Forthcoming 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 Articles will not be published until the final proofs are validated by their authors.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 also listed here. 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 (2 papers in press)

Regular Issues

  • On the stimulus of energy efficiency investments: web-based decision support and assessment tools   Order a copy of this article
    by Charikleia Karakosta, Filippos Dimitrios Mexis, Aikaterini Papapostolou, John Psarras 
    Abstract: A major factor causing climate change is the continuous increase in energy consumption. One of the best methods to reduce energy use is mainstreaming energy efficiency (EE) financing. Modernising the building stock and business techniques is considered essential for upscaling EE levels. The proposed methodology introduces methods, typologies and decision support tools to assess and benchmark EE investments, creating a unified framework. The decision support systems developed are part of the Triple-A Tools, which supports EE business actors to assess and classify different investment ideas in terms of crucial EE economic, macroeconomic and sustainability parameters. Also, the tools assist in the selection of the most profitable solutions, linking them with cutting-edge green finance strategies. The results are presented via the Triple-A Database, which incorporates EE financing fundamental data, contributing to intensifying the value chain of EE investments. The Triple-A Tools introduces an integrated strategy targeted to EE key players, involving them effectively in the process. As a result, this strategy and tools provide a central hub to assess, benchmark and fund green investments.
    Keywords: energy transition; energy efficiency; green investments; risk assessment; stakeholder consultation; benchmarking; decision support systems.
    DOI: 10.1504/IJDSS.2026.10076484
     
  • Development of a future value estimation-based decision support system for evaluating the financial performance of the Turkish sector   Order a copy of this article
    by Yusuf Tansel İç, Emin Kabacaoğlu, Çağlar Tümay 
    Abstract: In this study, we develop a decision support system (DSS) using the AHP and TOPSIS methods. We use the published financial ratios of the Central Bank of the Republic of Turkey (CBRT) to calculate the sectorial financial performance scores. Based on the three-year trend, we estimate the future years financial ratios. The estimated ratios are subsequently transformed into AHP-TOPSIS values to obtain sectorial ranking scores. Additionally, we developed a decision support system using the Excel-Visual Basic program. The forecasting module of the developed DSS provides an important advantage in predicting next years financial ratios for different sectors using data from the previous year. For the first time, this study demonstrates the application of the AHP-TOPSIS-Regression model to calculate sectorial financial performance scores. The presented DSS contributed to determining a quickly convertible performance measurement tool in real-life financial environments.
    Keywords: financial ratios; financial performance measurement; AHP; TOPSIS; decision support system; DSS; dynamic economic conditions; sector analysis.
    DOI: 10.1504/IJDSS.2026.10077903
     

 

Return to top