Abstract
This study aims at exploring the technical efficiency of lumber industry in northwestern Ontario, Canada using data envelopment analysis (DEA). The DEA model analyzes relative technical efficiency of lumber mills with disproportionate inputs and outputs by dividing the 10-year time series data, for inputs and outputs of 24 lumber mills, over two periods (1999–2003 and 2004–2008). Four inputs, namely, material (log volume), labour (man-hours), two types of energy (hog-fuel and electricity), and one output (lumber volume) are used in this study. The trend analysis shows an annual reduction of 10%, 13% and 13% for lumber output, log consumption (input) and number of employees, respectively, during the period 1999–2008. The results from DEA with two scenarios with energy inputs and without energy inputs, for the two periods are found to be mixed and interesting. While some mills have improved their performance in terms of best use of available scarce inputs in the second period, some have shown negative per cent change in efficiency. In the with energy input and the without energy input scenario, some of the mills show a reduction in efficiency in the second period from the first period, with the highest estimated reductions of −13.9% and −47.6%, respectively. A possible explanation for these negative performances of mills in the latter period is the decline in production in the second period compared to the first period, where these mills were not able to adjust their inputs (mostly labour) as proportional lay-offs might not have been possible. These results provide policy makers and industry stakeholders with an improved understanding of the trends of efficiency and employment as well as reallocation opportunities of future inputs in order to increase benefits from this sector.
Similar content being viewed by others
References
Ali AI, Seiford LM. 1993. The mathematical programming approach to efficiency analysis. In: Fried, Lovell, and Schmidt (eds.), The measurement of productive efficiency. Oxford, U.K.: Oxford University Press, pp. 120–159.
Andersen P, Petersen NC. 1993. A procedure for ranking efficient units in Data Envelopment Analysis. Management Science, 39: 1261–1264.
Banker RD, Morey RC. 1986. Efficiency analysis for exogenously fixed inputs and outputs. Operations Research, 34: 513–521.
Banker RR, Charnes A, Cooper WW. 1984. Some models for estimating technical and scale efficiencies in data envelopment analysis. Management Science, 30: 1078–1092.
Brendt ER, Wood DO. 1975. Technology, prices, and the derived demand for energy. Reveiw of Economics and Statisitics, 57: 259–267.
Buongiorno J, Gilless JK. 1980. Effects of input costs, economies of scale, and technological change on international pulp and paper prices. Forest Science, 26: 261–275.
Byrnes P, Färe R, Grosskopf S. 1984. Measuring productive efficiency, an application to Illinois strip mines. Management Science, 30: 671–681.
Charnes A, Cooper WW, Lewin AY, Seiford LM. 1994. Data envelopment analysis: The theory, methodology and applications. Kluwer Academic Publishers, Boston, MA.
Charnes A, Cooper WW, Rhodes E 1978. Measuring the efficiency of decision making units. European Journal of Operational Research, 2:429–444.
Christensen LR, Jorgenson DW. 1969. The measurement of U.S.real capital input, 1929–1967. Review of Income and Wealth (December), 293–320.
CIEEDAC (Canadian Industrial Energy End-use Data and Analysis Centre). 2010. A Review of Energy Consumption and Related Data in the Canadian Wood Products Industry: 1990, 1995 to 2008. A Report for Canadian Industry Program for Energy Conservation Forest Products Association of Canada. Simon Fraser University, Vancouver, BC.
Constantino LF, Townsend GW. 1986. Modelling short run producer behaviour as an operating rate decision: The Canaian sawmilling and pulp and paper industries. Forestry Economics and Policy Analysis Project, University of B.C. Report 86-10.
CSLS (Centre for the Study of Living Standards). 2003. An Analysis of Productivity Trends in the Forest Products Sector in Canada. A report prepared for the Forest Products Association of Canada by the Centre for the Study of Living Standards. CSLS Report 2003-1. Ottawa, Canada.
Denny M, Fuss M, Waverman L. 1981. The measurement and interpretation of total factor productivity in regulated industries, with an application to Canadian telecommunications. In: productivity measurement in regulated industries. Edited by Thomas G. Cowing and Rodney E. Stevenson. New York: Academic Press, pp.179–218.
Dyson RG, Allen R, Camanho AS, Podinovski VV, Sarrico CS, Shale EA. 2001. Pitfalls and protocols in DEA. European Journal of Operational Research, 132: 245–259.
Farrell MJ. 1957. The measurement of productive efficiency. Journal of Royal Statistical Society, Series A, General, 120: 253–281.
Kant S, Nautiyal JC. 1997. Production structure, factor substitution, technical change, and total factor productivity in the Canadian logging industry. Canadian Journal of Forest Research, 27: 701–710.
Kao C. 2000. Measuring the performance improvement of Taiwan forest after reorganization. Forest Science, 46: 577–584.
LLT (Living Legacy Trust). 2003. Ontario’s Value-Added wood products market potential in the U.S. great lakes states. A report prepared by Woodbridge Associates Inc. West Vancouver, BC.
Lovell CAK. 1993. Production frontiers and productive efficiency. In: Fried, Lovell, and Schmidt (eds.), The measurement of productive efficiency. Oxford, U.K: Oxford University Press, p. 428.
Lovell CAK. 1994. Linear programming approaches to the measurement and analysis of productive efficiency. Top, 2:175–248.
Manning G, Thorburn G. 1971. Capital deepening and technological change: the Canadian pulp and paper industry. Canadian Journal of Forest Research, 1: 159–166.
Martinello F. 1985. Input substitution, technological change, and returns to scale in Canadian forest industries. Canadian Journal of Forest Research, 15: 1116–1124.
Martinello F. 1987. Substitution, technological change, and returns to scale in B.C. wood products industries. Applied Economics, 19: 483–496.
Ministry of Natural Resources. 2009. Ontario’s Forests. Ministry of Natural Resources. Avaliable at: http://www.mnr.gov.on.ca/241215.pdf [Accessed on June 26, 2009]
Nanang DM, Ghebremichael A. 2006. Inter-regional comparisons of production technology in Canada’s timber harvesting industries. Forest Policy and Economics, 8:797–810.
Natural Resources Canada. 2012. Key Facts. Available at: http://cfs.nrcan.gc.ca/pages/242. [Accessed on October, 2012].
Nautiyal JC, Singh BK. 1985. Production structure and derived demand for factor inputs in the Canadian lumber industry. Forest Science, 31: 871–881.
OMNR (Ontario Ministry of Natural Resources). 2005. Ontario’s Forest Industry Facility (Mill) Statistics 1999 to 2003. OMNR, Ontario, Canada.
OMNR (Ontario Ministry of Natural Resources). 2010. Ontario’s Forest Industry Facility (Mill) Statistics 1999 to 2010. Unpublished data set provided by OMNR, Ontario, Canada.
OMNR (Ontario Ministry of Natural Resources). 2012. Forest Industry at a Glance. Available at: http://www.mnr.gov.on.ca/en/Business/Forests/2ColumnSubPage/STDPROD_091539.html. [Accessed on October 24. 2012].
Ontario Ministry of Energy (OME). 2006. An Assessment of the Viability of Exploiting Bio-Energy Resources Accessible to the Atikokan Generating Station in Northwestern Ontario. A consultancy report prepared by Forest BioProducts Inc. Sault Ste. Marie, Ontario, Canada.
Rao PS, Preston RS. 1983. Inter-factor substitution and total factor productivity growth. Economic Council Canada, Ottawa. Discussion paper 242.
Sexton TR, Silkman RH, Hogan AJ. 1986. Data envelopment analysis: critique and extensions. New Directions for Program Evaluation, no.32: 73–105.
Shahi C; Upadhyay TP; Pulkki R; Leitch M. 2011. Comparative analysis of the production technologies of logging, sawmill, pulp and paper, and veneer and plywood industries in Ontario. Canadian Journal of Forest Research, 41: 621–631.
Sherif F. 1983. Derived demand of inputs of production in the pulp and paper industry. Forest Products Journal, 33: 45–49.
Singh BK, Nautiyal JC. 1986. A comparison of observed and long run productivity of and demand for inputs in the Canadian lumber industry. Canadian Journal of Forest Research, 16: 443–455.
Smith P. 1997. Model misspecification in data envelopment analysis. Annals of Operations Research, 73: 233–252.
Stier J. 1980. Estimating the production technology in the U.S. lumber industries. Forest Science, 26:471–484.
Vittala EJ, Hänninen H. 1998. Measuring the efficiency of non-profit forestry organizations. Forest Science, 44: 298–307.
Woodland AD. 1975. Substitution of structures, equipment, and labour in Canadian production. International Economic Review, 16: 171–187.
Yin RS. 1998. DEA: A new methodology for evaluating the performance of forest products producers. Forest Product Journal, 48: 29–34.
Yin RS. 2000. Alternative measurements of productive efficiency in the global bleached softwood pulp sector. Forest Science, 46: 558–569.
Author information
Authors and Affiliations
Corresponding author
Additional information
Foundation project: This research work is a part of broad project, ‘Lakehead University-FPInnovations-Forintek Division: Partnership Development.
Rights and permissions
About this article
Cite this article
Upadhyay, T.P., Shahi, C., Leitch, M. et al. An application of data envelopment analysis to investigate the efficiency of lumber industry in northwestern Ontario, Canada. Journal of Forestry Research 23, 675–684 (2012). https://doi.org/10.1007/s11676-012-0309-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11676-012-0309-6