Forthcoming and Online First Articles

International Journal of Decision Support Systems

International Journal of Decision Support Systems (IJDSS)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

Forthcoming articles must be purchased for the purposes of research, teaching and private study only. These articles can be cited using the expression "in press". For example: Smith, J. (in press). Article Title. Journal Title.

Articles marked with this shopping trolley icon are available for purchase - click on the icon to send an email request to purchase.

Online First articles are published online here, before they appear in a journal issue. Online First articles are fully citeable, complete with a DOI. They can be cited, read, and downloaded. Online First articles are published as Open Access (OA) articles to make the latest research available as early as possible.

Open AccessArticles marked with this Open Access icon are Online First articles. They are freely available and openly accessible to all without any restriction except the ones stated in their respective CC licenses.

Register for our alerting service, which notifies you by email when new issues are published online.

International Journal of Decision Support Systems (4 papers in press)

Regular Issues

  • Decision support system applications (1980-2022). Classification and statistical analysis   Order a copy of this article
    by Panagiotis I. Mallios, Nikolaos F. Matsatsinis 
    Abstract: The main goal of decision support system applications (DSS), is to aid decision makers by collecting data and information into their structured environment, in order t take an optimal decision. They are developed to accomplish several tasks, that is, organise the overflow of data, knowledge and information, provide support to decision makers and illustrate their judgment and preferences. The purpose of the current survey is the categorisation and classification of DSS applications according to specific criteria and finally their statistical analysis according to special characteristics that may have. This paper provides a review of DSS applications over the period (January 1980-June 2022). Seven hundred and sixty published applications are identified.
    Keywords: decision support systems; DSS; survey; classification; statistical analysis.
    DOI: 10.1504/IJDSS.2024.10061753
     
  • Recommender system application for maritime crew recruiting and scheduling operations   Order a copy of this article
    by Panagiotis Mamatsis, Spiros Chountasis 
    Abstract: Registration and screening of personnel by shipping firms is a crucial process that is currently being studied. The aim of this research is to develop an optimised and automatic process for identifying the best option for crew assignment and scheduling based on a recommender system. A new model is proposed to capture the various constraints and objectives encountered in crew assignment and scheduling problems. The model is hosted on a recommender system. Its architecture can handle large amounts of data and complex computations. A case study has been successfully simulated. The results of the developed technique have been presented and evaluated proving that our approach can efficiently and accurately resolve the vessel scheduling issue for an entire crew list.
    Keywords: recommendation systems; OR in maritime industry; shipping crew scheduling; crew assignment.

Special Issue on: HELORS-2023 Decision Support Systems and Smart Technologies

  • Advanced preprocessing methods for large-scale data envelopment analysis models   Order a copy of this article
    by Terezia Fulova, Maria Trnovska, Lenka Filova 
    Abstract: The traditional approach to applying a data envelopment analysis (DEA) model for a given data set is sufficient, provided the data cardinality (the number of decision-making units) is small. If the data cardinality increases significantly, solving a DEA model in a reasonable time becomes problematic. The main idea behind some of the known approaches for solving large-scale DEA models is to efficiently detect a small subset of units generating the technology set, which is performed during the preprocessing phase. In this paper we introduce new preprocessing methods based on finding the minimum-volume enclosing ellipsoid.
    Keywords: data envelopment analysis; DEA; large-scale datasets; pre-processing methods; minimum-volume enclosing ellipsoid.

  • Factors affecting manual assembly lines with an overview of multiple criteria decision-making perspective   Order a copy of this article
    by Rhitankar Saha Roy 
    Abstract: UK Manufacturing is a key player in the global economy. However, the same industries also contribute vastly to the GHG emissions. This is an issue for manufacturing companies that are trying to achieve the UN Sustainability Goals. Technological advancements brought rapid advancement in manufacturing; however, research shows that industries continue to rely on manual labour. As industries try to meet sustainability goals with the challenges faced through manual operations, this paper explores the different criteria, and the different multi-criteria decision-making (MCDM) models that can be used for analysing the alternative solutions against those criteria. The paper compares old and newly constructed MCDM methods used in manufacturing problems and provides an understanding of the pros of cons of the methods. It then develops a new MCDM framework that will be used for the first time for solving a multi-criteria problem related to manufacturing and organisational sustainability.
    Keywords: sustainability; manufacturing; factors; manual assembly; MCDM; DSS.

 

Return to top