Economics at your fingertips  

Spatial Differentiation and Driving Mechanism of Agricultural Multifunctions in Economically Developed Areas: A Case Study of Jiangsu Province, China

Rongtian Zhang () and Ming Chen
Additional contact information
Rongtian Zhang: Institute of Rural Revitalization Strategy, Yangzhou University, Yangzhou 225009, China
Ming Chen: Institute of Rural Revitalization Strategy, Yangzhou University, Yangzhou 225009, China

Land, 2022, vol. 11, issue 10, 1-17

Abstract: Revealing the spatial patterns of differentiation and the driving mechanism of agricultural multifunctional patterns is an important aspect of coordinating the functional optimisation and coordinated development of different agricultural regions. On the basis of understanding the connotation of agricultural multiple functions, this paper constructed an evaluation index system of agricultural multiple functions. Taking Jiangsu Province as a typical case, the spatial patterns of agricultural multifunctions in Jiangsu since 1978 were analysed by using the entropy weight TOPSIS (technique for order preference by similarity to ideal solution) method and ESDA (exploratory spatial data analysis) model, and the influencing mechanism of agricultural multifunction spatial differentiation was revealed by a geographic detector model. The results showed that (1) the cities with higher agricultural grain production functions were mainly concentrated in Yancheng and Huai’an; cities with higher agricultural economic development functions were mainly distributed in the coastal areas of Jiangsu; cities with higher agricultural social security functions were mainly concentrated in the Suzhou–Wuxi–Changzhou metropolitan area; and cities with higher agricultural ecotourism functions evolved from Nanjing–Zhenjiang to Suzhou–Wuxi–Changzhou. (2) The H–H (high–high) cluster pattern of the agricultural grain production function shifted from southern Jiangsu to northern Jiangsu. The H–H clusters of the agricultural economic development function and social security function were mainly distributed in Suzhou–Wuxi–Changzhou, while the L–L (low–low) cluster was mainly distributed in northern Jiangsu. The H–H cluster of agricultural ecotourism functions was mainly distributed in the areas with rich mountain and hill resources or dense water networks in Jiangsu. (3) The agricultural multifunction pattern differentiation was affected by the natural environment and economic and social comprehensive factors; the level of economic development and population employment structure were the leading factors of agricultural multifunction spatial differentiation; industry structure and people’s living conditions were the important driving forces of agricultural multifunction spatial differentiation; and the natural environment and population density were the basic factors underlying agricultural multifunction spatial differentiation.

Keywords: agriculture multifunction; spatial pattern; spatial agglomeration; ESDA; geographical detector; driving mechanism; economically developed areas (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link) (application/pdf) (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this article

Land is currently edited by Ms. Carol Ma

More articles in Land from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

Page updated 2023-05-18
Handle: RePEc:gam:jlands:v:11:y:2022:i:10:p:1728-:d:934305