Evaluating The Urban Efficiencies Of Gansu Province With DEA

As an important province of the less developed regions in China, the urbanization process of Gansu Province continues to accelerate, the urbanization rate continuously improve, however, the urban efficiency did not attract enough attention. It’s significant to improve the urban competitiveness and sustainable development of less developed regions by increasing the urban efficiency. The data envelopment analysis (DEA) is the effective tool to measure urban efficiency, but the traditional DEA can not distinguish the difference among the effective units and define the urban efficiency growth potential. The aggressive cross-evaluation mechanism is introduced along with virtual decision making units (DMU) to overcome the shortcoming of the traditional DEA. In this paper, with land, capital, labor, technology, information, water and electricity consumption being the input indicators, and GDP the output indicator, the traditional DEA, the DEA-Cross Model and the Malmquist Model are employed to analyze the urban efficiency of12prefecture-level cities in Gansu Province based on the panel dataset of urban social economy from2004to2010.The result of the traditional DEA showed that the urban efficiency of Gansu Province is relatively low, only three cities of Gansu Province maintain DEA effective during study period, such as Lanzhou, Jinchang, Jiayuguan, accounting for25%of the total cities. The number of cities which pure technical efficiency is optimal is more than the number of cities with the best overall efficiency and scale efficiency. During2008-2010, only three cities of Gansu Province maintain scale effective, such as Lanzhou, Jinchang, Jiayuguan. The scale efficiency is the main factor that determines the urban efficiency. From the classification features, the urban efficiency of Hexi area is the highest, Longdong area lowest, Longzhong area between. The urban efficiency of professional city is higher than integrated city. The correlation between urban efficiency and the size of the urban population is not obvious.The results of the DEA-Cross Model showed that the urban efficiency in Gansu Province is low (between0.060and0.075) from2008to2010, less than7.5%of the ideal DMU. There is a significant differences between cities in Gansu Province, Lanzhou maximum, Dingxi minimum. From the perspective of spatial distribution, cities in the Longzhong Region have higher urban efficiency than those in the Longdong Region and in Hexi Region. From the perspective of city type, urban efficiency of industrial cities is higher than that of non-mining cities. From the perspective of city scale, urban efficiency of big cities is higher than that of small and medium-sized cities. The clustering results showed that Lanzhou, Jinchang and Jiayuguan belong to the "high input and high output" type, Dingxi and Longnan belong to the "high input and low output" type, and the remaining cities belong to the" low input and low output" type.The analysis of urban efficiency changes shows that the changes in technical, urban efficiency, productivity change, pure technical efficiency and scale efficiency had a slight decrease. Both the comprehensive efficiency change index and productivity change index decreased, indicating that the urban efficiency did not improve, and the tendency of productivity decline was obvious. The change of scale efficiency is the major determining factor of the change of comprehensive efficiency and productivity index. In terms of the classification of urban efficiency changes, the urban efficiency declined in each of the three regions, among which the Longdong region declined most and the Hexi region came next. The changes of comprehensive efficiency in comprehensive cities are bigger than those of professional cities during this period. The productivity of comprehensive cities showed a downward tendency, and the same to professional cities. The productivity of comprehensive cities decreased because of scale efficiency declined, and the technical backwards to productivity decreased of professional cities.The urban efficiency declined in cities of different scales, with greater decline in medium-sized cities than in small and big cities during this period. The productivity decreased more in big cities and medium-sized cities because of the declining scale of production.On the basis of the present study, some suggestions regarding improving urban efficiency were given in the current situation of urban construction and management, including strengthening regional exchanges, urban system construction, development of circular economy, rational flow of population, promoting the process of urban modernization, the protection of traditional culture and development information technology.The research would provide decision-makers and governor with some meaningful references for promoting urban resources utilization and urban sustainable development.