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User Satisfaction with an AI-Enabled Customer Relationship Management Chatbot

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HCI International 2021 - Late Breaking Posters (HCII 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1498))

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Abstract

Chatbots’ ability to carry out focused, result-oriented online conversations with human end-users impacts user experience and user satisfaction. Using “Chatbots” as key identifiable examples utilized by Electronic Commerce (E-Commerce) firms in Customer Relationship Management (CRM), this study offers a user satisfaction model in the context of Artificial Intelligence (AI) enabled CRM in E-Commerce. The model is based on Expectation Confirmation Theory (ECT) and Uncertainty Reduction Theory (URT) within the Chatbot context. This model will allow us to investigate if chatbots can provide both businesses and consumers the opportunity to complete a journey from normal through abnormal to the new normal in situations similar to a covid pandemic.

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Authors and Affiliations

  1. DeGroote School of Business, McMaster University, Hamilton, ON, Canada

    Maarif Sohail

  2. Lahore College for Women University, Lahore, Pakistan

    Zehra Mohsin

  3. Foundation University Islamabad, Islamabad, Pakistan

    Sehar Khaliq

Authors
  1. Maarif Sohail
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  2. Zehra Mohsin
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  3. Sehar Khaliq
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Correspondence to Maarif Sohail .

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Editors and Affiliations

  1. University of Crete and Foundation for Research and Technology – Hellas (FORTH), Heraklion, Crete, Greece

    Constantine Stephanidis

  2. Foundation for Research and Technology – Hellas (FORTH), Heraklion, Crete, Greece

    Margherita Antona

  3. Foundation for Research and Technology – Hellas (FORTH), Heraklion, Crete, Greece

    Stavroula Ntoa

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Sohail, M., Mohsin, Z., Khaliq, S. (2021). User Satisfaction with an AI-Enabled Customer Relationship Management Chatbot. In: Stephanidis, C., Antona, M., Ntoa, S. (eds) HCI International 2021 - Late Breaking Posters. HCII 2021. Communications in Computer and Information Science, vol 1498. Springer, Cham. https://doi.org/10.1007/978-3-030-90176-9_36

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  • DOI: https://doi.org/10.1007/978-3-030-90176-9_36

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