The Resilience–Efficiency Frontier in International  Trade: Structural Changes and Cost Impacts after COVID-19

Summera Khalid

doi:https://doi.org/10.54216/JIER.020205

Journal of International Economics Research | 2025

ESG Factors in Accounting and Auditing of Business Combinations (M&A): Methodological Approaches and Financial Implications

The article examines the role of Environmental, Social, and Governance (ESG) factors in accounting and auditing practices related to mergers and acquisitions (M&A). The study substantiates the necessity of integrating non-financial sustainability indicators into business valuation, consolidation procedures, and post-merger audit processes. Based on the synthesis of empirical studies and international standards, an authorial framework for incorporating ESG risks into accounting and audit methodologies is proposed.

groups

Aripova Anna Mixaylovna mail

link https://doi.org/10.54216/JIER.020202

Volume & Issue

Vol. Volume 2 / Iss. Issue 2

Details open_in_new

American Journal of Business and Operations Research | 2025

Structure of Global Innovation Systems and Knowledge Diffusion Patterns: Network Analysis

Digital transformation has fundamentally reshaped innovation dynamics in many parts of the global economy, and knowledge diffusion is no longer spatially bounded, as in large-scale innovation data collection, the density of collaborative ties and cross-border knowledge exchanges are increasing across institutional and technological domains. Due to structural changes in the daily organization of innovation activities, knowledge production has been reshaped by the expansion of digital infrastructures and the proliferation of networked research collaborations and innovation platforms. In this study, we aim to contribute to the understanding of global innovation systems by examining how patterns of knowledge diffusion are structured using network analysis in transnational innovation networks. This paper aims to identify structural configurations and relational mechanisms in innovation networks and how these contribute to theoretical understandings of knowledge diffusion. In this paper, we analyze the process of knowledge creation and diffusion as a networked system, using specific examples from our dataset of global innovation actors in order to examine their relational structures and positional roles of knowledge-producing entities. A sample of innovation network data from multiple sectors of global innovation systems took part in the empirical analysis, drawing from bibliometric indicators and the analysis of over large-scale relational linkages. We empirically found that we cannot assume uniformly that centrality or connectivity are either a prerequisite for innovation performance; a driver for diffusion of technological knowledge; a mechanism for individual learning; a mechanism for collective learning; and a determinant for accumulation of innovation capabilities. The findings indicate that actors adopt different strategies of using network positions in their learning: exploratory engagement or exploitative specialization. We argue for a more nuanced interpretation of innovation networks that acknowledges both its structural heterogeneity in shaping understandings of knowledge flows and providing policymakers with insights on organizations’ patterns of using digital infrastructures in other sectors and more complex configurations in the global system. The implications of this study could inform a policy framework in innovation governance on how actors can use their network resources for knowledge accumulation and coordination toward systemic innovation and that networks can function differently in alternative institutional contexts.

groups

Rakhimova Gulnoza mail -

Dilfuza Kuzikulova mail

link https://doi.org/10.54216/AJBOR.130201

Volume & Issue

Vol. Volume 13 / Iss. Issue 2

Details open_in_new

American Journal of Business and Operations Research | 2025

Network Structures and Systemic Dynamics of Globalization Processes: Gephi Based Analysis

In this study, we look at globalization processes over a longitudinal time horizon in the global system to reduce the fragmentation of analytical perspectives while integrating structural and relational dimensions. The analysis examines the dynamics of a complex network in global contexts, including economic, technological, institutional, and informational linkages, to identify systemic patterns that have implications for governance in the area of global integration. Based on a theoretical framework, we position this research to improve the understanding of globalization dynamics into empirically observable structures for the scholarly community. In this paper, we provide empirical insights into the structure of global networks by showing how connectivity and centrality have jointly shaped interaction patterns and asymmetries in the globalization process, affecting the stability of the system. Within each of these dimensions, we integrated observations into a multi-level repeated-measures analysis of network indicators (nodes × ties). Differences were assessed by use of a combination of correlation techniques and regression models, and network metrics within the global system that are relevant to these dynamics. Gephi-based visualization resulted in the exclusion of isolated components not being used for explanatory modeling and statistical testing. A significant main effect was found for network type and it influenced only the strength of associations and structural dependencies. The interaction of global actors of different system positions with other forms of global connectivity through network structures suggests that actors who are new to operating in a highly connected system may be at an increased risk of marginalization. Because increases in these structural imbalances have been associated with an increased likelihood of system-level instability, network-oriented analysis is an effective and integrative approach with potential to improve analytical rigor, policy relevance, and to inform globalization-related decision-making.

groups

Khasanova Zarina mail

link https://doi.org/10.54216/AJBOR.130202

Volume & Issue

Vol. Volume 13 / Iss. Issue 2

Details open_in_new

Journal of International Economics Research | 2025

Digital Marketing Tools in the Textile Industry: A Framework for Channel Selection and Performance Measurement

This article develops a reproducible framework for selecting digital marketing tools in the textile industry and for measuring performance for national brands with weak digital salience. The study covers 2021–2024 and uses a conceptual-methodological design: (i) a structured synthesis of peer‑reviewed research on digital marketing, customer journey and marketing metrics, and (ii) operationalization into seven implementation tables. A two‑tier measurement protocol is proposed: Tier A relies on open signals (official statistical releases, publicly observable Instagram/Meta signals, and a Google Trends branded‑search index as a proxy for awareness), while Tier B (when firm access exists) uses Google Analytics 4 (GA4) and CRM/sales data to compute conversion, customer acquisition cost (CAC), return on marketing investment (ROMI), and customer lifetime value (LTV). Results include a tool taxonomy (social media marketing, content, influencer marketing, SEO, PPC, analytics, CRM automation, AI personalization, AR/VR), a unified KPI dictionary, a digital maturity model, a risk/limitations map, a data‑accessibility matrix, and a 90‑day roadmap. The framework enables firms to move from reach‑only reporting to conversion and retention management under explicit data constraints.

groups

Tatyana Nam Gennadyevna mail

link https://doi.org/10.54216/JIER.020203

Volume & Issue

Vol. Volume 2 / Iss. Issue 2

Details open_in_new

International Journal of Neutrosophic Science | 2025

On Complex Fuzzy Soft Graph With Operations

The goal of this paper is to study complex fuzzy soft graph (CFSG). We introduce the concept of complex fuzzy soft graph from apply complex fuzzy set on fuzzy soft graph. The notations and definitions of some operations on two complex fuzzy soft graphs presented such as union, cartesian product, tensor product, normal product and composition of two complex fuzzy soft graphs. Also, a decision-making (DM) problem on supply chain management is discussed.

groups

Sana Abu-Ghurra mail -

Ghada Alafif mail -

Eman A. AbuHijleh mail -

Firas Safi mail

link https://doi.org/10.54216/IJNS.260331

Volume & Issue

Vol. Volume 26 / Iss. Issue 3

Details open_in_new

Fusion: Practice and Applications | 2025

Administrative Empowerment at Egyptian Universities: Field Study at Al-Arish University

This study aims to evaluate the reality of administrative empowerment in Egyptian universities, with a case study conducted at Al-Arish University, considering national efforts to improve institutional performance and the quality of higher education. Using a descriptive-analytical design, data was gathered through a structured questionnaire distributed to a purposeful sample of 40 administrative staff and mid-level managers. Data gathered from the structured questionnaire were analyzed to determine the levels of administrative empowerment at each of its key dimensions by using descriptive statistical methods comprising frequency distributions and weighted means. The study investigates the effectiveness of empowerment practices and their influence on institutional outcomes. Findings reveal a broad disparity between theory and practice with the levels of empowerment ranging from low to moderate. The major hindrances to participation are poor employee participation in decision-making, a lack of managerial support, discriminatory workplace culture, and low leadership development. Restricted senior management-employee interactions were also reported to hinder participatory practices. The study recommends that empowerment policies with clarity, actionable implementation strategies, and organizational resolve are necessary for creating a positive and motivational work culture. Recommendations made include enhancing internal communication, innovation, and incentive mechanisms to improve administrative performance. Such steps are vital to ensuring a productive environment to facilitate sustainable development and institutional change. Empirical findings demonstrate the significance of strategic empowerment to aid governance reform and quality assurance in Egyptian higher education.

groups

Amr El Koshiry mail -

Entesar Eliwa mail -

Ahmed Abd Allah Tony mail -

Ahmed Mahmoud Lotfy El-Masry mail

link https://doi.org/10.54216/FPA.200215

Volume & Issue

Vol. Volume 20 / Iss. Issue 2

Details open_in_new

Journal of International Economics Research | 2025

Organizational Mechanism of Interaction of Higher Education Institutions of Belarus and Uzbekistan with Employers

Research shows that effective communication between higher education institutions and employers contributes to the development of competent personnel prepared to solve real-world problems in production and business. This issue is highly relevant given rapid changes in the economy and technological processes, requiring the constant adaptation of educational programs and advanced training for graduates. This article examines areas of cooperation between universities in Belarus and Uzbekistan and proposes a model for their interaction with enterprises in the real sector of the economy in the context of the emerging knowledge economy and the trend toward developing education as a key element of scientific, technical, and innovation policy.

groups

Karpovich Viktar mail -

Ponomareva Natallia mail

link https://doi.org/10.54216/JIER.020204

Volume & Issue

Vol. Volume 2 / Iss. Issue 2

Details open_in_new

Galoitica: Journal of Mathematical Structures and Applications | 2025

Development of Numerical Algorithms for Solving Nonlinear Partial Differential Equations

This study focuses on the development of efficient numerical algorithms for solving nonlinear partial differential equations (PDEs). The research integrates theoretical analysis and practical numerical experiments to address the challenges posed by nonlinear PDEs, which often lack closed-form solutions and exhibit sensitivity to initial and boundary conditions. Benchmark models such as Burgers’ Equation, the Korteweg–de Vries (KdV) Equation, and the Navier–Stokes Equations are highlighted due to their significance in physical and engineering applications. Traditional numerical methods—Finite Difference Method (FDM), Finite Element Method (FEM), and Finite Volume Method (FVM)—are reviewed with respect to accuracy, stability, and computational efficiency. Numerical stability concepts, including Von Neumann analysis and the CFL condition, are discussed alongside sources of error and strategies for error reduction. New algorithms were proposed by enhancing traditional schemes, incorporating adaptive mesh refinement, and integrating stability techniques. Numerical experiments on benchmark problems demonstrated improved accuracy, enhanced stability in handling nonlinear terms, and acceptable computational efficiency. The findings emphasize the importance of selecting suitable numerical methods, conducting stability analysis, and applying adaptive techniques. The study recommends higher-order schemes, conservative formulations for fluid dynamics, and double precision when necessary, ensuring reliable and reproducible computational results.

groups

Zahraa Ahmed Sahib mail -

Najmeh Malek Mohammadi mail

link https://doi.org/10.54216/GJMSA.120203

Volume & Issue

Vol. Volume 12 / Iss. Issue 2

Details open_in_new

Fusion: Practice and Applications | 2025

Early Detection of Diseases in Hydroponic Saffron Crops Using a Diffused Concurrent Convolution Neural Network for Smart Farming

The detection of diseases in hydroponically cultivated saffron should be carried out as early and accurately as possible to maintain the quality of the yield, minimize losses, and promote sustainable farming practices. Manual diagnosis strategies are not suitable for high-density hydroponic systems where early symptoms tend to be subtle, as these methods are slow and rely extensively on experts. This research aims to develop a novel framework based on deep learning technology, using a Diffused Concurrent Convolutional Neural Network (DCCNN) to perform image analysis and detect diseases in saffron crops. The modified DCCNN includes a hierarchical three-stage classification pipeline consisting of crop recognition, disease detection, and Classification of the specific diseases, adding an “unknown” category for non-target or ambiguous outputs at each stage to enhance flexibility. The digression from standard deep learning techniques is justified due to the DCCNN construction, which contains a learnable diffusion layer and concurrent multi-scale convolutional blocks, and thus encapsulates strong feature propagation with fine-grained detection of complex and low-data environments. Evaluation on a specially annotated dataset of hydroponic saffron showed strong performance with up to 99.4% classification accuracy, exceeding well-known CNN baselines including EfficientNet and ResNet50. Additionally, the model processes static crop images and associated environmental sensor data, collectively referred to as 'non-sequential crop data,' focusing on spatial features without temporal dependencies. These findings confirm that the system, which is based on DCCNN, provides a transferable solution for precision disease detection in controlled-environment agriculture systems and can be extended to other high-value crops.

groups

Vivek Raj mail -

Gregory Allen mail -

Ananth Prabhu G. mail -

Melwin D. Souza mail

link https://doi.org/10.54216/FPA.200216

Volume & Issue

Vol. Volume 20 / Iss. Issue 2

Details open_in_new

Journal of International Economics Research | 2025

The Resilience–Efficiency Frontier in International Trade: Structural Changes and Cost Impacts after COVID-19

The post-pandemic period has led to a major reorientation in international economics, shifting the focus of global trade from cost efficiency to structural resilience. This study examines four key factors—supply chain diversification, reshoring initiatives, logistics disruptions, and cost shocks—to explore the transition from the era of "Fragile Efficiency" to a system focused on overall viability. Drawing on global trade data from 2024–2026 and analytical frameworks provided by the IMF, the research introduces the concept of the Resilience–Efficiency Frontier (REF). The findings show that moving from Just-in-Time (JIT) to Just-in-Case (JIC) manufacturing helps reduce the volatility caused by the Bullwhip Effect but also creates a persistent form of "Complexity Inflation." Empirical results indicate that firms are now incurring a "Resilience Premium" of 12–15% to protect their production and distribution networks. The study also emphasizes that trade is no longer purely economic but is increasingly connected to national security and environmental regulations, such as the EU’s Carbon Border Adjustment Mechanism (CBAM). This marks a clear shift from the deflationary trends that characterized global trade in the past.

groups

Summera Khalid mail

link https://doi.org/10.54216/JIER.020205

Volume & Issue

Vol. Volume 2 / Iss. Issue 2

Details open_in_new