Abstract
Robotic process automation (RPA) is a core software technology for automating digital tasks quickly and reliably and for enabling enterprise automation to execute business processes with speed and accuracy. Evaluation of RPA technologies is a muti-criteria decision making (MCDM) problem including many intangible criteria whose values are generally vague and imprecise. Spherical fuzzy sets (SFS) is an extension of Picture fuzzy sets providing a larger domain to assign membership degrees. Proportional fuzzy sets (PFS) provides a technique to determine membership degrees with a more consistent and sensitive way. In this article, a multiexpert proportional spherical fuzzy integrated AHP&TOPSIS methodology in which AHP is used for computing the criteria weights and TOPSIS is used for selecting the best RPA alternative is presented. Comparative and sensitivity analyses are also applied to determine the validation and robustness of RPA selection decision.
| Original language | English |
|---|---|
| Pages (from-to) | 277-309 |
| Number of pages | 33 |
| Journal | Journal of Multiple-Valued Logic and Soft Computing |
| Volume | 46 |
| Issue number | 2-4 |
| Publication status | Published - 2025 |
Bibliographical note
Publisher Copyright:©2025 Old City Publishing, Inc.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- fuzzy AHP
- fuzzy TOPSIS
- proportional fuzzy sets
- Robotic process automation
- spherical fuzzy sets
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