Decision Models for Economics and Business Management

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Theory and Methodology".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 217

Special Issue Editors


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Guest Editor
1. VALORIZA—Research Center for the Valorization of Endogenous Resources, BioBIP Building, Polytechnic Campus, 10, 7300-555 Portalegre, Portugal
2. Department of Economic and Organizational Sciences, ESTGD—Higher School of Technology, Management and Design, Portalegre Polytechnic University, Polytechnic Campus, 10, 7300-555 Portalegre, Portugal
3. CEFAGE, IIFA, University of Évora, Largo dos Colegiais 2, 7004-516 Évora, Portugal
Interests: cryptocurrencies; econophysics; financial markets; financial contagion; financial integration
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
1. CEFAGE, IIFA, University of Évora, Largo dos Colegiais 2, 7004-516 Évora, Portugal
2. Department of Management, School of Social Sciences, University of Évora, Largo dos Colegiais 2, 7004-516 Évora, Portugal
Interests: econometrics; econophysics; financial markets; fuzzy models; data analysis
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
1. VALORIZA—Research Center for the Valorization of Endogenous Resources, BioBIP Building, Polytechnic Campus, 10, 7300-555 Portalegre, Portugal
2. Department of Economic and Organizational Sciences, ESTGD—Higher School of Technology, Management and Design, Portalegre Polytechnic University, Polytechnic Campus, 10, 7300-555 Portalegre, Portugal
3. CEFAGE, IIFA, University of Évora, Largo dos Colegiais 2, 7004-516 Évora, Portugal
Interests: econophysics; financial markets; time series analysis; financial contagion; financial integration; data analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Financial markets and business environments are complex, fast-evolving systems with high levels of uncertainty, rendering most traditional decision-making frameworks unable to address these uncertainties and complexities. This Special Issue aims to highlight the most recent advances in decision models in economics and business management, focusing on innovative approaches to improve decision-making processes. Advanced models that integrate risk management, optimization techniques, stochastic processes, and simulation methods are increasingly important due to the growing volatility and interconnectedness of global markets. This Special Issue seeks to publish the latest research offering theoretical advances, empirical analysis, or practical applications in decision theory, game theory, computational intelligence, and simulation, with a focus on their application to financial markets, corporate strategy, and operational management, among others. It also welcomes interdisciplinary approaches that provide new insights into econophysics, information theory, data science, and simheuristics. Combining methodologies and perspectives from various schools of thought will allow for a comprehensive view of both the current state and future prospects of decision models in economics and business management, leading to a deeper understanding and more effective decision-making strategies.

Dr. Dora Almeida
Dr. Andreia Dionísio
Prof. Dr. Paulo Ferreira
Dr. Dimitris Apostolou
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 100 words) can be sent to the Editorial Office for announcement on this website.

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. Information 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 1600 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 models
  • economics
  • business management
  • risk management
  • optimization
  • financial markets
  • econophysics
  • information theory
  • computational intelligence
  • simulation
  • data science

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Published Papers (1 paper)

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Research

23 pages, 812 KiB  
Article
Innovation in Manufacturing Within the Digital Intelligence Context: Examining Faultlines Through Information Processing
by Kangli Zhang and Jinwei Zhu
Information 2025, 16(5), 346; https://doi.org/10.3390/info16050346 - 25 Apr 2025
Viewed by 168
Abstract
In the context of digital intelligence, innovation is vital for manufacturing enterprises to establish sustainable competitive advantages. As the cornerstone of decision-making, the information-processing capability of top management teams plays an essential role in driving organizational success. Using panel data from A-Share manufacturing [...] Read more.
In the context of digital intelligence, innovation is vital for manufacturing enterprises to establish sustainable competitive advantages. As the cornerstone of decision-making, the information-processing capability of top management teams plays an essential role in driving organizational success. Using panel data from A-Share manufacturing listed companies between 2015 and 2023, we conducted programming in the R language employing hierarchical clustering and k-means algorithms for faultline grouping calculations. The empirical analysis portion utilized STATA software, where the Hausman test was implemented to determine the use of a fixed-effects model for computation. The results demonstrate that task-related faultlines, driven by factors such as educational background, tenure, career experience, and years of service, have a positive impact on innovation performance. In contrast, relationship-related faultlines influenced by gender and age exhibit a negative effect. Furthermore, long-term investment decision preferences mediate the relationship between faultlines and innovation performance. Performance expectation gaps amplify the positive influence of task-related faultlines and mitigate the negative effects of relationship-related faultlines. In comparison with the majority subgroup, when the chairperson is part of a minority subgroup, the faultline has a more significant impact on innovation performance. This study presents a novel framework for fostering innovation within the manufacturing industry under the digital intelligence context. By combining R programming with empirical analysis, we thoroughly examine how the characteristics of top management teams’ faultlines influence innovation performance through an information processing perspective. Our findings provide actionable insights for optimizing executive structures and aligning decision-making strategies, thereby advancing organizational effectiveness. Full article
(This article belongs to the Special Issue Decision Models for Economics and Business Management)
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