Self-determination theory has shaped our understanding of what optimizes worker motivation by providing insights into how work context influences basic psychological needs for competence, autonomy and relatedness. As technological innovations change the nature of work, self-determination theory can provide insight into how the resulting uncertainty and interdependence might influence worker motivation, performance and well-being. In this Review, we summarize what self-determination theory has brought to the domain of work and how it is helping researchers and practitioners to shape the future of work. We consider how the experiences of job candidates are influenced by the new technologies used to assess and select them, and how self-determination theory can help to improve candidate attitudes and performance during selection assessments. We also discuss how technology transforms the design of work and its impact on worker motivation. We then describe three cases where technology is affecting work design and examine how this might influence needs satisfaction and motivation: remote work, virtual teamwork and algorithmic management. An understanding of how future work is likely to influence the satisfaction of the psychological needs of workers and how future work can be designed to satisfy such needs is of the utmost importance to worker performance and well-being. Technology is changing the nature of work by enabling new forms of automation and communication. In this Review, Gagné et al. describe how self-determination theory can help researchers and practitioners to shape the future of work to ensure that it meets the psychological needs of workers.
S. Dehghan, Sasan Sattarpanah Karganroudi, Said Echchakoui
et al.
This bibliographic analysis explores the evolving landscape of additive manufacturing (AM) in the context of Industry 4.0 and the emerging paradigms of Industry 5.0. This research critically examines the key literature and scholarly works to clarify the evolution, challenges, and opportunities presented by integrating AM technologies with digital transformation and advanced industrial practices. The exploration begins by tracing the foundational concepts of Industry 4.0, emphasizing the role of cyber–physical systems, data analytics, and automation in reshaping manufacturing ecosystems. It then moves to the developments of Industry 5.0, focusing on human-centric approaches, collaborative robotics, and sustainable manufacturing strategies that extend beyond automation. The impact of AM technologies across various sectors, from aerospace and automotive industries to healthcare and consumer goods, is central to this analysis. This article synthesizes empirical studies, case analyses, and theoretical frameworks to discern the synergies, challenges, and prospects of integrating AM into Industry 4.0 and the evolving Industry 5.0. Through this bibliographic journey, readers gain insights into the transformative potential of AM as a catalyst for innovation, agility, and sustainability in the digital age. The findings underscore the need for interdisciplinary collaborations, policy frameworks, and technological advancements to harness AM’s full potential within Industry 4.0 and 5.0.
The emergence of generative artificial intelligence (GenAI) represents not an incremental technological advance but a qualitative epistemological shift that challenges foundational assumptions of computer science. Whereas machine learning has been described as the automation of automation, generative AI operates by navigating contextual, semantic, and stylistic coherence rather than optimizing predefined objective metrics. This paper introduces the concept of Vibe-Automation to characterize this transition. The central claim is that the significance of GenAI lies in its functional access to operationalized tacit regularities: context-sensitive patterns embedded in practice that cannot be fully specified through explicit algorithmic rules. Although generative systems do not possess tacit knowledge in a phenomenological sense, they operationalize sensitivities to tone, intent, and situated judgment encoded in high-dimensional latent representations. On this basis, the human role shifts from algorithmic problem specification toward Vibe-Engineering, understood as the orchestration of alignment and contextual judgment in generative systems. The paper connects this epistemological shift to educational and institutional transformation by proposing a conceptual framework structured across three analytical levels and three domains of action: faculty worldview, industry relations, and curriculum design. The risks of mode collapse and cultural homogenization are briefly discussed, emphasizing the need for deliberate engagement with generative systems to avoid regression toward synthetic uniformity.
Ann Thong Lee, R Kanesaraj Ramasamy, Anusuyah Subbarao
(1) Background: Although technology constantly evolves and revolutionising many industries in this digital age, the healthcare industry is comparatively conservative and has been slow to adopt new technologies due to concerns about patient safety. Notwithstanding the abundance of research on technology acceptance, the majority of them fail to take into account departmental variations, making it impossible to enhance technology adoption in the medical sector. (2) Methods: This study examined the factors influencing Malaysian emergency department healthcare professionals' acceptance of new medical technology by combining two external variables, which are organisational support and training, with the Technology Acceptance Model (TAM). The target population of this study consisted of emergency department healthcare professionals in Malaysian hospitals who are 25 to 60 years old and above. A total of 140 valid questionnaires were gathered after the survey was sent by email and WhatsApp to hospital emergency departments around the country. Data collected were analysed using SPSS and SmartPLS. (3) Results: Perceived usefulness and training have a significant impact on attitude toward use, whereas attitude toward use is the sole variable that directly influences behavioural intention to use and acts as a mediator in certain paths. (4) Conclusion: To encourage the successful adoption and use of technology, hospital administration should focus on the real needs of medical personnel, enhance their knowledge of it, and provide focused training.
In an age of fast-paced technological change, patents have evolved into not only legal mechanisms of intellectual property, but also structured storage containers of knowledge full of metadata, categories, and formal innovation. This chapter proposes to reframe patents in the context of information science, by focusing on patents as knowledge artifacts, and by seeing patents as fundamentally tied to the global movement of scientific and technological knowledge. With a focus on three areas, the inventions of AIs, biotech patents, and international competition with patents, this work considers how new technologies are challenging traditional notions of inventorship, access, and moral accountability.The chapter provides a critical analysis of AI's implications for patent authorship and prior art searches, ownership issues arising from proprietary claims in biotechnology to ethical dilemmas, and the problem of using patents for strategic advantage in a global context of innovation competition. In this analysis, the chapter identified the importance of organizing information, creating metadata standards about originality, implementing retrieval systems to access previous works, and ethical contemplation about patenting unseen relationships in innovation ecosystems. Ultimately, the chapter called for a collaborative, transparent, and ethically-based approach in managing knowledge in the patenting environment highlighting the role for information professionals and policy to contribute to access equity in innovation.
This paper introduces an innovative design for robotic operating platforms, underpinned by a transformative Internet of Things (IoT) architecture, seamlessly integrating cutting-edge technologies such as large language models (LLMs), generative AI, edge computing, and 5G networks. The proposed platform aims to elevate the intelligence and autonomy of IoT systems and robotics, enabling them to make real-time decisions and adapt dynamically to changing environments. Through a series of compelling case studies across industries including smart manufacturing, healthcare, and service sectors, this paper demonstrates the substantial potential of IoT-enabled robotics to optimize operational workflows, enhance productivity, and deliver innovative, scalable solutions. By emphasizing the roles of LLMs and generative AI, the research highlights how these technologies drive the evolution of intelligent robotics and IoT, shaping the future of industry-specific advancements. The findings not only showcase the transformative power of these technologies but also offer a forward-looking perspective on their broader societal and industrial implications, positioning them as catalysts for next-generation automation and technological convergence.
Innovation and its complement exnovation describe the progression of realized possibilities from the past to the future, and the process depends on the structure of the underlying graph. For example, the phylogenetic tree represents the unique path of mutations to a single species. To a technology, paths are manifold, like a "truss." We solve for the phase diagram of a model, where a population innovates while outrunning exnovation. The dynamics progress on random graphs that capture the degree of historical contingency. Higher connectivity speeds innovation but also increases the risk of system collapse. We show how dynamics and structural connectivity conspire to unleash innovative diversity or to drive it extinct.
Global freshwater scarcity continues to escalate due to pollution, climate change, and population growth, making innovative sustainable desalination technologies increasingly vital. Solar stills offer a simple and eco-friendly method for freshwater production by utilizing renewable energy, yet their low productivity remains a major limitation. This study experimentally evaluates and quantifies several established enhancement techniques under real climatic conditions to improve evaporation and condensation efficiency. The integration of porous materials, such as black rocks, significantly improves thermal energy storage and management by retaining absorbed heat during the daytime and releasing it gradually, resulting in an average 30% increase in daily distillate production (SD = 6 mL). Additionally, forced convection using small fans enhances humid air removal and evaporation rates, increasing the average yield by approximately 11.4% (SD = 2 mL). Optical concentration through lenses intensifies solar irradiation on the evaporation surface, achieving the highest performance with an average 50% improvement in water output (SD = 5 mL). The incorporation of Phase Change Materials (PCM) is further proposed to extend thermal stability during off-sunshine hours, with materials selected based on a melting point range of 38–45 °C. To minimize nocturnal heat loss, future designs may integrate radiative cooling materials for passive night-time condensation support, by applying a radiative cooling coating to the condenser plate to enhance passive heat rejection to the sky. Overall, the validated combined use of renewable energy-driven desalination, thermal storage media, and advanced strategies presents a practical pathway toward high-efficiency solar stills suitable for sustainable buildings and decentralized water supply systems in arid regions.
Engineering machinery, tools, and implements, Technological innovations. Automation
In recent years, technology assessments, evaluations, and audits have emerged as a key strategy for surfacing and managing technology systems’ societal effects. However, the evaluation of computational and algorithmic systems has largely been approached through a uni-modal and uni-disciplinary perspective that heavily privileges computer science and engineering disciplines. Silos of discipline and modality, we argue, impose limitations on conceptions of what constitutes ‘technology’ – the object of the assessment – as well as how to evidence its risks and impacts. Reflecting on our experience conducting a multidisciplinary and multimodal assessment, we consider the opportunities afforded by evaluating from various lenses at once, and discuss the steep challenges of navigating tensions between different ways of knowing. Ultimately, we call on assessors to welcome unconventional methods and underrepresented disciplines into the assessment space, as a means to broaden our political visions of mitigation and ethics integration.
Anderson da Silva Gonçalves, Vana Izabel de Araújo Chalender Camacho
This study analyzes contemporary public governance in Brazil, highlighting its relevance in the face of historical challenges, regional inequalities, and technological transformations. The objective is to investigate public management in the current context, identifying structural obstacles and evaluating innovative strategies and tools aimed at improving efficiency, participation, and transparency in the relationship between the State and society. This is an explanatory research, guided by the deductive method, which employed bibliographic and documentary research with a qualitative and interpretative approach, based on recent national and international authors. The main findings show that, although Brazil has been incorporating digital technologies and participatory instruments, it still faces structural, cultural, and federative barriers that limit the effectiveness of public policies. There are inequalities in the technical capacity among municipalities, weaknesses in organizational culture, and low institutionalization of participatory mechanisms, while local experiences and cross-sectoral arrangements emerge as promising paths. It is concluded that modernizing public management requires more than technological innovation, demanding profound cultural changes, strengthening of multilevel governance, and continuous investment in human capital and evaluation instruments, considering governance as a means to build a fairer, more inclusive, and sustainable society.
Bioremediation is experiencing a paradigm shift by integrating three-dimensional (3D) bioprinting. This transformative approach augments the precision and versatility of engineering with the functional capabilities of material science to create environmental restoration strategies. This comprehensive review elucidates the foundational principles of 3D bioprinting technology for bioremediation, its current applications in bioremediation, and the prospective avenues for future research and technological evolution, emphasizing the intersection of additive manufacturing, functionalized biosystems, and environmental remediation; this review delineates how 3D bioprinting can tailor bioremediation apparatus to maximize pollutant degradation and removal. Innovations in biofabrication have yielded bio-based and biodegradable materials conducive to microbial proliferation and pollutant sequestration, thereby addressing contamination and adhering to sustainability precepts. The review presents an in-depth analysis of the application of 3D bioprinted constructs in enhancing bioremediation efforts, exemplifying the synergy between biological systems and engineered solutions. Concurrently, the review critically addresses the inherent challenges of incorporating 3D bioprinted materials into diverse ecological settings, including assessing their environmental impact, durability, and integration into large-scale bioremediation projects. Future perspectives discussed encompass the exploration of novel biocompatible materials, the automation of bioremediation, and the convergence of 3D bioprinting with cutting-edge fields such as nanotechnology and other emerging fields. This article posits 3D bioprinting as a cornerstone of next-generation bioremediation practices, offering scalable, customizable, and potentially greener solutions for reclaiming contaminated environments. Through this review, stakeholders in environmental science, engineering, and technology are provided with a critical appraisal of the current state of 3D bioprinting in bioremediation and its potential to drive forward the efficacy of environmental management practices.
In response to escalating energy consumption, particularly within the housing sector, a global imperative to reduce energy usage has emerged, propelling the concept of "smart houses" to the forefront of innovation. This paradigm shift owes its genesis to the convergence of advancements in energy conversion, communication networks, and information technology, catalyzing the emergence of the Internet of Things (IoT). The IoT facilitates seamless connectivity of devices via the World Wide Web, enabling remote management, monitoring, and detection capabilities. Capitalizing on this technological synergy, the integration of IoT, big data, and machine learning with home automation systems holds immense promise for enhancing energy efficiency. This paper introduces HEMS-IoT, a groundbreaking energy control system for intelligent homes, underpinned by big data analytics and machine learning algorithms, prioritizing security, convenience, and energy conservation. Leveraging J48 neural network technology and the Weka API, the study illuminates user behaviors and energy consumption patterns, enabling household classification based on energy usage profiles. Moreover, to ensure user comfort and safety, RuleML and Apache Mahout are deployed to customize energy-saving recommendations tailored to individual preferences. By presenting a practical demonstration of smart home monitoring, this paper validates the effectiveness of the proposed approach in enhancing security, comfort, and energy conservation. This pioneering research not only showcases the transformative potential of IoT-driven energy management systems but also sets the stage for a sustainable and interconnected future.
PurposeThe aim of this study is to examine in detail the impact of technological advancements on the workforce within the tourism industry. Specifically, it seeks to understand the effects of information and communication technologies (ICT), social media, the internet and websites, mobile technologies and other technological developments on workforce dynamics, skill requirements and job descriptions. The research intends to analyze how technological innovations are transforming the workforce and how these transformations are influencing practices within the industry.Design/methodology/approachThis study employs a comprehensive literature review to understand the impact of technological innovations on the workforce in the tourism industry. The research aims to conduct an in-depth examination of empirical data obtained from extensive databases in the fields of technology and tourism and detail the effects of technological advancements on the workforce. Additionally, it includes a general assessment of trends and transformation processes within the sector by synthesizing findings from existing literature on the relationship between technology and workforce.FindingsThe results of the research reveal that technological innovations have fundamentally transformed workforce dynamics and job descriptions. Developments in information technology have led to the automation of routine tasks and the creation of high-skilled new job roles. Social media has contributed to the emergence of new job roles and skill requirements, while the internet and websites have altered digital marketing strategies. Mobile technologies have increased the necessity for the workforce to develop mobile skills. Furthermore, big data and artificial intelligence applications have enhanced the workforce’s data management and analysis capabilities.Originality/valueThis study makes a significant contribution to understanding the impact of technological innovations on the workforce in the tourism industry. The findings emphasize how technological changes have altered skill requirements and job descriptions, highlighting the increased need for continuous education and skill development.
ABSTRACT Due to globalization and technological advancements, competition and challenges among organizations have increased. To handle the current situation, organizations are in the process of implementing Industry 4.0. Industry 4.0 signifies the transition from embedded systems to cyber-physical systems in terms of technological advancement. With the advent of Industry 4.0, organizational processes are evolving in new ways from time to time to compete and increase profit in the market. Imprecise inventory and warehouse management lead to problems that incur costs and time. To tackle this, there is a need to re-engineer the process with the help of technological innovations. This study employs the Business Process Reengineering approach to redesign the process with Industry 4.0, aiming to gain a deeper understanding of the potential of re-engineered inventory and warehouse management. Incorporating Industry 4.0 technologies, such as the IoT, RFID, sensors, and AI, significantly improves inventory and warehouse management by enhancing accuracy, minimizing manual errors, and speeding up processing times in generating and approving purchase orders, quality checks, receiving and storing goods. The model enhances decision-making via IIP in vendor selection, preventing stockouts and overstocking, space optimization, pilferage, obsolescence, and follow-up, improving accuracy by combining predictive analytics and real-time data through sensors. Automation optimizes resource allocation, leading to cost savings, while blockchain and IoT ensure full traceability across the supply chain, promoting transparency and accountability among suppliers, warehouses, and departments. It offers practical insights for industries that modernize their supply chains, providing a scalable framework to encourage flexibility and adaptability in various contexts.
Akan Ime Ibokette, Tunde Olamide Ogundare, Edwin Osei Danquah
et al.
This review paper explores the dual impacts of Emotional Intelligence (EI) and the Internet of Things (IoT) on Operational Efficiency (OE) in the manufacturing sectors of Nigeria and the United States, providing a comprehensive cross-cultural analysis. In an era where manufacturing industries globally are undergoing rapid technological advancements and organizational transformations, understanding the synergistic role of human and technological factors is crucial. EI, which encompasses the ability to recognize, understand, and manage emotions, significantly influences leadership effectiveness, team dynamics, and overall workplace harmony. Concurrently, the integration of IoT technologies facilitates real-time data monitoring, predictive maintenance, and enhanced automation, leading to substantial improvements in OE. The paper first delineates the conceptual frameworks of EI and IoT, highlighting their individual contributions to manufacturing efficiency. Subsequently, it discusses the comparative analysis of the manufacturing environments in Nigeria and the US, examining how cultural contexts shape the application and impact of EI and IoT. In the United States, advanced technological infrastructure and a culture of innovation foster the widespread adoption of IoT and the integration of EI in organizational practices. Conversely, Nigeria's manufacturing sector, while facing challenges such as infrastructural deficits and skill gaps, shows potential for growth through targeted investments in technology and human capital development. Through this cross-cultural lens, the paper identifies key differences in the perceptions and applications of EI, the extent of IoT integration, and the resulting OEs. The findings suggest that while the US benefits from a mature ecosystem for both EI and IoT, Nigeria's unique socio-economic landscape necessitates tailored strategies to harness these tools effectively. The analysis concludes with policy and practical implications, offering insights for enhancing manufacturing efficiency through balanced and culturally sensitive approaches to technological and EI advancements. This comprehensive review underscores the importance of synergizing human and technological capabilities to drive sustainable growth and competitiveness in the global manufacturing sector. Keywords: Emotional Intelligence, Internet of Things, Operational Efficiency, Manufacturing, Cross-Cultural Analysis, Nigeria and United States.
S. Weiskirchen, Antônio M Monteiro, Radovan Borojevic
et al.
Cell culture banks play a crucial role in advancing biomedical research by providing standardized, reproducible biological materials essential for various applications, from drug development to regenerative medicine. This opinion article presents a comprehensive overview of cell culture banks, exploring their establishment, maintenance, and characterization processes. The significance of ethical considerations and regulatory frameworks governing the use of cell lines is discussed, emphasizing the importance of quality control and validation in ensuring the integrity of research outcomes. Additionally, the diverse types of cell culture banks—primary cells, immortalized cell lines, and stem cells—and their specific contributions to different fields such as cancer research, virology, and tissue engineering are examined. The impact of technological advancements on cell banking practices is also highlighted, including automation and biobanking software that enhance efficiency and data management. Furthermore, challenges faced by researchers in accessing high-quality cell lines are addressed, along with proposed strategies for improving collaboration between academic institutions and commercial entities. By unlocking the potential of cell culture banks through these discussions, this article aims to underline their indispensable role in driving innovation within biomedical research and fostering future discoveries that could lead to significant therapeutic breakthroughs.
Mohammed Ayad Alkhafaji, Ghazi Mohamad Ramadan, Zain Jaffer
et al.
This review comprehensively examines the role of Artificial Intelligence (AI) and the Internet of Things (IoT) in revolutionizing agricultural practices. It highlights how these technologies are pivotal in enhancing crop productivity, optimizing resource use, and ensuring sustainability in response to the challenges of a growing global population and environmental concerns. The article synthesizes key studies to showcase advancements in smart aquaponics and marine farming, emphasizing the the importance of implementation of AI and IoT in agriculture faces significant challenges, including high costs, a digital skills gap among farmers, data management issues, and the need for robust technology. The review also addresses the socio-economic impacts, such as potential job displacement due to automation. Looking ahead, the article suggests that overcoming these challenges will require concerted efforts in technological innovation, policy-making, and education. The future of AI and IoT in agriculture is seen as promising, with potential for further advancements and wider adoption. The integration of these technologies with emerging fields like blockchain could lead to more secure, efficient, and transparent agricultural practices, contributing significantly to global food security and environmental sustainability.
: With the rapid development of AI technology, the digital transformation in the banking sector has entered a new chapter. This paper thoroughly explores the pivotal role of AI in driving the digital transformation of the banking industry, especially in enhancing operational efficiency and strengthening risk control. The article begins by outlining the background of digital transformation in banking, followed by a detailed introduction to the definition, functions, and implementation methods of AI technology in the banking sector. By analyzing the application of AI in areas such as customer service automation, credit risk assessment, transaction monitoring, and fraud detection, this paper highlights how AI optimizes banking business processes and improves service quality. Furthermore, the article discusses the limitations and challenges encountered in the application of AI, including issues related to technological interpretability and data security. Finally, this paper looks forward to the future development trends of AI in banking, pointing out key influencing factors including technological innovation and the involvement of policymakers. Through in-depth analysis, this paper provides practical guidance and strategic recommendations for the banking industry in the process of AI-driven digital transformation, aiming to promote the continuous development and innovation of the banking sector.
Automation in auditing represents a fundamental transformation, allowing for improved operational efficiency and accuracy in error detection. This study examines its advantages, challenges and impact on the auditor's role, highlighting the need to acquire new technological competencies and redefine the professional function. Through a qualitative approach, a literature review was conducted to identify the associated benefits, such as the ability to audit 100% of transactions and free auditors for higher value-added activities. However, the risks of excessive reliance on technology and information overload, which could negatively affect critical judgment, are cautioned. For a successful implementation, it is recommended to integrate automation in a phased manner, manage technology risks through adequate controls, and ensure continuous training of staff. Constant monitoring and adjustment of automated systems is essential to ensure their effectiveness in an environment of constant regulatory change. In conclusion, automation presents a unique opportunity to modernize auditing, but it requires a comprehensive approach that balances technological innovation with professional judgment.
Royani Royani, Sondang Deri Maulina, S. Sugiyono
et al.
This research is a review of recent advancements in the utilization of Machine Learning (ML) and Artificial Intelligence (AI), emphasizing their significant developments across diverse application domains. The purpose of this study is to provide a comprehensive understanding of these technologies and their transformative potential. To achieve this, we conducted an extensive analysis of scholarly literature and case studies, focusing on key applications and recent trends in AI and ML. Our findings reveal critical advancements, particularly in sectors such as business, healthcare, and automation, showcasing the profound impact of these technologies on innovation and operational efficiency. The review also highlights persistent challenges, including ethical concerns, data privacy, and infrastructure requirements. These insights are intended to assist stakeholders in identifying opportunities for the effective implementation and future development of AI and ML applications, ensuring their continued contribution to technological progress.