International Journal of Economic Sciences
type: channel
description: 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 publis…
publisher: Scientific Oasis
language: en
publication name: International Journal of Economic Sciences
issn: 1804-9796
items: Foreign Investors' Motives for Investing in Economies in Transition: The Case of Serbia
items: Economic Impacts of an Emissions Trading Scheme Pilot in Oligopolistic Agri-Food Supply Chains: A Network Equilibrium Analysis
items: Rethinking Higher Education Financing: Comparative Evidence on Equity, Capacity, and Social Value
items: Macroeconomic Determinants of Stock Market Volatility: A Comparative GARCH Analysis across Financial Markets with Varying Depth and Liquidity
items: Fostering Supply Chain Flexibility Under Economic Uncertainty: Role of Digitalization, Collaboration, Visibility, and Risk Management
items: Decision-Making Style of Managers in the Public Sector: Is There a Possibility for Improvement?
items: Evaluating Green Economy Strategies Through Multi-Criteria Decision Analysis: A Systematic Review
items: The Role of Financial Development in ESG Performance: A Bibliometric Analysis
items: Strategic Orientation and Firm Performance of Construction Enterprises in Guangdong Province: The Moderating Effect of Digital Technology Adoption
items: Research on the Role of ESG Performance in Capital Market Pricing Efficiency: An Analysis Based on Stock Price Synchronicity
items: Artificial Intelligence and Enterprise Export Price Markup in China’s Economy: Based on Large Language Models
items: Influence of Educational Factors on the Entrepreneurial Potential of Students as a Prerequisite for Economic Development
items: Logistics Infrastructure and Regional Economic Growth: A Causal Evaluation of Coordination Policies in China's Urban Agglomerations
items: Economics and Multi-Criteria Decision Support for Sustainable Cobalt Production
items: Artificial Intelligence Applications and Corporate Sustainable Development: An Economic and Environmental Performance Perspective
items: Emergency Management in Risk Control: Approaches for Surpassing Financial Challenges
items: Cross-National Benchmarking of Bankruptcy Prediction Models Across V4 Economies
items: Agility of the Drug Supply Chain Considering Economic and Social Aspects: Use of Internet of Things and Big Data Analysis
items: Economic Impact of University Knowledge Spillovers on Firm Innovation: A Spatial Analysis from China
items: Omnichannel Digital Marketing in the Postal and Logistics Sector: Strategic Functions and the Role of Leadership Visibility
items: Economic Efficiency Assessment of Sustainability Investment in EU Member States: A Data Envelopment Analysis with Crisis Impact Evaluation (2015-2024)
items: The Economic Mechanisms of Artificial Intelligence Resources Affecting Green Risk Management: Empirical Evidence from Chinese Listed Firms
items: The Synergy and Dynamic Interaction between Financial Opening-Up and RMB Internationalization
items: Spatial Autocorrelation in Housing Prices: Analysis of the Brno Metropolitan Area
items: Economic Evaluation of Digital Suppliers for Manufacturing SMEs Using Pythagorean Neutrosophic TOPSIS and VIKOR with a Flexible Distance Metric
items: Strategic Challenges and Opportunities for the Czech Steel Industry: A Path toward Sustainable Competitiveness
items: Smart Tourism Cities and Income Equity: How Digital Economy Reshapes Urban-Rural Disparities
items: The Mixed Incentive Effect of Government Subsidies and Venture Capital on the Sustainability of Enterprise Innovation
items: Digital Entrepreneurship Within International Business Landscape: Implications for Marketing Strategies
items: Beyond ESG: Unpacking Brand Loyalty Through the Emotional Mechanisms Lenses of Attachment and Love—A Hierarchical Regression Study of Alibaba in China

Foreign Investors' Motives for Investing in Economies in Transition: The Case of Serbia
type: item
description: Transition economies are attractive destinations for foreign direct investment (FDI), offering lower production costs, emerging consumer markets, and opportunities for strategic positioning, while also facing structural and institutional constraints. This study examines the motives of foreign investors in Serbia, with a particular focus on how investment motivations vary according to firms’ level of internationalization. The analysis is based on a survey of 300 foreign investors that entered the Serbian market between 2001 and 2019 (response rate: 29.3%). The findings indicate that the most important motives include entering a new market, observing consumers, customers, and suppliers, first-mover advantage, the availability of financial resources in the Serbian market, economies of scale, characteristics of the Serbian tax system, and natural resources and their prices in Serbia. However, a more detailed analysis reveals significant differences across investor types. Regional firms are primarily driven by market expansion, economies of scale, and resource-related factors, while global firms place greater emphasis on infrastructure, technological and informational inputs, and integration into broader production networks. Multinational firms display a more balanced pattern of motives, without a clearly dominant driver. These results highlight the importance of investor heterogeneity in shaping FDI patterns in transition economies. They also suggest that policy approaches tailored to specific investor profiles may be more effective than uniform strategies in attracting and sustaining foreign investment.
subject: Articles
  topic: section
subject: Foreign direct investment
  topic: keywords
subject: Internationalization
  topic: keywords
subject: Foreign investors
  topic: keywords
subject: Serbia
  topic: keywords
creator: Darko Marjanović
creator: Branislav Dudic
creator: Elena Jovičić
creator: Jelena Vujadinović
creator: Nikola Martinović
creator: Đorđe Ćelić
rights: Copyright (c) 2026 Darko Marjanović, Branislav Dudic, Elena Jovičić, Jelena Vujadinović, Nikola Martinović, Đorđe Ćelić (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-06-27
publication date: 2026-06-27
starting page: 1
ending page: 20
doi: 10.31181/ijes1612027287

Economic Impacts of an Emissions Trading Scheme Pilot in Oligopolistic Agri-Food Supply Chains: A Network Equilibrium Analysis
type: item
description: Emissions Trading Scheme (ETS) pilot programs impose binding quota constraints and enable allowance trading, reshaping cost structures and strategic interactions in oligopolistic agri-food supply chains. This paper quantifies the resulting economic impacts, including equilibrium prices, profits, and trade flows, by developing a multi-tier network equilibrium model that links upstream suppliers, downstream manufacturers, domestic and international demand markets, and a carbon trading center under an Emissions Trading Scheme pilot setting. Suppliers invest in low-carbon technologies, while manufacturers undertake labor-efficiency investments that affect unit costs and throughput, with proximity-based spillovers captured via a grid-distance mechanism. The equilibrium conditions are formulated as a variational inequality framework and computed numerically, enabling systematic comparative statics analysis under alternative quota stringency and trading conditions. Using China-EU garlic trade as an illustrative case, the numerical analysis indicates that tighter policy constraints and trading conditions shift production and allowance-trading patterns, with corresponding changes in prices, profits, and emissions across tiers. It also shows that moderate efficiency investment can improve productivity and may reduce aggregate emissions, whereas very high unilateral investment tends to exhibit diminishing returns and can be associated with non-smooth adjustments in network allocations. Finally, coordinated upstream-downstream investment is generally associated with more stable outcomes than isolated initiatives. The framework offers a decision-relevant tool for evaluating Emissions Trading Scheme pilot designs in regulated international agri-food trade networks.
subject: Articles
  topic: section
subject: Emissions Trading Scheme pilots
  topic: keywords
subject: Network equilibrium
  topic: keywords
subject: Variational inequality
  topic: keywords
subject: Oligopolistic supply chains
  topic: keywords
subject: international agri-food trade
  topic: keywords
subject: Economic impacts
  topic: keywords
creator: Tingfeng Wu
creator: Heyin Hou
rights: Copyright (c) 2026 Tingfeng Wu, Heyin Hou (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-04-21
publication date: 2026-04-21
starting page: 443
ending page: 477
doi: 10.31181/ijes1512026280

Rethinking Higher Education Financing: Comparative Evidence on Equity, Capacity, and Social Value
type: item
description: Higher education finance is often debated through statutory tuition, although this indicator does not capture system capacity or the burden students actually experience. This article examines European higher education financing by distinguishing between statutory price, cost benchmark, and effective student burden. The study uses a comparative cross-sectional design based on linked public datasets: Eurydice fee and support indicators for 39 systems, EUROSTUDENT 8 indicators on student expenses and financial difficulty, and OECD, Eurostat, UNESCO, and World Bank data on expenditure, national income, and funding mix. The analysis combines regime mapping, Spearman rank correlations, parsimonious ordinary least squares models with HC3 robust standard errors, and robustness checks. The results show that GDP per capita is weakly associated with statutory tuition but more clearly associated with expenditure per tertiary student. Statutory fees also provide a weak guide to severe student financial strain, whereas weighted effective burden better captures the share of students exposed to payment and the resources available to absorb it. Lithuania illustrates the policy relevance of this distinction: low statutory fee indicators coexist with modest per-student expenditure and non-trivial effective burden. The article concludes that policy debate should move from headline tuition comparisons toward a three-part assessment of price, capacity, and burden.
subject: Articles
  topic: section
subject: Higher education finance
  topic: keywords
subject: Comparative methodology
  topic: keywords
subject: Robustness analysis
  topic: keywords
subject: Tuition fees
  topic: keywords
subject: Student affordability
  topic: keywords
subject: Cost benchmark
  topic: keywords
subject: Lithuania
  topic: keywords
creator: Gabija Skučaitė
creator: Mehmet Recai Uygur
rights: Copyright (c) 2026 Gabija Sciences, Mehmet Recai Uygur (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-07-06
publication date: 2026-07-06
starting page: 1
ending page: 21
doi: 10.31181/ijes1612027292

Macroeconomic Determinants of Stock Market Volatility: A Comparative GARCH Analysis across Financial Markets with Varying Depth and Liquidity
type: item
description: This research investigates how selected macroeconomic determinants influence stock market returns and volatility across financial systems characterized by varying degrees of market depth and liquidity. The analysis focuses on four stock indices—FTSE 100, FTSE China A50, BUDAPEST SE, and SBITOP—over the period 2012–2022, which is further divided into pre-crisis and crisis/post-crisis subperiods to capture the effects of the COVID-19 shock. To account for time-varying and asymmetric volatility dynamics, the study employs customized multivariate GARCH-type models, including EGARCH, PGARCH, and TGARCH specifications, with model selection guided by information criteria. The empirical results confirm that macroeconomic factors such as inflation, interest rates, exchange rates, and commodity prices exert statistically significant effects on stock index returns and volatility, although the magnitude and direction of these effects differ across markets and across time periods. Developed and less liquid markets display distinct volatility transmission mechanisms, particularly during crisis periods. Overall, the findings highlight the relevance of flexible GARCH-based frameworks for understanding market-specific volatility dynamics and provide useful insights for investors and policymakers operating under conditions of heightened uncertainty.
subject: Articles
  topic: section
subject: Stock market volatility
  topic: keywords
subject: GARCH models
  topic: keywords
subject: Financial market development
  topic: keywords
subject: Macroeconomic factors
  topic: keywords
subject: Crisis effects
  topic: keywords
creator: Pavle Jakšić
creator: Mirela Mitrašević
creator: Darko Marjanović
creator: Branislav Dudić
creator: Miloš Pjanić
creator: Predrag Vidicki
rights: Copyright (c) 2026 Pavle Jakšić, Mirela Mitrašević, Darko Marjanović, Branislav Dudić, Miloš Pjanić, Predrag Vidicki (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-06-26
publication date: 2026-06-26
starting page: 1
ending page: 31
doi: 10.31181/ijes1612027288

Fostering Supply Chain Flexibility Under Economic Uncertainty: Role of Digitalization, Collaboration, Visibility, and Risk Management
type: item
description: Today, turbulence in the economic environment creates numerous challenges across various aspects of firms, requiring organizations to respond quickly to survive and grow. As a result, supply chain flexibility (SCF) has become a strategic priority for companies and a prevalent topic in academia. Grounded in Resource-Based View (RBV) and Dynamic Capabilities Theory (DCT), this study examines how the business environment (ENVI) drives digitalization in operations management activities (DOM) and how DOM enhances SCF both directly and indirectly through supply chain visibility (SCV), supply chain collaboration (SCC), and supply chain risk management (SCRM). In this research, we collected data from 289 Vietnamese firms and analyzed them using PLS-SEM. We checked the reliability and discriminant validity of the measurement scales, then predicted the effect sizes and mediation effects of the relationships. The results show that ENVI significantly drives DOM adoption, which in turn improves SCV, SCC, and SCRM, thereby strengthening SCF. The findings reveal that supply chain visibility and risk management, but not collaboration, mediate the DOM–SCF relationship and function as sequential pathways through which environmental turbulence translates into greater supply chain flexibility. Furthermore, the research offers managerial insights into leveraging digital tools to construct more adaptable and resilient supply chains in volatile economic environments.
subject: Articles
  topic: section
subject: Digitalization of operations management
  topic: keywords
subject: Supply chain flexibility
  topic: keywords
subject: Collaboration
  topic: keywords
subject: Visibility
  topic: keywords
subject: Risk management
  topic: keywords
creator: Thi Huong Tran
creator: Thu Vuong Thi Chuc
creator: Dieu Le Thi Huyen
rights: Copyright (c) 2026 Thi Huong Tran, Thu Vuong Thi Chuc, Dieu Le Thi Huyen (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-04-22
publication date: 2026-04-22
starting page: 1
ending page: 16
doi: 10.31181/ijes1612027284

Decision-Making Style of Managers in the Public Sector: Is There a Possibility for Improvement?
type: item
description: The modern market economy is characterized by turbulence, uncertainty, and an increasing pace of change. In such conditions, decision-making represents a fundamental and dynamic process in which managerial decisions directly influence organizational effectiveness and overall performance. The primary objective of this study is to identify, using a scientifically grounded methodological framework, the key determinants of managerial decision-making styles in public enterprises, with particular emphasis on the organization of work processes, individual demographic characteristics, and economic aspects of management. The research was conducted in public sector enterprises, which have shown insufficient functionality for many years. The study was conducted on a sample of 426 managers across a range of organizations, employing standardized instruments, namely the General Decision-Making Scale (GDMS) and the Work Organization Assessment Questionnaire (WOAQ). The results indicated statistically significant differences in managerial decision-making styles. Furthermore, a significant association was identified between decision-making styles and various dimensions of work organization. In addition, decision-making styles were found to be significantly related to the general demographic characteristics of the participating managers. Based on the research results, improving the decision-making process is necessary in the new digital environment.
subject: Articles
  topic: section
subject: Decision making
  topic: keywords
subject: Public companies
  topic: keywords
subject: Styles
  topic: keywords
subject: Demographic characteristics
  topic: keywords
subject: Economic aspects of management
  topic: keywords
subject: Empirical research
  topic: keywords
subject: Improvement
  topic: keywords
creator: Slavica Mitrovic Veljkovic
creator: Ivana Djakovic Radojicic
creator: Ana Nesic Tomasevic
creator: Mladen Subotic
creator: Dragan Nikolic
creator: Branislav Dudic
rights: Copyright (c) 2026 Slavica Mitrovic Veljkovic, Ivana Djakovic Radojicic, Ana Nesic Tomasevic, Mladen Subotic, Dragan Nikolic, Branislav Dudic (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-04-12
publication date: 2026-04-12
starting page: 386
ending page: 405
doi: 10.31181/ijes1512026283

Evaluating Green Economy Strategies Through Multi-Criteria Decision Analysis: A Systematic Review
type: item
description: 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
subject: Articles
  topic: section
subject: Sustainable development
  topic: keywords
subject: Green economy
  topic: keywords
subject: Multi-criteria decision analysis
  topic: keywords
subject: MCDM
  topic: keywords
subject: Bibliometric review
  topic: keywords
subject: Hybrid decision models
  topic: keywords
creator: Sushil Kumar Sahoo
creator: Shankha Shubhra Goswami
creator: Darko Božanić
creator: Soupayan Mitra
rights: Copyright (c) 2025 Sushil Kumar Sahoo, Shankha Shubhra Goswami, Darko Božanić, Soupayan Mitra (Author) https://creativecommons.org/licenses/by/4.0
date: 2025-11-27
publication date: 2025-11-27
starting page: 385
ending page: 407
doi: 10.31181/ijes1412025245

The Role of Financial Development in ESG Performance: A Bibliometric Analysis
type: item
description: This study explores the intersection between financial development and environmental, social, and governance (ESG) performance using a comprehensive bibliometric analysis. Drawing on 443 academic publications extracted from the Scopus database between 2000 and 2023, the research identifies major contributors, trending topics, and thematic evolutions in this interdisciplinary field. Using co-authorship, co-citation, and keyword co-occurrence analyses, the study reveals increasing scholarly attention on sustainable finance, ESG disclosure, and the role of institutions in fostering ESG practices. The results highlight a growing convergence between financial systems and sustainability goals, with significant research clusters emerging in Europe, North America, and Asia. The study contributes to the literature by mapping the intellectual structure of ESG–finance research and identifying gaps and future research directions. These insights are valuable for academics, practitioners, and policymakers aiming to align financial development with sustainability imperatives.
subject: Articles
  topic: section
subject: Financial Development
  topic: keywords
subject: ESG Performance
  topic: keywords
subject: Sustainable Finance
  topic: keywords
subject: Bibliometric Analysis
  topic: keywords
creator: Adel Bogari
rights: Copyright (c) 2026 Adel Bogari (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-26
publication date: 2026-01-26
starting page: 251
ending page: 302
doi: 10.31181/ijes1512026249

Strategic Orientation and Firm Performance of Construction Enterprises in Guangdong Province: The Moderating Effect of Digital Technology Adoption
type: item
description: This study examines how digital technology adoption moderates the relationship between strategic orientation and economic performance in construction enterprises. Drawing on the resource-based view and dynamic capabilities theories, we surveyed 193 construction firms in Guangdong Province, China, to investigate the economic effects of market orientation, entrepreneurial orientation, and technology orientation on performance, with digital technology adoption as a boundary condition. Using partial least squares structural equation modeling (PLS-SEM), our findings reveal differential impacts of strategic orientations on performance. Technology orientation emerges as the strongest predictor of economic performance (β = 0.246, p < 0.01), followed by market orientation (β = 0.187, p < 0.05), while entrepreneurial orientation shows no significant direct effect. Critically, digital technology adoption significantly moderates both the market orientation–performance (β = 0.134, p < 0.05) and technology orientation–performance (β = 0.198, p < 0.01) relationships, amplifying their economic value creation under conditions of high digital adoption. The model explains 38.4% of performance variance, with simple slope analysis revealing that strategic orientations generate substantial performance benefits only when supported by adequate digital infrastructure. These findings challenge the universal applicability of entrepreneurial frameworks in traditional industries and suggest that digital transformation fundamentally reconceptualizes which strategic orientations remain economically viable in increasingly digitized business environments.
subject: Articles
  topic: section
subject: Strategic orientation
  topic: keywords
subject: Digital technology adoption
  topic: keywords
subject: Economic performance
  topic: keywords
subject: Construction industry
  topic: keywords
subject: Moderation effect
  topic: keywords
creator: Hongbo Zhou
creator: Ye Zhang
creator: Muneera Binti Esa
rights: Copyright (c) 2025 Hongbo Zhou, Ye Zhang, Muneera Binti Esa (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-17
publication date: 2026-01-17
starting page: 177
ending page: 199
doi: 10.31181/ijes1512026233

Research on the Role of ESG Performance in Capital Market Pricing Efficiency: An Analysis Based on Stock Price Synchronicity
type: item
description: 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.
subject: Articles
  topic: section
subject: ESG
  topic: keywords
subject: Stock Price Synchronicity
  topic: keywords
subject: Mediating Effect
  topic: keywords
subject: Information Efficiency Theory
  topic: keywords
subject: Noise Theory
  topic: keywords
creator: Yuming Yin
creator: Zilong Li
creator: Kai Li
creator: Tao Wang
creator: Shunwei Cui
rights: Copyright (c) 2026 Yuming Yin, Zilong Li, Kai Li, Tao Wang, Shunwei Cui (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-17
publication date: 2026-01-17
starting page: 19
ending page: 40
doi: 10.31181/ijes1512026218

Artificial Intelligence and Enterprise Export Price Markup in China’s Economy: Based on Large Language Models
type: item
description: China’s exports face long-standing challenges of low quality, low price, and low profit margins. Amid intensifying global economic competition and deeper value chains, breaking the ‘low-value-added lock-in’ to boost export enterprises’ profit margins is urgent for addressing foreign trade bottlenecks. This study systematically examines artificial intelligence (AI)’s effect and mechanism on export enterprises’ price markup. It integrates 2007–2016 data from China’s Customs Database and Shanghai and Shenzhen A-share manufacturing listed companies, combined with AI indicators built by extracting annual report text via large language models. Results show AI significantly raises export enterprises’ price markup, with the ‘intelligent empowerment’ model having a stronger promotional effect than ‘machine replacing human’. Mechanism analysis reveals AI’s dual impacts: positive effects from efficiency improvement and technological innovation, and negative effects from intensified market competition and higher information transparency. Heterogeneity analysis finds AI benefits state-owned enterprises, high-productivity enterprises, quality-competitive enterprises, and those exporting to developed countries more. Additionally, it reduces markup dispersion and improves resource allocation efficiency. Overall, AI drives export enterprises to break low-value-added dilemmas, optimise resource allocation, and further boost China’s export economy.
subject: Articles
  topic: section
subject: Artificial intelligence
  topic: keywords
subject: Price markup
  topic: keywords
subject: Economic upgrading
  topic: keywords
subject: Staggered difference-in-differences
  topic: keywords
subject: Large language models
  topic: keywords
creator: Zhaosong Li
creator: Weiwen Qian
rights: Copyright (c) 2026 Zhaosong Li, Weiwen Qian (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-17
publication date: 2026-01-17
starting page: 200
ending page: 230
doi: 10.31181/ijes1512026255

Influence of Educational Factors on the Entrepreneurial Potential of Students as a Prerequisite for Economic Development
type: item
description: The primary objective of this study is to examine the influence of various educational factors on the entrepreneurial potential of university students as a prerequisite for the stability of business and economic systems, especially in EU candidate countries. Education is crucial for developing entrepreneurial skills and potential entrepreneurs who contribute to the development of national economies. The research sample comprised students from two non-EU countries and one EU member state. Data were collected from a total of 1,008 university students across these three countries. The instruments utilized in the study were the Questionnaire on Entrepreneurial Traits (QET) and the Scale of Entrepreneurial Potential (SEP). Different educational factors were analysed in this research: entrepreneurial education, different educational profiles, and the influence of faculties with a supportive environment toward entrepreneurship. Canonical discriminant analysis confirmed the significance and structure of differences among students who belong to faculties with different: a) orientations toward entrepreneurship, b) types of faculties, and c) experiences of previous entrepreneurial education compared with those who did not receive such education, considering their performance across the dimensions of the Entrepreneurial Traits Model (QET) and the Entrepreneurial Potential Model (SEP). Results from this research could shed light on the development of entrepreneurship and the importance of this phenomenon, which proves to be crucial for the regional economy.
subject: Articles
  topic: section
subject: Entrepreneurship
  topic: keywords
subject: Education
  topic: keywords
subject: Students
  topic: keywords
subject: Faculties
  topic: keywords
creator: Mladen Subotic
creator: Mia Maric
creator: Branislav Dudic
creator: Slavica Mitrovic Veljkovic
creator: Djordje Celic
creator: Aleksandra Peric
rights: Copyright (c) 2026 Mladen Subotic, Mia Maric, Branislav Dudic, Slavica Mitrovic Veljkovic, Djordje Celic, Aleksandra Peric (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-17
publication date: 2026-01-17
starting page: 231
ending page: 249
doi: 10.31181/ijes1512026238

Logistics Infrastructure and Regional Economic Growth: A Causal Evaluation of Coordination Policies in China's Urban Agglomerations
type: item
description: This study provides a causal estimate of the impact of logistics-focused coordination policies on regional economic growth in China. While the role of logistics in development is widely acknowledged, the existing literature offers limited causal evidence on the economic mechanisms through which policy-driven coordination unlocks growth. Addressing this gap, we employ a quasi-experimental design, treating the staggered implementation of coordination policies in three major urban agglomerations—Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD)—as natural experiments. We estimate a heterogeneous Difference-in-Differences (DID) model complemented by an instrumental variable (IV) approach to address endogeneity. Our analysis, structured around supply-side production scale, spatial coordination efficiency, and demand-side market intensity, reveals significant positive effects. However, we find heterogeneous treatment effects: the growth mechanism is infrastructure-driven in BTH, market-integration-led in YRD, and reliant on cross-border cooperation in PRD. By quantifying these distinct causal pathways, this research contributes to the discourses in economic geography and regional policy, underscoring the importance of regionally-tailored economic strategies for achieving efficient resource allocation and sustainable development.
subject: Articles
  topic: section
subject: Urban agglomeration coordination mechanisms
  topic: keywords
subject: Industrial collaboration
  topic: keywords
subject: Spatial spillovers
  topic: keywords
creator: Xiaobo Xue
creator: Guangbo Piao
rights: Copyright (c) 2026 Xiaobo Xue, Guangbo Piao (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-17
publication date: 2026-01-17
starting page: 250
ending page: 264
doi: 10.31181/ijes1512026236

Economics and Multi-Criteria Decision Support for Sustainable Cobalt Production
type: item
description: 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.
subject: Articles
  topic: section
subject: Economic Risk Assessment
  topic: keywords
subject: Critical minerals
  topic: keywords
subject: PESTLE analysis
  topic: keywords
subject: SWOT modelling
  topic: keywords
subject: Resource economics
  topic: keywords
subject: Operational research
  topic: keywords
creator: Rosa María Ricoy-Casas
creator: Jose María Lago Cabo
creator: Jorge Eduardo Vila Biglieri
creator: Darko Bozanic
rights: Copyright (c) 2026 Rosa María Ricoy-Casas , Jose María Lago Cabo, Jorge Eduardo Vila Biglieri, Darko Bozanic (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-17
publication date: 2026-01-17
starting page: 137
ending page: 157
doi: 10.31181/ijes1512026237

Artificial Intelligence Applications and Corporate Sustainable Development: An Economic and Environmental Performance Perspective
type: item
description: 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 …
subject: Articles
  topic: section
subject: Artificial Intelligence
  topic: keywords
subject: Corporate Sustainable Development Performance
  topic: keywords
subject: Financial Performance
  topic: keywords
subject: Environmental Performance
  topic: keywords
creator: Huixin Sun
creator: Rongchun Zhu
rights: Copyright (c) 2026 Huixin Sun, Rongchun Zhu (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-17
publication date: 2026-01-17
starting page: 85
ending page: 113
doi: 10.31181/ijes1512026234

Emergency Management in Risk Control: Approaches for Surpassing Financial Challenges
type: item
description: 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.
subject: Articles
  topic: section
subject: Risk management
  topic: keywords
subject: Insurance companies
  topic: keywords
subject: Innovation
  topic: keywords
subject: Risk assessment
  topic: keywords
subject: Teamwork
  topic: keywords
subject: Financial frugality
  topic: keywords
creator: Nataliia Tymoshyk
creator: Dmytro Rasshyvalov
creator: Iryna Tarasenko
creator: Kseniia Velykykh
rights: Copyright (c) 2026 Nataliia Tymoshyk, Dmytro Rasshyvalov, Iryna Tarasenko, Kseniia Velykykh (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-17
publication date: 2026-01-17
starting page: 41
ending page: 53
doi: 10.31181/ijes1512026226

Cross-National Benchmarking of Bankruptcy Prediction Models Across V4 Economies
type: item
description: In recent years, the prediction of corporate bankruptcy has become an increasingly important topic in financial and economic research, particularly in the manufacturing sector of Central and Eastern Europe. Accurate early-warning models are essential for mitigating financial risks and ensuring business sustainability. This study investigates the comparative performance of classical statistical and machine learning (ML) models for predicting corporate bankruptcy across manufacturing firms in the Visegrad Group (V4) countries, addressing the problem of financial distress forecasting in transitional economies. The purpose of the research is to evaluate whether pooled regional models perform as effectively as country-specific models and to examine the influence of national data characteristics, such as sample size and heterogeneity, on predictive accuracy. A balanced dataset of firm-level financial indicators from Slovakia, the Czech Republic, Hungary, and Poland was employed, and three classification techniques, namely logistic regression (LR), artificial neural networks (ANN), and decision trees (DT), were applied to develop predictive models for individual countries as well as for the combined V4 region. Model performance was assessed using multiple classification metrics including accuracy, F1 score, AUC (area under the receiver operating characteristic curve), precision, and recall, with careful attention to handling class imbalance. The results indicate consistently high discriminatory power across all models, with AUC values ranging from 0.929 to 0.991, classification accuracy between 94.9% and 98.3%, and F1 scores from 0.972 to 0.991. Artificial neural networks slightly outperformed logistic regression and decision trees, particularly in countries with larger samples, while pooled models demonstrated performance comparable to country-specific models, highlighting the generalizability of predictive models across V4 economies. The findings carry practical implicat…
subject: Articles
  topic: section
subject: Bankruptcy prediction
  topic: keywords
subject: Predictive analytics
  topic: keywords
subject: Economic decision-making
  topic: keywords
subject: AI and machine learning
  topic: keywords
subject: Cross-national analysis
  topic: keywords
subject: Visegrad Group countries
  topic: keywords
creator: Dominika Gajdosikova
creator: Katarina Valaskova
creator: Pavol Durana
rights: Copyright (c) 2026 Dominika Gajdosikova, Katarina Valaskova, Pavol Durana (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-17
publication date: 2026-01-17
starting page: 158
ending page: 176
doi: 10.31181/ijes1512026223

Agility of the Drug Supply Chain Considering Economic and Social Aspects: Use of Internet of Things and Big Data Analysis
type: item
description: 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 ne…
subject: Articles
  topic: section
subject: Drug supply chain management
  topic: keywords
subject: Robust feasibility optimization
  topic: keywords
subject: Uncertainty
  topic: keywords
subject: Internet of Things
  topic: keywords
subject: MOGWO algorithm
  topic: keywords
subject: Economic analysis
  topic: keywords
creator: Amirhamzeh Razavinejad
creator: Seyed Esmaeil Najafi
creator: Mehran Khalaj
creator: Hamed Kazemi Pour
rights: Copyright (c) 2026 Amirhamzeh Razavinejad, Seyed Esmaeil Najafi, Mehran Khalaj, Hamed Kazemi Pour (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-17
publication date: 2026-01-17
starting page: 54
ending page: 84
doi: 10.31181/ijes1512026214

Economic Impact of University Knowledge Spillovers on Firm Innovation: A Spatial Analysis from China
type: item
description: 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.
subject: Articles
  topic: section
subject: Knowledge Spillovers
  topic: keywords
subject: Geographic Distance
  topic: keywords
subject: Corporate innovation
  topic: keywords
subject: Regional Economic Development
  topic: keywords
subject: University–Enterprise Collaboration
  topic: keywords
creator: Xiangshuo Zhang
rights: Copyright (c) 2026 Xiangshuo Zhang (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-17
publication date: 2026-01-17
starting page: 114
ending page: 136
doi: 10.31181/ijes1512026217

Omnichannel Digital Marketing in the Postal and Logistics Sector: Strategic Functions and the Role of Leadership Visibility
type: item
description: 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.
subject: Articles
  topic: section
subject: Omni-Cultural Marketing
  topic: keywords
subject: Digital Logistics
  topic: keywords
subject: Multichannel Communication
  topic: keywords
subject: Customer Experience
  topic: keywords
subject: Public Visibility of the Leader
  topic: keywords
subject: Personalization of Service
  topic: keywords
subject: Brand Trust
  topic: keywords
creator: Marta Yankiv
creator: Roman Mykytyuk
creator: Andrii Gukaliuk
rights: Copyright (c) 2026 Marta Yankiv, Roman Mykytyuk , Andrii Gukaliuk (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-17
publication date: 2026-01-17
starting page: 1
ending page: 18
doi: 10.31181/ijes1512026199

Economic Efficiency Assessment of Sustainability Investment in EU Member States: A Data Envelopment Analysis with Crisis Impact Evaluation (2015-2024)
type: item
description: The article proposes an approach for assessing the efficiency of sustainability-related investments in the EU-27 member states over the period 2015–2024. This is achieved through a combination of a DEA-based approach, a composite efficiency coefficient, and cluster analysis. The composite coefficient measures the relationship between calibrated outcomes and inputs and, in essence, provides a “value-for-money” assessment of sustainable expenditures. The results show substantial differences between countries. The Baltic states and several Central and Eastern European economies display high efficiency, while some of the traditional “leaders” in sustainability exhibit more modest returns per unit of investment. The cluster analysis groups the countries into four clusters with similar characteristics. These range from groups in which investment volumes play the leading role to groups in which efficiency is the key driver, and clearly show differences in the outcomes of the policies pursued (including target-setting and the design of EU financial instruments). The analysis also takes into account the impact of COVID-19 and the war in Ukraine. The main finding is that institutional quality is a stronger factor in maintaining efficiency during crises than the level of economic development. This conclusion underlines that sustainability objectives should also include measurable indicators of administrative capacity in order to improve the system’s ability to adapt in times of crisis. The proposed model provides an empirical basis for improving the way European targets and instruments are formulated. It can help direct limited resources more effectively towards countries and regions with the greatest potential for efficiency improvement.
subject: Articles
  topic: section
subject: Economic efficiency
  topic: keywords
subject: Sustainability investment
  topic: keywords
subject: Financial resources
  topic: keywords
subject: Data Envelopment Analysis (DEA)
  topic: keywords
subject: Efficiency ratio (ER)
  topic: keywords
subject: EU‑27 sustainability policy
  topic: keywords
subject: Green public finance
  topic: keywords
subject: Crisis resilience
  topic: keywords
subject: Institutional quality
  topic: keywords
subject: Climate and energy transition
  topic: keywords
creator: Stefan Petrov
rights: Copyright (c) 2026 Stefan Petrov (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-04-15
publication date: 2026-04-15
starting page: 406
ending page: 442
doi: 10.31181/ijes1512026278

The Economic Mechanisms of Artificial Intelligence Resources Affecting Green Risk Management: Empirical Evidence from Chinese Listed Firms
type: item
description: Against the backdrop of the digital economy, artificial intelligence (AI) has become a critical strategic resource for firms. Beyond enhancing economic performance, AI has opened new pathways for addressing environmental externalities. Drawing on the resource-based view (RBV), this paper examines the economic mechanisms through which AI resources influence firms’ green risk management (GRM) practices. The empirical results show that AI attention has a negative impact on GRM, whereas AI depth and AI-driven innovation exert positive effects. Further analysis indicates that AI technology attention and software depth are the main factors driving the negative impact. A resource crowding-out effect exists between AI attention and green attention, but this effect is weakened when financing constraints are low. Although no crowding-out effect is observed between AI depth and green depth, environmental uncertainty promotes the emergence of such an effect. At the same time, green innovation is identified as an indispensable mediating variable in the process through which AI attention and AI depth influence GRM. Further analysis confirms that environmental subsidies and tax incentives, as key economic policy instruments, can complement AI resources and effectively promote green risk management.
subject: Articles
  topic: section
subject: Green Risk Management
  topic: keywords
subject: Artificial Intelligence
  topic: keywords
subject: Resource-based View
  topic: keywords
subject: Strategic Allocation
  topic: keywords
subject: Policy Synergy
  topic: keywords
creator: Yi Huang
creator: Zhe Zhang
creator: Sui Sun
rights: Copyright (c) 2026 Yi Huang, Zhe Zhang, Sui Sun (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-02-24
publication date: 2026-02-24
starting page: 303
ending page: 323
doi: 10.31181/ijes1512026277

The Synergy and Dynamic Interaction between Financial Opening-Up and RMB Internationalization
type: item
description: The internationalization of the RMB and China's financial opening represent a continuous process of co-evolution. This process is propelled by a mutually reinforcing cycle where institutional supply, market demand, and network effects interact dynamically. The bidirectional synergistic evolution of the two has unleashed significant institutional dividends, yet its deepening process still faces multiple structural constraints. The synergistic advancement of financial opening-up and RMB internationalization necessitates a holistic framework—one that strategically balances risk containment with growth momentum to ensure these processes are mutually reinforcing. This study examines the synergistic pathways and interactive dynamics between financial opening and RMB internationalization. The objective of this paper is to elucidate the intricate relationship between these processes and their strategic implications, thereby formulating a theoretical and policy-oriented framework to support high-level financial opening and enhance the international standing of the RMB.
subject: Articles
  topic: section
subject: Financial Opening-Up
  topic: keywords
subject: RMB Internationalization
  topic: keywords
subject: Interactive Dynamics
  topic: keywords
subject: Synergistic Evolution
  topic: keywords
creator: Kun Zhang
creator: Wei Li
creator: Zhichao Zhang
creator: Xiaoxiao Guan
rights: Copyright (c) 2026 Kun Zhang, Wei Li, Zhichao Zhang, Xiaoxiao Guan (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-03-03
publication date: 2026-03-03
starting page: 324
ending page: 346
doi: 10.31181/ijes1512026253

Spatial Autocorrelation in Housing Prices: Analysis of the Brno Metropolitan Area
type: item
description: This study examines the persistence of spatial autocorrelation in housing prices within the Brno metropolitan area, focusing on the dynamics between the core city and its peripheral municipalities. The aim of the study is to test whether spatial autocorrelation exists and the extent to which it can be explained by traditional variables. Using a log-linear specification, the analysis employs a hedonic price model estimated separately for the city’s central and peripheral areas. The dataset comprises 19,286 residential transactions from the period 2020–2023. Explanatory variables include structural characteristics, land use, crime rates, and accessibility to services. Spatial autocorrelation is measured using Moran’s I and Local Indicators of Spatial Association, both on raw data and model residuals. The results reveal that price clustering is substantially stronger in peripheral areas, where lower market liquidity and limited substitutability of dwellings amplify the transmission of price signals across municipal boundaries. The findings suggest that localized factors such as planning agreements and limited market liquidity affect price transmission across municipal borders. The study’s findings highlight that spatial autocorrelation is not merely a statistical pattern but a mechanism shaping housing affordability, market efficiency, and the distribution of price shocks. In peripheral areas, prices are strongly affected by proximity to the city center and access to public infrastructure, indicating the need for coordinated metropolitan policies, particularly in rapidly growing suburban areas where spillover effects are most pronounced. The study contributes to housing economics by quantifying the structural sources of spatial dependence and demonstrating their relevance for metropolitan policy design.
subject: Articles
  topic: section
subject: Local housing market
  topic: keywords
subject: Spatial Autocorrelation
  topic: keywords
subject: House price analysis
  topic: keywords
creator: Filip Emmer
creator: Jindřich Lacko
creator: Martin Slaný
rights: Copyright (c) 2026 Filip Emmer, Jindřich Lacko, Martin Slaný (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-03-25
publication date: 2026-03-25
starting page: 367
ending page: 385
doi: 10.31181/ijes1512026240

Economic Evaluation of Digital Suppliers for Manufacturing SMEs Using Pythagorean Neutrosophic TOPSIS and VIKOR with a Flexible Distance Metric
type: item
description: 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.
subject: Articles
  topic: section
subject: Pythagorean neutrosophic set
  topic: keywords
subject: MCDM
  topic: keywords
subject: TOPSIS
  topic: keywords
subject: VIKOR
  topic: keywords
subject: Economic evaluation
  topic: keywords
subject: Manufacturing SMEs
  topic: keywords
subject: Alternative ranking
  topic: keywords
subject: Neutrosophic distance measure
  topic: keywords
creator: Mohammad Syafiq Mohammad Kamari
creator: Zahari Md Rodzi
creator: Zaifilla Farrina Zainuddin
creator: Nor Hanimah Kamis
creator: Noraini Ahmad
creator: Samsiah Abdul Razak
creator: Faisal Al-Sharqi
rights: 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
date: 2025-09-24
publication date: 2025-09-24
starting page: 351
ending page: 384
doi: 10.31181/ijes1412025187

Strategic Challenges and Opportunities for the Czech Steel Industry: A Path toward Sustainable Competitiveness
type: item
description: 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.
subject: Articles
  topic: section
subject: Czech steel industry
  topic: keywords
subject: Decarbonization
  topic: keywords
subject: Modernization
  topic: keywords
subject: Global trade
  topic: keywords
subject: European Green Deal
  topic: keywords
subject: Energy efficiency
  topic: keywords
subject: Product innovation
  topic: keywords
subject: Competitiveness
  topic: keywords
creator: Eduard Hromada
creator: Klara Cermakova
creator: Bozena Kaderabkova
creator: Lucie Kurekova
creator: Martina Krasnicka
rights: Copyright (c) 2025 Eduard Hromada, Klara Cermakova, Bozena Kaderabkova, Lucie Kurekova, Martina Krasnicka (Author) https://creativecommons.org/licenses/by/4.0
date: 2025-09-12
publication date: 2025-09-12
starting page: 333
ending page: 350
doi: 10.31181/ijes1412025207

Smart Tourism Cities and Income Equity: How Digital Economy Reshapes Urban-Rural Disparities
type: item
description: 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.
subject: Articles
  topic: section
subject: Digital Economy
  topic: keywords
subject: Tourism Development
  topic: keywords
subject: Urban-Rural Income Gap
  topic: keywords
subject: Tourism cities
  topic: keywords
creator: Jia Wang
creator: Hangdi Zhao
rights: Copyright (c) 2025 Jia Wang, Hangdi Zhao (Author) https://creativecommons.org/licenses/by/4.0
date: 2025-08-28
publication date: 2025-08-28
starting page: 311
ending page: 332
doi: 10.31181/ijes1412025197

The Mixed Incentive Effect of Government Subsidies and Venture Capital on the Sustainability of Enterprise Innovation
type: item
description: 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.
subject: Articles
  topic: section
subject: Government Subsidies
  topic: keywords
subject: Venture Capital
  topic: keywords
subject: Sustainability of Innovation
  topic: keywords
subject: Control Function Method
  topic: keywords
subject: Survival Analysis
  topic: keywords
creator: Xi Chen
rights: Copyright (c) 2025 Xi Chen (Author) https://creativecommons.org/licenses/by/4.0
date: 2025-08-28
publication date: 2025-08-28
starting page: 292
ending page: 310
doi: 10.31181/ijes1412025206

Digital Entrepreneurship Within International Business Landscape: Implications for Marketing Strategies
type: item
description: 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.
subject: Articles
  topic: section
subject: Digital entrepreneurship
  topic: keywords
subject: Digital transformation
  topic: keywords
subject: Marketing strategies
  topic: keywords
subject: Global markets
  topic: keywords
subject: Business efficiency
  topic: keywords
subject: Financial performance
  topic: keywords
subject: Innovation
  topic: keywords
creator: Olena Ptashchenko
creator: Oleksandr Rozumnyi
creator: Elman Aliiev
creator: Volodymyr Vovk
creator: Olena Shersheniuk
rights: Copyright (c) 2025 Olena Ptashchenko, Oleksandr Rozumnyi, Elman Aliiev, Volodymyr Vovk, Olena Shersheniuk (Author) https://creativecommons.org/licenses/by/4.0
date: 2025-08-27
publication date: 2025-08-27
starting page: 274
ending page: 291
doi: 10.31181/ijes1412025200

Beyond ESG: Unpacking Brand Loyalty Through the Emotional Mechanisms Lenses of Attachment and Love—A Hierarchical Regression Study of Alibaba in China
type: item
description: 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.
subject: Articles
  topic: section
subject: ESG
  topic: keywords
subject: Brand attachment
  topic: keywords
subject: Brand follow
  topic: keywords
subject: Brand love
  topic: keywords
subject: Personal sustainability
  topic: keywords
creator: Xiaobo Xue
creator: Peilin Tian
rights: Copyright (c) 2025 Xiaobo Xue, Peilin Tian (Author) https://creativecommons.org/licenses/by/4.0
date: 2025-08-12
publication date: 2025-08-12
starting page: 259
ending page: 273
doi: 10.31181/ijes1412025195