Elimination by aspects

Submitted by Sukaina Bharwani | published 25th Mar 2011 | last updated 10th Dec 2014

While pilot knowledge elicitation tools (KnETs) attempt to classify important knowledge attributes of the domain, there may exist several (conscious and unconscious) phases of decision-making before a final decision is reached.

In their article on the decision-making of people purchasing a vehicle, Gladwin and Murtaugh (1980) write that people dismiss large categories of automobile before beginning to compare cars for the features that they desire. Murtaugh and Gladwin (1980) refer to this phase as the 'preattentive phase' to emphasise that though purposive, these decisions are not always conscious, while in a later article, Gladwin (1983) identifies this as the 'elimination by aspects' phase.

Clearly, this is an important dimension of the decision making process, though Werner and Schoepfle (1987) warn that the possible lack of consciousness of the actor, when performing this level of decision-making, may produce inconsistencies, once the actor is made distinctly aware of them.

However, McGregor writes that models developed using 'elimination by aspects' methodology have predicted better than 80% of decisions by farmers not included in samples used to develop the models. This involves identifying people with contrasting behaviour but the same belief and finding the reason for the difference (McGregor et al., 2001).

Murray-Prior (1998) has taken Gladwin's methodology one step further and incorporated it into a Personal Construct Theory framework allowing for the simplification of the decision making process with descriptive and predictive capabilities, by the faster identification of superordinate, subordinate and associated constructs. Murray-Prior's original work (1994) focused on wool producers in Australia and revealed that price and attitude to risk were important factors in all decisions. The main contribution of this approach was in understanding how farmers' decision making was affected by changes in prices and why they reacted in the way they did.

For example, farmers in the Australian wool industry interviewed by Murray-Prior (1994) seemed to ignore a great deal of information about changes in relative prices, either unconsciously or as a deliberate strategy. In the longer term they had little confidence in predictions regarding prices and preferred to rely on their own experience. Farmers tended to operate on criteria whereby prices existed in binary on/off states, that is they were either 'high' or 'low', rather than perceiving them as part of a continuous adjustment process. Therefore, price response was much less than might be expected from classical economic theory due to the strategic view taken by many farmers, which was dependent on their own personal goals and an understanding of the context in which they operated. McGregor et al. (2001) cite Murray-Prior's results (1994) as an example of the value of using anthropological and psychological methodologies to provide alternative and perhaps more insightful perspectives on farmer decision making.

Other decision-making methods

Analytic Hierarchy Process (AHP), has been successfully used in many adaptation and mitigation contexts (Bharwani et al., 2013, Varela-Ortega et al., 2014). It offers an alternative to full multi-criteria decision analysis with low data and resource requirements, yet is appropriate for evaluation of options in situations of high complexity, considering different time horizons, uncertainty and multiple and interdependent variables requiring multi-dimensional trade-offs.

Further resources

Bharwani, S., C. Varela-Ortega, I. Blanco, P. Esteve, E. Juarez, G. Trombi, M. Moriondo, M. Bindi, T. Devisscher, R. Taylor and P. Watkiss, 2013: Analytic Hierarchy Process (AHP). Decision Support Methods for Adaptation. MEDIATION Project Briefing Note 7.

Gladwin, C. H. (1983). Contributions of decision-tree methodology to a farming systems program. Human Organization, 42(2):146-157.

McGregor, M., Rola-Rubzen, F., and Murray-Prior, R. (2001). Micro and macro-level approaches to modelling decision making. Agricultural Systems (69), 63-83.

Murray-Prior, R.B. (1994). Modelling Decisions of Wool Producers: Hierarchical Decision Models and Personal Construct Theory, unpublished PhD thesis, University of New England, Armidale, NSW.

Murray-Prior, R. (1998). Modelling farmer behaviour: A personal construct theory interpretation of hierarchical decision models. Agricultural Systems, 57(4):541-556.

Murtaugh, M. and Gladwin, H. (1980). A hierarchical decision-process model for forecasting automobile type - choice automobile
choice and its energy-implications. Special Issue of Transportation Research.

Varela-Ortega, C., Blanco-Gutiérrez, I., Esteve, P., Bharwani, S., Fronzek, S. and Downing, T. E. (2014). How can irrigated agriculture adapt to climate change? Insights from the Guadiana Basin in Spain. Regional Environmental Change, . DOI:10.1007/s10113-014-0720-y.