Let us consider the Analytic Hierarchy Process in which the labels are structured as graded numbers. To obtain the scoring that corresponds to the best alternative, or the ranking of the alternatives, we need to use a total order for the graded numbers involved in the problem. In this article, we co
The sensitivity of the analytic hierarchy process to alternative scale and cue presentations
โ Scribed by Sally A. Webber; Barbara Apostolou; John M. Hassell
- Publisher
- Elsevier Science
- Year
- 1997
- Tongue
- English
- Weight
- 775 KB
- Volume
- 96
- Category
- Article
- ISSN
- 0377-2217
No coin nor oath required. For personal study only.
โฆ Synopsis
The Analytic Hierarchy Process (AHP) has gained prominence in the accounting literature as a method to model the decisions of experts. Also, the AHP is used to help individuals structure decisions. AHP researchers have several choices when constructing AHP instruments that elicit judgments from participants; however, little guidance is available regarding the 'best' choice. In particular, the AHP response scale can be numerical, verbal, or graphical. Paired comparisons can be presented in a random or nonrandom format, or in a top-down or bottom-up order. This paper reports the results of three related experiments investigating whether differences in the scale used or the format order of paired comparisons yields significant differences in the AHP models.
The results offer some evidence that the scale used is associated with different AHP models. Also, some evidence is provided that the random versus nonrandom format of the paired-comparison presentation is associated with different AHP models. However, the results for the scale and format effects are not evident across all experiments.
๐ SIMILAR VOLUMES
This study compares alternative preference elicitation methods that are currently available in software implementations of the analytic hierarchy process. For the simple problem used in this study, the elicitation methods may be sorted from least to most accurate as follows: (1) direct estimation, (