Schmidt Mike

A Proposal for an Integrated Methodological and Scientific Approach to Cost Used Forestry Machines

volume: 42, issue:

This paper offers a conceptual analysis of the unaccounted-for cost of owning and operating used machines from an operational, financial and market perspective. It is based on input from experts and a literature review. In the scientific literature, assessing the operating cost of used machines in forest operations is typically based on standard cost assessment methods using costing/pricing input from similar unused machines. This is the case since there are usually no historical data for observed used machines available to analyze. This substitute analysis is problematic to many used and depreciated machines owners. The changing trends in forest technology attest that old machinery do not hold to the same input cost data variables or values of new machines. In fact, they belong to two rather competing different markets: (used vs. new equipment markets). With the technological, market and machinery regulations and dynamic changes, the substitute cost analysis is not representative. Better data is required to understand the cost of owning and operating used machines and the justification is the focal point of this paper. The outcome of the expert and literature analysis in this paper demonstrates that a broader understanding of the cost of a used machine is required and doable. A proposed understanding integrates the machine availability (performance), cost factors (financial) and market evaluation (price), in isolation (single piece of machine) as well as in a fleet, to assess a used machine ownership cost. The study is intended to offer forest machine operators, owners, scientists, and practitioners a proposed new approach to value used machines and further investigations and data inputs required to make used machines costing methods more relevant.


Web of Science Impact factor (2019): 2.500
Five-years impact factor: 2.077

Quartile: Q1 - Forestry

Subject area

Agricultural and Biological Sciences