本研究通过系统性文献综述及欧洲Living Labs联盟(European Network of Living Labs,ENoLL)中167个案例分析比较,理清Living Lab这一开放创新模式的起源、内涵、创新机制研究流派,及不同类型Living Lab中开放设计现状等,为深入理解Livin...本研究通过系统性文献综述及欧洲Living Labs联盟(European Network of Living Labs,ENoLL)中167个案例分析比较,理清Living Lab这一开放创新模式的起源、内涵、创新机制研究流派,及不同类型Living Lab中开放设计现状等,为深入理解Living Lab式社会创新模式,以及构建为开放而设计的概念框架提供基础。展开更多
The co-evolution of social relationships and individual behavior in time and space has important implications, but is poorly understood because of the difficulty of closely tracking the everyday life of a com- plete c...The co-evolution of social relationships and individual behavior in time and space has important implications, but is poorly understood because of the difficulty of closely tracking the everyday life of a com- plete community. We offer evidence that relationships and behavior co-evolve in a student dormitory, based on monthly surveys and location tracking through resident cellular phones over a period of nine months. We demonstrate that a Markov jump process could capture the co-evolution in terms of the rates at which resi- dents visit places and friends. Our co-evolution model will be useful in bridging sensor networks data and organizational dynamics theories, simulating different ways to shape behavior and relationships, and turning mobile phone data into data products.展开更多
文摘本研究通过系统性文献综述及欧洲Living Labs联盟(European Network of Living Labs,ENoLL)中167个案例分析比较,理清Living Lab这一开放创新模式的起源、内涵、创新机制研究流派,及不同类型Living Lab中开放设计现状等,为深入理解Living Lab式社会创新模式,以及构建为开放而设计的概念框架提供基础。
基金Supported by the Army Research Laboratory of USA (No.W911NF-09-2-0053)Air Force Office of Scientific Research of USA (No.FA9550-10-1-0122)Bruno Lepri's research is funded by PERSI project inside the Marie Curie Cofund 7th Framework
文摘The co-evolution of social relationships and individual behavior in time and space has important implications, but is poorly understood because of the difficulty of closely tracking the everyday life of a com- plete community. We offer evidence that relationships and behavior co-evolve in a student dormitory, based on monthly surveys and location tracking through resident cellular phones over a period of nine months. We demonstrate that a Markov jump process could capture the co-evolution in terms of the rates at which resi- dents visit places and friends. Our co-evolution model will be useful in bridging sensor networks data and organizational dynamics theories, simulating different ways to shape behavior and relationships, and turning mobile phone data into data products.
