A computer system supporting agricultural machinery and farm tractor purchase decisions

Heliyon. 2020 Oct 3;6(10):e05039. doi: 10.1016/j.heliyon.2020.e05039. eCollection 2020 Oct.

Abstract

Operational research, i.e. searching for optimal solutions in a situation of uncertainty and risk, can also be used to support decisions to purchase expensive agricultural machinery. Although Polish farmers receive subsidies from the EU, it does not mean they do not need to make well-thought-out purchases, because wrong purchase decisions will have long-term consequences while using machinery. The article presents the results of the IFOP - the system which has been available on the Internet for several years. It collects data on farming machinery and vehicles based on users' voluntary but subjective opinions. The authors of this article developed an original multi-criteria method of evaluating the quality of these specific products, which enabled them to make relevant rankings of brands. It is an algorithmic-heuristic method, which uses pairwise comparison tools to determine the significance ratios of the criteria. This article presents the results of the 1st and 2nd IFOP edition (Race Ranking), which included several dozen brands of tractors registered in Poland. More than fifty qualitative (Q) and non-qualitative (C) traits of farm tractors were taken into account. According to Polish farmers, Valtra - a Finnish brand of farm tractors, part of the AGCO concern, was the most versatile (Q = 4.39 and Q&C = 4.23). These tractors received the best opinions for their functionality, durability, ergonomics and safety.

Keywords: Agricultural engineering; Agricultural machinery and vehicles; Agricultural science; Agricultural technology; Information science; Inherent traits; MCDA; Mechanical systems; Operational research; Quality; Quality/price ratio; Quantification; Systems engineering.