Abstract
In order to analyze the coordination relationship between investment potential and economic development and its driving mechanisms, this study integrated the entropy weight method, coupling coordination degree model, exploratory spatial data analysis, geographic detector, and geographically weighted regression model. The developed approach was applied using data from 51 African countries from 2008 to 2016. The results showed that: (1) While the level of economic development in the African continent has increased steadily, the overall investment potential needs to be improved. The mean economic development index rose from 0.116 to 0.151, but the economic gap among countries was still highly evident. (2) Uncoordinated development and barely coordinated development level were the dominant types of relationship between investment potential and economic development in African countries. The spatial distribution showed significant agglomeration characteristics; the sub-hot spot and sub-cold point regions maintained strong dependence with their hot spot and cold point counterparts. The hot spot areas gradually formed an agglomeration in Southern Africa and highly fragmented distribution in other areas. The cold spot areas formed a spatial distribution pattern of “one core and one belt” with some countries in Western Africa forming the core, while some Central and East African countries constituting the belt. (3) The coordination relationship between investment potential and economic development was influenced mainly by factors including economic base, residents’ living standard, industrial construction level, information support level, and business friendliness. Using geographically weighted regression coefficient distribution of indicators, the driving mechanisms of spatial distribution could be divided into five types: economic base driven, industry-driven, information application-driven, business convenience-driven, and consumer market-driven.
Highlights
In the era of economic globalization, international investment and trade have become more ubiquitous and profitable, becoming essential engines for stimulating global economic growth
The static analysis of investment potential based on the entropy weight method (EWM), the grey correlation degree model (GCDM), factor analysis (FA), and data envelopment analysis (DEA) has percolated into the mainstream of current researches [7,8]
Based on the coordination degree and the corresponding data of investment potential and economic development from 2008 to 2016, we developed a regression model to analyze the driving factors that led to the spatial heterogeneity of the coordination relationship
Summary
In the era of economic globalization, international investment and trade have become more ubiquitous and profitable, becoming essential engines for stimulating global economic growth. The static analysis of investment potential based on the entropy weight method (EWM), the grey correlation degree model (GCDM), factor analysis (FA), and data envelopment analysis (DEA) has percolated into the mainstream of current researches [7,8]. This static analysis has largely evaded the impact of economic cycle changes, resulting in a lack of long-term reference for investment potential. Some scholars have established investment potential evaluation systems using fundamental indicators such as GDP and population size These assessment systems have limited capacity to understand the impact of resource development, economic environment, open environment, entrepreneurial environment, and other development systems on investment potential. Establishing an evaluation index system that comprehensively reflects the investment potential is crucial in analyzing the evolution of investment potential of underdeveloped regions
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