Using Structural Variation Analysis to Measure Interdisciplinary Knowledge Integration in Operations Research

Khaled Mili and Majdi Argoubi
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Khaled Mili: Department of Quantitative Methods, College of Business Administration, King Faisal University, Saudi Arabia
Majdi Argoubi: University of Sousse, Tunisia

International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), 2025, vol. 16, issue 1, 1-16

Abstract: Traditional citation analyses often fail to capture how research reshapes intellectual landscapes. This study applies Structural Variation Analysis (SVA) to assess the interdisciplinary impact of a highly cited paper on the Cross-Entropy Method in Operations Research. Using co-citation network analysis, the authors examine structural shifts through key metrics, including modularity change (∆M = 52.57), cluster linkage (CL = 135.2), centrality divergence (CKL = 0.47), and entropy (E = 0.98). The findings reveal that this methodological paper plays a pivotal role in bridging previously unconnected research domains. Beyond accumulating citations, the Cross-Entropy Method has fundamentally altered research connectivity. SVA offers an early indicator of transformative research before conventional citation metrics can capture their full impact.

Date: 2025
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