Cross-country comparison of the efficiency of the European forest sector and second stage DEA approach

Gutiérrez, Ester; Lozano, Sebastián

doi:10.1007/s10479-020-03756-9

Cited by 28 publications

(20 citation statements)

References 51 publications

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“…From the analysis of the factors of forestry ecological efficiency, EDL was a moderating important factor. However, in the study of Ester and Sebastian [52], GDP was a vital factor to the efficiency of the forest sector. The reasons for the different conclusions the 28 EU/EFTA countries taken as a subject, and GDP played an important role in international efficiency evaluation.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of Forestry Ecological Efficiency: A Spatiotemporal Empirical Study Based on China’s Provinces

Chen

Yao

2021

Forests

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Forests play a very important role in carbon dioxide emissions and climate change, and the development of China’s forestry is of great significance to our citizens. However, it is an arduous task for us to improve forestry output at a high and good level while taking environmental factors into account. In this paper, the non-expected super-efficiency SBM (slacks-based measure) model was used to measure the forestry ecological efficiency (FEE) of 31 provinces in China from 2004 to 2018, and the spatial and temporal evolution of FEE in different regions of China was analysed by using spatial econometric method. Tobit regression and random forest algorithm were selected to analyze the influence on FEE. The results showed that, firstly, the average annual increase of the national total factor productivity change of China’s forestry was 1.2%, and that the average annual increase of the national total factor productivity change in the eastern region was lower than that in the central and western regions. Secondly, the distribution of China’s FEE of the northeast and the south was higher, and FEE of China’s middle regions was relatively lower in 2004, but then the FEE in Northeast China has decreased, and the FEE has increased gradually from north to south in 2018. The agglomeration of high-tech industries in most regions of China had obvious positive spatial correlation characteristics in 2018. Thirdly, there was a negative correlation between forestry fixed assets investment and FEE, environmental regulation was an important factor affecting the ecological efficiency of forestry in China, and the level of economic development and industrial structure also had a certain impact on FEE.

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Section: Discussionmentioning

confidence: 99%

Evaluation of Forestry Ecological Efficiency: A Spatiotemporal Empirical Study Based on China’s Provinces

Chen

Yao

2021

Forests

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“…This interesting result involves the costs for services and outlines their role in efficiency. The same authors (Kovalčík, 2020) and Gutiérrez and Lozano (2020) made cross-country efficiency comparisons of forestry through the DEA. The research of Gutiérrez and Lozano covered 29 countries, including Bulgaria and Slovakia.…”

Section: Entrepreneurship and Sustainability Issuesmentioning

confidence: 99%

Performance measuring of wood-processing microenterprises through Data Envelopment Analysis: A case study of Slovakia, Poland, and Bulgaria

Sedliačiková,

Neykov,

Dobrovič

et al. 2024

JESI

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In the context of the role the wood-processing industry has in Slovakia, Poland, and Bulgaria, as an income provider in rural regions and contemporary challenges like inflation and intensive competition, there is a need to assess the performance of microenterprises using Data Envelopment Analysis (DEA), considering the crucial role these entities play in the regional economies. The aim is the creation of a more universally applicable DEA model for assessing the efficiency and performance of wood-processing microenterprises, taking into account the unique challenges and opportunities in Slovakia, Poland, and Bulgaria, defining the profile of optimal enterprise according to methodology in the current research, and indicating the leading problems in their performance. In their management, wood-processing enterprises respond to changes in the external environment, pursuing profit extraction in the competitive struggle. Comparisons with similar companies provide data on the economic efficiency of the sector and the gaps the enterprise needs to correct. Data from the Eurostat Structural Business Statistics were involved for 2011-2020. The current study used Data Envelopment Analysis (DEA), a nonparametric technique that allows enterprises to compare their efficiency frontiers and, from there, reveal their competitiveness. Thus, they can be arranged and measured, and the differences between the inputs and outputs of enterprises can be measured, as well as the efficiency. The results revealed that all the surveyed countries have a problem with the gross value added by a wood-processing micro-enterprise. Polish and Bulgarian enterprises have a problem with pure technical efficiency. Slovakian enterprises have excellent performance and can be used as a benchmark in optimizing the activities of Polish and Bulgarian enterprises.

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“…The same can be seen in the sawmill studies, where each sawmill is considered a DMU (Yin 1998). Another common approach is to pool data for the same districts or units over a number of years, so the number of DMUs increases (Diaz-Balteiro et al 2006;Kovalčík 2020;Gutiérrez and Lozano 2020). Bogetoft et al (2003) and LeBel (1996) pooled data over 3 and 6 years, respectively, so that a contractor's annual performance represented a DMU.…”

Section: Choice Of Dmus and Inputs And Outputsmentioning

confidence: 99%

Applications of DEA and SFA in benchmarking studies in forestry: state-of-the-art and future directions

Strange

Bogetoft

Aalmo

et al. 2021

International Journal of Forest Engineering

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The forestry sector is constantly looking for ways for making data-driven decisions and improving efficiency. The application of Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) allow the users to go beyond looking at simple key performance indicators. Benchmarking is one of the most common tools in business for improving efficiency and competitiveness. This study searched for benchmarking studies in Web of Science until December 2020. It reviewed 56 benchmarking studies in forestry and discusses the potential advantages of using benchmarking in forestry. More than 80% of the studies apply DEA. This review found that almost half of the benchmarking studies in forestry have attempted to estimate the efficiency of forest management organizations at regional scale, mostly being public or state-owned forest districts. A bit more than one-third of the studies have focused on benchmarking forest industries and one-fifth, benchmarking of forest operations. Forest management organizations mainly applied benchmarking for internal comparison and forest industries entirely focused on competitive benchmarking. Surprisingly, in most cases the studies do not necessarily overlap geographically with forest rich countries (e.g., Russian Federation or Brazil). A number of studies address multiple criteria. The future potential for applying automatic data transfer from harvest machines to interactive benchmarking systems are discussed. Finally, the paper discusses the advantages and weaknesses of benchmarking and future research on improving usefulness and usability of benchmarking in forest businesses.

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Cross-country comparison of the efficiency of the European forest sector and second stage DEA approach

Cited by 28 publications

References 51 publications

Evaluation of Forestry Ecological Efficiency: A Spatiotemporal Empirical Study Based on China’s Provinces

Evaluation of Forestry Ecological Efficiency: A Spatiotemporal Empirical Study Based on China’s Provinces

Performance measuring of wood-processing microenterprises through Data Envelopment Analysis: A case study of Slovakia, Poland, and Bulgaria

Applications of DEA and SFA in benchmarking studies in forestry: state-of-the-art and future directions

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