Published in: 14th International Industrial Engineering Conference
COI code: IIEC14_068
Paper Language: English
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Authors The Classification of Investment Companies Using the Interval Network Data Envelopment Analysis ModelPejman Peykani - Faculty of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran
Emran Mohammadi - Faculty of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran
Fatemeh Sadat Seyed Esmaeili - Faculty of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran
Abstract:The main purpose of this paper is to propose an approach for performance measurement, classification and ranking of investment companies (ICs) by considering internal structure and uncertainty. So, in order to reach this goal, the interval network data envelopment analysis (INDEA) model are extended. This model is capable to modeling the two-stage efficiency with intermediate measures in a single implementation. Additionally, the proposed INDEA models of the paper is implemented for a real case studyof ICs in Tehran Stock Exchange (TSE) and Illustrative results show that proposed INDEA models is effective in order to classification and ranking of investment companies.
Keywords:Data Envelopment Analysis (DEA), Network Data Envelopment Analysis (NetDEA), Interval Data, Uncertainty, Investment Company,Tehran Stock Exchange (TSE)
COI code: IIEC14_068
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Peykani, Pejman; Emran Mohammadi & Fatemeh Sadat Seyed Esmaeili, 2017, The Classification of Investment Companies Using the Interval Network Data Envelopment Analysis Model, 14th International Industrial Engineering Conference, تهران, انجمن مهندسي صنايع ايران - دانشگاه علم و صنعت ايران, https://www.civilica.com/Paper-IIEC14-IIEC14_068.htmlInside the text, wherever referred to or an achievement of this article is mentioned, after mentioning the article, inside the parental, the following specifications are written.
First Time: (Peykani, Pejman; Emran Mohammadi & Fatemeh Sadat Seyed Esmaeili, 2017)
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Type: state university
Paper No.: 20366
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