Hayri Uygun

Despite the growing recognition of Artificial Intelligence (AI)’s potential for global education, the literature lacks strategic analyses on how to maximize personalized learning and ensure equitable access within the vast and diverse Indian educational system. The objective of this study is to analyze this strategic integration of AI into the Indian educational system, focusing on maximizing personalized learning and ensuring equitable access across diverse socioeconomic contexts, while evaluating current initiatives and the relevance of reporting guidelines, such as the use of Self-Sovereign Identity (SSI). The methodology employed bibliographic and documentary research, alongside the analysis of governmental and sectoral policies. The results indicate that the sustainable implementation of AI is critically dependent on the mitigation of algorithmic bias and the rigorous assurance of data privacy. In conclusion, to balance technological innovation with human-centered pedagogical approaches, maintaining the educator’s fundamental role and fostering collaboration among stakeholders for responsible governance are essential.

Objective: To analyze female consumers’ behaviour in the purchase and use of cosmetic products, focusing on the influence of social, economic, and psychological factors, as well as overall consumer satisfaction. Method: A quantitative research design was adopted, based on a structured questionnaire using a Likert scale, administered to 200 female consumers in Ludhiana, India. The instrument captured demographic data, social and economic influences, reasons for cosmetic use, and satisfaction levels. Data were analyzed using descriptive statistics, including percentages, tables, and graphical representations. Results: The findings reveal that cosmetic consumption is more prevalent among young and middle-aged, well-educated women. Price sensitivity, discounts, and perceived value for money strongly influence purchasing decisions, whereas prestige associated with premium brands plays a limited role. Psychological factors such as self-confidence, personal image enhancement, and self-expression are key drivers of cosmetic usage. Overall satisfaction levels are high, with most respondents reporting that cosmetic products meet their quality and performance expectations. Contributions: This study advances consumer behaviour research by demonstrating that cosmetic purchasing decisions are primarily driven by perceived value, personal satisfaction, and functional benefits rather than social status. The findings provide practical insights for marketers and policymakers targeting female consumers in rapidly developing urban markets.

Purpose: This paper examines how Artificial Intelligence (AI) is revolutionizing content marketing by automating creativity, enhancing personalization, and optimizing engagement in digital campaigns. It aims to assess how businesses leverage AI-driven tools such as Natural Language Generation (NLG), predictive analytics, and machine learning to strengthen marketing strategies while addressing ethical and creative challenges. Design/Methodology/Approach: The study employs a comprehensive literature review combined with real-world case analyses of companies including Coca-Cola, Netflix, The Washington Post, and Amazon. It synthesizes findings from academic research, industry reports, and practical applications to evaluate the effectiveness of AI-powered content generation, personalization algorithms, and predictive analytics. The analysis also considers the role of AI chatbots, SEO optimization, and automated data-driven decision-making in digital marketing. Findings: Results demonstrate that AI enhances efficiency and engagement by automating repetitive tasks, generating personalized and data-informed content, and predicting consumer behavior with high accuracy. Case studies reveal that AI adoption leads to improved targeting, faster content production, and optimized campaign performance. However, challenges persist regarding authenticity, algorithmic bias, and ethical data usage. Maintaining a balance between automation and human creativity is crucial to sustaining brand trust and emotional resonance. Practical Implications: Businesses must adopt responsible AI integration practices, ensuring transparency, ethical governance, and creative oversight. Marketers should combine AI automation with human insight to produce authentic, meaningful, and engaging content. Originality/Value: This study provides a holistic perspective on the intersection of AI and content marketing, highlighting how automation can enhance strategic creativity while emphasizing ethical and human-centered innovation.

Purpose: This paper investigates the transformative role of Artificial Intelligence (AI) and automation in the context of Industry 4.0, examining how these technologies enhance industrial productivity, operational efficiency, and innovation while addressing emerging ethical, social, and regulatory challenges. Design/Methodology/Approach: A qualitative research approach was employed, integrating an extensive literature review of academic sources, policy reports, and industrial case studies. The analysis focuses on the applications of AI and automation in manufacturing, logistics, and service sectors, identifying their impacts on predictive maintenance, workforce transformation, and decision-making processes. The study further discusses ethical considerations such as data privacy, job displacement, algorithmic bias, and accountability within autonomous systems. Findings: The findings demonstrate that AI and automation significantly improve efficiency, precision, and responsiveness in industrial operations through predictive analytics and machine learning. These technologies optimize production lines, reduce downtime, and enhance quality control. However, they also introduce ethical and operational challenges, including workforce disruption, cybersecurity vulnerabilities, and opaque decision-making mechanisms. The absence of robust governance frameworks and adequate workforce reskilling strategies poses substantial barriers to equitable technological adoption. Practical Implications: The paper emphasizes the need for comprehensive AI governance frameworks, transparent algorithmic systems, and ethical deployment standards. It also calls for workforce reskilling initiatives to mitigate the socioeconomic impacts of automation and ensure sustainable industrial transformation. Originality/Value: By synthesizing technological, ethical, and regulatory perspectives, this study provides an interdisciplinary understanding of AI and automation in Industry 4.0, offering practical pathways for responsible innovation and sustainable industrial progress.

Purpose: This paper investigates the integration of Artificial Intelligence (AI) and Blockchain technology in assessing and mitigating financial fraud risks within the banking sector. It aims to explore how these technologies enhance the efficiency, transparency, and security of banking operations while reducing cyber threats and operational vulnerabilities. Design/Methodology/Approach: A mixed-method research design was adopted, combining exploratory and analytical approaches. The study reviews extensive literature and incorporates a case analysis of JPMorgan Chase to illustrate real-world implementation. Data were sourced from peer-reviewed publications, financial reports, and institutional studies. Machine learning models such as Random Forest, Support Vector Machine (SVM), and regression algorithms were examined for their effectiveness in fraud detection. Blockchain’s decentralized and tamper-proof ledger system was analyzed for its role in improving compliance, data integrity, and fraud prevention. Findings: The integration of AI and Blockchain enhances fraud detection accuracy, reduces false positives, and minimizes transaction manipulation risks. AI-driven predictive models identify anomalies in real time, while Blockchain ensures transparency and immutable recordkeeping. The JPMorgan case demonstrates that these technologies collectively improve operational efficiency, cut investigation time, and strengthen compliance with KYC and AML regulations. However, challenges remain in areas such as data privacy, interoperability, and ethical governance. Practical Implications: The research provides actionable insights for banks and policymakers to develop AI-Blockchain frameworks that bolster fraud prevention and regulatory compliance while fostering customer trust and financial inclusion. Originality/Value: This study contributes to the growing body of interdisciplinary research connecting AI, Blockchain, and financial risk management, emphasizing their synergistic potential in transforming global banking security.

This book explores the critical intersection between emerging technologies and the principles of sustainable development. Covering topics such as artificial intelligence, blockchain, cloud computing, and big data, the work investigates how these innovations can drive meaningful change toward circular economies, resilient infrastructures, and more equitable societies. Beyond technological possibilities, the authors address ethical challenges, the need for robust public policies, and the essential role of human capital in advancing a fair and sustainable digital future. Aimed at researchers, practitioners, and policymakers, this comprehensive and accessible analysis seeks to inspire discussion, collaboration, and transformative actions for a world where innovation and sustainability go hand in hand.

Amaç–Bu araştırmada, Scopus’daindekslenen dergilerde yayınlanmış olan elektronik ağızdan ağıza iletişim (eWOM) makalelerin bibliyometrik analizleri, Eren ve Eren(2020)’nin Web of Science (WoS)’da yapmış oldukları bibliyometrikanaliz sonuçlarıyla karşılaştırılmıştır. Veri tabanları arasındaki benzerlik ve farklılıkların belirlenmesi amaçlanmıştır. Yöntem–Çalışma, nicel araştırma desenlerinden betimsel tarama desenine göre yürütülmüştür. Bu amaç doğrultusunda bibliyometrik analiz yöntemi kullanılmıştır. Bibliyometrik analiz için veriler VOSviewer programı kullanılarak analiz edilmiştir. Ağ ve yoğunluk haritaları çıkartılan verilerin elde edilmesinde, 2006-2018 yılları arasında Scopus’da eWOM konusunda yayınlanmış 501 makale kullanılmıştır.Bulgular–Scopus’da eWOM ile ilgili 2006-2018 yılları arasında yayınlanmış 501 makaleye 12999 atıf yapılırken, 2019-2022 yılları arasında yayınlanmış olan 774 makaleye 333392 atıf yapılmıştır. Makale başına ortalama atıf sayısı 36,39 olmuştur. Makalelerin h indeksi de 102’dir. 1638 atıf ile Litvin, Goldsmith ve Pan’ın 2008 yılında yayınlamış oldukları eWOM makalesi, en çok atıf alan makale olmuştur. Araştırmacılar makalelerinin anahtar kelimelerinde en çok “ewom” anahtar kelimesini kullanmışlardır. Tartışma–Elektronik ağızdan ağıza iletişim, pazarlama alanı dışında da bir çok alanda kullanılmıştır. Özellikle COVID-19 pandemi ve sonrasında bu alanda daha fazla araştırma yapılmıştır. Bunda teknolojinin gelişmesi, özellikle internetin yaygınlaşması, akıllı telefonların etkisiyle sosyal medya kullanıcısının her geçen gün artmasının etkisi olmuştur. eWOM konusunda yapılan araştırmalar artarken, uluslararası literatürde Türkiye’den herhangi bir çalışmanın olmaması, bu alanda daha çok çalışma yapılmasını gerektirmektedir.

Background: The use of ChatGPT in the learning process is becoming a common practice. Researchers identify opportunities to improve the learning process using AI tools. At the same time, there are many unresolved problems and threats from the use of ChatGPT. These include unreliable information, false information, lack of references to primary sources, lack of intellectual property protection, and especially the problem of plagiarism in academic texts. Objectives: The purpose of the study is to summarise the results of published research on the benefits and threats of using ChatGPT in higher education and to analyse the experience of using AI to write academic assignments by university students in compliance with the requirements of academic integrity. Methods: A survey was conducted among Kyiv National Economic University named after Vadym Hetman (KNEU) students about their experience of using ChatGPT in performing academic tasks and the degree of satisfaction with this tool. Results: The survey involved 58 KNEU students. We have analysed how satisfied students are with using ChatGPT for different learning purposes. Students are most satisfied with using ChatGPT to quickly find information and translate texts. The majority of respondents said that ChatGPT does not always provide accurate and reliable information. Students also pointed to the problem of violating academic integrity when using ChatGPT to complete their assignments. Conclusions: The study shows the general advantages and disadvantages of using ChatGPT in higher education. Particular attention should be paid to the level of borrowing in academic texts prepared with the help of ChatGPT.

Civil Aviation Industry is one of the fastest-growing industries in India. Passengers are most concerned about their choice of airlines for their travel purposes. This research paper mainly focuses on identifying the influence of service quality on customer satisfaction with low-cost carriers in India. The study also explores the gap between low-cost air carriers in India regarding the overall quality of airline service efficiency, customer satisfaction, and other selected attributes. The research is based on a literature review and an initial interpretation of a survey primarily designed to classify the views of passengers who have flown in Indigo, AirAsia, Go Air and SpiceJet. This study would allow Airlines to understand what passengers expect from airlines regarding service quality and provide input to service providers.