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An Exploratory Study on Artificial Intelligence Quality, Preference and Continuous Usage Intention: A Case of Online Job Information Platform

인공지능이 적용된 온라인 구인정보 플랫폼의 품질 및 선호가 지속사용의도에 미치는 영향에 관한 탐색적 연구

  • An, Kyung-Min (The Cooperative Department of Techno-Management, Dongguk University) ;
  • Lee, Young-Chan (Department of Business Administration, Dongguk University Gyeongju)
  • 안경민 (동국대학교 테크노경영협동과정) ;
  • 이영찬 (동국대학교 경주캠퍼스 경영학부)
  • Received : 2019.04.28
  • Accepted : 2019.07.20
  • Published : 2019.07.28

Abstract

The purpose of this study is to clarify the continuous usage intention of artificial intelligence products and services. In this study, we try to define the artificial intelligence quality and preference on the online job information platform and investigate the effect of artificial intelligence on continues usage intention. A survey of artificial intelligence users was conducted and recalled 184. The empirical analysis shows that the artificial intelligence quality and preference have a positive effect on satisfaction, and that the satisfaction has significant effect on the intention of continuing use. but the artificial intelligence quality does not significantly affect the intention of continuing use. These results are expected to provide useful guidelines for artificial intelligence technology products or services in the future.

본 연구는 최근 빠르게 확산되는 인공지능의 지속적인수용에 관하여 탐색하고자 온라인 구인정보 플랫폼에 적용된 인공지능의 품질을 정의하고 인공지능의 선호, 지속사용의도 간의 구조적인 관계를 규명하였다. 인공지능 사용자를 대상으로 설문조사를 시행하였고 184개를 회수하였다. 실증분석결과 인공지능의 품질과 선호가 만족에 긍정적인 영향을 미치며, 인공지능의 만족이 지속사용의도에 통계적으로 유의한 수준에서 긍정적인 영향을 미치는 것으로 나타났다. 그러나 예상과는 달리 인공지능의 품질은 지속사용의도에 유의한 영향을 미치지 않는 것으로 나타났다. 이와 같은 결과는 향후 인공지능 기술을 제품이나 서비스에 적용하는데 있어 이론적, 실무적인 차원의 유용한 가이드라인을 제시할 수 있을 것으로 기대한다.

Keywords

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Fig. 1. User information process framework

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Fig. 2. Research model

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Fig. 3. Result of hypothesis tests

Table 1. Operation definition and Measurement items

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Table 2. Exploratory factor analysis

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Table 3. Results of reliabilities and validity

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Table 4. Result of correlation matrix and discriminant validity

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Table 5. Second-order model test

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Table 6. Summary of hypothesis testing

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