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Economics and Finance (R0)

Hien Thu Thi Nguyen

Hai Hong Phan

Van-Nam Huynh

Data Science in Finance and Accounting

&lt;p&gt;On Explainable Data Science.- Why Shapley Value and Its Generalizations Are Effective in Economics and Finance, Machine Learning, and Systems Engineering.- Why Skew-Normal Distributions and How They Are Related to ReLU Activation Function in Deep Learning.- A Study of Machine Learning Models for Financial Distress Prediction.- SPredict Stock Market Prediction with Social Media Sentiment Analysis and Machine Learning.- Post-IPO Performance Prediction: A Comparative Study of Logistic Regression and Machine Learning Techniques for Thai IPO Firms.- Enhancing Corporate Bankruptcy Prediction with Machine Learning and Textual Analysis.- AI-Enhanced Investing Sentiment Analysis, Strategy Design, and Automation.- Explainable AI in Finance: Enhancing Transparency and Interpretability of AI Models in Financial Decision-Making.- On Shared Directors and Liquidation Evidence from UK SMEs.- Optimizing Portfolio and Asset Allocation Strategies.- The Impact of Capital Structure on the Performance of Non-financial Enterprises in Vietnam.- Analyze Financial Data Using Benford&amp;rsquo;s Law Evidence From Vietnam Before and During the COVID-19 Pandemic.- IT Governance and Perceived Usefulness of CAATs An Empirical Study.- Micro-level Determinants of Household Financial Portfolio Choices in Rural Vietnam.- The Impact of Information and Communication Technology on Economic Growth and Productivity Paradox in Southeast Asia, Analyzed with Bayesian Methods.- Big Data Analytics for Financial Decisions of Companies a Systematic Literature Review.&lt;/p&gt;

Master's Thesis from the year 2025 in the subject Leadership and Human Resources - Recruiting, grade: 1,2, University of Applied Sciences Dortmund, language: English, abstract: This master's thesis explores the role of artificial intelligence (AI) in modern recruitment processes with a particular focus on applicants' trust. As digitalization and AI increasingly transform the world of work, organizations are adopting AI-supported recruiting tools to enhance efficiency, standardization, and data-driven decision-making. At the same time, the use of AI in personnel selection raises important questions regarding transparency, fairness, and acceptance from the applicants' perspective.

The objective of this thesis is to examine how applicants perceive AI-assisted recruitment processes and which aspects are relevant for the development of trust in this context. To address this research objective, a qualitative research design was chosen. Semi-structured interviews were conducted with participants who had either experienced AI-supported recruitment processes or reflected on their expectations toward such processes.

The empirical data were analyzed using qualitative content analysis following Kuckartz' approach. This method allows for a systematic examination of subjective perceptions, attitudes, and evaluations, while combining theory-driven and data-driven coding. The analysis focuses on applicants' experiences with different forms of AI usage in recruitment, their expectations toward human and technological decision-making, and their assessment of AI-supported processes within the broader candidate journey.

By linking theoretical concepts of trust in technology with empirical insights from applicants, this thesis contributes to the growing body of literature on AI in recruiting. In addition, it provides a structured foundation for further academic research and offers valuable insights for organizations seeking to better understand applicant perspectives on AI-supported recruitment processes.

Artificial intelligence in the recruitment process. How can companies gain applicants' trust?

How the rise of AI agents--and other forms of autonomous intelligence--will transform every aspect of how companies create value and compete.Companies have long operated with a basic assumption: intelligence is scarce. Talent is limited, expertise is expensive, and good judgment is hard to scale. But that world is ending.AI agents are bringing a new form of labor into the enterprise--one that can work autonomously, learn continuously, and scale instantly. Their embodied counterparts, from drones to humanoid robots, are doing the same in the physical world. Together, these systems are introducing a new economic reality: cognition is becoming cheap, elastic, and abundant.In Abundant Intelligence, Deloitte's Nitin Mittal and futurist Mike Walsh show what happens when intelligence becomes cheap and widely available. Drawing on inside access to the people leading AI transformations at the world's most powerful companies, they uncover how this shift is challenging every assumption about strategy, productivity, and leadership, and what organizations must do now to stay ahead.As abundance becomes the new normal, the leader's job shifts from collecting intelligence to directing it. Those who learn to harness this expanding workforce of digital labor will unlock new levels of speed, creativity, and advantage. For everyone else, the gap will widen fast.

How Digital Labor Will Rewrite the Rules of Business

Abundant Intelligence

A Comprehensive Introduction

Financial Technology

Gen AI is changing the way you work. So why is your team stuck in neutral?The adoption of generative AI is now widespread, yet it is still typically used on an individual basis: one person, one screen, one task. Meanwhile, the most important work in organizations happens in teams. The transformative potential of enhancing teamwork with gen AI is too big to ignore; fortunately, you can make AI-enabled collaboration real right now and see immediate results.The HBR Guide to Generative AI for Teams is packed with practical tips, prompts, and case studies to elevate team-based work. Whether you're a team leader, manage AI transformation initiatives, or facilitate group work of any kind, you'll learn how to: <ul><li>Bring gen AI into any meeting, workshop, or session</li><li>Run better brainstorms, business reviews, and retrospectives</li><li>Leverage gen AI as a team member, not just a notetaker</li><li>Use your team's collective judgment to avoid pitfalls</li><li>Reach team outcomes that were impossible before gen AI</li><li>Establish a new "humans+AI" way of working in teams</li></ul>Arm yourself with the advice you need to succeed on the job, with the most trusted brand in business. Packed with how-to essentials from leading experts, the HBR Guides provide smart answers to your most pressing work challenges.

HBR Guide to Generative AI for Teams

Accelerating Innovation in the Age of Artificial Intelligence

SuperCreativity

New Information Communication Technologies in the Digital Era

AI Economics: Growth, Organization, and Society in the Age of Intelligence is a comprehensive exploration of how artificial intelligence is not merely a technological tool but a civilization-level paradigm shift that rebuilds business and growth paradigms from the ground up.The central thesis of the book is the collapse of intelligence costs. The author argues that human history has seen three decisive cost leaps: the collapse of physical costs via the steam engine, the collapse of information costs via the internet, and now the collapse of intelligence costs via AI.

Growth, Organization, and Society in the Age of Intelligence

Artificial Intelligence Economics

edition suhrkamp

Was kommt danach?

Liberale Demokratie ohne Zukunft

Platform Supply Chains in the AI Era

Risk Management

Platform Supply Chains 5

The accelerating global demand for sustainable solutions has catalyzed the integration of emerging technologies with sustainability-driven innovations. This book explores the intersection of technology, engineering, and environmental responsibility through six critical themes: Artificial Intelligence and Machine Learning for Sustainability, Cloud Computing Technologies, Sustainable Energy Technologies, Sustainable Materials and the Built Environment, Sustainable Actions, and Innovative Engineering and Technology.Artificial intelligence and machine learning play a pivotal role in optimizing resource management and enabling low-carbon decision-making, while cloud computing technologies provide scalable platforms for collaboration and innovation. Sustainable energy technologies such as solar, wind, and bioenergy are examined as vital pathways toward clean power generation. The discussion extends to sustainable materials and the built environment, emphasizing eco-friendly design and circular economy principles. The book also highlights sustainable actions driven by policy, behavioral change, and community engagement. Together, these domains represent a multidisciplinary pathway toward achieving global sustainability goals, fostering a balance between technological advancement and ecological preservation.This book is a key resource for leaders, academia, policymakers, professionals, and researchers to advance sustainable development through science, technology, and engineering. It provides valuable insights for integrating AI, renewable energy, and sustainable engineering into practical applications for a greener future.

Emerging Frontiers in Sustainable Energy, Smart Systems, and Green Technology

An acclaimed New York Times Magazine writer brings us into the world of the controversial technology firm Palantir and its very colorful and outspoken CEO, Alex Karp, tracing the ascent of Big Data, the rise of surveillance technology, and the shifting global balance of power in the 21st century. Palantir builds data integration software: its technology ingests vast quantities of information and quickly identifies patterns, trends, and connections that might elude the human eye. Founded in 2003 to help the US government in the war on terrorism—an early investor was the CIA—Palantir is now a $400 billion global colossus whose software is used by major intelligence services (including the Mossad), the US military, dozens of federal agencies, and corporate giants like Airbus and BP. From AI to counterterrorism to climate change to immigration to financial fraud to the future of warfare, the company is at the nexus of the most critical issues of the twenty-first century. Its CEO, Alex Karp, is a distinctive figure on the global business scene. A biracial Jew who is also severely dyslexic, Karp has built Palantir into a tech giant despite having no background in either business or computer science. Instead, he’s a trained philosopher who has become known for his strongly held views on a range of issues and for his willingness to grapple with the moral and ethical implications of Palantir’s work. Those questions have taken on added urgency during the Trump era, which has also brought attention to the political activism of Karp’s close friend and Palantir cofounder Peter Thiel. In The Philosopher in the Valley, journalist Michael Steinberger explores the world of Alex Karp, Palantir, and the future that they are leading us toward. It is an urgent and illuminating work about one of Silicon Valley’s most secretive and powerful companies, whose technology is at the leading edge of the surveillance state.

Alex Karp, Palantir, and the Rise of the Surveillance State

The Philosopher in the Valley

Intelligent Urban Infrastructure: Smart Solutions for Sustainable Cities explores how emerging digital technologies are reshaping the design, management, and sustainability of modern cities. This comprehensive volume examines the integration of Artificial Intelligence (AI), Internet of Things (IoT), data analytics, and intelligent automation into critical urban systems such as transportation, energy, water management, healthcare, and public safety. It presents a forward-looking perspective on how infrastructure can evolve to become more adaptive, resilient, and environmentally responsible. The book highlights practical frameworks and technology-driven content that demonstrate measurable improvements in efficiency, cost optimization, and environmental performance. Designed for researchers, postgraduate students, urban planners, engineers, policymakers, and industry professionals, this book serves as a valuable reference for those seeking to understand and implement intelligent infrastructure solutions that enable smarter, greener, and more liveable cities worldwide.

Smart Solutions for Sustainable Cities

Intelligent Urban Infrastructure

Data Science in Finance and Accounting

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