DecisionTech Review
Peer-reviewed, open-access journal on the intersection of decision science, management, and computer science.
Scope
Cutting-edge research at the nexus of decision science, management, and computer science. It serves as a platform for disseminating theoretical and practical knowledge, encouraging interdisciplinary approaches to complex problems.
Indexing
Google Scholar, Crossref, Dimensions
APC
No APC
License
Open Access, CC BY-NC 4.0
Languages
English / Spanish / Portuguese
About the Journal
The DecisionTech Review (e-ISSN: 2806-397X) is a peer-reviewed journal that publishes cutting-edge research at the nexus of decision science, management, and computer science. It serves as a platform for disseminating theoretical and practical knowledge, encouraging interdisciplinary approaches to complex problems. The journal caters to academics, practitioners, and policymakers interested in the latest developments and innovative solutions at the intersection of these fields.
Aims & Scope
- Decision analysis and support systems
- Management science and operations research
- Artificial intelligence and machine learning in business
- Information systems and technology management
- Human-computer interaction and user experience
- Big data and analytics
- Blockchain and emerging technologies
- Interdisciplinary approaches and case studies
Editorial Model & Policies
Peer Review
Double-blind, external reviewers
Licensing & Access
Open access, CC license
Ethics
COPE compliance, plagiarism screening
Author Information
Special Issues Highlight
We welcome proposals for special issues and thematic sections that promote critical debates on the intersection between decision science, management, and computer science.