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Predicting personal information system adoption using an integrated diffusion model

机译:使用集成扩散模型预测个人信息系统的采用

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摘要

The purpose of this study is to develop a research model that integrates the relationship between innovation characteristics (innovation diffusion theory) and technology characteristics (task-technology fit model). With the research model, the current study investigates the adoption of the "personal information system," a concept that we develop in the context of mobile technologies. In this paper, we performed the first quantitative test of the model by integrating the innovation diffusion and task-technology fit models. Further, we proposed a theoretical definition of "personal information systems" by highlighting the differences in the types of tasks across individual users' needs. To test our research model, 202 college students were surveyed. Partial least squares (PLS) structural equation modeling was employed to analyze our data, and these analyses provided empirical support for the proposed hypotheses. Quality, compatibility, cost, and relative advantage were found to be important indicators of the intention to adopt due to their impact on the intended communication, information, transaction, and entertainment tasks, while compatibility, relative advantage, and complexity had a direct impact on the intention to adopt.
机译:本研究的目的是建立一个研究模型,该模型整合了创新特征(创新扩散理论)和技术特征(任务-技术拟合模型)之间的关系。通过研究模型,当前的研究调查了“个人信息系统”的采用,该概念是我们在移动技术的背景下开发的。在本文中,我们通过整合创新扩散和任务技术拟合模型对模型进行了首次定量测试。此外,我们通过强调跨各个用户需求的任务类型的差异,提出了“个人信息系统”的理论定义。为了检验我们的研究模型,对202名大学生进行了调查。偏最小二乘(PLS)结构方程模型被用来分析我们的数据,这些分析为提出的假设提供了经验支持。由于质量,兼容性,成本和相对优势会影响预期的通信,信息,交易和娱乐任务,因此质量,兼容性,成本和相对优势是要采用的重要指标,而兼容性,相对优势和复杂性则直接影响了质量,兼容性,成本和相对优势。采纳的意图。

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