<?xml version='1.0' encoding='UTF-8'?><metadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns="http://dublincore.org/documents/dcmi-terms/"><dcterms:title>Transaction Network Structural Shift under Crisis: Macro and Micro Perspectives</dcterms:title><dcterms:identifier>https://doi.org/10.34820/FK2/06LQEJ</dcterms:identifier><dcterms:creator>Andry Alamsyah</dcterms:creator><dcterms:creator>Dian Puteri Ramadhani</dcterms:creator><dcterms:creator>Farida Titik Kristanti</dcterms:creator><dcterms:creator>Khairunnisa Khairunnisa</dcterms:creator><dcterms:publisher>Root</dcterms:publisher><dcterms:issued>2022-03-04</dcterms:issued><dcterms:modified>2022-03-04T10:34:26Z</dcterms:modified><dcterms:description>In 2008, the Lehman Brothers’ bankruptcy, accumulated from the global financial crisis, proved a unique role of the highly interconnected financial entities. Shocks in a bank might trigger loss, induce spillovers, provoke a contagion shock spreading to other entities, trigger the whole banking system to collapse, and ultimately unsettle the worldwide economy. Therefore, evaluating financial stability through a system-wide network approach provides more adequate knowledge than evaluating a bank as an individual. In this approach, individual banks and their transaction activities are modeled into a transaction network, forming a network topology. Financial shocks are generally detected through various macro procedures, such as outstanding external debt and uncontrolled transaction deficits. This study proposes financial shock detection from a macro and micro perspective by exploring the effect of disruption on transaction network structure. We investigate the most changing triadic motif as a crisis predictor from a micro perspective due to the crisis period. The case study is the transaction network structural shift under the 2008 crisis in Indonesia, where the observations were performed from the pre-crisis to the post-crisis period. We discovered a motif with the significant changes as the underlying financial crisis predictor. This scenario provides support for the financial system’s stability control</dcterms:description><dcterms:subject>Business and Management</dcterms:subject><dcterms:subject>transaction network; network structure; network topology; network motifs; financial crisis</dcterms:subject><dcterms:isReferencedBy>Alamsyah, A.; Ramadhani, D.P.; Kristanti, F.T.; Khairunnisa, K. Transaction Network Structural Shift under Crisis: Macro and Micro Perspectives. Economies 2022, 10, 56. https://doi.org/10.3390/economies10030056, doi, https://www.mdpi.com/2227-7099/10/3/56</dcterms:isReferencedBy><dcterms:contributor>KHAIRUNNISA, KHAIRUNNISA</dcterms:contributor><dcterms:dateSubmitted>2022-03-04</dcterms:dateSubmitted><dcterms:license>CC0</dcterms:license><dcterms:rights>CC0 Waiver</dcterms:rights></metadata>