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A SEM-neural network approach for predicting antecedents of m-commerce acceptance

机译:SEM神经网络方法预测移动商务接受度的前因

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Higher penetration of powerful mobile devices - especially smartphones - and high-speed mobile inter net access are leading to better offer and higher levels of usage of these devices in commercial activities, especially among young generations. The purpose of this paper is to determine the key factors that influence consumers' adoption of mobile commerce. The extended model incorporates basic TAM predictors, such as perceived usefulness and perceived ease of use, but also several external variables, such as trust, mobility, customization and customer involvement. Data was collected from 224 m-commerce consumers. First, structural equation modeling (SEM) was used to determine which variables had significant influence on m-commerce adoption. In a second phase, the neural network model was used to rank the relative influence of significant predictors obtained from SEM. The results showed that customization and customer involvement are the strongest antecedents of the intention to use m-commerce. The study results will be useful for m-commerce providers in formulating optimal marketing strategies to attract new consumers. (C) 2016 Elsevier Ltd. All rights reserved.
机译:功能强大的移动设备(尤其是智能手机)的更高渗透率以及高速移动互联网访问,导致这些设备在商业活动中(尤其是在年轻一代中)提供更好的产品和更高的使用率。本文的目的是确定影响消费者采用移动商务的关键因素。扩展模型不仅包含基本的TAM预测变量,例如感知的有用性和感知的易用性,还包含一些外部变量,例如信任,移动性,自定义和客户参与度。数据来自224个移动商务消费者。首先,使用结构方程模型(SEM)来确定哪些变量对移动商务的采用产生重大影响。在第二阶段,使用神经网络模型对从SEM获得的重要预测变量的相对影响进行排名。结果表明,定制和客户参与是使用移动商务意图的最强先决条件。该研究结果对于移动商务提供商制定最佳营销策略以吸引新消费者将是有用的。 (C)2016 Elsevier Ltd.保留所有权利。

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