文献类型：期刊文献

中文题名：在线群体研讨的信息组织结构研究

英文题名：Information organization structure for online group discussion

作者：李嘉[1,2];张朋柱[2];刘景方[2];吕英杰[2];张晓燕[2]

机构：[1]华东理工大学商学院,上海200237;[2]上海交通大学安泰经济与管理学院,上海200052

年份：2014

卷号：17

期号：9

起止页码：1

中文期刊名：管理科学学报

外文期刊名：Journal of Management Sciences in China

收录：CSTPCD;;北大核心:【北大核心2011】；CSSCI:【CSSCI2014_2016】；

基金：国家自然科学基金资助项目(71371005);国家自然科学青年基金资助项目(71001038)

语种：中文

中文关键词：在线群体研讨;群体支持系统;信息组织结构;任务—技术匹配;复杂度

外文关键词：online group discussion; group support systems; information organization structure; task-technology fitness; complexity

摘要：虽然在线研讨平台已经广泛应用并受到学术界的大量关注,它的信息组织结构却还是停留在非常原始的阶段.关于哪一类信息组织结构更适合在线研讨的研究一直很少,仅有的一些研究也很零散,并且研究结果难以统一,因此就非常迫切需要可以系统化解释在线群体研讨中最优信息组织结构的理论.文章从任务—技术匹配的观点出发,从沟通、协调组织和信息处理3个维度阐述了任务和信息组织结构之间的匹配关系,并将其用于预测不同任务—技术匹配环境下的研讨绩效.设计了实验来验证这种匹配关系与研讨绩效之间的关系.实验结果表明,对主意产生型任务,采用线性结构的研讨平台比采用树状结构的研讨平台具有更高的研讨绩效;对于决策型任务,采用树状结构的研讨平台比采用线性结构的研讨平台具有更高的研讨绩效.所展示的匹配分析的理论和方法具有一定的扩展性,当有新类型任务到来或新技术被发明时,就可以用这种方法去分析新任务和新技术的匹配性,进而预测群体的绩效.
While online discussion platforms have been widely used and received a lot of attention in the information systems communities,its information organization structure is still in the original form.Research that explains what kind of information organization structure is more suitable for online discussion is rare and confused if any.Thus a theory for optimal information organization in online group discussion is highly desirable.In this study,we follow the perspective of task-technology fitness,describe the fitness between tasks and information organization structures from the three perspectives of communication,process structuring,and information processing,and predict group performances based on task-technology fit condition.We also designed an experiment to validate if a match between task and information organization structure will lead to increased performance.The results indicate that for idea generation tasks,using a groupware with linear structures will lead to higher group performances compared to tree structures.On the other hand,for judgment tasks,using a groupware with tree structures will lead to higher group performances compared to linear structures.The proposed theory and method is extendable,which means we can evaluate the fitness between new task types and unseen technology,and predict the group performances.