Journal of Modelling in Management

Journal of Modelling in Management


ISSN: 1746-5664

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CiteScore 2016: 0.85
CiteScoreTracker 2017: 0.39 (Updated Monthly)

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Editorial objective

Journal of Modelling in Management (JM2) provides a forum for academics and researchers with a strong interest in business and management modelling. The journal analyses the conceptual antecedents and theoretical underpinnings leading to research modelling processes which derive useful consequences in terms of management science, business and management implementation and applications.

Editorial criteria

JM2 is focused on the utilization of management data, which is amenable to research modelling processes, and welcomes academic papers that not only encompass the whole research process (from conceptualization to managerial implications) but also make explicit the individual links between 'antecedents and modelling' (how to tackle certain problems) and 'modelling and consequences' (how to apply the models and draw appropriate conclusions). The journal is particularly interested in innovative methodological and statistical modelling processes and those models that result in clear and justified managerial decisions.

Coverage

JM2 specifically promotes and supports research writing, that engages in an academically rigorous manner, in areas related to research modelling such as:

  • A priori theorizing conceptual models
  • Artificial intelligence, machine learning
  • Association rule mining, clustering, feature selection   
  • Business analytics: Descriptive, Predictive, and Prescriptive Analytics
  • Causal analytics: structural equation modeling, partial least squares modeling  
  • Computable general equilibrium models
  • Computer-based models
  • Data mining, data analytics with big data
  • Decision support systems and business intelligence
  • Econometric models
  • Fuzzy logic modeling
  • Generalized linear models
  • Multi-attribute decision-making models
  • Non-linear models
  • Optimization
  • Simulation models
  • Statistical decision models
  • Statistical inference making and probabilistic modeling
  • Text mining, web mining, and visual analytics
  • Uncertainty-based reasoning models

JM2's ethos is focused on the utilization of management data which is susceptible to research modelling processes. The main management disciplines from which submissions derive are:

  • Business analytics
  • Audit and accounting
  • Energy management and climate economics
  • Entrepreneurship
  • Financial engineering
  • Healthcare management
  • Human resource management and organizational behavior
  • Information systems management
  • Innovation management and technology management
  • International business management and small business management
  • Management Science
  • Medical informatics 
  • Operations management
  • Organizational systems
  • Performance management and productivity management
  • Risk management
  • Strategy and marketing
  • Supply chain management

Areas and Area Editors

Business Analytics and Big Data
Area Editor: Asil Oztekin, University of Massachusetts Lowell, USA
Business analytics is the process of transforming raw data into insightful decisions via descriptive analytics, predictive analytics, and prescriptive analytics. On the other hand, big data approaches enable the creation of knowledge that helps organizations make effective and efficient decisions in various business functions. The adoption of an analytics-driven culture and the use of big data approaches for decision-making has proven the potential to lead organizations towards sustainable competitive advantage. In line with this shift, the Business Analytics & Big Data area of JM2 is focused on studies where theoretical foundation development, novel applied and innovative methodological approaches are presented for improved managerial decision-making practices.

 
Quantitative Research Methods and Modeling in Marketing and Organizational Systems
Area Editor: Ajay Manrai, University of Delaware, USA
Research papers with conceptual, empirical, mathematical and theoretical orientation as well as those focusing on techniques, methods and applications are welcome. A wide range of marketing and organizational systems domains will be covered including consumer perceptions, consideration and choice, brand management and brand switching and loyalty behavior, cross-cultural research, international marketing research, market structure analysis, competitive analysis, marketing mix decisions, research concerning personnel selection, motivation and compensation, performance appraisal, training and development, human resource planning and human cognition.
 
Supply Chain and Operation Management
Area Editor: Qinglong Gou, The University of Science and Technology of China, China
Research papers on all aspects of operations research, management science, decision science and supply chain management, including: operations processes in manufacturing and service organizations, supply, demand and inventory management, manufacturing and service systems design and development, operations planning, scheduling and control, quality management, inpatient and outpatient services in health systems, optimizing logistics in health systems and supply chain management within hospitals.
 
Economic Models and Energy Management
Area Editor: Yi-Ming Wei, Beijing Institute of Technology, China
Research papers concerned with economics modelling and analysis of energy issues, including: economic theory, financial economics, computational economics, statistics, econometrics, operational research and strategic modelling of energy systems. Theoretical and empirical research papers on the measurement, analysis, and improvement of productivity.
 
Finance and Risk Management
Area Editor: Anatoliy Swishchuk, University of Calgary, CA
Research papers on links between mathematics, engineering, economics and finance, including business, economics and financial theory and application, financial and banking management, financial economics, mathematical methods and quantitative finance, and financial and marketing risk analysis.

Unique Attributes

JM2 is the only journal that supports multi-disciplinary study related to research modelling in business and management. JM2 actively encourages the advancement of knowledge and is committed to publishing research that provides sufficient clarity to produce unambiguous, testable and stable implications.

Key Journal Audiences

Research-led academics and researchers from the multi-disciplinary field of business and management and other related management fields who put an emphasis on the development of research models are the primary audience. Although most of these modelling approaches are predominantly quantitative, JM2 welcomes paper submissions constructed around the designing of pure theoretical and/or conceptual models and the combined use of quantitative and qualitative approaches and information for model-building and model validation. JM2 also targets key specialized practitioners – e.g. business analysts, system analysts, system engineers and business modellers.

This journal is indexed & abstracted in:

ABI/INFORM, Business Source Alumni Edition/Complete/Corporate Plus/Elite/Premier (EBSCO), Cabell's Directory of Publishing Opportunities in Management & Marketing, INSPEC, OCLC's Electronic Collections Online, ProQuest, ReadCube Discover, Scopus, Thomson Reuters Emerging Sources Citation Index (ESCI)

This journal is ranked by:

Australian Business Deans Council (ABDC) Quality Journal List, Australian Research Council (ERA Journal List), BFI (Denmark), ESSEC Rankings of Journals 2016,  JourQUAL 2.1 (Germany), NSD (Norway), Polish Scholarly Bibliography (PBN), The Publication Forum (Finland), Qualis (Brazil)

Journal of Modelling in Management is available as part of an online subscription to the Emerald Business, Management & Strategy eJournals Collection. For more information, please email collections@emeraldinsight.com or visit the Emerald Business, Management & Strategy eJournals Collection page.

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This journal is a member of and subscribes to the principles of the Committee on Publication Ethics. More on Emerald's approach is available in our Publication Ethics guidelines.
 

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