| A dynamic model and an algorithm for short-term supply chain scheduling in the smart factory industry 4.0 D Ivanov, A Dolgui, B Sokolov, F Werner, M Ivanova International Journal of Production Research 54 (2), 386-402, 2016 | 379 | 2016 |
| Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case D Ivanov Transportation Research Part E: Logistics and Transportation Review 136, 101922, 2020 | 373 | 2020 |
| The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics D Ivanov, A Dolgui, B Sokolov International Journal of Production Research 57 (3), 829-846, 2019 | 348 | 2019 |
| The Ripple effect in supply chains: trade-off ˇefficiency-flexibility-resilience˘in disruption management D Ivanov, B Sokolov, A Dolgui International Journal of Production Research 52 (7), 2154-2172, 2014 | 310 | 2014 |
| A multi-structural framework for adaptive supply chain planning and operations control with structure dynamics considerations D Ivanov, B Sokolov, J Kaeschel European journal of operational research 200 (2), 409-420, 2010 | 305 | 2010 |
| Adaptive supply chain management D Ivanov, B Sokolov Springer Science & Business Media, 2009 | 251 | 2009 |
| Ripple effect in the supply chain: an analysis and recent literature A Dolgui, D Ivanov, B Sokolov International Journal of Production Research 56 (1-2), 414-430, 2018 | 249 | 2018 |
| Literature review on disruption recovery in the supply chain D Ivanov, A Dolgui, B Sokolov, M Ivanova International Journal of Production Research 55 (20), 6158-6174, 2017 | 244 | 2017 |
| Viability of intertwined supply networks: extending the supply chain resilience angles towards survivability. A position paper motivated by COVID-19 outbreak D Ivanov, A Dolgui International Journal of Production Research 58 (10), 2904-2915, 2020 | 190 | 2020 |
| Control and system-theoretic identification of the supply chain dynamics domain for planning, analysis and adaptation of performance under uncertainty D Ivanov, B Sokolov European Journal of Operational Research 224 (2), 313-323, 2013 | 174 | 2013 |
| Review of quantitative methods for supply chain resilience analysis S Hosseini, D Ivanov, A Dolgui Transportation Research Part E: Logistics and Transportation Review 125, 285-307, 2019 | 168 | 2019 |
| An adaptive framework for aligning (re) planning decisions on supply chain strategy, design, tactics, and operations D Ivanov International journal of production research 48 (13), 3999-4017, 2010 | 148 | 2010 |
| Revealing interfaces of supply chain resilience and sustainability: a simulation study D Ivanov International Journal of Production Research 56 (10), 3507-3523, 2018 | 129 | 2018 |
| Simulation-based ripple effect modelling in the supply chain D Ivanov International Journal of Production Research 55 (7), 2083-2101, 2017 | 128 | 2017 |
| Global supply chain and operations management D Ivanov, A Tsipoulanidis, J Schönberger A decision-oriented introduction to the creation of value 2, 2017 | 126 | 2017 |
| Dynamic supply chain scheduling D Ivanov, B Sokolov Journal of scheduling 15 (2), 201-216, 2012 | 124 | 2012 |
| Structural dynamics and resilience in supply chain risk management D Ivanov Springer International Publishing, 2018 | 123 | 2018 |
| Optimal distribution (re) planning in a centralized multi-stage supply network under conditions of the ripple effect and structure dynamics D Ivanov, A Pavlov, B Sokolov European Journal of Operational Research 237 (2), 758-770, 2014 | 118 | 2014 |
| Scheduling in production, supply chain and Industry 4.0 systems by optimal control: fundamentals, state-of-the-art and applications A Dolgui, D Ivanov, SP Sethi, B Sokolov International Journal of Production Research 57 (2), 411-432, 2019 | 116 | 2019 |
| Low-Certainty-Need (LCN) supply chains: a new perspective in managing disruption risks and resilience D Ivanov, A Dolgui International Journal of Production Research 57 (15-16), 5119-5136, 2019 | 115 | 2019 |
