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Improving the performance and economic sustainability of agricultural producers requires the integration of many dimensions, one of which is logistics. Establishing efficient and cost-effective transportation is a key element of establishing sustainable linkages along food supply chains between farmers, storage and transport companies, and consumers. In this regard, infrastructural constraints to sustainability in agricultural production exacerbate transportation costs and risks, and thus result in lower performance of agricultural producers. As fuel consumption is, first, the most significant cost in agricultural logistics and, second, particularly sensitive to disruptions of transport, loading, and storage infrastructure, management of fuel costs is crucial to assure profit margin of an agricultural enterprise. By transforming the standard economic order quantity (EOQ) model, the authors attempt to build an approach to the optimization of fuel costs. The analysis made in the cases of twelve large crop farms in three territories of Southern Russia allowed the consideration of: (1) fragmentation in storage infrastructure; (2) variations in fuel consumption depending on the vehicle load ratio; (3) the use of their own fleet of vehicles against the outsourcing of transport operations. The authors find that the tactics of optimization of fuel costs vary depending on the location of a farm in relation to grain storage facilities. Particularly, the farms located in areas of high concentration of storage facilities benefit from using their own fleet of vehicles, while those experiencing longer distances of transportation should outsource the performance of logistics operations to third parties. To overcome a site-specific nature, the transformed EOQ model should accommodate country-specific requirements, specifically, the level of fragmentation of transport and storage infrastructure, average distance of transportation from a farm to receival site, and average fuel consumption rates depending on the types of trucks commonly used by farmers. The key recommendation is that sustainability-aimed management of logistics costs should consider combining the operation of trucks by a farm with the outsourcing of transportation operations to address the fragmentation of transport and storage infrastructure.
Tianming Gao; Vasilii Erokhin; Aleksandr Arskiy. Dynamic Optimization of Fuel and Logistics Costs as a Tool in Pursuing Economic Sustainability of a Farm. Sustainability 2019, 11, 5463 .
AMA StyleTianming Gao, Vasilii Erokhin, Aleksandr Arskiy. Dynamic Optimization of Fuel and Logistics Costs as a Tool in Pursuing Economic Sustainability of a Farm. Sustainability. 2019; 11 (19):5463.
Chicago/Turabian StyleTianming Gao; Vasilii Erokhin; Aleksandr Arskiy. 2019. "Dynamic Optimization of Fuel and Logistics Costs as a Tool in Pursuing Economic Sustainability of a Farm." Sustainability 11, no. 19: 5463.
For a long time, the majority of China, which has the world’s largest population, has been immobile and lived in rural areas. However, over recent decades, with the economic rise of China, rural labor has demonstrated a trend of moving to rapidly industrializing regions in search of higher income and better employment opportunities. Along with the labor cutback, out-migration introduces negatives to the sustainable development of rural areas, i.e., depopulation, the abandonment of rural settlements and agricultural lands, and the aging of the population, among others. Due to the threats of labor outflow to sustainability, studying the causes of China’s rural out-migration can reveal lessons on how state policies can be designed to reduce the negative impacts of out-migration on rural communities. The purpose of this paper is to identify the major causes of migration movements among the rural areas of northern China that are considered to be the best-performing among the provinces of the country in terms of rural development, agricultural production, and the wealth of rural dwellers. A two-stage survey of a panel of experts involved: (1) respondents representing government officials and universities of the Heilongjiang, Jilin, and Liaoning provinces and the Inner Mongolia Autonomous Region, and (2) regional and district levels of administration, and research and public establishments of Heilongjiang Province. In stage three, drawing on the authors’ own survey of 128 rural households in three counties of Heilongjiang Province, the major migration drivers have been identified, and the portfolio of a typical rural migrant has been developed. Some of the key findings are that migration intentions are fueled by the rural–urban income gap, poverty, a reduction of demand for labor in rural areas, underdeveloped infrastructure, the low quality of social services in rural settlements, and the low social standing of rural dwellers. The approach allows monitoring the dynamics of migration attitudes as responses to the policy interventions that are aimed at the sustainable development of rural areas.
Gao Tianming; Anna Ivolga; Vasilii Erokhin. Sustainable Rural Development in Northern China: Caught in a Vice between Poverty, Urban Attractions, and Migration. Sustainability 2018, 10, 1467 .
AMA StyleGao Tianming, Anna Ivolga, Vasilii Erokhin. Sustainable Rural Development in Northern China: Caught in a Vice between Poverty, Urban Attractions, and Migration. Sustainability. 2018; 10 (5):1467.
Chicago/Turabian StyleGao Tianming; Anna Ivolga; Vasilii Erokhin. 2018. "Sustainable Rural Development in Northern China: Caught in a Vice between Poverty, Urban Attractions, and Migration." Sustainability 10, no. 5: 1467.