Data Envelopment Analysis of Urban Development Efficiency from a Traffic Congestion Perspective

Abstract

In general, socioeconomic factors play an essential role in traffic congestion. However, there is still doubt whether traffic congestion fluctuates indefinitely with the change in socioeconomic factors. Using a time analysis unit–based data envelopment analysis (DEA), this study aims to demonstrate urban development efficiency from the perspective of traffic congestion. We employ a linear model to illustrate the effect of internal correlation between independent variables on the model’s accuracy. Through the Gray correlation model, we explore the correlation between socioeconomic factors and the traffic congestion index and select the key evaluation indices of development efficiency. Because the urban development efficiency evaluation belongs to a multi-input and single-output system, we introduce DEA to build a quantitative model for the coupling situation between socioeconomic factors and traffic congestion and to identify the factors with high redundancy. The results show that Beijing’s urban development over the past two decades has been relatively efficient in terms of traffic congestion. This means that the change in relevant socioeconomic factors has played a rather good role in reducing traffic congestion. The discoveries presented here can make us understand the economic principle of socioeconomic factors to reduce traffic congestion and lay the foundation for adjusting socioeconomic factors' utilities in modeling traffic congestion.