Jacobsen Joseph J, Guastello Stephen J
Milwaukee Area Technical College, 4202 West Martin Drive, Milwaukee, WI 53208, USA.
Nonlinear Dynamics Psychol Life Sci. 2007 Oct;11(4):499-520.
Four different theoretical models for explaining the diffusion of innovation were compared for 13 energy-related innovations--the Theory of Planned Behavior, the S-curve for Diffusion of Innovations, the power law distribution, and the cusp catastrophe. The substantive concern was to explore the roles of facilitative and obstructive factors in diffusing industrial and commercial innovations. Participants were 102 industrial plant and facilities managers from sites that were among the top users of electrical energy and natural gas in the United States. They completed a survey that contained measurements of positive attitudes toward innovation, organizational resistance to innovation, and the extent to which they had investigated or adopted each of the target innovations. Seven of the 13 innovations exhibited strong cusp catastrophe models (via nonlinear regression, average R2 = .91) compared to linear alternative models (average R2 = .31) for those innovations; the S-curve for diffusion was regarded as a simplified version of the cusp. One innovation was characterized best by a power law distribution (R2 = .94), and the remaining five were characterized best by a linear model that was based on the Theory of Planned Behavior (R2 = .41). Different underlying dynamics for the various innovations were implied by these results.
针对13项与能源相关的创新,比较了四种不同的用于解释创新扩散的理论模型——计划行为理论、创新扩散的S曲线、幂律分布和尖点突变。主要关注点是探究促进因素和阻碍因素在工商业创新扩散中的作用。参与者是来自美国电能和天然气顶级用户场所的102名工业厂房和设施经理。他们完成了一项调查,该调查包含对创新的积极态度、组织对创新的阻力的测量,以及他们对每项目标创新进行调查或采用的程度。与这些创新的线性替代模型(平均R² = 0.31)相比,13项创新中的7项呈现出强大的尖点突变模型(通过非线性回归,平均R² = 0.91);扩散的S曲线被视为尖点的简化版本。一项创新最适合用幂律分布来描述(R² = 0.94),其余五项最适合用基于计划行为理论的线性模型来描述(R² = 0.41)。这些结果暗示了各种创新背后不同的动态变化。