Abstract
ABSTRACTData envelopment analysis (DEA), a non-parametric performance measurement approach, is used to measure the relative operational efficiency of logging contractors. An existing cost and productivity benchmarking dataset was used that contains system, stand and terrain factors with over 1000 unique entries on forest harvest operations in New Zealand from 2009 to 2015. Five input factors, number of harvest days, number of machines, total harvest area, number of log sorts, and total volume of timber accounted for 77.1% variation in the production output and are used in the DEA. Output-orientation under the assumption of constant, and variable returns to scale are used to estimate the performance of the logging contractors. The results indicate that the majority of the logging contractors are operating at or near scale efficiency level, and the main source of inefficiency in the industry is both technical and managerial. Analysis shows that if all inefficient contractors operate at optimal input and output levels, on an average, system productivity could increase by 52.2% from 28.7 to 52.2 tons/SMH. The DEA suggests that investment in technology and human capital could improve the overall efficiency of the logging industry.
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