2018•Journal of Rural DevelopmentOpen access

Factors Affecting the formation of Smart Rural Development in Iran

Aliakbar Anabestani, Mahdi Javanshiri

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Abstract

Physical-spatial expansion of human settlements, especially over the last few decades, thanks to technological advances, has been increasing in a higher speed; therefore, developing an optimum and sustainable model for physical-spatial expansion of human settlements (particularly in the developing world) has created an enormous challenge. To the extent that it has affected not only the policies of physical planning but also socio-economic, and environmental issues of many rural and urban areas. Efforts have been made to counter the negative effects of urban dispersion; the most significant one was "smart growth strategy". Present study aims to investigate the smart development in rural areas of Iran to present a framework for this strategy, including the principles and factors affecting its development using Fuzzy Analytic Hierarchy Process (FAHP), Accordingly, the relationships between objectives, indicators and sub-indicators and the process of determining the weights of indicators and subindicators, and the final score of indicators was examined using fuzzy hierarchical analysis model and experts' opinions. Results showed the indicator of 'creative rural economy' with a weight of 0.534 was the most significant indicator in smart rural development. The indicators of environmental factors and human capital weighting 0.214 and 0.148, respectively, were in the next order.

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Physical-spatial expansion of human settlements, especially over the last few decades, thanks to technological advances, has been increasing in a higher speed; therefore, developing an optimum and sustainable model for physical-spatial expansion of human settlements (particularly in the developing world) has created an enormous challenge. To the extent that it has affected not only the policies of physical planning but also socio-economic, and environmental issues of many rural and urban areas. Efforts have been made to counter the negative effects of urban dispersion; the most significant one was "smart growth strategy". Present study aims to investigate the smart development in rural areas of Iran to present a framework for this strategy, including the principles and factors affecting its development using Fuzzy Analytic Hierarchy Process (FAHP), Accordingly, the relationships between objectives, indicators and sub-indicators and the process of determining the weights of indicators and subindicators, and the final score of indicators was examined using fuzzy hierarchical analysis model and experts' opinions. Results showed the indicator of 'creative rural economy' with a weight of 0.534 was the most significant indicator in smart rural development. The indicators of environmental factors and human capital weighting 0.214 and 0.148, respectively, were in the next order.

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Available abstract

Physical-spatial expansion of human settlements, especially over the last few decades, thanks to technological advances, has been increasing in a higher speed; therefore, developing an optimum and sustainable model for physical-spatial expansion of human settlements (particularly in the developing world) has created an enormous challenge. To the extent that it has affected not only the policies of physical planning but also socio-economic, and environmental issues of many rural and urban areas. Efforts have been made to counter the negative effects of urban dispersion; the most significant one was "smart growth strategy". Present study aims to investigate the smart development in rural areas of Iran to present a framework for this strategy, including the principles and factors affecting its development using Fuzzy Analytic Hierarchy Process (FAHP), Accordingly, the relationships between objectives, indicators and sub-indicators and the process of determining the weights of indicators and subindicators, and the final score of indicators was examined using fuzzy hierarchical analysis model and experts' opinions. Results showed the indicator of 'creative rural economy' with a weight of 0.534 was the most significant indicator in smart rural development. The indicators of environmental factors and human capital weighting 0.214 and 0.148, respectively, were in the next order.

Key concepts: Weighting, Human settlement, Analytic hierarchy process, Human capital, Sustainable development, Rural area, Environmental economics, Fuzzy logic

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