An integrated fuzzy Data Envelopment Analysis and Data Mining for Performance assessment of Insurance branches
Journal Title: International Research Journal of Applied and Basic Sciences - Year 2014, Vol 8, Issue 7
Abstract
This paper presents a Fuzzy Data Envelopment Analysis (FDEA) model combined with Bootstrapping to assess performance of one of the Data mining Algorithms. We used a two-step process for performance productivity analysis of Insurance Branches in Iran. First, using a Fuzzy Data Envelopment Analysis (FDEA) model, the study analyzes the productivity of eighteen Decision making units (DMUs). Using a Malmquist Index, FDEA determines the productivity scores but cannot give details of factors depend on Regress and Progress Productivity. FDEA model uses a new Latent Variable radial input-oriented technology and simultaneously reduces inputs and undesirable outputs in a single multiple objective linear program.On the other hand, the classification and regression tree (C&R) efficiency model was then utilized to extract rules for exploring and discovering meaningful and hidden information from the vast data bases. The conclusion of the combined model is a set of rules that can be used by policy makers to explore reasons behind the progress and regress productivities of DMUs.
Authors and Affiliations
Somayeh Shafaghizadeh *| Department of Industrial Engineering, Science & Research Branch, Islamic Azad University, Qazvin, Iran, email: s_shafaghizadeh@yahoo.com, Mahdi Yousefi Nejad Attari| Faculty of Industrial and Mechanical Engineering, Bonab branch, Islamic Azad University, Bonab, Iran
Keywords
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