Application of enhanced cluster validity index function to automatic stock portfolio selection system

Huang, Kuang Yu; Wan, Shiuan

doi:10.1007/s10799-011-0103-8

Cited by 3 publications

(1 citation statement)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It can deal effectively with multi-variable input, less data and data distribution unknown to overcome the disadvantages of traditional statistical methods. Today, GRA is widely and commonly used as a method for selecting representative indicators, such as Ho (2006), Hsu (2012), Huang and Wan (2011), Kung and Wen (2007), Lee et al (2012) and Li (2011). Therefore, this study applies IGRA as an indicator selection method for (1) selecting input and output variables to use in the DEA model, (2) selecting representative indicators of financial ratios for evaluating performance.…”

Section: Igramentioning

confidence: 99%

Using a Decision-Making Process to Evaluate Efficiency and Operating Performance for Listed Semiconductor Companies

Hsu

2014

Technological and Economic Development of Economy

View full text Add to dashboard Cite

Today's high-tech industries face increasing competition and challenges. Thus, for hightech companies, making effective use of resources to enhance business performance and maintain the competitive advantage in the market has become increasingly important. Therefore, this study aimed to design a decision-making model for evaluating the efficiency and operating performance of Taiwan's listed semiconductor companies in 2010 to provide a basis for improving business performance. In view of this, this study combines data envelopment analysis (DEA) and improved grey relational analysis (IGRA) as efficiency tools to measure relative efficiencies; the semiconductor companies are divided into two groups, efficient and inefficient. We then integrate the multiple criteria decision making (MCDM) method (e.g. VlseKriterijumska Optimizacija I Kompromisno Resenje, VIKOR), IGRA and the entropy weight method to evaluate the operating performance of the efficient and inefficient groups, respectively. Establishing a reasonable, objective and valid evaluation model to measure semiconductor companies' operating efficiency can provide company managers, investors and policy makers with a reference for performance evaluation.Business operators and investors are concerned about how companies view their operating strategies and whether or not they make use of their limited resources. They are also concerned with how the external environment influences the achievement of cost minimization, revenue maximization, and sustainable business performance. Today's high-tech industries face increasing competition and challenges. Making effective use of resources to enhance production performance and maintain competitive advantage has become an increasingly important issue. Much of the previous research (Chen et al. 2006;Hung, Lu 2008;Wu et al. 2007) has paid attention to analyze input-output efficiency and the performance evaluation of the high-tech industries based on DEA. However, in addition to achieving fuller and more efficient use of resources, superior financial performance is the key success factor for companies to remain competitive in high-tech industries. Therefore, this article combines efficiency analysis, production performance and financial performance to construct an effective performance evaluation decision-making process. This approach can provide managers and investors with effective decision making process for performance evaluation.The concept of efficiency is widely used in the empirical research of company's production performance. From the perspective of resource allocation, efficiency is defined as a minimum input or maximum output with a given set of input. Efficiency measures provide a basis for evaluating and improving company's productivity. They can also help management to understand whether or not the company is achieving effective and efficient resource allocation and use. From the internal point of view of operational efficiency, company performance can be revealed by the efficiency of resource inputs and outputs. ...

show abstract

Section: Igramentioning

confidence: 99%

Using a Decision-Making Process to Evaluate Efficiency and Operating Performance for Listed Semiconductor Companies

Hsu

2014

Technological and Economic Development of Economy

View full text Add to dashboard Cite

show abstract

Indian Stock Market Analysis Using CHAID Regression Tree

Aggarwal

Sabitha

Choudhury

et al. 2017

Advances in Intelligent Systems and Computing

View full text Add to dashboard Cite

Business intelligence in enterprise computing environment

Zeng

Duan

2012

Inf Technol Manag

View full text Add to dashboard Cite

The evolution of the SAS 9.2 architecture provides a powerful, distributed, and flexible environment for real-time, responsive analytic and reporting capabilities. This paper describes how information technology (IT) and SAS administrators can use vendor and open source enterprise systems management products to ascertain the state or status of the SAS 9.2 Enterprise Business Intelligence environment, as well as generate alerts for user-specified conditions. The management products reviewed include IBM Tivoli Enterprise Console, HP Software OpenView, open source products Xymon and Hyperic, and the SAS 9.2 Audit and Performance Measurement package.

show abstract

Application of enhanced cluster validity index function to automatic stock portfolio selection system

Cited by 3 publications

References 34 publications

Using a Decision-Making Process to Evaluate Efficiency and Operating Performance for Listed Semiconductor Companies

Using a Decision-Making Process to Evaluate Efficiency and Operating Performance for Listed Semiconductor Companies

Indian Stock Market Analysis Using CHAID Regression Tree

Business intelligence in enterprise computing environment

Contact Info

Product

Resources

About