Decision Making in Uncertain Environments via Advanced Analytical Methods: Second Edition

A special issue of Systems (ISSN 2079-8954). This special issue belongs to the section "Systems Practice in Social Science".

Deadline for manuscript submissions: 30 June 2026 | Viewed by 561

Special Issue Editors


E-Mail Website
Guest Editor
Department of Shipping Trade and Transport, Business School, University of the Aegean, Korai 2A Str., 82100 Chios, Greece
Interests: engineering economics; project management; financial engineering; fuzzy logic; quantitative methods; project appraisal; crisis management; performance management
Special Issues, Collections and Topics in MDPI journals
School of Economics and Management, Dalian University of Technology, Dalian 116024, China
Interests: group decision making; linguistic decision making; fuzzy set; multi-criteria decision making
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Decision making is a process of choosing a particular direction or course that involves a combination of directions among a finite or non-finite set of alternatives. Decision making is not only applicable in many fields, but it is also a necessary condition to achieve reliable results in most applied sciences (finance/economics, engineering, management, health sciences, environmental sciences, etc.). Modern and efficient tools in the decision-making process are advanced analytical methods, especially in environments with inherent uncertainty. In these constantly evolving environments, there are multiple determinants of decisions, and their weights are vague and changing. For this reason, deploying advanced analytical methods is considered to be effective and efficient in the scientific field of decision analysis. These methods may include (indicatively) the following:

  • Fuzzy sets and fuzzy logic:
    • Fuzzy arithmetic;
    • Fuzzy statistics;
    • Fuzzy probabilities;
    • Fuzzy multi-criteria analysis;
    • Fuzzy regression.
  • Scenario analysis:
    • Exploratory scenario analysis;
    • Predictive scenario analysis (time series, regression analysis, etc.);
    • Qualitative scenario analysis (the Delphi method, narrative scenarios, etc.);
    • Quantitative scenario analysis (probabilistic scenarios, stress testing, etc.).
  • Decision analysis:
    • Decision trees;
    • Utility theory.
  • Statistical inference:
    • Hypothesis testing;
    • Bayesian inference.
  • Mixed methods.

During the decision-making process, these methods can be used individually or in combination depending on the nature, complexity, and duration of the problem under examination and its effects on its immediate environment. In this Special Issue, authors can publish articles in the following subjects (indicatively):

  • Finance and investments;
  • Business administration;
  • Performance management;
  • Revenue management;
  • Managerial accounting;
  • Engineering risk analysis;
  • Project management;
  • Environmental planning;
  • Blue economy;
  • Maritime transport systems;
  • Sustainable Development Goal (SDG) achievement;
  • Crisis/disaster management;
  • Innovation and technology management;
  • Public policy and administration;
  • Education and academia;
  • Health sciences.

Dr. Konstantinos A. Chrysafis
Dr. Zhen Zhang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Systems is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • decision making
  • fuzzy sets and fuzzy logic
  • scenario analysis
  • decision analysis
  • statistical inference
  • mixed methods

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Related Special Issue

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

41 pages, 485 KB  
Article
F-DeNETS: A Hybrid Methodology for Complex Multi-Criteria Decision-Making Under Uncertainty
by Konstantinos A. Chrysafis
Systems 2025, 13(11), 1019; https://doi.org/10.3390/systems13111019 - 13 Nov 2025
Viewed by 291
Abstract
In the modern business environment, where uncertainty and complexity make decision-making difficult, the need for robust, transparent and adaptable support tools is highlighted. The proposed method, named Flexible Decision Navigator for Evaluating Trends and Strategies (F-DeNETS), offers a complementary perspective to classic Artificial [...] Read more.
In the modern business environment, where uncertainty and complexity make decision-making difficult, the need for robust, transparent and adaptable support tools is highlighted. The proposed method, named Flexible Decision Navigator for Evaluating Trends and Strategies (F-DeNETS), offers a complementary perspective to classic Artificial Intelligence (AI), Big Data and Multi-Criteria Decision-Making (MCDM) tools. Despite their broad use, these methods frequently suffer from critical sensitivities in the weighting of criteria and the handling of uncertainty, leading to compromised reliability and limited practical utility in environments with limited data availability. To bridge this gap, F-DeNETS integrates intuition and uncertainty into a transparent and statistically grounded process. It introduces a balanced approach that combines statistical evidence with human judgment, extending the boundaries of classic AI, Big Data and MCDM methods. Classic MCDM methods, although useful, are sometimes limited by subjectivity, staticity and dependence on large volumes of data. To fill this gap, F-DeNETS, a hybrid framework combining Fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL), Non-Asymptotic Fuzzy Estimators (NAFEs) and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), transforms expert judgments into statistically sound fuzzy quantifications, incorporates dynamic adaptation to new data, reduces bias and enhances reliability. A numerical application from the shipping industry demonstrates that F-DeNETS offers a flexible and interpretable methodology for optimal decisions in environments of high uncertainty. Full article
Back to TopTop