Efficiency of Wood-Processing Enterprises—Evaluation Based on DEA and MPI: A Comparison between Slovakia and Bulgaria for the Period 2014–2018
Abstract
:1. Introduction
2. Materials and Methods
2.1. Data Envelopment Analysis (DEA)
2.2. Malmquist Productivity Index (MPI)
3. Results and Discussion
3.1. Data Envelopment Analysis CCR Scores
3.2. Malmquist Productivity Index Results
4. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Vincová, K. Using DEA models to measure efficiency. BIATEC 2009, 13, 24–28. [Google Scholar]
- Martic, M.; Novakovic, M.; Baggia, A. Data Envelop ment Analysis Basic Models and their Utilization. Organizacija 2009, 42, 37–43. [Google Scholar] [CrossRef]
- Mala, D.; Sedliacikova, M.; Kascakova, A.; Bencikova, D.; Vavrova, K.; Bikar, M. Green Logistics in Slovak Small and Medium Wood-Processing Enterprises. Bioresources 2017, 12, 5155–5173. [Google Scholar] [CrossRef] [Green Version]
- Whittaker, W. Resource Allocation Funding Formulae, Efficiency of. In Encyclopaedia of Health Economics; Culyer, A.J., Ed.; Elsevier: Amsterdam, The Netherlands, 2014; pp. 256–266. ISBN 9780123756794. [Google Scholar] [CrossRef]
- Milewski, R.; Kwiatkowski, E. Podstawy Ekonomii; Wydawnictwo Naukowe PWN: Warszawa, Poland, 2018. [Google Scholar]
- Agriculture, Forestry and Fishery Statistics—2020 Edition; Publications Office of the European Union: Luxembourg, 2020; Available online: https://ec.europa.eu/eurostat/documents/3217494/12069644/KS-FK-20-001-EN-N.pdf/a7439b01-671b-80ce-85e4-4d803c44340a?t=1608139005821 (accessed on 14 July 2021).
- Neykov, N.; Krišťáková, S.; Hajdúchová, I.; Sedliačiková, M.; Antov, P.; Giertliová, B. Economic Efficiency of Forest Enterprises—Empirical Study Based on Data Envelopment Analysis. Forests 2021, 12, 462. [Google Scholar] [CrossRef]
- Pezdevšek Malovrh, Š.; Paletto, A.; Posavec, S.; Dobšinská, Z.; Đorđević, I.; Marić, B.; Avdibegović, M.; Kitchoukov, E.; Stijović, A.; Trajkov, P.; et al. Evaluation of the Operational Environment Factors of Nature Conservation Policy Implementation: Cases of Selected EU and Non-EU Countries. Forests 2019, 10, 1099. [Google Scholar] [CrossRef] [Green Version]
- Andersson, E.; Keskitalo, E.C.H. Adaptation to climate change? Why business-as-usual remains the logical choice in Swedish forestry. Glob. Environ. Chang. 2018, 48, 76–85. [Google Scholar] [CrossRef]
- Vu, T.T.H.; Tian, G.; Khan, N.; Zada, M.; Zhang, B.; Nguyen, T.V. Evaluating the International Competitiveness of Vietnam Wood Processing Industry by Combining the Variation Coefficient and the Entropy Method. Forests 2019, 10, 901. [Google Scholar] [CrossRef] [Green Version]
- Báliková, K.; Dobšinská, Z.; Paletto, A.; Sarvašová, Z.; Hillayová, M.K.K.; Šterbová, M.; Výbošt’ok, J.; Šálka, J. The Design of the Payments for Water-Related Ecosystem Services: What Should the Ideal Payment in Slovakia Look Like? Water 2020, 12, 1583. [Google Scholar] [CrossRef]
- Kupčák, V.; Šmída, Z. Forestry and Wood Sector and Profitability Development in the Wood-processing Industry of the Czech Republic. J. For. Sci. 2015, 61, 244–249. [Google Scholar] [CrossRef] [Green Version]
- Lähtinen, K. Linking resource-based view with business economics of woodworking industry: Earlier findings and future insights. Silva Fenn. 2007, 41, 149–165. [Google Scholar] [CrossRef] [Green Version]
- Tofallis, C. Combining two approaches to efficiency assessment. J. Oper. Res. Soc. 2001, 52, 1225–1231. [Google Scholar] [CrossRef]
- Hollingsworth, B. Non-Parametric and Parametric Applications Measuring Efficiency in Health Care. Health Care Manag. Sci. 2003, 6, 203–218. [Google Scholar] [CrossRef] [PubMed]
- Sedivka, P. Estimation of Technical Efficiency in Production Technologies of Czech Sawmills. Drv. Ind. 2009, 60, 197–207. [Google Scholar]
- Prasetyo, V.; Belleville, B.; Ozarska, B. Furniture Production Efficiency in the Indonesian Context. In Proceedings of the 29th International Conference on Wood Modification and Technology “Implementation of Wood Science in Woodworking Sector”, Zagreb, Croatia, 6–7 December 2018. [Google Scholar]
- Charnes, A.; Cooper, W.; Rhodes, E. Measuring the efficiency of decision making units. Eur. J. Oper. Res. 1978, 2, 429–444. [Google Scholar] [CrossRef]
- Yin, R. DEA: A new methodology for evaluating the performance of forest products producers. For. Prod. J. 1998, 48, 29–34. [Google Scholar]
- Yin, R. Production efficiency and cost competitiveness of pulp producers in the Pacific Rim. For. Prod. J. 1999, 49, 43–49. [Google Scholar]
- Yin, R. Alternative measurements of productive efficiency in the global bleached softwood pulp sector. For. Sci. 2000, 46, 558–569. [Google Scholar]
- Helvoigt, T.L.; Adams, D.M. Data envelopment analysis of technical efficiency and productivity growth in the US Pacific Northwest sawmill industry. Can. J. For. Res. 2008, 38, 2553–2565. [Google Scholar] [CrossRef]
- Salehirad, N.; Sowlati, T. Dynamic efficiency analysis of primary wood producers in British Columbia. Math. Comput. Model. 2007, 45, 1179–1188. [Google Scholar] [CrossRef]
- Salehirad, N.; Sowlati, T. Productivity and efficiency assessment of the wood industry: A review with a focus on Canada. For. Prod. J. 2006, 56, 25–32. [Google Scholar]
- Dobos, I.; Vörösmarty, G. Supplier selection: Comparison of DEA models with additive and reciprocal data. Cent. Eur. J. Oper. Res. 2021, 29, 447–462. [Google Scholar] [CrossRef] [Green Version]
- Cook, W.D.; Seiford, L.M. Data envelopment analysis (DEA)—Thirty years on. Eur. J. Oper. Res. 2009, 192, 1–17. [Google Scholar] [CrossRef]
- Alzamora, R.M.; Apiolaza, L.A. A DEA approach to assess the efficiency of radiata pine logs to produce New Zealand structural grades. J. For. Econ. 2013, 19, 221–233. [Google Scholar] [CrossRef]
- Susaeta, A.; Adams, D.; Carter, D.; Gonzalez-Benecke, C.; Dwivedi, P. Technical, allocative, and total profit efficiency of loblolly pine forests under changing climatic conditions. For. Policy Econ. 2016, 72, 106–114. [Google Scholar] [CrossRef] [Green Version]
- Korkmaz, E. Measuring the productive efficiency of forest enterprises in Mediterranean Region of Turkey using data envelopment analysis. Afr. J. Agric. Res. 2011, 6, 4522–4532. [Google Scholar]
- Sporcic, M.; Martinic, I.; Landekic, M.; Lovric, M. Measuring Efficiency of Organizational Units in Forestry by Nonparametric Model. Croat. J. For. Eng. 2009, 30, 1–13. [Google Scholar]
- Kovalčík, M. Efficiency of the Slovak forestry in comparison to other European countries: An application of Data Envelopment Analysis. Cent. Eur. For. J. 2018, 64, 46–54. [Google Scholar] [CrossRef] [Green Version]
- Sari, D.; Handayani, N.; Ulkhaq, M.; Budiawan, W.; Maharani, D.; Ardi, F. A data envelopment analysis approach for assessing the efficiency of small and mediumsized wood-furniture enterprises: A case study. MATEC Web Conf. 2018, 204, 01015. [Google Scholar] [CrossRef] [Green Version]
- Ma, Y. An Analysis on the Relative Efficiency of Furniture Enterprises in Guangdong Province Based on DEA-BCC and Clustering Method. Open J. Bus. Manag. 2016, 4, 349–354. [Google Scholar] [CrossRef] [Green Version]
- Trigkas, M.; Papadopoulos, I.; Karagouni, G. Economic efficiency of wood and furniture innovation system. Eur. J. Innov. Manag. 2012, 15, 150–176. [Google Scholar] [CrossRef]
- Vahid, S.; Sowlati, T. Efficiency analysis of the Canadian wood-product manufacturing subsectors: A DEA approach. For. Prod. J. 2007, 57, 71–77. [Google Scholar]
- Fotiou, S.I. Efficiency measurement and logistics: An application of DEA in Greek sawmills. In Proceedings of the 1st World Symposium: Logistics in the Forest Sector, Helsinki, Finland, 15–16 May 2000; Sjostrom, K., Ed.; Timber Logistics Club: Helsinki, Finland; pp. 189–203. [Google Scholar]
- Nyrud, A.Q.; Bergseng, E.R. Production efficiency and size in Norwegian sawmilling. Scand. J. For. Res. 2002, 17, 566–575. [Google Scholar] [CrossRef]
- Salehirad, N.; Sowlati, T. Performance analysis of primary wood producers in British Columbia using data envelopment analysis. Can. J. For. Res. 2005, 35, 285–294. [Google Scholar] [CrossRef]
- Delivering the European Green Deal. Available online: https://ec.europa.eu/info/publications/delivering-european-green-deal_en?fbclid=IwAR0gNBZ_5NLkCB2lpnEW4CUKTTBaH_1HCdH2VOn-NMy_ge0NxrXsPL--Ryc.16.7.2021 (accessed on 1 July 2021).
- Coelli, T.; Rahman, S.; Thirtle, C. Technical, Allocative, Cost and Scale Efficiencies in Bangladesh Rice Cultivation: A Non-Parametric Approach. J. Agric. Econ. 2005, 53, 607–626. [Google Scholar] [CrossRef]
- Li, L.; Hao, T.; Chi, T. Evaluation on China’s forestry resources efficiency based on big data. J. Clean. Prod. 2017, 142, 513–523. [Google Scholar] [CrossRef]
- Charnes, A.; Cooper, W.; Golany, B.; Seiford, L.; Stutz, J. Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions. J. Econ. 1985, 30, 91–107. [Google Scholar] [CrossRef]
- Banker, R.D.; Charnes, A.; Cooper, W.W. Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis. Manag. Sci. 1984, 30, 1078–1092. [Google Scholar] [CrossRef] [Green Version]
- Cook, W.D.; Tone, K.; Zhu, J. Data envelopment analysis: Prior to choosing a model. Omega 2014, 44, 1–4. [Google Scholar] [CrossRef]
- Cook, W.D.; Zhu, J. Data Envelopment Analysis: A Handbook of Modeling Internal Structure and Network; Springer: New York, NY, USA, 2014. [Google Scholar]
- Zhu, J. Data Envelopment Analysis. A Handbook of Models and Methods; Springer: New York, NY, USA, 2015. [Google Scholar]
- Chen, Y. Ranking efficient units in DEA. Omega 2004, 32, 213–219. [Google Scholar] [CrossRef]
- Soares de Mello, J.C.; Angulo Meza, L.; da Silveira, J.; Gomes, E. About negative efficiencies in Cross Evaluation BCC input oriented models. Eur. J. Oper. Res. 2013, 229, 732–737. [Google Scholar] [CrossRef]
- Shahverdi, R.; Ebrahimnejad, A. DEA and Malmquist productivity indices for measuring group performance in two periods. Int. J. Ind. Sys. Eng. 2014, 16, 382–395. [Google Scholar] [CrossRef]
- Malmquist, S. Index numbers and indifference surfaces. Trab. Estat. 1953, 4, 209–242. [Google Scholar] [CrossRef]
- Caves, D.W.; Christensen, L.R.; Diewert, W.E. The economic theory of index numbers and the measurement of input, output, and productivity. Econometric 1982, 50, 1393–1414. [Google Scholar] [CrossRef]
- Färe, R.; Grosskopf, S.; Lindgren, B.; Roos, P. Productivity changes in Swedish pharamacies 1980–1989: A non-parametric Malmquist approach. J. Prod. Anal. 1992, 3, 85–101. [Google Scholar] [CrossRef]
- Li, C.; Zhou, Z.; Wu, Y.; Huang, Y.; Cao, G. Is metabolism in all regions of China performing well?—Evidence from a new DEA-Malmquist productivity approach. Ecol. Indic. 2019, 106, 105487. [Google Scholar] [CrossRef]
- NACE Rev. 2. Statistical Classification of Economic Activities in the European Community; Office for Official Publications of the European Communities: Luxembourg, 2008. [Google Scholar]
- Savov, V.; Mihajlova, J.; Yotov, N.; Madjarov, B. Influence of hot-pressing temperature on properties of eco-friendly dry-process fibrebords with lignosulfonate adhesive. Innov. Woodwork. Ind. Eng. Des. 2021, 19, 29–36. [Google Scholar]
- Savov, V.; Valchev, I.; Yavorov, N.; Sabev, K. Influence of press factor and additional thermal treatment on technology for production of eco-friendly MDF based on lignosulfonate adhesives. Bulg. Chem. Com. 2020, 52, 48–52. [Google Scholar] [CrossRef]
- Savov, V.; Mihajlova, J.; Grogorov, R. Selected physical and mechanical properties of combined wood based panels from wood fibres and sawdust. Innov. Woodwork. Ind. Eng. Des. 2019, 2, 42–48. [Google Scholar]
- Meil, J.K.; Singh, B.K.; Nautiyal, J.C. Short-run actual and least-cost productivities of variable inputs for the British Columbia interior softwood lumber industry. For. Sci. 1988, 34, 88–101. [Google Scholar]
- Hernandez-Sancho, F.; Picazo-Tadeo, A.; Reig-Martinez, E. Efficiency and environmental regulation. Environ. Resour. Econ. 2000, 15, 365–378. [Google Scholar] [CrossRef]
- Kao, C.; Hwang, S. Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan. Eur. J. Oper. Res. 2008, 185, 418–429. [Google Scholar] [CrossRef]
- Chen, Y.; Liang, L.; Yong, F. A DEA game model approach to supply chain efficiency. Ann. Oper. Res. 2006, 145, 5–13. [Google Scholar] [CrossRef]
- Doyle, J.; Green, R. Efficiency and cross-efficiency in DEA: Derivations, meanings and uses. J. Oper. Res. Soc. 1994, 45, 567–578. [Google Scholar] [CrossRef]
- Ebrahimi, B.; Tavana, M.; Rahmani, M.; Santos-Arteaga, F.J. Efficiency measurement in data envelopment analysis in the presence of ordinal and interval data. Neural Comput. Appl. 2018, 30, 1971–1982. [Google Scholar] [CrossRef]
- Halalisan, A.F.; Popa, B.; Heras-Saizarbitoria, I.; Ioras, F.; Abrudan, I.V. Drivers, perceived benefits and impacts of FSC Chain of Custody Certification in a challenging sectoral context: The case of Romania. Int. For. Rev. 2019, 21, 195–211. [Google Scholar] [CrossRef] [Green Version]
- Halalisan, A.F.; Abrudan, I.V.; Popa, B. Management Certification in Romania: Motivations and Perceptions. Forests 2018, 9, 425. [Google Scholar] [CrossRef] [Green Version]
- Liu, H.; Yan, X.; Cheng, J.; Zhang, J.; Bu, Y. Driving Factors for the Spatiotemporal Heterogeneity in Technical Efficiency of China’s New Energy Industry. Energies 2021, 14, 4151. [Google Scholar] [CrossRef]
- Liu, R.; He, F.; Ren, J. Promoting or Inhibiting? The Impact of Enterprise Environmental Performance on Economic Performance: Evidence from China’s Large Iron and Steel Enterprises. Sustainability 2021, 13, 6465. [Google Scholar] [CrossRef]
- Lorincova, S.; Schmidtova, J.; Balazova, Z. Perception of the Corporate Culture by Managers and Blue Collar Workers in Slovak Wood-Processing Businesses. Acta Fac. Xylologiae Zvolen 2016, 58, 149–163. [Google Scholar] [CrossRef]
- Leu, J.-D.; Tsai, W.-H.; Fan, M.-N.; Chuang, S. Benchmarking Sustainable Manufacturing: A DEA-Based Method and Application. Energies 2020, 13, 5962. [Google Scholar] [CrossRef]
- Sedliacikova, M.; Strokova, Z.; Klementova, J.; Satanova, A.; Moresova, M. Impacts of Behavioral Aspects on Financial Decision-Making of Owners of Woodworking and Furniture Manufacturing and Trading Enterprises. Acta Fac. Xylologiae Zvolen 2020, 62, 165–176. [Google Scholar] [CrossRef]
- Kropivšek, J.; Grošelj, P. Long-term Financial Analysis of the Slovenian Wood Industry Using DEA. Drv. Ind. 2019, 70, 61–70. [Google Scholar] [CrossRef] [Green Version]
Inputs | 2014 | 2015 | 2016 | 2017 | 2018 | Average | σ |
---|---|---|---|---|---|---|---|
Labour and Materials costs | - | - | |||||
Bulgarian | 0.95 | 0.98 | 0.94 | 0.96 | 0.95 | 0.96 | 0.01 |
Slovak | 0.87 | 0.38 | 0.88 | 0.87 | 0.94 | 0.79 | 0.21 |
Labour and Depreciations | - | - | |||||
Bulgarian | 0.54 | 0.84 | 0.81 | 0.91 | 0.81 | 0.78 | 0.13 |
Slovak | 1.00 | 0.92 | 0.90 | 0.91 | 0.90 | 0.93 | 0.04 |
Labour and Other Costs | - | - | |||||
Bulgarian | 0.54 | 0.56 | 0.53 | 0.55 | 0.52 | 0.54 | 0.01 |
Slovak | 0.98 | 0.98 | 0.96 | 1.00 | 1.00 | 0.98 | 0.01 |
DMU Name, Country | 2014 | 2015 | 2016 | 2017 | 2018 | Average | σ |
---|---|---|---|---|---|---|---|
Kronospan Bulgaria EOOD, BG | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 0.00 |
WELDE Bulgaria AD, BG | 0.85 | 0.92 | 0.83 | 0.84 | 0.87 | 0.86 | 0.03 |
Kastamonu Bulgaria AD, BG | 0.94 | 0.99 | 0.93 | 1.00 | 0.95 | 0.96 | 0.03 |
Coop Obnova, BG | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 0.00 |
Rettenmeier Tatra Timber, LLC, SK | 0.83 | 0.44 | 0.86 | 0.87 | 0.94 | 0.79 | 0.16 |
PRP, LLC, SK | 0.87 | 0.41 | 0.82 | 0.80 | 0.93 | 0.76 | 0.17 |
Kronospan, LLC, SK | 0.93 | 0.49 | 1.00 | 1.00 | 1.00 | 0.88 | 0.18 |
Slovincom, LLC, SK | 0.86 | 0.17 | 0.85 | 0.81 | 0.89 | 0.72 | 0.25 |
DMU Name, Country | 2014 | 2015 | 2016 | 2017 | 2018 | Average | σ |
---|---|---|---|---|---|---|---|
Kronospan Bulgaria EOOD, BG | 1.00 | 1.00 | 1.00 | 1.00 | 0.97 | 0.99 | 0.01 |
WELDE Bulgaria AD, BG | 0.30 | 1.00 | 1.00 | 1.00 | 1.00 | 0.86 | 0.26 |
Kastamonu Bulgaria AD, BG | 0.70 | 0.80 | 0.75 | 1.00 | 0.74 | 0.80 | 0.10 |
Coop Obnova, BG | 0.16 | 0.57 | 0.50 | 0.65 | 0.54 | 0.48 | 0.15 |
Rettenmeier Tatra Timber, LLC, SK | 0.98 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 0.01 |
PRP, LLC, SK | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 0.00 |
Kronospan, LLC, SK | 1.00 | 0.96 | 0.98 | 1.00 | 1.00 | 0.99 | 0.02 |
Slovincom, LLC, SK | 1.00 | 0.72 | 0.63 | 0.65 | 0.62 | 0.72 | 0.13 |
DMU Name, Country | 2014 | 2015 | 2016 | 2017 | 2018 | Average | σ |
---|---|---|---|---|---|---|---|
Kronospan Bulgaria EOOD, BG | 1.00 | 1.00 | 1.00 | 1.00 | 0.97 | 0.99 | 0.01 |
WELDE Bulgaria AD, BG | 0.30 | 0.34 | 0.30 | 0.31 | 0.30 | 0.31 | 0.01 |
Kastamonu Bulgaria AD, BG | 0.70 | 0.71 | 0.67 | 0.72 | 0.64 | 0.69 | 0.03 |
Coop Obnova, BG | 0.16 | 0.18 | 0.16 | 0.18 | 0.18 | 0.17 | 0.01 |
Rettenmeier Tatra Timber, LLC, SK | 1.00 | 1.00 | 1.00 | 0.99 | 1.00 | 1.00 | 0.00 |
PRP, LLC, SK | 0.93 | 0.92 | 0.86 | 1.00 | 1.00 | 0.94 | 0.05 |
Kronospan, LLC, SK | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 0.00 |
Slovincom, LLC, SK | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 0.00 |
Inputs | Labour Costs/Materials Costs | Labour Costs/Depreciations | Labour Costs/Other Costs |
---|---|---|---|
2014 | 0.71 | 0.00 | 0.01 |
2015 | 0.14 | 0.00 | 0.01 |
2016 | 0.92 | 0.00 | 0.04 |
2017 | 1.00 | 0.97 | 0.00 |
2018 | 0.87 | 0.01 | 0.01 |
t-Test p = 0.05, H0: No Differences | ||||
Labour costs/Materials costs | - | - | ||
- | 2015 | 2016 | 2017 | 2018 |
2014 | 0.06 | 0.92 | 0.78 | 0.03 |
2015 | - | 0.07 | 0.049 | 0.048 |
2016 | - | - | 0.74 | 0.04 |
2017 | - | - | - | 0.15 |
Wilcoxon matched-pairs rank sum test, p = 0.05, H0: No differences | ||||
Labour costs/Depreciations | - | - | ||
- | 2015 | 2016 | 2017 | 2018 |
2014 | 0.35 | 0.39 | 0.19 | 0.35 |
2015 | - | 0.22 | 0.37 | 0.19 |
2016 | - | - | 0.048 | 0.88 |
2017 | - | - | - | 0.048 |
Labour costs/Other costs | - | - | ||
- | 2015 | 2016 | 2017 | 2018 |
2014 | 0.25 | 0.16 | 0.12 | 0.99 |
2015 | - | 0.048 | 0.87 | 0.62 |
2016 | - | - | 0.12 | 0.99 |
2017 | - | - | - | 0.25 |
DMU Name, Country | θt | θ(t + 1) | θt + 1(xt; yt) | θt(x(t + 1); y(t + 1)) | TEC | FS | MPI |
---|---|---|---|---|---|---|---|
Kronospan Bulgaria EOOD, BG | 1 | 1 | 1 | 0.996 | 1 | 0.998 | 0.998 |
WELDE Bulgaria AD, BG | 0.85 | 0.87 | 0.903 | 0.814 | 1.024 | 0.938 | 0.96 |
Kastamonu Bulgaria AD, BG | 0.94 | 0.95 | 1 | 1 | 1.011 | 0.995 | 1.005 |
Coop Obnova, BG | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
Rettenmeier Tatra Timber, LLC, SK | 0.83 | 0.94 | 1 | 0.878 | 1.133 | 0.881 | 0.997 |
PRP, LLC, SK | 0.87 | 0.93 | 1 | 0.866 | 1.069 | 0.9 | 0.962 |
Kronospan, LLC, SK | 0.93 | 1 | 1 | 0.91 | 1.075 | 0.92 | 0.989 |
Slovincom, LLC, SK | 0.86 | 0.89 | 0.917 | 0.831 | 1.035 | 0.936 | 0.968 |
Bulgarian, average | 1.009 | 0.983 | 0.991 | ||||
Slovak, average | 1.078 | 0.909 | 0.979 |
DMU Name, Country | θt | θ(t + 1) | θt + 1(xt; yt) | θt(x(t + 1); y(t + 1)) | TEC | FS | MPI |
---|---|---|---|---|---|---|---|
Kronospan Bulgaria EOOD, BG | 1.000 | 0.969 | 1.000 | 0.938 | 0.969 | 0.984 | 0.954 |
WELDE Bulgaria AD, BG | 1.000 | 1.000 | 0.960 | 1.000 | 1.000 | 1.020 | 1.020 |
Kastamonu Bulgaria AD, BG | 1.000 | 0.735 | 1.000 | 0.710 | 0.735 | 0.983 | 0.723 |
Coop Obnova, BG | 0.649 | 0.539 | 0.573 | 0.880 | 0.831 | 1.359 | 1.130 |
Rettenmeier Tatra Timber, LLC, SK | 1.000 | 1.000 | 1.000 | 0.989 | 1.000 | 0.995 | 0.995 |
PRP, LLC, SK | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
Kronospan, LLC, SK | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
Slovincom, LLC, SK | 0.649 | 0.617 | 0.573 | 0.723 | 0.951 | 1.152 | 1.095 |
Bulgarian, average | - | - | - | - | 0.884 | 1.087 | 0.957 |
Slovak, average | - | - | - | - | 0.988 | 1.037 | 1.022 |
DMU Name, Country | θt | θ(t + 1) | θt + 1(xt; yt) | θt(x(t + 1); y(t + 1)) | TEC | FS | MPI |
---|---|---|---|---|---|---|---|
Kronospan Bulgaria EOOD, BG | 1.000 | 1.000 | 1.000 | 0.815 | 1.000 | 0.903 | 0.903 |
WELDE Bulgaria AD, BG | 0.339 | 0.302 | 0.321 | 0.242 | 0.891 | 0.921 | 0.820 |
Kastamonu Bulgaria AD, BG | 0.714 | 0.669 | 0.682 | 0.575 | 0.937 | 0.949 | 0.888 |
Coop Obnova, BG | 0.177 | 0.161 | 0.160 | 0.134 | 0.910 | 0.961 | 0.874 |
Rettenmeier Tatra Timber, LLC, SK | 1.000 | 1.000 | 1.000 | 0.845 | 1.000 | 0.919 | 0.919 |
PRP, LLC, SK | 0.915 | 0.858 | 0.571 | 1.000 | 0.938 | 1.366 | 1.282 |
Kronospan, LLC, SK | 1.000 | 1.000 | 1.000 | 0.810 | 1.000 | 0.900 | 0.900 |
Slovincom, LLC, SK | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
Bulgarian, average | - | - | - | - | 0.934 | 0.933 | 0.871 |
Slovak, average | - | - | - | - | 0.985 | 1.046 | 1.025 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Krišťáková, S.; Neykov, N.; Antov, P.; Sedliačiková, M.; Reh, R.; Halalisan, A.-F.; Hajdúchová, I. Efficiency of Wood-Processing Enterprises—Evaluation Based on DEA and MPI: A Comparison between Slovakia and Bulgaria for the Period 2014–2018. Forests 2021, 12, 1026. https://doi.org/10.3390/f12081026
Krišťáková S, Neykov N, Antov P, Sedliačiková M, Reh R, Halalisan A-F, Hajdúchová I. Efficiency of Wood-Processing Enterprises—Evaluation Based on DEA and MPI: A Comparison between Slovakia and Bulgaria for the Period 2014–2018. Forests. 2021; 12(8):1026. https://doi.org/10.3390/f12081026
Chicago/Turabian StyleKrišťáková, Stanislava, Nikolay Neykov, Petar Antov, Mariana Sedliačiková, Roman Reh, Aureliu-Florin Halalisan, and Iveta Hajdúchová. 2021. "Efficiency of Wood-Processing Enterprises—Evaluation Based on DEA and MPI: A Comparison between Slovakia and Bulgaria for the Period 2014–2018" Forests 12, no. 8: 1026. https://doi.org/10.3390/f12081026
APA StyleKrišťáková, S., Neykov, N., Antov, P., Sedliačiková, M., Reh, R., Halalisan, A.-F., & Hajdúchová, I. (2021). Efficiency of Wood-Processing Enterprises—Evaluation Based on DEA and MPI: A Comparison between Slovakia and Bulgaria for the Period 2014–2018. Forests, 12(8), 1026. https://doi.org/10.3390/f12081026