scholarly journals Demand and Supply of Cut Flowers Production in Krishnagiri District of Tamil Nadu - An Approach by Data Envelopment Analysis

2021 ◽  
Author(s):  
R. Thulasiram ◽  
S. Usha Nandhini ◽  
S. Amarnath
Keyword(s):  
Data Envelopment Analysis ◽  
Tamil Nadu ◽  
Sampling Method ◽  
Total Sample ◽  
Data Envelopment ◽  
Cut Flowers ◽  
Demand And Supply ◽  
Horticultural Crops ◽  
Efficiency Measures ◽  
Wide Range

Background: India has been bestowed with wide range of climate and physio-geographical conditions making it suitable for growing various kinds of horticultural crops. Out of which the awareness on usage of cut flowers for various occasions has raised the demand for cut flowers in the market, especially Tamil Nadu. The overall objective of the study is to estimate the demand and supply of cut flowers in Tamil Nadu. Methods: Hosur block in Krishnagiri district of Tamil Nadu was purposively selected as it is the leader in area and production of rose flowers. A two-stage random sampling method was adopted to select the sample farms with a total sample size of 120. Simple percentage analysis and Data Envelopment Analysis were used to discuss the results. Result: The important period of demand for cut flowers in Hosur block are events like Navratri, Christmas, New Year, Valentine Day, Therthiruvizha, Ramjan and Bakrith. There were 164 days in a year which would be auspicious. On an average 450 bunches of rose, 320 bunches of gerberas and 150 bunches of carnations are used in an event in addition to some other flowers. The technical efficiency measures for Roses indicated that most farmers belonged to the least efficient category ( less than 90 per cent) with a proportion of 62.50 per cent to total.

scholarly journals A Revised Inverse Data Envelopment Analysis Model Based on Radial Models

Mathematics ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 803
Author(s):  
Xiaoyin Hu ◽  
Jianshu Li ◽  
Xiaoya Li ◽  
Jinchuan Cui
Keyword(s):  
Data Envelopment Analysis ◽  
Efficiency Index ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Numerical Examples ◽  
Wide Range ◽  
Dea Models ◽  
Overall Efficiency ◽  
Decision Making Units

In recent years, there has been an increasing interest in applying inverse data envelopment analysis (DEA) to a wide range of disciplines, and most applications have adopted radial-based inverse DEA models. However, results given by existing radial based inverse DEA models can be unreliable as they neglect slacks while evaluating decision-making units’ (DMUs) overall efficiency level, whereas classic radial DEA models measure the efficiency level through not only radial efficiency index but also slacks. This paper points out these disadvantages with a counterexample, where current inverse DEA models give results that outputs shall increase when inputs decrease. We show that these unreasonable results are the consequence of existing inverse DEA models’ failure in preserving DMU’s efficiency level. To rectify this problem, we propose a revised model for the situation where the investigated DMU has no slacks. Compared to existing radial inverse DEA models, our revised model can preserve radial efficiency index as well as eliminating all slacks, thus fulfilling the requirement of efficiency level invariant. Numerical examples are provided to illustrate the validity and limitations of the revised model.

Distance optimization approach to ratio-form efficiency measures in data envelopment analysis

2013 ◽  
Vol 42 (2) ◽  
pp. 175-186 ◽  
Author(s):  
Hirofumi Fukuyama ◽  
Hiroya Masaki ◽  
Kazuyuki Sekitani ◽  
Jianming Shi
Keyword(s):  
Data Envelopment Analysis ◽  
Optimization Approach ◽  
Data Envelopment ◽  
Efficiency Measures

scholarly journals MEASURING TECHNICAL EFFICIENCY OF MALAYSIAN REAL ESTATE INVESTMENT TRUSTS: A DATA ENVELOPMENT ANALYSIS APPROACH

2019 ◽  
Vol 17 (9) ◽  
Author(s):  
Nor Nazihah Chuweni
Keyword(s):  
Data Envelopment Analysis ◽  
Real Estate ◽  
Technical Efficiency ◽  
Economies Of Scale ◽  
Efficient Frontier ◽  
Data Envelopment ◽  
Real Estate Investment ◽  
Nonparametric Approach ◽  
Efficiency Measures ◽  
Efficiency Performance

The research examines the technical efficiency (TE) and economies of scale for the Malaysian Real Estate Investment Trust (M-REITs) from 2010 to 2014, using a non-parametric approach of Data Envelopment Analysis (DEA). The nonparametric approach of Variable Return to Scale DEA (VRS-DEA model) was used to estimate the efficiency scores for M-REITs. The negative inefficient value for the technical inefficiencies is identified as a result of both poor input utilisation (managerial inefficiency) and failure of M-REITs to operate at optimum scale (scale inefficiency). The mean technical efficiency (TE) measures ranged from as low as 41.70% in 2011 to as high as 84.30% in 2014. Despite having the Sharia requirement, Islamic REITs in Malaysia provide an effective investment opportunity evidenced by the higher scores for all efficiency measures, as compared to conventional REITs for the period under study. Pure technical inefficiency has a greater deviation in the efficient frontier than scale inefficiency, suggesting that M-REITs inputs are not fully minimised to produce more outputs. With regard to scale inefficiency, M-REITs are operating at economies of scale, indicating the importance of expansion or growth to improve on efficiency performance. This will then allow M-REIT managers to formulate better strategic investment decisions.

scholarly journals Eco-efficiency Assessment in Agriculture: A Literature Review Focused on Methods and Indicators

2020 ◽  
Vol 12 (7) ◽  
pp. 118
Author(s):  
Luis H. Suzigan ◽  
Carlos Rosano Peña ◽  
Patricia Guarnieri
Keyword(s):  
Data Envelopment Analysis ◽  
Literature Review ◽  
Social Impact ◽  
Efficiency Analysis ◽  
Environmental Indicators ◽  
Social Dimension ◽  
Data Envelopment ◽  
Agricultural Systems ◽  
Efficiency Assessment ◽  
Wide Range

Combining economic performance with environmental and social concern has been a developing topic in recent decades. Eco-efficiency analysis is a widely applied tool to assess the efficiency of agricultural systems, while increasingly considering their environmental and social impact. The main objective of this article is to accomplish a literature review on the application of eco-efficiency analysis in agricultural systems, focusing on methods and indicators that are most regarded for the quantitative assessment of agricultural eco-efficiency. The literature review found two main methods most widely applied to assess eco-efficiency: Life Cycle Assessment (LCA) and Data Envelopment Analysis (DEA), which are often combined. LCA is generally focused on the assessment of the environmental impacts of products and practices. DEA is mostly used to measure the eco-efficiency of decision-making units, such as farms, regions, or countries, and has no subjective focus on neither technical nor environmental performance. Both methods share a wide range of economic and environmental indicators but fail to incorporate the social dimension of sustainability into the eco-efficiency analysis. A simple framework, based on Data Envelopment Analysis, is offered to assess the eco-efficiency of the Brazilian agriculture, aiming at identifying the benefits and limitations of the analysis.

scholarly journals EFISIENSI TEKNIS USAHA TANI PADI DI DESA MEUNASAH PANTON LABU KECAMATAN TANAH JAMBO AYE KABUPATEN ACEH UTARA

2019 ◽  
Vol 2 (1) ◽  
pp. 17
Author(s):  
Mutia Fhazira ◽  
Devi Andriyani
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Sampling Method ◽  
Primary Data ◽  
Data Envelopment ◽  
Rice Farming ◽  
Purposive Sampling

This study aims to analyze the technical efficiency of rice farming in Desa Meunasah Panton Labu, Tanah Jambo Aye Sub-district, North Aceh Regency. This study uses primary data obtained from the distribution of questionnaires to 50 respondents who are landowners and farmers in Desa Meunasah Panton Labu, Tanah Jambo Aye Sub-district, North Aceh Regency. This study used is the Purposive sampling method. Data Envelopment Analysis (DEA) is used to analysis the data. The results showed that the landowners were more technically efficient than sharecroppers where the number of farmers who had reached the level of efficiency as many as 19 respondents.

A comparative approach of stochastic frontier analysis and data envelopment analysis estimators: evidence from banking system

2020 ◽  
Vol 47 (7) ◽  
pp. 1787-1810
Author(s):  
Kekoura Sakouvogui
Keyword(s):  
Data Envelopment Analysis ◽  
Cost Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Data Envelopment ◽  
Content Type ◽  
Frontier Analysis ◽  
Efficiency Measures ◽  
Clustering Approach ◽  
Over Time

PurposeThe consistency of stochastic frontier analysis (SFA) and data envelopment analysis (DEA) cost efficiency measures using a sample of 650 commercial and domestic banks in the United States is investigated based on cluster analysis while accounting for the yearly variation in banks.Design/methodology/approachDue to the importance of efficiency measures for policy and managerial decision-making, the cost efficiency measures of SFA and DEA estimators are examined according to four criteria: levels, rankings, stability over time and stability over clustering groups. In this paper, we present two clustering methods, Gap Statistic and Dindex, that involve SFA and DEA cost efficiency measures. The clustering approach creates homogeneous groups of banks offering a similar mix of efficiency levels. Hence, each evaluated bank knows the cluster to which it belongs. Furthermore, this paper provides nonparametric statistical tests of SFA and DEA cost efficiency measures estimated with and without a clustering approach.FindingsThe results suggest that the clustering approach plays a considerable role in the rankings of US banks. Furthermore, the average SFA and DEA cost efficiency measures over time of the homogeneous US banks are substantially higher than those of the heterogeneous US banks.Originality/valueThis research is the first to provide comparative efficiency measures needed for desirable policy conclusions of heterogeneous and homogeneous US banks.

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