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Analyzing the Priority of Selection Attributes for Generative AI Services: An Application of AHP and Fuzzy AHP

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2026, 31(5), pp.251~261
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : April 9, 2026
  • Accepted : May 8, 2026
  • Published : May 29, 2026

Yujin Kim 1 Hyung-Seok Lee 1

1충북대학교

Accredited

ABSTRACT

This study proposes a hierarchical decision-making model based on six key selection attributes, including anthropomorphism, personalization, information accuracy, enjoyment, creativity, and response uncertainty, to better understand the complexity of users’ choice environments arising from the increasing diversity of generative AI services. To enhance analytical robustness, both traditional AHP and fuzzy AHP were employed to account for the ambiguity inherent in human judgment. The analysis of priority weight confirms that information accuracy is firmly established as the core value of generative AI services. However, the findings reveal that attribute evaluation structures are distinctly differentiated by service type (ChatGPT vs. Gemini) and user group (university student vs. working adult). Platform-specific comparisons demonstrate that while ChatGPT is perceived as a hybrid service simultaneously pursuing functional utility and emotional playfulness, Gemini exhibits a strong identity as a specialized professional tool centered on reliability and accuracy. Furthermore, whereas office workers perform multi-criteria evaluations encompassing work efficiency and creativity, university students exhibit a single-purpose orientation focused predominantly on output accuracy. These findings provide empirical guidelines for target-specific differentiation and strategic resource allocation in the design of future AI services.

Citation status

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