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Integrating AI for Sustainable Disaster
Management

Integrating AI for Sustainable Disaster Management

Building Resilience and Preventing Catastrophes

Preface xvii 1 Introduction to Sustainable Development and Disaster Management 1 Rajasekaran Thangaraj, Palanichamy Naveen, Maheswar R., Mohanasundaram K., Arivazhagan S. and Kolla Bhanu Prakash 1.1 Introduction 2 1.1.1 Overview of Sustainable Development 2 1.1.1.1 Core Concepts of Sustainable Development 2 1.1.1.2 Historical Context of Sustainable Development 3 1.1.1.3 Principles of Sustainable Development 3 1.1.1.4 Challenges and Opportunities in Achieving Sustainable Development 4 1.1.2 Importance of Disaster Management 5 1.1.2.1 Definition and Scope of Disaster Management 5 1.1.2.2 Phases of Disaster Management 6 1.1.2.3 Types of Disasters 6 1.1.2.4 Challenges in Disaster Management 6 1.1.2.5 Importance of Effective Disaster Management 7 1.1.2.6 Case Studies of Disaster Management 8 1.1.3 Intersection of AI, Sustainable Development, and Disaster Management 9 1.2 Sustainable Development 9 1.2.1 Definition and Principles 9 1.2.2 Historical Context and Evolution 9 1.2.3 Goals and Global Initiatives (SDGs) 10 1.3 Disaster Management 10 1.3.1 Definition and Types of Disasters 10 1.3.2 Phases of Disaster Management 10 1.3.3 Challenges in Traditional Disaster Management Approaches 11 1.4 Role of AI in Sustainable Development 12 1.4.1 AI Technologies and their Applications 12 1.4.2 Case Studies of AI in Sustainable Development 12 1.5 Role of AI in Disaster Management 15 1.5.1 AI Technologies in Disaster Prediction and Early Warning 15 1.5.2 AI in Disaster Response and Recovery 15 1.5.3 Case Studies of AI in Disaster Management 16 1.6 Integration of AI in Sustainable Disaster Management 17 1.6.1 Benefits of AI Integration 17 1.6.2 Framework for AI Integration 18 1.6.2.1 Identifying Key Areas for AI Application 18 1.6.2.2 Ensuring Data Accessibility and Quality 18 1.6.2.3 Fostering Collaboration Among Stakeholders 18 1.6.2.4 Addressing Ethical Considerations 19 1.6.2.5 Ensuring Transparency 19 1.6.3 Challenges and Ethical Considerations 19 1.7 Conclusion 21 References 22 2 Earthquake Risk Assessment Using Artificial Intelligence - A Review on Traditional Methods and Artificial Intelligence- Based Methods 25 Jeba Wincy Deborah. W., Karishma. R., D. Pamela, Joses Jenish Smart, Shajin Prince and Bini. D. Introduction to Earthquake Risk Assessment 26 Understanding Seismic Hazards 27 Data Source of Earthquake Risk Assessment 27 Scenario of Earthquake Incidents of the World 28 Scenario of Earthquake Incidents of India 29 Brief Overview of Earthquake Incidents in India 29 Traditional Methods Used in Earthquake Risk Assessment and Predictions: Historical Data Analysis 33 Seismic Hazard Mapping 34 Ground Motion Prediction 35 Fault Rupture Hazard Analysis 36 Site-Specific Studies 37 Building Vulnerability Assessment 37 Organizations for Earthquake Risk Assessment and Predictions 42 Earthquake Risk Assessment Using Artificial Intelligence 43 Prediction of Earthquake Using AI 44 Algorithms Used for Earthquake Risk Assessment and Predictions: Deep Learning Algorithms 45 Machine Learning Algorithms 45 Methods for Earthquake Risk Assessment and Prediction Using AI 46 Pattern Recognition in Seismic Data 46 Anomaly Detection 47 Earthquake Forecasting Model 47 Data Fusion and Integration 48 Damage and Impact Assessment 49 Real-Time Monitoring 50 Early Warning Systems 51 Risk Mitigation 52 Resilience Planning 52 Predictive Modeling for Earthquake Forecasting Using AI 54 Integration of AI Techniques in Seismic Hazard Analysis 55 Construction Practices and Urban Planning for Earthquake Assessment Using AI 56 Future Scope of Earthquake Risk Assessment and Prediction Using AI 57 Conclusion 58 References 59 3 AI Applications in Earthquake Resistance Using Change in Structural Design 61 E. Nirmala, M. Suresh and Sankar Muthu Paramasivam 3.1 Introduction 62 3.2 Review of Literature 63 3.3 Proposed Techniques 64 3.3.1 Different Techniques Used in Structural Design to Reduce Risk in Posterior Earthquakes 64 3.3.2 Earthquake Prediction Using ANN 67 3.3.3 AI-Neural Network-Based Earthquake Prediction 67 3.3.4 AI-Based Dynamic Interpretation Network (DIN)- Multilayer Propagation Algorithm for Earthquake Prediction 68 3.4 AI- and ML-Based Techniques 70 3.4.1 Earthquakes of Smaller Size Can Predict Large-Size Earthquakes Using Substance of AI Machine Learning Algorithms 70 3.4.2 AI-Assisted Simulation-Driven Earthquake-Resistant Design Framework: Taking a Strong Back System as an Example 71 3.4.3 Guidelines for Architectural Design Changes to Predict from Earthquake 73 3.4.4 Seismic Advancement of Prevailing Masonry Structures 73 3.5 Conclusion and Future Work 74 Bibliography 75 4 Automatic Detection of Tropical Cyclones from Satellite Images Using YOLO Models 79 Rajasekaran Thangaraj, Pandiyan P., Palanichamy Naveen, Balasubramaniam Vadivel, P. Prakash and S. Manoj Kumar 4.1 Introduction 80 4.2 Related Works 82 4.3 Dataset Description 83 4.3.1 Dataset Collection 83 4.3.2 Dataset Preprocessing 83 4.4 Methodology 84 4.4.1 Yolo 84 4.4.2 YOLOv 3 84 4.4.3 Tiny-YOLOv 4 85 4.4.4 YOLOv 5 87 4.5 Model Evaluation Indicators 88 4.6 Experimental Results 89 4.7 Discussion 93 4.8 Conclusion 94 References 95 5 Intelligent Transportation Systems in Cyclone-Prone Areas: A Study and Future Perspectives 99 Geetha S. K., Kiruthika J. K., Sathya S., Srisathya K. B., Rajasekaran Thangaraj and R. Devi Priya 5.1 Introduction 100 5.2 Importance of Intelligent Transportation Systems in Cyclone Resilience 101 5.3 Early Warning Systems 103 5.4 Applications of Unmanned Aerial Vehicles and Robots in Disaster Management 106 5.5 Emerging Technologies and Future Trends in ITSs for Cyclone-Prone Areas 108 5.6 Optimizing Mobility: Advanced Approaches to Traffic Management and Control 111 5.7 Conclusion 117 References 117 6 AI-Enhanced Risk Assessment and Mitigation for Mass Movements 121 G. Anusha, V. Sathish Kumar, U. Johnson Alengaram, S. Nagamani and N. Srimathi 6.1 Introduction 122 6.2 Understanding Mass Movements 123 6.3 Traditional Risk Assessment and Mitigation Methods 124 6.4 The Role of AI in Risk Assessment 125 6.5 AI-Enhanced Mitigation Strategies 127 6.6 Challenges and Ethical Considerations 129 6.7 Future Trends and Innovations in AI-Enhanced Mass Movement Management 130 6.8 Case Studies in AI-Enhanced Mass Movement Management 132 6.9 Conclusions 134 References 135 7 Distributed AI Systems for Disaster Response and Recovery 137 Ravikumar S., Eugene Berna I., Vijay K., J. Jeyalakshmi and Eashaan Manohar 7.1 Introduction 138 7.2 Technology Applied in Critical Cases 141 7.2.1 Disaster Management Architecture 143 7.2.2 Proposed Framework 144 7.2.3 Disaster Management Ontology 145 7.3 Approach to Disaster Relief That is Enabled by Information and Communication Technology 145 7.4 ml and Deep Learning Methods: An Overview 146 7.4.1 Convolutional Neural Network 147 7.4.2 Lstm 148 7.4.3 Support Vector Machine 148 7.4.4 ML/DL Methods for Disaster and Hazard Prediction 148 7.4.5 ML/DL Methods for Risk and Vulnerability Assessment 149 7.4.6 ML/DL Methods for Disaster Detection 150 7.4.7 ML/DL Methods for Disaster Monitoring 150 7.4.8 ML/DL Methods for Damage Assessment 150 7.5 Phases of Disaster Management 151 7.5.1 Prediction 151 7.5.2 Detection 152 7.5.3 Response 152 7.5.4 Recovery 152 7.5.5 Before Disaster 152 7.5.5.1 Risk Assessment 152 7.5.5.2 Mitigation 153 7.5.5.3 Prevention 153 7.5.5.4 Prediction 153 7.5.5.5 Detection 153 7.5.6 During Disaster 153 7.5.6.1 Preparation 154 7.5.6.2 Management 154 7.5.6.3 Response 154 7.5.7 After Disaster 154 7.5.7.1 Recovery 154 7.5.7.2 Monitoring 154 7.5.7.3 Lessons Learned 155 7.6 Disaster Management and Disaster Resilience 155 7.7 Applications of AI for Disaster Management 156 7.8 AI Applications in Disaster Mitigation 156 7.9 Conclusion 157 References 158 8 Intelligent Reasoning and Decision¿Making in Disaster Scenarios 163 Sreenivasa Chakravarthi Sangapu, Sreenija Reddy D., Likitha D. and Sountharrajan S. 8.1 Introduction 164 8.2 Types of Natural Disasters 165 8.3 Impact of Natural Disasters 167 8.4 Decision-Making in a Disaster Scenario 170 8.4.1 Disaster Prediction 171 8.4.2 Decision-Making in Analyzing the Impact of Disaster 171 8.4.3 Disaster Precautions and Measures 171 8.4.4 Benefits of Decision-Making in Disaster Scenario 172 8.4.5 Technology in Decision-Making Process of a Disaster 173 8.5 AI/Machine Learning in Decision-Making of Disaster Scenario 174 8.5.1 AI/ML in Predisaster Stage 175 8.5.2 AI/ML in During Disaster Stage 176 8.5.3 AI/ML in Postdisaster Stage 178 8.6 AI Methods for Disaster Prediction 179 8.6.1 Cyclone 179 8.6.2 Drought 180 8.6.3 Earthquake 184 8.6.4 Floods 189 8.6.5 Landslides 192 8.7 AI Methods to Analyze the Impact of Disasters 195 8.7.1 Cyclone 196 8.7.2 Drought 198 8.7.3 Earthquake 201 8.7.4 Floods 204 8.7.5 Landslide 205 8.8 AI/ML Methods in Providing Precautionary Measures 210 8.9 Intelligent Reasoning 214 8.10 Conclusion 219 References 220 9 AI Applications in Real-Time Intelligent Automation 229 M. Maragatharajan, L. Sathishkumar, G. Vishnuvarthanan and Jun li 9.1 Introduction 230 9.2 Related Works 233 9.3 Proposed Methods 235 9.3.1 Use of Drones in Disaster Management 236 9.3.1.1 Understanding Drone Technology 238 9.3.1.2 Components and Functionality 238 9.3.1.3 Types and Classifications 239 9.3.1.4 Applications 239 9.3.1.5 Challenges and Future Trends 239 9.3.1.6 Drone Applications in Earthquake Disaster Response 240 9.3.1.7 Rapid Damage Assessment 240 9.3.1.8 Search and Rescue Operations 240 9.3.1.9 Communication and Coordination 240 9.3.1.10 Environmental Monitoring and Mapping 241 9.3.2 Flood Disaster Management Using the Flood Detection Secure System 241 9.3.2.1 Terminologies in FDSS 243 9.3.2.2 The Process of FDSS 244 9.3.3 Flood Management Using AI and IoT 246 9.3.3.1 Architecture 247 9.4 Conclusion and Future Perspectives 248 References 248 10 Knowledge Management and Processing in Disaster Management 251 R. Jayaraghavi, L. S. Jayashree, Palanichamy Naveen and M. Saravanan 10.1 Introduction 252 10.1.1 Importance of Knowledge Management 252 10.1.2 Role of AI 253 10.2 Knowledge Management in Disaster Management 255 10.2.1 Data Collection 255 10.2.2 Information Processing 257 10.2.3 Knowledge Dissemination 259 10.2.4 Decision Support Systems 262 10.3 Integration of AI in Disaster Management 265 10.3.1 Machine Learning Applications 265 10.3.2 Natural Language Processing 265 10.3.3 Predictive Analytics 271 10.4 Challenges and Ethical Considerations 275 10.4.1 Data Privacy 275 10.4.2 Bias and Reliability 278 10.4.3 Resource Allocation 280 10.5 Future Prospects and Innovations 284 10.5.1 Technological Advances 284 10.5.2 Integration with Existing Systems 288 10.5.3 Global Collaboration 290 10.6 Conclusion 294 10.6.1 Summary of Key Points 294 10.6.2 Call to Action 296 10.6.3 Future Vision 298 References 298 11 Perception Technologies for Disaster Situations 301 Ganesh Nataraj, K. Mohanasundaram and S. Ramesh Babu 11.1 Introduction 302 11.2 Understanding Disaster Situations 303 11.3 Role of Perception Technologies 305 11.4 Categories of Perception Disaster Technologies 306 11.4.1 Remote Sensing and Imaging Technologies 306 11.4.2 Computer Vision and Image Analysis 307 11.4.3 Internet of Things (IoT) Sensors 307 11.4.4 Data Fusion and Integration 308 11.4.5 Human-Computer Interaction and Decision Support Systems 309 11.4.6 Ethical and Privacy Considerations 310 11.4.7 Future Directions and Challenges 311 11.5 Conclusion 311 References 312 12 Integration of AI and Software Engineering for Disaster Management: A Multimodal Disaster Identification Perspective 315 Mithrashree V., Sowmya V., Premjith B. and Jyothish Lal G. 12.1 Introduction 316 12.2 Related Works 318 12.3 Methodology 320 12.4 Experiments and Result Discussion 323 12.5 Conclusion 328 Bibliography 330 13 An Intelligent AI-Based Fault Detection Mechanism for Autonomous Vehicles with Blockchain Security 333 Indra Priyadharshini S., Thankaraja Raja Sree and Kanmani S. 13.1 Introduction 334 13.2 Evolution of Autonomous Vehicles 335 13.3 Role of AI in Autonomous Systems 336 13.3.1 Architecture Diagram 337 13.3.2 AI Algorithms for Fault Prediction and Recognition 340 13.3.2.1 Isolation Forest Algorithm 341 13.4 Challenges of Artificial Intelligence in Autonomous Systems 344 13.5 Blockchain Security Measures for Autonomous Vehicles 346 13.5.1 Secure Autonomous Vehicle Network Using Blockchain 348 13.6 List of Software/Tools, Design Techniques and Programming Languages for Autonomus Systems 349 13.6.1 Case Studies and Practical Implementations in an Autonomous System 351 13.6.2 Key Findings and Contributions 353 13.7 Conclusion 353 References 354 14 Industrial Experiences in Crop Cultivation Using AI for Disaster Management 357 Sagar Rohi, Ishaan Shrikant Kulkarni, Gagan Deep and Geetanjali Rathee 14.1 Introduction 358 14.1.1 AI in Agriculture 358 14.1.2 Contribution 359 14.2 Related Work 360 14.3 Proposed Framework 362 14.3.1 Construction of Knowledge Graph 363 14.4 Performance Analysis 364 14.4.1 Crop Query Dataset 364 14.4.2 Results Discussion 364 14.5 Conclusion 366 References 366 15 A Comprehensive Review on Robotics in Disaster Response and Recovery 369 J. Sarathkumar Sebastin, Sivaraman and V. K. Kuberaganapathi 15.1 Introduction 370 15.1.1 Role of Robotics in Disaster Response 370 15.1.2 Role of Robotics in Disaster Recovery 371 15.1.3 The Key Objectives of Reviewing Robotics in Disaster Response and Recovery 372 15.2 Disaster Response Robotics 372 15.2.1 Overview of Different Types of Disasters (Natural and Man-Made) 372 15.2.2 Robotics Technologies Used in Disaster Response 374 15.3 Robotics in Disaster Recovery 376 15.3.1 The Transition from the Response to the Recovery Phase in Disaster Management 376 15.3.2 The Role of Robotics in Postdisaster Recovery 377 15.3.3 Infrastructure Inspection and Assessment Using Drones and Ground Robots 379 15.3.4 Debris Clearance and Demolition with Robotic Assistance 380 15.3.5 Rehabilitation and Reconstruction Aided by Robotics in Construction 382 15.3.6 Psychological Support Through Robotic Companionship and Therapy 383 15.3.7 Review of Case Studies or Research Papers Demonstrating the Application and Impact of Robotics in Disaster Recovery Efforts 385 15.4 Future Directions 387 15.4.1 Exploration of Emerging Trends and Future Directions in Disaster Robotics Research 387 15.4.2 Recommendations for Future Research and Development Efforts to Maximize the Potential of Robotics in Disaster Response and Recovery 389 15.5 Conclusion 390 References 391 Index 393

Intelligent Manufacturing and Industrial Engineering

Smart Industries in the Gig Economy: Scope, Opportunities, and Challenges discusses topics from manufacturing to service sectors, from startups to established corporations, and from localized operations to global networks using the threads of Smart Industries and the Gig Economy to weave a tapestry of innovation and change.

Scope, Opportunities, and Challenges

Smart Industries in the Gig Economy

Schriften zum Wirtschafts- und Technikrecht

Der Einsatz von Künstlicher Intelligenz (KI) bietet durch Unterstützung oder Substitution menschlicher Tätigkeiten und Entscheidungen Effizienz- und Kostenvorteile, wird aber u.a. durch rechtliche Unsicherheit der Geschäftsleitung gehemmt. Die Arbeit mindert diese Unsicherheit, indem sie anhand des Aktienrechts Leitlinien für den unternehmensinternen KI-Einsatz entwickelt. Unter Beachtung besonderer KI-Risiken werden anhand der Dogmatik Kriterien herausgearbeitet, an denen sich der Vorstand orientieren kann. Aktienrechtliche Grundsätze für den KI-Einsatz bei tatsächlichen Aufgaben, Beratung, Entscheidungsvorbereitung oder beim Treffen von Entscheidungen werden konkretisiert. Die Beachtung dieser Anforderungen beugt einer Organhaftung vor.

Vorstandspflichten und -haftung beim Einsatz von Künstlicher Intelligenz

KI-Governance in der Aktiengesellschaft

Tokenisation is the new champion of digital transformation: a revolution that strikes at the heart of industry and commerce by elevating the humble ledger to global scale.While other technologies stole the headlines, tokenisation quietly and steadily got to work, becoming the engine room that is now powering a wave of innovation across sectors. It is driving out inefficiency, eliminating friction, mobilising data, and enabling distributed processes built on the principles of transparency, equitable access, and trust.From theory to practice, this clear and compelling guide explores the foundations and applications of tokenisation. Starting from such blockchain essentials as cryptographic keys, wallets and transactions, it moves into the truly transformational world of smart contracts, distributed databases and interoperability before analysing real-world applications in trade finance, healthcare, wealth management, and real estate.Wherever you look, tokenisation is turning bold ideas into operational reality. This isn't theory; it's infrastructure. And it's here.Whether you are a curious newcomer or a seasoned technologist, Tokenisation Applied looks beyond the hype to demonstrate where and why this technology matters.Part primer, part playbook, it is an essential roadmap to the Web3 future.

A Business Leader's Guide to Blockchain, Smart Contracts, and Unlocking Web3

Tokenisation Applied

This is an open access title available under the terms of a CC BY-NC-ND 4.0 International licence. It is free to read on the Oxford Academic platform and offered as a free PDF download from OUP and selected open access locations. In an era when economic, social, and geopolitical uncertainties are reshaping the world of management, Management Education and the Rise of Uncertainty of Global Business offers a timely, collective reflection on how business and management schools can prepare tomorrow's leaders. Drawing on insights from international experts, the book reimagines the internationalization of management education--not as a mere export of Western norms but as a catalyst for inclusion, peace, and mutual understanding. Showcasing innovative institutions and programmes across Asia, Africa, Europe, and Latin America, the book highlights models of 'inclusive internationalization' that prioritize diverse practices, co-created pedagogy, and contextualized knowledge. It also explores shifting student expectations: a search for meaning, a drive for social impact, and a readiness to address twenty-first-century challenges like climate change, inequality, and technology. Amid growing pressure to specialize, sometimes at the expense of a common educational foundation, this book champions a universal vision for management education--one that develops adaptable, critical, and responsible professionals for a rapidly changing world.

Management Education and the Rise of Uncertainty of Global Business

Mastery in the 21st-century digital economy demands a new approach. This book offers a groundbreaking guide for business leaders looking to navigate the complexities of this new era. Based on extensive research and proprietary tools like the Capability Profile and Leadership Scorecard, this book moves beyond outdated management techniques to provide a practical framework for success. It reveals how to identify your organization's dominant patterns - whether based on management style, growth stage, or industry - and then leverage that insight to overcome capability barriers that stifle growth and innovation. The book is not just a theoretical exploration; it is a hands-on resource filled with actionable business cases. Through 21 detailed examples from diverse industries like Financial Services, Healthcare, Technology, and Education, you will gain a deep understanding of what truly drives performance. The book's unique application of the "digital twin" concept to management provides a visual, data-driven representation of your organization, helping you to "see around corners" and make informed, low-risk decisions. By adopting this dynamic approach, you can master complexity, anticipate change, and unlock sustainable competitive advantage.

Business cases for the digital economy

Patterns of Mastery

Willkommen in der Zukunft der Künstlichen Intelligenz, in der „AI First“ das neue „Digital First“ ist und „AI Native“&nbsp;zu einer greifbaren Strategie für Unternehmen wird. AI Native beschreibt eine neue Generation von Unternehmen, in denen Künstliche Intelligenz nicht nur unterstützend wirkt, sondern eine zentrale Funktion einnimmt, sodass sie mit minimalem menschlichen Eingriff skalieren, Entscheidungen treffen und wachsen können.Dieses Buch erklärt, warum nicht jedes Unternehmen AI Native werden kann, wie jedoch alle von einer ganzheitlichen KI-Strategie im Sinne von AI First profitieren können. Aber wie finden Unternehmen den richtigen Weg? Tristan Post zeigt auf, wo die tatsächlichen Chancen für eine nachhaltige Transformation liegen und warnt vor möglichen Irrwegen.Er bietet einen klaren, praxisorientierten Fahrplan, der Ihnen hilft, eine KI-Vision zu entwickeln, relevante Anwendungsfälle zu identifizieren und tiefgreifende Veränderungen in Ihrer Organisation zu gestalten.Ob Sie ein etabliertes Traditionsunternehmen oder ein digitaler Vorreiter sind - dieses Buch zeigt Ihnen Schritt für Schritt, wie Sie KI strategisch einsetzen, mutig handeln&nbsp;und Ihre Organisation fit für die Zukunft machen.Über den AutorTristan Post
 ist AI-Stratege und Dozent mit Fokus auf die Entwicklung von KI-Lösungen für Start-ups und Unternehmen.
Er bietet Workshops zu Themen wie KI-Strategie und Projektmanagement an und berät Organisationen. Zudem engagiert er sich als Start-up-Berater und Investor und hat mit Institutionen wie dem GovTech Campus und Bitkom zusammengearbeitet.

Das Managementbuch für das KI-Zeitalter

AI Native

An original discussion of how to find exciting competitive opportunities by reexamining how you do business For decades, business leaders have chased advantage through efficiency, innovation, and scale. But a deeper truth has emerged: no company can thrive in a society that is failing. After World War II, Western democracies invested boldly in trust, fair capitalism, and education-three engines that unleashed prosperity across the free world.&nbsp; Today, those engines are seizing. Trust in institutions has collapsed. Economic fairness is eroding. Education-the foundation of innovation and progress-has become unaffordable and unequal. As democracy falters, the very marketplace that business depends on is destabilizing. The era of societal bankruptcy has arrived. Yet within this crisis lies extraordinary opportunity. In The Future of Competitive Advantage, bestselling author and business futurist Doug Stephens lays out an inspiring new blueprint for succeeding in an age of uncertainty. He reveals how radical trust, fairness in action, and collective intelligence are not soft ideals but hard strategies-the next generation of business superpowers. Stephens argues that by defending democracy, companies will secure their customers, empower their people, and strengthen their brands-creating a future where doing good is not a trade-off, but the ultimate competitive advantage. <ul> <li>A New Lens on Prosperity - Discover the powerful historical connection between trusted democracy, fair capitalism, and universal education-and how these forces once ignited the greatest era of shared prosperity in history.</li> <li>The Warning Signs - Uncover the economic, social, and political currents now eroding these foundations-and the hidden risks they pose to every business sector.</li> <li>The Strategic Opportunity - Learn why today's leaders who actively defend democracy will unlock the next great wave of competitive advantage.</li> <li>The Blueprint for Action - Follow a clear, step-by-step business plan for strengthening democracy while amplifying investor confidence, employee commitment, customer loyalty, and brand integrity.</li> </ul> The Future of Competitive Advantage is more than a book - it's a business plan to save your customers, your company the democracy your business depends on.

A Business Plan to Save Your Customers, Your Company, and Democracy

The Future of Competitive Advantage

Roadmap to Successful Digital Health Ecosystems: A Global Perspective, Second Edition, explores the transformative integration of digital health technologies to enhance healthcare delivery and patient outcomes. This book provides a comprehensive overview of the evolving landscape of digital health, focusing on next-generation systems and the role of artificial intelligence in creating efficient healthcare ecosystems. The revised content covers topics such as regional implementation experiences, workforce management, and precision healthcare. New chapters highlight advancements in digital health technologies, case studies from Jamaica and Africa, and strategies for addressing fragmentation in healthcare systems. The book emphasizes ethical AI use and proactive, integrated healthcare approaches. For the academic audience, this revision serves as an essential resource, compiling cutting-edge research and practical applications that inform best practices in digital health. It equips researchers, educators, and practitioners with the knowledge needed to navigate the complexities of digital health ecosystems and drive innovation in their fields.

A Global Perspective

Roadmap to Successful Digital Health Ecosystems

Build a culture that drives people and performance.Crafting Cultures is a comprehensive guide for business leaders who want to create meaningful, people-first organizations. Blending research-based insights with practical frameworks, it explores what it truly means to cultivate a thriving workplace culture--one where people feel valued, connected, and inspired to perform at their best. Bridging the gap between theory and real-world practice, this playbook offers actionable strategies, relatable stories, and proven tools to help leaders align their organization's intended culture with the one their people actually experience. As employees challenge traditional ideas of purpose, priorities, and loyalty, Crafting Cultures equips leaders to navigate this shift with confidence. It provides a roadmap for driving engagement, innovation, and well-being through a human-centered approach that transforms how organizations think, lead, and succeed.

People + Profit = Performance

The Human-Centric Leader

Build credibility and make a meaningful impact without chasing followers Valuable and Visible: Redefining Personal Branding By Leading With Impact Over Image&nbsp;offers a revolutionary, service-first approach to personal branding for professionals who want to share their expertise and help others without the self-promotion and vanity metrics of influencer culture. Created by Vanessa Errecarte, who teaches&nbsp;one of&nbsp;the only MBA-level personal branding courses&nbsp;in the United States, this book introduces the proven EPIC Framework that helps readers gain visibility and credibility by serving their audiences rather than chasing fame. The book guides readers through establishing their unique positioning, packaging their knowledge into frameworks and intellectual property, creating consistent and valuable social media content, and cultivating sustainable growth. Readers learn to stop the scroll with the AEIOU method, build websites they own, overcome vulnerability around video content, and implement a simple weekly routine that doesn't lead to burnout.&nbsp;&nbsp;Real success stories that come from professionals like an optometrist, an embryologist, a leadership coach, a reality TV contestant, and more demonstrate how the framework transforms careers across diverse fields. Readers will also discover: <ul> <li>The&nbsp;TRUTH framework and Fab Four question set&nbsp;that positions your expertise in a counterintuitive, novel way that captures attention and establishes authority with your target audience</li> <li>A recycled social strategy that prioritizes consistency and value over algorithm hacks, allowing busy professionals to maintain visibility in just a few hours per week</li> <li>The SERVE script for creating authentic video content that overcomes vulnerability and builds genuine connections without performance anxiety or self-promotion</li> <li>Practical exercises for building owned audiences through websites,&nbsp;text,&nbsp;and email lists rather than renting space on platforms controlled by others</li> <li>Strategic methods for measuring success through impact and professional opportunities rather than follower counts</li> </ul> Perfect for MBA students, graduate students,&nbsp;undergraduate students,&nbsp;academics, researchers, mid-career professionals seeking career advancement,&nbsp;entrepreneurs, leaders, and executives, Valuable and Visible offers an ethical, sustainable alternative to traditional personal branding that&nbsp;leads with impact over image. This book empowers specialized professionals to share breakthrough ideas and build meaningful professional credibility by helping others solve real problems.

Redefining Personal Branding by Leading with Impact Over Image

Valuable and Visible

New Information Communication Technologies in the Digital Era

Integrating AI for Sustainable Disaster Management

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