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Predicting adoption of mobile payments from the perspective of taxi drivers

机译:从出租车司机的角度预测移动支付的采用

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With the development of mobile communication technologies, it brings new implementations in intelligent transport system (ITS). Previous studies of ITS ignored the advanced services from service providers and especially taxi drivers who provide mobile payment service at front-line towards passengers. This research combines the unified theory of acceptance and use technology 2 (UTAUT2) and the moderating variable of experience, perceived risk (PR), to investigate the key influence on the adoption intention of mobile payments for the taxi drivers. A total of 228 valid questionnaires were collected and subsequently analysed by using the structural equation modelling (SEM) approach and back-propagation artificial neural network. The results demonstrate that performance expectancy (PE), effort expectancy (EE) facilitating conditions (FCs), and PR are significant with respect to the adoption intention. As there is limited UTAUT2-based research conducted on mobile payments, this article is among the few that attempt to extend the model and study taxi drivers in Taiwan, who play both roles of business and customer. This finding provides the current situation of a new technology on taxi industry. Furthermore, it also provides useful information and direction for mobile stakeholders and ITS implementations to understand the rationale behind the use of service and how it leads to promoting acceptance.
机译:随着移动通信技术的发展,它带来了智能运输系统(ITS)的新实现。先前对ITS的研究忽略了服务提供商(尤其是出租车司机)提供的先进服务,后者在前线为乘客提供移动支付服务。这项研究结合了接受和使用技术的统一理论2(UTAUT2)和经验的适度变量,感知风险(PR),以研究对出租车司机采用移动支付的意图的关键影响。总共收集了228份有效问卷,然后使用结构方程模型(SEM)方法和反向传播人工神经网络对其进行了分析。结果表明,就采用意图而言,预期绩效(PE),预期工作量(EE)促进条件(FC)和PR均很重要。由于针对移动支付进行的基于UTAUT2的研究有限,因此本文是为数不多的尝试扩展该模型并研究台湾出租车司机的人,他们既扮演企业角色,又扮演顾客角色。这一发现提供了出租车行业新技术的现状。此外,它还为移动涉众和ITS实施提供有用的信息和指导,以了解使用服务背后的基本原理以及它如何导致促进接受度。

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