounting.

Author
Peng Hu; Yeming Gong; Yaobin Lu; Amy Wenxuan Ding
Publisher
Elsevier BV
Published
2022
Language
EN
Field
Business, Management and Accounting (Social Sciences)

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