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Do chatbots establish “humanness” in the customer purchase journey? An investigation through explanatory sequential design

Yogesh Dwivedi Orcid Logo, Janarthanan Balakrishnan, Abdullah M. Baabdullah, Ronnie Das

Psychology and Marketing, Volume: 40, Issue: 11, Pages: 2244 - 2271

Swansea University Author: Yogesh Dwivedi Orcid Logo

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DOI (Published version): 10.1002/mar.21888

Abstract

Chatbots incorporate various behavioral and psychological marketing elements to satisfy customers at various stages of their purchase journey. This research follows the foundations of the Elaboration Likelihood Model (ELM) and examines how cognitive and peripheral cues impact experiential dimensions...

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Published in: Psychology and Marketing
ISSN: 0742-6046 1520-6793
Published: Wiley 2023
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa64041
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Abstract: Chatbots incorporate various behavioral and psychological marketing elements to satisfy customers at various stages of their purchase journey. This research follows the foundations of the Elaboration Likelihood Model (ELM) and examines how cognitive and peripheral cues impact experiential dimensions, leading to chatbot user recommendation intentions. The study introduced warmth and competence as mediating variables in both the purchase and postpurchase stages, utilizing a robust explanatory sequential mixed-method research design. The researchers tested and validated the proposed conceptual model using a 3 × 3 factorial design, collecting 354 responses in the purchase stage and 286 responses in the postpurchase stage. In the second stage, they conducted in-depth qualitative interviews (Study 2) to gain further insights into the validity of the experimental research (Study 1). The results obtained from Study 1 revealed that “cognitive cues” and “competence” significantly influence recommendation intentions among chatbot users. On the other hand, “peripheral cues” and warmth significantly contribute to positive experiences encountered during the purchase stage. The researchers further identified 69 thematic codes through exploratory research, providing a deeper understanding of the variables. Theoretically, this study extends the ELM by introducing new dimensions to human-machine interactions at the heart of digital transformation. From a managerial standpoint, the study emphasizes the significance of adding a “humanness” element in chatbot development to create more engaging and positive customer experiences actively.
Keywords: AI humanness, chatbots, customer journey, elaboration likelihood model (ELM), marketing automation, recommendation intention
College: Faculty of Humanities and Social Sciences
Funders: Swansea University
Issue: 11
Start Page: 2244
End Page: 2271

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