Management Science Advances (MSA) publishes high quality scientific papers that contribute significantly to the fields of management sciences. The material published is of high quality and relevance, written in a manner which makes it accessible to all of this wide-ranging readership. Preference will be given to papers with management and decision making implications to the practice of management and engineering. MSA covers all aspects of decision making in sustainable development, risk management, supply chain management, sustainability and supply chain management, transportation networks and operations management. Submissions should present the state of the art in specific fields or functions of management, while there are shorter critical assessments of particular management techniques. Preference will be given to papers with implications to the practice of management. Full experimental and methodical details must be provided so that the results can be reproduced. Submissions of purely theoretical papers are discouraged. Contents include papers exploring the interactions of management techniques with other relevant disciplines such as decision making, artificial intelligence, soft computing and computer science. This is a unique feature of MSA compared to other existing management journals, providing a means to explore new directions in management research in a interdisciplinary context. Overview papers from eminent scientists in significant fields of management that review the state-of-the-art in these fields, are also welcome. General Journal guidelines for authors Management Science Advances publishes research articles, reviews, short communications, and case studies. Research articles must include: motivation for the work, an adequate overview of the representative work in the field including up-to-date references, a clear statement of the novelty in the presented research, suitable theoretical background, one or more examples to demonstrate and discuss the presented ideas and, finally, conclusions. Short communications are usually 4-7 pages long, research articles and case studies 8-14 pages, while reviews can be longer. Page number limits are not strict and, with appropriate reasoning, the submitted articles can also be longer or shorter. Authors are requested to follow the MSA guidelines and strictly format their manuscripts as per the article template that is available here. If extensions of previously published conference papers are submitted, Editors will check if sufficient new material has been added to fulfill the journal standards and qualify the submission for the review process. The added material must have not been previously published. New results are desired but not necessarily required; however, the submission should contain expansions of key ideas, examples, elaborations, etc. of the conference submission. Aims and Scope: The principal aim of the journal is to bring together the latest research and development in various fields of decision science. We would like to highlight that papers should refer to Aims and scope, but they are not limited to. Publication Frequency: One issue per year is published online, but processed and accepted papers, with full bibliographic data, are added to the issue continuously over the whole year. Open Access: This is an open-access journal which means that all content is freely available without charge to the user or his/her institution. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles in this journal without asking prior permission from the publisher or the author. eISSN (Online): 3042-2205 Publication fee: There is no submission charge or publication fee. Publication in MSA is free of charge for the authors. Publisher: Scientific Oasis Tekeriška 28a, 11000 Belgrade, Serbia Tel. +38164-23-77-908 Email: office@scientificoasis.org Indexing: Google Scholar; ROAD; Crossref; doiSerbia;
Examining Work-Life Balance and Its Effect on Employee Commitment: A Case Study of International Breweries PLC
This study examined the effects of work-life balance on employee commitment advances, focusing on International Breweries PLC in Lagos State. The research aimed to assess how leave policies, flexible working arrangements, and wellness programmes influence employee commitment. Data were collected using a structured questionnaire distributed to a sample of 334 respondents, selected through convenience sampling techniques. The primary research instrument is the questionnaire, which includes specific questions aligned with the study's objectives. Both independent and dependent variables are measured using a five-point Likert scale. Data analysis was conducted using the Statistical Package for Social Science (SPSS), version 21.0. Correlation and multiple regression analysis are applied to test the hypotheses. The findings indicate a positive relationship between work-life balance and employee commitment. Based on these results, the study recommends that management should prioritize initiatives that support employees in balancing their work and personal lives. This approach also enhances employee commitment and contributes to organizational success.
Copyright (c) 2025 Alaba Victor Oyakhire (Author) https://creativecommons.org/licenses/by/4.0
Modern Information and Communication Technology Platforms: Advancing SecuDroneComm Management
The rapid advancement of information and communication technology (ICT) solutions has significantly changed the landscape of secure communication systems, especially in scenarios involving unmanned aerial vehicles (UAVs) and real-time data exchange. SecuDroneComm, a hybrid platform created for secure, low-latency communication between drones and command centers, represents an innovative management approach to tackling issues related to data security, latency, and scalability. This paper provides a thorough comparative analysis of SecuDroneComm alongside leading ICT platforms, including ITU-T X.805 frameworks, SmartNet architecture for energy systems, and federated global identity frameworks for mobile and wireless communications. By exploring these systems, we pinpoint essential design principles and innovations that have influenced secure management communication platforms, with a focus on encryption, data integrity, server architecture, and hybrid deployment strategies. The findings highlight the platform's flexibility in managing critical situations like battlefield intelligence, disaster response, and public health monitoring. Additionally, the analysis investigates possible improvements, such as the integration of 5G technologies, blockchain for data validation, and enhanced access control systems. SecuDroneComm’s cutting-edge architecture, which merges security with real-time responsiveness, provides notable benefits compared to both traditional and modern platforms, meeting the changing demands.
Information and Communication Technology Platforms
Copyright (c) 2025 Rexhep Mustafovski (Author) https://creativecommons.org/licenses/by/4.0
FinTech and the Level of Its Adoption in Different Countries Around the World
FinTech, or Financial Technology, refers to the use of modern technologies in the financial and banking sectors to improve and facilitate financial services. The adoption of this technology is rapidly increasing in many advanced societies. Investment in FinTech has surged in recent years, with key factors driving this growth including the rising demand for digital financial services, the rapid growth of the digital economy, the increasing popularity of blockchain technologies and cryptocurrencies, and, ultimately, supportive regulations for the FinTech industry. FinTech has expanded significantly in countries worldwide, especially in Asian nations and developing economies. In this study, we first provide an overview of FinTech, its objectives, and the necessary infrastructure for its implementation and then briefly discuss the extent of its development and adoption in various countries, followed by a review of several studies conducted by researchers in the FinTech field. Finally, we conclude with a discussion of the challenges faced in the development and investment in FinTech.
Copyright (c) 2025 Elaheh Rivandi (Author) https://creativecommons.org/licenses/by/4.0
Sustainability as a Management Strategy: Integrating Environmental, Social, and Governance Practices into Business Administration
The article discusses the way in which sustainability can be viewed as an integrated part of the organizational strategy by incorporating environmental, social, and governance (ESG) practices into core components of business administration. When ESG is seen as a strategic framework versus compliance, the corporation will develop corporate resilience, build stakeholder trust, and increase long-term profitability. The study addresses the theoretical aspects of ESG with respect to strategic management and describes how ESG integration affects decision-making throughout administrative, financial, and operational functions. By synthesizing current literature, the paper highlights how effective ESG adoption contributes to innovation, competitiveness, and alignment with the United Nations Sustainable Development Goals. It also discusses the barriers organizations face, such as limited standardization, high implementation costs, and cultural resistance. The findings emphasize that embedding ESG into business administration is essential for organizations seeking sustainable growth, improved governance, and long-term stakeholder value in an increasingly dynamic global market.
Environmental, Social, and Governance Practices
Copyright (c) 2025 Mohamed Ibrahim Hassan Farag (Author) https://creativecommons.org/licenses/by/4.0
Behavioral Biases and Investment Management Decisions: The Mediating Role of Risk Perception and the Moderating Role of Financial Literacy
The purpose of the study is to explore the impact of behavioral biases on the investment decisions of individual investors of the Pakistan Stock Exchange, with the mediation and moderation mechanism. The study employs both theoretical and empirical evidence to examine the influence of behavioral biases in deviating from the conventional model of investment decision. Data is analyzed with the help of SmartPLS software drawn from a sample of 297 responses. The study finds that self-attribution bias, confirmation bias, regret aversion, and framing bias significantly influence investment decisions through risk perception. Self-attribution bias and regret aversion bias have a significant direct effect on investment decisions. The confirmation bias and framing bias show no significant direct impact. Research indicates that financial literacy does not moderate the link between risk perception and investment decisions. The study offers deeper insight into investor psychology and advances the decision-making process. It aims to help investors, policymakers, and management science advisors improve the performance on stock markets.
Copyright (c) 2025 Iraj Khalid, Lubna Riaz (Author) https://creativecommons.org/licenses/by/4.0
The Role of SWOT Analysis in Enhancing Business Growth and Long-Term Management Sustainability
This article talks about the strategic importance of SWOT analysis as an important tool to develop business growth and to promote sustainability in the long term. By examining practically every aspect of the four dimensions (strength, weakness, opportunity, and threat), SWOT provides organizations with a relevant way to evaluate their internal capabilities to adapt to the external world. The article highlights the SWOT framework, implications for driving business growth, and implications for supporting sustainability efforts. Within each of the components, the article outlines how SWOT provides firms the opportunity to obtain competitive advantages as well as to link corporate objectives to global sustainable development goals in general. Finally, the article concludes that SWOT analysis remains timely and relevant in the ever-changing business environment today.
Copyright (c) 2025 (Author) https://creativecommons.org/licenses/by/4.0
Formula-based Architectural Framework of the SecuDroneComm Platform for Unmanned Aerial Vehicle Communications
The SecuDroneComm platform is designed to provide secure, reliable, and efficient communication between drones and the tactical operations center. Its architecture integrates data integrity, encryption efficiency, energy optimization, collision avoidance, and real-time processing through a mathematical framework of dedicated formulas. The platform ensures that critical mission data is protected from tampering, transmitted with minimal delay, and prioritized based on urgency and network stability. By applying specialized formulas, such as the drone data integrity formula, encrypted data transmission efficiency formula, and data prioritization index, the platform strengthens communication security and improves decision-making in operational environments. Additional formulas address challenges of battery optimization, multi-drone coordination, network congestion, and system reliability, ensuring resilient operations during missions. The integration of YOLOv8 within the platform enhances object detection by balancing accuracy and inference speed, supported by GPU load analysis and bandwidth allocation models. The hybrid server structure optimizes latency, resource distribution, and encryption key management, creating a unified solution for real-time unmanned aerial vehicle surveillance. This paper presents the complete formula-based framework of SecuDroneComm, demonstrating its capability to improve operational efficiency, cybersecurity resilience, and mission sustainability in dynamic and high-risk environments.
Integrated Reporting Quality as a Determinant of Financial Performance: Evidence from Emerging and Developed Markets
This study aims to clarify the effects of integrated reporting quality (IRQ) on financial performance indicators. To do so, this paper is based on measuring IRQ by scoring integrated reports of 82 firms with a 328-firm observation from both emerging and developed markets, where they published integrated reports or integrated annual reports between 2019 and 2022. This study is based on a scoring method that considers the elements of the entire integrated reporting (IR) framework to measure quality and various financial performance indicators. The research brings originality to the literature due to the lack of uniformity among studies, especially in industry and market effects settings, to reveal meaningful results. Unlike the existing literature, the results of this paper are more reliable and consistent, depending on the use of panel data analysis and an endogeneity check. The findings show that a significant relationship exists between IRQ and "return on assets", "return on equity", and "earnings per share" in a varying degree of impact, where "board size" and "audit committee meeting" have no impact. There are no significant differences in whether the integrated reporters are located in emerging or developed markets. Therefore, strict application of the IR framework is essential to ensure IR quality, leading to improved financial performance regardless of the distinction between emerging and developed markets. Firms should consider the IR framework in their practices as a way to improve quality and to be transparent and accountable.
Copyright (c) 2025 Mert Sarioglu, Engin Ozsoz, Vladimir Simic, Karahan Kara (Author) https://creativecommons.org/licenses/by/4.0
A Reconsideration Note of the Mathematical Frameworks for Fuzzy and Neutrosophic Risk Management
Uncertainty modeling underpins decision-making across diverse domains, and over the years a rich array of theoretical frameworks has emerged to capture its many facets. Notable among these are Fuzzy Sets, Rough Sets, Hyperrough Sets, Vague Sets, Intuitionistic Fuzzy Sets, Hesitant Fuzzy Sets, Neutrosophic Sets, and Plithogenic Sets, alongside ongoing advances in hybrid and higher-order uncertain frameworks. Risk management—the systematic process of identifying, quantifying, and mitigating potential losses—is indispensable in contexts ranging from project planning and system engineering to business operations. Although fuzzy-logic approaches to risk assessment have been widely studied, existing treatments often lack fully formalized, probability-theoretic foundations. In this paper, we introduce rigorously defined mathematical frameworks for fuzzy risk management and for neutrosophic risk management. Each framework extends the classical risk-optimization model by embedding fuzzy or neutrosophic membership structures into coherent risk measures, thereby enabling graded preference analysis and enhanced expressiveness. Our formulations not only generalize the crisp risk-management paradigm but also provide a unified basis for future theoretical developments and practical applications of fuzzy and neutrosophic risk models.
Copyright (c) 2025 Takaaki Fujita (Author) https://creativecommons.org/licenses/by/4.0
Machine Learning in the Service of Mental Health Management: Optimization Metaheuristics for Improving Disorder Classification
Mental health awareness has become an increasingly pressing societal issue in recent years. Many individuals struggle with undiagnosed disorders, leading to a significantly reduced quality of life. Consequently, timely diagnosis and effective treatment have become essential. Improving mental health care benefits not only individuals but also society as a whole by promoting overall well-being and productivity. However, limited resources and infrastructure often constrain patients' access to mental health professionals. This work seeks to explore the use of advanced machine learning-powered classification algorithms for detecting and identifying mental health disorders with higher accuracy. Since the performance of classification algorithms depends heavily on proper parameter selection, a modified metaheuristic optimization algorithm, based on the firefly algorithm, is introduced to enhance performance and reliability. The proposed approach was evaluated on a publicly available real-world dataset, and a detailed comparative analysis with several contemporary algorithms was conducted. The best-performing models achieved an accuracy exceeding 94%, suggesting the approach's strong viability for real-world assistive applications in mental health care.
Copyright (c) 2025 Lepa Babic, Stanislava Kozakijevic, Luka Jovanovic, Branislav Radomirovic, Ivana Strumberger, Milos Antonijevic, Ninoslava Jankovic, Smiljana Tedic (Author) https://creativecommons.org/licenses/by/4.0
Half a Century of Fuzzy Decision Making in Italy: A Bibliometric Analysis
Italy is a developed country, and researchers in fuzzy decision-making are publishing actively. However, the extent and impact of contributions remain unexplored in scholarly evaluations. Thus, this study aims to provide a bibliometric analysis of fuzzy research in Italy from 1973–2024, utilizing the Scopus database and VOSviewer software. The main findings show a significant growth, with total publications increasing from 45 (1973-1999) to 543 (2000-2024). Early research focused on foundational concepts like fuzzy sets and fuzzy logic, while recent studies emphasize applied domains such as decision-making, artificial intelligence, and machine learning. Leading contributors include Fausto Cavallaro from the University of Molise, with the University of Naples Federico II (41 total papers) as the most productive institution. Collaboration analysis identifies India as the primary partner. The topical and keyword analysis reveals that the focus of the area of research is less aligned with global trends in fuzzy theories. Institutions can encourage strategic publishing to improve global rankings and citation impact.
Copyright (c) 2025 Muhammad Saqlain (Author) https://creativecommons.org/licenses/by/4.0
Multi-Attribute Decision-Analytic Approach based on Spherical Fuzzy Rough Schweizer-Sklar Aggregation Operators with Applications in Agricultural Management Systems
To find reasonable solutions for complex issues, multi-attribute group decision-making is an essential method that considers relevant attributes. For this purpose, the Schweizer–Sklar t-norms and t-conorms offer flexible and effective aggregation operators. Meanwhile, prioritized aggregation operators integrate critical information from available data to further enhance decision-making. To address uncertainty and imprecision in decision-making, in this script, we explore the spherical fuzzy rough set theory. Motivated by the utility of the Schweizer–Sklar t-norms and t-conorms, we propose a range of novel aggregation operators specifically designed for spherical fuzzy rough values, including the spherical fuzzy rough Schweizer–Sklar weighted averaging and spherical fuzzy rough Schweizer–Sklar weighted geometric operators. We examine the fundamental properties of the proposed operators in detail and demonstrate how multi-attribute group decision-making can benefit from them. A numerical example in agricultural management systems is provided to illustrate how to select the best alternative based on the given criteria. Finally, we compare the outcomes obtained using these newly postulated operators with those derived from existing studies in the literature to validate the effectiveness and practicality of the designed approaches.
Copyright (c) 2025 Mehwish Sarfraz, Rizwan Gul (Author) https://creativecommons.org/licenses/by/4.0
Variance Measure in Decision-Making Process: An Interpretation
This paper considers variance measure that is popularly used in multi-attribute decision-making (MADM) either as a holistic approach or as a snippet of a holistic approach for determining values of key decision entities such as attributes and/or alternatives. Specifically, we attempt to understand the results that emanate from the variance measure through a detailed interpretive construct, which will serve as a guide to decision-making scholars for rational usage of the popular approach in their respective MADM problems. We present illustrative examples to clarify the interpretations. Furthermore, we explore how the interpretive construct can be extended to analyze consistency in attribute weighting, thereby strengthening the reliability of MADM results. We also demonstrate how the variance measure can complement rank-based and aggregation-based methods, offering a unified perspective that integrates statistical interpretation with decision-making logic.
Copyright (c) 2025 Kattur Soundarapandian Ravichandran (Author) https://creativecommons.org/licenses/by/4.0
The Principle of Distributed Management in the Knowledge Economy
The subject of the research is the principle of “distributed management” and the possibility of its application in the “knowledge economy.” The purpose of the study is to reveal the content of the “distributed management” principle, as well as to demonstrate its application in the field of knowledge economy management, when the power of a policy instrument and the cumulative effect of development policy are important. The methodological basis of the research is the theory of economic policy, ideas about the development of the “knowledge economy,” a mathematical scheme for the implementation of the “distributed management” principle, the “income–risk” model, and the typification method. The overall result of the study is that we have obtained a picture of distributed management in the “knowledge economy” as a sector that includes the following types of activities: science, education, and high-tech sectors. The necessity of direct statistical accounting of the “knowledge economy” is substantiated in order to obtain an adequate assessment of the dissemination of knowledge and the application of development policy tools. The article identifies the pros and cons of measuring the “knowledge economy” by Eurostat and provides the author's proposals for direct measurement of this sector. In addition, a model of the development of the “knowledge economy” has been built in the “income–risk” coordinates. This model illustrates the application of various management methods based on the principle of “distributed management.” The study defines knowledge management modes in the “income–risk” coordinates, which actualizes the formulation and solution of the “distributed management” problem, involving the consideration of changes in the impact and accumulation of implemented development policy measures. The perspective of the study is to measure the use of each of the possible tools to stimulate the development of the “knowledge economy” and to compare them across countries, in particular the European Union and other regions of the global economy.
Copyright (c) 2025 Oleg Sergeevich Sukharev (Author) https://creativecommons.org/licenses/by/4.0
Management Science Burdens in Bangladesh: A Case of Food-Services Organizations
The COVID-19 pandemic severely disrupted global work environments, particularly in developing economies. This study investigates how a Bangladeshi food-services company managed talent during the early pandemic phase. A survey of 30 mid-to-senior-level managers assessed operational disruptions, remote work challenges, and financial pressures. Quantitative analysis using SPSS, including multiple regression, identified drivers of employee performance decline. Performance decline was significantly predicted by pandemic disruption and resistance to change, explaining 72% of the variance. Strategic practices such as cross-training and remote work planning mitigated performance risks. The findings establish a valuable baseline for longitudinal research. Organizations in developing economies must institutionalize agile, digitally enabled workforce strategies to enhance resilience against future crises.
Copyright (c) 2025 Md Nowshed Tuhin (Author) https://creativecommons.org/licenses/by/4.0
More than Classrooms: How School Culture Creates a School Brand?
School culture is important for creating a school identity and, consequently, school branding. Using the method of critical and content analysis and theoretical reflection, the study explores the correlation between school culture, marketing, and educational sciences. The research problem arises from the insufficiently clear connection between the school brand, school culture, and the role of principals. The aim of the study is to determine how school culture contributes to the formation of a school brand. The theoretical assumptions of Keller's CBBE model and Balmer's AC4ID model of corporate identity were used. This study is interdisciplinary because it connects the fields of management, marketing, and pedagogy with the aim of bridging the gap between the educational sciences of school leadership and management. The main results indicate the strong influence of school culture on the emotional connection of all stakeholders, as well as their loyalty to the school. This study also provides a deep understanding of the concept of school culture and branding, offering valuable insights for educational institutions.
Copyright (c) 2025 Dinko Jukić (Author) https://creativecommons.org/licenses/by/4.0
Evaluating the Impact of the Covid-19 Pandemic on Snapchat’s Business Outcomes
This paper explores the impact of the COVID-19 pandemic on the operational and financial performance of the Snapchat platform. The research aims to assess the resilience of the Snapchat platform during the COVID-19 crisis and to understand how platform-based business models respond differently to global disruptions than traditional businesses. The analysis is based on key financial indicators derived from the profit and loss statement, alongside trends in user growth. Methodologically, the study employs financial analysis and statistical regression models to evaluate selected business metrics. The findings suggest that the global pandemic did not significantly disrupt Snapchat’s operations. On the contrary, both gross profit and user numbers increased during the pandemic, with the platform recording its highest gross profit in the final year of the analyzed seven-year period, following the pandemic’s end. While the pandemic had limited impact on overall business performance, a notable post-pandemic trend was observed: revenue growth fell below the average for the period studied. Despite consistently posting negative net results, investor interest in the platform remained stable. These findings underscore a key distinction between platform-based business models and traditional “pipeline” models, highlighting the resilience and unique dynamics of digital platform economies.
Copyright (c) 2025 Joško Lozić, Katerina Fotova Čiković, Damira Keček (Author) https://creativecommons.org/licenses/by/4.0
Financial Literacy and Retirement Planning: A Global Bibliometric Analysis of Research Trends and Influential Contributions
This study presents a comprehensive bibliometric analysis of global research on financial literacy and retirement planning from 2010 to April 2025. Drawing on 507 open-access journal articles sourced from the Dimensions.ai database, it explores the evolution, influence, and thematic structure of academic contributions in this field. Using VOSviewer for mapping co-authorship networks, keyword co-occurrence, and citation patterns, the analysis highlights the increasing scholarly focus on financial capability, aging populations, and retirement preparedness. Results reveal a sharp rise in publications and citations after 2016, peaking in 2023, driven by global pension reforms and heightened awareness following financial crises and the COVID-19 pandemic. The United States, Netherlands, and the United Kingdom emerge as leading contributors, while scholars such as Lusardi and Post dominate high-impact research. Institutions like George Washington University and Netspar show exceptional citation performance. The study also identifies core journals, such as the Journal of Pension Economics and Finance, shaping academic discourse. Emerging research themes include behavioral finance, digital inclusion, and financial education. By mapping influential contributions and collaborative patterns, this paper offers valuable insights for academics, policymakers, and educators aiming to enhance retirement readiness through improved financial literacy. The findings underscore the field's growing relevance in global policy and personal financial planning.
Copyright (c) 2025 Rahul Kumar, Sushil Kumar Sahoo, Paras Tripathi (Author) https://creativecommons.org/licenses/by/4.0
Exploring the Potential Applications of Artificial Intelligence in Parcel Delivery Systems
This paper examines the potential applications and impacts of artificial intelligence within postal systems. A concise review of the relevant literature is presented, along with an overview of the most widely adopted artificial intelligence solutions implemented by leading global parcel delivery companies. To derive meaningful insights that may inform the implementation and operational use of artificial intelligence in this domain, a study is conducted involving expert opinions on the subject. There is a need to address issues of interoperability between different technologies and systems, as well as to provide adequate training for employees to operate within artificial intelligence-driven environments. Besides, the analysis highlights key priorities, anticipated benefits, and major challenges associated with the integration of artificial intelligence technologies into modern postal services.
Copyright (c) 2025 Momčilo Dobrodolac, Dragan Lazarević, Aleksandar Trifunović, Maja Petrović (Author) https://creativecommons.org/licenses/by/4.0
Evaluating Medical College Projects with Hamacher Aggregation Operators under the Interval-valued Complex T-Spherical Fuzzy Environment
The study explores the utilization of Hamacher aggregation operators (HAOs) in inscription selection for medical health projects. We employ interval-valued complex T-spherical fuzzy (IVCTSF) information to address the inherent uncertainties in healthcare data. In this paper, we develop the multiple-attribute decision-making (MADM) problems with IVCTSF set information. A few HAOs built on IVCTSF sets are presented in this work. We practice the Hamacher t-norm (HTNM) and Hamacher t-conorm (HTCNM) to characterize certain operational Hamacher operational rules within the context of the IVCTSF sets. We utilize averaging and geometric operations to develop a family of operators for aggregating IVCTSF information, namely IVCTSF Hamacher weighted averaging (IVCTFHWA), IVCTSF Hamacher order weighted averaging (IVCTSFHOWA), IVCTSF Hamacher hybrid weighted averaging (IVCTSFHHWA), IVCTSF Hamacher weighted geometric (IVCTSFHWG), IVCTSF Hamacher ordered weighted geometric (IVCTSFHOWG), and IVCTSF Hamacher hybrid weighted geometric (IVCTSFHHWG) operators. Several noteworthy properties of the developed operators are examined. Besides, an approach to the MADM algorithm is formulated using the proposed operators and is applied to a detailed case study. The case study measures the effectiveness of the proposed algorithm, analyzes the effect of variable parameters on the decision-making procedure, and ensures the stability of ranking results. A comparative analysis is conducted against existing studies to underscore the significance and advantages. Our findings demonstrate the effectiveness of this approach in improving decision-making for healthcare management in complex scenarios.
Complex Interval-Value T-Spherical Fuzzy Sets
Presenting a Conceptual Model of the Effectiveness of Storytelling at Different Stages of Strategic Management in Organizations
In the two decades since storytelling has been called "spreading the common sense of organizations". Research and study in the field of storytelling in management has devoted a wide range of research. Organizational storytelling is a new and modern management technique that has led to the success of many executive projects in large and famous organizations. Therefore, the necessity and importance of familiarizing Iranian organizations with this new management technique is evident. Organizational strategies, like old stories, are long-term processes. Strategies and strategic plans focus on the long-term goals and processes of the organization. Strategies are a tool for achieving long-term goals. Considering these cases, this article presents a conceptual model of the effectiveness of storytelling in various strategic management processes in organizations. A conceptual model with 20 storytelling applications has been presented. Experts in this study have also approved this model, and different statistical tests, including the binomial test and Friedman, have also been used for its validity, reliability, and performance. For the case study, Madiran Industrial Group, one of the leading companies in the information technology field, is selected. The results indicate that only nine out of 20 suggested uses of organizational storytelling are used in this organization. It should be noted that this research is one of the first studies to examine and create a conceptual framework for using organizational storytelling in strategic management.
Copyright (c) 2025 Alireza Hajiakhondi, Amir Sadeghi, Amir Karbbasi Yazdi (Author) https://creativecommons.org/licenses/by/4.0
Addressing Human Capital Development Challenges in Developing Countries Using an Interval-spherical Fuzzy Environment
This study evaluates and ranks the challenges of human capital development in developing countries based on their severity. Human capital development is crucial for economic growth, as acquiring knowledge, skills, and abilities plays a vital role in advancing these countries. However, various challenges impede the ability of developing countries to invest in human capital. Six key challenges were identified through a review of existing literature and expert insights. To analyse these challenges, the Stepwise Weight Assessment Ratio Analysis (SWARA) method within an interval-valued spherical fuzzy (IVSF) framework was utilized. The findings reveal that high unemployment, low literacy and education levels, and inadequate investment in skills development are the most significant challenges. Based on these results, the study offers actionable recommendations for governments seeking to enhance human capital development in these countries.
Copyright (c) 2025 Mouhamed Bayane Bouraima, Su Qian, Yanjun Qiu, Ibrahim Badi, Machioud Maxime Sangaré-Oumar (Author) https://creativecommons.org/licenses/by/4.0
Double Decker Decision Framework with Fuzzy Data for Multi-Attribute Decision-Making
This paper presents a new framework for decision-making with fuzzy data. Specifically, in a double-decker setup, the first deck contains methods that perform rank value calculation of alternatives. The second deck fuses the rank order to provide a holistic ordering of alternatives. The first deck is highly scalable, as it can accommodate multiple approaches for ranking, and the final ordering is obtained by sending the rank orders from the first deck to the second—where the simple rank procedure is utilized. Earlier frameworks cannot perform rank fusion or use techniques like averaging and the Borda count without considering the personal choice of alternatives. This framework circumvents this challenge, and its usefulness is demonstrated through numerical examples.
Decision-analytics-based Sustainable Location Problem - Neutrosophic CRITIC-COPRAS Assessment Model
School is the place where students get the opportunity to accrue knowledge and quality education. Choosing a suitable location for establishing a new school is dependent on various factors like population density, socio-economic situation, environment of that place, land availability, accessibility, infrastructure etc. In this paper, our aim is to identify the optimal site for establishing a new school in Paschim Bardhaman district using Multi Criteria Decision Making (MCDM) method. Here, two MCDM method namely Criteria Importance Through Intercriteria Correlation (CRITIC) method is used for evaluating criteria weight and further the Complex Proportional Assessment (COPRAS) method is applied for ranking the sites chosen as alternatives. We consider Intuitionistic fuzzy number to incorporate uncertainty in data set. Further sensitivity and comparative analysis are performed to verify the accuracy and stability of the result. Thus we obtain a framework which will be very helpful for urban planners and government policy makers to make informed decisions for educational development.
Copyright (c) 2025 Tripti Basuri, Kamal Hossain Gazi, Prodip Bhaduri, Srabani Guria Das, Sankar Prasad Mondal (Author) https://creativecommons.org/licenses/by/4.0
Global Trends and Research Patterns in Financial Literacy and Behavior: A Bibliometric Analysis
Financial literacy and behavior are pivotal for fostering personal economic stability and global financial resilience. This study utilizes bibliometric methods to analyze global research trends, identify key contributors, and explore thematic advancements in financial literacy and behavior over the decade 2014-2024. Data sourced from Dimensions.AI was systematically examined using VOSviewer to map collaboration networks, citation patterns, and emerging research themes. Findings reveal a significant rise in academic interest post-2020, driven by the heightened focus on financial resilience during the COVID-19 pandemic. The study identifies the United States and European nations as leading contributors, while also highlighting emerging areas such as the role of digital tools, behavioral insights into financial decision-making, and sustainable financial practices. Addressing research gaps, particularly in underrepresented regions, the paper advocates for cross-disciplinary collaborations and innovative financial education strategies. Future directions emphasize integrating advanced technologies like AI and blockchain to enhance financial inclusion, bridge inequalities, and support sustainable economic growth globally.
Copyright (c) 2025 Rahul Kumar (Author) https://creativecommons.org/licenses/by/4.0
Finding Effective Factor for Circular Economy Using Uncertain MCDM Approach
The paper aims to analyze the efficiency of the related criterion for adopting the circular economy concepts. The five related criteria, namely sustainability, resource management, product lifespan, collaboration and partnerships, and technology-innovation, are considered to formulate the decision-making models. For methodology, interval-valued DEMATEL is considered. Multi expert’s data sets are taken to reach the final decision. Finally, analysis of the result in an uncertain environment and the scatter diagram to examine the dependency among the criteria.
Copyright (c) 2024 Aditi Biswas, Kamal Hossain Gazi, Sankar Prasad Mondal (Author) https://creativecommons.org/licenses/by/4.0
A Comparative Analysis of AES, RSA, and 3DES Encryption Standards based on Speed and Performance
Information security is important in the digital era, with encryption emerging as a fixed solution to safeguard sensitive data from unauthorized access. This paper provides an overview of encryption by categorizing cryptographic algorithms into symmetric and asymmetric, along with hashing. Symmetric cryptography uses a single key for encryption and decryption, and asymmetric cryptography utilizes distinct public and private keys. Hashing maps input messages into compact bit strings. The literature survey explores the performance analysis of encryption algorithms, focusing on Rivest Shamir Adleman (RSA), Data Encryption Standard (DES), and Advanced Encryption Standard (AES), considering parameters like computation time and memory usage. Furthermore, the comparative analysis of encryption algorithms, including AES, RSA, and 3DES, is discussed. The paper delves into the motivation for cryptography in secure document transfer systems, emphasizing the need for confidentiality, integrity, and availability. Finally, the study presents detailed insights into AES, RSA, and 3DES encryption standards, highlighting their principles and applications.
Copyright (c) 2024 Mirza Hamza Munir Baig, Hafiz Burhan Ul Haq, Waleed Habib (Author) https://creativecommons.org/licenses/by/4.0
Optimizing Diabetes Data Insights Through Kmapper-Based Topological Networks: A Decision Analytics Approach for Predictive and Prescriptive Modeling
A highly effective technique for identifying and showing structures in high-dimensional datasets is topological data analysis. The Kmapper software creates overlaying clustering graphs and topological networks to facilitate the investigation of such information. The objective of the work was to visualize a dataset of diabetes patients that included information on blood pressure, glucose levels, and pregnancies using the Kmapper software. Afterward, it applied topological data analysis to see if any underlying structures or patterns could be established. The preprocessed dataset of diabetic patients was acquired via Kaggle. Kmapper was run with a difference of parameter settings, which includes 0.4 overlap, 15 hypercubes, and varying numbers of PCA components (1, 2, and 3). We investigated the generated graph visualizations. Although two PCA components were used, the topological graphs disclosed likely intriguing highlights such as three peaks. To understand these illustrated structures in the background of the diabetes data, additional investigation is mandatory. Also with every aspect considered, Kmapper worked well for using topological representations to contribute intuition into the high-dimensional dataset.
Copyright (c) 2024 Muhammad Abid, Muhammad Saqlain (Author) https://creativecommons.org/licenses/by/4.0