Environmental implications of economic efficiency in cotton production: a case study from Turkey

2011 ◽  
Vol 7 (1) ◽  
pp. 42-49
Author(s):  
C. Gunden
Author(s):  
D Kodirov ◽  
O Tursunov ◽  
A Ahmedov ◽  
R Khakimov ◽  
M Rakhmataliev

2015 ◽  
Vol 103 ◽  
pp. 675-684 ◽  
Author(s):  
Francois Visser ◽  
Paul Dargusch ◽  
Carl Smith ◽  
Peter R. Grace
Keyword(s):  

2021 ◽  
Vol 11 (3) ◽  
Author(s):  
Aleksander Kuczabski

The article proposes a new unique approach to assessing the economic efficiency of national governments. The assessment is based on the indicator of gross free product per capita, which is a difference between GDP and government size per capita. This method was used to analyze the situation in two post-communist states – Poland and Ukraine. The author studied their economic development in 2009–2019, and the received data was used to draw conclusions about economic policies in the two countries in the period in question. A forecast has been made about the possible impact of the Covid-19 pandemic on economic processes from the perspective of changes in the gross free product per capita.


Author(s):  
Moslem Sami ◽  
Habib Reyhani

This study evaluated the impacts of cotton farming on the climate changes in terms of energy and greenhouse gas (GHG) emission indices. Energy consumption pattern and sensitivity of energy inputs were evaluated and share of each input in GHG emissions was determined in the form of direct and indirect emissions for cotton farms in Golestan province of Iran. The total energy input and energy output were calculated to be 34,424.19 and 41,496.67 MJ/ha respectively. The share of fertilizers by 45.0 % of total energy inputs was the highest. This was followed by energies of fuel (18.4 %) and irrigation (17.9 %) respectively. Fertilizers and fuels were also the biggest producers of GHGs in the farms with shares of 61.95 and 24.32 % of total GHGs emission. Energy ratio, energy balance, energy intensity and energy productivity were found as 1.21, 7,072.48 MJ/ha, 9.79 MJ/kg and 0.10 kg/MJ, respectively. Results of sensitivity analysis indicated that the cotton production was more sensitive to energies of seed and human labour than other inputs and an additional use of 1 MJ of each of these inputs would lead to a change in the yield by −0.75 and 0.73 kg/ha, respectively. The results also showed, in the process of cotton farming 897.80 and 1177.67 kg CO2 – equivalent of direct and indirect GHG were emitted per hectare respectively.


2020 ◽  
pp. 447-484 ◽  
Author(s):  
Muhammad Habib ur Rahman ◽  
Ishfaq Ahmad ◽  
Abdul Ghaffar ◽  
Ghulam Haider ◽  
Ashfaq Ahmad ◽  
...  

Author(s):  
Konstantinos Kirytopoulos ◽  
Dimitra Voulgaridou ◽  
Vrassidas Leopoulos

Due to the rapid evolution of information technology, supply chain integration is nowadays easier than in the past. Moreover, the need for economic efficiency leads suppliers and customers to closely co-operate in pursuit of, what seems to be the holy grail of modern supply chain management, end to end optimization. The core objective of this chapter is the provision of a decision framework for enterprise formations organized as collaborative clusters, which is a sophisticated form of a virtual enterprise network. This framework, based on the ANP-BOCR model, takes into account clusters’ special characteristics the most important of which is that the supply chain entities do have a clear picture of strategies, policies, needs, strengths and weaknesses of one another. The whole approach is illustrated through a parapharmaceutical cluster case study which reveals that “common” knowledge and risks are very important in an environment where entities are sometimes partners and sometimes competitors.


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