An Empirical Study of Commuting Efficiency Between Different Educational Categories of Workers in Shanghai

Spatial interaction models can simulate commuting levels and evaluate the effort required for commuting optimization, providing more valuable information than a linear program. We take advantage of a large data set in Shanghai and exploit the fact that these data can be split by a key socioeconomic stratifier (education). By simulating the effect of shorter trip length, we estimate the extent to which commuting is relatively organized or excessive. More important, however, is that characteristics of the study region promote somewhat different results compared to US cities: well-educated cohorts use their higher-income to dominate central locations with higher access and amenity. The findings are consistent with the mathematical expectation from prior work, in that trip length reduction represents a decrease in entropy (i.e., an increase in organization). The potential for such improvement varies by educational level, and generally is higher for well-educated workers and lower for poorly educated workers.