The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON BUSINESS AND ECONOMICS
Transactions ID Number: 52-146
Full Name: Ching-Yi Chiu
Position: Ph.D. Candidate
Age: ON
Sex: Female
Address: No.137, Lane 75, Sec. 3, Kangning Rd., Neihu District, Taipei City 114, Taiwan R.O.C.Department of Business Administration, Knag-Ning Junior College of Medical Care and Management
Country: TAIWAN
Tel:
Tel prefix:
Fax:
E-mail address: arista@knjc.edu.tw
Other E-mails: aristachiu@gmail.com
Title of the Paper: An Integrated DEA-based Model to Measuring Financial Performance of Construction Companies
Authors as they appear in the Paper: Ching-yi Chiu, Ching-hwang Wang, Mei-wei Wang
Email addresses of all the authors: arista@knjc.edu.tw,C.H.Wang@mail.ntust.edu.tw,maviswmh@webmail.ntcb.edu.tw
Number of paper pages: 18
Abstract: Abstract: - This paper proposes an evaluation model which effectively assesses the financial performance of construction companies. This model successfully combines the methods of Strength Weakness Opportunity Threats (SWOT), Canonical Correlation Analysis (CCA) and Data Envelopment Analysis (DEA). The model first analyzes the operation characteristics of construction companies by using SWOT and, therefore, selects the representative indicators for evaluating financial performance. Afterward, it adopts CCA to solve the problems generated by indicators correlation and assure the ability to distinguish performance evaluation. The model finally can utilize DEA to acquire reasonable efficiency values and priorities of financial performance. Through the case studies presented in the paper, it is evident that the proposed model is an effective tool that can rationally execute performance evaluation of construction companies and also suggest valuable improvements for com!
pany operations.
Keywords: Financial performance, Indicators correlation, Evaluation model, Construction companies, Data envelopment analysis
EXTENSION of the file: .doc
Special (Invited) Session:
Organizer of the Session:
How Did you learn about congress:
IP ADDRESS: 119.77.174.156