Systematic Content Analysis Research Articles

Anatomy's missing faces: An assessment of representation gaps in atlas and textbook imagery.

Previous research suggests that underrepresentation in medical curricula perpetuates inequities in healthcare. This study aimed to quantify the prevalence of human phenotypic diversity (e.g., skin tone, sex, body size, and age) across 11 commonly used anatomy atlases and textbooks in pre-clerkship medical education, published from 2015 to 2020. A systematic visual content analysis was conducted on 5001 images in which at least one phenotypic attribute was quantifiable. Anatomy images most prevalently portrayed light skin tones, males, persons with intermediate body sizes, and young to middle-aged adults. Of the 3883 images in which there was a codable skin tone, 81.2% (n = 3154) depicted light, 14.3% (n = 554) depicted intermediate, and 4.5% (n = 175) depicted dark skin tones. Of the 2384 images that could be categorized into a sex binary, 38.4% (n = 915) depicted females and 61.6% (n = 1469) depicted males. A male bias persisted across all whole-body and regional-body images, including those showing sex organs or those showing characteristics commonly associated with a specific sex (e.g. for males, facial hair and/or muscle hypertrophy). Within sex-specific contexts, darker skin was underrepresented, but male depictions displayed greater overall skin tone variation. Although most images could not be assigned to a body size or age category, when codable, these images overwhelmingly depicted adults (85.0%; 482 of 567) with smaller (34.7%; 93 of 268) or intermediate (64.6%; 173 of 268) body sizes. Ultimately, these outcomes provide reference metrics for monitoring ongoing and future efforts to address representation inequalities portrayed in anatomical imagery.

Digital transformation as a catalyst for business model innovation: A critical review of impact and implementation strategies

This study critically examines the transformative impact of digitalization on business models and identifies effective implementation strategies for navigating digital transformation. The primary objective was to explore how digital technologies act as catalysts for innovation within business models, assessing both the opportunities and challenges they present. Through a systematic literature review and content analysis, this research analyzed peer-reviewed articles and conference papers published between 2014 and 2024, focusing on the integration of emerging technologies such as AI, IoT, and blockchain into business practices. The methodology involved a comprehensive search across multiple databases, adhering to strict inclusion and exclusion criteria to ensure the relevance and quality of the literature. The analysis revealed that digitalization significantly enhances business agility, customer engagement, and operational efficiency, driving the evolution of traditional business models towards more adaptive, data-driven frameworks. Key insights highlight the necessity for organizations to embrace a culture of innovation and continuous learning to leverage digital transformation effectively. Strategic recommendations for practitioners emphasize the importance of developing digital literacy, fostering collaborative ecosystems, and aligning digital initiatives with broader business objectives. The study also discusses policy implications, urging the creation of supportive regulatory environments that facilitate digital innovation while addressing concerns related to data privacy and workforce displacement. Finally, this research underscores the critical role of digitalization in shaping the future of business models and outlines avenues for future research to bridge existing knowledge gaps and explore emerging digital trends. The findings serve as a valuable guide for business leaders, policymakers, and scholars in navigating the complexities of digital transformation.

Leveraging artificial intelligence for enhanced supply chain optimization

This study provides a comprehensive review of the integration of Artificial Intelligence (AI) into Supply Chain Management (SCM), focusing on its impact on operational efficiency, strategic innovation, and sustainability. Employing a systematic literature review and content analysis methodology, the research synthesizes findings from peer-reviewed articles and conference papers published between 2013 and 2023. The study identifies key advancements in AI technologies, such as machine learning, natural language processing, and robotics, and their applications across various supply chain processes including demand forecasting, inventory management, and logistics optimization. Key findings reveal that AI significantly enhances supply chain efficiency by improving decision-making, reducing costs, and optimizing resource allocation. However, challenges such as data privacy concerns, ethical considerations, and the need for skilled personnel emerge as critical factors influencing AI adoption in SCM. The future outlook for AI-enhanced supply chains is promising, with potential for further innovation and resilience, albeit contingent upon addressing existing challenges. The study concludes with strategic recommendations for practitioners and policymakers, emphasizing the importance of fostering a culture of innovation, developing digital competencies, and creating supportive regulatory frameworks for AI integration. Directions for future research include exploring the long-term impacts of AI on supply chain sustainability, ethical implications of autonomous systems, and the interplay between AI and emerging technologies. This research contributes to the academic discourse on AI in SCM, offering insights for enhancing supply chain operations in the digital age.

Empowering marginalized communities through legal and financial literacy: The development and impact of the LEFL-Framework.

This study evaluates the impact of the Legal and Financial Literacy Framework (LEFL-Framework) on empowering marginalized communities, focusing on integrating legal and financial literacy as a means of socio-economic empowerment. Employing a systematic literature review and content analysis, the research scrutinizes peer-reviewed journals, official reports, and policy documents published from 2005 onwards. The methodology hinges on a comprehensive search strategy, with inclusion and exclusion criteria meticulously designed to filter relevant literature, followed by a thematic categorization and content analysis to distill key insights. Key discoveries reveal that legal and financial literacy are pivotal in enhancing the socio-economic conditions of marginalized communities, offering them the necessary tools to navigate complex legal and financial environments. The study identifies challenges such as digital divides and cultural barriers but also highlights opportunities through digital learning platforms and cross-sector partnerships. Strategic directions suggest leveraging technology, fostering community-based education, and advocating for policy support to integrate legal and financial literacy into broader educational frameworks. Recommendations are provided for practitioners, policymakers, and community leaders to develop culturally sensitive materials, support policy reforms, and mobilize local resources for sustainable literacy initiatives. The study concludes with a call for ongoing research into innovative educational methodologies, the long-term impacts of literacy programs, and the role of digital technologies in enhancing accessibility and effectiveness. This research underscores the transformative potential of legal and financial literacy in empowering marginalized communities and contributing to their socio-economic advancement.

Risk management and HR practices in supply chains: Preparing for the future

This study explores the strategic integration of risk management and Human Resources (HR) practices within the context of supply chain management, aiming to identify how such integration enhances organizational resilience and sustainability. Employing a systematic literature review and content analysis, the study examines scholarly articles from key databases, focusing on the period from January 2000 to the present. The methodology involves a comprehensive search strategy, stringent inclusion and exclusion criteria, and a detailed selection process to distill insights from relevant literature. Key findings reveal that strategic HR practices, such as talent management, leadership development, and fostering a risk-aware culture, significantly contribute to mitigating supply chain risks and bolstering resilience. Furthermore, the study highlights the pivotal role of technological advancements, including artificial intelligence, blockchain, and the Internet of Things, in supporting the dynamic integration of risk management and HR practices. This integration not only addresses operational efficiencies but also aligns with strategic objectives towards sustainability and adaptability in the face of global disruptions. The study concludes that the strategic importance of integrating risk management with HR practices cannot be overstated, emphasizing its necessity for building agile, resilient, and sustainable supply chains. As organizations navigate the complexities of modern supply chains, this integrated approach offers a pathway to not only survive but thrive amid uncertainties, underscoring a blueprint for sustainable competitive advantage in evolving global markets. This review contributes to the existing body of knowledge by providing a comprehensive overview of current practices and future directions for integrating risk management and HR practices in supply chain management.

Navigating the digital transformation journey: strategies for startup growth and innovation in the digital era

This study delves into the strategies for startup growth and innovation within the digital transformation journey, highlighting the imperative for startups to adapt and thrive in the digital era. Employing a systematic literature review and content analysis, the research scrutinizes peer-reviewed articles, industry reports, and case studies from 2013 to 2023 to unearth pivotal digital transformation strategies and their impact on startup success. The methodology ensures a comprehensive exploration of the digital landscape, focusing on the integration of digital technologies, the cultivation of a digital-first culture, and the navigation of regulatory landscapes. Key findings reveal that successful digital transformation for startups hinges on a multifaceted approach encompassing agile methodologies, digital literacy, customer-centric innovation, and proactive regulatory engagement. The study identifies emerging technologies, such as AI and blockchain, as critical enablers of innovation and operational efficiency, while emphasizing the significance of digital ecosystems and platform-based models for future growth. Finally, the research offers actionable recommendations for startups, including fostering innovation cultures, enhancing digital skills, engaging in ecosystem partnerships, and adopting customer-centric strategies. It also outlines future research directions, suggesting a focus on the impact of emerging technologies, digital transformation outside the tech sector, and longitudinal studies on startup success. This study contributes to the understanding of digital transformation strategies, providing a roadmap for startups aiming to navigate the complexities of the digital age and underscores the ongoing need for adaptive strategies in the face of rapid technological evolution.

LEVERAGING WORKFORCE ANALYTICS FOR SUPPLY CHAIN EFFICIENCY: A REVIEW OF HR DATA-DRIVEN PRACTICES

This study explores the pivotal role of HR analytics in enhancing supply chain management (SCM) efficiency, marking a significant shift from traditional HR practices to data-driven decision-making. The main objective was to bridge the gap between HR analytics and SCM performance, highlighting the transformative potential of integrating advanced data analysis in workforce management to optimize supply chain operations. Employing a systematic literature review and content analysis methodology, this research meticulously analyzed peer-reviewed articles, conference papers, and scholarly books from prominent databases. The search strategy was comprehensive, incorporating a broad spectrum of relevant keywords to ensure the inclusion of significant studies that address the integration of HR analytics into SCM. Key findings underscore the transformative power of HR analytics in SCM, revealing that data-driven HR practices significantly contribute to operational efficiency, strategic decision-making, and enhanced competitive advantage. Advanced analytical tools, such as AI, machine learning, and predictive analytics, have been identified as critical in optimizing workforce performance and aligning human capital with supply chain objectives. The study concludes with actionable recommendations for practitioners, leaders, and policymakers, emphasizing the importance of robust data governance, cross-functional collaboration, and the development of analytics competencies. It also outlines emerging challenges and opportunities in leveraging workforce analytics, suggesting directions for future research, particularly in exploring the strategic impacts of HR analytics on supply chain resilience and sustainability. This research contributes to the growing body of knowledge on the strategic integration of HR analytics in supply chain management, offering a roadmap for organizations seeking to enhance supply chain efficiency through data-driven HR practices. Keywords: HR Analytics, Supply Chain Management, Data-Driven Decision-Making, Workforce Optimization.

REMOTE WORK POLICIES FOR IT PROFESSIONALS: REVIEW OF CURRENT PRACTICES AND FUTURE TRENDS

This study investigates the dynamics of remote work in the Information Technology (IT) sector, focusing on best practices, challenges, and future implications. Through a systematic literature review and content analysis, the study explores the key objectives, methodology, findings, and conclusions regarding remote work policies and technologies in the IT industry. The main objectives of the study include synthesizing insights into best practices for remote work, examining the future landscape of IT remote work, providing strategic recommendations for enhancing remote work policies and technologies, and identifying directions for future research in remote work dynamics. Methodologically, the study employs a systematic approach, utilizing reputable academic databases and search strategies to identify relevant literature. Inclusion and exclusion criteria are established to ensure the rigor and relevance of the selected articles, which are then subjected to data analysis using content analysis techniques to identify recurring themes and insights. Key findings from the study highlight the importance of clear communication, technological support, trust, and work-life balance in remote work environments. Challenges such as cybersecurity risks, team cohesion, and equity concerns are also identified. However, the study also emphasizes the promises of remote work, including increased flexibility, productivity, and talent retention. Based on these findings, strategic recommendations are provided for enhancing remote work policies and technologies in the IT sector, including investing in cybersecurity measures, implementing comprehensive training programs, and leveraging emerging technologies. The study concludes by highlighting the need for continued research in understanding the long-term impacts of remote work and effectively managing remote teams to foster inclusive and sustainable work environments in the digital age. Keywords: Remote Work, Information Technology (IT) Sector, Diversity And Inclusion, Work-Life Balance.

Research trends in science education from 2018 to 2022: a systematic content analysis of publications in selected journals

ABSTRACT This study uncovers research trends by analysing 1,142 papers published in Science Education, Journal of Research in Science Teaching, and International Journal of Science Education: Part A between 2018 and 2022, followed by a series of systematic reviews dating back to 1998. The main findings indicate that, during the period of 2018–2022, the three most studied research topics were associated with learner characteristics and classroom contexts (Learning-Context), teacher thinking/cognition and pedagogical issues (Teaching), and preservice education/in-service professional development (Teacher Education). An emerging interest in investigating the influence of cultural, social, and gender factors on science education (Culture, Social, and Gender) was observed. The analysis of the top 10 most-cited papers unveiled a notable focus on pertinent theoretical discussions and empirical research within the context of STEM/STEAM education. Besides, issues regarding engagement in and out of school settings, learners’ epistemologies, or sensemaking and science as practice were also highly cited. It is worth noting that there has been a rapid surge and new trend in research concerning science identity, garnering substantial attention by researchers as a meaningful lens for exploring relevant issues associated with participation and pipeline/career paths in STEM-related fields.

AUGMENTED AND VIRTUAL REALITY IN U.S. EDUCATION: A REVIEW: ANALYZING THE IMPACT, EFFECTIVENESS, AND FUTURE PROSPECTS OF AR/VR TOOLS IN ENHANCING LEARNING EXPERIENCES

This study provides an in-depth analysis of the impact, effectiveness, and future prospects of Augmented Reality (AR) and Virtual Reality (VR) in educational settings. The primary objective was to explore how these immersive technologies are reshaping learning and teaching landscapes. Employing a systematic literature review and content analysis methodology, the research analyzed recent scholarly articles and reports from 2014 to 2024, focusing on AR/VR applications in education. The findings reveal that AR and VR significantly enhance learning experiences by offering immersive, interactive, and engaging environments. These technologies have been shown to improve student engagement, knowledge retention, and skill development. AR enriches traditional educational materials by overlaying digital information onto the real world, while VR facilitates experiential learning in virtual environments. However, challenges such as high costs, technical infrastructure requirements, and content development complexities were identified as barriers to widespread adoption. The study predicts a future where AR and VR technologies will continue to evolve, focusing on enhancing user experience, improving accessibility, and integrating seamlessly into educational curricula. Recommendations for stakeholders, including educators, administrators, and policymakers, emphasize the need for investment in infrastructure, educator training, content development, and collaboration with technology companies. Lastly, AR and VR technologies hold great promise for transforming educational practices. Addressing current challenges and leveraging opportunities will be key to realizing their full potential in enhancing teaching and learning experiences. Continued research and innovation in this field are essential for the effective integration of AR and VR in education.
 Keywords: Augmented Reality (AR), Virtual Reality (VR), Educational Technology, Immersive Learning.

Zooming in on Topics: An Investigation of the Prevalence and Motives for Selective News Avoidance

ABSTRACT Intentional news avoidance is a common behavior that can be influenced by individual, content, and contextual factors. However, prior studies have primarily focused on general news avoidance and neglected selective avoidance of specific topics. Therefore, our study aimed to determine which topics people tend to avoid and the reasons behind this behavior. We conducted an online survey (N = 1071) with open-ended questions to gather information on topic-specific news avoidance and motives. Our systematic quantitative content analysis revealed that the most commonly avoided news topics were related to the pandemic, political issues, and soft news. Participants cited negative emotional reactions and lack of interest as their primary reasons for avoiding news on an individual level, while redundancy and lack of trust were cited as reasons related to content. Logistic regression analyses revealed that specific motives were related to topic-specific avoidance. Issue fatigue was the primary motivator for avoiding news about COVID-19, while anger and lack of trust were the main reasons for avoiding political news. Lack of interest and overload were the motivators for avoiding soft news. Our study highlights the importance of understanding selective news avoidance and provides insights into the reasons why people choose to avoid certain news topics.

COMBATING BURNOUT IN THE IT INDUSTRY: A REVIEW OF EMPLOYEE WELL-BEING INITIATIVES

This study conducts a systematic literature review and content analysis to explore the effectiveness of employee well-being initiatives in combating burnout within the Information Technology (IT) industry. With the rapid pace of technological advancements and the high-pressure environment characteristic of the IT sector, burnout has emerged as a significant concern, affecting not only individual employees' mental and physical health but also organizational productivity and success. The primary objectives of this review were to identify the state of employee well-being in the IT industry, evaluate the current and potential future strategies for burnout prevention, and offer strategic directions for fostering a healthier workplace. Data were sourced from a comprehensive search across multiple academic and professional databases, focusing on studies published in English from 2000 to 2024 The inclusion criteria targeted research explicitly related to well-being initiatives in the IT sector, resulting in a selection of empirical studies, review articles, and grey literature for analysis.Key findings indicate a prevalent issue of burnout among IT professionals, driven by unique industry challenges. However, initiatives such as flexible work arrangements, leadership development, mental health support, and the use of AI for personalized well-being interventions show promise in mitigating these effects. The study concludes that fostering a culture of well-being and resilience within the IT industry requires a multifaceted approach, emphasizing the need for organizational commitment to employee health and continuous adaptation of well-being strategies to meet evolving workforce needs.
 Keywords: Burnout Prevention, Information Technology (IT), Employee Well-being, Systematic Literature Review

REVIEW OF WORKFORCE UPSKILLING INITIATIVES FOR EMERGING TECHNOLOGIES IN IT

This study provides a comprehensive analysis of workforce upskilling initiatives for emerging technologies in the Information Technology (IT) sector, with the primary objective of identifying effective strategies to prepare professionals for the rapidly evolving digital landscape. Employing a systematic literature review and content analysis, the research scrutinizes various upskilling programs, focusing on their design, implementation, and outcomes. Data sources include peer-reviewed journals and conference proceedings, selected based on criteria that ensure relevance and timeliness to the current IT context. Key findings reveal the critical need for anticipating technological trends to align workforce capabilities with future demands, highlighting the significance of personalized and experiential learning pathways. The study emphasizes the strategic role of upskilling in bridging the digital divide, advocating for inclusive and accessible learning opportunities to cultivate a diverse and globally competitive workforce. Recommendations for stakeholders center around adopting flexible learning models, fostering industry-academia partnerships, and emphasizing the development of both technical and soft skills. Finally, the study underscores the imperative for a proactive and collaborative approach to IT education and workforce development. By integrating advanced learning technologies and inclusive strategies, stakeholders can ensure the IT workforce remains agile and prepared to contribute innovatively in the face of technological advancements. This framework sets the foundation for future research and policy-making, aiming to enhance the resilience and diversity of the IT sector globally.
 Keywords: Workforce Upskilling, Emerging Technologies, IT Education, Inclusive Learning Strategies.

"It's My Secret": Shame as a Barrier to Care in Individuals With Opioid Use Disorder.

Substance use disorder (SUD) is a chronic illness impacting more than 59 million Americans last year. Opioid use disorder (OUD) is a subset of SUD. The literature supports that healthcare providers frequently stigmatize patients with OUD. Individuals with OUD often feel shame associated with their disorder. Shame has been associated with maladaptive and avoidant behaviors. The aim of this qualitative descriptive study was to examine and describe the experiences of shame and health-seeking behaviors in individuals with OUD. A qualitative exploratory design using focus groups with individuals in treatment for OUD was used to identify the issue of shame and its relationship to health-seeking behaviors. A systematic content analysis of discussions with 11 participants in four focus groups revealed four major themes and associated subthemes: Avoidance of Preventive Care (belief providers are judgmental); the Hidden Disorder (keeping secrets); Constraints of Shame (justification for the continuation of drug usage); and Trust in MOUD (Medication for Opioid Use Disorder) Providers. The feeling of shame leads to a reluctance to engage in health-promoting actions, such as scheduling appointments with primary care providers and dentists. Healthcare practitioners must prioritize providing a safe, nonstigmatizing environment for patients with SUD/OUD. This includes establishing trust and rapport, providing education, collaboration with psychiatric mental health specialists and other healthcare providers, and the offering support and resources to help patients manage their condition to achieve optimal health outcomes.

Fashion brands in the metaverse: Achievements from a marketing perspective

ABSTRACT Since the early developments of Web3 and the Metaverse, the fashion industry has been actively launching initiatives, especially through gamification, Non-Fungible Tokens (NFTs) and shopping experience. Up until now the academic literature relating to the implications for fashion brands in a digital fashion marketing context has been scarce. Through a systematic content analysis of 235 articles published between 2021 and 2023 in Vogue Business and The Business of Fashion, this research has focused on the main brands and uses of the Metaverse, as well as their real applications. Through a thorough analysis, this research reveals that the most active fashion sub-industries on the Metaverse are those relating to luxury, sportswear and beauty, with Nike, Gucci and Hermès emerging as the leading brands. Furthermore, when it comes to fashion and the Metaverse, the most popular topics relate to NFTs and gamification, to the point that they are used as synonyms of the Metaverse. This practice creates confusion, not only in terms of the meaning of the term “metaverse”, but also regarding its implications for fashion brands. Finally, the study identifies issues that demand further analysis in subsequent academic research regarding the notion of falsity and the Metaverse.

A comprehensive review of talent management strategies for seafarers: Challenges and opportunities

This study embarked on a systematic literature review and content analysis to explore the intricacies of talent management within the maritime sector, focusing on the challenges and strategic imperatives faced by the industry in managing its workforce. The primary objectives were to identify current practices in talent management, assess the challenges in recruiting, retaining, and developing seafarers, and to propose strategic recommendations for maritime industry leaders and policymakers. Employing a comprehensive search strategy, the study scrutinized academic databases and industry reports to collate relevant literature on talent management practices within the maritime ecosystem. Inclusion criteria were meticulously defined to focus on contemporary research and publications that provided insights into the dynamics of talent management specific to the maritime context. Through content analysis, the research distilled key themes related to talent management strategies, their implications for various stakeholders, and the alignment with regulatory standards and best practices. Key findings revealed the critical importance of aligning talent management with organizational goals and global standards to ensure operational efficiency and compliance. The study also highlighted the essential role of specialized training and development tailored to the maritime sector's unique demands, alongside the significance of seafarers' well-being and career progression. Conclusively, the study underscores the necessity for maritime industry leaders to embrace digital transformation, foster continuous learning, prioritize seafarer welfare, and proactively adapt to regulatory changes. Future research directions were suggested, including the impact of digitalization on seafaring roles, cross-cultural competency development, and longitudinal studies to evaluate talent management outcomes over time.

Unlocking Secrets: Bioinformatics' Impact on Forensic Bio-Examinations

Bioinformatics (BI) is a diverse and interdisciplinary domain that studies biological data through computational techniques. Its rapid technological progress has led to a significant increase in biological data production, sparking a notable expansion in BI research and application. In recent years, the convergence between BI and forensic science has become increasingly evident, with the growing use of BI tools and techniques in forensic investigations. BI is not only extensively used in biomedical research to analyse biological data and forecast gene regulation but also in the development of drugs targeting disorders linked to epigenetic alterations. It merges principles from various fields like biology, computer science, and statistics to process extensive omics data, create databases, predict structures, and model metabolic processes. The impact of BI on biomedical research is substantial, aiding in data processing, prediction, and visualisation. Moreover, BI is increasingly important in analysing data generated through Sanger-based electrophoresis methods and massively parallel sequencing in forensic DNA analysis, demonstrating its practical application in the field. Therefore, BI plays a critical role in forensic identification, searching databases side by side, forensic DNA phenotyping and biographic ancestry, forensic genetic genealogy, and forensic epigenomics. An overview of different bioinformatic methodologies employed in forensic applications, exploring approaches for managing data and investigating trend analysis strategies within forensic contexts, is discussed. Additionally, it investigates data management strategies. The primary objective was to explore how BI facilitates forensic BI's use, integration, and impact. Utilising a systematic literature review and content analysis, the study examined peer-reviewed articles, conference proceedings, and reports from critical databases like Google Scholar and Scopus, focusing on publications from 2010 to 2024. Key findings highlight the significant advancements in genomic sequencing technologies and their application in personalised therapeutics. Forensic scientists can improve forensic exams' accuracy, reliability, and efficiency by using BI tools, metrics, and efficient data management procedures.

Investigating Syntactic and Morphological Differences in the Written Productions of Turkish Learners Based on the Learning Context

Purpose: The aim of this study is to investigate the potential impact of the learning context on learners’ written production. Comparing the syntactic and morphological errors, the study tries to find out whether there are differences between written language productions of learners learning Turkish in Turkey and the ones outside the target community. Design/Methodology/Approach: Following descriptive research method, the study adopted qualitative design through systematic content analysis to analyse the data gathered from 78 learners of Turkish at A2 proficiency level, in Turkey (N=42) and outside of Turkey (N=36). The statistical analyses were then carried out to identify the ratios and the categorical distributions of errors determined through error analysis. Findings: The results reveal that learning a language in the target context impacts writing performances significantly at syntactic and morphological level. Based on the findings, instructional implications are provided to enhance effective language input. Highlights: Writing, an important and functional skill in multiple domains, is one of the most challenging skills to master and requires receive sufficient and meaningful authentic language input. As Turkish possesses distinct characteristics compared to Germanic or Semitic Languages, learners of Turkish have additional challenges at language production level. Learners of Turkish display significant differences in the types of syntactic and morphological errors in their writing depending on their learning contexts. The learning context has impacts on the writing productions of learners. The results suggest that educators and program developers in the field of Turkish Language teaching need to consider the role of the context in learning a foreign language while incorporating the special linguistic characteristics of Turkish in designing their teaching programs, materials and lessons.

THE ROLE OF PREDICTIVE ANALYTICS IN OPTIMIZING SUPPLY CHAIN RESILIENCE: A REVIEW OF TECHNIQUES AND CASE STUDIES

This study investigates the transformative impact of predictive analytics on enhancing supply chain resilience (SCR). Employing a systematic literature review and content analysis, the research aims to explore the integration, challenges, and strategic implications of predictive analytics within the supply chain ecosystem. Focusing on literature from 2014 to 2023, the study synthesizes insights from peer-reviewed articles and conference papers, adhering to stringent inclusion and exclusion criteria to ensure relevance and recency. The findings reveal that predictive analytics significantly contributes to supply chain agility, flexibility, and responsiveness, thereby bolstering SCR against disruptions. Key challenges identified include data privacy concerns, the need for skilled personnel, and the integration of predictive analytics into existing supply chain frameworks. Despite these challenges, the future outlook for predictive analytics in SCM is promising, with potential for unprecedented efficiency, sustainability, and competitive advantage. Strategic recommendations for practitioners emphasize the importance of developing predictive analytics capabilities, prioritizing data governance, and continuous staff training. For policymakers, the study suggests the need for standards and regulations that encourage innovation while ensuring the ethical use of predictive analytics. Finally, predictive analytics is pivotal in revolutionizing SCM, offering pathways for innovation, efficiency, and enhanced resilience. Future research should focus on the integration of emerging technologies, ethical data use frameworks, and overcoming adoption barriers, particularly in SMEs and developing economies. This study underscores the critical role of predictive analytics in the future of SCM, driving forward the agenda for research and practice in this evolving field.
 Keywords: Predictive Analytics, Supply Chain Resilience, Systematic Literature Review, Strategic Implications.

HARNESSING BUSINESS ANALYTICS FOR GAINING COMPETITIVE ADVANTAGE IN EMERGING MARKETS: A SYSTEMATIC REVIEW OF APPROACHES AND OUTCOMES

This study systematically reviews the impact of business analytics on achieving competitive advantage in emerging markets, focusing on the integration of advanced analytical tools and strategies within organizational processes. Employing a systematic literature review and content analysis methodology, this research scrutinizes peer-reviewed articles, conference papers, and grey literature from 2018 to 2023, sourced from databases such as Web of Science, Scopus, and IEEE Xplore. The inclusion criteria targeted studies that explore the application, outcomes, and strategic implications of business analytics, while exclusion criteria filtered out non-peer-reviewed sources, non-English literature, and studies outside the scope of emerging markets or published before 2018. Key findings reveal that business analytics significantly enhances strategic decision-making, operational efficiency, and innovation, providing firms in emerging markets with a robust foundation for sustaining competitive advantage. The study identifies the critical role of data-driven insights in transforming organizational strategies and operations. However, challenges such as data privacy, security, and the digital skills gap pose potential barriers to the full realization of business analytics benefits. The study concludes with strategic recommendations for practitioners and policymakers to foster a culture of data literacy and develop supportive frameworks for data privacy and security. Future research directions are proposed to bridge existing gaps in literature, particularly focusing on the long-term impacts of business analytics, ethical considerations, and the integration of emerging technologies. This research contributes to the understanding of how business analytics can be leveraged to navigate the complexities of emerging markets, offering a roadmap for organizations seeking to harness data for competitive advantage.
 Keywords: Business Analytics, Competitive Advantage, Emerging Markets, Data-Driven Decision-Making.