基于文本分析的模糊认知地图支持战略规划

P. Hájek, Ondřej Procházka, P. Pachura
{"title":"基于文本分析的模糊认知地图支持战略规划","authors":"P. Hájek, Ondřej Procházka, P. Pachura","doi":"10.1109/ICRIIS.2017.8002479","DOIUrl":null,"url":null,"abstract":"Strategy maps are attracting considerable interest in strategic planning due to their capacity to represent causal-effect relationships among the key concepts. Several studies have used expert estimates to quantify the relationships. However, these evolve dynamically and are context-specific. Therefore, there is a need to develop automatic knowledge acquisition systems. Here, the assumption was used that knowledge can be extracted from strategic documents in order to conduct a detailed analysis of causal strategic concepts. First, latent semantic analysis is employed to obtain an interpretable semantic model. Second, collocated causal concepts are used to model relationships among strategic concepts. This approach to generate fuzzy cognitive maps (FCMs) is semi-automatic, requiring theoretical background literature/domain experts to determine the direction of the causalities. The FCMs can subsequently be used to simulate the effects of strategic management and, thus, provide an effective decision support tool. Several innovation strategies of regions are used as a case study and it is demonstrated that the generated FCMs are consistent with expert opinions and fuzzy ANP method.","PeriodicalId":384130,"journal":{"name":"2017 International Conference on Research and Innovation in Information Systems (ICRIIS)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Fuzzy cognitive maps based on text analysis for supporting strategic planning\",\"authors\":\"P. Hájek, Ondřej Procházka, P. Pachura\",\"doi\":\"10.1109/ICRIIS.2017.8002479\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Strategy maps are attracting considerable interest in strategic planning due to their capacity to represent causal-effect relationships among the key concepts. Several studies have used expert estimates to quantify the relationships. However, these evolve dynamically and are context-specific. Therefore, there is a need to develop automatic knowledge acquisition systems. Here, the assumption was used that knowledge can be extracted from strategic documents in order to conduct a detailed analysis of causal strategic concepts. First, latent semantic analysis is employed to obtain an interpretable semantic model. Second, collocated causal concepts are used to model relationships among strategic concepts. This approach to generate fuzzy cognitive maps (FCMs) is semi-automatic, requiring theoretical background literature/domain experts to determine the direction of the causalities. The FCMs can subsequently be used to simulate the effects of strategic management and, thus, provide an effective decision support tool. Several innovation strategies of regions are used as a case study and it is demonstrated that the generated FCMs are consistent with expert opinions and fuzzy ANP method.\",\"PeriodicalId\":384130,\"journal\":{\"name\":\"2017 International Conference on Research and Innovation in Information Systems (ICRIIS)\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Research and Innovation in Information Systems (ICRIIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICRIIS.2017.8002479\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Research and Innovation in Information Systems (ICRIIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRIIS.2017.8002479","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

摘要

战略地图由于能够表示关键概念之间的因果关系,在战略规划方面引起了相当大的兴趣。有几项研究使用了专家的估计来量化这种关系。然而,这些都是动态发展的,并且是特定于上下文的。因此,有必要开发自动知识获取系统。在这里,假设可以从战略文件中提取知识,以便对因果战略概念进行详细分析。首先,利用潜在语义分析获得可解释的语义模型。其次,利用并列因果概念对战略概念之间的关系进行建模。这种生成模糊认知图(fcm)的方法是半自动的,需要理论背景文献/领域专家来确定因果关系的方向。fcm随后可用于模拟战略管理的效果,从而提供有效的决策支持工具。以不同地区的创新策略为例,结果表明所生成的fcm与专家意见和模糊ANP方法是一致的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Fuzzy cognitive maps based on text analysis for supporting strategic planning
Strategy maps are attracting considerable interest in strategic planning due to their capacity to represent causal-effect relationships among the key concepts. Several studies have used expert estimates to quantify the relationships. However, these evolve dynamically and are context-specific. Therefore, there is a need to develop automatic knowledge acquisition systems. Here, the assumption was used that knowledge can be extracted from strategic documents in order to conduct a detailed analysis of causal strategic concepts. First, latent semantic analysis is employed to obtain an interpretable semantic model. Second, collocated causal concepts are used to model relationships among strategic concepts. This approach to generate fuzzy cognitive maps (FCMs) is semi-automatic, requiring theoretical background literature/domain experts to determine the direction of the causalities. The FCMs can subsequently be used to simulate the effects of strategic management and, thus, provide an effective decision support tool. Several innovation strategies of regions are used as a case study and it is demonstrated that the generated FCMs are consistent with expert opinions and fuzzy ANP method.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A firm and individual characteristic-based prediction model for E2.0 continuance adoption Understanding knowledge management behavior from a social exchange perspective Healthcare employees' perception on information privacy concerns Detection and prevention of possible unauthorized login attempts through stolen credentials from a phishing attack in an online banking system Resolving data duplication, inaccuracy and inconsistency issues using Master Data Management
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1