Cities exist through the interaction of multidimensional elements such as population (agents), economy (production), and space (environment). This study utilizes administrative entities as samples to identify the multidimensional relationships among c...
Cities exist through the interaction of multidimensional elements such as population (agents), economy (production), and space (environment). This study utilizes administrative entities as samples to identify the multidimensional relationships among common quantitative indicators. By analyzing scenarios of these administrative entities, the study interprets the significance of these relational expressions. Furthermore, it proposes an Inherent Performance Index to compare multi-layered entities using a shared structure. This index evaluates inherent performance by leveling the influence of considered aspects, offering an alternative to the consequential performance typically provided by economic perspectives.
Various indicators representing urban scale exhibit strong quantitative correlations. By selectively combining those relationships with high degrees of correlation, it is possible to derive a common relational pattern in the form of a single equation. An analysis using the data from South Korea reveals that four indicators—total workforce, GRDP, service workforce, and total building floor area—constitute the most robust interdependent structure. Based on this structure, the equation was optimized using a genetic algorithm. The equation estimates the total workforce as a function of the other three variables. This estimation demonstrates high explanatory power with an average error of less than 10,000 people. Given that the observed range spans from 4.6 thousand to 24.93 million people, this level of accuracy is considered substantial.
The common structure expressed as a single equation shows that diverse administrative entities can be interpreted through the same numerical pattern. Using this pattern, city scenarios were examined across growth, maturity, and decline phases. The process confirmed that the scale of the service industry acts as a constraint on the expansion of the built environment during growth and as a resistance to contraction during decline. Furthermore, the applicability of the same equation across hierarchies—National, Metropolitan, and Basic local governments—provides empirical evidence for the self-similarity of administrative entities.
The study also establishes a comparative method using this equation. First, the generality of the equation was tested. Analyzing data from the Northeastern United States revealed that the coefficients differed from those in South Korea. Thus, the derived equation is not a universal property but an individual pattern shared by specific groups. This understanding addresses the possibility of inter-regional comparison through coefficients. To compare performance with a single coefficient value, the calculation method adjusted the other parts of the equation to be identical. Results were derived for every metropolitan local government in Korea. The calculated coefficient is an index reflecting performance by leveling the factors of industrial population, service industry population, and total floor area. This was named as the Inherent Productivity Index (IPI) representing performance that flattens the influence of available resources and environment.
Productivity from an economic perspective is a consequential performance that compresses related factors into monetary quantities. In contrast, the IPI reflects performance by leveling related population, industry, and built-environment factors. It provides a distinct understanding by assuming identical conditions for the factors considered. Furthermore, the derivation process of the IPI offers the advantage of interpreting patterns and meanings by identifying the underlying relational structure. As neither method is superior to the other, a balanced consideration of both perspectives is essential for a multidimensional understanding of cities.