ABSTRACT: 

Effective workforce allocation is central to industrial productivity, yet the decision-making tools most used to support it struggle to accommodate the uncertainty and subjectivity inherent in expert judgment. This study develops and validates a Fuzzy Analytic Hierarchy Process (Fuzzy-AHP) model for workforce allocation in the Jordanian industrial sector, a context shaped by rapid Industry 4.0 transformation, persistent youth unemployment, and a widening gap between the skills industry demands and the skills the labor market supplies. The problem addressed is that the classical Analytic Hierarchy Process (AHP) requires decision-makers to express pairwise preferences as exact numerical values, a requirement that does not reflect the imprecise nature of real managerial judgment. To resolve this limitation, the study integrates fuzzy logic, represented through triangular fuzzy numbers, into the classical AHP framework using Buckley's geometric mean method. Data were collected through semi-structured interviews and pairwise-comparison surveys with six experts’ production managers, plant managers, a CEO, and operations engineers representing pharmaceutical, construction-products, and cement companies operating in Jordan. Thematic analysis of the interviews, cross-checked against the literature, identified six criteria: Experience, Technical, Human and Behavioral, Operational, Organizational, and Logistical factors. All six individual pairwise matrices achieved Consistency Ratios between 0.0142 and 0.0229, confirming the reliability of expert judgments. Geometric-mean aggregation produced crisp AHP weights led by Experience (37.7%) and Operational factors (21.7%), while the Fuzzy-AHP extension, verified through alpha-cut sensitivity analysis at five confidence levels, confirmed the same ranking and produced defuzzified weights of Experience (36.9%), Operational (21.8%), Technical (18.5%), Human and Behavioral (11.2%), Organizational (6.6%), and Logistical (5.0%). The convergence between the crisp and fuzzy results validates the robustness of the derived priorities and demonstrates that the Fuzzy-AHP model provides Jordanian industrial firms with a transparent, uncertainty-aware, and practically actionable tool for workforce allocation decisions.

Keywords:   Analytic Hierarchy Process; Fuzzy Logic; Workforce Allocation; Multi-Criteria Decision-Making; Triangular Fuzzy Numbers; Jordan Industrial Sector.