DECISION SCIENCES

Scope & Guideline

Empowering Insights for Strategic Decision-Making

Introduction

Delve into the academic richness of DECISION SCIENCES with our guidelines, detailing its aims and scope. Our resource identifies emerging and trending topics paving the way for new academic progress. We also provide insights into declining or waning topics, helping you stay informed about changing research landscapes. Evaluate highly cited topics and recent publications within these guidelines to align your work with influential scholarly trends.
LanguageEnglish
ISSN0011-7315
PublisherWILEY
Support Open AccessNo
CountryUnited Kingdom
TypeJournal
Convergefrom 1970 to 2024
AbbreviationDECISION SCI / Decis. Sci.
Frequency6 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
Address111 RIVER ST, HOBOKEN 07030-5774, NJ

Aims and Scopes

The journal 'Decision Sciences' focuses on the intersection of decision-making processes and their implications in various fields, particularly in operations and supply chain management. It emphasizes the application of quantitative methods and empirical research to enhance decision-making strategies.
  1. Operations Management:
    Research in this area addresses the optimization of processes, resource allocation, and efficiency in operations across different industries, utilizing methodologies like simulation and mathematical modeling.
  2. Supply Chain Management:
    The journal explores strategies for improving supply chain efficiency, resilience, and coordination, with a focus on real-world applications and empirical studies.
  3. Healthcare Decision Making:
    It includes research on decision-making frameworks in healthcare settings, such as patient management, operational efficiency, and resource allocation within healthcare systems.
  4. Behavioral Decision Theory:
    This area investigates how cognitive biases and social factors influence decision-making processes, particularly in business and economic contexts.
  5. Data Analytics and Machine Learning:
    The journal publishes studies employing data-driven approaches and machine learning techniques to derive insights and improve decision-making in various sectors.
  6. Sustainability and Ethical Considerations:
    Research addressing the integration of sustainability and ethical considerations in decision-making processes, particularly in supply chains and operations.
The journal has identified several trending and emerging themes that reflect the evolving landscape of decision sciences. These themes indicate where researchers are increasingly focusing their efforts, responding to contemporary challenges and technological advancements.
  1. Digital Transformation and Data Privacy:
    Recent publications emphasize the impact of digitalization on decision-making processes, particularly concerning privacy concerns in data usage, reflecting the growing importance of cybersecurity and ethical data management.
  2. Healthcare Innovations and Decision Support Systems:
    There is a surge in research related to decision support systems in healthcare, highlighting innovations that improve patient outcomes and operational efficiency in medical settings.
  3. Sustainability and Circular Economy:
    Emerging research focuses on sustainable practices within supply chains, exploring how businesses can adapt to environmental challenges while maintaining efficiency and profitability.
  4. Machine Learning and Predictive Analytics:
    The integration of advanced analytics and machine learning techniques into decision-making processes is increasingly prevalent, showcasing the journal's commitment to contemporary analytical methodologies.
  5. Behavioral Insights in Decision Making:
    A growing body of work is exploring how behavioral factors influence decision-making in various contexts, indicating a trend towards understanding the psychological aspects of decision processes.

Declining or Waning

While 'Decision Sciences' continues to explore a broad range of topics, some areas have seen a decline in focus over recent years. This section highlights these waning themes, reflecting shifts in research priorities and emerging trends.
  1. Traditional Inventory Management Techniques:
    There has been a noticeable decrease in publications focusing solely on conventional inventory management strategies, as the field shifts towards more complex, data-driven approaches that incorporate uncertainty and dynamic environments.
  2. Static Decision-Making Models:
    The journal has seen fewer studies centered around static models that do not account for real-time data or changing conditions, indicating a move towards more adaptive and flexible decision-making frameworks.
  3. Purely Theoretical Frameworks:
    Research that is solely theoretical without empirical validation is becoming less common, as there is a clear preference for studies that demonstrate practical application and real-world relevance.

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