HVMSHenson Valley Montessori School (Upper Marlboro, MD)
HVMSHidden Valley Middle School (Roanoke, VA)
HVMSHellenic Veterinary Medical Society (Greece)
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The next step consists in identifying amongst all the relations, those that will compose the hierarchical value map (HVM).
Women's HVM presents relationships that were highlighted in the men's HVM, as the benefit of being up to date with fashion trends and a higher purpose of life that is to be admired (43%), besides the relationship between pleasure and gratification with the life project professional and financial success (43%).
Another observation from the HVM was the strong links between interactions, teamwork and the resulting value of warm relationships with others, which shows that as the participants work through the course they form close friendships with each other.
Reynolds and Gutman (1988) present a straightforward decision rule for determining what associations should be illustrated in an HVM. Each association is compared with a cutoff level.
After the implication matrix is constructed, a cutoff value is selected by the analyst to determine which connections should be represented on the HVM. To assist the analyst in making this decision, a bar chart is provided on screen by the software to show how much variance would be explained by different levels of cutoff values (see Figure 3).
Interestingly, the total number of 1s accounted for in the HVM which is reported can be considered a measure of the representativeness of the solution.
After the data is analyzed to determine exactly which associations should be illustrated as connections on the HVM, the final stage of producing an HVM must be performed.
The algorithm discussed in Stage C only determines what connections should be made, but does not actually indicate where nodes should be placed to draw an intelligible HVM. Gengler and Reynolds (1989) presented a heuristic-based algorithm and interactive editing software which can aid analysts in drawing an HVM derived from the binary matrix.
In sum, the construction of an HVM from raw laddering data involves several stages of both quantifiable and nonquantifiable analysis.
The resultant HVM from an analysis of the dog food category is shown in Figure 3, with verbatim examples nested under each code.
The HVM can be divided into three fairly distinct levels corresponding to the a/c/v codes.
These links are actually the key to understanding and using an HVM. This is true for two reasons.