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Exploratory analysis of the impact of information dynamics on innovation diffusion

机译:探索性研究信息动力学对创新扩散的影响

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Understanding the dynamic nature of innovation diffusion processes, and mechanisms underlying these dynamics is crucial, since such an understanding is potentially very important in designing effective innovation support policies and developing better diffusion forecasts. The role of information diffusion in conditioning the diffusion dynamics of an innovation is the locus of this study. In order to investigate this, a simulation model that distinguishes between the real attributes of the innovation and their perceived levels by the user groups has been developed. The model makes it possible to separately trace the diffusion dynamics of innovation and the information about an innovation. Additionally, the formulation of the model enables the message broadcasted via word-of-mouth to change in nature from positive to negative, or vice versa. This generic model is used in an exploratory way, which is discussed as a novel approach for conducting a simulation-based analysis. Such an exploration covers a wide range of plausible diffusion behaviors, and aims to demonstrate the extent to which information imperfections and dynamics may influence the diffusion process. During experiments it is observed that information imperfections as well as the pace of learning processes may yield significant changes in the diffusion patterns. These changes may be in the form of altering the basic characteristics of the well-known S-shaped diffusion curve, as well as stopping the diffusion at much lower levels than full adoption. The analysis presented in the article shows that exploratory analysis is a promising way to utilize simulation models for developing general insights about dynamics processes.
机译:理解创新扩散过程的动态性质以及这些动力学的基础机制至关重要,因为这种理解对于设计有效的创新支持政策和制定更好的扩散预测非常重要。信息扩散在调节创新扩散动力学中的作用是本研究的重点。为了对此进行研究,已经开发出一种模拟模型,该模型可以区分创新的真实属性和用户群体对创新水平的感知程度。该模型使得可以分别跟踪创新的扩散动态和有关创新的信息。此外,该模型的制定使通过口碑传播的消息的性质从正变为负,反之亦然。该通用模型以探索性方式使用,作为一种进行基于模拟的分析的新颖方法而被讨论。这样的探索涵盖了广泛的可能的扩散行为,旨在证明信息缺陷和动态可能在多大程度上影响扩散过程。在实验过程中,观察到信息不完善以及学习过程的节奏可能会导致扩散模式发生重大变化。这些变化的形式可以是改变众所周知的S形扩散曲线的基本特征,以及将扩散停止在比完全采用低得多的水平上。本文提供的分析表明,探索性分析是一种利用模拟模型来开发有关动力学过程的一般见解的有前途的方法。

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