PIPRECIA - PIvot Pairwise RElative Criteria Importance Assessment

Overview

PIPRECIA is a variant of SWARA that allows s_j < 1 (criterion j+1 is more important than criterion j), making it usable even when the initial ranking is uncertain. k_j = 2 − s_j: if s_j = 1.5 then k_j = 0.5 meaning criterion j has twice the weight of criterion j+1.

Output

Weight, higher is better

Data

Crisp, expert input required

Weights

Derived internally, no weight source needed

Size

2+ alternatives, 3-12 criteria works best

Used for

Expert-driven decision making, MAGDM

How it works

1. 1

   Pivot criterion designated as baseline; relative importance s_j vs preceding criterion (1.0 default for pivot).

   $$s_j:\text{relative importance of }{C}_j\text{ vs }{C}_{j-1}$$

   Stanujkic 2017, p.5 Sec.3

2. 2

   Coefficient k_j = 2 − s_j; recalculated weight q_j = q_{j-1}/k_j.

   $$k_j=\{\begin{array}{ll}1& j=1\\ 2-s_j& j>1\end{array};q_j=\frac{q_{j-1}}{k_j}$$

   Stanujkic 2017, p.5 Eqs.(1)-(2)

3. 3

   Final weights w_j = q_j / Σ q_k.

   $$w_j=\frac{q_j}{{\sum }_{k=1}^n{q}_k}$$

   Stanujkic 2017, p.6 Eq.(3)

Fits when / Look elsewhere when

Assumptions to verify

• Domain experts available
• Experts can express consistent comparisons

Edge cases and pitfalls

• •default for pivot).

• Confusing PIPRECIA's s_j scale with SWARA's: SWARA s_j ∈ [0,∞), PIPRECIA s_j ∈ (0,2). They share the same k_j = s_j+1 vs k_j = 2−s_j - opposite directions.

Works with

How to cite