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Title: Enhanced DEA model with undesirable output and interval data for rice growing farmers performance assessment

Agricultural production process typically produces two types of outputs which are economic desirable as well as environmentally undesirable outputs (such as greenhouse gas emission, nitrate leaching, effects to human and organisms and water pollution). In efficiency analysis, this undesirable outputs cannot be ignored and need to be included in order to obtain the actual estimation of firms efficiency. Additionally, climatic factors as well as data uncertainty can significantly affect the efficiency analysis. There are a number of approaches that has been proposed in DEA literature to account for undesirable outputs. Many researchers has pointed that directional distance function (DDF) approach is the best as it allows for simultaneous increase in desirable outputs and reduction of undesirable outputs. Additionally, it has been found that interval data approach is the most suitable to account for data uncertainty as it is much simpler to model and need less information regarding its distribution and membership function. In this paper, an enhanced DEA model based on DDF approach that considers undesirable outputs as well as climatic factors and interval data is proposed. This model will be used to determine the efficiency of rice farmers who produces undesirable outputs and operates under uncertainty. It is hopedmore » that the proposed model will provide a better estimate of rice farmers’ efficiency.« less
Authors:
; ;  [1]
  1. School of Quantitative Sciences, UUM College of Arts and Sciences, Universiti Utara Malaysia, 06010 Sintok, Kedah (Malaysia)
Publication Date:
OSTI Identifier:
22496244
Resource Type:
Journal Article
Resource Relation:
Journal Name: AIP Conference Proceedings; Journal Volume: 1691; Journal Issue: 1; Conference: IACE 2015: 2. innovation and analytics conference and exhibition, Kedah (Malaysia), 29 Sep - 1 Oct 2015; Other Information: (c) 2015 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; CLIMATE MODELS; DATA COVARIANCES; EFFICIENCY; FARMS; GREENHOUSE GASES; NITRATES; RICE; WATER POLLUTION