Selecting common projection direction in DEA directional distance function based on directional extensibility

2021 ◽  
Vol 154 ◽  
pp. 107105
Author(s):  
Junfei Chu ◽  
Fangqing Wei ◽  
Jie Wu ◽  
Zhe Yuan
Keyword(s):  
Distance Function ◽  
Directional Distance Function ◽  
Projection Direction

scholarly journals Directional Distance Function Technical Efficiency of Chili Production in Thailand

2021 ◽  
Vol 13 (2) ◽  
pp. 741
Author(s):  
Wirat Krasachat ◽  
Suthathip Yaisawarng
Keyword(s):  
Distance Function ◽  
Rainy Season ◽  
Sample Selection ◽  
Agricultural Practices ◽  
Directional Distance Function ◽  
Dry Season ◽  
Small Samples ◽  
Function Technique ◽  
Security Problem ◽  
Gap Technology

To overcome the challenging food safety and security problem, in 2003, the Thai government initiated ‘Good Agricultural Practices’ (GAP) technology. This paper used a sample of 107 small chili farms from the Chiyaphoom province for the 2012 crop year, and data envelopment analysis (DEA) meta-frontier directional distance function technique to answer two questions: (1) Are GAP-adopting farms, on average, more efficient than conventional farms? (2) Does access to GAP technology affect farmers’ decisions to adopt GAP technology? We also developed an ‘indirect’ approach to reduce the potential sample selection bias for small samples. For the dry-season subsample, GAP farms were more technically efficient when compared with non-GAP farms. These dry-season non-GAP farms may not adopt the GAP method because they have limited access to GAP technology. For the rainy-season subsample, on average, GAP farms were more efficient than non-GAP farms at the 5% level. Access to the GAP technology is not a possible reason for non-GAP rainy season farms to not adopt the GAP technology. To enable sustainable development, government agencies and nongovernmental organizations (NGOs) must develop and implement appropriate educational and training workshops to promote and assist GAP technology adoption for chili farms in Thailand.

scholarly journals Measurement of Dynamic Efficiency: A Directional Distance Function Parametric Approach

2011 ◽  
Vol 93 (3) ◽  
pp. 756-767 ◽  
Author(s):  
Teresa Serra ◽  
Alfons Oude Lansink ◽  
Spiro E. Stefanou
Keyword(s):  
Distance Function ◽  
Directional Distance Function ◽  
Dynamic Efficiency ◽  
Parametric Approach

Examining the relationship between farm size and productive efficiency: a Bayesian directional distance function approach

2019 ◽  
Vol 50 (2) ◽  
pp. 237-246 ◽  
Author(s):  
Robertson R.B. Khataza ◽  
Atakelty Hailu ◽  
Graeme J. Doole ◽  
Marit E. Kragt ◽  
Arega D. Alene
Keyword(s):  
Distance Function ◽  
Directional Distance Function ◽  
Productive Efficiency ◽  
Function Approach ◽  
Farm Size ◽  
The Relationship

Analysis of Energy Efficiency in China with a Slack-Based Directional Distance Function Approach

2013 ◽  
Vol 291-294 ◽  
pp. 1241-1244 ◽  
Author(s):  
Rui Xiang Liu ◽  
Jing Luo
Keyword(s):  
Energy Efficiency ◽  
Environmental Regulation ◽  
Distance Function ◽  
Central Area ◽  
Average Energy ◽  
Directional Distance Function ◽  
Function Approach ◽  
Improve Energy Efficiency ◽  
Regional Energy ◽  
Energy Conversation

It is crucial to improve China’s energy efficiency in the context of energy conversation and environmental regulation. This paper approaches the measurement of Chinese regional energy efficiency based on slack-based directional distance function from a production theoretic perspective. The results show that there exists inequality among different regions in China and the east area have the best average energy efficiency for the period 2000-2009, followed by the central area. Based on these findings, this paper correspondingly proposes some policies to improve energy efficiency in China.

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