Strategic Recovery and Institutional Resilience in Digital Asset Exchanges The Indodax Case Study and the S3-Resilience Model

This study examines institutional resilience and strategic recovery dynamics of Indodax following a cyber security incident in September 2024. The research aims to evaluate the effectiveness of the recovery process using the S3-Resilience Model framework, focusing on the interplay between operational speed, financial solvency, and public sentiment. This study employs a descriptive-analytical case study method with a qualitative approach. Data were gathered from reconstructed market events, publicly accessible blockchain records, and official institutional disclosures. The analysis was conducted by applying the S3-Resilience Model conceptual framework, integrating three main pillars: Speed, Solvency, and Sentiment. Quantitative metrics such as the Crisis Shock Coverage Ratio (CSCR) and V-Shaped Recovery patterns in trading activity were used to validate the resilience indicators. The findings reveal a high degree of systemic resilience, evidenced by service restoration within 80 hours, significantly below the industry average. Transparency was maintained through the publication of Proof of Reserve amounting to Rp11.5 trillion with a CSCR of 34x. Market response remained positive, indicated by net positive fund inflows and a swift return to normal trading volumes. The Indodax case demonstrates that institutional resilience in digital asset exchanges depends on a balanced integration of technical readiness and transparent financial accountability. The study concludes that the S3-Resilience Model is a viable framework for managing systemic risks and maintaining market trust during high-impact cyber crises.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-29
DOI
https://doi.org/10.5281/zenodo.18759502
Primary Topic
Supply Chain Resilience and Risk Management
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

Strategic Recovery and Institutional Resilience in Digital Asset Exchanges The Indodax Case Study and the S3-Resilience Model

Sutarno Sarba
Zenodo (CERN European Organization for Nuclear Research)
Supply Chain Resilience and Risk Management
preprint

Strategic Recovery and Institutional Resilience in Digital Asset Exchanges The Indodax Case Study and the S3-Resilience Model

Sutarno Sarba
preprint en

Abstract

This study examines institutional resilience and strategic recovery dynamics of Indodax following a cyber security incident in September 2024. The research aims to evaluate the effectiveness of the recovery process using the S3-Resilience Model framework, focusing on the interplay between operational speed, financial solvency, and public sentiment. This study employs a descriptive-analytical case study method with a qualitative approach. Data were gathered from reconstructed market events, publicly accessible blockchain records, and official institutional disclosures. The analysis was conducted by applying the S3-Resilience Model conceptual framework, integrating three main pillars: Speed, Solvency, and Sentiment. Quantitative metrics such as the Crisis Shock Coverage Ratio (CSCR) and V-Shaped Recovery patterns in trading activity were used to validate the resilience indicators. The findings reveal a high degree of systemic resilience, evidenced by service restoration within 80 hours, significantly below the industry average. Transparency was maintained through the publication of Proof of Reserve amounting to Rp11.5 trillion with a CSCR of 34x. Market response remained positive, indicated by net positive fund inflows and a swift return to normal trading volumes. The Indodax case demonstrates that institutional resilience in digital asset exchanges depends on a balanced integration of technical readiness and transparent financial accountability. The study concludes that the S3-Resilience Model is a viable framework for managing systemic risks and maintaining market trust during high-impact cyber crises.

Zenodo (CERN European Organization for Nuclear Research)
Supply Chain Resilience and Risk Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.