Integrated Artificial Intelligence and Visualization Technique for Enhanced Management Decision in Today's Turbulent Business Environments

文化大學機構典藏 CCUR > 商學院 > 會計學系暨研究所 > 期刊論文 > Item 987654321/49493

jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://irlib.pccu.edu.tw/handle/987654321/49493

题名:	Integrated Artificial Intelligence and Visualization Technique for Enhanced Management Decision in Today's Turbulent Business Environments
作者:	Lin, SJ (Lin, Sin-Jin)
贡献者:	會計系
关键词:	Artificial intelligence decision making risk management visualization
日期:	2021-01-28
上传时间:	2021-04-19 10:41:39 (UTC+8)
摘要:	The dramatic deterioration in a corporate's profitability not only threatens its own interests, employees, and investors, but can also impact external entities and people through financial losses and high risk exposure. Thus, in today's turbulent market environments an essential issue arises as to how to set up an effective pre-warning model that provides managers with specific avenues to avoid financial troubles from getting worse and offers investors useful directions to adjust their investment portfolios. However, extant forecasting models are not yet capable of fully explaining the relationships between past and future performances, which may be due to the omission of some critical information. To capture the multidimensional nature of performance assessment, this study extends a singular data envelopment analysis (DEA) specification to multiple DEA specifications and further incorporates them with a risk-adjusted metric so as to present an overarching reflection of corporates' operations. To make the outcome much more accessible to non-specialists, we utilize a visualization technique to represent the data's main structure and then feed the analyzed data into a twin parametric-margin support vector machine (TPSVM) to construct the forecasting model. Due to the obscure nature of the SVM-based model, this study executes the multiple instances learning (MIL) algorithm to extract the inherent decision logics and to represent them in human readable way. After examining it with real cases, the proposed model is a promising alternative for performance assessment and forecasting.
關聯:	CYBERNETICS AND SYSTEMS 卷冊: 52 期: 4 頁數: 274-292
显示于类别:	[會計學系暨研究所 ] 期刊論文

文件中的档案:

档案	描述	大小	格式	浏览次数
index.html		0Kb	HTML	246	检视/开启

检视Licence

在CCUR中所有的数据项都受到原著作权保护.

数据加载中.....