发表期刊: Humanities and Social Sciences Communications
Lee, J. C., Tang, Y., & Jiang, S. (2023). Understanding continuance intention of artificial intelligence (AI)-enabled mobile banking applications: an extension of AI characteristics to an expectation confirmation model. Humanities and Social Sciences Communications, 10(1), 1-12.
https://www.nature.com/articles/s41599-023-01845-1
论文简介
Artificial intelligence (AI) has been proven to be a disruptive financial technology in the
context of mobile banking that can provide more practical value to users and banks. AI is a critical way of facilitating user acceptance and adoption of mobile banking applications(apps). Nevertheless, the ways in which AI features influence users’ continuance intention towards AI-enabled mobile banking apps have not been investigated from the perspective of an expectation confirmation model (ECM). To address this research gap, this paper develops a research model by combining two constructs pertaining to AI characteristics, namely, perceived intelligence and perceived anthropomorphism, and by using the ECM to explore users’ continuance intentions in this context. We employed a survey research method using a random sampling approach to collect 365 valid responses. A partial least squares approach
was used to examine the model. The results show that both intelligence and anthropomorphism can increase user satisfaction via confirmation and perceived usefulness, which in turn fosters users’ willingness to continue to engage in mobile banking. This paper offers theoretical advancements, discusses future directions for mobile banking research and provides practical guidance to app developers with respect to designing and developing proper mobile banking apps using AI technology.
在移动银行的背景下，人工智能(AI)已经被证明是一种颠覆性的金融科技，可以为用户和银行提供更多的实用价值。人工智能是促进用户接受和采用移动银行应用程序的关键途径。然而，尚未从期望确认模型(ECM)的角度研究人工智能功能如何影响用户对支持人工智能的移动银行应用程序的继续意愿。为了解决这一研究空白，本文通过结合与人工智能特征相关的两个结构(即感知智能和感知拟人化)开发了一个研究模型，并通过使用ECM来探索用户在此背景下的继续意图。采用随机抽样的调查研究方法，共收集有效问卷365份。偏最小二乘法用于检验模型。结果表明，智能和拟人化都可以通过确认和感知有用性来提高用户满意度，从而促进用户继续从事手机银行业务的意愿。本文提供了理论进展，讨论了移动银行研究的未来方向，并为应用程序开发人员使用AI技术设计和开发合适的移动银行应用程序提供了实践指导。