Journal of Management Information and Decision Sciences (Print ISSN: 1524-7252; Online ISSN: 1532-5806)

Research Article: 2017 Vol: 20 Issue: 1

Research Ideas for the Journal of Management Information and Decision Sciences

Chia-Lin Chang, Department of Applied Economics and Department of Finance National Chung Hsing University, Taiwan

Michael McAleer, Department of Quantitative Finance, National Tsing Hua University, Taiwan

Wing Keung Wong, Department of Finance and Big Data Research Center, Asia University, Taiwan

Journal of Management Information and Decision Sciences (JMIDS) is a highly reputable open access journal that is affiliated with the Allied Business Academies. JMIDS was inaugurated in 1998, and 2017 marks the 20th Anniversary of the journal. Consequently, JMIDS will publish a 20th Anniversary special issue, indicated as 20(A), as a single volume in 2017. The journal focuses on disseminating the latest discoveries and innovations comprising theoretical, conceptual and empirical research in Information Systems, Decision Sciences, and cognate disciplines.

Recent and innovative research in the fields of management information systems and decision sciences, and their roles in scientific and professional decision making, as well interactions with cognate disciplines, including Economics, Finance, Management, Management Science, Marketing, Statistics, Operations Research, and Engineering, are directed\\ly relevant for academics, researchers and practitioners alike.

JMIDS also caters to the needs of leading business executives and management who are actively involved in management, strategic and scientific decision making. The journal seeks academically rigorous papers that will appeal to theoreticians and also have direct relevance to policy makers and practitioners in management information and decision sciences.

Contributions that use rigorous analytical, mathematical and statistical methods based on panel data, cross section data, time series data, simulated numerical data, or case study data, in the empirical testing of theoretical models arising from management information and decision sciences, are strongly encouraged. Case studies that will enable portability of the findings in management information and decision sciences to academic, theoretical and practical research within the discipline, as well as across cognate disciplines, are also of serious interest.

JMIDS encompasses a wide spectrum of innovative topics in the disciplines of management information and decision sciences, and cognate disciplines that include, but are not restricted to, the following: 




Management Science


Accounting Research

Quantitative Methods

Time Series Analysis

Cross Section Data Analysis

Dynamic Panel Data Models



Operations Research


 Published articles in JMIDS have covered, but have not been restricted to, the following topics:

Sustainable Supply Chain Management

Collective Decision Making

Multi-Attribute Utility Theory

Information System and Decision Making

Fuzzy Models of Decision Making

Integer and Binary Programming

Linear Programming,

Quadratic Programming

Markov Processes

Mathematical Programming 

Multi-Tier Supply Chain Management

Dynamic and Naturalistic Decision Making 

General Decision Making 

Applications of Decision Aids 

Behavioural Aspects of Decision Making 

International Decision Making

North American Decision Making Framework 

Resource Dependence Theory 

Environmental Management Systems 

Marketing Information Systems

Financial Decision Making

Financial Risk Analysis

Financial Risk Management

Economic Decision Making

Financial Econometrics

Energy Economics

Energy Finance 

Renewable and Sustainable Energy 

Carbon Emissions 

Operations Research 


Financial Engineering


Some research areas of significant academic, theoretical, practical and public policy interest that are of substantial interest to JMIDS include, but are to restricted to, the following:

Information must be collected before it can be used to make sensible and optimal managerial and scientific decisions. Information in the sense of data can be collected in many different ways, including panel cross section, time series, numerical, and from case studies. This naturally leads to considerations of Big Data, which is a growing phenomenon, and needs to be understood clearly and carefully before achieving optimal development strategies based on managerial and decision science theory.

 Big Data can be defined as involving two components, the first of which is Computer Software. Data sets can be so complex that standard computer software for dealing with them are inadequate. Consequently, new computer software and hardware facilities, such as increasing the size of memory on computer software, faster computers, expanding the capacity of standard commercial software, bootstrap methods, numerical calculation, and optimal subsampling algorithms, need to be developed.

The second component in the analysis of Big Data is the use of Data Analytics that require novel and advanced techniques for purposes of processing, locating, searching, discovering, capturing, checking, storing, updating, protecting, retrieving, sending, sharing, transferring, receiving, extracting, estimating, modelling, evaluating, and predicting Big Data

The application of innovative developments in computer software and data analytics are especially important for analysing and testing theoretical models and approaches in management information and decisions sciences. Data can arise from panels, cross sections, time series, numerical analysis, and case studies need to be understood. Big data issues arising from such data sources, especially countably finite but exhaustive data sets that can be downloaded from the internet, need to be understood and managed sensibly and carefully. The interactions between the availability of information for managerial and scientific decisions are reached have never been more daunting or challenging.


As can be seen from the above suggestions, there are numerous possible research topics that arise from the disciplines of managerial information and decision sciences, and numerous cognate disciplines, that can be applied to analyse important and critical issues related to the topical issues published in JMIDS.

The journal is confident that academics, researchers, advanced graduate students, practitioners and policy makers can create, develop, establish and use many more exciting research topics that use a wide range of possible data options to estimate and test academic and intellectual theories, and evaluate empirical regularities and practical case studies in management information and decision sciences.

The editorial staffs at JMIDS hopes that these and other important areas of research in management information and decision sciences, and cognate disciplines, will attract interesting, high quality, innovative and challenging submissions.


It is a genuine challenge, and an honour and pleasure for the four co-editorialists to have been appointed the Co-Editor-in-Chief, Chair of the Editorial Board, Co-Editor-in-Chief, and Editor-in-Chief, respectively, of the Journal of Management Information and Decision Sciences (JMIDS).

We look forward to working with the active and vibrant members of the International Advisory Board, Editorial Board, extensive reviewing panels, and contributors to make JMIDS an accessible and leading outlet for high quality academic, theoretical, and practical research in all areas of management information and decision sciences, and their relationships to cognate disciplines. For financial support, the authors wish to thank the National Science Council, Ministry of Science and Technology (MOST), Taiwan, and the Australian Research Council.

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