基于唤起理论的协同创新任务难度划分研究 本期目录 >>
Title: Research on Cooperation Innovation Task Difficulty based on Arousing Theory
作者 游静
Author(s): You Jing
摘要: 任务分解与合作是协同创新的重要途径,确定合理的任务难度是调动创新主体最优唤起水平,从而提升创新绩效的关键。基于心理学唤起理论中作业绩效与唤起水平的倒U型曲线关系以及任务难易程度对倒U型曲线产生的偏移,构建任务难易程度影响下的协同创新收益模型。通过模型演算得到,提高任务难度有利于降低主体的最优唤起水平,提高创新资源投入分摊比例只能降低其自身的最优唤起水平,协作方的最优唤起水平反而随着分摊比例提升而提高。恰当的任务难易程度受到创新效率常数、创新收益常数以及创新资源投入比例的共同影响。以算例和案例对模型结论进行验证。研究结论有助于协同创新组织合理确定创新任务难度以及分配创新任务。
Abstract: Tack assignment is the important route of cooperation innovation. Best task difficulty is the key factor of best arousing level and best innovation performance. Cooperation innovation profit model is built up on foundation of reversal U curve between performance and arousing level and shifting of it with the influence of task difficulty. The results are that high task difficulty would introduce low arousing level; high resource sharing ratio would do help to its own arousing level while no to partners’. And task difficulty is influenced by innovation efficiency constant, innovation profit constant and innovation resource sharing ratio. These conclusions are test by example and case study. They are valuable for confirming best task difficulty and task assignment.
关键词: 唤起理论;协同创新;任务难度
Keywords: Arousing theory; Cooperation innovation; Task difficulty
基金项目: 国家社科基金
发表期数: 2017年 第3期
中图分类号: 文献标识码: 文章编号:
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