A new measure of firm-level AI investments is proposed, using a unique combination of worker resume and job postings datasets, which reveals a stark increase in AI investments across sectors.
The key finding from this study demonstrates the need for continuous development of AI models that could be alert to the latest fraudulent activities and exploration of existing limitations of ML or DL-enhanced models.
This study provides a comprehensive understanding of AI and GAI's functionality and applications in the SCOM context, offering a practical framework for both practitioners and researchers and systematically identifies where and how AI and GAI can be applied in SCOM.
This paper tries to answer the question: How does ICT affect the leadership in virtual teams?
The findings indicate that AI integration significantly improves SCM by improving demand forecasting, inventory management, and overall decision-making capabilities and underlines the importance of a balanced approach that integrates technological developments with human-centric and sustainable practices.
The empirical results show that the technology context (IT infrastructure and digital tools) along with the existing level of innovation are the main drivers that act as stepping stones in digital technology adoption.
A review of the optimization techniques of LMD, focusing on Artificial Intelligence (AI) driven decision-making, IoT-supported real-time monitoring, and hybrid delivery networks, finds that the combination of AI and IoT improves predictive analytics, dynamic routing, and fleet management, but scalability and regulatory issues are still major concerns.
It is shown that a rising Bitcoin price is followed by entry of new users, in particular among more risk-seeking segments of the population, and that when prices rise larger holders sell, likely making a return at retail users’ expense.
Evaluating the effect on the performance of small and medium enterprises (SMEs) of technological developments, including digital marketing, and the variables that affect the relationship revealed that digital marketing is essential for SME effectiveness, as a driver of digital transformation, leading to stronger economic results and an enlarged market presence.
This review delves into the intersection of e-commerce and consumer behavior, focusing on the transformative role of Artificial Intelligence (AI)-powered personalization and its impact on market trends.
This article provides an overview of the diverse AI models and algorithms employed in logistics optimization, with a focus on sustainable practices, and explores emerging trends in AI-driven logistics optimization, such as the integration of real-time data analytics, blockchain technology, and autonomous systems.
The results of the study shed light on how much perceived augmentation and interaction affect consumers’ cognitive and emotive reactions, including feelings of realism, immersion, and telepresence.
This study sheds light on the intricacies of the digitalization process, while also providing valuable insights into the factors influencing its adoption and the resulting performance outcomes in the SME context.
The study identifies patterns among EU countries based on their digital technology adoption, innovation expenditures, and revenues and the proportion of enterprises engaged in innovation activities and highlights the central role of digital technologies in enhancing innovation and competitiveness.
This research explores the transformative influence of Artificial Intelligence on various industries, such as software engineering, automation, education, accounting, mining, legal services, and media, and underscores the importance of crucial skill sets, such as technical proficiency and adaptability, to successfully adopt AI.
The analysis shows that the ES method surpasses the accuracy of the GB machine learning for material forecasting to minimize inventory, and gives practitioners a practical roadmap for the optimal forecasting strategy to streamline inventory management operations.
The research presents valuable insights both researchers and practitioners, facilitating the navigation of adoption barriers, capitalizing on enablers, and unlocking AI’s potential to reshape project management practices across industries.
The study finds that following ethical concerns are the hinderance in the adaptation of AI in business (Privacy and data protection, bias and fairness, transparency and explainability, job displacement and workforce changes, algorithmic influence, and manipulation, accountability, and liability).
Findings of this study emphasise the pivotal role of NMs in driving EBP implementation through adaptive leadership, strategic resource management, and fostering learning networks in enhancing EBP uptake within resource-limited settings.
The AI Risk Repository is the first attempt to rigorously curate, analyze, and extract AI risk frameworks into a publicly accessible, comprehensive, extensible, and categorized risk database that creates a foundation for a more coordinated, coherent, and complete approach to defining, auditing, and managing the risks posed by AI systems.
This review delves into the intricate landscape of sentiment analysis, exploring its significance, challenges, and evolving methodologies and examines crucial aspects like dataset selection, algorithm choice, language considerations, and emerging sentiment tasks.
It is suggested that AI and BD readily contribute to further sustainable development of the weak form, but that it also holds great promise for achieving the strong sustainability ideal.
Article Galaxy Pages is a free service from Research Solutions, a company that offers access to content in collaboration with publishing partners, online repositories and discovery services.