User satisfaction with the service quality of ChatGPT

Kim Shin Young, Sang-Gun Lee and Ga Youn Hong ()
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Kim Shin Young: Sogang University
Sang-Gun Lee: Sogang University
Ga Youn Hong: Sogang University

Service Business, 2024, vol. 18, issue 3, No 3, 417-431

Abstract: Abstract The present study identified the attributes of generative AI services provided by enterprises that affect satisfaction and dissatisfaction. The KANO model was validated on the data collected from two-hundred respondents participated in the present work. The results from an KANO model analysis indicate that (1) ChatGPT’s service quality factors were categorized into the sector of must-be quality, attractive quality, and one-dimensional quality, presenting a positive image to users; and (2) service improvement efforts in attractive quality factors had strong influence on satisfaction, whereas service improvement efforts in must-be quality factors had weak influence on satisfaction. The findings from the study should be applied by companies using ChatGPT to establish effective ChatGPT utilization strategies.

Keywords: Generative AI; ChatGPT; KANO model; Customer satisfaction coefficient; Service quality factors (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11628-024-00566-y

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