Impact Of Transformation Research Articles

Research Advanced in Speech Emotion Recognition based on Deep Learning

Speech Emotion Recognition (SER)s burgeoning significance within intelligent systems is underscored by its transformative impact across various fields, from human-computer interaction, and virtual assistants to mental health monitoring. Over the rapid development of this technology in the past two decades, studies have continuously confronted and overcome kinds of real-world challenges, such as data scarcity, environmental noise, and cross-language differences. This survey focuses on recent innovations in SER, particularly deep learning architectures, and synthetic data augmentation, and addresses recent developments in cross-domain and multimodal SER techniques, which have expanded the applicability of SER to more diverse datasets.

Methodological and Technological Advancements in E-Learning

The present survey examines the intersection of methodological advancements and technological innovations in e-learning, emphasizing their transformative impact on modern education. It systematically explores instructional design frameworks, adaptive learning systems, immersive technologies, and data-driven analytics, highlighting their role in fostering personalized, scalable, and inclusive learning environments. Through the integration of pedagogical theories with advanced tools like artificial intelligence (AI), augmented reality (AR), virtual reality (VR), and mixed reality (MR), this study demonstrates how e-learning systems enhance engagement, retention, and accessibility. The survey addresses critical challenges such as the digital divide, data privacy, and resistance to adoption, offering evidence-based strategies to mitigate these issues. It underscores the importance of bridging equity gaps while maintaining scalability and sustainability, particularly in underserved regions. By synthesizing state-of-the-art research and practical applications, this work provides actionable insights into the future of e-learning, advocating for a balanced approach to innovation that aligns technological capabilities with the diverse needs of global learners. The findings contribute to the broader discourse on sustainable, inclusive, and effective digital education ecosystems.

The Impact of Digital Transformation on ESGEvidence from the Listed Companies in China

In the digital economy era, the influence of digital transformation on enterprises' ESG performance has received extensive attention. This article selects Chinese A-share listed companies from 2010 to 2022 as samples, constructs a digital transformation index encompassing five dimensions: artificial intelligence, big data, cloud computing, blockchain, and digital technology application, and employs the ESG rating data from Huazheng to measure enterprises' ESG performance. The research discovers that digital transformation significantly and positively affects enterprises' ESG performance. Particularly when external supervision is relatively weak, its promoting effect is more pronounced. Digital transformation enhances enterprises' risk-taking capacity by optimizing resource allocation, strengthening green technology innovation, and improving the quality of information disclosure, thereby elevating enterprises' value creation ability. This article expands the literature research on the influencing factors of enterprises' ESG performance from the micro level of digital transformation, which holds significant importance for improving the digitalization strategies and governance systems of listed companies, further standardizing corporate governance, and enhancing enterprise value.

Variables and Dynamics of the Middle Eastern System

Background This study explores the transformative impact of three significant events on the Middle Eastern regional system: the September 11, 2001, terrorist attacks, the Arab Spring of 2011, and the October 7, 2023, Hamas attack on Israel. These events have altered the regional balance, leading to an evolving, complex, and multi-polar system. This research assesses the role of both state and non-state actors, examining their influence on the region’s stability and overall structure. Methods Employing an integrative approach that combines area studies and international relations (IR) theory, this study examines the regional power dynamics using twelve indicators to assess hard and soft power, including economic, military, and socio-political metrics. The analysis positions regional actors within a multi-tiered structure, evaluating the interplay between internal and external influences to explain the current distribution of power. Results The study finds that the Middle Eastern system has developed into a hierarchical yet anarchic structure, characterized by a competitive and multi-polar power distribution. Although external actors, such as the United States, continue to play pivotal roles, regional powers – including Saudi Arabia, Israel, Turkey, and Iran – exert significant influence, leading to an inherently unstable system. This dynamic interplay fosters competition and limits cooperative stability. Conclusion The findings suggest that the Middle Eastern regional system’s volatility is rooted in this unique distribution of power, where continuous struggles among actors contribute to persistent instability. Understanding these dynamics is essential for assessing future developments and potential stability within the region.

Digital Transformation as a Catalyst for High-Quality Development: Examining Total Factor Productivity and ESG Performance in China's Manufacturing Sector

This study investigates the impact of digital transformation on total factor productivity (TFP) and environmental, social, and governance (ESG) performance in Chinese manufacturing firms, exploring the balance between economic output and sustainability for high-quality development. Results reveal two key mechanisms: innovation and efficiency. Digital transformation boosts productivity through open innovation and data-driven resource allocation while enhancing ESG performance via green technologies and efficient supply chains. The external institutional environment, including business climate and marketization, significantly influences its effectiveness. Over time, digital transformation's impact on TFP diminishes, but its role in promoting ESG performance strengthens as firms advance in sustainability. This research offers insights for enterprises and policymakers on leveraging digitalization to achieve sustainable growth, emphasizing the need to clarify specific pathways within China’s manufacturing sector.

Digital Transformation and Human Resource Management: Their Impact on Business Profitability and Contribution to Sustainable Economic Growth (SDG 8)

Objective: This study explores the relationship between human resource management (HRM) and business profitability, emphasizing the impact of digital transformation on this dynamic. The aim is to understand how technological advancements modify traditional HRM practices and influence financial outcomes. Theoretical Framework: The research builds on theories of human capital, firm performance, and digitalization. Studies such as those by Turulja and Bajgoric (2018) and Androniceanu et al. (2020) highlight the pivotal role of HRM and digital innovation in organizational success, serving as the foundation for this investigation. Method: A systematic literature review was conducted, analyzing 29 studies that examine the interplay between HRM, digitalization, and profitability. Articles were categorized by their research approaches and the nature of the relationships studied, with data synthesized to identify recurring themes and patterns. Results and Discussion: Findings indicate that 84 % of articles reviewed reported a positive relationship between HRM and profitability, often mediated by variables such as job satisfaction and innovation. Regarding digital transformation, 90 % of studies highlighted its positive influence, contingent on factors such as industry type, organizational characteristics, and workforce skills. Challenges include skill gaps and regulatory barriers. Research Implications: The study underscores the necessity of aligning HRM strategies with digital transformation initiatives to enhance productivity and profitability. It also highlights the importance of industry-specific approaches and skill development. Originality/Value: By integrating HRM and digitalization perspectives, this research contributes a comprehensive understanding of their combined effects on firm performance, offering actionable insights for businesses navigating digital transformation.

Quantitative Analysis of the Impact of Digital Transformation on Museum Management: Examining Visitor Satisfaction and Engagement Through Augmented Reality (AR) and Virtual Exhibitions in the UK Art Museums

Introduction: Digital technologies such as AR and Virtual exhibitions are changing the art and cultural industry such as museums by impacting visitor engagement and satisfaction. In the UK, the museum sector represents a broad landscape due to the vast number of museums, in which these technologies are implemented to address the challenges of declining visitors and enhancing visitor satisfaction. Objective: This study purported to investigate the impact of AR and Virtual Exhibitions on visitor engagement and satisfaction in UK art museums. Methodology: A cross-sectional research design was employed, collecting data from 155 respondents through a structured questionnaire based on the Technology Acceptance Model (TAM). Results: The results revealed that AR and Virtual exhibitions have a positive impact on visitor engagement and satisfaction though moderated by factors such as technical usability, visitor demographics and museum types. Here, larger museums have more resources which demonstrates greater capacity to adopt digital transformation, while smaller museums may have to face resource constraints. Conclusion: In a nutshell, it can be said that AR and Virtual Exhibitions can enhance museum experiences and foster long-term visitor behaviours such as repeat visits and positive word of mouth. Hence, the hybrid model of museums us critical for museums to combine all the digital and physical experiences for diverse audiences.

Evolution of banking systems: A comprehensive historical analysis

This paper provides a comprehensive historical analysis of the evolution of banking systems, tracing their origins from ancient Greece and Rome through medieval Europe, the Renaissance, and the emergence of modern banking institutions. It explores the foundational practices of ancient Greek "trapezitai" and Roman "argentarii," which laid the groundwork for more advanced systems that flourished in the Italian city-states during the Middle Ages and Renaissance. The development of commercial and central banking systems in early modern Europe, including the establishment of the Bank of Amsterdam and the Bank of England, is examined in detail. The study further highlights the role of colonial powers in shaping banking structures across the globe and discusses significant innovations of the 19th and 20th centuries, such as fractional reserves and the rise of investment banking. Emphasis is placed on the transformational impact of globalization, deregulation, and technological advancements in the modern banking era. Additionally, the paper delves into contemporary challenges, including cybersecurity, data privacy, and the integration of artificial intelligence, offering insights into the future trajectory of banking institutions. By bridging historical developments with modern trends, this analysis underscores the enduring significance of banking as a dynamic and essential component of economic systems, providing valuable lessons for understanding its future evolution.

SCM Meets Big Data: Transforming Supply Chain Management

This paper examines the transformative impact of integrating Big Data technologies into Supply Chain Management (SCM). It highlights how advanced analytics, machine learning, and cloud computing are reshaping traditional supply chain processes by enabling real-time insights, predictive capabilities, and enhanced decision-making. The study focuses on three critical areas: Demand forecasting, inventory optimization, and logistics planning. In demand forecasting, Big Data leverages historical and real-time data to improve accuracy, helping organizations better align supply and demand. Inventory optimization benefits from predictive analytics that reduce overstocking and understocking risks, ensuring cost efficiency and improved service levels. Logistics planning is enhanced through real-time data processing, enabling dynamic route optimization and reduced delivery times. The paper includes detailed case studies from various industries to demonstrate how Big Data has driven measurable improvements in supply chain performance, including reduced costs, increased agility, and enhanced customer satisfaction. Challenges in implementing Big Data solutions, such as data integration and security concerns, are also discussed, along with strategies to overcome them. This research underscores the pivotal role of Big Data in modernizing SCM and creating a competitive edge for businesses.

Modelling future urban growth utilizing multilayer perceptron and Markov chain models in West Himalayan urban centre: Srinagar Municipal Corporation

The urban spatial planning challenges encountered in areas situated in hilly regions, such as the Srinagar in Jammu and Kashmir, are distinguished by the swift growth of population, disorganized expansion of built-up areas, and insufficient data on alterations in urban expansion and land utilization. The study was conducted to examine the trends in urban growth in order to implement sustainable urban management within the Srinagar Municipal Corporation. The complexities arising from the rapid aggregation of population and unregulated urbanization necessitate a proactive approach to urban spatial planning. The aim of this investigation is to contribute to the development of effective strategies by analysing the current patterns of urban growth and anticipating future changes. The findings of this investigation display a notable trend in which the predicted LULC shows the rapid expansion of built-up areas from 134.72 km2 to 170.89 km2 and corresponds with a continuous decrease in agricultural and Fallow lands to 16.64 km2 and 6.62 km2 respectively. This emphasizes the transformative impact on the land-use, highlighting the requirement for comprehensive surveillance and predictive tools to direct the dynamic interplay between human activities and the environment. Also, the study could improve the city's planning, resource allocation and decision-making processes by providing probabilistic insights into various urban issues especially land-use planning in hilly regions.

Understanding Agentic Frameworks in AI Development: A Technical Analysis

This technical article examines the evolution and implementation of agentic frameworks in artificial intelligence development, focusing on their transformative impact across multiple industries. The article explores the fundamental architectural components, implementation methodologies, and practical applications of these frameworks in manufacturing, financial services, and healthcare sectors. By investigating the core components, including perception systems and decision architectures, alongside the Belief-Desire-Intention model and advanced learning mechanisms, this article provides comprehensive insights into how agentic frameworks are revolutionizing autonomous decision-making capabilities. The article also addresses critical technical challenges in scalability and safety while offering potential solutions and future directions for development, highlighting the growing importance of these frameworks in shaping the future of AI technology.

The Impact of Digital Transformation on Internal Auditing and Financial Performance of Iraqi Banks

This study investigates the extent to which regulatory systems for electronic accounting information systems, with conventional controls, are implemented in banks. The research employs a questionnaire divided into two main sections : the first section focuses on the personal characteristics of the study sample, while the second section is divided into eight themes. These themes cover the bank's commitment to deregulation of electronic accounting systems, regulatory controls on access to information, security and protection of files, documentation and development of the electronic accounting system, input and output controls, operations, and the risks associated with electronic accounting information systems. Key recommendations include improving control procedures, protecting software and hardware, and adopting clear regulations for responsibilities and powers within banks. The study underscores the importance of continuous internal audits and the development of efficient electronic accounting information systems to mitigate risks and enhance the overall performance of Iraqi private banks.

The Impact of Artificial Intelligence on eCommerce in the UAE from the Customer Perspective

The transformative impact of Artificial Intelligence (AI) on the burgeoning e-commerce sector in the United Arab Emirates (UAE). Focusing on consumer perspectives, the study examines the synergistic relationship between AI integration and the evolving e-commerce practices within the UAE. It highlights how the incorporation of AI redefines business operations and consumer interactions on e-commerce platforms, showcasing the UAE's leading position in innovation and technological advancement. Utilizing rigorous primary research methods, including surveys and interviews, alongside comprehensive secondary research, the findings reveal significant trends such as the predominance of younger demographics, a preference for personalized experiences, and growing concerns regarding data security and privacy. The results indicate a strong consumer inclination towards AI-driven features; however, respondents also underscore the necessity for enhanced data protection regulations and increased customization. This study underscores the importance of a balanced approach to AI implementation, emphasizing the critical role of customer trust and innovation in supporting the UAE's rapid e-commerce growth.

A narrative inquiry of international students' experiences in Indonesia

This study explores the promotion of ethical behavior through intercultural education via a narrative inquiry research design. Seven international students from Madagascar, Libya, Turkmenistan, Thailand, and Malaysia participated, providing diverse perspectives on their experiences. The participants' narratives were analyzed through the lenses of transitivity and language appraisal, revealing nuanced insights into how intercultural education shapes ethical behavior. The findings highlight the transformative impact of intercultural learning environments on international students' intercultural development and decision-making processes. This research underpins the integration of intercultural education into curricula to foster ethical global citizens and offers practical implications for educators and policymakers seeking to cultivate inclusive, ethically aware educational settings.

Is Artificial Intelligence the Next Co-Pilot for Primary Care in Diagnosing and Recommending Treatments for Depression?

Depression poses significant challenges to global healthcare systems and impacts the quality of life of individuals and their family members. Recent advancements in artificial intelligence (AI) have had a transformative impact on the diagnosis and treatment of depression. These innovations have the potential to significantly enhance clinical decision-making processes and improve patient outcomes in healthcare settings. AI-powered tools can analyze extensive patient data—including medical records, genetic information, and behavioral patterns—to identify early warning signs of depression, thereby enhancing diagnostic accuracy. By recognizing subtle indicators that traditional assessments may overlook, these tools enable healthcare providers to make timely and precise diagnostic decisions that are crucial in preventing the onset or escalation of depressive episodes. In terms of treatment, AI algorithms can assist in personalizing therapeutic interventions by predicting the effectiveness of various approaches for individual patients based on their unique characteristics and medical history. This includes recommending tailored treatment plans that consider the patient’s specific symptoms. Such personalized strategies aim to optimize therapeutic outcomes and improve the overall efficiency of healthcare. This theoretical review uniquely synthesizes current evidence on AI applications in primary care depression management, offering a comprehensive analysis of both diagnostic and treatment personalization capabilities. Alongside these advancements, we also address the conflicting findings in the field and the presence of biases that necessitate important limitations.

Impact of digital transformation on financial performance of licensed commercial banks in Sri Lanka pre and post COVID-19 pandemic

Enhancing the quality of goods and services through innovation and the integration of electronic applications is a fundamental aspect of digital transformation. This topic has increasingly captivated the attention of management and organizational scholars. This focus is especially relevant in improving organizational performance by digitalizing core operations. The global and Sri Lankan economies have faced severe disruptions due to the COVID-19 pandemic, which has compelled commercial banks to adopt innovative digital strategies as a means of mitigating the resultant risks and maintaining stability. This study explores the impact of digital transformation on the financial performance of 10 Licensed Commercial Banks in Sri Lanka, comparing outcomes before and after the pandemic’s onset. By employing a robust methodological framework that includes descriptive statistics, correlation analysis, and T-test analysis, the research investigates key variables to discern trends and patterns across different timeframes. The assessment of digital transformation is conducted through a multi-dimensional approach, focusing on metrics such as the volume of digital transactions, income from fees and commissions, and the proliferation of Automated Teller Machines (ATMs) and Cash Deposit Machines (CDMs). Financial performance, on the other hand, is gauged using critical indicators like Return on Assets (ROA) and Return on Equity (ROE). The analysis reveals nuanced insights: while the increase in ATMs and CDMs correlates positively with financial performance, this relationship lacks statistical significance. In contrast, a substantial and positive effect on financial performance is observed from the volume of digital transactions and the income generated from fees and commissions. Significantly, the findings indicate that digital transformation initiatives have enabled commercial banks to not only weather the pandemic but also enhance their financial performance during this period of unprecedented challenge. These results emphasize the imperative for financial institutions to strategically integrate advanced technologies, such as artificial intelligence, into their digital transformation agendas. By doing so, they can secure and potentially elevate financial performance, even amidst unforeseen global crises like a pandemic.

Exploring the Impact of Urban Transformation on Building Functions: A Case Study of Main Saddar Bazar Sialkot Cantt

Exploring the Impact of Urban Transformation on Building Functions: A Case Study of Main Saddar Bazar Sialkot Cantt

Behavioural intention to adopt mobile trading apps: an integrated theoretical and digital framework, privacy concerns, and information richness model

This research investigates the transformative impact of mobile trading apps on the Indian financial landscape, particularly in the context of the unprecedented surge in DMAT (dematerialisation) accounts following the COVID-19 pandemic. Due to the advancement of online platforms and fast internet connectivity, stock exchanges across the globe have seen a dramatic inflow of retail investors and brokerage firms. The choice of using a particular mobile trading app draws significant importance because various factors determine the ability and ease of use of a specific app. The study underscores the role of FinTech services, particularly mobile trading apps, in revolutionizing stock trading by offering real-time access, increased trading activity, and enhanced features. Despite the proliferation of research on FinTech apps, a notable gap exists in understanding the adoption dynamics of mobile trading apps, especially in the Indian context. To address this gap, our research applies an adapted and extended version of the Unified Theory of Acceptance and Use of Technology (UTAUT-3) framework to examine the factors influencing investors’ intentions and usage of mobile trading apps. We introduce novel elements such as information richness and privacy concerns, which are crucial in the financial domain. A convenient sample size of 573 actively brokerage app-using respondents was selected to investigate and conclude the consumers’ behavioural intention to use mobile trading apps. The findings highlight the significant impact of practical value, effort expectancy, social influence, hedonic motivation, trust, information richness, privacy concerns, facilitating conditions, and personal innovativeness in IT (Information technology) on investors’ intentions to use trading apps. These factors influence behavioural intentions and mediate the relationship between various constructs, emphasizing their multifaceted roles in shaping user perceptions. Theoretical implications of the research contribute to extending the UTAUT-3 model and providing a comprehensive framework for examining technology adoption in the financial domain. Moreover, practical implications guide developers, financial institutions, and policymakers in creating secure, user-friendly, and information-rich mobile trading systems. While acknowledging sampling and self-reported data limitations, this research lays the groundwork for future longitudinal studies. It encourages the exploration of diverse FinTech services to gain a holistic understanding of adoption dynamics in the evolving financial technology landscape. This study adds empirical knowledge to mobile trading app adoption and catalyzes further research, shaping the trajectory of FinTech studies and practical applications in the ever-evolving financial ecosystem.

Advancing Quality and Safety Culture in Healthcare: Insights From the Evaluation of an Improvement Science Program for Nurses and Midwives.

This paper presents the outcomes and insights gained from the implementation of an Improvement Science program tailored for nursing and midwifery staff within a large local health district in New South Wales. The programme aimed to enhance frontline clinicians' confidence and capability in quality improvement, ultimately improving patient outcomes and safety culture. Through an explanatory sequential mixed-methods evaluation study, we assessed the programme's effectiveness in building capacity, sustaining practice changes and fostering a culture of continuous improvement. Quantitative data were collected through pre-post knowledge surveys, post workshop feedback and programme participation rates. Qualitative data were then collected via nine interviews with programme participants. Simple descriptive statistical analysis for quantitative data and a thematic analysis of qualitative data was undertaken. Data were then integrated from these multiple sources to gain a deeper understanding of the outcomes of the Improvement Science Program. Key findings indicate that coaching and mentoring support significantly contributed to project completion and sustained practice changes. Structured coaching sessions, collaborative team meetings, and executive sponsorship were vital components that facilitated successful outcomes. Notably, effective leadership, often demonstrated by Clinical Nurse Educators and Consultants, played a crucial role in fostering staff collaboration and participation. Insights from qualitative interviews highlight the transformative impact of the programme on participants' skills, confidence and practice. The paper concludes with recommendations for future Improvement Science programs, emphasising the importance of structured coaching, accountability mechanisms, and the identification and support of future coaches. Overall, this study underscores the value of ongoing training initiatives in promoting a culture of safety, quality improvement and enhanced patient outcomes in healthcare settings. This study had no patient or public contribution. Adherence to Standards for Reporting Qualitative Research (SRQR) EQUATOR guidelines (see Supplementary file).

Relationship-Centered Care for Older Adults in Long-Term Care Homes: A Scoping Review.

This scoping review, following Levac et al.'s methodology, examines the implementation and impact of relationship-centered care (RCC) in long-term care (LTC) settings for older adults. Peer-reviewed articles from AgeLine, CINAHL Complete, MEDLINE, PsycINFO, and Web of Science were included if published after 2000, involved older adults in LTC homes, focused on RCC, and conducted in Australia, Europe, New Zealand, or North America. Key findings were organized using inductive content analysis, and 41 empirical studies with qualitative, quantitative, and mixed-methods designs were included. Three categories emerged: (1) Core Practices of RCC-relationship building and reciprocal exchange; (2) Transformative Impacts of RCC-improved care quality and collaboration; and (3) Pathways and Roadblocks to RCC-individual and organizational factors. By understanding the key elements, facilitators, and barriers of RCC, policymakers and practitioners can develop targeted strategies to improve care experiences and outcomes for residents, families, staff, and all others involved in LTC.