Era Of Transformation Research Articles

Fostering Tech Integration: Teachers' Attitudes Mediating Lifelong Learning and Technology Integration Self-Efficacy

What matters in education now is teaching and learning in a transformational era. It is primarily about what we demand from education and how we acquire information. To manage the dynamism of learning and teaching, it is crucial to research the teachers’ integration of technology in the context of lifelong education. This study investigates how teachers’ perspectives of lifelong learning and technology attitudes influence technology integration self-efficacy. A structural equation model was constructed to represent the causal relationships between variables. In the 2021-2022 academic year, 386 teachers from various high schools in Eskişehir, Türkiye, were selected using the stratified sampling method. Descriptive analysis and simple linear regression analysis were used to analyze the data, and exploratory and confirmatory factor analysis determined the structural validity of the scales. The validity of the structural equation model was tested by means of path analysis and the model was found to be acceptable. Results show that teacher attitudes mediate between lifelong learning and technology integration self-efficacy, thereby influencing successful technology integration in the classroom. Examining the relationship between teachers’ perceptions of lifelong learning and their level of competence in adapting to technological advances is expected to contribute to relevant studies in this area.

The Law of Data-driven on Employee Growth in Enterprise Human Resource Management in the Era of Digital Transformation

In the era of digital transformation, the popularity of artificial intelligence technology has driven the development of the field of Human Resource Management (HRM) in enterprises, and data-driven HRM has become the key to the development and success of enterprises. Due to the late start, data-driven HRM is still in the development stage in China. To address the problem that traditional HRM lacks accuracy and real-time, this study proposes a Growth Potential Prediction (GPP) model based on the combination of all class features and a Random Forest (RF) classifier. The results of the study showed that the prediction accuracy of interpersonal background, work ability, educational status and organisational environment characteristics under the screening index based on [Formula: see text]1 value were 85.01%, 66.34%, 66.41%, 44.19% and 64.27%, respectively. The accuracy of ROS under the RF classifier and the macro [Formula: see text]1 value were 87.31% and 87.24%. After adding the network features, the accuracy and macro [Formula: see text]1 values of the feature ensemble could reach 90%, and the accuracy and macro [Formula: see text]1 values of all class feature combinations were 89.01% and 89.10%, respectively. In summary, the GPP model based on the combination of all class features and the RF classifier proposed in the study can accurately predict the growth potential of employees and provide some guarantee for mining the growth pattern of employees.

Navigating the Future of Pedagogy: The Integration of AI Tools in Developing Educational Assessment Rubrics

ABSTRACTThe advent of artificial intelligence (AI) technologies heralds a transformative era in education. This study investigates the integration of AI tools in developing educational assessment rubrics within the ‘Curriculum Design Development and Evaluation’ course at the University of A Coruña during the 2023–2024 academic year. Employing an action–research methodological approach, 27 comprehensive evaluation rubrics were developed using AI tools like ChatGPT. The findings highlight AI's ability to enhance rubric precision, efficiency and alignment with curricular objectives, thus facilitating personalised learning experiences. This research underscores AI's transformative potential in education, advocating for broader adoption and the necessity for educators to acquire AI proficiency. The study demonstrates how AI tools can streamline the rubric development process, making it more accurate and time efficient while also ensuring the inclusion of essential curricular elements. Through this approach, AI can support innovative assessment strategies that are both effective and adaptable to diverse educational contexts.

A probabilistic forecast for multi-year ENSO using Bayesian convolutional neural network

Abstract A robust El Niño Southern Oscillation (ENSO) prediction is essential for monitoring the global climate, regional monsoons, and weather extremes. Despite dedicated efforts spanning decades, the precise prediction of ENSO events through numerical modeling beyond a couple of seasonal lead times remains a daunting challenge. The advent of deep learning-based approaches marks a transformative era in climate and weather prediction. However, many machine learning-based studies attempting ENSO prediction are confined to singular estimates, lacking adequate quantification of uncertainty in learned parameters and overlooking the crucial need for a nuanced understanding of ENSO prediction confidence. Here, we introduce a deep learning-based Bayesian convolutional neural network model that provides robust probabilistic predictions for ENSO with a lead time of up to 9–10 months across all seasons. The Bayesian layers within the convolutional neural network maintain the capability to predict a distribution of learned parameters. Augmented with bias correction, our model reproduces the amplitude of the Niño 3.4 index with fidelity for lead up to 9–10 months. The inherent capacity for uncertainty modeling enhances the reliability of bayesian neural networks (BNNs), making them particularly valuable in operational services. This research holds substantial socio-economic implications as it enhances our forecasting capabilities and rigorously quantifies forecast uncertainties, providing valuable insights for planning and policymaking.

Application and Prospect of Artificial Intelligence Technology in Low-Carbon Cities—From the Perspective of Urban Planning Content and Process

In the era of digital transformation, artificial intelligence (AI) technology—one of the swiftest growing emerging technologies—when integrated with urban planning, can introduce innovative approaches for low-carbon city development and foster the attainment of dual carbon objectives: carbon neutrality and peak carbon emissions. Current research predominantly investigates the influence and alterations of emerging technologies on urban elements, yet it overlooks a comprehensive examination of the applicable procedures of these technologies and their potential synergy with urban planning. Consequently, this study employs a systematic literature review to delve into the application of AI in sectors such as architecture, transportation, land use, and green space development. It categorizes the specific impact processes into monitoring, identification, simulation, and prediction. By offering an exhaustive analysis of urban planning’s content and methodology, this paper elucidates the role of AI technology in the creation of low-carbon cities. The study found that: (1) Due to the varying degrees of application and integration with professional technologies in different fields, the current research focuses more on architecture, land use, and transportation. (2) Combining the four steps of urban planning, artificial intelligence can be divided into monitoring, recognition, simulation, and prediction types, each with its own characteristics. (3) Overall, AI technology is mainly applied in the identification and simulation of architecture, transportation, and land use. (4) There is still room for improvement in the application of AI technology in waste emissions and other algorithms.

The impact of servitization transformation on the ESG performance of manufacturing firms

In the new era of green and low-carbon economic transformation, servitization transformation enhances the production efficiency and perceptual capabilities of manufacturing firms and offers a novel approach to fulfilling environmental, social, and governance (ESG) responsibilities. This study employs a sample of Chinese-listed manufacturing firms from 2009 to 2021 to provide a theoretical analysis of the intrinsic mechanisms by which servitization transformation impacts ESG performance, including the roles played by total factor productivity, human capital, and firm goodwill. We then empirically examine the impact and mechanisms by which servitization transformation impacts the ESG performance of firms, finding the following. First, servitization transformation significantly improves ESG performance and this conclusion still holds following a series of robustness tests. Second, servitization transformation enhances ESG performance through the following three channels: improving total factor productivity, optimizing the structure of human capital, and accumulating firm goodwill. Third, the ESG performance of state-owned, high-tech, and large firms is more sensitive to servitization transformation. This study enriches and expands the application of servitization transformation research to manufacturing, providing policy insights that would allow manufacturing firms to better fulfill their ESG responsibilities and promote green and sustainable economic development.

The Impact of Quiet Quitting on Turnover Intentions in the Era of Digital Transformation: The Mediating Roles of Job Satisfaction and Affective Commitment, and the Moderating Role of Psychological Safety

This study examines the impact of “quiet quitting” during digital transformation on job satisfaction, affective commitment, and turnover intention. A time-lagged survey was conducted over six months with two waves of data collection from full-time employees in South Korea, resulting in 258 valid responses. Using the PROCESS macro for analysis, the findings reveal that quiet quitting significantly reduces job satisfaction and affective commitment, which, in turn, increases turnover intention. Furthermore, psychological safety serves as a critical moderator, buffering the negative effects of quiet quitting on these outcomes. The study confirms that the influence of quiet quitting on turnover intention operates through the mediating roles of job satisfaction and affective commitment, and organizations with higher psychological safety are better equipped to mitigate these adverse effects. Grounded in Withdrawal Progression Theory, this study empirically demonstrates the progression of quiet quitting into turnover intention and provides strategic insights for organizations to prevent employee turnover and maintain employee engagement during digital transformation.

Implementing agile management practices in the era of digital transformation

In the era of digital transformation, organizations face unprecedented technological changes that demand a shift toward more adaptive and responsive management practices. This paper Analyses how organizations can strategically implement agile management practices to navigate these rapid changes effectively. Agile management emphasizes flexibility, collaboration, and customer-centricity, enabling organizations to respond swiftly to market dynamics and evolving customer needs. By adopting frameworks such as Scrum, Kanban, and Lean, companies can enhance their management processes, fostering a culture of continuous improvement and innovation. The paper explores the fundamental principles of agile management and their relevance in the context of digital transformation. It discusses how cross-functional teams, iterative development, and regular feedback loops can facilitate quicker decision-making and enhance collaboration among stakeholders. Additionally, the integration of digital tools, such as project management software and communication platforms, supports agile methodologies by streamlining workflows and improving transparency. Key considerations for successful implementation include aligning agile practices with organizational goals, investing in employee training, and promoting a mindset that embraces change. The paper highlights real-world case studies demonstrating the successful application of agile management in various industries, showcasing its potential to improve responsiveness and operational efficiency. Ultimately, this analysis underscores the critical role of agile management practices in enabling organizations to thrive amidst the challenges of digital transformation

The Strategic Role of Digital Transformation: Leveraging Digital Leadership to Enhance Employee Performance and Organizational Commitment in the Digital Era

Given the rapid advancements in the digital transformation era, digital leadership has become essential for enhancing employee performance and organizational commitment. This study specifically examines the mediating role of digital transformation in the relationship between digital leadership, employee performance, and organizational commitment, drawing on data collected between June and August 2024 from 579 participants across diverse industries. The findings demonstrate that digital leadership significantly enhances employee outcomes by driving digital transformation, which serves as a crucial intermediary that amplifies the positive effects of leadership. This research underscores the importance of aligning leadership strategies with digital transformation initiatives, especially in the DT-driven business landscape, to promote sustainable growth and maintain a competitive edge. By highlighting the combined influence of leadership and digital transformation on employee performance and organizational commitment, this study provides valuable insights for organizations addressing the complexities of digital change. It also emphasizes the pivotal role of leadership in fostering innovation and organizational resilience in the digital transformation era.

Leveraging quantum blockchain for secure multiparty space sharing and authentication on specialized metaverse platform

In the era of digital transformation, securing data on metaverse platforms poses significant challenges. This paper proposes Multiparty Space Sharing and Authentication (MSSA), a novel approach for secure user login and location access control within specialized metaverse platforms. MSSA leverages Quantum Multiparty Secret Computation (QMSC) integrated with a quantum blockchain network. This integration facilitates user verification within the presence of potentially untrusted metaverse authority. The underlying quantum blockchain employs a Delegated Proof-of-Stake (DPoS) consensus mechanism with a Borda voting scheme for authority node selection. By harnessing the principles of quantum cryptography, MSSA offers enhanced security against both classical and anticipated future quantum attacks. This research demonstrates the feasibility and potential of quantum blockchain for securing metaverse platforms, paving the way for secure and decentralized digital ecosystems.

Talent Management in the Era of Digital Transformation: Challenges and Prospects

This article explores the intricate landscape of talent management in the context of digital transformation, highlighting the associated challenges and prospects that organizations face. Utilizing a qualitative approach, the study employs a comprehensive literature review and library research to synthesize existing knowledge on the evolving role of talent management in a rapidly changing digital environment. The findings reveal that digital transformation significantly impacts recruitment, retention, and development strategies, necessitating a shift in traditional talent management practices. Organizations must adapt to technological advancements and changing workforce expectations, embracing new tools and methodologies to effectively engage and develop talent. Key challenges identified include the skills gap, resistance to change, and the need for continuous learning and development. Conversely, the prospects for enhancing employee engagement and fostering innovation through strategic talent management practices are promising. The study concludes that organizations must adopt a proactive and adaptive approach to talent management, ensuring alignment with digital transformation initiatives to achieve sustained competitive advantage. This research contributes to the ongoing discourse on talent management by providing valuable insights into the interplay between digital transformation and effective talent strategies, offering practical recommendations for practitioners and scholars alike.

Development augmented reality assisted teaching modules human sensory system to improve student learning outcomes

In the era of digital transformation, the use of technology to improve the quality of learning is very important. This research aimed to develop a teaching module for human sensory system material assisted by augmented reality media to improve students' biology learning outcomes. This research uses research and development methods. The subjects of this research were 22 Biology Education students at the University of Papua. Data collection instruments include validation sheets and questionnaires to determine the validity and responses of students to teaching modules as well as providing multiple choice questions to measure learning outcomes. The data analysis technique is descriptive by calculating validation results, analyzing student response questionnaires and student learning outcomes. The research results show that media and material expert validation test results obtained a percentage of 93.33% with a very valid category. The results of assessing student responses in the trial obtained an average percentage of 85.13% in the very good category. Student biology learning results show an average of 61.36 in the sufficient category. The conclusion of the research on Augmented Reality-assisted teaching modules meets the criteria of being valid, practical and effective and improving students' biology learning outcomes.

Examining the impact of artificial intelligence on employee performance in the digital era: An analysis and future research direction

A new era of digital transformation has begun with the rapid integration of Artificial Intelligence (AI) technology with human management, changing traditional methods to people management. Due to the unprecedented digital transitions that businesses are seeing, AI integration in Human resource management (HRM) has become a significant area of focus. This systematic literature critically examines how AI is altering the landscape of its impact on employee performance in the HRM area in the era of digital transformation. The Scopus database, where 73 peer-reviewed articles are found These are subjected to integrated methodology of Bibliometric analysis, Content analysis, Epistemological analysis and Substantive analysis to identify the emerging themes, trends and contribution of theory in the AI impact on the employee performance in digital transformation era. The results identifies the major themes a) Digital Transformation in HRM for enhancing Efficiency b) Deep learning and neural networks in HRM c) Innovation and Technology adoption in HRM and d) Human resource investments. From the epistemological analysis results “Resource Based theory,” has been mentioned highest (4 times) and shows how HRM is evolving in the context of digital change. With 3 instances each, institutional theory with empirical study is being the most common method. Substantive analysis shows the Digital Transformation, Employee Performance, Work life balance, and Organisational change are the significant criteria, whereas sub-criteria included Innovation, performance management, and Techno stress. Additionally, it investigates the challenges and opportunities arising from how AI is incorporated into HRM procedures and its implications for workforce dynamics. The study has proposed a model of 3 major criteria and 14 sub criteria for future research actions based on substantive analysis. AI integration in HRM requires strategic planning, ethical considerations, and employee well-being. Organisations that recognise these consequences and handle issues will be more prepared for AI-driven HRM.

Leadership Training in the Era of Digital Transformation: Case Study of Amazon

Abstract: Enterprises are entering the digital transformation era to adapt to rapidly changing market conditions and technological advancements. As organisations undergo digital transformation and reshape their business models and practices, this study explores how digital technology facilitates the development of new business models, changes corporate interaction channels, and the positive impact of digital transformation on leadership training. As a global leader in e-commerce and cloud computing, Amazon provides lessons and insights for other companies' leadership training in digital transformation through an in-depth study of its leadership training models and practices. This study explores in depth the impact of digital transformation on leadership training, analyses the effectiveness and challenges of leadership training in the context of digital transformation, and how to innovate leadership training models in the context of digital transformation. Analysing the case of Amazon enriches and improves the existing leadership training theories and provides new research perspectives and ideas for the academic community.

Employee participation at company level: institutions, articulation and challenges

Employee participation at company level is one of the core institutions of what can be called the ‘European social model’, based on national regulations and regulations at EU level, such as the directives on European Works Councils (EWCs) and the Societas Europaea (SE). This process of institutionalisation coincides with fundamental changes in the current era of globalisation and transformation, which increase the importance of the company level for employee participation. We argue that this development highlights the problem of articulation within the multi-level system of employee participation. By comparing institutions of participation at national – we include the cases of France, Germany, Spain and Sweden – and at EU level we analyse whether and how these institutions create opportunities to influence company decisions by giving voice to workers’ representatives. In doing so we identify good practices and, on that basis, develop policy recommendations to strengthen the articulation of employee representation at company level.

Critical factors for the success of Sustainable Development Goal 12 in the digital transformation era: The effect of ISO 14001

AbstractCompeting in the global market requires organizations to change rapidly, addressing both digital transformation and sustainable development challenges. This study uncovers new relationships and critical factors, enriching current knowledge and guiding future research on how digital transformation enhances sustainable consumption and production (Sustainable Development Goal 12 [SDG12]) success. It identifies key factors that enhance or inhibit these relationships by combining structural model and necessary conditions analysis. The findings reveal that organizations must excel in digital capabilities directly and through excellence practices to achieve SDG12 success. ISO 14001 further strengthens the impact of digital transformation and excellence practices on SDG12. The results empirically demonstrate what European Foundation for Quality Management (EFQM) and American Society for Quality (ASQ) advocate: excellence practices are a tool for sustainable development. This study adds both to the literature and practice on the relationships between digital transformation, excellence models, and sustainable development and how these relationships are influenced by ISO standards.

Трансформация технологий профессионального образования в условиях цифровизации

The aim of study is to develop a technology for effective interaction between universities and business based on the analysis of the problems of vocational education in the era of digital transformation. The article examines the changes that have occurred in the business processes of organizations and highlights the key gaps between the level of graduate qualifications and employer requirements. To solve the identified problems, it is proposed to establish a systemic collaboration between business, science and education. The following forms of interaction between business and universities are being explored: case study technologies, educational hackathons and scientific crowdsourcing. These technologies can bring mutual benefits to all stakeholders. For the interaction of the educational and scientific components of the university, a new concept of student association called student scientific enterprise is proposed. This association is built on the principles of self-organization and self-government and has the characteristics of a real enterprise. Its main goal is to involve students in scientific work and adapt young people to future professional activities. Scientific novelty: a theoretical model of collaboration between business and universities for mutual benefit has been developed. As a result of the study, forms of interaction among science, professional education and business were proposed.

Paperless libraries: The trending way to go in the fifth industrial revolution

The idea that spurred the author’s interest in carrying out this study results from understanding a cashless society, where users of banking systems only move around with their ATM cards. With their ATM cards, they can access their money anywhere globally. This approach could resonate in libraries, where we now have a paperless society, having cost-benefit analysis in the era of the fifth Industrial Revolution (5IR). The 5IR has to do with humans interacting between technology or machines either to solve individual and organizational societal problems from a general or specific perspective. The interaction between humans and technology would assist in recognizing the synergistic in addressing the support for task accomplishment. The methodology applied is in two stages, first, a systematic literature review and second, interpretive content analysis of literature harvested from the database of Scopus. Findings revealed that technological advancements have enabled paperless libraries such that on-screen reading is increasingly prevalent, rapid development support through mobile computing, software, and internet/connections/Wi-Fi, multifarious electronic information retrieval among others. Furthermore, other findings were anchored on the relevance of paperless libraries in the 5IR, the functionality of paperless library systems, enhanced accessibility, and inclusivity, collaboration and connectivity, and environmental impact. Meanwhile, certain challenges and mitigation strategies were proffered. The study concludes that as we navigate this transformative era, the emergence of paperless libraries stands as a testament to the harmonious integration of technological prowess and human aspirations. Therefore, envision human-machine interactions be encouraged to bring about paperless libraries, considering the significance of AI and human-centric innovation.

The Public Interest in the Digital Age: Exploring the Emerging Roles and Governance Models of the AI as a Common Good

With the continuous development of artificial intelligence, we are living through the era of digital transformation, and the fourth Industrial Revolution is a paradigm change with unprecedented speed, scale, scope and complexity, and is fundamentally transforming production, consumption and society as a whole. As the basic unit of public management research, data has established a strong connection between the promotion of digital revolution and the change of public management research paradigm. The rise of AI technologies has enhanced AI governance and brought unprecedented help to policymakers. This study has used a cross-sectional quantitative design to capture perception and attitude towards AI as common good from a sample of 400 Chinese responders coming from diverse age, group and occupation categories. The key factors which measured were public awareness of AIGC, the extent of its utilization in government policy, public attitudes toward AIGC, and public participation in policy development. The findings indicated that public understanding and trust are paramount to successfully integrate Ai as common good in governance framework. Public enthusiasm and participations are highly affected by trust and public understanding. To deliver policies without much resistance, heightened awareness, participations and trust becomes essential.

Navigating uncertainty: Exploring consumer acceptance of artificial intelligence under self-threats and high-stakes decisions

In an era of transformation fueled by Artificial Intelligence (AI), human resistance to adopt this powerful technology has emerged as one of its most critical barriers. In a series of four studies involving almost 4,000 consumers, this research explores factors that contribute to consumer reluctance toward AI through theories related to algorithm aversion, decision-making under risk, and compensatory decision-making. The results underscore the impact of decision stakes and their adverse outcomes on AI service agent adoption across decision domains. These effects can be attributed to the self-threat experienced by consumers in high-stakes decision scenarios. Together, the current findings advance our understanding of consumer responses in the context of AI adoption, illustrating how perceived stakes and self-threats foster reluctance to rely on AI agents for advice. From a practical standpoint, the results emphasize the need of a hybrid approach—combining AI and human agents—for a successful transition toward AI-powered service industries.