Discussion of Methods Involved
The ICRAM-1 uses the Analytical Hierarchy Process
(AHP) to analyze the hierarchy of risk indicators within
each level and to determine the relative importance of
the risk indicators by establishing priority among the criteria,
subcriteria, and indicators. This analysis was important
since all the indicators in a particular level might
not have the same degree of significance with respect to
the project, market, and country under consideration.
The hierarchy of risk indicators is systematically evaluated
by using a series of matrix computations to determine
the decision maker’s preference order among the
various criteria. For additional information on the application
of AHP, refer to Hastak (1998); Hastak and Halpin
(1998); Saaty (1980; 1982; and 1990); and Vargas
(1990).
The risk associated with each indicator is subjectively
established by the primary decision maker (PDM) by using a predetermined scale of 0–100, where 0 implies
no risk and 100 implies maximum risk (Table 4). In the
relative scale shown in Table 4, the risk is defined as a
function of the probability of the event and the associated
severity (loss), where high, medium, and low severity
are defined by the user based on the risk-taking
capacity of the user firm. The determination of risk associated
with each indicator (that is, the probability and
severity) is based on the available information about the
country/market/project and the knowledge of the user.
The risk values are estimated by using the predetermined
scale, as shown in Table 4. The subjective risk assessment
and weight associated with the indicators (established
earlier using the AHP) together provide the
weighted aggregate risk for a particular level.
The subjectivity of risk assessment is reduced as more
information about the risk indicators is available to the
user. Since the model relies on subjective assessment of
risk indicators, it is important that the user provide input
based on reliable sources of information and his or her
own judgment. Presently, the ICRAM-1 allows one user
at a time to work with the model and provide input.
However, future development of this model will include
a group decision module for synthesizing the input and
observations provided by a team of experts evaluating
the situation.
The ICRAM-1 takes into account the transfer of risk
between levels. The user identifies the indicators that
could be affected by an upper-level risk environment.
The transfer of risk from one level to the affected indicators
at the next lower level is established by using a
modification of the Pair Wise Comparison (PWC)
method (Ahmad 1990). In the PWC method, two indicators
are compared at a time to determine their relative
importance with respect to the impacting level. The results
of the pairwise comparisons are subsequently normalized
for all the indicators under consideration.
The PWC method was modified slightly to account
for modeling assumptions (4) and (5) discussed earlier.
According to these assumptions, all the indicators directly
impacted by an upper level are uniquely impacted
by that level and cannot be assessed a risk value greater
than the degree of risk associated with the impacting
level. Therefore, instead of normalizing the comparison
results (as required by the PWC method), the weights
are modified by dividing them with the maximum weight
obtained by any of the selected indicators. The indicator
with the maximum weight is assigned the full risk impact
of the previous level, whereas the other selected
indicators are assigned risk according to their modified
weights. Additionally, a relative scale for the ‘‘degree of
impact,’’ giving the assessment for each, was developed
for the PWC evaluations and is shown below.
• Much more impacted: 1.5
• More impacted: 1.25
• Same impact: 1.0
• Less impact: 1/1.25 = 0.8
• Much less impact: 1/1.5 = 0.67
To obtain the aggregate risk at a particular level, the
risk transferred from a previous level (macro or both
macro and market) is combined with the weighted risk
assessed for that level. The following paragraphs illustrate
the methodology in detail