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  MEASURING THE LEVEL OF ORGANISATIONAL AMBIDEXTERITY OF MUNICIPAL ADMINISTRATIONS

  The research on organisational ambidexterity, understood as an ability to effectively solve current problems while ensuring long-term strategic development, is relatively recent. Very limited number of studies focus on ambidexterity in public organisations, or if any, it is considered primarily as an outcome rather than a strategy for achieving ... The research on organisational ambidexterity, understood as an ability to effectively solve current problems while ensuring long-term strategic development, is relatively recent. Very limited number of studies focus on ambidexterity in public organisations, or if any, it is considered primarily as an outcome rather than a strategy for achieving long-term success. This study aims to assess the organisational ambidexterity of a group of municipalities in two ways: by answering questions posed to municipal representatives and by calculating financial indicators that provide evidence of local governments’ preferences for funding current needs and investments for the future. The results were tested for statistically significant difference using the t-test. It is concluded that it is evident from their responses that municipal officials understand the need to achieve organisational ambidexterity, but the data from the analysis of the financial indicators of the studied municipalities clearly indicate a preference for spending on current needs over spending on investment and development.

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  A DUAL-LAYER HYBRID SECURITY FRAMEWORK: ANALYZING DIGITAL MODELS TO ENHANCE CYBERSECURITY MANAGEMENT FOR START-UPS AND SMES

  The rapid evolution of generative AI is transforming cybersecurity practices by providing advanced capabilities for threat detection and response. For start-ups and SMEs, these technologies offer a cost-effective way to defend against sophisticated online threats without the need for massive capital investment. While AI facilitates the ... The rapid evolution of generative AI is transforming cybersecurity practices by providing advanced capabilities for threat detection and response. For start-ups and SMEs, these technologies offer a cost-effective way to defend against sophisticated online threats without the need for massive capital investment. While AI facilitates the identification of anomalies and malicious behavior, it also introduces new risks, such as deepfakes, zero-day exploits, and the potential for attackers to manipulate AI models themselves. The study examines the impact of large language models and artificial intelligence on the software and architecture of cybersecurity systems. The main types of attacks on artificial intelligence systems and the changes in the software development paradigm that result from them are being considered. To address the evolving threat landscape, this study proposes a Dual-Layer Hybrid Security Framework that integrates high-speed algorithmic detection with cognitive analysis. We present an algorithm for building a security system using LLM models. We also propose a software application tailored explicitly for the comprehensive analysis of network traffic while detecting cybersecurity incidents using Python and the Pandas library. Furthermore, it leverages artificial intelligence to provide a comprehensive approach to detecting and mitigating cybersecurity threats. This will enable start-ups and small businesses to manage their cybersecurity in-house.

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  DIGITAL DISTANCE AND TRADE DYNAMICS: THRESHOLD EFFECTS ON TURKIYE’S EXPORT PERFORMANCE

  This study investigates whether digital distance—defined as disparities in digital and technological capabilities between countries—constitutes a critical determinant of Turkey’s export performance in the evolving architecture of international trade. Moving beyond traditional gravity-based explanations centered on geographical distance, the ... This study investigates whether digital distance—defined as disparities in digital and technological capabilities between countries—constitutes a critical determinant of Turkey’s export performance in the evolving architecture of international trade. Moving beyond traditional gravity-based explanations centered on geographical distance, the article develops a multidimensional digital distance index derived from the Frontier Technological Readiness Index (FTRI) and the Economic Complexity Index (ECI). Using annual panel data for 108 trading partners over the period 2008–2022, the analysis integrates GDP and exchange-rate controls within a panel threshold regression framework, complemented by panel causality tests. The findings reveal a statistically significant single-threshold structure, demonstrating that digital distance exerts nonlinear and asymmetric effects on Turkey’s exports. While convergence in ICT infrastructure and financial access tends to enhance export performance, narrowing gaps in certain dimensions—particularly skills and R&D—does not uniformly yield positive trade outcomes. In fact, larger disparities in selected technological capabilities may generate temporary competitive advantages, consistent with technology-gap theory. Robustness checks incorporating economic complexity distance confirm these threshold dynamics. Moreover, causality results indicate predominantly bidirectional relationships between exports and digital dimensions, underscoring mutual reinforcement between trade and digital transformation. Overall, the results challenge the presumption that digital convergence universally promotes trade. Instead, they highlight the strategic importance of selective digital specialization and innovation-driven competitiveness. By conceptualizing and empirically validating digital distance as a structural trade determinant, the study contributes to the emerging literature on digitalization and international trade and offers policy insights for adaptive, data-driven export strategies in an era of technological disruption.