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Using Structural Variation Analysis to Measure Interdisciplinary Knowledge Integration in Operations Research
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Author(s): Khaled Mili (Department of Quantitative Methods, College of Business Administration, King Faisal University, Saudi Arabia)and Majdi Argoubi (University of Sousse, Tunisia)
Copyright: 2025
Volume: 16
Issue: 1
Pages: 16
Source title:
International Journal of Service Science, Management, Engineering, and Technology (IJSSMET)
Editor(s)-in-Chief: Ahmad Taher Azar (College of Computer & Information Sciences, Prince Sultan University, Riyadh, Saudi Arabia & Faculty of Computers and Artificial Intelligence, Benha University, Benha, Egypt)and Ghazy Assassa (Benha University, Egypt)
DOI: 10.4018/IJSSMET.381314
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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.
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