A New Concept of Transforming Service: Impact of Generative Voice Chatbots on Customer Satisfaction and Banking Industry Productivity

Generative Voice Chatbots Banks Artificial Intelligence Productivity Customer Satisfaction Bank Performance Customer Expectation Customer Focus Distant Bank Customer Support Service.

Authors

  • Saltanat Kondybayeva Department of Economics, Al-Farabi Kazakh National University,, Kazakhstan
  • Meruyert Daribayeva
    m_daribayeva@outlook.com
    Department of Finance And Accounting, Al-Farabi Kazakh National University,, Kazakhstan
  • Raffaele Fiume Department of Accounting and Economics, Universití  degli Studi di Napoli Parthenope,, Italy
  • Symbat Abilda Department of Economics, Al-Farabi Kazakh National University,, Kazakhstan
  • Olga Staroverova Department of State and Municipal Finance, Plekhanov Russian University of Economics,, Russian Federation
  • Vadim Ponkratov Institute for Research on Socio-Economic Transformations and Financial Policy, Financial University under the Government of the Russian Federation,, Russian Federation
  • Larisa Vatutina Department of Management, Moscow Polytechnic University,, Russian Federation
  • Galina Shapoval Department of Philosophy with courses on Bioethics and Spiritual Foundations of Medical Activity, Rostov State Medical University,, Russian Federation
  • Elena Mikhina Institute for Research on Socio-Economic Transformations and Financial Policy, Financial University under the Government of the Russian Federation,, Russian Federation
  • Irina Nikolaeva Department of Mathematical Economics and Applied Informatics, M.K. Ammosov North-Eastern Federal University,, Russian Federation

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This study examines the impact of implementing generative AI voice chatbots on customer expectations and satisfaction in the banking sectors of Kazakhstan, Russia, and Italy. To achieve this objective, this study conducted a survey of 253 customers from 35 commercial banks in Kazakhstan, Russia, and Italy from November 2023 to early April 2024. This study employed partial least squares structural equation modelling (PLS-SEM) to assess and validate the validity and reliability of the research model. The study integrates the Expectation Confirmation Model with AI components to analyze factors influencing customer satisfaction with AI-enabled digital banking services. Key findings indicate that expectation confirmation, perceived performance, visual attractiveness, problem-solving capabilities, and communication quality significantly affect customer satisfaction with AI chatbots. However, trendiness and customization features showed minimal impact. The research also explores how customer satisfaction and corporate reputation influence chatbot adoption. Additionally, the study investigates the relationship between chatbot adoption and productivity performance in banking operations. The study provides several policy recommendations, including enhancing perceived performance, expectation confirmation, communication quality, visual attractiveness, and corporate reputation, which can improve customer satisfaction and increase confidence in generative AI voice chatbots in the digital banking industry.

 

Doi: 10.28991/ESJ-2024-08-06-09

Full Text: PDF