Big Data, Artificial Intelligence, and Financial Literacy: Exploring their Combined Influence on Investment Behavior among Chinese Household

Author:

Zhang Runhe12ORCID,Sidik Morni Hayati Jaafar3ORCID

Affiliation:

1. Ph.D candidate, Business School, Universiti Kuala Lumpur, Kuala Lumpur, Malaysia

2. Teaching Assistant, Zhejiang Financial College, Faculty of Investment and Insurance, Hangzhou, China

3. Doctor, Senior Lecturer, Business School, Universiti Kuala Lumpur, Kuala Lumpur, Malaysia

Abstract

The investing behavior of Chinese families is undergoing a dramatic transition in the context of the digital financial era, impacted by factors such as big data use, AI adoption, financial literacy, digital literacy, and risk aversion. Although prior research has offered useful insights into certain components, a thorough examination of their linked dynamics has been lacking. The purpose of this research was to look into how big data usage, AI adoption, financial literacy, digital literacy, and risk aversion influence investment behavior among Chinese households. Additionally, it aimed to learn more about how risk aversion and digital literacy function as mediators in these relationships. A questionnaire-based survey of 370 Chinese families was employed as part of the quantitative research methodology. The study employed AMOS to find the relationship between variables. The research found that big data usage, AI adoption, financial literacy, and digital literacy significantly and favorably influenced Chinese households' investment behavior. It was discovered that digital literacy mediated the linkages between the adoption of technology and investment decisions. Furthermore, risk aversion reduced the effects of financial literacy and big data usage on investment behavior. This study added to the body of knowledge by providing a comprehensive framework that incorporates several aspects impacting investment behavior. It shed insight into the complicated dynamics of technology uptake and literacy, as well as their impact on investment decisions. The study went beyond individual components to investigate their interactions, resulting in a more complex view of modern investment behavior. This study has broad-ranging effects that will help investors, financial institutions, governments, educators, and researchers. The focus on a particular setting and self-reported data are two important constraints that must be acknowledged. Future studies can investigate longitudinal dynamics and cross-cultural variances to further our understanding of investment behavior in the digital age.

Publisher

International Association for Digital Transformation and Technological Innovation

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