INDEPENDENT POWER PRODUCERS’ EFFICIENCY PERFORMANCE USING FUZZY DATA ENVELOPMENT ANALYSIS (FDEA) MODEL
DOI:
https://doi.org/10.46827/ejsss.v12i2.2168Ključne riječi:
Fuzzy DEA, correlation, slacks, technical efficiency performance, Independent Power Producer IndustrySažetak
The purpose of this study is to evaluate and investigate the efficiency performance of nine (9) selected Independent Power Producer (IPP) firms using the Fuzzy Data Envelopment Analysis (FDEA) Model. The data were drawn from a database of 7 panel firms in the Luzon Area, Philippines, over the period 2000-2006. The efficiency performance evaluations were done first from 63 pooled panel data prior to cross-sectional analysis in three stages (CVSTE 1, UCVRSTE 2 and UCVRSTE 3). The input controllable variables were (X1) Total Number of Employees, (X2) Depreciation, input uncontrollable variable (X3) ISO Certification. The output controllable variables were (Y1) Total Operating Revenue, (Y2) Total MWH- Sales, output uncontrollable variable (Y3) Age of Technology. Empirically, this study suggested that: (1) ISO Certification and Age of Technology entry into the IPP firm study implies enhanced fuzzification, thus connoting the possible loss of precision; (2) Input and output orientation via UCVRSTE (Stages 2 & 3 ) manifests deficiencies through inappropriate use of scale transformation; (3) slacks occurrence exhibited in three stages implies mismanagement of variable alternatives; (4) an average of 1.33 percent yearly for ISO Certification compliance is required for the IPP’s relative technical efficiency and continuous deterrence yields non-compliance of quality standards; (5) average reduction of 1.22 percent yearly for refurbishment of old technologies is tantamount to an IPP firms’ efficient score, otherwise, non-adherence means disregard of technology rehabilitation and upgrading. This study provides the theoretical, comparative empirical models, and robust evidence of how the DEA-CVRSTE Model (Stage 1) justified the enhanced discriminating power of FDEA-UCVRSTE (Stage 2) Model. The methodology tackles handling information that contains controllable (precise, exact) and uncontrollable (imprecise, uncertain, missing, unclear, vague, fuzzy) values. Hence, this studyReference
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