Selecting suitable software components in complex domains such as healthcare requires

careful evaluation based on multiple criteria. The study focuses on comparing two multi-

criteria decision-making methods, the Analytic Hierarchy Process (AHP) and the Pugh

matrix, to determine which is the most effective and suitable for guiding selection of a

subcomponent in a professional software development context. The study focuses on the

case of prioritizing web-based text editors within medical reporting, in collaboration with

Sectra Imaging IT Solutions AB. Seven editors were evaluated using 25 different criteria.

The methodology involved gathering and prioritizing evaluation criteria through semi-

structured interviews with Sectra employees and a survey. Based on these criteria, a selec-

tion of web-based text editors was identified and systematically tested in a controlled test

environment developed using React and TypeScript. The results from the tests, combined

with survey data, were then used to evaluate the editors with AHP, along with the basic

version of the Pugh matrix, and the Pugh matrix with weighted criteria.

Both AHP and the Pugh matrix were applied independently using the same dataset, allow-

ing for a direct comparison of their methodological strengths and limitations. The results

from AHP and the weighted Pugh matrix were consistent, identifying TipTap (commercial

version) and Lexical as the most suitable editors for radiological reporting within Sectra’s

products. The unweighted Pugh matrix also pointed to TipTap (commercial version) as

the best option, but its results were less nuanced. All three methods consistently identified

TinyMCE and Slate as the least suitable alternatives, primarily due to performance issues,

licensing restrictions, and implementation complexity.

The comparison of methods showed that AHP is a more structured and detailed approach,

particularly useful for scenarios involving numerous criteria with varying importance. The

Pugh matrix is simpler and faster to use, but the unweighted version lacks sensitivity to

prioritized criteria.

The study proposes a beneficial combination of the two methods: utilizing the Pugh mat-

rix for an initial screening to eliminate less suitable options, followed by AHP for a more

detailed comparison of the highest-ranked alternatives. This hybrid method can optim-

ize decision-making efficiency while ensuring high decision quality. Finally, the study

provides a framework for software component evaluation that can be applied to similar

professional contexts.