{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T08:48:00Z","timestamp":1782809280292,"version":"3.54.5"},"reference-count":0,"publisher":"ECMS","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,6,23]]},"abstract":"<jats:p>One crucial aspect of modern supply chains is that they operate not just in dynamic environments but in rapidly changing, fluid ones. Change is relentless, and adjustments must be made instantly once a change is addressed. The continuous adjustment pressures extend beyond dynamics and best describe modern supply chains. That\u2019s why it is essential to incorporate all the chain\u2019s changes, and one recent approach to address this behaviour is supply chain stress testing. The primary objective is to employ simulation techniques to develop data-driven models that enhance supply chain resilience. Businesses can better adapt to changes by preparing for disruptions through simulation. Preparing for disruptions requires understanding their characteristics, like how long they last, how often they occur, and how severe they are. This study examines how higher disruption frequency impacts supply chain performance and resilience. Using discrete-event simulation, we analysed twelve different frequency scenarios. The model was tested on a transformers manufacturer serving clients throughout Africa and the Middle East. The findings show specific disruption frequencies at which service levels drop significantly, and backlogs become persistent. Additionally, service degradation at higher frequencies is non-linear, with all areas experiencing over 50% reductions that do not improve over two years. These findings highlight the frequency of disruptions as a driver of supply chain non\u2011viability.<\/jats:p>","DOI":"10.7148\/2026-0017","type":"proceedings-article","created":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T08:36:46Z","timestamp":1782808606000},"page":"17-23","source":"Crossref","is-referenced-by-count":0,"title":["Examining the effects of disruption frequency on supply chain performance"],"prefix":"10.7148","author":[{"given":"Ibrahim","family":"Fikry","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dmitry","family":"Ivanov","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kieran","family":"Conboy","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"4144","published-online":{"date-parts":[[2026,6,23]]},"event":{"name":"40th ECMS International Conference on Modelling and Simulation"},"container-title":["ECMS 2026 Proceedings edited by Filippo Sanfilippo, Florenc Demrozi, Fabio Sgarbossa, Mohammad Poursina"],"original-title":[],"deposited":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T08:36:47Z","timestamp":1782808607000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.scs-europe.net\/dlib\/2026\/ecms2026acceptedpapers\/0017_rssc_ecms2026_0052.pdf"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,23]]},"references-count":0,"URL":"https:\/\/doi.org\/10.7148\/2026-0017","relation":{},"subject":[],"published":{"date-parts":[[2026,6,23]]}}}