印尼三宝垄地区产业集聚的空间格局与地方经济决定因素

Q4 Social Sciences
R. A. Pangarso, R. Suharyadi, R. Rijanta
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引用次数: 0

摘要

城市化为印度尼西亚创造了机会,有可能促进经济增长,创建充满活力的城市(大都市)。城市化和集聚经济应该是印度尼西亚发展成为中等收入国家的一个重要因素。制造业成为三宝垄等大都市地区的主导经济部门,呈现出城市化与工业化的关系。产业集聚可能会引发该地区的社会经济变化。为了准备这些变化,重要的是了解集聚的空间动力学并局部预测其决定因素。本文旨在回答与三宝垄大都市外围三宝垄市产业集聚的空间格局和决定因素有关的问题。最近邻分析用于识别空间格局,其次是埃里森和格莱泽指数用于衡量集聚强度,专业化指数用于衡量产业专业化。地理加权回归用于确定集聚的决定因素。分析使用了2016年大中型工业地理数据库和相关的基于街道的数据。结果表明,21个行业细分领域中有11个行业在地理上形成聚集(聚集)格局。其中6个强烈聚集(大部分为局部聚集)。这六个分区的高度专业化发生在14个分区。结果得到一个显著的空间回归模型,解释了三个子行业同时发生的自变量的影响:饮料;穿着服装;木材和软木制品,家具、稻草制品和编织材料除外。在一定程度上,三个子行业专业化在街道层面的产业集聚是由变量决定的:工业就业;职业学校;地区生产总值;人口主干道;农业用地可用性;以及农业家庭。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Spatial Patterns and Local Economic Determinant of Industrial Agglomeration in Semarang District, Indonesia
Urbanization creates opportunities for Indonesia, potentially to boost economic growth and create vibrant cities (metropolitan). Urbanization and agglomeration economies should be an important element in Indonesia‘s development as a mid-income country. Manufacturing industry becomes a dominant economic sector in metropolitan area such as Semarang that shows urbanization-industrialization relationship. Industrial agglomeration potentially induces socio-economic changes in the region. To prepare these changes, it is important to understand the spatial dynamics of agglomeration and predict its determinants locally. This paper aims to answer questions related to the spatial patterns and determinants of industrial agglomeration in Semarang Regency, a periphery of Semarang metropolitan. Nearest Neighbor Analysis is used to identify spatial patterns, followed by Ellison and Glaeser Index to measure agglomeration strength, and Specialization Index to measure industrial specialization. Geographically Weighted Regression is used to identify determinants of agglomeration. Analysis uses geographical database of Large and Medium Industries in 2016 and related sub-district based data. Result shows 11 of 21 sub-sectors of industries geographically form clustered (agglomerated) pattern. Six of them are strongly agglomerated (most localized). High specializations in these six sub-sectors occur in 14 sub-districts. Result obtains a significant spatial regression model explains the effect of independent variables simultaneously occurring in three sub-sectors: beverages; wearing apparel; wood and products of wood and cork, except furniture, articles of straw and plaiting materials. Partially, industrial agglomeration by three sub-sector’s specializations in sub-district level is determined by variables: industrial employment; vocational school; Gross Regional Domestic Product; population; arterial road; agricultural land availability; and agricultural households.
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来源期刊
Geoplanning Journal of Geomatics and Planning
Geoplanning Journal of Geomatics and Planning Earth and Planetary Sciences-Computers in Earth Sciences
CiteScore
1.00
自引率
0.00%
发文量
5
审稿时长
4 weeks
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