Author: David Prakash
Publisher: BoD – Books on Demand
ISBN: 3756863514
Category : Business & Economics
Languages : en
Pages : 155
Book Description
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.
Behavioral Consequences of Dynamic Pricing
Author: David Prakash
Publisher: BoD – Books on Demand
ISBN: 3756863514
Category : Business & Economics
Languages : en
Pages : 155
Book Description
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.
Publisher: BoD – Books on Demand
ISBN: 3756863514
Category : Business & Economics
Languages : en
Pages : 155
Book Description
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.
The Elements of Joint Learning and Optimization in Operations Management
Author: Xi Chen
Publisher: Springer Nature
ISBN: 3031019261
Category : Business & Economics
Languages : en
Pages : 444
Book Description
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.
Publisher: Springer Nature
ISBN: 3031019261
Category : Business & Economics
Languages : en
Pages : 444
Book Description
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.
Revenue Management and Pricing Analytics
Author: Guillermo Gallego
Publisher: Springer
ISBN: 1493996061
Category : Business & Economics
Languages : en
Pages : 346
Book Description
“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.
Publisher: Springer
ISBN: 1493996061
Category : Business & Economics
Languages : en
Pages : 346
Book Description
“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.
Information Processing and Management of Uncertainty in Knowledge-Based Systems
Author: Marie-Jeanne Lesot
Publisher: Springer Nature
ISBN: 3030501469
Category : Computers
Languages : en
Pages : 779
Book Description
This three volume set (CCIS 1237-1239) constitutes the proceedings of the 18th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2020, in June 2020. The conference was scheduled to take place in Lisbon, Portugal, at University of Lisbon, but due to COVID-19 pandemic it was held virtually. The 173 papers were carefully reviewed and selected from 213 submissions. The papers are organized in topical sections: homage to Enrique Ruspini; invited talks; foundations and mathematics; decision making, preferences and votes; optimization and uncertainty; games; real world applications; knowledge processing and creation; machine learning I; machine learning II; XAI; image processing; temporal data processing; text analysis and processing; fuzzy interval analysis; theoretical and applied aspects of imprecise probabilities; similarities in artificial intelligence; belief function theory and its applications; aggregation: theory and practice; aggregation: pre-aggregation functions and other generalizations of monotonicity; aggregation: aggregation of different data structures; fuzzy methods in data mining and knowledge discovery; computational intelligence for logistics and transportation problems; fuzzy implication functions; soft methods in statistics and data analysis; image understanding and explainable AI; fuzzy and generalized quantifier theory; mathematical methods towards dealing with uncertainty in applied sciences; statistical image processing and analysis, with applications in neuroimaging; interval uncertainty; discrete models and computational intelligence; current techniques to model, process and describe time series; mathematical fuzzy logic and graded reasoning models; formal concept analysis, rough sets, general operators and related topics; computational intelligence methods in information modelling, representation and processing.
Publisher: Springer Nature
ISBN: 3030501469
Category : Computers
Languages : en
Pages : 779
Book Description
This three volume set (CCIS 1237-1239) constitutes the proceedings of the 18th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2020, in June 2020. The conference was scheduled to take place in Lisbon, Portugal, at University of Lisbon, but due to COVID-19 pandemic it was held virtually. The 173 papers were carefully reviewed and selected from 213 submissions. The papers are organized in topical sections: homage to Enrique Ruspini; invited talks; foundations and mathematics; decision making, preferences and votes; optimization and uncertainty; games; real world applications; knowledge processing and creation; machine learning I; machine learning II; XAI; image processing; temporal data processing; text analysis and processing; fuzzy interval analysis; theoretical and applied aspects of imprecise probabilities; similarities in artificial intelligence; belief function theory and its applications; aggregation: theory and practice; aggregation: pre-aggregation functions and other generalizations of monotonicity; aggregation: aggregation of different data structures; fuzzy methods in data mining and knowledge discovery; computational intelligence for logistics and transportation problems; fuzzy implication functions; soft methods in statistics and data analysis; image understanding and explainable AI; fuzzy and generalized quantifier theory; mathematical methods towards dealing with uncertainty in applied sciences; statistical image processing and analysis, with applications in neuroimaging; interval uncertainty; discrete models and computational intelligence; current techniques to model, process and describe time series; mathematical fuzzy logic and graded reasoning models; formal concept analysis, rough sets, general operators and related topics; computational intelligence methods in information modelling, representation and processing.
Digital Era and Fuzzy Applications in Management and Economy
Author: Martha del Pilar Rodríguez García
Publisher: Springer Nature
ISBN: 3030944859
Category : Technology & Engineering
Languages : en
Pages : 198
Book Description
This book aims to contribute to the discussion about the implications of fuzzy logic, neural networks, digital era, and other intelligent techniques on organizations. This book will be very useful for academic researchers and postgraduate students aiming to introduce themselves to the field of quantitative techniques for overcoming uncertain environments and developing models to make decisions. Developments in other theories and socioeconomic and computational changes have shed light on the importance of fuzzy applications in social sciences. The treatment of uncertainty in the economic and business analysis is fundamental and requires instruments compatible with the uncertain environment of economics and business, because most of the traditional models have been overtaken by this reality when trying to make decisions with uncertain information. In the face of information technology, digitization, and uncertainty, organizations confront new opportunities and challenges. In order to take advantage of these opportunities and overcome current and future challenges, it is needed to understand the evolution of these phenomenon.
Publisher: Springer Nature
ISBN: 3030944859
Category : Technology & Engineering
Languages : en
Pages : 198
Book Description
This book aims to contribute to the discussion about the implications of fuzzy logic, neural networks, digital era, and other intelligent techniques on organizations. This book will be very useful for academic researchers and postgraduate students aiming to introduce themselves to the field of quantitative techniques for overcoming uncertain environments and developing models to make decisions. Developments in other theories and socioeconomic and computational changes have shed light on the importance of fuzzy applications in social sciences. The treatment of uncertainty in the economic and business analysis is fundamental and requires instruments compatible with the uncertain environment of economics and business, because most of the traditional models have been overtaken by this reality when trying to make decisions with uncertain information. In the face of information technology, digitization, and uncertainty, organizations confront new opportunities and challenges. In order to take advantage of these opportunities and overcome current and future challenges, it is needed to understand the evolution of these phenomenon.
The Theory of Optimal Stopping
Author: Yuan Shih Chow
Publisher: Dover Publications
ISBN: 9780486666501
Category : Mathematics
Languages : en
Pages : 139
Book Description
Publisher: Dover Publications
ISBN: 9780486666501
Category : Mathematics
Languages : en
Pages : 139
Book Description
Local Electricity Markets
Author: Tiago Pinto
Publisher: Academic Press
ISBN: 0128226668
Category : Business & Economics
Languages : en
Pages : 474
Book Description
Local Electricity Markets introduces the fundamental characteristics, needs, and constraints shaping the design and implementation of local electricity markets. It addresses current proposed local market models and lessons from their limited practical implementation. The work discusses relevant decision and informatics tools considered important in the implementation of local electricity markets. It also includes a review on management and trading platforms, including commercially available tools. Aspects of local electricity market infrastructure are identified and discussed, including physical and software infrastructure. It discusses the current regulatory frameworks available for local electricity market development internationally. The work concludes with a discussion of barriers and opportunities for local electricity markets in the future. - Delineates key components shaping the design and implementation of local electricity market structure - Provides a coherent view on the enabling infrastructures and technologies that underpin local market expansion - Explores the current regulatory environment for local electricity markets drawn from a global panel of contributors - Exposes future paths toward widespread implementation of local electricity markets using an empirical review of barriers and opportunities - Reviews relevant local electricity market case studies, pilots and demonstrators already deployed and under implementation
Publisher: Academic Press
ISBN: 0128226668
Category : Business & Economics
Languages : en
Pages : 474
Book Description
Local Electricity Markets introduces the fundamental characteristics, needs, and constraints shaping the design and implementation of local electricity markets. It addresses current proposed local market models and lessons from their limited practical implementation. The work discusses relevant decision and informatics tools considered important in the implementation of local electricity markets. It also includes a review on management and trading platforms, including commercially available tools. Aspects of local electricity market infrastructure are identified and discussed, including physical and software infrastructure. It discusses the current regulatory frameworks available for local electricity market development internationally. The work concludes with a discussion of barriers and opportunities for local electricity markets in the future. - Delineates key components shaping the design and implementation of local electricity market structure - Provides a coherent view on the enabling infrastructures and technologies that underpin local market expansion - Explores the current regulatory environment for local electricity markets drawn from a global panel of contributors - Exposes future paths toward widespread implementation of local electricity markets using an empirical review of barriers and opportunities - Reviews relevant local electricity market case studies, pilots and demonstrators already deployed and under implementation
The Great Mental Models, Volume 1
Author: Shane Parrish
Publisher: Penguin
ISBN: 0593719972
Category : Business & Economics
Languages : en
Pages : 209
Book Description
Discover the essential thinking tools you’ve been missing with The Great Mental Models series by Shane Parrish, New York Times bestselling author and the mind behind the acclaimed Farnam Street blog and “The Knowledge Project” podcast. This first book in the series is your guide to learning the crucial thinking tools nobody ever taught you. Time and time again, great thinkers such as Charlie Munger and Warren Buffett have credited their success to mental models–representations of how something works that can scale onto other fields. Mastering a small number of mental models enables you to rapidly grasp new information, identify patterns others miss, and avoid the common mistakes that hold people back. The Great Mental Models: Volume 1, General Thinking Concepts shows you how making a few tiny changes in the way you think can deliver big results. Drawing on examples from history, business, art, and science, this book details nine of the most versatile, all-purpose mental models you can use right away to improve your decision making and productivity. This book will teach you how to: Avoid blind spots when looking at problems. Find non-obvious solutions. Anticipate and achieve desired outcomes. Play to your strengths, avoid your weaknesses, … and more. The Great Mental Models series demystifies once elusive concepts and illuminates rich knowledge that traditional education overlooks. This series is the most comprehensive and accessible guide on using mental models to better understand our world, solve problems, and gain an advantage.
Publisher: Penguin
ISBN: 0593719972
Category : Business & Economics
Languages : en
Pages : 209
Book Description
Discover the essential thinking tools you’ve been missing with The Great Mental Models series by Shane Parrish, New York Times bestselling author and the mind behind the acclaimed Farnam Street blog and “The Knowledge Project” podcast. This first book in the series is your guide to learning the crucial thinking tools nobody ever taught you. Time and time again, great thinkers such as Charlie Munger and Warren Buffett have credited their success to mental models–representations of how something works that can scale onto other fields. Mastering a small number of mental models enables you to rapidly grasp new information, identify patterns others miss, and avoid the common mistakes that hold people back. The Great Mental Models: Volume 1, General Thinking Concepts shows you how making a few tiny changes in the way you think can deliver big results. Drawing on examples from history, business, art, and science, this book details nine of the most versatile, all-purpose mental models you can use right away to improve your decision making and productivity. This book will teach you how to: Avoid blind spots when looking at problems. Find non-obvious solutions. Anticipate and achieve desired outcomes. Play to your strengths, avoid your weaknesses, … and more. The Great Mental Models series demystifies once elusive concepts and illuminates rich knowledge that traditional education overlooks. This series is the most comprehensive and accessible guide on using mental models to better understand our world, solve problems, and gain an advantage.
Patterns, Predictions, and Actions: Foundations of Machine Learning
Author: Moritz Hardt
Publisher: Princeton University Press
ISBN: 0691233721
Category : Computers
Languages : en
Pages : 321
Book Description
An authoritative, up-to-date graduate textbook on machine learning that highlights its historical context and societal impacts Patterns, Predictions, and Actions introduces graduate students to the essentials of machine learning while offering invaluable perspective on its history and social implications. Beginning with the foundations of decision making, Moritz Hardt and Benjamin Recht explain how representation, optimization, and generalization are the constituents of supervised learning. They go on to provide self-contained discussions of causality, the practice of causal inference, sequential decision making, and reinforcement learning, equipping readers with the concepts and tools they need to assess the consequences that may arise from acting on statistical decisions. Provides a modern introduction to machine learning, showing how data patterns support predictions and consequential actions Pays special attention to societal impacts and fairness in decision making Traces the development of machine learning from its origins to today Features a novel chapter on machine learning benchmarks and datasets Invites readers from all backgrounds, requiring some experience with probability, calculus, and linear algebra An essential textbook for students and a guide for researchers
Publisher: Princeton University Press
ISBN: 0691233721
Category : Computers
Languages : en
Pages : 321
Book Description
An authoritative, up-to-date graduate textbook on machine learning that highlights its historical context and societal impacts Patterns, Predictions, and Actions introduces graduate students to the essentials of machine learning while offering invaluable perspective on its history and social implications. Beginning with the foundations of decision making, Moritz Hardt and Benjamin Recht explain how representation, optimization, and generalization are the constituents of supervised learning. They go on to provide self-contained discussions of causality, the practice of causal inference, sequential decision making, and reinforcement learning, equipping readers with the concepts and tools they need to assess the consequences that may arise from acting on statistical decisions. Provides a modern introduction to machine learning, showing how data patterns support predictions and consequential actions Pays special attention to societal impacts and fairness in decision making Traces the development of machine learning from its origins to today Features a novel chapter on machine learning benchmarks and datasets Invites readers from all backgrounds, requiring some experience with probability, calculus, and linear algebra An essential textbook for students and a guide for researchers
The Fundamentals of Heavy Tails
Author: Jayakrishnan Nair
Publisher: Cambridge University Press
ISBN: 1009062964
Category : Mathematics
Languages : en
Pages : 266
Book Description
Heavy tails –extreme events or values more common than expected –emerge everywhere: the economy, natural events, and social and information networks are just a few examples. Yet after decades of progress, they are still treated as mysterious, surprising, and even controversial, primarily because the necessary mathematical models and statistical methods are not widely known. This book, for the first time, provides a rigorous introduction to heavy-tailed distributions accessible to anyone who knows elementary probability. It tackles and tames the zoo of terminology for models and properties, demystifying topics such as the generalized central limit theorem and regular variation. It tracks the natural emergence of heavy-tailed distributions from a wide variety of general processes, building intuition. And it reveals the controversy surrounding heavy tails to be the result of flawed statistics, then equips readers to identify and estimate with confidence. Over 100 exercises complete this engaging package.
Publisher: Cambridge University Press
ISBN: 1009062964
Category : Mathematics
Languages : en
Pages : 266
Book Description
Heavy tails –extreme events or values more common than expected –emerge everywhere: the economy, natural events, and social and information networks are just a few examples. Yet after decades of progress, they are still treated as mysterious, surprising, and even controversial, primarily because the necessary mathematical models and statistical methods are not widely known. This book, for the first time, provides a rigorous introduction to heavy-tailed distributions accessible to anyone who knows elementary probability. It tackles and tames the zoo of terminology for models and properties, demystifying topics such as the generalized central limit theorem and regular variation. It tracks the natural emergence of heavy-tailed distributions from a wide variety of general processes, building intuition. And it reveals the controversy surrounding heavy tails to be the result of flawed statistics, then equips readers to identify and estimate with confidence. Over 100 exercises complete this engaging package.