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Including Exogenous Factors in the Evaluation of Harvesting Crew Technical Efficiency using a Multi-Step Data Envelopment Analysis Procedure

Copyright © 2017 by Croatian Journal of Forest Engineering
volume: 39, issue: 2
pp: 10
Author(s):
  • Obi Okey Francis
  • Visser Rien
Article category:
Original scientific paper
Keywords:
data envelopment analysis, operating environment, forest harvesting, performance evaluation

Abstract

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The performance of a harvesting crew in terms of its ability to transform inputs into outputs
is influenced by discretionary factors within the unit’s control, such as the selection of machines
and operators. However, factors associated with the operating environment, such as
terrain slope and tree size that are outside the direct control of management, can also influence
harvesting system efficiency. Using data on forest harvesting operations in New Zealand, this
paper applies an established four-stage Data Envelopment Analysis (DEA) procedure to estimate
the managerial efficiency of independent forest harvesting contractors, while taking into
account the influence of the operating environment. The performance of 67 harvesting contractors
is evaluated using seven inputs, one output (system productivity) and three operating
environment factors in an input-oriented, variable return to scale DEA. The results show that
the operating environment including terrain slope, log sorts and piece size influence the efficient
use of inputs by harvesting contractors. A significant difference is observed between the
mean managerial efficiency of the crews before and after controlling for the influence of the
operating environment, the latter being higher by 11%. This study provides evidence that
without accounting for the influence of the operating environment, the resulting DEA efficiency
estimates will be biased; the performance of crews in favourable operating environment
would be overestimated and those in unfavourable environment underestimated.

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Web of Science Impact factor (2017): 1.714
Five-years impact factor: 1.775
Next issue: January 2019

Subject area

Agricultural and Biological Sciences

Category/Quartile

Forestry/Q1