Critical Factors Affecting the Adoption of Artificial Intelligence: An Empirical Study in Vietnam

• 발행기관: 한국유통과학회
• 저자명: Thanh Luan NGUYEN Van Phuoc NGUYEN Thi Viet Duc DANG
• 간행물 정보: 『The Journal of Asian Finance, Economics and Business(JAFEB)』The Journal of Asian Finance, Economics, and Business Vol. 9 No.5, 225~237쪽, 전체 13쪽
• 주제분류: 경제경영 > 경제학
• 파일형태: PDF
• 발행일자: 2022.05.30

영문 초록

The term “artificial intelligence” is considered a component of sophisticated technological developments, and several intelligent tools have been developed to assist organizations and entrepreneurs in making business decisions. Artificial intelligence (AI) is defined as the concept of transforming inanimate objects into intelligent beings that can reason in the same way that humans do. Computer systems can imitate a variety of human intelligence activities, including learning, reasoning, problem-solving, speech recognition, and planning. This study’s objective is to provide responses to the questions: Which factors should be taken into account while deciding whether or not to use AI applications? What role do these elements have in AI application adoption? However, this study proposes a framework to explore the significance and relation of success factors to AI adoption based on the technology-organization-environment model. Ten critical factors related to AI adoption are identified. The framework is empirically tested with data collected by mail surveying organizations in Vietnam. Structural Equation Modeling is applied to analyze the data. The results indicate that Technical compatibility, Relative advantage, Technical complexity, Technical capability, Managerial capability, Organizational readiness, Government involvement, Market uncertainty, and Vendor partnership are significantly related to AI applications adoption.

목차

1. Introduction

2. Theoretical Background

3. Research Model and Hypotheses

4. Research Methodology

5. Results and Discussion

6. Conclusion

References

키워드

Artificial Intelligence Adoption Technology Organization Environment Model Structural Equation Model