Российский город в условиях капитализма: социальная трансформация внутригородского пространства
In light of the increasingly complex socio-economic processes and changes, today’s cities as complex systems will not be able to respond to numerous challenges unless they possess a governance model that can flexibly adjust to shifting external conditions. In this regard, there is growing demand for innovative management tools combining solutions from different fields. The ‘smart city’ concept is one of the most sought after. This article analyses the advantages of this concept, the conditions needed, as well as the obstacles for implementing it. We consider the challenges related to becoming a ‘smart city’, the different ways a smart city comes into being, evaluate the future for smart city solutions, as well as assess the current willingness of administrations of Russian cities to adopt this model.From our analysis, we conclude that ‘smart city’ strategies continue in many cases to rely on a narrow, ‘technological’ approach. Such an approach presupposes that the availability alone of smart infrastructure can solve many urban problems and improve the quality of urban life. However, in contrast to the extended, comprehensive approach, it does not address many socio-economic factors and the real needs of the population. Consequently, certain targets remain largely unfulfilled. The implementation of an integrated approach implies a number of conditions, such as the ability to integrate management decisions taken at various levels and predict how changes in one system affect other systems; a focus on interdisciplinary collaboration; and an ability to deal with resistance to changes.A survey conducted by the HSE’s Research Institute for Regional and Urban Planning in 2015 aimed to evaluate the future prospects for establishing the concept of ‘smart city’ in Russian cities. The survey results show that city managers in Russia in general positively perceive the ‘smart city’ approach as a basis for urban development strategies. Yet, the possibilities for implementing it are mostly seen as medium or long-term options.
We address the external effects on public sector efficiency measures acquired using Data Envelopment Analysis. We use the health care system in Russian regions in 2011 to evaluate modern approaches to accounting for external effects. We propose a promising method of correcting DEA efficiency measures. Despite the multiple advantages DEA offers, the usage of this approach carries with it a number of methodological difficulties. Accounting for multiple factors of efficiency calls for more complex methods, among which the most promising are DMU clustering and calculating local production possibility frontiers. Using regression models for estimate correction requires further study due to possible systematic errors during estimation. A mixture of data correction and DMU clustering together with multi-stage DEA seems most promising at the moment. Analyzing several stages of transforming society’s resources into social welfare will allow for picking out the weak points in a state agency’s work.