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Predicting System Usage from Intention and Past Use: Scale Issues in the Predictors

机译:从意图和过去使用情况预测系统使用情况:预测器中的规模问题

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摘要

The objective of this study is to provide insights into how the predictive power for computer-recorded system usage can be improved. Based on 386 responses from actual users of an information system, we examine the predictive power for system usage according to the scales of the predictors used, namely, intention and past use. First, we show that the predictive power of intention can be significantly improved with the choice of an appropriate measure. However, even the desirable intention measure failed to explain two-thirds of the variance in system usage. Second, the results show that past use as measured by computer-recorded log data can significantly enhance our ability to predict system usage. Finally, when both intention and past use are controlled for, the explained variance in system usage is shown to vary widely from 20% to 73%, depending on the predictors' scales. Overall, our findings suggest that an accurate prediction of system usage requires a more rigorous approach than that often applied in information systems research.
机译:这项研究的目的是提供有关如何改善计算机记录的系统使用的预测能力的见解。基于来自信息系统实际用户的386个响应,我们根据所使用的预测变量的规模(即意图和过去的使用)来检查系统使用的预测能力。首先,我们表明,通过选择适当的措施,可以大大提高意图的预测能力。但是,即使是期望的意图度量也无法解释系统使用率差异的三分之二。其次,结果表明,通过计算机记录的日志数据衡量的过去使用可以显着增强我们预测系统使用的能力。最后,当意图和过去的使用都受到控制时,系统使用率的解释差异显示为从20%到73%不等,具体取决于预测指标的范围。总体而言,我们的发现表明,与通常在信息系统研究中使用的方法相比,对系统使用情况进行准确的预测需要更严格的方法。

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