基于综合集成的团队创新支持理论与方法研究
|
摘要
二十一世纪全球经济形态已转变成为以创新为主的知识经济时代。国家和地区的知识创新体系和创新能力,已成为决定一个国家、地区经济和社会发展的重要基础,成为影响其竞争力的关键因素。然而,同国外的企业相比,我国企业总体的自主创新能力仍然十分薄弱,国际竞争力不强,这已成为制约我国经济发展的瓶颈。从我国经济发展和提高企业的国际竞争力出发,当务之急就是要提升企业的自主创新能力。
在知识经济时代,企业间的竞争已经实现了从价格竞争向差异化竞争的转变。在市场竞争中,价格竞争主要反映在企业的成本优势上,而企业的差异化竞争主要表现为产品差异化、服务差异化等方面。新产品开发是企业通过产品差异化建立竞争优势的基础。随着竞争程度的日益激烈,现在的企业为适应新的竞争方式,需要提升其创新能力。惟有成为创新型企业,才能确保企业成功鼎立于现代企业竞争之林。
在当今时代,市场需求的差异化、细分化和个性化不断加强,使得员工队伍向多元化发展。同时,由于创新所涉及的知识相当广泛,许多时候新的想法和解决方案往往会来自于不同的领域,需要利用各种不同知识背景员工的创造力。因此,现代企业通过组建团队,借助团队成员之间的交互,完成复杂的创新任务。对创新团队的有效管理和支持已成为现代企业管理的一个焦点。
团队创新是一个充满不确定的复杂问题:随着科技的发展,产品的复杂性越来越高,这同样增加了创新的复杂性,使得创新需要多种专业知识和技能;团队创新的参与者不仅包括具有不同知识背景的团队成员还包括与团队创新任务相关的专家、利益相关者等,这些参与者分布于企业的多个部门,甚至处于多个地理位置;团队创新的过程是团队成员不断的产生主意和观点、反复论证形成解决方案并实施方案的复杂过程。钱学森等人提出了解决复杂问题的“从定性到定量综合集成方法论”,倡导将专家集体、统计数据和信息知识有机结合起来,构成一个高度智能化的人机交互系统,具有综合集成的各种知识,从感性上升到理性,实现从定性到定量的功能。综合集成方法论能够为团队创新提供很好的方法论基础和系统框架。
本文在综合集成方法论的指导下,系统地分析了团队的创新过程,研究了团队创新支持理论,并设计和实现了一个综合集成团队创新支持系统。
本文的主要研究工作及成果包括:
1.本文系统综述了国内外与团队创新相关研究成果,并指出已有研究中存在的问题和不足之处。内容主要分为四个部分:首先介绍了国内外对团队创新的相关研究;其次综述了已有的知识创新的相关研究;然后综述了信息系统支持团队创新领域的相关研究;最后综述了人机结合综合集成方法论的相关研究。
2.研究了团队创新中人机结合的潜在创新点识别方法。首先对团队所获的知识进行预处理,采用一个统一的模式将团队知识存储到知识库中,并将团队知识以任务为中心进行组织。然后应用一种信息检索的技术(潜在语义分析)计算主意与已有知识间相似度,依据相似度的大小,实现知识的自动排序,帮助团队找出与主意最相关的知识,并最终以人机结合的方式,由专家通过比较主意与最相关的知识而快速识别出新的创造性的主意,即潜在创新点。
3.研究了团队创新中人机结合的潜在创新点选择。为了从团队成员所产生的大量主意中选择出最好的潜在创新点,本文建立了一个人机结合的潜在创新点选择模型。首先进行主意的初步分类。应用一种新的模式识别方法-支持向量机-由团队成员来对主意进行分类,将其分为低质量主意、具有一定质量但不适合于团队任务的主意以及合适的主意三类。主意分类的目的是快速剔除掉那些低质量和明显不适合于团队任务的主意,被剔除掉的主意就不必进入以下阶段由专家对其进行详细的综合评价和研讨,从而可以大大节省评价时间,提高团队创新的效率。其次进行主意综合评价。经过上一阶段的主意分类,那些低质量和不适合于团队任务的主意已经被剔除掉,剩下的是较为合适的有可能被最终选中的主意,在这一阶段,由团队中的相关成员、专家以及任务的利益相关者共同对这些主意进行综合评价。第三阶段就是由专家进行群体决策。这一阶段中参与研讨得专家包括团队中的相关成员、技术专家以及客户等。专家研讨的目的是要选择出最优的潜在创新点,讨论潜在创新点的优点与缺点、对潜在创新点提出改进意见。
4.研究了创新点的进化过程及其可视化。首先分析了创新点的进化过程;其次建立了创新点的进化模型;最后在这个模型的基础上实现了潜在创新点改进过程以及完整创新点形成过程的可视化。创新点进化模型及其可视化动态展示了在团队完成创新任务的过程中,潜在创新点的改进、成熟创新点的形成以及最终得到完整创新点的创新点进化的整个过程,从而可以有效地指导创新点进化的具体过程。
5.研究了团队成员创新价值评估方法。首先在信息透明的基础上由团队成员互评得到每个成员的贡献度;然后根据每个成员的贡献度评估得到每个成员所创造的价值;价值评价的结果可以为团队创新激励机制的建立提供依据。
6.综合集成团队创新支持系统设计及应用研究。首先在研究了潜在创新点的识别与选择、创新点的进化及可视化以及团队成员创新价值评价的基础上,构建了团队创新的支持平台-综合集成团队创新支持系统,并开发实现了综合集成团队创新支持系统。然后对综合集成团队创新支持系统进行应用研究,分析了其实际应用的效果。并以开发注塑模设计系统这个创新任务为实际应用案例,对综合集成团队创新支持系统的应用效果进行了分析和阐述。
本文的主要创新之处归纳为如下四点:
1.研究了团队创新中人机结合的潜在创新点识别。在对团队创新中的知识进行记录和分类组织的基础上,应用潜在语义分析实现了知识的自动排序。知识自动排序的结果能够帮助团队成员找出与主意最相关的知识,通过比较主意及与其最相关的知识可以帮助团队成员识别出新的创造性的主意,即潜在创新点。应用这个人机结合的潜在创新点方法可以避免知识和文献的人工检索与筛选,节省团队和专家大量冗余繁琐的劳动时间,从而为团队创新中潜在创新点的识别提供有效的支持。
2.建立了人机结合的团队创新潜在创新点选择模型。潜在创新点模型是一个分为三个阶段逐步过滤主意,最终达到选择潜在创新点这个目的。第一阶段为主意的初步分类,应用支持向量机这个方法由团队成员来对主意进行分类,将其分为低质量主意、具有一定质量但不适合于团队任务的主意以及合适的主意三类;第二阶段为面向任务的主意综合评价,由团队中的相关成员、专家以及任务的利益相关者根据团队的创新任务共同对较为合适的有可能被最终选中的主意进行综合评价;第三阶段为专家群体决策,讨论主意的优点与缺点、选出最合适的潜在创新点、对潜在创新点提出改进意见。
3.研究了团队创新中创新点进化及其可视化。分析了创新点进化的过程;建立了创新点进化模型;实现了潜在创新点改进过程以及完成创新点形成过程的可视化,应用可视化的方法支持创新点的进化过程。创新点进化模型及其可视化动态展示了在团队完成创新任务的过程中,潜在创新点的改进、成熟创新点的形成以及完整创新点产生的整个过程,从而可以有效地指导创新点进化的具体过程。
4.研究了团队成员的创新价值评估方法。该方法在信息透明的基础上由团队成员互评各成员的贡献度,并进一步评价团队各成员所创造的价值。这种团队内部的成员对自己的工作进行评价的方法,可以给与成员一定的自主权,有利于创造一个宽松的工作环境。价值评价的结果可以为团队创新激励机制的建立提供依据。
In twenty-first century global economy form has turned to knowledge economy era dominated by creation. Knowledge creation system and creative ability of a country or district is an important foundation of determining a country or district’s economy and society development, and becomes a key factor of their competitiveness. However, compared with foreign corporations, the independent creative ability of corporations in our country is still very weak. Low international competitiveness becomes an important factor of restricting economy development of our country. In order to improve Chinese economy development and Chinese corporations’international competitiveness, we have to enhance Chinese corporations’independent creative ability.
In knowledge economy era, competition between corporations has turned from price competition to diversity competition. In market competition, price competition reflects corporation’s cost dominance, while diversity competition reflects product difference and service difference. In nowadays in order to adapt to new competition mode, corporation needs to improve its creative ability. Only if a corporation becomes a creative corporation, it can success in modern society.
Under this circumstances, the only way of corporation’s survive and development is constantly creation. To most corporations creation is the key of maintaining and acquiring competition dominance, and is the basic factor of deciding corporation’s market station and growing potential. If a corporation doesn’t have creative ability, while other competitors have, it by all means will lose.
In the current era, diversity, subdivision and personalization of market demand is ceaselessly enhancing, so employee of corporations is more and more diversified. In the meantime, because creation involves very comprehensive knowledge, new idea and scheme often come from different domains and need creativity of different employees who have diversified knowledge background. Therefore, modern corporations often form teams and use team members’cooperation to accomplish complicated creation task.
Team creation is a complicated problem with much uncertainty. Along with the development of technology, complexity of product is increasing which also causes the complexity of creation. Participants of team creation not only include team members with different knowledge background but also include related experts. These participants distribute in different departments in a corporation, and even distribute in different locations. Team creation process is a complex process of idea generation, improvement, and implementation. Qian Xuesen brought forward a metasynthesis approach for solving complex problem. This approach indicates to synthesize experts, statistic data and information, and construct an artificial human-computer cooperative system. Metasynthesis can provide methodology base and framework for the research of team creation.
In this thesis, on the basis of metasynthesis approach, we systematically analyze creation process of teams, research the theory of team creation support, and design and realize a meta-synthetic team creation support system.
The main work and results of this dissertation are summed up in the following:
1.We systematically review previous correlative researches, and point out problems and deficiencies in these researches. The researches we review are divided into four parts which are researches about team creation, knowledge creation, team creation support using information system, and metasynthesis approach.
2. We research about how to support idea recognition using human-computer cooperative method. First we pre- dispose the knowledge that team acquired by storing it in the knowledge base in a uniform pattern. Then we use one kind of information retrieval technology- Latent Semantic Analysis- to calculate the similar degree of an idea and existing knowledge. According to the similar degree we realize automatic sort of knowledge which can help team members to find out the most correlative knowledge of an idea. In a human-computer cooperation manner, Experts or team members can frequently find out creative idea by comparing idea and the most correlative knowledge.
3. In order to select the best idea in a mass of ideas that team generate, we establish a model of human-computer cooperative team creation idea recognition. First we use a new pattern recognition method- Support Vector Machine- to classify ideas. The ideas are classified to three kinds: ideas of low quality, ideas which are not appropriate to the team task but with good quality, appropriate ideas. The purpose of idea classification is to quickly eliminate those ideas of low quality and which are not appropriate to the team task but with good quality. Eliminated ideas don’t need to enter the next procedure- synthetically evaluation and discussion by experts and customs which can greatly save time of experts and customs.
The second phase of the model is synthetic idea evaluation. In this phase team members, experts and customs together sequence those appropriate ideas.
The last phase is experts’group decision. Because of high creative degree of team task, the selection of idea is difficult to be depicted and figured out by a formula. The creative idea selection is a semi-structured or unstructured problem, so subjective judgment of experts is very important to idea selection. The purpose of experts’discussion is to argument the advantages and disadvantages of idea, select the most appropriate idea, and give opinion about idea improvement implement.
4.We research about support method of creative point’s evolution process. First we analyze creative point’s evolution process. Then we establish produce model of creative point evolution. At last we realize the visualization of idea improvement process and creative point produce process based on the model we establish. Evolution model of creative point and visualization can dynamically reveal the process of idea improvement; scheme forming and creative point produce process. Thereby it cans effectively guidance the concrete process of creative point produce.
5. We research about how to evaluate the value created by each team members. First on the basis of transparent information we find out contribution degree of each team member by commutative evaluation of team members. Then we acquire the value created by each member based on their contribution degree.
6. We design meta-synthetic team creation support system and research about its application. First on the basis of our previous research we design and develop meta-synthetic team creation support system. Then we research about its application and analyze the effect. We use a practical application case to analyze its application effect.
The primary innovations of this thesis are summarized in the following:
1. We research the human-computer cooperative creative idea recognition in team creation. On the basis of knowledge storing and classifying, we realize automatic sort of knowledge used by Latent Semantic Analysis. The result of automatic sort of knowledge can help team members to find out the most correlative knowledge of an idea. Experts or team members can frequently find out creative idea by comparing idea and the most correlative knowledge. Thereby by using this method team members and experts can avoid knowledge search by manpower, and save their time. So this method can effectively support creative idea recognition in team creation.
2. We establish a model of human-computer cooperative creative idea selection in team creation. This model is separated into three phases to filtering ideas; finally reaches the purpose of creative idea recognition. The first phase is idea classification. Using Support Vector Machine we classify ideas to three kinds: ideas of low quality, ideas which are not appropriate to the team task but with good quality, appropriate ideas. The second phase of is idea evaluation. In this phase team members, experts and customs together evaluate those appropriate ideas. The last phase is experts’group decision. The purpose of experts’discussion is to argument the advantages and disadvantages of idea, select the most appropriate idea, and give opinion about idea improvement implement.
3. We establish a model of creative point evolution and its visualization. We analyze the process of creative point evolution; establish the creative point evolution model; realize the visualization of idea improvement process and creative point evolution process and using visualization to support creative point produce process. Evolution model of creative point and visualization can dynamically reveal the process of idea improvement; scheme forming and creative point evolution process. Thereby it cans effectively guidance the concrete process of creative point evolution.
4. We research about the value evaluation method of team creation. This method finds out the contribution degree of each team member by commutative evaluation of team members on the basis of transparent information; then acquires the value created by each member based on their contribution degree. This method of commutative evaluation among team members can give team members independent right to a certain extent which is propitious to create a loose working environment.
在知识经济时代,企业间的竞争已经实现了从价格竞争向差异化竞争的转变。在市场竞争中,价格竞争主要反映在企业的成本优势上,而企业的差异化竞争主要表现为产品差异化、服务差异化等方面。新产品开发是企业通过产品差异化建立竞争优势的基础。随着竞争程度的日益激烈,现在的企业为适应新的竞争方式,需要提升其创新能力。惟有成为创新型企业,才能确保企业成功鼎立于现代企业竞争之林。
在当今时代,市场需求的差异化、细分化和个性化不断加强,使得员工队伍向多元化发展。同时,由于创新所涉及的知识相当广泛,许多时候新的想法和解决方案往往会来自于不同的领域,需要利用各种不同知识背景员工的创造力。因此,现代企业通过组建团队,借助团队成员之间的交互,完成复杂的创新任务。对创新团队的有效管理和支持已成为现代企业管理的一个焦点。
团队创新是一个充满不确定的复杂问题:随着科技的发展,产品的复杂性越来越高,这同样增加了创新的复杂性,使得创新需要多种专业知识和技能;团队创新的参与者不仅包括具有不同知识背景的团队成员还包括与团队创新任务相关的专家、利益相关者等,这些参与者分布于企业的多个部门,甚至处于多个地理位置;团队创新的过程是团队成员不断的产生主意和观点、反复论证形成解决方案并实施方案的复杂过程。钱学森等人提出了解决复杂问题的“从定性到定量综合集成方法论”,倡导将专家集体、统计数据和信息知识有机结合起来,构成一个高度智能化的人机交互系统,具有综合集成的各种知识,从感性上升到理性,实现从定性到定量的功能。综合集成方法论能够为团队创新提供很好的方法论基础和系统框架。
本文在综合集成方法论的指导下,系统地分析了团队的创新过程,研究了团队创新支持理论,并设计和实现了一个综合集成团队创新支持系统。
本文的主要研究工作及成果包括:
1.本文系统综述了国内外与团队创新相关研究成果,并指出已有研究中存在的问题和不足之处。内容主要分为四个部分:首先介绍了国内外对团队创新的相关研究;其次综述了已有的知识创新的相关研究;然后综述了信息系统支持团队创新领域的相关研究;最后综述了人机结合综合集成方法论的相关研究。
2.研究了团队创新中人机结合的潜在创新点识别方法。首先对团队所获的知识进行预处理,采用一个统一的模式将团队知识存储到知识库中,并将团队知识以任务为中心进行组织。然后应用一种信息检索的技术(潜在语义分析)计算主意与已有知识间相似度,依据相似度的大小,实现知识的自动排序,帮助团队找出与主意最相关的知识,并最终以人机结合的方式,由专家通过比较主意与最相关的知识而快速识别出新的创造性的主意,即潜在创新点。
3.研究了团队创新中人机结合的潜在创新点选择。为了从团队成员所产生的大量主意中选择出最好的潜在创新点,本文建立了一个人机结合的潜在创新点选择模型。首先进行主意的初步分类。应用一种新的模式识别方法-支持向量机-由团队成员来对主意进行分类,将其分为低质量主意、具有一定质量但不适合于团队任务的主意以及合适的主意三类。主意分类的目的是快速剔除掉那些低质量和明显不适合于团队任务的主意,被剔除掉的主意就不必进入以下阶段由专家对其进行详细的综合评价和研讨,从而可以大大节省评价时间,提高团队创新的效率。其次进行主意综合评价。经过上一阶段的主意分类,那些低质量和不适合于团队任务的主意已经被剔除掉,剩下的是较为合适的有可能被最终选中的主意,在这一阶段,由团队中的相关成员、专家以及任务的利益相关者共同对这些主意进行综合评价。第三阶段就是由专家进行群体决策。这一阶段中参与研讨得专家包括团队中的相关成员、技术专家以及客户等。专家研讨的目的是要选择出最优的潜在创新点,讨论潜在创新点的优点与缺点、对潜在创新点提出改进意见。
4.研究了创新点的进化过程及其可视化。首先分析了创新点的进化过程;其次建立了创新点的进化模型;最后在这个模型的基础上实现了潜在创新点改进过程以及完整创新点形成过程的可视化。创新点进化模型及其可视化动态展示了在团队完成创新任务的过程中,潜在创新点的改进、成熟创新点的形成以及最终得到完整创新点的创新点进化的整个过程,从而可以有效地指导创新点进化的具体过程。
5.研究了团队成员创新价值评估方法。首先在信息透明的基础上由团队成员互评得到每个成员的贡献度;然后根据每个成员的贡献度评估得到每个成员所创造的价值;价值评价的结果可以为团队创新激励机制的建立提供依据。
6.综合集成团队创新支持系统设计及应用研究。首先在研究了潜在创新点的识别与选择、创新点的进化及可视化以及团队成员创新价值评价的基础上,构建了团队创新的支持平台-综合集成团队创新支持系统,并开发实现了综合集成团队创新支持系统。然后对综合集成团队创新支持系统进行应用研究,分析了其实际应用的效果。并以开发注塑模设计系统这个创新任务为实际应用案例,对综合集成团队创新支持系统的应用效果进行了分析和阐述。
本文的主要创新之处归纳为如下四点:
1.研究了团队创新中人机结合的潜在创新点识别。在对团队创新中的知识进行记录和分类组织的基础上,应用潜在语义分析实现了知识的自动排序。知识自动排序的结果能够帮助团队成员找出与主意最相关的知识,通过比较主意及与其最相关的知识可以帮助团队成员识别出新的创造性的主意,即潜在创新点。应用这个人机结合的潜在创新点方法可以避免知识和文献的人工检索与筛选,节省团队和专家大量冗余繁琐的劳动时间,从而为团队创新中潜在创新点的识别提供有效的支持。
2.建立了人机结合的团队创新潜在创新点选择模型。潜在创新点模型是一个分为三个阶段逐步过滤主意,最终达到选择潜在创新点这个目的。第一阶段为主意的初步分类,应用支持向量机这个方法由团队成员来对主意进行分类,将其分为低质量主意、具有一定质量但不适合于团队任务的主意以及合适的主意三类;第二阶段为面向任务的主意综合评价,由团队中的相关成员、专家以及任务的利益相关者根据团队的创新任务共同对较为合适的有可能被最终选中的主意进行综合评价;第三阶段为专家群体决策,讨论主意的优点与缺点、选出最合适的潜在创新点、对潜在创新点提出改进意见。
3.研究了团队创新中创新点进化及其可视化。分析了创新点进化的过程;建立了创新点进化模型;实现了潜在创新点改进过程以及完成创新点形成过程的可视化,应用可视化的方法支持创新点的进化过程。创新点进化模型及其可视化动态展示了在团队完成创新任务的过程中,潜在创新点的改进、成熟创新点的形成以及完整创新点产生的整个过程,从而可以有效地指导创新点进化的具体过程。
4.研究了团队成员的创新价值评估方法。该方法在信息透明的基础上由团队成员互评各成员的贡献度,并进一步评价团队各成员所创造的价值。这种团队内部的成员对自己的工作进行评价的方法,可以给与成员一定的自主权,有利于创造一个宽松的工作环境。价值评价的结果可以为团队创新激励机制的建立提供依据。
In twenty-first century global economy form has turned to knowledge economy era dominated by creation. Knowledge creation system and creative ability of a country or district is an important foundation of determining a country or district’s economy and society development, and becomes a key factor of their competitiveness. However, compared with foreign corporations, the independent creative ability of corporations in our country is still very weak. Low international competitiveness becomes an important factor of restricting economy development of our country. In order to improve Chinese economy development and Chinese corporations’international competitiveness, we have to enhance Chinese corporations’independent creative ability.
In knowledge economy era, competition between corporations has turned from price competition to diversity competition. In market competition, price competition reflects corporation’s cost dominance, while diversity competition reflects product difference and service difference. In nowadays in order to adapt to new competition mode, corporation needs to improve its creative ability. Only if a corporation becomes a creative corporation, it can success in modern society.
Under this circumstances, the only way of corporation’s survive and development is constantly creation. To most corporations creation is the key of maintaining and acquiring competition dominance, and is the basic factor of deciding corporation’s market station and growing potential. If a corporation doesn’t have creative ability, while other competitors have, it by all means will lose.
In the current era, diversity, subdivision and personalization of market demand is ceaselessly enhancing, so employee of corporations is more and more diversified. In the meantime, because creation involves very comprehensive knowledge, new idea and scheme often come from different domains and need creativity of different employees who have diversified knowledge background. Therefore, modern corporations often form teams and use team members’cooperation to accomplish complicated creation task.
Team creation is a complicated problem with much uncertainty. Along with the development of technology, complexity of product is increasing which also causes the complexity of creation. Participants of team creation not only include team members with different knowledge background but also include related experts. These participants distribute in different departments in a corporation, and even distribute in different locations. Team creation process is a complex process of idea generation, improvement, and implementation. Qian Xuesen brought forward a metasynthesis approach for solving complex problem. This approach indicates to synthesize experts, statistic data and information, and construct an artificial human-computer cooperative system. Metasynthesis can provide methodology base and framework for the research of team creation.
In this thesis, on the basis of metasynthesis approach, we systematically analyze creation process of teams, research the theory of team creation support, and design and realize a meta-synthetic team creation support system.
The main work and results of this dissertation are summed up in the following:
1.We systematically review previous correlative researches, and point out problems and deficiencies in these researches. The researches we review are divided into four parts which are researches about team creation, knowledge creation, team creation support using information system, and metasynthesis approach.
2. We research about how to support idea recognition using human-computer cooperative method. First we pre- dispose the knowledge that team acquired by storing it in the knowledge base in a uniform pattern. Then we use one kind of information retrieval technology- Latent Semantic Analysis- to calculate the similar degree of an idea and existing knowledge. According to the similar degree we realize automatic sort of knowledge which can help team members to find out the most correlative knowledge of an idea. In a human-computer cooperation manner, Experts or team members can frequently find out creative idea by comparing idea and the most correlative knowledge.
3. In order to select the best idea in a mass of ideas that team generate, we establish a model of human-computer cooperative team creation idea recognition. First we use a new pattern recognition method- Support Vector Machine- to classify ideas. The ideas are classified to three kinds: ideas of low quality, ideas which are not appropriate to the team task but with good quality, appropriate ideas. The purpose of idea classification is to quickly eliminate those ideas of low quality and which are not appropriate to the team task but with good quality. Eliminated ideas don’t need to enter the next procedure- synthetically evaluation and discussion by experts and customs which can greatly save time of experts and customs.
The second phase of the model is synthetic idea evaluation. In this phase team members, experts and customs together sequence those appropriate ideas.
The last phase is experts’group decision. Because of high creative degree of team task, the selection of idea is difficult to be depicted and figured out by a formula. The creative idea selection is a semi-structured or unstructured problem, so subjective judgment of experts is very important to idea selection. The purpose of experts’discussion is to argument the advantages and disadvantages of idea, select the most appropriate idea, and give opinion about idea improvement implement.
4.We research about support method of creative point’s evolution process. First we analyze creative point’s evolution process. Then we establish produce model of creative point evolution. At last we realize the visualization of idea improvement process and creative point produce process based on the model we establish. Evolution model of creative point and visualization can dynamically reveal the process of idea improvement; scheme forming and creative point produce process. Thereby it cans effectively guidance the concrete process of creative point produce.
5. We research about how to evaluate the value created by each team members. First on the basis of transparent information we find out contribution degree of each team member by commutative evaluation of team members. Then we acquire the value created by each member based on their contribution degree.
6. We design meta-synthetic team creation support system and research about its application. First on the basis of our previous research we design and develop meta-synthetic team creation support system. Then we research about its application and analyze the effect. We use a practical application case to analyze its application effect.
The primary innovations of this thesis are summarized in the following:
1. We research the human-computer cooperative creative idea recognition in team creation. On the basis of knowledge storing and classifying, we realize automatic sort of knowledge used by Latent Semantic Analysis. The result of automatic sort of knowledge can help team members to find out the most correlative knowledge of an idea. Experts or team members can frequently find out creative idea by comparing idea and the most correlative knowledge. Thereby by using this method team members and experts can avoid knowledge search by manpower, and save their time. So this method can effectively support creative idea recognition in team creation.
2. We establish a model of human-computer cooperative creative idea selection in team creation. This model is separated into three phases to filtering ideas; finally reaches the purpose of creative idea recognition. The first phase is idea classification. Using Support Vector Machine we classify ideas to three kinds: ideas of low quality, ideas which are not appropriate to the team task but with good quality, appropriate ideas. The second phase of is idea evaluation. In this phase team members, experts and customs together evaluate those appropriate ideas. The last phase is experts’group decision. The purpose of experts’discussion is to argument the advantages and disadvantages of idea, select the most appropriate idea, and give opinion about idea improvement implement.
3. We establish a model of creative point evolution and its visualization. We analyze the process of creative point evolution; establish the creative point evolution model; realize the visualization of idea improvement process and creative point evolution process and using visualization to support creative point produce process. Evolution model of creative point and visualization can dynamically reveal the process of idea improvement; scheme forming and creative point evolution process. Thereby it cans effectively guidance the concrete process of creative point evolution.
4. We research about the value evaluation method of team creation. This method finds out the contribution degree of each team member by commutative evaluation of team members on the basis of transparent information; then acquires the value created by each member based on their contribution degree. This method of commutative evaluation among team members can give team members independent right to a certain extent which is propitious to create a loose working environment.
引文
1.陈劲,永续发展-企业技术创新透析[M].北京:科学出版社, 2001.
2.钱学森,于景元,戴汝为.一个科学的新领域——开放的复杂巨系统及其方法论[J].自然杂志, 1990, 13(1): 3-10.
1.熊彼特,约.,经济发展理论[M].北京:商务印书馆. 1990: 73.
2. OECD, The nature of innovation and the evolution of the productive system. technology and productivity-the challenge for economic policy [R]. Paris: OECD. 1991: 303-314.
3. Couger, J.D., Creative problem solving and opportunity finding [M]. Massachusetts, Boyd & Fraser publishing Co.. 1995: 35.
4. Leonard, S., When sparks fly - igniting creativity in Groups [M]. Boston: Harvard Business School Press. 1999:103-105.
5. Mumford, M.D., Scott, G. M., Gaddis, B., Strange, J. M., Leading creative people: Orchestrating expertise and relationships [J]. Leadership Quarterly, 2002. (13): 705-750.
6. West, M.A., Sparkling fountains or stagnant ponds: An integrative model of creativity and innovation implementation in work groups [J]. Applied psychology: an international review, 2002. 51(3): 355-387.
7. Hoegl, M., Parboteeah, K. P., Munson, C. L., Team Level antecedents of individuals' knowledge networks [J]. Decision sciences, 2003. 34(4): 741-770.
8. Katzenbach, J.R., Smith, D. K., The discipline of teams [J]. Harvard Business Review, 2005. 83(7/8): 162-171.
9. Quick, T.L., Winning team plays [J]. Supervisory management, 1995. 40(1): 12-13.
10. Piercy, N.F., Morgan, N. A., Organizational context and behavioural problems as determinants of the effectiveness of the strategic marketing planning process [J]. Journal of marketing management, 1990. 6(2): 127-143.
11.袁和平,团队管理[M].深圳:海天出版社, 2002:. 49.
12. Wallas G., The Art of Thought [M], New York: Harcort Brace. 1926: 80-82.
13. Simon, H.A., Scientific Discovery and The Psychology of Problem Solving [M], University of Pittsburgh Press, 1966.
14. Amabile, T.M., The social psychology of creativity [M]. New York: Springer-Verlag New York Incorporated, 1983.
15. Finke, R., Ward, T. Smith, S., Creative cognition [M]. Cambridge: MIT Press,1992.
16. Aihara K., Hori, K., Enhancing creativity through reorganizing mental space concealed in aresearch notes stack [J], Knowledge-Based System, 1998. 11(7): 469-478.
17. Isaksen, S.G., Dorval, K. B., Treffinger, D. J., Creative Approaches to Problem Solving [M]. Kendall and Hunt, Dubuque, IA, 1994.
18. Findlay, C.S., Lumsden, C. J., The creative mind: Toward and evolutionary theory of discovery and innovation [J]. Journal of Biological and Social Structures, 1988. 11: 3-55.
19. Evaristo, R., Eierman, M. A., Creativity in idea generation [C]. Proceeding of the Twenty-Sixth Hawaii International Conference on Systems Sciences, 1993: 369-377.
20.道格拉斯.诺斯,经济史上的结构与变迁[M].商务印书馆. 1992: 161.
21. Polanyi, M., The Tacit Dimension [M], London:Routledge and Kegan paul, 1966.
22. Nonaka, I., Takeuchi, H., The Knowledge Creating Company: How Japanese Companies Create the Dynamics of Innovation [M]. New York: Oxford University Press, 1995.
23. Byounggu, C., Heeseok, L., Knowledge management strategy and its link to knowledge creation process [J]. Expert Systems with Applications, 2002. 23(3): 173-187.
24. Fong, P.S.W., Knowledge creation in multidisciplinary project teams: an empirical study of the processes and their dynamic interrelationships [J]. International Journal of Project Management, 2003. 21(7): 479-486.
25. Hoegl, M., Schulze, A., How to Support Knowledge Creation in New Product Development: An Investigation of Knowledge Management Methods [J]. European Management Journal, 2005. 23(3): 263-273.
26. Gregorio, M., Pedro, L., Jose E., Processes of knowledge creation in knowledge-intensive firms: Empirical evidence from Boston's Route 128 and Spain [J]. Technovation, 2008, 28 (4): 222-230.
27. Parent, M., Gallupe, R.B., Salisbury W.D., Handelman, J.M., Knowledge creation in focus groups: can group technologies help [J]? Information & Management, 2000. 38(1): 47-58.
28. Couger, J.D., A Framework for Research on Creativity/Innovation in IS Organizations [C], Proceedings of the 29th Annual Hawaii International Conference on System Sciences. 1996.
29. Nagasundaram, M., Dennis, A. R., When a group is not a group: The cognitive foundation of group idea generation [J]. Small Group Research, 1993. 24(4): 463-489.
30. MacCrimmon, K.R., Wagner, C., Supporting problem formulation and alternative generation in managerial decision making [C]. Proceedings Hawaiian International Conference on Systems Science HICSS-24, 1991: 432-441.
31. Proctor, T., Experiments with two computer assisted creative problem solving aids [J]. Omega,1988. 17(2): 197-200.
32. Proctor, T., Generating insights with a computer [J]. Creativity and Innovation Yearbook, 1988: 87-100.
33. Young, L.F., Right brained decision support systems [J]. Database, 1983. 14(4): 28-36.
34. Elam, J.J., Mead, M., Can software influence creativity [J]. Information Systems Research, 1990. 1(1): 1-22.
35. Durand, D.E., VanHuss., S. E., Creativity software and DSS: Cautionary findings [J]. Information and Management, 1992. 23: 1-6.
36. MacCrimmon, K.R., Wagner, C., Stimulating ideas through creativity software [J]. Management Science, 1994. 40(11): 1514-1532.
37. Massetti, B., An empirical examination of the value of creativity support systems on idea generation [J]. MIS Quarterly, 1996. 20(1): 83-97.
38. Wagner, C., Creative behavior through basic inferences: Evidence from person-computer interactions [J]. Journal of Creative Behavior, 1996. 30(2): 105-125.
39. Marakas, G., Elam, J. J., Creativity enhancement in Problem Solving: Through software or process [J]? Management Science, 1997. 43(8): 1136-1146.
40. Wierenga, B., Bruggen, G. H., The Dependent Variable in Research Into the Effects of Creativity Support Systems: Quality and Quantity of Ideas [J]. MIS Quarterly, 1998. 22(1): 81-87.
41. Malaga, R.A., The effect of stimulus modes and associative distance in individual creativity support systems [J]. Decision Support Systems, 2000. 29(2): 125-141.
42. Hewett, T.T., Informing the design of computer-based environments to support creativity [J]. International Journal of Human-Computer Studies, 2005. 63(4): 383-409.
43. Forgionne, G., Newman, J., An experiment on the effectiveness of creativity enhancing decision-making support systems [J]. Decision Support Systems, 2007. 42(4): 2126-2136.
44. Applegate, L.M., Technology support for cooperative work: a framework for studying introduction and assimilation in organizations [J]. Journal of Organizational Computing, 1991. 1: 11-39.
45. Couger, J.D., Flynn, P., Hellyer, D., Enhancing the creativity of reengineering [J]. Information Systems Management, 1994. 11(2): 24-29.
46. Nunamaker Jr., J.F., Dennis, A. R., Valacich, J. S., Vogel, D. R., George, J. F., Electronic meeting systems to support group work [J]. Communications of the ACM, 1991. 34(7): 40-61.
47. Diehl, M., Stroebe, W., Productivity loss in brainstorming groups: toward a solution of a riddle [J].Journal of Personality and Social Psychology, 1987. 53(3): 497-509.
48. Walker, H.A., Ilardi, B. C., McMahon, A. M., Fennell, M. L., Gender, interaction, and leadership [J]. Social Psychology Quarterly, 1996. 59(3): 255-272.
49. Duncan, N., Paradice, D., Creativity in GDSS: An integration of creativity, group dynamics, and problem solving theory [C], Proceedings of the Twenty-Fifth Hawaii International Conference on Systems Sciences. 1992: Hawaii.
50. Fellers, J.W., Bostrom, R. P., Application of group support systems to promote creativity in information systems organizations [C]. Proceedings of the Twenty-Sixth Hawaii International Conference on Systems Sciences, 1993: 332-341.
51. Lobert, B.M., The impact of group support systems on idea incubation: Exploring creativity in information system development projects. The City University of New York, 1993.
52. Nagasundaram, M., Bostrom, R. P., The Structuring of Creative Processes: Implications for GSS Research [C], Proceedings of the Twenty-Seventh Hawaii International Conference on Systems Sciences. 1994: Hawaii.
53. Nagasundaram, M., Bostrom, R. P., The Structuring of Creative Processes using GSS: A Framework for Research [J]. Journal of Management Information Systems, 1995. 11(3): 89-116.
54. Nagasundaram, M., Bostrom, R. P., Structuring Creativity with GSS: An Experiment [C]. Proceedings of the First Americas Conference on Information Systems, 1995: 258-260.
55. Ocker, R., Hiltz, S. R., Turoff, M., Fjermestad, J., The effects of distributed group support and process structuring on software requirements development teams: Results on creativity and quality [J]. Journal of Management Information Systems, 1996. 12(3): 127-153.
56. McFadzea, E., Improving group productivity with group support systems and creative problem solving techniques [J]. Creativity and innovation management, 1997. 6(4): 218-225.
57. Klein, E.E., Dologite, D. G., The role of computer support tools and gender composition in innovative information system idea generation by small groups [J]. Computers in Human Behavior, 2000. 16(2): 111-139.
58. Hender, J., Dean, D., Rodgers, T., Nunamaker Jr, J., Improving Group Creativity: Brainstorming Versus Non-brainstorming Techniques in a GSS Environment [C]. Proceedings of the 34th Hawaii International Conference on System Sciences, 2001.
59. Shaw, D., Creativity and learning through electronic group causal mapping [J]. International Journal of Innovation and Learning. 2004. 1(4): 364-377.
60.吴江,赵宗涛,创新支持系统模型及开发技术[J].西北大学学报, 2005. 35(5): 531-535.
61.李欣苗,面向任务的团队创新支持理论及其系统研究,上海交通大学博士学位论文,2005.
62.钱学森,于景元,戴汝为,一个科学的新领域——开放的复杂巨系统及其方法论[J].自然杂志, 1990. 13(1): 3-10.
63.王寿云,于景元,戴汝为,开放的复杂巨系统[M].杭州:浙江科学技术出版社, 1996.
64.于景元,涂元季,从定性到定量的综合集成方法—案例研究[J].系统工程理论与实践, 2002. 5: 1-2.
65.于景元,钱学森的现代科学技术体系与综合集成方法论.中国工程科学, 2001. 3(11): 10-18.
66.于景元,周晓纪,从定性到定量综合集成方法的实现和应用[J].系统工程理论与实践, 2002. 10: 26-32.
67.戴汝为,操龙兵,综合集成研讨厅的研制[J].管理科学学报, 2002. 5(3): 10-16.
68.唐锡晋,刘怡君,群思考的计算机支持工具研究.西部开发与系统工程[M].北京:海洋出版社, 2002: 351-355.
69.张兴学,张鹏翥,群体决策研讨意见分布可视化研究[J].管理科学学报, 2005. 8(4): 15-27.
70. Bostrom, R. P., Research in Creativity and GSS. Proceedings of the 31st Annual Hawaii International Conference on System Sciences, IEEE, Kohala Coast, HI, 1998: 391-404.
1. Letsche, T. A., Berry, M. W., Large-Scale Information Retrieval with Latent Semantic Indexing [J]. Information Sciences, 1997. 100(1): 105-137.
2. Andrews, J., Creative ideas take time: business practices that help product managers cope with time pressure [J]. The journal of product innovation management, 1996. 13(6): 553-554.
3. Chen, H., Schuffels, C., Orwig, R., Internet categorization and search: a self-organizing approach [J]. Journal of Visual Communication and Image Representation, 1996. 7(1): 88-102.
4. George, J. F., Easton, G. K., Nunamaker, J. F., Northcraft, G. B. A study of collaborative group work with and without computer-based support [J]. Information Systems Research, 1990. 1(4): 394-415.
5. Chen, H., Hsu, P., Orwig, R., Hoopes, L., Nunamaker, J. F. Automatic Concept Classification of Text from Electronic Meetings [J]. Communications of the ACM, 1994. 37(10): 56-73.
6. Roussinov, D., Zhao, L., Automatic discovery of similarity relationships through Web mining [J]. Decision Support Systems, 2002. 35(1): p. 149-166.
7. Duen-Ren Liu, Chik-Kun Ke, Knowledge support for problem-solving in a production process: A hybrid of knowledge discovery and case-based reasoning [J]. Expert Systems with Applications, 2007. 33: 147-161.
8.邱明,语义相似性度量及其在设计管理系统中的应用.浙江大学博士学位论文, 2006.
9.姜韶华,科研项目管理中的文本挖掘方法研究及应用.大连理工大学博士学位论文, 2006.
10. Ellis, C. A., Gibbs, J.S., Rein, G. L., Groupware: some issues and experiences [J]. Communications of the ACM, 1991. 34(1): 38-58.
11.李欣苗,面向任务的团队创新支持理论及其系统研究,上海交通大学博士学位论文, 2005.
12.焦玉英,信息检索进展[M]. 2003,北京:科学出版社. 17-57.
13. Salton, G., Wong, A., Yang, C. S., a vector space model for automatic indexing [J]. Communications of the ACM, 1975. 18(11): 613-620.
14. Dumais S., Furnas, G., Landauer T., Scott D., et al, Using Latent Semantic Analysis to Improve Access to Textual Information [C]. Proceedings of Computer Human Interaction, 1988: 281-285.
15.林鸿飞,姚天顺,基于潜在语义索引的文本浏览机制[J].中文信息学报, 2000. 14(5): 49-56.
16. Kendall, M.G., Rank correlation methods [M]. London: Griffin, 1948.
1. Hewett, T.T., Informing the design of computer-based environments to support creativity [J]. International Journal of Human-Computer Studies, 2005. 63: 27.
2. Briggs, R.O., Nunamaker, J.F. Jr, Sprague, R.H. Jr, 1001 unanswered research questions in GSS [J]. Journal of Management Information Systems, 1998. 14(3): 3.
3. MumFord, M. D., Something Old, something new: Revisiting Guilford’s conception of creative problem solving. and Creativity Research Journal, 2000: 267–276.
4. Reiter-Palmon, R., Illies, J.J., Leadership and creativity Understanding leadership from a creative problem-solving perspective [J]. The Leadership Quarterly, 2004, 15:35-53.
5. Chen, H.,Hsu, P.,Orwig, R.,Hoopes, L.,Nunamaker, J. F., Automatic concept classification of text from electronic meetings [J]. Communications of the ACM, 1994. 37(10): 56-73.
6. Montoya-Weiss, M.M., O'Driscoll, T.M., From Experience: Applying Performance Support Technology in the Fuzzy Front End [J]. The journal of product innovation management, 2000. 17(2): 143-161.
7. Olshavsky R.W., Spreng R.A., An exploratory study of the innovation evaluation process [J]. The journal of product innovation management, 1996. 13(6): 512-529.
8.刘文海,产品概念设计方案的评价决策技术及应用研究,大连理工大学博士学位论文, 2005.
9.薛立华,黄洪钟,张旭,古莹奎,赵宏,概念设计方案评价和决策线性物理规划模型研究[J].大连理工大学学报, 2005. 45(4): 562-565.
10.杨明顺,林志航,李言,李鹏阳,袁启龙,产品总体方案评价与优选的证据推理决策[J].工程图学学报, 2006(2): 32-38.
11. Shih, H. S., Wang, C. H., Lee, E, S., A Multiattribute GDSS for Aiding Problem-Solving [J]. Mathematical and Computer Modelling 2004. 39(11): 1397-1412.
12. Valacich, J. S., Jessup, L.M., Dennis, A. R., Nunamaker, J. F., Electronic meeting support: The group systems concept [J]. International Journal of Man-Machine Studies, 1992. 34: 261-282.
13.王刊良,席酉民,汪应洛,电子头脑风暴(EBS)研究[J].系统工程, 1994. 12(5): 1-8.
14. Diehl, M., Stroebe, W., Productivity loss in brainstorming groups: Toward the solution of a riddle [J]. Jounral of Personality and Social Psychology, 1987. 53(3): 497-509.
15.张学工,关于统计学习理论与支持向量机[J].自动化学报, 2000. 26(1): 32-42.
16.王国胜,钟义信,支持向量机的理论基础—统计学习理论[J].计算机工程与应用, 2001. 19: 19-20.
17.谭东宁,谭东汉,小样本机器学习理论:统计学习理论[J].南京理工大学学报, 2001. 25(1): 108-112.
18.任建峰,郭雷,李刚,多类支持向量机的自然图像分类[J].西北工业大学学报, 2005. 23(3): 295-298.
19.马勇,丁晓青,基于层次型支持向量机的人脸检测[J].清华大学学报(自然科学版), 2003. 43(1): 35-38.
20. Cooper, R. G., Kleinschmidt, E. J., An investigation into the new product development process: Steps, deficiencies, impact [J]. Journal of Product Innovation Management, 1986, 3: 374-391.
21.朱龙英,朱如鹏,刘正埙,基于信息公理的产品设计方案评价方法[J].南京航空航天大学学报, 2005. 37(3): 386-390.
22.杨明顺,林志航,李言,李鹏阳,袁启龙,产品总体方案评价与优选的证据推理决策[J].工程图学学报, 2006(2): 32-38.
23.边肇祺,张学工,模式识别[M].北京:清华大学出版社, 2000.
24. Vapnik, V., The nature of Statistical Learning Theory [M]. New York: Springer-Verlag, 1995.
25. Knerr, S., Personnaz, L., Dreyfus, G., Single-layer learning revisited : A stepwise procedure for building and training a neural network [A], Neurcomputing : Algorithms , Architectures and Applications. 1999, New York : Springer-Verlag.
26. Saaty, T.L., The Analytic Hierarchy Process [M]. RWS Pub, Pittsburgh, PA, 1990.
1. Bostrom, R. P., Research in Creativity and GSS. Proceedings of the 31st Annual Hawaii International Conference on System Sciences, IEEE, Kohala Coast, HI, 1998: 391-404.
2. Wallas G., The Art of Thought [M], New York: Harcort Brace. 1926: 80-82.
3. MacCrimmon, K. R., Wagner, C., Stimulating idea through creativity software [J]. Management Science, 1994. 40(11): 1514-1532.
4. Massetti, B., An empirical examination of the value of creativity support systems on idea generation [J]. MIS Quarterly, 1996. 20(1): 83-97.
5. Malaga, R.A., The effect of stimulus modes and associative distance in individual creativity support systems [J]. Decision Support Systems, 2000. 29(2): 125-141.
6. Hewett, T.T., Informingthe design of computer-based environments to support creativity [J]. International Journal of Human-Computer Studies, 2005. 63(4): 383-409.
7. Elam, J.J., Mead, M., Can software influence creativity [J]. Information Systems Research, 1990. 1(1): 1-22.
8. Mumford, M.D., Scott, G. M., Gaddis, B., Strange, J. M., Leading creative people: Orchestrating expertise and relationships [J]. Leadership Quarterly, 2002. (13): 705-750.
9. West, M.A., Sparkling fountains or stagnant ponds: An integrative model of creativity and innovation implementation in work groups [J]. Applied psychology: an international review, 2002. 51(3): 355-387.
10.周宁,杨峰,信息可视化系统的RDV模型研究[J].情报学报, 2003. 22(5): 619-624.
11. Zhou Ning , Liu Wei, On the methods of information resources visualization [C]. The Proceedings of Digital Library-IT Opportunities and Challenges in the New Millennium. 2002.
12. Xiang, Y., Chau, M., Atabakhsh, H., Chen, H., Visualizing Criminal Relationships: Comparison of a Hyperbolic Tree and a Hierarchical List 2006 [J]. Decision Support Systems. 41(1): 69-83.
13. Forgionne, G., Newman, J., An experiment on the effectiveness of creativity enhancing decision-making support systems [J]. Decision Support Systems, 2007. 42(4): 2126-2136.
14. van der Lugt R. Developing a graphic tool for creative problem solving in design groups. Design Studies, 2000. 21(5): 505-522.
15.唐锡晋,刘怡君,群思考的计算机支持工具研究.西部开发与系统工程[M].北京:海洋出版社, 2002: 351-355.
16.李欣苗,面向任务的团队创新支持理论及其系统研究,上海交通大学, 2005.
1. Schumann , Paul A., Ransley , Jr., Derek L., Prestwood , Donna C. L., Measuring R&D Performance [J]. Research Technology Management, 1995. 38(3): 47-52.
2. Tipping, J.W., Zeffren, E., Fusfeld, A.R., Assessing the value of your technology [J]. Research Technology Management, 1995. 38(5): 22-39.
3. Lee, M., Son, B., Lee, H., Measuring R&D effectiveness in Korean companies [J]. Research Technology Management, 1996. 39(6): 28-31.
4. Carroll, J. J., Newbould, G. D., NPV vs. IRR with capital budgeting, which do you choose [J]? Healthcare Financial Management, 1986. 40(11): 62-67.
5. Allen, D., DCF: elegant theory of sound practice [J]? Management Accounting (London), 1992. 8: 62.
6. Cheng, C. S. A., Kite, D., Radtke, R., The applicablity and usage of NPV and IRR capital budgeting techniques [J]. Managerial Finance, 1994. 20(7): 94-104.
7. Akalu, M.M., Re-examining project appraisal and control: developing a focus on wealth creation [J]. International Journal of Project Management, 2001. 19(7): 357-383.
8. Ekern, S., An option pricing approach to evaluating petroleum project [J]. Energy Economics, 1988. 23(3): 91-99.
9. Roll , R., What every CFO should know about scientific progress in financial economics: what is known and what remains to be resolved [J]. Financial Management, 1994. 23(2): 69-75.
10. Copeland, T., Weiner, J., Proactive management of uncertainty [J]. The McKinsey Quarterly, 1990. 10(4): 133-152.
1. Dennis, A.R., George, J. F., Jessup, L. M., Nunamaker, J. F., Vogel, D. R., Information technology to support electronic meetings [J]. MIS Quarterly, 1988. 12(4): 591-624.
2. Jelassi, M.T., Beauclair, R. A., An integrated framework for group decision support system design [J]. Information and Management, 1987. 13(3): 143-155.
3. Nunamaker Jr., J.F., Dennis, A. R., Valacich, J. S., Vogel, D. R., George, J. F., Electronic meeting systems to support group work [J]. Communications of the ACM, 1991. 34(7): 40-61.
4. Couger, J.D., A framework for research on creativity/innovation in IS organizations [C]. In Proceedings of the 29th Annual Hawaii International Conference on System Science, 1996. 1: 30-38.
5. Massetti, B., An empirical examination of the value of Creativity Support Systems on idea generation [J]. MIS Quarterly, 1996. 20(1): 83-97.
6. Marakas, G.., Elam, J. J., Creativity enhancement in problem solving: through software or process [J]? Management Science, 1997. 43(8): 1136-1146.
7. Robert P. Bostrom, M.N., Research in creativity and GSS [C]. IEEE Proc. 31st Annual Hawaii International Conference on System Sciences, 1998: 391-404.
8. Fischer, G., McCall, R., Morch, A. JANUS: integrating hypertext with a knowledge-based design environment [C]. Proceedings of the Hypertext'89 Conference. New York: ACM. 1989.
9. Streitz, N., Hannemann, J., Thuring, M. From ideas and arguments to hyper-documents: travelling through activity spaces [C]. Proceedings of the Hypertext'89 Conference. New York: ACM. 1989.
10. Lee, J. SIBYL: a tool for managing group decision rationale [C]. Proceedings of the CSCW'90 Conference. New York: ACM. 1990.
11. Shum, S., MacLean, A., Forder, J., Hammond, N., Summarising the evolution of design concepts within a design rationale framework [C]. Adjunct Proceedings of InterCHI'93: ACM/IFIP Conference on Human Factors in Computing Systems. The Netherlands: Amsterdam. 1993.
12. Metcalfe, M., Argumentative systems for IS design [J]. Information Technology and People, 2002. 15(1): 60-73.
13. Bose, R., Group support systems: technologies and products selection [J]. Industrial Management and Data Systems, 2003. 103(9): 649-656.
14.李欣苗,面向任务的团队创新支持理论及其系统研究,上海交通大学博士学位论文, 2005.
15. Townsend A.M., DeMarie S.M., Hendrickson A.R., Virtual teams: technology and the workplace of the future [J]. Academy of Management Executive, 1998. 12(3): 17-29.
16. Erran, C., Global software teams [M]. Upper Saddle River: NJ: Prentice Hall. 1999.
2.钱学森,于景元,戴汝为.一个科学的新领域——开放的复杂巨系统及其方法论[J].自然杂志, 1990, 13(1): 3-10.
1.熊彼特,约.,经济发展理论[M].北京:商务印书馆. 1990: 73.
2. OECD, The nature of innovation and the evolution of the productive system. technology and productivity-the challenge for economic policy [R]. Paris: OECD. 1991: 303-314.
3. Couger, J.D., Creative problem solving and opportunity finding [M]. Massachusetts, Boyd & Fraser publishing Co.. 1995: 35.
4. Leonard, S., When sparks fly - igniting creativity in Groups [M]. Boston: Harvard Business School Press. 1999:103-105.
5. Mumford, M.D., Scott, G. M., Gaddis, B., Strange, J. M., Leading creative people: Orchestrating expertise and relationships [J]. Leadership Quarterly, 2002. (13): 705-750.
6. West, M.A., Sparkling fountains or stagnant ponds: An integrative model of creativity and innovation implementation in work groups [J]. Applied psychology: an international review, 2002. 51(3): 355-387.
7. Hoegl, M., Parboteeah, K. P., Munson, C. L., Team Level antecedents of individuals' knowledge networks [J]. Decision sciences, 2003. 34(4): 741-770.
8. Katzenbach, J.R., Smith, D. K., The discipline of teams [J]. Harvard Business Review, 2005. 83(7/8): 162-171.
9. Quick, T.L., Winning team plays [J]. Supervisory management, 1995. 40(1): 12-13.
10. Piercy, N.F., Morgan, N. A., Organizational context and behavioural problems as determinants of the effectiveness of the strategic marketing planning process [J]. Journal of marketing management, 1990. 6(2): 127-143.
11.袁和平,团队管理[M].深圳:海天出版社, 2002:. 49.
12. Wallas G., The Art of Thought [M], New York: Harcort Brace. 1926: 80-82.
13. Simon, H.A., Scientific Discovery and The Psychology of Problem Solving [M], University of Pittsburgh Press, 1966.
14. Amabile, T.M., The social psychology of creativity [M]. New York: Springer-Verlag New York Incorporated, 1983.
15. Finke, R., Ward, T. Smith, S., Creative cognition [M]. Cambridge: MIT Press,1992.
16. Aihara K., Hori, K., Enhancing creativity through reorganizing mental space concealed in aresearch notes stack [J], Knowledge-Based System, 1998. 11(7): 469-478.
17. Isaksen, S.G., Dorval, K. B., Treffinger, D. J., Creative Approaches to Problem Solving [M]. Kendall and Hunt, Dubuque, IA, 1994.
18. Findlay, C.S., Lumsden, C. J., The creative mind: Toward and evolutionary theory of discovery and innovation [J]. Journal of Biological and Social Structures, 1988. 11: 3-55.
19. Evaristo, R., Eierman, M. A., Creativity in idea generation [C]. Proceeding of the Twenty-Sixth Hawaii International Conference on Systems Sciences, 1993: 369-377.
20.道格拉斯.诺斯,经济史上的结构与变迁[M].商务印书馆. 1992: 161.
21. Polanyi, M., The Tacit Dimension [M], London:Routledge and Kegan paul, 1966.
22. Nonaka, I., Takeuchi, H., The Knowledge Creating Company: How Japanese Companies Create the Dynamics of Innovation [M]. New York: Oxford University Press, 1995.
23. Byounggu, C., Heeseok, L., Knowledge management strategy and its link to knowledge creation process [J]. Expert Systems with Applications, 2002. 23(3): 173-187.
24. Fong, P.S.W., Knowledge creation in multidisciplinary project teams: an empirical study of the processes and their dynamic interrelationships [J]. International Journal of Project Management, 2003. 21(7): 479-486.
25. Hoegl, M., Schulze, A., How to Support Knowledge Creation in New Product Development: An Investigation of Knowledge Management Methods [J]. European Management Journal, 2005. 23(3): 263-273.
26. Gregorio, M., Pedro, L., Jose E., Processes of knowledge creation in knowledge-intensive firms: Empirical evidence from Boston's Route 128 and Spain [J]. Technovation, 2008, 28 (4): 222-230.
27. Parent, M., Gallupe, R.B., Salisbury W.D., Handelman, J.M., Knowledge creation in focus groups: can group technologies help [J]? Information & Management, 2000. 38(1): 47-58.
28. Couger, J.D., A Framework for Research on Creativity/Innovation in IS Organizations [C], Proceedings of the 29th Annual Hawaii International Conference on System Sciences. 1996.
29. Nagasundaram, M., Dennis, A. R., When a group is not a group: The cognitive foundation of group idea generation [J]. Small Group Research, 1993. 24(4): 463-489.
30. MacCrimmon, K.R., Wagner, C., Supporting problem formulation and alternative generation in managerial decision making [C]. Proceedings Hawaiian International Conference on Systems Science HICSS-24, 1991: 432-441.
31. Proctor, T., Experiments with two computer assisted creative problem solving aids [J]. Omega,1988. 17(2): 197-200.
32. Proctor, T., Generating insights with a computer [J]. Creativity and Innovation Yearbook, 1988: 87-100.
33. Young, L.F., Right brained decision support systems [J]. Database, 1983. 14(4): 28-36.
34. Elam, J.J., Mead, M., Can software influence creativity [J]. Information Systems Research, 1990. 1(1): 1-22.
35. Durand, D.E., VanHuss., S. E., Creativity software and DSS: Cautionary findings [J]. Information and Management, 1992. 23: 1-6.
36. MacCrimmon, K.R., Wagner, C., Stimulating ideas through creativity software [J]. Management Science, 1994. 40(11): 1514-1532.
37. Massetti, B., An empirical examination of the value of creativity support systems on idea generation [J]. MIS Quarterly, 1996. 20(1): 83-97.
38. Wagner, C., Creative behavior through basic inferences: Evidence from person-computer interactions [J]. Journal of Creative Behavior, 1996. 30(2): 105-125.
39. Marakas, G., Elam, J. J., Creativity enhancement in Problem Solving: Through software or process [J]? Management Science, 1997. 43(8): 1136-1146.
40. Wierenga, B., Bruggen, G. H., The Dependent Variable in Research Into the Effects of Creativity Support Systems: Quality and Quantity of Ideas [J]. MIS Quarterly, 1998. 22(1): 81-87.
41. Malaga, R.A., The effect of stimulus modes and associative distance in individual creativity support systems [J]. Decision Support Systems, 2000. 29(2): 125-141.
42. Hewett, T.T., Informing the design of computer-based environments to support creativity [J]. International Journal of Human-Computer Studies, 2005. 63(4): 383-409.
43. Forgionne, G., Newman, J., An experiment on the effectiveness of creativity enhancing decision-making support systems [J]. Decision Support Systems, 2007. 42(4): 2126-2136.
44. Applegate, L.M., Technology support for cooperative work: a framework for studying introduction and assimilation in organizations [J]. Journal of Organizational Computing, 1991. 1: 11-39.
45. Couger, J.D., Flynn, P., Hellyer, D., Enhancing the creativity of reengineering [J]. Information Systems Management, 1994. 11(2): 24-29.
46. Nunamaker Jr., J.F., Dennis, A. R., Valacich, J. S., Vogel, D. R., George, J. F., Electronic meeting systems to support group work [J]. Communications of the ACM, 1991. 34(7): 40-61.
47. Diehl, M., Stroebe, W., Productivity loss in brainstorming groups: toward a solution of a riddle [J].Journal of Personality and Social Psychology, 1987. 53(3): 497-509.
48. Walker, H.A., Ilardi, B. C., McMahon, A. M., Fennell, M. L., Gender, interaction, and leadership [J]. Social Psychology Quarterly, 1996. 59(3): 255-272.
49. Duncan, N., Paradice, D., Creativity in GDSS: An integration of creativity, group dynamics, and problem solving theory [C], Proceedings of the Twenty-Fifth Hawaii International Conference on Systems Sciences. 1992: Hawaii.
50. Fellers, J.W., Bostrom, R. P., Application of group support systems to promote creativity in information systems organizations [C]. Proceedings of the Twenty-Sixth Hawaii International Conference on Systems Sciences, 1993: 332-341.
51. Lobert, B.M., The impact of group support systems on idea incubation: Exploring creativity in information system development projects. The City University of New York, 1993.
52. Nagasundaram, M., Bostrom, R. P., The Structuring of Creative Processes: Implications for GSS Research [C], Proceedings of the Twenty-Seventh Hawaii International Conference on Systems Sciences. 1994: Hawaii.
53. Nagasundaram, M., Bostrom, R. P., The Structuring of Creative Processes using GSS: A Framework for Research [J]. Journal of Management Information Systems, 1995. 11(3): 89-116.
54. Nagasundaram, M., Bostrom, R. P., Structuring Creativity with GSS: An Experiment [C]. Proceedings of the First Americas Conference on Information Systems, 1995: 258-260.
55. Ocker, R., Hiltz, S. R., Turoff, M., Fjermestad, J., The effects of distributed group support and process structuring on software requirements development teams: Results on creativity and quality [J]. Journal of Management Information Systems, 1996. 12(3): 127-153.
56. McFadzea, E., Improving group productivity with group support systems and creative problem solving techniques [J]. Creativity and innovation management, 1997. 6(4): 218-225.
57. Klein, E.E., Dologite, D. G., The role of computer support tools and gender composition in innovative information system idea generation by small groups [J]. Computers in Human Behavior, 2000. 16(2): 111-139.
58. Hender, J., Dean, D., Rodgers, T., Nunamaker Jr, J., Improving Group Creativity: Brainstorming Versus Non-brainstorming Techniques in a GSS Environment [C]. Proceedings of the 34th Hawaii International Conference on System Sciences, 2001.
59. Shaw, D., Creativity and learning through electronic group causal mapping [J]. International Journal of Innovation and Learning. 2004. 1(4): 364-377.
60.吴江,赵宗涛,创新支持系统模型及开发技术[J].西北大学学报, 2005. 35(5): 531-535.
61.李欣苗,面向任务的团队创新支持理论及其系统研究,上海交通大学博士学位论文,2005.
62.钱学森,于景元,戴汝为,一个科学的新领域——开放的复杂巨系统及其方法论[J].自然杂志, 1990. 13(1): 3-10.
63.王寿云,于景元,戴汝为,开放的复杂巨系统[M].杭州:浙江科学技术出版社, 1996.
64.于景元,涂元季,从定性到定量的综合集成方法—案例研究[J].系统工程理论与实践, 2002. 5: 1-2.
65.于景元,钱学森的现代科学技术体系与综合集成方法论.中国工程科学, 2001. 3(11): 10-18.
66.于景元,周晓纪,从定性到定量综合集成方法的实现和应用[J].系统工程理论与实践, 2002. 10: 26-32.
67.戴汝为,操龙兵,综合集成研讨厅的研制[J].管理科学学报, 2002. 5(3): 10-16.
68.唐锡晋,刘怡君,群思考的计算机支持工具研究.西部开发与系统工程[M].北京:海洋出版社, 2002: 351-355.
69.张兴学,张鹏翥,群体决策研讨意见分布可视化研究[J].管理科学学报, 2005. 8(4): 15-27.
70. Bostrom, R. P., Research in Creativity and GSS. Proceedings of the 31st Annual Hawaii International Conference on System Sciences, IEEE, Kohala Coast, HI, 1998: 391-404.
1. Letsche, T. A., Berry, M. W., Large-Scale Information Retrieval with Latent Semantic Indexing [J]. Information Sciences, 1997. 100(1): 105-137.
2. Andrews, J., Creative ideas take time: business practices that help product managers cope with time pressure [J]. The journal of product innovation management, 1996. 13(6): 553-554.
3. Chen, H., Schuffels, C., Orwig, R., Internet categorization and search: a self-organizing approach [J]. Journal of Visual Communication and Image Representation, 1996. 7(1): 88-102.
4. George, J. F., Easton, G. K., Nunamaker, J. F., Northcraft, G. B. A study of collaborative group work with and without computer-based support [J]. Information Systems Research, 1990. 1(4): 394-415.
5. Chen, H., Hsu, P., Orwig, R., Hoopes, L., Nunamaker, J. F. Automatic Concept Classification of Text from Electronic Meetings [J]. Communications of the ACM, 1994. 37(10): 56-73.
6. Roussinov, D., Zhao, L., Automatic discovery of similarity relationships through Web mining [J]. Decision Support Systems, 2002. 35(1): p. 149-166.
7. Duen-Ren Liu, Chik-Kun Ke, Knowledge support for problem-solving in a production process: A hybrid of knowledge discovery and case-based reasoning [J]. Expert Systems with Applications, 2007. 33: 147-161.
8.邱明,语义相似性度量及其在设计管理系统中的应用.浙江大学博士学位论文, 2006.
9.姜韶华,科研项目管理中的文本挖掘方法研究及应用.大连理工大学博士学位论文, 2006.
10. Ellis, C. A., Gibbs, J.S., Rein, G. L., Groupware: some issues and experiences [J]. Communications of the ACM, 1991. 34(1): 38-58.
11.李欣苗,面向任务的团队创新支持理论及其系统研究,上海交通大学博士学位论文, 2005.
12.焦玉英,信息检索进展[M]. 2003,北京:科学出版社. 17-57.
13. Salton, G., Wong, A., Yang, C. S., a vector space model for automatic indexing [J]. Communications of the ACM, 1975. 18(11): 613-620.
14. Dumais S., Furnas, G., Landauer T., Scott D., et al, Using Latent Semantic Analysis to Improve Access to Textual Information [C]. Proceedings of Computer Human Interaction, 1988: 281-285.
15.林鸿飞,姚天顺,基于潜在语义索引的文本浏览机制[J].中文信息学报, 2000. 14(5): 49-56.
16. Kendall, M.G., Rank correlation methods [M]. London: Griffin, 1948.
1. Hewett, T.T., Informing the design of computer-based environments to support creativity [J]. International Journal of Human-Computer Studies, 2005. 63: 27.
2. Briggs, R.O., Nunamaker, J.F. Jr, Sprague, R.H. Jr, 1001 unanswered research questions in GSS [J]. Journal of Management Information Systems, 1998. 14(3): 3.
3. MumFord, M. D., Something Old, something new: Revisiting Guilford’s conception of creative problem solving. and Creativity Research Journal, 2000: 267–276.
4. Reiter-Palmon, R., Illies, J.J., Leadership and creativity Understanding leadership from a creative problem-solving perspective [J]. The Leadership Quarterly, 2004, 15:35-53.
5. Chen, H.,Hsu, P.,Orwig, R.,Hoopes, L.,Nunamaker, J. F., Automatic concept classification of text from electronic meetings [J]. Communications of the ACM, 1994. 37(10): 56-73.
6. Montoya-Weiss, M.M., O'Driscoll, T.M., From Experience: Applying Performance Support Technology in the Fuzzy Front End [J]. The journal of product innovation management, 2000. 17(2): 143-161.
7. Olshavsky R.W., Spreng R.A., An exploratory study of the innovation evaluation process [J]. The journal of product innovation management, 1996. 13(6): 512-529.
8.刘文海,产品概念设计方案的评价决策技术及应用研究,大连理工大学博士学位论文, 2005.
9.薛立华,黄洪钟,张旭,古莹奎,赵宏,概念设计方案评价和决策线性物理规划模型研究[J].大连理工大学学报, 2005. 45(4): 562-565.
10.杨明顺,林志航,李言,李鹏阳,袁启龙,产品总体方案评价与优选的证据推理决策[J].工程图学学报, 2006(2): 32-38.
11. Shih, H. S., Wang, C. H., Lee, E, S., A Multiattribute GDSS for Aiding Problem-Solving [J]. Mathematical and Computer Modelling 2004. 39(11): 1397-1412.
12. Valacich, J. S., Jessup, L.M., Dennis, A. R., Nunamaker, J. F., Electronic meeting support: The group systems concept [J]. International Journal of Man-Machine Studies, 1992. 34: 261-282.
13.王刊良,席酉民,汪应洛,电子头脑风暴(EBS)研究[J].系统工程, 1994. 12(5): 1-8.
14. Diehl, M., Stroebe, W., Productivity loss in brainstorming groups: Toward the solution of a riddle [J]. Jounral of Personality and Social Psychology, 1987. 53(3): 497-509.
15.张学工,关于统计学习理论与支持向量机[J].自动化学报, 2000. 26(1): 32-42.
16.王国胜,钟义信,支持向量机的理论基础—统计学习理论[J].计算机工程与应用, 2001. 19: 19-20.
17.谭东宁,谭东汉,小样本机器学习理论:统计学习理论[J].南京理工大学学报, 2001. 25(1): 108-112.
18.任建峰,郭雷,李刚,多类支持向量机的自然图像分类[J].西北工业大学学报, 2005. 23(3): 295-298.
19.马勇,丁晓青,基于层次型支持向量机的人脸检测[J].清华大学学报(自然科学版), 2003. 43(1): 35-38.
20. Cooper, R. G., Kleinschmidt, E. J., An investigation into the new product development process: Steps, deficiencies, impact [J]. Journal of Product Innovation Management, 1986, 3: 374-391.
21.朱龙英,朱如鹏,刘正埙,基于信息公理的产品设计方案评价方法[J].南京航空航天大学学报, 2005. 37(3): 386-390.
22.杨明顺,林志航,李言,李鹏阳,袁启龙,产品总体方案评价与优选的证据推理决策[J].工程图学学报, 2006(2): 32-38.
23.边肇祺,张学工,模式识别[M].北京:清华大学出版社, 2000.
24. Vapnik, V., The nature of Statistical Learning Theory [M]. New York: Springer-Verlag, 1995.
25. Knerr, S., Personnaz, L., Dreyfus, G., Single-layer learning revisited : A stepwise procedure for building and training a neural network [A], Neurcomputing : Algorithms , Architectures and Applications. 1999, New York : Springer-Verlag.
26. Saaty, T.L., The Analytic Hierarchy Process [M]. RWS Pub, Pittsburgh, PA, 1990.
1. Bostrom, R. P., Research in Creativity and GSS. Proceedings of the 31st Annual Hawaii International Conference on System Sciences, IEEE, Kohala Coast, HI, 1998: 391-404.
2. Wallas G., The Art of Thought [M], New York: Harcort Brace. 1926: 80-82.
3. MacCrimmon, K. R., Wagner, C., Stimulating idea through creativity software [J]. Management Science, 1994. 40(11): 1514-1532.
4. Massetti, B., An empirical examination of the value of creativity support systems on idea generation [J]. MIS Quarterly, 1996. 20(1): 83-97.
5. Malaga, R.A., The effect of stimulus modes and associative distance in individual creativity support systems [J]. Decision Support Systems, 2000. 29(2): 125-141.
6. Hewett, T.T., Informingthe design of computer-based environments to support creativity [J]. International Journal of Human-Computer Studies, 2005. 63(4): 383-409.
7. Elam, J.J., Mead, M., Can software influence creativity [J]. Information Systems Research, 1990. 1(1): 1-22.
8. Mumford, M.D., Scott, G. M., Gaddis, B., Strange, J. M., Leading creative people: Orchestrating expertise and relationships [J]. Leadership Quarterly, 2002. (13): 705-750.
9. West, M.A., Sparkling fountains or stagnant ponds: An integrative model of creativity and innovation implementation in work groups [J]. Applied psychology: an international review, 2002. 51(3): 355-387.
10.周宁,杨峰,信息可视化系统的RDV模型研究[J].情报学报, 2003. 22(5): 619-624.
11. Zhou Ning , Liu Wei, On the methods of information resources visualization [C]. The Proceedings of Digital Library-IT Opportunities and Challenges in the New Millennium. 2002.
12. Xiang, Y., Chau, M., Atabakhsh, H., Chen, H., Visualizing Criminal Relationships: Comparison of a Hyperbolic Tree and a Hierarchical List 2006 [J]. Decision Support Systems. 41(1): 69-83.
13. Forgionne, G., Newman, J., An experiment on the effectiveness of creativity enhancing decision-making support systems [J]. Decision Support Systems, 2007. 42(4): 2126-2136.
14. van der Lugt R. Developing a graphic tool for creative problem solving in design groups. Design Studies, 2000. 21(5): 505-522.
15.唐锡晋,刘怡君,群思考的计算机支持工具研究.西部开发与系统工程[M].北京:海洋出版社, 2002: 351-355.
16.李欣苗,面向任务的团队创新支持理论及其系统研究,上海交通大学, 2005.
1. Schumann , Paul A., Ransley , Jr., Derek L., Prestwood , Donna C. L., Measuring R&D Performance [J]. Research Technology Management, 1995. 38(3): 47-52.
2. Tipping, J.W., Zeffren, E., Fusfeld, A.R., Assessing the value of your technology [J]. Research Technology Management, 1995. 38(5): 22-39.
3. Lee, M., Son, B., Lee, H., Measuring R&D effectiveness in Korean companies [J]. Research Technology Management, 1996. 39(6): 28-31.
4. Carroll, J. J., Newbould, G. D., NPV vs. IRR with capital budgeting, which do you choose [J]? Healthcare Financial Management, 1986. 40(11): 62-67.
5. Allen, D., DCF: elegant theory of sound practice [J]? Management Accounting (London), 1992. 8: 62.
6. Cheng, C. S. A., Kite, D., Radtke, R., The applicablity and usage of NPV and IRR capital budgeting techniques [J]. Managerial Finance, 1994. 20(7): 94-104.
7. Akalu, M.M., Re-examining project appraisal and control: developing a focus on wealth creation [J]. International Journal of Project Management, 2001. 19(7): 357-383.
8. Ekern, S., An option pricing approach to evaluating petroleum project [J]. Energy Economics, 1988. 23(3): 91-99.
9. Roll , R., What every CFO should know about scientific progress in financial economics: what is known and what remains to be resolved [J]. Financial Management, 1994. 23(2): 69-75.
10. Copeland, T., Weiner, J., Proactive management of uncertainty [J]. The McKinsey Quarterly, 1990. 10(4): 133-152.
1. Dennis, A.R., George, J. F., Jessup, L. M., Nunamaker, J. F., Vogel, D. R., Information technology to support electronic meetings [J]. MIS Quarterly, 1988. 12(4): 591-624.
2. Jelassi, M.T., Beauclair, R. A., An integrated framework for group decision support system design [J]. Information and Management, 1987. 13(3): 143-155.
3. Nunamaker Jr., J.F., Dennis, A. R., Valacich, J. S., Vogel, D. R., George, J. F., Electronic meeting systems to support group work [J]. Communications of the ACM, 1991. 34(7): 40-61.
4. Couger, J.D., A framework for research on creativity/innovation in IS organizations [C]. In Proceedings of the 29th Annual Hawaii International Conference on System Science, 1996. 1: 30-38.
5. Massetti, B., An empirical examination of the value of Creativity Support Systems on idea generation [J]. MIS Quarterly, 1996. 20(1): 83-97.
6. Marakas, G.., Elam, J. J., Creativity enhancement in problem solving: through software or process [J]? Management Science, 1997. 43(8): 1136-1146.
7. Robert P. Bostrom, M.N., Research in creativity and GSS [C]. IEEE Proc. 31st Annual Hawaii International Conference on System Sciences, 1998: 391-404.
8. Fischer, G., McCall, R., Morch, A. JANUS: integrating hypertext with a knowledge-based design environment [C]. Proceedings of the Hypertext'89 Conference. New York: ACM. 1989.
9. Streitz, N., Hannemann, J., Thuring, M. From ideas and arguments to hyper-documents: travelling through activity spaces [C]. Proceedings of the Hypertext'89 Conference. New York: ACM. 1989.
10. Lee, J. SIBYL: a tool for managing group decision rationale [C]. Proceedings of the CSCW'90 Conference. New York: ACM. 1990.
11. Shum, S., MacLean, A., Forder, J., Hammond, N., Summarising the evolution of design concepts within a design rationale framework [C]. Adjunct Proceedings of InterCHI'93: ACM/IFIP Conference on Human Factors in Computing Systems. The Netherlands: Amsterdam. 1993.
12. Metcalfe, M., Argumentative systems for IS design [J]. Information Technology and People, 2002. 15(1): 60-73.
13. Bose, R., Group support systems: technologies and products selection [J]. Industrial Management and Data Systems, 2003. 103(9): 649-656.
14.李欣苗,面向任务的团队创新支持理论及其系统研究,上海交通大学博士学位论文, 2005.
15. Townsend A.M., DeMarie S.M., Hendrickson A.R., Virtual teams: technology and the workplace of the future [J]. Academy of Management Executive, 1998. 12(3): 17-29.
16. Erran, C., Global software teams [M]. Upper Saddle River: NJ: Prentice Hall. 1999.