PIPRECIA: PIvot Pairwise RElative Criteria Importance Assessment

Overview

Pivot pairwise sequential ratio weighting. Output typically weight (higher value = preferred).

Strengths

• •Method-specific: Pivot pairwise sequential ratio weighting
• •Native group-decision support (multi-DM aggregation built into the pipeline)

Limitations

• •Assumes: Domain experts available
• •Assumes: Experts can express consistent comparisons

Assumptions to verify

• •Domain experts available
• •Experts can express consistent comparisons

When not to use

• •No experts available → use objective weighting
• •High inconsistency → discard and re-elicit

Edge cases

• •default for pivot).

Common pitfalls

• •Hatalı: 'PIPRECIA bu varsayımı kontrol etmeden uygulamak'. Doğrusu: Domain experts available
• •Hatalı: 'PIPRECIA bu varsayımı kontrol etmeden uygulamak'. Doğrusu: Experts can express consistent comparisons
• •Hatalı: PIPRECIA'yi 'No experts available → use objective weighting' durumunda kullanmak: recommendation_metadata.not_recommended_when alternatif öneriyor.
• •Hatalı: PIPRECIA'yi 'High inconsistency → discard and re-elicit' durumunda kullanmak: recommendation_metadata.not_recommended_when alternatif öneriyor.

Worked example

1. 1.Adım 1 (F1): Step 1: Pivot criterion designated as baseline; relative importance s_j vs preceding criterion (1.0 default for pivot). Formül: s_{j}: \text{relative importance of }C_{j}\text{ vs }C_{j-1} Anchor: Stanujkic 2017, p.5 Sec.3
2. 2.Adım 2 (F2): Step 2: Coefficient k_j = 2 − s_j; recalculated weight q_j = q_{j-1}/k_j. Formül: k_{j} = \begin{cases} 1 & j=1 \\ 2 - s_{j} & j>1 \end{cases};\quad q_{j} = \dfrac{q_{j-1}}{k_{j}} Anchor: Stanujkic 2017, p.5 Eqs.(1)-(2)
3. 3.Adım 3 (F3): Step 3: Final weights w_j = q_j / Σ q_k. Formül: w_{j} = \dfrac{q_{j}}{\sum_{k=1}^{n} q_{k}} Anchor: Stanujkic 2017, p.6 Eq.(3)

Commonly paired with

• •PIPRECIA + TOPSIS (high)
• •PIPRECIA + VIKOR (high)
• •PIPRECIA + EDAS (high)
• •PIPRECIA + PROMETHEE (high)
• •PIPRECIA + ELECTRE-III (high)

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