Data-driven intelligence in crisis
The case of Ukrainian refugee management
Bibliographic Data
| ID | 6426529 |
|---|---|
| Authors | Kilian Sprenkamp (0000-0003-1354-1538), Mateusz Dolata (0000-0002-2732-4465), Gerhard Schwabe (0000-0002-0453-9762), Liudmila Zavolokina (0000-0002-0762-3505) |
| Year | 2024 |
| Volume | 42 |
| Issue | 1 |
| Pages | 101978-101978 |
| Publication date | 2024-12-10 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Government Information Quarterly (JOURNAL) |
| Journal identifiers | ISSN: 0740-624X • E-ISSN: 1872-9517 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.giq.2024.101978 |
| OpenAlex | W4405219228 |
| Language | EN |
| Citations received | 2 |
| References cited | 41 |
Business · Computer security · Crisis management · Linguistics · Political science · Refugee · Refugee crisis · Ukrainian · Computer Science · Data Quality and Management · Intelligence, Security, War Strategy · Law
The new science of management decision.
Big data in the policy cycle
Pre-train, Prompt, and Predict
Nonhuman humanitarianism
The Qualitative Interview in Is Research
Thrive or Survive? Explaining Variation in Economic Outcomes for Refugees
Refugee debate and networked framing in the hybrid media environment
Psychological research evidence in refugee status determination
Research with Refugees in Fragile Political Contexts
Media Framing Dynamics of the ‘European Refugee Crisis’
E-government design research
Public AI canvas for AI-enabled public value
Assessing the public policy-cycle framework in the age of artificial intelligence
Design principles for creating digital transparency in government
Transforming the communication between citizens and government through AI-guided chatbots
Artificial Intelligence for data-driven decision-making and governance in public affairs
A decade of design in digital government research
Big Data and AI – A transformational shift for government
Purposeful Sampling in Qualitative Research Synthesis
Predictive modelling of movements of refugees and internally displaced people
| Citations per year | 2 |
|---|---|
| Citation span | 2025 - 2026 (2) |
| Highly cited | No |