Big Data From Social Media and Scientific Literature Databases Reveals Relationships Among Risk Management, Project Management and Project Success

Dr. Maria Papadaki, Dr Nikolaos Bakas, Professor Edward Ochieng, Dr. Ioannis Karamitsos, Dr. Richard Kirkham
{"title":"Big Data From Social Media and Scientific Literature Databases Reveals Relationships Among Risk Management, Project Management and Project Success","authors":"Dr. Maria Papadaki, Dr Nikolaos Bakas, Professor Edward Ochieng, Dr. Ioannis Karamitsos, Dr. Richard Kirkham","doi":"10.2139/ssrn.3459936","DOIUrl":null,"url":null,"abstract":"The literature review highlights that previous studies have been identifying risk management as an essential tool for project management and could increase the chance of successfully meeting project objectives. In addition, as found from the reviewed literature, risk management has been seen as a tool of allowing the project team to communicate risk information, so as to enhance the decision-making process towards balancing threats and opportunities. Thus, this research aims to examine participants’ views on the alignment of risk management, project management and organizational project success. Machine learning algorithms are employed to explore collective data from posts on twitter in order to obtain valuable knowledge about discussions regarding risk management, and project management. Additionally, the corresponding scientific literature obtained from Scopus database was analyzed utilizing bibliometric tools, in order to investigate diverse perceptions in academia and industry. Findings of this study will have implications for practitioners’ perception of project risk management.","PeriodicalId":406435,"journal":{"name":"CompSciRN: Other Machine Learning (Topic)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"CompSciRN: Other Machine Learning (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3459936","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14

Abstract

The literature review highlights that previous studies have been identifying risk management as an essential tool for project management and could increase the chance of successfully meeting project objectives. In addition, as found from the reviewed literature, risk management has been seen as a tool of allowing the project team to communicate risk information, so as to enhance the decision-making process towards balancing threats and opportunities. Thus, this research aims to examine participants’ views on the alignment of risk management, project management and organizational project success. Machine learning algorithms are employed to explore collective data from posts on twitter in order to obtain valuable knowledge about discussions regarding risk management, and project management. Additionally, the corresponding scientific literature obtained from Scopus database was analyzed utilizing bibliometric tools, in order to investigate diverse perceptions in academia and industry. Findings of this study will have implications for practitioners’ perception of project risk management.
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
来自社交媒体和科学文献数据库的大数据揭示了风险管理、项目管理和项目成功之间的关系
文献综述强调,以前的研究已经确定风险管理是项目管理的基本工具,可以增加成功实现项目目标的机会。此外,正如所回顾的文献所发现的,风险管理已被视为允许项目团队沟通风险信息的工具,从而增强决策过程以平衡威胁和机会。因此,本研究旨在考察参与者对风险管理、项目管理和组织项目成功的一致性的看法。机器学习算法用于探索twitter帖子中的集体数据,以获得有关风险管理和项目管理讨论的宝贵知识。此外,利用文献计量学工具对Scopus数据库中相应的科学文献进行分析,以调查学术界和工业界的不同看法。本研究的发现将对从业者对项目风险管理的认知产生影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Visualizing The Implicit Model Selection Tradeoff Troubleshooting: a Dynamic Solution for Achieving Reliable Fault Detection by Combining Augmented Reality and Machine Learning Policy Optimization Using Semiparametric Models for Dynamic Pricing Policy Gradient Methods Find the Nash Equilibrium in N-player General-sum Linear-quadratic Games Deep Learning under Model Uncertainty
×
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