Computational and Mathematical Organization Theory

Scope & Guideline

Exploring the synergy of mathematics and organization in a complex world.

Introduction

Welcome to the Computational and Mathematical Organization Theory information hub, where our guidelines provide a wealth of knowledge about the journal’s focus and academic contributions. This page includes an extensive look at the aims and scope of Computational and Mathematical Organization Theory, highlighting trending and emerging areas of study. We also examine declining topics to offer insight into academic interest shifts. Our curated list of highly cited topics and recent publications is part of our effort to guide scholars, using these guidelines to stay ahead in their research endeavors.
LanguageEnglish
ISSN1381-298x
PublisherSPRINGER
Support Open AccessNo
CountryNetherlands
TypeJournal
Converge1995, from 2005 to 2024
AbbreviationCOMPUT MATH ORGAN TH / Comput. Math. Organ. Theory
Frequency4 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressVAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS

Aims and Scopes

The journal 'Computational and Mathematical Organization Theory' focuses on the intersection of computational methodologies and organizational theory, aiming to provide insights into complex social phenomena through rigorous modeling and analysis.
  1. Computational Modeling and Simulation:
    The journal emphasizes the use of computational models, including agent-based modeling and simulation, to explore and understand organizational dynamics and social behavior.
  2. Interdisciplinary Research:
    It encourages interdisciplinary approaches that blend insights from social sciences, management, mathematics, and computer science to address complex organizational challenges.
  3. Data-Driven Analysis:
    The journal highlights the importance of data analytics, particularly in the context of social networks and digital media, to inform organizational decision-making and strategy.
  4. Ethical and Social Implications:
    Research that delves into the ethical dimensions and societal impacts of technology, misinformation, and organizational behavior is a key focus, particularly as it pertains to current global issues.
  5. Dynamic Systems and Network Analysis:
    Investigations into network dynamics, including the spread of information and misinformation in digital environments, are central to the journal's contributions.
The journal has identified several emerging themes that reflect the evolving landscape of computational and mathematical organization theory, particularly in response to contemporary societal challenges.
  1. Misinformation and Disinformation Analysis:
    Research focused on the mechanisms of misinformation and disinformation, especially in social networks, has surged, highlighting the critical role of computational methods in understanding and mitigating these issues.
  2. COVID-19 Related Studies:
    There is a significant increase in studies related to the COVID-19 pandemic, particularly those that model information propagation and analyze the societal impacts of health crises.
  3. Agent-Based Modeling Applications:
    The use of agent-based modeling to explore complex interactions within organizations and society is on the rise, showcasing its utility in simulating real-world behaviors and outcomes.
  4. Ethics of Technology:
    Emerging discussions around the ethical implications of technology use, particularly in areas like gene editing and online extremism, indicate a growing concern for the societal impacts of organizational actions.
  5. Leadership and Organizational Dynamics:
    Research examining the dynamic effects of leadership styles and organizational behavior over time is gaining traction, reflecting a deeper interest in the interplay between leadership and employee outcomes.

Declining or Waning

While the journal continues to explore a variety of themes, certain areas have shown a decline in prominence in recent years, reflecting shifts in research focus and emerging priorities.
  1. Traditional Organizational Behavior Studies:
    There seems to be a waning interest in conventional studies of organizational behavior that do not incorporate computational or data-driven approaches, as the field increasingly favors more innovative methodologies.
  2. Static Models:
    Research employing static models of organizational analysis has decreased, with a shift towards dynamic and computational models that can better capture the complexities of real-world scenarios.
  3. Focus on Non-Digital Contexts:
    The relevance of studies focusing on non-digital or analog contexts in organizational theory appears to be declining, as the impact of digital transformation and online interactions becomes more central to research.
  4. Basic Statistical Methods:
    There is a noticeable reduction in the use of basic statistical methods without the integration of advanced computational techniques, as the field moves towards more sophisticated analytical tools.
  5. Descriptive Studies:
    The prevalence of purely descriptive studies without a strong theoretical framework or computational analysis is diminishing, as the journal seeks more rigorous and innovative contributions.

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