Interactive Internet Framework Proposal of WASPAS Method: A Computational Contribution for Decision-Making Analysis

Abstract

Concerning the development of computational tools and solutions as a decision-making aid, this paper presents the results of the waspasWEB project, which strives to provide decision-makers with a readily accessible mechanism to employ the weighted aggregated sum product assessment (WASPAS) method. The social contribution of the project encompasses the development of a user-friendly and publicly accessible internet tool, as well as a package launched on the Comprehensive R Archive Network (CRAN) to serve the community of users of the R language. The use of operational research methodologies is crucial to justify decisions, and this effort seeks to advance the adoption of such methodologies, offering managers, researchers, and the general public an intuitive and easily accessible multi-criteria decision-making tool. In this way, we present the technical specifications, usability, and interactivity of the user with the computational platform, being validated its viability through a hypothetical case study. At the end of the research, it exposes the limitations and feasibility of the proposed computational model along with future research.

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“…Subjective weights are described merely by the preferences of the decisionmakers. Usually, the subjective judgments are mainly based on pairwise comparison methods such as AHP (Analytic Hierarchy Process) ( Van Nguyen et al, 2023;Tavana et al, 2023), DEMATEL (Decision-making Trial and Evaluation Laboratory) (Bali et al, 2023;Šmidovnik & Grošelj, 2023), SWARA (Step-Wise Weight Assessment Ratio Analysis) (Alrasheedi et al, 2023;Deveci et al, 2023), PIPRECIA (Pivot Pairwise Relative Criteria Importance Assessment) (Janovac et al, 2023;Qaddoori & Breesam, 2023), or WASPAS (weighted aggregated sum product assessment) (Alrasheedi et al, 2023;Barbara et al, 2023;Zavadskas et al, 2012). Recently, WASPAS and its different modifications have been broadly employed for several multi-criteria decision-making tasks (Pandurang, 2021;Petrovas & Bausys, 2022;Semenas & Bausys, 2022;Vaid et al, 2022).…”