2335 averaged 50.72 (SD=15.20) against a theoretical maximum of 125, representing only 40.6% of potential capacity. The observed range (22.28–87.35) demonstrates that the highest-potential worker exhibits approximately four times the productive capacity of the lowest, justifying differentiated talent management approaches. Sensitivity analysis confirmed Motivation (ρ=0.759, p<0.001) and Commitment (ρ=0.757, p<0.001) as the strongest predictors, identifying these “soft” dimensions as primary intervention targets. 4.1.1 Counterintuitive Moderator Effects Three findings challenge conventional assumptions about workforce readiness for technological transitions. First, labor reconversion status showed no significant differences in change openness (U=1442.5, p=0.852), indicating that workers displaced from the closed smelter are no less receptive to new technology than original workers. Second, age demonstrated null correlation with resistance (ρ=–0.089, p=0.506); workers over 50 years showed equivalent openness (M=3.87) to those under 35 (M=3.83). This finding directly supports Kraiger and Ford’s (2021) assertion that “well-designed training works for all” regardless of age. Third, work group differences proved significant (H=10.89, p=0.012), with supervisors explaining 15–20% of variance in change readiness—exceeding all demographic predictors—confirming the BurkeLitwin (1992) causal framework positioning immediate supervisors as critical mediators between organizational strategy and individual response. 4.2 Qualitative Findings (1,320 Narratives) Thematic analysis of 1,320 narrative responses (inter-coder reliability Kappa=0.78) using Braun and Clarke’s (2006) six-phase method, complemented by game theory interpretation, revealed four emergent dimensions. Temporal orientation analysis showed 36.4% future-oriented workers (M change openness=4.12), 42.2% present-focused (M=3.84), and 21.4% anchored in the past (M=3.51)—the 0.61point difference between future and past orientations (t=5.23, p<0.001) demonstrating temporal framing’s impact on adaptability. Among reconverted workers, past-anchoring was particularly prevalent, with narratives revealing unresolved identity loss and nostalgia for the closed facility. Locus of control analysis found 42.4% of narratives exhibiting internal attribution, indicating latent personal agency. Change Agents showed a 12.9:1 internal-to-external ratio, while workers Requiring Intervention showed near-parity (1.2:1), suggesting a relationship between perceived agency and productive potential. Social interaction strategies revealed cooperative orientations predominating at 14.8% versus 3.4% individualist/competitive combined, yielding a 4:1 cooperation ratio. Perceived facilitators exceeded barriers 4.4:1, with training mentioned 57 times as primary facilitator—suggesting that organizational conditions fundamentally support change, though specific capacity-building needs remain. Game theory analysis identified worker-supervisor interactions as repeated games with imperfect information. Strategy distribution revealed: 63.3% cooperate with change, 23.3% passive resistance, 8.3% active resistance, and 5.0% selective adaptation. Multiple Nash equilibria coexist across work groups: Groups 1 and 4 achieved cooperative optimal equilibrium, Group 2 remains trapped in suboptimal mutualresistance equilibrium (stable but inefficient), and Group 3 occupies transitional instability representing a critical intervention window. Three coordination dilemmas—“who moves first” mutual waiting, trust deficit from broken promises, and early-adopter social costs—explain why uniform interventions have historically failed. Based on Maskin’s (2007) mechanism design theory, five mechanisms were proposed to modify payoff structures toward mutual cooperation: visible recognition, participatory decision-making, stability guarantees, supervisor early-adoption modeling, and collective benefit alignment. 4.3 Workforce Segmentation The quadrant model classifies workers based on two meta-indices: Base Capabilities (Discipline + Motivation)/2 on the X-axis, and Enhancers (Commitment + Attitude)/2 on the Y-axis, using empiricallyderived median cutpoints (X=3.984; Y=3.675). The classification revealed a bipolar distribution with 63.4% concentrated at extremes: Change Agents (31.7%, n=19; Productivity Index M=65.3) showing high scores across all dimensions and concentrating in Groups 1 and 4, and workers Requiring Intervention (31.7%,
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