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Labour productivity is one of the key factors determining the wood-based industry development and competitiveness. This study assessed the importance of human resources and labour productivity in the furniture sector in the European Union (EU) countries. A cluster analysis and multivariate linear ordering analysis were conducted. The EU15, especial...
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... following indicators were covered: the share of the employees in the furniture industry in the total industry (%), the number of employees per enterprise (number of persons), the furniture production sold per employee (EUR), the annual wages per employee (EUR), the share of labour costs in production (%), and the furniture production sold for every 1000 euro of the labour costs (EUR). Table 1 presents the definitions of the labour and work productivity indicators analysed in the research. . Laboor in wood industry,, BioResources 16(2), 3643-3661. ...Citations
... The forest industry is strategically important for many countries (Hagadone and Grala 2012;Ratnasingam et al. 2017;Griffin et al. 2020;Grzegorzewska and Sedliačiková 2021;Ab Latib et al. 2022), including Russia (Trofimova et al. 2021). Today, new approaches to forestry are in demand. ...
World experience in the creating of clusters in different industries has shown their effectiveness. This paper investigated the resource potential for creating a cluster designed for wood processing and to process wood waste from the timber industry of the Krasnoyarsk Territory of Russia. Static indicators were assessed, representing a quantitative characteristic of forest raw material resources: total and operational reserves of wood available in the region. While studying the state and use of forest resources, significant reserves of forest resources and secondary raw materials were revealed. Main indicators of the forest industry of the region over recent years were analyzed. The main systemic issues hindering the development of the timber industry were exposed. It was concluded that the region has raw material potential and industrial infrastructure necessary for the formation and sustainable development of a cluster for processing waste from the timber industry. Analysis of the producers and harvesters of forest products’ locations revealed potential wood industry clusters, and areas suitable for cluster economic development were proposed. The average figures of the nearest neighbor were used and analyzed to examine the spatial distribution of raw material harvesters and enterprises that produce finished products with respect to transport infrastructure, staffing, and raw material availability.
