Earticle

초록

영어

This research examines how ChatGPT characteristics influence user acceptance in finance, exploring the interplay with the Technology Acceptance Model (TAM) (Davis 1989). It emphasizes accuracy, innovation, recommendation, perceived usefulness, and ease of use, analyzing their impact on financial communication and decision-making. Findings from the structural equation model show accuracy significantly affects perceived usefulness, while innovation and recommendation impact ease of use. The study also assesses how digital proficiency moderates the relationship between perceived usefulness, ease of use, and acceptance intentions. The structural equation model employed in the study demonstrates overall suitability, with accuracy significantly affecting perceived usefulness and innovation and recommendation significantly affecting perceived ease of use. Notably, perceived usefulness and ease of use emerge as key factors influencing acceptance intentions, particularly among less digitally skilled financiers. This paper adopts the questionnaire survey method and the questionnaire survey was conducted from September to November 2023 in Korea. 182 copies of the questionnaires were used as final analysis data. SPSS 26.0 and Amos 28.0 software were used to analyze the data. In summary, this paper provides valuable insights into the interplay of ChatGPT characteristics and acceptance intention within the financial sector. By combining these insights with an understanding of the financial landscape, the study contributes to a comprehensive knowledge base on the factors influencing AI adoption in finance, facilitating informed decision-making in this evolving technological landscape.

목차

ABSTRACT
I. Introduction
II. Literature and Review
1. ChatGPT
2. ChatGPT and Finance
3. Accuracy, Innovation and Recommendation
4. Digital Technology Proficiency of Financiers
II. Research Methods
1. Research Model and Hypotheses
IV. Data Analysis
1. Questionnaire Design
2. Data Collection and Sample Characteristics
3. Reliability Analysis
4. Exploratory Factor Analysis
5. Correlation Analysis
6. Structural Equation Model Analysis
V. Conclusion
1. Research Conclusion
2. Implications
3. Research Limitations and Future Research Directions
Reference

키워드

저자

• Park, Sujin [ Ph. D. Student/Lecturer, Department of Global Business, Kyonggi University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  콘텐츠와산업 [Journal of Contents and Industry]

• 간기

  격월간

• pISSN

  2765-317X

• 수록기간

  2019~2026

• 등재여부

  KCI 등재

• 십진분류

  KDC 600 DDC 700