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Unformatted text preview: beyond, while being constrained by, what
is more firmly known which are subject to retraction when, and if, they conflict with
new evidence, or with lines of reasoning supported by other assumptions (Cohen,
1989). Using assumption-based reasoning, experienced decision-makers can act quickly and efficiently within their domain of expertise with very little information
(Lipshitz and Ben Shaul, 1997). Scenario planning, imagining possible future
15 developments in script-like fashion (Schoemaker, 1995), is another strategy of
reducing risk and uncertainty that combines prediction and assumption-based
reasoning. Finally, risk and uncertainty can also be reduced by improving predictability through shortening time horizons (preferring short-term to long-term
goals, and short-term feedback to long range planning, Cyert and March, 1963), by
selling risks to other parties (Hirst and Schweitzer, 1990), and by selecting one of the
many possible interpretations of equivocal information (Weick, 1979).
It is important to recognise, however, that reducing risk and uncertainty by collecting
information can be problematic since often the information is ambiguous or
misleading to the point of being worthless (Hammond et al, 1999; Morgan and
Henrion, 1990; Feldman and March, 1981; Grandori, 1984; Wohstetter, 1962).
Moreover, there is evidence to suggest that collecting information does not help the
decision quality when the level of environmental uncertainty is very high (Fredrickson
and Mitchell, 1984). This leads some to adopt an entirely different approach to
reducing risk and uncertainty by controlling the sources of variability that decrease
predictability. For example, as discussed above, according to Allaire and Firsitrotu
(1989), some organisations use “power responses” (Lipshitz and Strauss, 1997).
It is the second stage of the R.Q.P. heuristic that much of the decision theory literature
discusses (for example, Clemen and Kwit, 2000; Hammond et al., 1999; Clemen,
1999; Thomas and Samson, 1986; Keeney, 1979; Kaufman and Thomas, 1977; Raiffa,
1968). Decision analysis (Raiffa, 1968; Howard, 1968; Raiffa and Schlaifer, 1961) is
a normative discipline within decision theory consisting of various techniques and
concepts that provide a comprehensive way to evaluate and compare the degree of
risk and uncertainty associated with investment choices (Newendorp, 1996).
Traditional methods of analysing decision options involve only cash flow
considerations, such as computation of an average rate of return (Newendorp, 1996).
The new dimension that is added to the decision process with decision analysis is the
quantitative consideration of risk and uncertainty (Clemen and Kwit, 2000; Clemen,
1999; Newendorp, 1996; Goodwin and Wright, 1991; Morgan and Henrion, 1990;
French, 1989; Raiffa, 1968; Howard, 1968; Raiffa and Schlaifer, 1961). In Chapter 5,
all aspects of decision analysis will be discussed in detail and specific techniques will
be reviewed. However, for the purposes of gaining an ov...
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This document was uploaded on 03/30/2014.
- Summer '14
- The Land