Journal of Decision Systems

Aims & Scope

The Journal of Decision Systems (JDS) is a world-leading journal extending scientific knowledge related to decision making and decision support.

Published articles focus on the process of decision-making in different environments/conditions, how that process is influenced by specific social and/or technical factors, and ultimately how new or adapted sociotechnical systems can be introduced to improve decision-making.

The types of studied decision systems vary in scale.

Some studies focus on individual decision-making, others focus on group decisions, others on organisational or community decision-making, and others on some combination of these.

The types of studied decision systems also vary by domain.

Examples include systems development, human resource management, health and wellbeing, marketing, product design, green IT, financial services, and crisis management, to name a few.

JDS encourages research that draws on different backgrounds, theories, and methodologies.

We are particularly welcoming to articles that seek to open up the black box of decision-making in a way that produces new insights with clear practical implications.

A range of decision-related topics will be considered; examples include: -Big Data and Data Analytics- Business Intelligence- Clinical and Health Information and Decision Systems- Collaborative Decision Making- Context in Decision Making- Decision Support Systems- Decision Making During Design and Organisational Change- Distributed Decision Making- Emergency Management- Enterprise Systems- Evaluation of Decision Systems- Integrated Decision Support Systems- Intelligent or Augmented Decision Systems- Knowledge Management- Managerial Decision Making- Mindful Decision Making- Multi-Criteria Decision Making- NeuroIS- Open Decision Making Behaviour, e.g.

Open Strategy, Crowd Filtering/Evaluation- Production and Logistics Systems- Sense-Making- Situational Decision Making

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	4.3
2024	2.80

Journal Rank

Year	Value
2024	7242

Journal Citation Indicator

Year	Value
2024	559

SJR (SCImago Journal Rank)

Year	Value
2024	0.761

Quartile

Year	Value
2024	Q1

h-index

Year	Value
2024	37

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Business, Management and Accounting, Computer Science and Social Sciences, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Challenges for digital transformation – towards a conceptual decision support guide for managers

  Citation: 245

  Authors: Ciara, Daniel J.

• Frameworks for developing impactful systematic literature reviews and theory building: What, Why and How?

  Citation: 238

  Authors: Justin, Puja, Harshleen

• Transparency and trust in artificial intelligence systems

  Citation: 233

  Authors: Philipp, Felix, Timm

• Analysing the past to prepare for the future: Writing a literature review a roadmap for release 2.0

  Citation: 176

  Authors: Richard T., Jane

• Decision making under stress: the role of information overload, time pressure, complexity, and uncertainty

  Citation: 171

  Authors: Gloria, Monica

• An integrated patient journey mapping tool for embedding quality in healthcare service reform

  Citation: 156

  Authors: Stephen, Paidi, Simon, Yoke Lin, Louise C., Frédéric

• Impact of Social Media and Web 2.0 on Decision-Making

  Citation: 115

  Authors: Daniel J., Gloria

• The PROMETHEE VI procedure: how to differentiate hard from soft multicriteria problems

  Citation: 108

  Authors: Jean-Pierre, Bertrand

• Workers’ technostress: a review of its causes, strains, inhibitors, and impacts

  Citation: 103

  Authors: Amna Shifia, Gaye, Carolanne

• Using ‘Big Data’ for analytics and decision support

  Citation: 100

  Authors: Daniel J.

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