Journal of Modelling in Management

Scope & Guideline

Transforming Theoretical Insights into Practical Solutions.

Introduction

Explore the comprehensive scope of Journal of Modelling in Management through our detailed guidelines, including its aims and scope. Stay updated with trending and emerging topics, and delve into declining areas to understand shifts in academic interest. Our guidelines also showcase highly cited topics, featuring influential research making a significant impact. Additionally, discover the latest published papers and those with high citation counts, offering a snapshot of current scholarly conversations. Use these guidelines to explore Journal of Modelling in Management in depth and align your research initiatives with current academic trends.
LanguageEnglish
ISSN1746-5664
PublisherEMERALD GROUP PUBLISHING LTD
Support Open AccessNo
CountryUnited Kingdom
TypeJournal
Convergefrom 2006 to 2024
AbbreviationJ MODEL MANAG / J. Model. Manag.
Frequency3 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressFloor 5, Northspring 21-23 Wellington Street, Leeds, W YORKSHIRE LS1 4DL, ENGLAND

Aims and Scopes

The Journal of Modelling in Management focuses on the integration of advanced modeling techniques and management practices to address complex problems in various sectors. The journal aims to present innovative methodologies that enhance decision-making processes and improve operational efficiencies across diverse fields such as supply chain management, finance, and organizational behavior.
  1. Supply Chain Management:
    The journal extensively covers topics related to supply chain optimization, resilience, and sustainability, focusing on innovative modeling techniques like mixed-integer programming, simulation, and fuzzy logic.
  2. Decision-Making Models:
    It emphasizes the development and application of decision-making frameworks, including multi-criteria decision-making (MCDM) and data envelopment analysis (DEA), aiding organizations in making informed choices.
  3. Financial Modeling and Risk Assessment:
    Research in this area includes financial performance prediction, risk management strategies, and the impact of economic factors on organizational behavior, often utilizing machine learning and statistical methods.
  4. Sustainability and Circular Economy:
    A significant focus is on sustainable practices within supply chains and organizations, exploring frameworks that promote environmental responsibility and circular economy principles.
  5. Technology Integration in Management:
    The journal addresses the implications of emerging technologies such as artificial intelligence and blockchain on management practices and decision-making processes.
  6. Behavioral and Psychological Aspects of Management:
    It investigates the human factors influencing organizational effectiveness, including leadership, employee engagement, and consumer behavior.
Recent publications in the Journal of Modelling in Management highlight emerging themes and trends that reflect the evolving landscape of management practices and research methodologies. These trends indicate a growing interest in innovative approaches and interdisciplinary research.
  1. Artificial Intelligence and Machine Learning:
    There is a significant increase in research applying AI and machine learning techniques to improve decision-making processes across various sectors, emphasizing the need for data-driven insights.
  2. Sustainable Supply Chain Practices:
    A growing emphasis on sustainability is evident, with many studies exploring innovative approaches to enhance ecological responsibility and resilience in supply chains.
  3. Digital Transformation and Industry 4.0:
    Research on the implications of digital technologies and Industry 4.0 frameworks is trending, focusing on how these advancements reshape management practices and operational efficiencies.
  4. Behavioral Insights in Management:
    Emerging themes include the exploration of psychological factors and behavioral economics in organizational decision-making, highlighting the importance of human behavior in management strategies.
  5. Collaborative and Networked Approaches:
    There is a trend towards collaborative models that emphasize the importance of partnerships and networks in achieving strategic objectives, particularly in logistics and supply chain management.

Declining or Waning

As the Journal of Modelling in Management evolves, certain themes have shown a decrease in emphasis, reflecting shifts in research priorities and emerging trends in the field. The following areas are becoming less prevalent in recent publications.
  1. Traditional Manufacturing Techniques:
    Research focusing on conventional manufacturing processes and methodologies is declining as the industry shifts towards automation and advanced manufacturing technologies.
  2. Static Financial Models:
    There has been a noticeable waning in the relevance of static financial models that do not account for dynamic market conditions, as researchers increasingly favor models that incorporate real-time data and adaptability.
  3. Basic Predictive Analytics:
    While predictive analytics remains important, basic models without sophisticated algorithms or machine learning techniques are less frequently published, indicating a move towards more complex methodologies.
  4. Non-Integrated Approaches to Supply Chain Management:
    Standalone studies that do not consider the integrated nature of supply chains and their interconnectedness are becoming less common, as holistic views are favored.
  5. Focus on Localized Case Studies:
    There is a trend away from localized case studies that do not contribute to broader theoretical frameworks, as the journal seeks research that provides generalizable insights.

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