Farmer movement concept map
Answers
Explanation:
reality such as profit and costs; objectives represent directions of improvement or preference such as maximizing profitability; and criteria are a general term that expresses attributes, objectives, and goals.) Although many variations of the methodology have been applied to agricultural and natural resource management (Hayashi, 1999; Hayashi, 2000b), there are two basic types. One is the compensatory approach, which aggregates multiple attributes into overall values by, for example, multiattribute value (utility) functions in which the concept of tradeoffs plays a crucial role. The other is the non-compensatory or outranking approach, which introduces aggregation procedures based on concordance and discordance concepts that are derived from outranking relations, which express that an alternative is at least as good as another one. The distance-based approach such as compromise programming, in which the distance between the ideal point and the alternatives is minimized, can also be applicable to the decisions. Table 1 summarizes the evaluation examples of farming practices by multicriteria analysis. One of the main features in these applications is that attention is paid to the tradeoffs between economic objectives and environmental objectives except for Arondel and Girardin (2000). That is, most of the problems can be expressed hierar- chically as depicted in Figure 1. Agricultural practices are evaluated from the view- point of profitability and environmental quality of soil and water. Although this hierarchical representation of criteria will be useful by itself especially for understanding evaluation problems, it is necessary to elicit attribute weights, parameters to determine tradeoff rates between criteria. Weights elicited from decision makers are combined with the values of attribute levels in order to derive overall values for alternatives, which are used for comparing the performance of each alternative. As a concept used for adjusting a balance between criteria, importance weights are used in many studies. There are, however, difficulties in weighting. The most serious difficulty is that the meaning of weights based on the relative importance of attributes is ambiguous. Moreover, the weights based on importance judgments may distort re- scaling of single-attribute value functions. It is a well-known result that weight elicitation methods without relying on attribute ranges might lead to biased weights (von Nitzsch and Weber, 1993; Fischer, 1995). Because of the difficulty, weighting steps are referred to as “optional element” in ISO 14042 (2000), although weighting is recognized as a crucial part of LCA (Goedkoop, Effting and Collignon, 2000). The other is swing weighting, in which the best and the worst attribute levels are ref- erenced and direct numerical estimation is used for weighting (von Winterfeldt and Edwards, 1986). These weighting methods can be expected to provide us proper weights for attributes. Unfortunately, there is another difficulty, even if we have the theoretically sound procedures for measuring appropriate weights. For example, attribute weights for raw data such as nitrate levels in groundwater are in general difficult to understand for decision makers and even for experts as compared with the case of the tradeoffs between a salary and a vacation in a job decision. Moreover, if raw data are used as attributes, the number of criteria will increase. This means the problems in the real world tend to have a considerable number of attributes. Consequently, we have to measure huge numbers of weights that may be beyond human cognitive ability. Indeed, the difficulty in weighting when a problem has 10 attributes or more is pointed out in LCA (Goedkoop, Effting and Collignon, 2000). Therefore, it is necessary to introduce a methodology for transforming the data into the other values so that the meaning is easy to grasp. This is especially true for societal decision making because without introducing understandable measures into evaluation processes, differences in perceptions are not settled. In the next section, a mapping method is used to conceptually reduce the number of attributes. Then, the current state of understanding on health and ecological risks is outlined to recognize the possibility of aggregating attributes by the concept of risks. As a method to clarify how the attributes used for evaluating farming practices are transposed into two basic risk concepts – health risks and ecological risks, a mapping method (a concept map) is used because it can graphically represent the complex relations among actions, phenomena, and concepts. Figure 2 shows an example of a concept map. This figure illustrates that the practices such as fertilizer application cause many effects on the environment.