TY - JOUR

T1 - The Voting Analytic Hierarchy Process revisited

T2 - A revised method with application to sustainable supplier selection

AU - Pishchulov, Grigory

AU - Trautrims, Alexander

AU - Chesney, Thomas

AU - Gold, Stefan

AU - Schwab, Leila

PY - 2019/5/1

Y1 - 2019/5/1

N2 - Civil society increasingly holds focal companies accountable for ensuring socially and environmentally sustainable production standards among their supply base. These standards entail increased levels of complexity to be addressed by appropriately designed tools, such as the Voting Analytic Hierarchy Process (VAHP) proposed by Liu and Hai (2005). This method of multi-criteria group decision making structures decision criteria in a hierarchical fashion as per Saaty's Analytic Hierarchy Process (AHP) and employs data envelopment analysis (DEA) for deriving criteria weights from the ordinal preferences of the group members. Compared to AHP, the method permits a simpler application in a group decision context. However, its theoretical underpinnings have been questioned in the literature. This specifically concerns (i) the requirement of a strong convex order for the importance weights of ordinal rank gradations, and (ii) the choice of discrimination threshold for consecutive rank weights in the underlying DEA model. We propose a revised VAHP method that overcomes both issues (i) and (ii) by pursuing a game-theoretic approach to elicitation of criteria weights — so as to remove subjectivity from rank discrimination. We illustrate the application of the method on a real-world problem of sustainable supplier selection. We contribute to theory by proposing a more robust VAHP tool that helps supply chain and purchasing managers selecting suppliers based on a comprehensive set of criteria spanning all three sustainability dimensions (economic, environmental, and social), while coping with parsimonious input by group decision-makers.

AB - Civil society increasingly holds focal companies accountable for ensuring socially and environmentally sustainable production standards among their supply base. These standards entail increased levels of complexity to be addressed by appropriately designed tools, such as the Voting Analytic Hierarchy Process (VAHP) proposed by Liu and Hai (2005). This method of multi-criteria group decision making structures decision criteria in a hierarchical fashion as per Saaty's Analytic Hierarchy Process (AHP) and employs data envelopment analysis (DEA) for deriving criteria weights from the ordinal preferences of the group members. Compared to AHP, the method permits a simpler application in a group decision context. However, its theoretical underpinnings have been questioned in the literature. This specifically concerns (i) the requirement of a strong convex order for the importance weights of ordinal rank gradations, and (ii) the choice of discrimination threshold for consecutive rank weights in the underlying DEA model. We propose a revised VAHP method that overcomes both issues (i) and (ii) by pursuing a game-theoretic approach to elicitation of criteria weights — so as to remove subjectivity from rank discrimination. We illustrate the application of the method on a real-world problem of sustainable supplier selection. We contribute to theory by proposing a more robust VAHP tool that helps supply chain and purchasing managers selecting suppliers based on a comprehensive set of criteria spanning all three sustainability dimensions (economic, environmental, and social), while coping with parsimonious input by group decision-makers.

KW - Game theory

KW - Group decisions

KW - Multi-criteria decision making

KW - Ordinal preferences

KW - Preference aggregation

KW - Supplier selection

KW - Sustainability

UR - http://www.scopus.com/inward/record.url?scp=85061664920&partnerID=8YFLogxK

U2 - 10.1016/j.ijpe.2019.01.025

DO - 10.1016/j.ijpe.2019.01.025

M3 - Article

AN - SCOPUS:85061664920

VL - 211

SP - 166

EP - 179

JO - International Journal of Production Economics

JF - International Journal of Production Economics

SN - 0925-5273

ER -