Bioenergy Based on Wood Chips as the Development Driver of Non-Urban Forested Areas – The Case Study of Ural Region
One of the most important key factors for the development of non-urban areas is infrastructure, and energy generation is one of the fundamental infrastructure elements. This paper provides a new solution for energy generation based on wood chips which has a multi-sector effect because the authors offer to combine planning of forest cleaning cutting with bioenergy generation in one complex project, which will have socio-economic and ecological effects. The situation with forest fires makes the authors’ idea more attractive because after forest fires the problem of cleaning cutting in forest becomes very important and urgent by ecological and economical points: after cleaning cutting there are a lot of low quality wood which can be recycled into chips for the production bioenergy by the authors’ idea. This enriched methodology has successfully been applied into the regional strategical planning in the field of bioenergy and forestry of the Ural region of Russia; however, it is suitable for applications in regional development in any non-urban forested region of the world.
Purpose – The purpose of this paper is to introduce findings of comparative analysis and various models based on cultural heritage resources to foster regional development.
Design/methodology/approach – Comparison of operational schemes, market positions and branding of three successful cultural heritage centers in Germany, Great Britain and Russia demonstrates a variety of regional development models based on cultural resources and tourism development, and reveals their advantages and disadvantages.
Findings – The paper evidences the potential of cultural resources and the tourism sector as drivers for regional development, and helps formulate basic recommendations for the Russian situation requiring elaboration of adequate financial and social instruments.
Originality/value – The paper provides a complex analysis of different operational models in three European countries with regard to specific national situations and specificity of heritage operational management.
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.