International Journal of Economic Sciences
The International Journal of Economic Sciences (IJES) is a single-blind, peer-reviewed journal which is freely available online under open access policy and serves as the primary source highlighting original research. The aim of the IJES is to publish articles that contribute significantly to the body of scientific knowledge and to provide an international platform for academic researchers, academicians, students, practitioners and policy makers from different background, who engage in theoretical and empirical research of chapters in economics, economic theory, finance, banking, international trade and related disciplines on micro, mezo and macro levels. Published articles use scientific research methods, including: economic modeling, econometric and statistical analysis, case studies, field research and historical analysis. General Journal guidelines for authors The International Journal of Economic Sciences 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 IJES 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): 1804-9796 Publisher: Scientific Oasis (SCIO) - Association for Engineering, Decision Making, and Operational Research was established in 2014 as the European Centre for Operational Research (ECOR), operating under the umbrella of the Regional Association for Security and Crisis Management (RABEK). Over the past decade, ECOR has evolved beyond its initial role as an internal center within RABEK through numerous activities and international collaborations. Given the increasing scope of its responsibilities, the natural decision was to separate ECOR as an independent association. In 2023, it was renamed Scientific Oasis (SCIO Association).....more info Indexing: Web of Science Emerging Sources Citation Index (ESCI) EconLit ERIH Plus RePEc Google Scholar ProQuest ABI/Inform Ulrich´s Periodicals Research Bible NewJour-L EconBiz WorldCat
Economics and Multi-Criteria Decision Support for Sustainable Cobalt Production
Mining critical minerals in the Democratic Republic of Congo comes with tough governance hurdles, environmental damage, and deep socioeconomic strains. This study’s approach blends SWOT with PESTLE analysis, drawing on the insight of experts from 32 organizations in 11 countries, including Canada, France, Germany, India, Norway, Pakistan, Poland, Portugal, Romania, Spain, and the United States. This two‑pronged approach makes it easier to fully examine the structural, political, and socio‑environmental sides of the cobalt industry in the Democratic Republic of the Congo. The PESTLE analysis paints the DRC’s political climate as unstable and steeped in corruption, with social governance in deep crisis and environmental oversight falling far short. In the SWOT analysis, strengths at 14.49 and opportunities at 12.54 edge ahead of weaknesses at 12.95 and threats at 11.27 on average. This forms the foundation for the study’s conclusion: greater transparency in institutions, fairer labour market governance, and stronger environmental laws could help curb the extractive injustices tied to cobalt mining in the DRC.
Copyright (c) 2025 Rosa María Ricoy-Casas , Jose María Lago Cabo, Jorge Eduardo Vila Biglieri, Darko Bozanic (Author) https://creativecommons.org/licenses/by/4.0
Evaluating Green Economy Strategies through Multi-Criteria Decision Analysis: A Systematic Review
Green economy transition needs efficient metrics to evaluate the trade-off between environmental, economic, and social objectives. This paper review articles on Multi-Criteria Decision Analysis (MCDA) in green economy strategies published between 2010 and 2025 based on the Dimensions.ai database. After following a designed PRISMA method, 1626 articles were filtered and examined through bibliometric mapping and qualitative analysis. The findings demonstrate that Journal of Cleaner Production, Sustainability, and Renewable and Sustainable Energy Reviews are the most fruitful journals and China and Europe are the countries that present most of the research. AHP, TOPSIS, and hybrid approaches are some of the common MCDA methods which have been used in renewable energy planning, waste management, sustainable transport, supply chain optimization, and policy evaluation. The results suggest that MCDA assists in making the decisions more transparent, participatory, and evidence-based. Nevertheless, there are still difficulties, such as subjective approaches, unreliable information, and insufficient research of the world. All in all, this paper demonstrates the value of MCDA in aiding the green economy approach and suggests more comprehensive, technology-based approaches to procedure in the future
Copyright (c) 2025 Sushil Kumar Sahoo, Shankha Shubhra Goswami, Darko Božanić, Soupayan Mitra (Author) https://creativecommons.org/licenses/by/4.0
Economic Impact of University Knowledge Spillovers on Firm Innovation: A Spatial Analysis from China
University knowledge spillovers are widely recognized as vital drivers of corporate innovation and regional economic development. However, the economic impact of geographic distance between enterprises and universities on innovation output remains underexplored. This study investigates the relationship between spatial proximity to universities and corporate innovation performance using invention patent data from Chinese A-share listed firms between 2010 and 2022. Employing Ordinary Least Squares (OLS) models with city and year fixed effects, we find a significant negative association between geographic distance and firms’ innovation outputs. Mechanism analyses identify university–enterprise patent collaboration and firms’ innovation-related information disclosure as key economic channels for knowledge spillover effects. Moreover, heterogeneity analyses show that these effects are more pronounced in cities with smaller economic scales or limited innovation resources, underscoring the importance of spatial economic factors. By analyzing the impact of university knowledge spillovers on firm innovation, this study broadens the set of identified determinants of corporate innovation, thereby providing additional evidence and theoretical foundations for advancing high-quality, innovation-driven economic development.
Copyright (c) 2025 Xiangshuo Zhang (Author) https://creativecommons.org/licenses/by/4.0
Artificial Intelligence Applications and Corporate Sustainable Development: An Economic and Environmental Performance Perspective
Against the backdrop of rapid advancements in intelligent technologies and the convergence of China's "dual carbon" strategic goals, how enterprises leverage artificial intelligence to enhance economic and environmental benefits while achieving sustainable development has emerged as a critical research question. This study adopts a dual-perspective approach, examining both financial and environmental performance within the framework of sustainable development. Based on a sample of Chinese A-share listed companies from 2013 to 2023, this study employs a multi-period Difference-in-Differences model to empirically examine the impact of applications of artificial intelligence on corporate sustainable development performance, as well as the underlying mechanisms. The findings reveal: (1) Applications of artificial intelligence enhance both the financial and environmental performance of corporations, thereby improving their overall sustainable development performance. The conclusion has passed a series of robustness tests, including heterogeneity tests and double machine learning. (2) Mechanism analysis reveals that artificial intelligence influences corporate sustainable development performance through green innovation effects, efficiency enhancement effects, and information acquisition effects. The Porter Hypothesis, the Resource-Based View, and the Information Asymmetry Theory, among other theories, have been verified. (3) The promotional effect of artificial intelligence applications on sustainable development performance exhibits heterogeneity. Specifically, the promotional effect is more pronounced in non-heavily polluting enterprises, high-tech enterprises, and enterprises with senior executives possessing environmental protection backgrounds. (4) When enterprises are engaged in intense market competition, the positive relationship between artificial intelligence adoption and sustainability performance strengthens. Our findings offer valuable insights for managers and policymakers aiming to leverage AI for achieving sustainable growth.
Corporate Sustainable Development Performance
Copyright (c) 2025 Huixin Sun, Rongchun Zhu (Author) https://creativecommons.org/licenses/by/4.0
Agility of the Drug Supply Chain Considering Economic and Social Aspects: Use of Internet of Things and Big Data Analysis
The importance of drug supply and the efficiency and effectiveness of the drug supply chain as a strategic commodity are not hidden from anyone. Supplying raw materials for the production, storage, and distribution of medicines within a supply chain network is crucial. Today, the development of the Internet of Things and the analysis of vast amounts of data have enabled the rapid preparation of large data production resources, allowing decisions in the drug supply chain network to be made quickly with the aid of appropriate tools. This article aims to provide a framework for agile drug supply chain management, focusing on the Internet of Things and big data analysis to manage the country's drug supply chain effectively. Rebif-22-44 drugs, which are used in the treatment of MS disease, are investigated in this paper, and an attempt is made to minimize the costs of the drug supply chain network design and minimize the maximum unmet demand of drug distribution based on big data sources by using a framework. MOGWO analysis tools and epsilon constraints are discussed. Considering the existence of uncertainty in drug demand and transportation costs, the robust possibilistic planning method has been used to control uncertain parameters. The analysis of big data shows that, in order to reduce the shortage of drugs in the country, it is necessary to use more supplies and increase the number of drug production centers and warehouses. This leads to an increase in the design costs of the supply chain network. In the analysis of the model, 11 efficient solutions were obtained by the MOGWO algorithm, and seven efficient solutions were obtained by the epsilon constraint method. It was also observed that, in Iran, with the increase in the uncertainty rate, the demand for Rebif-22-44 drugs has increased, and this has led to a rise in network design costs and drug shortages in the country. Concretely, lowering the maximum unmet demand from 78 to 47 units required raising the total network cost from 1,303,212.72 to 1,498,842.94 (USD), quantifying the cost–equity trade-off, and MOGWO produced a broader, faster Pareto set than the ε-constraint method (11 solutions in 68.49 s, MSI = 195,630 vs. seven solutions in 1,342.15 s, MSI = 184,4.
Copyright (c) 2025 Amirhamzeh Razavinejad, Seyed Esmaeil Najafi, Mehran Khalaj, Hamed Kazemi Pour (Author) https://creativecommons.org/licenses/by/4.0
Emergency Management in Risk Control: Approaches for Surpassing Financial Challenges
Crisis management is an essential component of strategic planning and forecasting in companies, and its importance has grown significantly in the aftermath of the global crisis caused by the COVID-19 pandemic. While insurance companies traditionally focus on preventing and compensating for negative economic events, effective crisis management is equally crucial for accurate risk assessment, as the stability of the insurance sector directly supports the stability of the wider financial system. The aim of this research was to analyze contemporary perspectives on anti-crisis management in insurance and evaluate the effectiveness of measures applied to overcome crisis situations. To achieve this, the study employed bibliographic-analytical methods, induction, deduction, synthesis, generalization, online surveys, and logical, as well as statistical and graphical, comparison. The findings revealed notable differences in risk management approaches across companies of different sizes. Large insurance companies placed considerable emphasis on training staff in crisis management and employing specialists in analytics and risk assessment. Medium-sized firms often relied on external consultations, scenario planning, and employee training, while small firms generally paid insufficient attention to risk management practices. Among anti-crisis measures and management staff training, the work of strategic planning departments, strengthening teamwork, and financial frugality were associated with the effectiveness, speed, and progressiveness of overcoming an economic crisis with a medium-strength connection. That is why large companies that combined these measures were more effective in overcoming crises. In contrast, medium and small enterprises achieved lower effectiveness, reflecting their more limited and inconsistent adoption of crisis management measures.
Copyright (c) 2025 Nataliia Tymoshyk, Dmytro Rasshyvalov, Iryna Tarasenko, Kseniia Velykykh (Author) https://creativecommons.org/licenses/by/4.0
Research on the Role of ESG Performance in Capital Market Pricing Efficiency: An Analysis Based on Stock Price Synchronicity
Firms’ active practice of Environmental, Social, and Governance (ESG) development principles holds significant value for enhancing capital market pricing efficiency. Using panel data from Chinese A-share listed firms from 2009 to 2023 and relying on the Hua Zheng ESG rating system, we constructed corresponding indicators to investigate the impact of ESG performance on stock price synchronicity. We find that firms’ ESG performance contributes to increased stock price synchronicity. This positive effect of ESG is more pronounced in samples of state-owned firms, large firms, and firms with higher bankruptcy risk. We further reveal the mechanism through which ESG promotes stock price synchronicity, identifying information disclosure quality and analyst attention as two key mediating variables, while information asymmetry exhibits a masking effect. We integrate information efficiency theory and noise theory within a unified analytical framework, advancing the development of relevant theories in emerging markets. The findings offer important insights into optimizing the role of ESG in enhancing capital market pricing efficiency.
Copyright (c) 2025 Yuming Yin, Zilong Li, Kai Li, Tao Wang, Shunwei Cui (Author) https://creativecommons.org/licenses/by/4.0
Omnichannel Digital Marketing in the Postal and Logistics Sector: Strategic Functions and the Role of Leadership Visibility
In the current conditions of digital transformation of logistics services, omni-cultural marketing as a strategy of personalized multichannel customer interaction is becoming especially relevant. Rising consumer expectations regarding the quality of digital communication and service transparency require new approaches to building trust and loyalty in logistics companies. The purpose of the study is to examine the digital behavior of customers of the logistics company Meest and to assess the impact of communication channels and the public presence of management on brand perception. The object of the study is digital communication channels in logistics. The methodological basis is a quantitative online survey of Meest customers (n = 1011) conducted in February 2025, using descriptive statistics to analyze the responses. The results revealed a high level of multimodal interaction: 72.5% of users use at least three channels, and 60% regularly switch between them. The highest level of satisfaction was recorded for the mobile app (96%), although it is inferior to email and messengers in terms of reach. For 92% of respondents, the style of communication affects brand trust, and 68.7% positively assess the public activity of management. A functional typology of channels by strategic purpose (attraction, retention, brand building) has been built, which allows optimization of the digital architecture of logistics companies. The practical significance of the study lies in the possibility of adapting the findings to develop effective omni-cultural strategies, taking into account behavioral and emotional factors of interaction.
Copyright (c) 2025 Marta Yankiv, Roman Mykytyuk , Andrii Gukaliuk (Author) https://creativecommons.org/licenses/by/4.0
Economic Evaluation of Digital Suppliers for Manufacturing SMEs Using Pythagorean Neutrosophic TOPSIS and VIKOR with a Flexible Distance Metric
Selecting digital suppliers is not only a technological issue but also a fundamental economic decision for manufacturing SMEs pursuing digital transformation. Supplier choice directly affects cost efficiency, resource allocation, and long-term competitiveness. This study develops a quantitative multi-criteria decision-making (MCDM) framework that integrates Pythagorean Neutrosophic TOPSIS (PNTOPSIS) and VIKOR (PNVIKOR), strengthened by a novel distance measure, the Flexible Indeterminacy Quantifier (FIQ). The framework explicitly addresses incomplete and uncertain evaluations that complicate procurement under financial and operational constraints. A real-world case with five digital suppliers is analyzed across criteria including system capability, vendor support, total cost, and risk of disruption. The findings highlight the supplier that delivers the highest economic value by aligning affordability with operational reliability. FIQ improves score differentiation and ranking stability, enabling SMEs to make more economically rational choices. Sensitivity analysis confirms that the model produces consistent outcomes under varying budgetary assumptions, demonstrating its robustness for strategic procurement. Overall, this research provides SMEs with an uncertainty-aware, cost-sensitive tool that reduces financial risks, enhances transparency in supplier selection, and supports sustainable economic performance within digitally transforming industrial ecosystems.
Copyright (c) 2025 Mohammad Syafiq Mohammad Kamari, Zahari Md Rodzi, Zaifilla Farrina Zainuddin, Nor Hanimah Kamis, Noraini Ahmad, Samsiah Abdul Razak, Faisal Al-Sharqi (Author) https://creativecommons.org/licenses/by/4.0
Strategic Challenges and Opportunities for the Czech Steel Industry: A Path toward Sustainable Competitiveness
The Czech steel industry is a vital contributor to the national economy, supplying sectors like automotive, construction, and energy. However, it faces challenges such as global overproduction, high energy costs, decarbonization requirements, and shrinking demand in key markets. This article examines the systemic risks affecting the industry’s competitiveness from 2008 to 2023, highlighting global trade dynamics, EU environmental regulations, and workforce issues. Despite these pressures, the sector has shown resilience. The study outlines a strategic approach focusing on technological modernization, product diversification, policy collaboration, and workforce upskills to ensure long-term sustainability and competitiveness in a rapidly evolving market.
Copyright (c) 2025 Eduard Hromada, Klara Cermakova, Bozena Kaderabkova, Lucie Kurekova, Martina Krasnicka (Author) https://creativecommons.org/licenses/by/4.0
The Mixed Incentive Effect of Government Subsidies and Venture Capital on the Sustainability of Enterprise Innovation
The innovation effects of enterprises receiving subsidies remain a widely debated issue in academic research. Using the Control Function (CF) method, this study integrates government subsidies and venture capital into a unified framework to examine their combined incentive effects on the sustainability of firm innovation. Survival analysis is employed to compare the probability of enterprises ceasing innovation under a single-subsidy mechanism versus dual-financing conditions. The findings reveal that the interaction of public subsidies and private capital produces a significant complementary effect, generating stronger and broader stimulation of continuous innovation activities than government subsidies alone. In the technology-intensive industry sample, the synergy of subsidies and venture capital reduces the probability of innovation discontinuation by approximately 6.4%. Results from the Cox proportional hazards model further indicate that determinants of sustained innovation differ depending on enterprises’ levels of effective patent output. These empirical results advance the understanding of corporate innovation financing, enrich theoretical perspectives in the field, and provide practical implications by highlighting the importance of combining public and private financing to foster sustainable innovation, thereby supporting China’s innovation-driven development strategy.
Copyright (c) 2025 Xi Chen (Author) https://creativecommons.org/licenses/by/4.0
Smart Tourism Cities and Income Equity: How Digital Economy Reshapes Urban-Rural Disparities
In the context of the rapid rise of the digital economy, comprehending its role in shaping urban-rural income dynamics has become increasingly critical. This study focuses on smart tourism cities (a hallmark of the digital economy) to examine how the digital economy influences the urban-rural income gap from a tourism perspective. Despite the growing prominence of the digital economy, its specific impact on urban-rural income disparities in tourism-dependent regions remains underexplored, motivating this investigation. This study selects 71 key tourism cities over the period 2012–2019 and employs advanced analytical methods, including mediating effects analysis, multi-period Difference-in-Differences (DID) testing, instrumental variable approaches, robustness testing, and heterogeneity analysis. The findings indicate that: first, the digital economy significantly reduces the urban-rural income gap in tourism cities; second, tourism serves as a key mediating variable in this process; third, after conducting an exogenous shock test using a multi-period DID econometric model based on the "Broadband China" initiative, the conclusions remain robust; fourth, the digital economy's impact on narrowing the income gap is particularly pronounced in second-tier and lower-tier cities, especially in third-tier and lower-tier cities, while no significant effect is observed in first-tier cities. In summary, the development of the digital economy effectively narrows the urban-rural income gap in tourism cities. Therefore, governments should prioritize enhancing the construction of smart and digital tourism cities to further promote balanced regional development.
Copyright (c) 2025 Jia Wang, Hangdi Zhao (Author) https://creativecommons.org/licenses/by/4.0
Digital Entrepreneurship Within International Business Landscape: Implications for Marketing Strategies
With the rise of digital advancements, the global economic landscape is reshaping marketing and entrepreneurship, creating both new opportunities for growth and significant challenges for businesses. Rapid economic shifts, combined with society’s increasing reliance on digital technologies, require organizations to continuously adapt and modify their business models. This study is particularly relevant, as maintaining competitive advantage and ensuring long-term sustainability now depend heavily on the integration of digital solutions. The research evaluates the impact of digital technologies on marketing strategies, financial performance, and overall business effectiveness at the global level. By analyzing digital transformation strategies through a combination of statistical and practical approaches, the study highlights critical success factors as well as barriers to implementation. Findings reveal that the adoption of digital tools enhances process automation, strengthens customer engagement, improves resource management, and ultimately increases productivity and profitability. However, challenges remain, including regulatory constraints, cybersecurity risks, and the constant demand for technological innovation. Despite these obstacles, digital transformation creates pathways to new markets and fosters innovative opportunities. To fully capitalize on these benefits, companies must design adaptive strategies that not only mitigate risks but also maximize the potential of emerging technologies. These insights provide valuable guidance for businesses seeking to build sustainable digital strategies, ensuring long-term competitiveness in the global marketplace.
Copyright (c) 2025 Olena Ptashchenko, Oleksandr Rozumnyi, Elman Aliiev, Volodymyr Vovk, Olena Shersheniuk (Author) https://creativecommons.org/licenses/by/4.0
Beyond ESG: Unpacking Brand Loyalty Through the Emotional Mechanisms Lenses of Attachment and Love—A Hierarchical Regression Study of Alibaba in China
Currently, research on Environmental, Social, and Governance (ESG) initiatives primarily emphasizes consumers' cognitive evaluations—such as awareness, knowledge, and rational assessment—providing a limited perspective on the underlying mechanisms that drive brand loyalty. However, the internal structural pathway between ESG and brand loyalty remains underexplored, particularly with regard to emotional mechanisms. This study addresses that gap by examining how ESG perceptions influence brand loyalty through the sequential mediating roles of brand attachment and brand love. The research moves beyond cognitive frameworks to uncover the emotional pathways through which ESG initiatives shape consumer behavior. Using survey data, the study applies hierarchical regression analysis alongside a sequential mediation model to assess the emotional effects of ESG perceptions. The findings reveal that the environmental and social dimensions of ESG are especially effective in fostering emotional bonds with consumers. ESG efforts serve as credibility signals, evoke emotional responses, and fulfill consumers' intrinsic needs for connection and attachment. The study concludes that ESG is not merely a tool for regulatory compliance or corporate image management, but a strategic resource for cultivating long-term consumer loyalty through emotional engagement. By integrating theories of signaling, consumer emotion, and emotional attachment, this research offers a comprehensive framework for understanding the emotional impact of ESG on consumer–brand relationships. The results provide practical insights for brands seeking to strengthen loyalty by aligning ESG initiatives with consumers' emotional values and expectations.
Copyright (c) 2025 Xiaobo Xue, Peilin Tian (Author) https://creativecommons.org/licenses/by/4.0
A New Paradigm of Advertising Marketing Experience Based on New Media Extended Reality Technology
As media technology has evolved, advertising formats have also transformed, with extended reality (XR) emerging as a new medium that offers immersive experiences for marketing. This study systematically proposes a new paradigm for immersive advertising in XR environments to enhance user experience and marketing effectiveness. As XR becomes a pivotal marketing tool, its ability to transcend traditional one-way communication calls for a systematic analysis of user experience dynamics. By collecting and analyzing XR advertising cases and prior literature, we identify significant shifts in user experience compared to traditional advertisements. Based on these findings, this paper proposes a model describing the XR advertising experience, which includes three dimensions: multi-sensory presentation, narrative approach, and intelligent interaction. The model also highlights both internal and external factors that influence user experience. The study concludes that XR advertising offers unique advantages in terms of interactive engagement, deep immersion, and personalization, signaling important trends for the future of advertising.
Copyright (c) 2025 Xin Min, Yuxuan Liu, Iek On Lu (Author) https://creativecommons.org/licenses/by/4.0
Use of Beneish M-Score: Case Study in the Spanish Fishing Sector
The manipulation of financial statements is a practice used by companies to obtain illicit benefits or advantages over competitors. One of the world's largest bluefin tuna exporters is implicated in an alleged fraud case and accused of committing multiple crimes, including offenses against public safety and money laundering. This study analyzes the company's likelihood of fraud using the Beneish method, which detected potential accounting irregularities in five of the eight years examined (2015–2022). The findings appear to corroborate the fraud allegations against the company.
Copyright (c) 2025 Raquel Fernández-González, Félix Puime-Guillén, Patricia Coloret Portela, Dragan Pamucar (Author) https://creativecommons.org/licenses/by/4.0
Asymmetric Impact of Climate Change Vulnerability and Adaptive Capacity on Economic Growth in Developing Economies
Climate change has become a significant global issue, particularly impacting economic systems in developing nations. This study highlights the complex relationship between climate vulnerability (CV), adaptive capacity (AC), and economic growth (GDP) in developing economies. While previous research has largely focused on the direct effects of climate change on GDP, this study advances the literature by investigating both direct and indirect pathways using Structural Equation Modelling (SEM). Data from Asian emerging economies, covering the period 2000–2022, were sourced from the World Bank. The results reveal a significant negative direct effect of CV on GDP growth (β = –0.214, p < 0.01) and a positive, significant effect of CV on AC (β = 22.16, p < 0.001), indicating that greater climate vulnerability drives increased investment in adaptation. The findings also show that AC has a positive impact on economic growth (β = 0.007, p < 0.01), suggesting a partial mediation effect that mitigates the negative consequences of CV on GDP. These results emphasize the importance of adaptive systems in reducing climate risks and enhancing economic resilience. The study offers actionable insights for researchers and policymakers aiming to achieve resilient growth.
Copyright (c) 2025 Unbreen Arif, Sahar Latif Rana, Sarah Azhar, Muhammad Bilal Ahmad, Fatima Shaukat (Author) https://creativecommons.org/licenses/by/4.0
Economic Rebuilding Frameworks in Post-War States: Takeaways for Ukraine
The post-war recovery of Ukraine’s economy is increasingly debated among scholars and experts, with key issues including financing sources for reconstruction, investment conditions, institutional barriers, and the effectiveness of monetary and fiscal policies. This article examines the implementation of economic recovery models in post-conflict countries and develops recommendations tailored to Ukraine. Using a descriptive-analytical approach, the study analyses and systematises macroeconomic indicators for 2021–2027 (including forecasts) to assess Ukraine’s recovery potential. The findings indicate moderate economic growth, declining inflation, and a reduced key policy rate in 2025, with stronger recovery anticipated in 2026–2027. Budget deficits are expected to be financed by external loans and grants, primarily directed to the defence sector. In this context, the government must prioritize identifying sustainable recovery sources. Continued structural reforms will be essential for building institutional capacity to address post-war economic and social challenges. International experience underscores the need for political stability, institutional strengthening, trade liberalisation, and targeted international aid to support vulnerable sectors. Support funds and external resources must be carefully allocated to Ukraine’s most pressing needs. Ensuring political stability through effective security mechanisms is crucial to the long-term reconstruction process. Economic recovery drivers will centre on directing international assistance toward structural weaknesses in Ukraine’s economy, promoting innovation, and enabling the return of highly skilled migrants. The practical value of this study lies in its identification of key macroeconomic trends that will shape Ukraine’s post-war recovery path and inform the development of a sustainable and effective growth model.
Copyright (c) 2025 Nina Petrukha, Nataliia Fedirko, Iryna Piatnychuk, Pavlo Lyashenko, Dmytro Plakhotnii (Author) https://creativecommons.org/licenses/by/4.0
A Multi-Criteria Framework for Economic Decision Support in Urban Sustainability: Comparative Insights from European Cities
Sustainable urban development has become an economic imperative as cities grapple with escalating environmental, social, and financial pressures. This study evaluates the economic performance and fiscal sustainability of European capitals—Stockholm, Oslo, Copenhagen, Lahti, London, Berlin, Madrid, Paris, Amsterdam, and İstanbul—through a robust Multi-Criteria Decision-Making (MCDM) framework. The analysis incorporates twelve key indicators that reflect not only environmental resilience but also resource efficiency, infrastructure investment, and the economic viability of sustainability policies. These include Scope 1 Emissions, Consumption-Based GHG Emissions, Particulate Air Pollution, Open Public Space, Road Infrastructure Efficiency, Sustainable Transport, Vehicle Dependence, Water Access, Water Consumption, Solid Waste Generated, Climate Change Resilience, and Sustainable Policy Implementation. A hybrid MCDM model combining MEREC-based RAWEC with Extended AROMAN and MARA methods was applied. The MEREC method was used to derive economically weighted priorities among criteria, while final rankings were aggregated using RAWEC, Extended AROMAN, MARA, and Borda Count methods. Results identified Scope 1 emissions as the most economically impactful criterion, while particulate air pollution had a lower fiscal weighting. Cities such as Stockholm, Oslo, and Copenhagen consistently emerged as top performers due to their cost-effective and forward-looking urban sustainability policies. In contrast, Paris, İstanbul, and Amsterdam demonstrated lower cost-efficiency scores. Sensitivity analysis further validated the model's reliability. This framework not only supports environmental assessment but also informs economic decision-making by guiding policymakers toward fiscally responsible and sustainable urban planning strategies.
Copyright (c) 2025 Emre Kadir Özekenci (Author) https://creativecommons.org/licenses/by/4.0
Corporate Social Responsibility Investment and Its Impact on the Financial Performance of Securities Companies
The objective of this paper is to clarify the impact of corporate social responsibility (CSR) investment on the financial performance of Vietnamese securities companies. Previous studies have focused on companies in the manufacturing, construction, banking, and insurance sectors, while there are very few studies addressing securities brokerage companies. This study aims to fill the above gaps by analyzing and finding evidence on the relationship between CSR and financial performance based on the theoretical framework [1]. The database was collected online by the authors. The survey period was from September 2024 to December 2024. The research results included 122 valid responses. Using quantitative research, the PLS-SEM linear structural model was performed using SPSS and AMOS 20 software. The results and new findings show that two CSR factors have a strong impact on the financial performance of securities companies: responsibility to investors and issuers, and responsibility to securities employees. The new findings show that investing in CSR activities is necessary for securities companies. The core factors to improve business performance for these companies are customers and employees. Based on the results of empirical research, the article recommends that securities companies in countries with financial markets developing similarly to Vietnam actively promote investment in building and implementing CSR, focusing strongly on the factors of investors, issuers, and securities employees to improve financial efficiency.
Copyright (c) 2025 Tran Van Hai, Vu Thuy Linh, Hoang Van Quynh, Do Thi Van Dung, Nguyen Van Quang, Nguyen The Hung, Tran Thi Lan Anh (Author) https://creativecommons.org/licenses/by/4.0
Economics of the Fish Processing Industry: Applying the Beneish M-Score Model
Financial statement manipulation has been a practice since the dawn of commerce, resulting in substantial financial losses that have a significant impact on the market. Various factors can lead to such behaviour, such as economic downturns or strong competitive pressures, which affect all sectors of the economy. One of these sectors, the frozen fish industry, stands out in Galicia (Spain) because of its importance due to its strategic location, with a large number of companies integrated into this commercial sector. One of these companies, Hiperxel S.L., was one of the best known for its development and size of business, but this did not prevent it from going bankrupt in 2023, an event that the Spanish Tax Agency considers to be the result of a multi-million-euro fraud. This study analyses the likelihood of fraud committed by this company through the Beneish model and shows index results that support this theory, as a Beneish M-score of 4.137 and -1.127 was obtained in 2019 and 2021, respectively, data that confirm the possible existence of financial statement manipulation before the collapse of Hiperxel S.L.
Copyright (c) 2025 Raquel Fernández-González, Félix Puime-Guillén, Patricia Coloret Portela, Judit Koltai (Author) https://creativecommons.org/licenses/by/4.0
Adaptive Utility Ranking Algorithm for Evaluating Blockchain-Enabled Microfinance in Emerging - A New MCDM Perspective
Blockchain integration in microfinance is beginning to reshape the scenario of financial inclusion and economic empowerment in emerging markets. To support a strategic decision on adoption, the study introduces the Adaptive Utility Ranking Algorithm (AURA), a newly established Multi-Criteria Decision-Making (MCDM) method to be used in evaluating blockchain-based alternatives relevant to microfinance in Malaysia. AURA stands apart from traditional MCDM techniques in that it has a distance function that is flexible and a normalization scheme that is dynamic by nature, thereby making it capable of offering the decision maker more leverage in terms of adaptability to actual economic conditions. For demonstrating the methodology, a simulated dataset based on eight blockchain-modeled alternatives and six criteria considered important in economic performance was constructed. These criteria were used for sensitivity analysis; the application of comparative evaluation of well-known MCDM methods such as TOPSIS, VIKOR, and COBRA; and robustness checks with the simulation methodology, all of which helped attest to the reliability of AURA. Even though it was based on synthetic data, the study has provided strong conceptual insight into the possibility of financial institutions being able to prioritize options from the technology perspective under complex economic constraints. Portraying AURA as a competitive decision-support tool for technology evaluation in microfinance will certainly make an impact.
Copyright (c) 2025 Muhammad Mukhlis Kamarul Zaman, Zahari Md Rodzi, Yusrina Andu, Nur Aima Shafie, Zuraidah Mohd Sanusi, Aziatul Waznah Ghazali, Jamilah Mohd Mahyideen (Author) https://creativecommons.org/licenses/by/4.0
Improving Hospital Efficiency and Economic Performance: A DEA Approach with Undesirable Factors in Tehran Emergency Wards
Since the 1980s, Data Envelopment Analysis (DEA) has undergone remarkable advancements in both theoretical foundations and practical applications, surpassing initial expectations in the field. To optimize organizational performance, identifying and incorporating undesirable inputs and outputs is vital for improving system efficiency, minimizing waste, and enhancing resource allocation—ultimately contributing to economic efficiency. This research employs established DEA models to assess decision-making units' (DMUs) performance while explicitly accounting for undesirable factors. The results demonstrate that including undesirable inputs and outputs significantly influences the identification of the efficiency frontier, thereby affecting the comparative assessment of DMUs and providing a more accurate reflection of real-world economic constraints. Consequently, DMU efficiency and performance can be improved by reducing undesirable outputs and increasing desirable ones, pushing them toward the efficient frontier. In healthcare, this leads to better patient outcomes and more effective resource utilization. Economically, it translates to lower operational costs, improved resource allocation, and greater overall productivity in the healthcare system. To validate the proposed models, a case study was conducted using real-world data from 30 emergency wards in Tehran hospitals, comprising five desirable inputs, one undesirable input, four desirable outputs, and one undesirable output.
Copyright (c) 2025 Abbasali Monzeli, Behrouz Daneshian, Ghasem Tohidi, Masud Sanei, Shabnam Razaveian (Author) https://creativecommons.org/licenses/by/4.0
Modeling Sustainable Development of Cryptocurrencies by a Fractional Pure-Jump Process in DEA Framework
Sustainable cryptocurrency modeling is vital for maximizing both economic and environmental benefits amid significant investor interest. This research develops a comprehensive methodology for cryptocurrency selection by holistically integrating financial aspects, such as returns and risk, with environmental sustainability. To quantify risk and further evaluate cryptocurrency efficiency, we employ an ARMA-GARCH model with fractional normal inverse Gaussian (FNIG) innovations to forecast Value at Risk (VaR) and expected returns. Subsequently, we apply Data Envelopment Analysis (DEA) to identify the most efficient cryptocurrencies, incorporating mining costs and the forecasted VaR as inputs—representing energy cost and risk, respectively—while using the forecasted expected returns as the output. This approach enables a direct comparison of cryptocurrencies based on these critical factors. Our findings demonstrate that accounting for the inherent stochastic behavior of cryptocurrencies leads to more accurate estimations, and the DEA highlights the essential role of energy costs in selecting efficient cryptocurrencies.
Copyright (c) 2025 Navideh Modarresi, Moshtagh Darvishi, Shokoofeh Banihashemi (Author) https://creativecommons.org/licenses/by/4.0
Social Media Opinion Leaders’ Self-Presentation and Youth Tourism Impulse Buying: A Mediated SOR Analysis
This study pioneers the application of impression management theory to tourism impulse buying, identifying four novel self-presentation attributes. Data were collected from an online and an offline survey of 345 Chinese university students. Using SPSS22.0 and AMOS21.0 statistical software, this paper analyses the pre-survey and formal survey data through descriptive statistics, reliability and validity tests, correlation analysis and structural equation model testing, and the calculation results verify the validity of the research hypotheses and models proposed in this paper. The results reveal that the four self-presentation attributes, professionalism, interactivity, homophily, and entertainment, positively influence young people’s impulsive buying tendency. Among them, the influence of professionalism exceeds the other three attributes, and its impact on perceived value exceeds the impact on flow experience. Interactivity had a greater impact on the flow experience, outpacing the other three attributes. Homogeneity had a slightly stronger effect on perceived value than on flow experience. Entertainment has more of an impact on perceived value than the other three attributes. Moreover, flow experience and perceived value significantly affect impulsive buying and mediate these relationships. Also, perceived value has a greater impact on impulse buying than flow experience. These findings clarify the psychological mechanisms and pathways underpinning young people’s impulsive buying tendency, emphasizing their impulsive, highly visual, and immediate nature, as well as their dependence on digital technology. The study also offers strategies to guide young consumers toward more rational purchase decisions.
Copyright (c) 2025 Qianqian Fan, Yuting Yang (Author) https://creativecommons.org/licenses/by/4.0
Reporting of Taxonomic Indicators and Greenhouse Gas Emissions in the Practice of the Largest Construction Companies in the Czech Republic
This study examines the economic impact of taxonomic indicator reporting and greenhouse gas (GHG) emission disclosures by leading construction companies in the Czech Republic. As environmental, social, and governance (ESG) criteria grow in importance, transparent sustainability reporting has become a key factor influencing financial stability, investment attractiveness, and regulatory compliance. Using qualitative content analysis of company reports, the study reveals significant disparities between subsidiaries of international construction firms and Czech-owned companies. While the former align with global frameworks such as the Global Reporting Initiative (GRI) and the Greenhouse Gas Protocol, the latter lag in ESG adoption, exposing them to financial and competitive risks. The findings highlight the economic benefits of standardized ESG reporting, identify gaps in local practices, and provide actionable recommendations—including adopting international frameworks, investing in sustainability training, and leveraging government incentives. Additionally, the study supports regulatory preparedness for upcoming EU requirements. These insights contribute to the broader discourse on integrating ESG principles into corporate strategy and financial performance.
Copyright (c) 2025 Vladimira Novakova (Author) https://creativecommons.org/licenses/by/4.0
Revolutionizing Decision-Making in E-Commerce and IT Procurement: An IVPNS-COBRA Linguistic Variable Framework for Enhanced Multi-Criteria Analysis
Real-world challenges in e-commerce strategy selection and IT supplier evaluation are inherently complex due to uncertainty and incomplete information, necessitating a multi-faceted approach for effective decision-making. Traditional single methods often fail to address these complexities adequately. To overcome this limitation, this research introduces an advanced methodology by integrating the Interval-Valued Pythagorean Neutrosophic Set (IVPNS) with the Comprehensive Distance-Based Ranking (COBRA) approach, enhancing the handling of indeterminate information related to truth, falsity, and uncertainty. IVPNS provides a robust mathematical framework for managing ambiguity, a common challenge in Multi-Criteria Decision-Making (MCDM) across various domains. Prior to this study, IVPNS lacked a linguistic variable—a crucial component for expressing human judgments. To bridge this gap, we enhance the IVPNS-COBRA framework by incorporating 5-point and 7-point linguistic scales, ensuring compliance with established IVPNS conditions. Additionally, we introduce two distance measures, Euclidean and Hamming distances, to refine alternative evaluations. The proposed IVPNS-COBRA method is validated through real-world applications, including the evaluation of three e-commerce development strategies (assessed against five criteria) and four IT supplier selection alternatives (evaluated using nine criteria). The results demonstrate the reliability of this MCDM model, providing decision-makers with a more precise and structured approach for selecting optimal e-commerce strategies and IT suppliers in complex environments.
Interval-valued Pythagorean Neutrosophic set
Copyright (c) 2025 Samsiah Abdul Razak, Zahari Md Rodzi, Faisal Al-Sharqi, Nazirah Ramli (Author) https://creativecommons.org/licenses/by/4.0
Study on the Countermeasures and Insights of Consumption Structure Optimization under the Strategy of Expanding Domestic Demand— Multi-period and Multi-dimensional Analysis Based on Kunming Panel Data from 2017 to 2024
In 2025, the Chinese Government Work Report proposed accelerating the stimulation of domestic demand, particularly in the area of consumption. This study takes Kunming as a case example, integrating 44 types of consumption and economic indicators, and employs the Pearson correlation coefficient and principal component analysis to construct a multidimensional analytical framework. The findings indicate that demand for non-essential and high-end consumer goods in Kunming remains persistently sluggish; consumption related to the real estate industry chain has declined significantly; there is an excessive reliance on government spending and public services; the transformation of traditional retail formats is lagging; income distribution and savings tendencies are constraining demand; and fluctuations in imports and exports are exacerbating consumption uncertainty. It is recommended that Kunming optimize its consumption supply structure, stabilize the real estate industry chain, enhance endogenous market momentum, accelerate digital transformation, improve the income distribution mechanism, and strengthen the competitiveness of local brands. This research offers valuable insights for China and other countries seeking to promote consumption.
Copyright (c) 2025 Qianyu Li (Author) https://creativecommons.org/licenses/by/4.0
SVAR MODEL TO EXAMINE THE SHORT AND LONG TERM MONETARY POLICY IN INDONESIA
This research was conducted by the author to see the impact of monetary policy on the domestic macro-economic variables is important in Indonesia using a structural model of the short and long term, contained in a structural model of vectorAutoregressions (SVAR). The author uses the effects of macroeconomic policy is the key in this research, by applying the matrix model SVAR initiated by Bernanke & Mihov (1998) short term and Blancard & Quah (1989) long term. Research conducted using the 4 variables, consisting of two domestic variables, namely the interest rate of Bank Indonesia (SBI), the consumer price index (CPI) and two non-domestic variables, namely the interest rate the central bank United States(FFF), the rate of inflation in the United States (INF_USA). From the research that has been done can be inferred that the SVAR models used in this study can be used as a reference to the theoretical expectations in order to show that the rise in interest rates and the central bank of the United States could affect Indonesia's domestic variables. Data: Received: 8 Oct 2015 Revised: 21 Nov 2015 Accepted: 6 Dec 2015 Published: 20 Dec 2015
Copyright (c) 2015 Teguh Sugiarto (Author) https://creativecommons.org/licenses/by/4.0
THE MARRIAGE PREMIUM AND PRODUCTIVITY: THE CASE OF NBA PLAYERS
Numerous studies have shown that there is a marriage premium among male workers - married men's wages are higher than those of single men. One explanation for the existence of a marriage premium is increased productivity. While the estimation of workers' productivity in the standard labor market is often inaccurate and subjective, throughput can be estimated easily in professional sports. This study examines whether a marriage premium exists in relation to the performance and efficiency of professional league basketball players in the United States (NBA). A total marriage premium of 16.4% was found in a comprehensive analysis of the performance of all league players. A more thorough analysis showed that there is a higher marriage premium among international players compared to American players. Data: Received: 20 Sep 2015 Revised: 14 Nov 2015 Accepted: 6 Dec 2015 Published: 20 Dec 2015
Copyright (c) 2015 Ze'ev Shtudiner (Author) https://creativecommons.org/licenses/by/4.0