the business alternative 1 is suggested.
Key-words: uncertainty, Wald’s, Hurwicz’s, Maximax, Savage’s and Laplace’s criterion, decision support
system, agriculture
INTRODUCTION
Typically, personal and professional decisions can be made with some difficulty. Either the best
course of action is clear or the varieties of the decision are not significant enough to require a great
amount of attention. Occasionally, decisions arise where the path is not clear and it is necessary to
take substantial time and effort in devising a systematic method of analyzing the various courses of
action. With decisions under uncertainty, the decision maker should:
1. Take an inventory of all viable options available for gathering information, for experimentation
and for action
2. List all events that may occur
3. Arrange all pertinent information and choices/assumptions made
4. Rank the consequences resulting from the various courses of action
5. Determine the probability of an uncertain event occurring.
Upon systematically describing the problem and recording all necessary data, judgments, and
preferences, the decision maker should synthesize the information set before using the most
appropriate decision rules. Decision rules prescribe how an individual faced with a decision under
uncertainty should go about choosing a course of action consistent with the individual’s basic
judgments
and
preferences
(http://terpconnect.umd.edu/~sandborn/courses/808S_projects/reynolds.html).
When a decision maker should choose one possible actions, the ultimate consequences of some, if not
all of these actions will generally depend on uncertain events and future actions extending indefinitely
far into the future. The uncertainty is specially expressed in agriculture. Sahin et al. (2008) determine
the cattle fattening breed, which maximizes the net profit for the producers under risk and
uncertainties. The Wald’s, Hurwicz’s, Maximax, Savage’s, Laplace’s and Utility criterions were used.
On the other hand the decision on which crops to include in crop rotation is one of the most important
decisions in field crop farm management. Agronomic, economic
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DSc. Karmen Pažek. Assist. Prof. and DSc. Črtomir Rozman, Assist. Prof. - University of Maribor, Faculty of
Agriculture and Life Sciences, Pivola 10, 2311 Hoče, Slovenia; e-mail: karmen.pazek@uni-mb.si
and market information about each individual crop constitutes an informative basis for decision-
making. There is a significant amount of valuable agronomic and market information already available
on main crop production, including oil crops (Rozman et al., 2006). However, the potential for a wider
range of alternative crops, including oil pumpkin (Bavec and Bavec, 2006), should be evaluated in
order to determine their break-crop characteristics and the benefits and challenges which they bring to
systems (Robson et al., 2002). According to Lampkin and Measures (1999), the economics of oil
pumpkin depends on market price, therefore enquires with potential buyers should be undertaken.
However, recent farm management research has also shown oil pumpkin production can be financially
feasible assuming that the pumpkin oil can be successfully sold. Pažek (2003) and Pažek et al. (2005)
conducted a financial and economical analysis of farm product processing on Slovene farms using a
simulation - modelling approach that included also pumpkin oil production. In agriculture there is a
lack of studies that observe the application of criteria in the situation under uncertainness. From this
reason in the paper five decision rules (criteria) commonly used in decision process under uncertainty
were presented and applied in the case study of production and processing of oil pumpkin:
Wald’s Maximin criterion
Hurwicz’s criterion
Maximax criterion
Savage’s minimax regret criterion
Laplace’s insufficient reason criterion.
The paper is organized as follows; in the first part the methodology and theoretical background of the
decision rules (criteria) is presented. In the second part of the paper the application of observed
decision rules were presented on the example in agriculture; pumpkin oil processing (considering
production area and specific selling presumption by pumpkin oil marketing). The paper is concluded
with results by the observed criteria in the conditions of uncertainty in agriculture.
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