Download or read book Personalized Dynamic Pricing with Machine Learning written by Gah-Yi Ban and published by . This book was released on 2020 with total page 53 pages. Available in PDF, EPUB and Kindle. Book excerpt: We consider a seller who can dynamically adjust the price of a product at the individual customer level, by utilizing information about customers' characteristics encoded as a d-dimensional feature vector. We assume a personalized demand model, parameters of which depend on s out of the d features. The seller initially does not know the relationship between the customer features and the product demand, but learns this through sales observations over a selling horizon of T periods. We prove that the seller's expected regret, i.e., the revenue loss against a clairvoyant who knows the underlying demand relationship, is at least of order s √T under any admissible policy. We then design a near-optimal pricing policy for a “semi-clairvoyant” seller (who knows which s of the d features are in the demand model) that achieves an expected regret of order s √Tlog T. We extend this policy to a more realistic setting where the seller does not know the true demand predictors, and show that this policy has an expected regret of order s √T(log d+logT), which is also near-optimal. Finally, we test our theory on simulated data and on a data set from an online auto loan company in the United States. On both data sets, our experimentation-based pricing policy is superior to intuitive and/or widely-practiced customized pricing methods such as myopic pricing and segment-then- optimize policies. Furthermore, our policy improves upon the loan company's historical pricing decisions by 47% in expected revenue over a six-month period.
Download or read book A Primal dual Learning Algorithm for Personalized Dynamic Pricing with an Inventory Constraint written by Ningyuan Chen and published by . This book was released on 2020 with total page 41 pages. Available in PDF, EPUB and Kindle. Book excerpt: We consider the problem of a firm seeking to use personalized pricing to sell an exogenously given stock of a product over a finite selling horizon to different consumer types. We assume that the type of an arriving consumer can be observed but the demand function associated with each type is initially unknown. The firm sets personalized prices dynamically for each type and attempts to maximize the revenue over the season. We provide a learning algorithm that is near-optimal when the demand and capacity scale in proportion. The algorithm utilizes the primal-dual formulation of the problem and learns the dual optimal solution explicitly. It allows the algorithm to overcome the curse of dimensionality (the rate of regret is independent of the number of types) and sheds light on novel algorithmic designs for learning problems with resource constraints.
Download or read book Privacy Preserving Dynamic Personalized Pricing with Demand Learning written by Chen, Xi and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Behavioral Consequences of Dynamic Pricing written by David Prakash and published by BoD – Books on Demand. This book was released on 2022-08-19 with total page 155 pages. Available in PDF, EPUB and Kindle. Book excerpt: Digital technologies are driving the application of dynamic pricing. Today, this pricing strategy is used not only for perishable products such as flights or hotel rooms, but for almost any product or service category. With dynamic pricing, retailers frequently adjust their prices over time to respond to factors such as demand, their supply and that of competitors, or the time of sale. Additionally, dynamic pricing allows retailers to take advantage of a large share of consumers' willingness to pay while avoiding losses from unsold products. Ultimately, this can lead to an increase in revenue and profit. However, the application of dynamic pricing comes with great challenges. In addition to the technological implementation, companies have to take into account that dynamic pricing can cause complex and unintended behavioral consequences on the consumer side. The key objective of this dissertation is to provide a deeper understanding of the impact of dynamic pricing on consumer behavior. To this end, this dissertation presents insights from four perspectives. First, how reference prices as a critical component in purchase decisions are operationalized. Second, how customers search for products priced dynamically, differentiated by business and private customers, as well as by different devices used for the search. Third, whether and how dynamic pricing influences the impact of internal reference prices on purchase decisions. Finally, this dissertation demonstrates that consumers perceive price changes as personalized in different purchase contexts, leading to reduced perceptions of fairness and undesirable behavioral consequences.
Download or read book Algorithmic Pricing Based on Big Data A Critical Reflection written by Lukas Kern and published by . This book was released on 2020-08-21 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master's Thesis from the year 2020 in the subject Business economics - Customer Relationship Management, CRM, grade: 1,0, language: English, abstract: Setting the right product prices is crucial for companies and is part of their marketing mix and image. For instance, deviations from "optimal" sales prices can lead to considerable losses in revenue and margin. However, a huge amount of data affect the "optimal" price and the pricing process requires extensive manual resources. Advanced algorithms like machine learning might have the potential to overcome the aforementioned challenges with almost no manual interactions. Pricing algorithms constantly automate and optimize pricing decisions based on the available data. Besides positive one-time effects of price optimizations, algorithmic pricing enables companies to implement new pricing strategies like dynamic pricing, price personalization, and markdown pricing. This master thesis combines the results of a literature review and expert interviews to solve three questions: What is the research gap between the current state of the literature and business practice regarding the use of advanced algorithms based on big data for algorithmic pricing? What progress and insights have companies made in using algorithmic pricing? And how can algorithmic pricing be enhanced for future application? The master thesis starts by explaining the basic concepts of algorithmic pricing and relevant technologies. Therefore, the results and takeaways are useful for business managers without prior experience in this area. This master thesis then provides corporate decision makers with recommendations on what to consider for new pricing algorithms and on opportunities for future development of existing pricing algorithms.
Download or read book Innovative Technology at the Interface of Finance and Operations written by Volodymyr Babich and published by Springer Nature. This book was released on 2022-06-09 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines the challenges and opportunities arising from an assortment of technologies as they relate to Operations Management and Finance. It contains primers on operations, finance, and their interface. Innovative technologies and new business models enabled by those technologies are changing the practice and the theory of Operations Management and Finance, as well as their interface. These technologies and business models include Big Data and Analytics, Artificial Intelligence, Machine Learning, Blockchain, IoT, 3D printing, sharing platforms, crowdfunding, and crowdsourcing. The book will be an attractive choice for PhD-level courses and for self-study.
Download or read book The Elements of Joint Learning and Optimization in Operations Management written by Xi Chen and published by Springer Nature. This book was released on 2022-09-20 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines recent developments in Operations Management, and focuses on four major application areas: dynamic pricing, assortment optimization, supply chain and inventory management, and healthcare operations. Data-driven optimization in which real-time input of data is being used to simultaneously learn the (true) underlying model of a system and optimize its performance, is becoming increasingly important in the last few years, especially with the rise of Big Data.
Download or read book Personalized Pricing and Consumer Welfare written by Jean-Pierre Dubé and published by . This book was released on 2017 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We study the welfare implications of personalized pricing, an extreme form of third-degree price discrimination implemented with machine learning for a large, digital firm. Using data from a unique randomized controlled pricing field experiment we train a demand model and conduct inference about the effects of personalized pricing on firm and consumer surplus. In a second experiment, we validate our predictions in the field. The initial experiment reveals unexercised market power that allows the firm to raise its price optimally, generating a 55% increase in profits. Personalized pricing improves the firm's expected posterior profits by an additional 19%, relative to the optimized uniform price, and by 86%, relative to the firm's unoptimized status quo price. Turning to welfare effects on the demand side, total consumer surplus declines 23% under personalized pricing relative to uniform pricing, and 47% relative to the firm's unoptimized status quo price. However, over 60% of consumers benefit from lower prices under personalization and total welfare can increase under standard inequity-averse welfare functions. Simulations with our demand estimates reveal a non-monotonic relationship between the granularity of the segmentation data and the total consumer surplus under personalization. These findings indicate a need for caution in the current public policy debate regarding data privacy and personalized pricing insofar as some data restrictions may not per se improve consumer welfare.
Download or read book Revenue Management and Pricing Analytics written by Guillermo Gallego and published by Springer. This book was released on 2019-08-14 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: “There is no strategic investment that has a higher return than investing in good pricing, and the text by Gallego and Topaloghu provides the best technical treatment of pricing strategy and tactics available.” Preston McAfee, the J. Stanley Johnson Professor, California Institute of Technology and Chief Economist and Corp VP, Microsoft. “The book by Gallego and Topaloglu provides a fresh, up-to-date and in depth treatment of revenue management and pricing. It fills an important gap as it covers not only traditional revenue management topics also new and important topics such as revenue management under customer choice as well as pricing under competition and online learning. The book can be used for different audiences that range from advanced undergraduate students to masters and PhD students. It provides an in-depth treatment covering recent state of the art topics in an interesting and innovative way. I highly recommend it." Professor Georgia Perakis, the William F. Pounds Professor of Operations Research and Operations Management at the Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts. “This book is an important and timely addition to the pricing analytics literature by two authors who have made major contributions to the field. It covers traditional revenue management as well as assortment optimization and dynamic pricing. The comprehensive treatment of choice models in each application is particularly welcome. It is mathematically rigorous but accessible to students at the advanced undergraduate or graduate levels with a rich set of exercises at the end of each chapter. This book is highly recommended for Masters or PhD level courses on the topic and is a necessity for researchers with an interest in the field.” Robert L. Phillips, Director of Pricing Research at Amazon “At last, a serious and comprehensive treatment of modern revenue management and assortment optimization integrated with choice modeling. In this book, Gallego and Topaloglu provide the underlying model derivations together with a wide range of applications and examples; all of these facets will better equip students for handling real-world problems. For mathematically inclined researchers and practitioners, it will doubtless prove to be thought-provoking and an invaluable reference.” Richard Ratliff, Research Scientist at Sabre “This book, written by two of the leading researchers in the area, brings together in one place most of the recent research on revenue management and pricing analytics. New industries (ride sharing, cloud computing, restaurants) and new developments in the airline and hotel industries make this book very timely and relevant, and will serve as a critical reference for researchers.” Professor Kalyan Talluri, the Munjal Chair in Global Business and Operations, Imperial College, London, UK.
Download or read book Digital Pricing Strategy written by Stephan M. Liozu and published by Taylor & Francis. This book was released on 2023-06-27 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt: Digital Pricing Strategy provides a best-practice overview of how companies design, analyze, and execute digital pricing strategies. Bringing together insights from academic and professional experts globally, the text covers essential areas of the value and pricing of data, platform pricing, pricing of subscriptions and monetization of the global environment. Case studies, examples and interviews from leading organizations, including Zuora, Honeywell, Relayr, Alcatel Lucent, ABB, Thales, and General Electric, illustrate key concepts in practice. To aid student learning, chapter objectives, summaries, and key questions feature in every chapter, alongside PowerPoint slides and a test bank available online for lecturers. Comprehensive and applied in its approach, this text provides postgraduate, MBA, and Executive Education students with an understanding of the capabilities, processes, and tools that enable executives to effectively implement digital transformations and capture value from digital innovations.
Download or read book Web 3 0 written by Prabhat Kumar Srivastav and published by CRC Press. This book was released on 2024-08-01 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book underscores AI's transformative impact on reshaping physical, digital, and biological boundaries, converging with technologies like robotics, IoT, 3D printing, genetic engineering, and quantum computing—termed Web 3.0 Industrial Revolution. This global revolution integrates advanced production techniques beyond connected machines, extending into gene sequencing, nanotechnology, renewable energies, and quantum computing. The book's main goals include providing a collaborative platform for academia and industry researchers to share contributions and shape the future through knowledge exchange. Recognizing recent progress driven by increased computing power, it highlights the positive impact of digital technology—AI, IoT, AR/VR, Additive Manufacturing, CPS, cloud computing, and robotics—on industrial efficiency and quality. Revolutionary AI Fusion: AI revolutionizes by blending physical, digital, and biological boundaries through cutting-edge technologies like robotics, IoT, 3D printing, genetic engineering, and quantum computing. Global Manufacturing Cooperation: AI creates a collaborative landscape where virtual and physical systems flexibly cooperate on a global scale. AI's Diverse Impact: Beyond smart machines, AI drives breakthroughs in gene sequencing, nanotechnology, renewable energies, and quantum computing, distinguishing it from prior industrial revolutions. Progress and Digital Interface: Recent progress, powered by computing advancements, boosts industrial efficiency. The digital technology interface (AI, IoT, AR/VR, 3D Printing, CPS, CC, Robotics) significantly impacts industrial performance. In conclusion, AI spearheads a transformative revolution, redefining the boundaries of the physical, digital, and biological realms. The fusion of AI with Web 3.0 Industrial Revolution, integrating advanced production techniques and global manufacturing cooperation, surpassing past industrial shifts. The book aims to be a collaborative platform for academia and industry researchers, fostering knowledge exchange to shape the future. In AI-driven manufacturing within Web 3.0, a paradigm shift envisions maximum output with minimal resource use. Coupled with 'Digital Reality,' it transforms business practices, consumer behaviour, and employment dynamics, redistributing wealth toward innovation and technology.
Download or read book Artificial Intelligence and Machine Learning in the Travel Industry written by Ben Vinod and published by Springer Nature. This book was released on 2023-05-26 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past decade, Artificial Intelligence has proved invaluable in a range of industry verticals such as automotive and assembly, life sciences, retail, oil and gas, and travel. The leading sectors adopting AI rapidly are Financial Services, Automotive and Assembly, High Tech and Telecommunications. Travel has been slow in adoption, but the opportunity for generating incremental value by leveraging AI to augment traditional analytics driven solutions is extremely high. The contributions in this book, originally published as a special issue for the Journal of Revenue and Pricing Management, showcase the breadth and scope of the technological advances that have the potential to transform the travel experience, as well as the individuals who are already putting them into practice.
Download or read book Personalized Machine Learning written by Julian McAuley and published by Cambridge University Press. This book was released on 2022-02-03 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Every day we interact with machine learning systems offering individualized predictions for our entertainment, social connections, purchases, or health. These involve several modalities of data, from sequences of clicks to text, images, and social interactions. This book introduces common principles and methods that underpin the design of personalized predictive models for a variety of settings and modalities. The book begins by revising 'traditional' machine learning models, focusing on adapting them to settings involving user data, then presents techniques based on advanced principles such as matrix factorization, deep learning, and generative modeling, and concludes with a detailed study of the consequences and risks of deploying personalized predictive systems. A series of case studies in domains ranging from e-commerce to health plus hands-on projects and code examples will give readers understanding and experience with large-scale real-world datasets and the ability to design models and systems for a wide range of applications.
Download or read book Leveraging AI for Effective Digital Relationship Marketing written by Santos, José Duarte and published by IGI Global. This book was released on 2024-10-11 with total page 634 pages. Available in PDF, EPUB and Kindle. Book excerpt: Todays businesses face the pressing challenge of how to effectively engage and build lasting relationships with customers in an increasingly crowded and competitive online space. Traditional marketing tactics are no longer sufficient to capture the attention and loyalty of modern consumers who demand personalized experiences and sustainable practices from the brands they support. This shifting paradigm necessitates innovative solutions that leverage cutting-edge technologies to enhance customer engagement and foster meaningful connections. Leveraging AI for Effective Digital Relationship Marketing addresses this critical dilemma by exploring the transformative potential of artificial intelligence (AI) in revolutionizing customer relationships. By harnessing the power of AI-driven strategies, businesses can gain deeper insights into individual customer behaviors and preferences, enabling them to deliver personalized interactions and anticipate customer needs with unparalleled accuracy. Through the implementation of AI-powered solutions, companies can navigate the complexities of digital marketing with confidence, positioning themselves as leaders in building sustainable and mutually beneficial relationships with their customers.
Download or read book AI Powered Productivity written by Dr. Asma Asfour and published by Asma Asfour. This book was released on 2024-07-29 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book, "AI-Powered Productivity," aims to provide a guide to understanding, utilizing AI and generative tools in various professional settings. The primary purpose of this book is to offer readers a deep dive into the concepts, tools, and practices that define the current AI landscape. From foundational principles to advanced applications, this book is structured to cater to both beginners and professionals looking to enhance their knowledge and skills in AI. This book is divided into nine chapters, each focusing on a specific aspect of AI and its practical applications: Chapter 1 introduces the basic concepts of AI, its impact on various sectors, and key factors driving its rapid advancement, along with an overview of generative AI tools. Chapter 2 delves into large language models like ChatGPT, Google Gemini, Claude, Microsoft's Turing NLG, and Facebook's BlenderBot, exploring their integration with multimodal technologies and their effects on professional productivity. Chapter 3 offers a practical guide to mastering LLM prompting and customization, including tutorials on crafting effective prompts and advanced techniques, as well as real-world examples of AI applications. Chapter 4 examines how AI can enhance individual productivity, focusing on professional and personal benefits, ethical use, and future trends. Chapter 5 addresses data-driven decision- making, covering data analysis techniques, AI in trend identification, consumer behavior analysis, strategic planning, and product development. Chapter 6 discusses strategic and ethical considerations of AI, including AI feasibility, tool selection, multimodal workflows, and best practices for ethical AI development and deployment. Chapter 7 highlights the role of AI in transforming training and professional development, covering structured training programs, continuous learning initiatives, and fostering a culture of innovation and experimentation. Chapter 8 provides a guide to successfully implementing AI in organizations, discussing team composition, collaborative approaches, iterative development processes, and strategic alignment for AI initiatives. Finally, Chapter 9 looks ahead to the future of work, preparing readers for the AI revolution by addressing training and education, career paths, common fears, and future trends in the workforce. The primary audience for the book is professionals seeking to enhance productivity and organizations or businesses. For professionals, the book targets individuals from various industries, reflecting its aim to reach a broad audience across different professional fields. It is designed for employees at all levels, offering valuable insights to both newcomers to AI and seasoned professionals. Covering a range of topics from foundational concepts to advanced applications, the book is particularly relevant for those interested in improving efficiency, with a strong emphasis on practical applications and productivity tools to optimize work processes. For organizations and businesses, the book serves as a valuable resource for decision-makers and managers, especially with chapters on data-driven decision-making, strategic considerations, and AI implementation. HR and training professionals will find the focus on AI in training and development beneficial for talent management, while IT and technology teams will appreciate the information on AI tools and concepts.
Download or read book The Art of Structuring written by Katrin Bergener and published by Springer. This book was released on 2019-01-25 with total page 535 pages. Available in PDF, EPUB and Kindle. Book excerpt: Structuring, or, as it is referred to in the title of this book, the art of structuring, is one of the core elements in the discipline of Information Systems. While the world is becoming increasingly complex, and a growing number of disciplines are evolving to help make it a better place, structure is what is needed in order to understand and combine the various perspectives and approaches involved. Structure is the essential component that allows us to bridge the gaps between these different worlds, and offers a medium for communication and exchange. The contributions in this book build these bridges, which are vital in order to communicate between different worlds of thought and methodology – be it between Information Systems (IS) research and practice, or between IS research and other research disciplines. They describe how structuring can be and should be done so as to foster communication and collaboration. The topics covered reflect various layers of structure that can serve as bridges: models, processes, data, organizations, and technologies. In turn, these aspects are complemented by visionary outlooks on how structure influences the field.
Download or read book Elgar Encyclopedia of Pricing written by Andreas Hinterhuber and published by Edward Elgar Publishing. This book was released on 2024-07-05 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Elgar Encyclopedia of Pricing presents a holistic view of cutting-edge topics, practical insights, and global perspectives on pricing. In-depth entries cover everything from behavioral pricing and artificial intelligence to sustainability pricing strategies and dynamic online pricing.
