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AI-Based Chatbot Agents as Drivers of Purchase Intentions: An Interdisciplinary Study

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Data Analytics for Internet of Things Infrastructure

Part of the book series: Internet of Things ((ITTCC))

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Abstract

The area of e-marketing can benefit from the usage of digital technology like chatbots. This study aimed to determine the impact of chatbots on customers’ purchase intentions. An empirical study was carried out on the impact of chatbot agent’s informational support, Emotional Credibility, and trust on purchasing intentions. The data was collected through an online survey from 223 Delhi-NCR customers who use chatbots while making online purchases. PLS-SEM was used to analyze the data that was collected. The results of structural equation modeling (SEM) showed a significant impact on informational support, emotional credibility, and trust of chatbots on purchase intentions of customers. The results of the study can be used as guidance by marketers to achieve a competitive edge in the changing business environment. The findings of the present study will encourage marketers to use technologies such as chatbots and help customers to get information. The marketers are encouraged to utilize and monitor chatbots efficiently and effectively. This study intends to contribute to the field of e-marketing.

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Authors and Affiliations

  1. Faculty of Management, SRM Institute of Science and Technology, Ghaziabad, Uttar Pradesh, India

    Priyanka Tyagi & Ajay Jain

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  1. Priyanka Tyagi
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  2. Ajay Jain
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Editors and Affiliations

  1. SRM Institute of Science and Technology, Delhi NCR Campus, Ghaziabad, Uttar Pradesh, India

    Rohit Sharma

  2. Incheon National University, Incheon, Korea (Republic of)

    Gwanggil Jeon

  3. Xi’an Shiyou University, Xi'An, China

    Yan Zhang

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Tyagi, P., Jain, A. (2023). AI-Based Chatbot Agents as Drivers of Purchase Intentions: An Interdisciplinary Study. In: Sharma, R., Jeon, G., Zhang, Y. (eds) Data Analytics for Internet of Things Infrastructure. Internet of Things. Springer, Cham. https://doi.org/10.1007/978-3-031-33808-3_5

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  • DOI: https://doi.org/10.1007/978-3-031-33808-3_5

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  • Online ISBN: 978-3-031-33808-3

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