Pharanun ouanhlee (15 risultati)

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000. Ouanhlee, Pharanun (illustratore).

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000. Ouanhlee, Pharanun (illustratore).

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000. Ouanhlee, Pharanun (illustratore).

Taschenbuch. Condizione: Neu. Neuware - Artificial intelligence is transforming personalisation from a relatively simple exercise in customer segmentation into a sophisticated capability for predicting, adapting to, and potentially influencing individual behaviour.Behavioural AI Personalisation: Theory, Practice, and Responsible Deployment provides a comprehensive examination of this transformation. Bringing together artificial intelligence, behavioural economics, cognitive psychology, customer analytics, and choice architecture, the book explains how behavioural AI systems can convert data into insight, prediction, personalisation, and action.Across seventeen chapters, readers progress from the theoretical foundations of behavioural AI to its practical implementation. The book examines customer behaviour and data, recommendation architectures, predictive customer analytics, behavioural targeting, personalisation strategy, digital nudging, conversational AI, and omnichannel personalisation. It then addresses the critical questions surrounding ethical influence, privacy, regulation, industry applications, and the measurement of behavioural AI.A distinctive feature of the book is its treatment of responsibility as an integral part of AI personalisation rather than an afterthought. Commercial effectiveness is considered alongside autonomy, transparency, fairness, privacy, consumer welfare, governance, and trust.With international examples and particular attention to emerging-economy contexts, the book is designed for postgraduate students, academics, managers, strategists, analysts, product professionals, and practitioners seeking to understand both the opportunities and responsibilities created by AI-driven personalisation.The result is an integrated framework for understanding behavioural AI not simply as a technology, but as a managerial and organisational capability requiring the coordinated application of data, behavioural insight, artificial intelligence, strategy, ethics, governance, and measurement. Ouanhlee, Pharanun (illustratore). …

Paperback. Condizione: new. Paperback. Artificial intelligence does not create lasting organisational value through models alone. It depends on governed data, dependable infrastructure, disciplined delivery, responsible practice, and leadership capable of bringing them together.Data Governance, Infrastructure, and AI Project Leadership presents these elements as one integrated enterprise practice. Written for postgraduate students, researchers, managers, technology professionals, and organisational leaders, the textbook connects the strategic governance of data with the technical foundations of AI and the practical realities of leading AI initiatives.Across fifteen structured chapters, readers will examine: - the intellectual foundations and strategic purpose of data governance;- data operating models and the office of the chief data officer;- data quality, metadata, master-data management, privacy, and protection;- enterprise data architecture and the modern AI infrastructure stack;- cloud, edge, and hybrid deployment decisions;- MLOps and the operation of production AI systems;- AI project methods, delivery lifecycles, teams, and stakeholder engagement;- risk, regulatory compliance, ethics, and responsible AI;- AI centres of excellence, enterprise scaling, and value measurement.Composite opening scenarios place each chapter's concepts in realistic organisational settings. Thirty case studies connect the discussion to practice across industries and regions, while figures, tables, synthesis sections, and reflection and application questions support teaching, independent study, and professional development.Rather than treating governance, infrastructure, project delivery, and responsible AI as separate concerns, this textbook demonstrates why they must be designed and led as a coherent whole. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Ouanhlee, Pharanun (illustratore). …

Condizione: New. Print on Demand. Ouanhlee, Pharanun (illustratore).

Condizione: New. Print on Demand. Ouanhlee, Pharanun (illustratore).

Condizione: New. Print on Demand. Ouanhlee, Pharanun (illustratore).

Paperback. Condizione: new. Paperback. The strategic question survives the arrival of AI. Many of its answers do not.AI Strategy and Competitive Advantage is a postgraduate textbook for the leaders, analysts, and MBA and executive-education students who must think clearly about competition in an era when the cost of prediction is collapsing, industry boundaries are dissolving, and the tempo of strategic revision has shifted from the annual cycle toward something closer to continuous.Its premise is disciplined rather than breathless. The question strategy has always asked - why some firms outperform others over sustained periods, and how their leaders can deliberately produce that result - remains intact. What changes is the terrain on which it is answered. This book equips the reader to tell the difference between an AI capability that confers durable advantage and one that merely impresses, and to act on the distinction.Across seventeen chapters and seven thematic parts, the book builds a complete analytical apparatus and then shows it in use: The inherited architecture, re-examined - Porter's positioning school, the resource-based view, dynamic capabilities, blue-ocean thinking, disruptive innovation, and Rumelt's discipline of good strategy, each assessed for where it still holds and where it strains under AI-era conditions.The strategic resources that actually matter - a VRIO-grounded treatment of data, models, talent, and infrastructure, and the data-advantage paradox: why accumulating data does not, by itself, produce sustained advantage.Diagnosis and positioning - the AI Readiness Maturity Model, Porter's Five Forces extended to dissolving industry boundaries, and generic strategies reworked for a world of symmetric adoption.Capability, ecosystems, and execution - the build-buy-partner decision, the AI operating model, a phased implementation roadmap, the three-lines and five-domain governance apparatus, the AI capability stack, and a balanced-scorecard approach to measuring strategic impact.A capstone that asks the reader to assemble these elements into an integrative AI Strategy Document for an organisation of their own choosing.The book is deliberately global in its outlook. Its composite teaching scenarios are set in boardrooms and markets from Doha and Phnom Penh to Lagos, Nairobi, and Ulaanbaatar, treating emerging-economy strategy as central rather than peripheral. Every chapter closes with reflection questions, self-assessment exercises, key terms, and further reading, and the argument is illustrated throughout by twenty-nine purpose-built figures.For readers who want frameworks they can defend, apply, and build on - not slogans - this is a textbook written to be used. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Ouanhlee, Pharanun (illustratore).…

Condizione: New. Print on Demand. Ouanhlee, Pharanun (illustratore).

Condizione: New. Print on Demand. Ouanhlee, Pharanun (illustratore).

Paperback. Condizione: new. Paperback. Artificial intelligence does not create lasting organisational value through models alone. It depends on governed data, dependable infrastructure, disciplined delivery, responsible practice, and leadership capable of bringing them together.Data Governance, Infrastructure, and AI Project Leadership presents these elements as one integrated enterprise practice. Written for postgraduate students, researchers, managers, technology professionals, and organisational leaders, the textbook connects the strategic governance of data with the technical foundations of AI and the practical realities of leading AI initiatives.Across fifteen structured chapters, readers will examine: - the intellectual foundations and strategic purpose of data governance;- data operating models and the office of the chief data officer;- data quality, metadata, master-data management, privacy, and protection;- enterprise data architecture and the modern AI infrastructure stack;- cloud, edge, and hybrid deployment decisions;- MLOps and the operation of production AI systems;- AI project methods, delivery lifecycles, teams, and stakeholder engagement;- risk, regulatory compliance, ethics, and responsible AI;- AI centres of excellence, enterprise scaling, and value measurement.Composite opening scenarios place each chapter's concepts in realistic organisational settings. Thirty case studies connect the discussion to practice across industries and regions, while figures, tables, synthesis sections, and reflection and application questions support teaching, independent study, and professional development.Rather than treating governance, infrastructure, project delivery, and responsible AI as separate concerns, this textbook demonstrates why they must be designed and led as a coherent whole. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Ouanhlee, Pharanun (illustratore). …

Paperback. Condizione: new. Paperback. Artificial intelligence is transforming personalisation from a relatively simple exercise in customer segmentation into a sophisticated capability for predicting, adapting to, and potentially influencing individual behaviour.Behavioural AI Personalisation: Theory, Practice, and Responsible Deployment provides a comprehensive examination of this transformation. Bringing together artificial intelligence, behavioural economics, cognitive psychology, customer analytics, and choice architecture, the book explains how behavioural AI systems can convert data into insight, prediction, personalisation, and action.Across seventeen chapters, readers progress from the theoretical foundations of behavioural AI to its practical implementation. The book examines customer behaviour and data, recommendation architectures, predictive customer analytics, behavioural targeting, personalisation strategy, digital nudging, conversational AI, and omnichannel personalisation. It then addresses the critical questions surrounding ethical influence, privacy, regulation, industry applications, and the measurement of behavioural AI.A distinctive feature of the book is its treatment of responsibility as an integral part of AI personalisation rather than an afterthought. Commercial effectiveness is considered alongside autonomy, transparency, fairness, privacy, consumer welfare, governance, and trust.With international examples and particular attention to emerging-economy contexts, the book is designed for postgraduate students, academics, managers, strategists, analysts, product professionals, and practitioners seeking to understand both the opportunities and responsibilities created by AI-driven personalisation.The result is an integrated framework for understanding behavioural AI not simply as a technology, but as a managerial and organisational capability requiring the coordinated application of data, behavioural insight, artificial intelligence, strategy, ethics, governance, and measurement. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Ouanhlee, Pharanun (illustratore). …

Paperback. Condizione: new. Paperback. Computer science is no longer defined by isolated advances in hardware, software, algorithms, or artificial intelligence. Modern computing emerges from the interaction of algorithms, data, computing infrastructure, networks, intelligent models, physical systems, human users, organisations, and governance.Modern Computer Science: Foundations, Artificial Intelligence, Emerging Technologies, Responsible Computing, and the Future of Computing provides a comprehensive graduate-level examination of this changing discipline.Organised into eight parts and twenty-seven chapters, the book begins with the intellectual and technical foundations of computer science before examining the technologies reshaping contemporary computing. Topics include the evolution of computing, data science, theory of computation and computational complexity, algorithms and data structures, programming languages and compilers, operating systems, databases, networks, machine learning and deep learning, foundation models and generative AI, AI agents, distributed computing, high-performance and quantum computing, big data, cybersecurity, blockchain, IoT and advanced connectivity.The discussion then extends beyond technical capability to the wider challenges facing modern computing, including AI ethics and governance, sustainability, human-AI collaboration, robotics, embedded and high-integrity systems, human-computer interaction, generative AI in software engineering, open-source ecosystems, global technology competition, and the future of computer science.Rather than treating emerging technologies as replacements for classical computer science, the book demonstrates how they extend, recombine, and expose the limits of established computing principles. Its systems-oriented perspective encourages readers to examine interactions among hardware, software, data, networks, AI, interfaces, organisations, and institutions.The textbook also addresses a fundamental reality of contemporary computing: technical capability alone does not determine whether a system will succeed. Reliability, cybersecurity, privacy, governance, sustainability, human oversight, infrastructure, and institutional context increasingly influence what systems can be built and how they can responsibly be deployed.Designed principally for postgraduate students, including MSc students in Data Science and Artificial Intelligence, the book is also suitable for computer science and AI students, computing professionals, researchers, educators, technology managers, and readers from adjacent disciplines seeking a rigorous understanding of the modern computing landscape.Each chapter combines conceptual foundations with technical analysis, current evidence, international cases, critical evaluation, future directions, chapter summaries, key terms, discussion questions, and MSc-level exercises and research activities.Modern Computer Science is not simply a catalogue of current technologies. Its purpose is to develop the analytical ability required to understand how computing systems work, how technologies converge, how trade-offs should be evaluated, and how computer science may evolve in an increasingly intelligent, connected, and computationally intensive world. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Ouanhlee, Pharanun (illustratore).…

Paperback. Condizione: new. Paperback. The strategic question survives the arrival of AI. Many of its answers do not.AI Strategy and Competitive Advantage is a postgraduate textbook for the leaders, analysts, and MBA and executive-education students who must think clearly about competition in an era when the cost of prediction is collapsing, industry boundaries are dissolving, and the tempo of strategic revision has shifted from the annual cycle toward something closer to continuous.Its premise is disciplined rather than breathless. The question strategy has always asked - why some firms outperform others over sustained periods, and how their leaders can deliberately produce that result - remains intact. What changes is the terrain on which it is answered. This book equips the reader to tell the difference between an AI capability that confers durable advantage and one that merely impresses, and to act on the distinction.Across seventeen chapters and seven thematic parts, the book builds a complete analytical apparatus and then shows it in use: The inherited architecture, re-examined - Porter's positioning school, the resource-based view, dynamic capabilities, blue-ocean thinking, disruptive innovation, and Rumelt's discipline of good strategy, each assessed for where it still holds and where it strains under AI-era conditions.The strategic resources that actually matter - a VRIO-grounded treatment of data, models, talent, and infrastructure, and the data-advantage paradox: why accumulating data does not, by itself, produce sustained advantage.Diagnosis and positioning - the AI Readiness Maturity Model, Porter's Five Forces extended to dissolving industry boundaries, and generic strategies reworked for a world of symmetric adoption.Capability, ecosystems, and execution - the build-buy-partner decision, the AI operating model, a phased implementation roadmap, the three-lines and five-domain governance apparatus, the AI capability stack, and a balanced-scorecard approach to measuring strategic impact.A capstone that asks the reader to assemble these elements into an integrative AI Strategy Document for an organisation of their own choosing.The book is deliberately global in its outlook. Its composite teaching scenarios are set in boardrooms and markets from Doha and Phnom Penh to Lagos, Nairobi, and Ulaanbaatar, treating emerging-economy strategy as central rather than peripheral. Every chapter closes with reflection questions, self-assessment exercises, key terms, and further reading, and the argument is illustrated throughout by twenty-nine purpose-built figures.For readers who want frameworks they can defend, apply, and build on - not slogans - this is a textbook written to be used. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Ouanhlee, Pharanun (illustratore).…