Article: Expert-elicited weights in multi-criteria decision analysis: theory and practice Journal: International Journal of Economics and Business Research (IJEBR) 2026 Vol.30 No.3 pp.51 - 66 Abstract: The expert weighting method has been applied in decision-making for years but lacks a firm theoretical basis. This study introduces a mathematical framework to address this gap. Due to the additive-only nature of the five-point Likert scale, a 100-point system was adopted. Experts rated each variable based on a baseline of 1, and matrix multiplication was used to generate proportional importance values, overcoming the limits of ordinal comparisons. Mathematical induction shows that, with equal initial scores, variables with higher variance receive lower importance. This supports the logic of the weighting process and improves the scale's sensitivity in distinguishing variable significance. By analysing internal variance, the method allows for clearer importance ranking and enhances evaluation precision. While the Likert scale is common, its statistical limits reduce reliability. Incorporating the expert weighting method addresses these flaws and improves evaluation tools. Inderscience Publishers - linking academia, business and industry through research

Title: Expert-elicited weights in multi-criteria decision analysis: theory and practice

Authors: Shu-ya Chang

Addresses: Dhurakij Pundit University, Chinese International College, Bangkok, Thailand

Abstract: The expert weighting method has been applied in decision-making for years but lacks a firm theoretical basis. This study introduces a mathematical framework to address this gap. Due to the additive-only nature of the five-point Likert scale, a 100-point system was adopted. Experts rated each variable based on a baseline of 1, and matrix multiplication was used to generate proportional importance values, overcoming the limits of ordinal comparisons. Mathematical induction shows that, with equal initial scores, variables with higher variance receive lower importance. This supports the logic of the weighting process and improves the scale's sensitivity in distinguishing variable significance. By analysing internal variance, the method allows for clearer importance ranking and enhances evaluation precision. While the Likert scale is common, its statistical limits reduce reliability. Incorporating the expert weighting method addresses these flaws and improves evaluation tools.

Keywords: expert weighting method; decision-making evaluation; 100-point scoring system; mathematical induction.

DOI: 10.1504/IJEBR.2026.152458

International Journal of Economics and Business Research, 2026 Vol.30 No.3, pp.51 - 66

Received: 29 Nov 2025
Accepted: 30 Jan 2026
Published online: 20 Mar 2026 *

Title: Expert-elicited weights in multi-criteria decision analysis: theory and practice

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