文献类型：期刊文献

中文题名：网络风险、知识和声誉与跨网络边界学习关系实证研究

英文题名：The Relation Study of the Risk, Knowledge and Reputation of Networks with the Learning Cross the Boundaries of Enterprise Networks

作者：赖红波[1,2];王建玲[3];程建新[2]

机构：[1]华东理工大学社会学博士后科研流动站;[2]华东理工大学艺术设计与传媒学院,上海200237;[3]上海海洋大学工程学院,上海201306

年份：2012

卷号：29

期号：16

起止页码：130

中文期刊名：科技进步与对策

外文期刊名：Science & Technology Progress and Policy

收录：CSTPCD;;国家哲学社会科学学术期刊数据库;北大核心:【北大核心2011】；CSSCI:【CSSCI2012_2013】；

基金：上海市科技发展基金软科学研究项目(11692191000)

语种：中文

中文关键词：网络风险;知识;声誉;跨网络学习

外文关键词：Networks Risk;Knowledge;Reputation;Learning Across The Boundaries of Enterprise Networks

摘要：在分析网络内企业如何通过学习实现转型升级的基础上,建立了网络风险、知识和声誉与跨网络学习的关系模型。基于7大网络内179份调研问卷,运用SPSS统计工具进一步研究了网络风险、知识和声誉与跨网络边界学习的关系及其对组织绩效的影响。研究发现,网络风险和声誉对跨网络组织边界学习有显著影响,而网络知识对跨网络知识边界学习有显著影响。可以看出,在全球化背景下,开展跨网络学习可以突破来自网络有形和无形边界的"锁定",并帮助组织跨越各种"壁垒"。跨网络学习也在转型升级的宏观战略和微观行动之间搭起了一座桥梁,从而不断实现由低级网络阶段向高级网络阶段的动态演进。
Based on the problem of local enterprise in networks how to get development and upgrading in high level through the study, This paper brings forward the relation model of the risk, knowledge and reputation of enterprise networks with the learning cross the boundaries of networks. Through the investigation of the enterprises coming from representative seven local networks and 179 questionnaires, the paper uses the statistical tool of SPSS to analyze the impact of enterprise performance, with the different factors coming from the networks risk, knowledge, reputation, and the learning across the boundaries of enterprise networks. The research of demonstration found that, the risk and the reputation of networks have distinctive effect on the learning across the organized boundaries of enterprise networks, and the knowledge of cluster have distinctive effect to learning cross the knowledge boundaries of enterprise networks. With the background of globalization, the paper consider that the learning across the boundaries of enterprise networks can break through the fetter of the boundaries of enterprise networks, which can be visible or invisible. At the same time, the learning cross the boundaries of enterprise network, put up a bridge between the macro strategy of model transfer upgrading and the microcosmic action, which can get the new opportunity from low level to high level of enterprise networks, and get the dynamic evolvement.