摘要
为明确以环境变化为导向的战略联盟知识空间适应性演化机理,建立基于"刺激-反应"的多层结构原理模型,采用Agent仿真方法进行模拟实验。研究结果表明:战略联盟知识空间演化的适应性取决于环境的刺激、原有知识结构以及规则集限定下联盟组织间的知识流动流量;演化过程中,知识空间内的知识基因具备主动追求更高适应性的需求,知识的复杂程度提高,知识的属性标识更加专业化也更具针对性;知识能力随演化的深入得到提升,但在无法获取异质性资源或遭遇瓶颈时提升速度趋于平缓;知识价值水平在演化初期有所下降,但随后呈现快速上升的趋势;知识空间的适应性演化过程不稳定性,演化存在渐进和突变两种路径,演化具有对称性破缺特征,且可以在无外力作用下自发演化至新的稳定态。
In order to specify the adaptive evolutionary mechanisms in knowledge space of strategic alliance driven by the environment,in this paper,a multi-layer structure model was established based on the stimulus-response theory,and a simulation experiment was conducted using agent-based modeling.The research results show that the adaptation of knowledge space in strategic alliance depends on the stimulus from the environment,the initial knowledge structure,and the knowledge flow among alliance organizations constrained by rule sets.In the evolutionary process,the kenes in the knowledge space are equipped with the demand for pursuing higher adaptation,thus the complexity of knowledge is improved,and knowledge capabilities are more specialized and targeted.Knowledge abilities are improved with the evolution,yet tend to have a gentle improving speed when failing to acquire heterogeneity resources or coming across bottleneck.Knowledge expertise fall in the early evolutionary process,but it presents a sharp rise later.The adaptive evolutionary process of knowledge space is unstable.Two types of evolutionary pathways which are incremental and mutational exist in the process.The evolution has the characteristic of symmetry breaking,and is able to evolve spontaneously into a new stable state without external forces.
作者
赵健宇
王铁男
ZHAO Jianyu;WANG Tienan(School of Management,Harbin Institute of Technology,Harbin 150001,China;SchooI of Economics and Management,Harbin Engineering University,Harbin 50001,China)
出处
《系统管理学报》
CSSCI
CSCD
北大核心
2019年第1期10-21,30,共13页
Journal of Systems & Management
基金
国家自然科学基金资助项目(71602041
71602042)
黑龙江省自然科学基金资助项目(QC2017082)
关键词
刺激-反应
战略联盟
知识空间
适应性演化
知识基因
stimulus-response
strategic alliance
knowledge space
adaptive evolution
knowledge gene