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
Economic Impacts of an Emissions Trading Scheme Pilot in Oligopolistic Agri-Food Supply Chains: A Network Equilibrium Analysis
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.
Copyright (c) 2026 Tingfeng Wu, Heyin Hou (Author) https://creativecommons.org/licenses/by/4.0
Fostering Supply Chain Flexibility Under Economic Uncertainty: Role of Digitalization, Collaboration, Visibility, and Risk Management
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.
Copyright (c) 2026 Thi Huong Tran, Thu Vuong Thi Chuc, Dieu Le Thi Huyen (Author) https://creativecommons.org/licenses/by/4.0
Decision-Making Style of Managers in the Public Sector: Is There a Possibility for Improvement?
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.
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
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
The Role of Financial Development in ESG Performance: A Bibliometric Analysis
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.
Copyright (c) 2026 Adel Bogari (Author) https://creativecommons.org/licenses/by/4.0
Strategic Orientation and Firm Performance of Construction Enterprises in Guangdong Province: The Moderating Effect of Digital Technology Adoption
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.
Copyright (c) 2025 Hongbo Zhou, Ye Zhang, Muneera Binti Esa (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) 2026 Yuming Yin, Zilong Li, Kai Li, Tao Wang, Shunwei Cui (Author) https://creativecommons.org/licenses/by/4.0
Artificial Intelligence and Enterprise Export Price Markup in China’s Economy: Based on Large Language Models
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.
Copyright (c) 2026 Zhaosong Li, Weiwen Qian (Author) https://creativecommons.org/licenses/by/4.0
Influence of Educational Factors on the Entrepreneurial Potential of Students as a Prerequisite for Economic Development
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.
Copyright (c) 2026 Mladen Subotic, Mia Maric, Branislav Dudic, Slavica Mitrovic Veljkovic, Djordje Celic, Aleksandra Peric (Author) https://creativecommons.org/licenses/by/4.0
Logistics Infrastructure and Regional Economic Growth: A Causal Evaluation of Coordination Policies in China's Urban Agglomerations
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.
Urban agglomeration coordination mechanisms
Copyright (c) 2026 Xiaobo Xue, Guangbo Piao (Author) https://creativecommons.org/licenses/by/4.0
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) 2026 Rosa María Ricoy-Casas , Jose María Lago Cabo, Jorge Eduardo Vila Biglieri, Darko Bozanic (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) 2026 Huixin Sun, Rongchun Zhu (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) 2026 Nataliia Tymoshyk, Dmytro Rasshyvalov, Iryna Tarasenko, Kseniia Velykykh (Author) https://creativecommons.org/licenses/by/4.0
Cross-National Benchmarking of Bankruptcy Prediction Models Across V4 Economies
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 implications for policymakers, creditors, and business managers, supporting the development of scalable early-warning systems, enhancing risk assessment practices, and informing strategic decision-making in dynamic economic environments. Overall, the study contributes both to the theoretical understanding of model performance in bankruptcy prediction and to applied knowledge for regional economic foresight and business intelligence.
Copyright (c) 2026 Dominika Gajdosikova, Katarina Valaskova, Pavol Durana (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) 2026 Amirhamzeh Razavinejad, Seyed Esmaeil Najafi, Mehran Khalaj, Hamed Kazemi Pour (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) 2026 Xiangshuo Zhang (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) 2026 Marta Yankiv, Roman Mykytyuk , Andrii Gukaliuk (Author) https://creativecommons.org/licenses/by/4.0
Economic Efficiency Assessment of Sustainability Investment in EU Member States: A Data Envelopment Analysis with Crisis Impact Evaluation (2015-2024)
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.
Copyright (c) 2026 Stefan Petrov (Author) https://creativecommons.org/licenses/by/4.0
The Economic Mechanisms of Artificial Intelligence Resources Affecting Green Risk Management: Empirical Evidence from Chinese Listed Firms
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.
Copyright (c) 2026 Yi Huang, Zhe Zhang, Sui Sun (Author) https://creativecommons.org/licenses/by/4.0
The Synergy and Dynamic Interaction between Financial Opening-Up and RMB Internationalization
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.
Copyright (c) 2026 Kun Zhang, Wei Li, Zhichao Zhang, Xiaoxiao Guan (Author) https://creativecommons.org/licenses/by/4.0
Spatial Autocorrelation in Housing Prices: Analysis of the Brno Metropolitan Area
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.
Copyright (c) 2026 Filip Emmer, Jindřich Lacko, Martin Slaný (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
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
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
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