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                <text>Faculty Publications</text>
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              <text>Orupalli, Surendra; Sayama, Hiroki</text>
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              <text>Impact of Node Failures on Productivity in Multilayer Supply Chain Networks: An Influence Network Analysis in the Indian Electronics Sector</text>
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              <text>01-01-2025</text>
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              <text>Northeast Journal of Complex Systems;Volume;7;Issue;1;Article No.;5;pp.1-17</text>
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              <text>&lt;a href="https://doi.org/10.22191/nejcs/vol7/iss1/5" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.22191/nejcs/vol7/iss1/5&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105003764454?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105003764454?origin=resultslist&lt;/a&gt;</text>
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              <text>Orupalli S., School of Systems Science and Industrial Engineering, Binghamton University, NY, United States; Sayama H., School of Systems Science and Industrial Engineering, Binghamton University, NY, United States, Waseda Innovation Lab, Waseda University, Tokyo, Japan, School of Sciences, Christ University, Lavasa, India</text>
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              <text>Supply chain networks are essential for the delivery of goods and information, but disruptions such as natural disasters or trade embargoes can severely impact them. Resilience of entire networks under different types of disruptions when nodes or edges fail has been extensively studied. However, the extent to which the failure of a particular company affects another company of interest within a network has not been widely explored. To address this, we created a multilayer physical supply chain network of companies in the Indian electronics industry. Through systematic node removal simulations, we examined how the productivity of one company is impacted by the removal of another. Extending these simulations to include all possible combinations of companies yielded an influence network that represents interdependence among nodes in terms of productivity. We observed that removing a critical node could lead to not only a decrease but, quite counter-intuitively, an increase as well in the productivity of affected nodes. This study identifies the factors that influence these productivity changes and offers insights to supply chain managers to maintain network resilience in the face of node failures.  2025, Binghamton University Libraries. All rights reserved.</text>
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              <text>Influence Network; Multilayer Network; Node Failure; Productivity Impact; Supply Chain Resilience</text>
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              <text>Binghamton University Libraries</text>
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              <text>ISSN: 25778439;</text>
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              <text>All Open Access; Gold Open Access</text>
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