Download or read book Artificial Intelligence and Pricing written by Diego Aparicio and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: As businesses become more sophisticated and welcome new technologies, artificial intelligence-based methods are increasingly being used for firms' pricing decisions. In this review article, we provide a survey of research in the area of AI and pricing. On the upside, research has shown that algorithms allow companies to achieve unprecedented advantages, including real-time response to demand and supply shocks, personalized pricing, and demand learning. However, recent research has uncovered unforeseen downsides to algorithmic pricing that are important for managers and policy makers to consider.

Download or read book Artificial Intelligence for Automated Pricing Based on Product Descriptions written by Nguyen Thi Ngoc Anh and published by Springer Nature. This book was released on 2021-08-28 with total page 62 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights artificial intelligence algorithms used in implementation of automated pricing. It presents the process for building automated pricing models from crawl data, preprocessed data to implement models, and their applications. The book also focuses on machine learning and deep learning methods for pricing, including from regression methods to hybrid and ensemble methods. The computational experiments are presented to illustrate the pricing processes and models.

Download or read book The Economics of Artificial Intelligence written by Ajay Agrawal and published by University of Chicago Press. This book was released on 2024-03-05 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.

Download or read book Machine Learning in Asset Pricing written by Stefan Nagel and published by Princeton University Press. This book was released on 2021-05-11 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: A groundbreaking, authoritative introduction to how machine learning can be applied to asset pricing Investors in financial markets are faced with an abundance of potentially value-relevant information from a wide variety of different sources. In such data-rich, high-dimensional environments, techniques from the rapidly advancing field of machine learning (ML) are well-suited for solving prediction problems. Accordingly, ML methods are quickly becoming part of the toolkit in asset pricing research and quantitative investing. In this book, Stefan Nagel examines the promises and challenges of ML applications in asset pricing. Asset pricing problems are substantially different from the settings for which ML tools were developed originally. To realize the potential of ML methods, they must be adapted for the specific conditions in asset pricing applications. Economic considerations, such as portfolio optimization, absence of near arbitrage, and investor learning can guide the selection and modification of ML tools. Beginning with a brief survey of basic supervised ML methods, Nagel then discusses the application of these techniques in empirical research in asset pricing and shows how they promise to advance the theoretical modeling of financial markets. Machine Learning in Asset Pricing presents the exciting possibilities of using cutting-edge methods in research on financial asset valuation.

Download or read book Artificial Intelligence and Pricing written by John Asker and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The behavior of artificial intelligences algorithms (AIAs) is shaped by how they learn about their environment. We compare the prices generated by AIAs that use different learning protocols when there is market interaction. Asynchronous learning occurs when the AIA only learns about the return from the action it took. Synchronous learning occurs when the AIA conducts counterfactuals to learn about the returns it would have earned had it taken an alternative action. The two lead to markedly different market prices. When future profits are not given positive weight by the AIA, synchronous updating leads to competitive pricing, while asynchronous can lead to pricing close to monopoly levels. We investigate how this result varies when either counterfactuals can only be calculated imperfectly and/or when the AIA places a weight on future profits.

Download or read book Artificial Intelligence Algorithmic Pricing and Collusion written by Emilio Calvano and published by . This book was released on 2018 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pricing algorithms are increasingly replacing human decision making in real marketplaces. To inform the competition policy debate on possible consequences, we run experiments with pricing algorithms powered by Artificial Intelligence in controlled environments (computer simulations). In particular, we study the interaction among a number of Q-learning algorithms in the context of a workhorse oligopoly model of price competition with Logit demand and constant marginal costs. We show that the algorithms consistently learn to charge supra-competitive prices, without communicating with each other. The high prices are sustained by classical collusive strategies with a finite punishment phase followed by a gradual return to cooperation. This finding is robust to asymmetries in cost or demand and to changes in the number of players.

Download or read book The Ends Game written by Marco Bertini and published by MIT Press. This book was released on 2022-01-11 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: How companies like Dollar Shave Club and Rent the Runway rewrite the rules of commerce by pursuing outcomes rather than products and services. The seventh book in the Management on the Cutting Edge series—for business professionals looking to do deliver excellent customer service while maximizing value and revenue. Would you rather pay for healthcare or for better health? For school or education? For groceries or nutrition? A car or transportation? A theater performance or entertainment? In The Ends Game, Marco Bertini and Oded Koenigsberg describe how some firms are rewriting the rules of commerce: instead of selling the “means” (their products and services), they adopt innovative revenue models to pursue “ends” (actual outcomes). They examine companies such as: • Dollar Shave Club • Rent the Runway • Netflix • Spotify • Michelin • Adobe • Pearson • And many more! They show that paying by the pill, semester, food item, vehicle, or show does not necessarily reflect the value that customers actually derive from their purchases. Revenue models anchored on the ownership of products, they argue, are patently inferior.

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 The AI Advantage written by Thomas H. Davenport and published by MIT Press. This book was released on 2019-08-06 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cutting through the hype, a practical guide to using artificial intelligence for business benefits and competitive advantage. In The AI Advantage, Thomas Davenport offers a guide to using artificial intelligence in business. He describes what technologies are available and how companies can use them for business benefits and competitive advantage. He cuts through the hype of the AI craze—remember when it seemed plausible that IBM's Watson could cure cancer?—to explain how businesses can put artificial intelligence to work now, in the real world. His key recommendation: don't go for the “moonshot” (curing cancer, or synthesizing all investment knowledge); look for the “low-hanging fruit” to make your company more efficient. Davenport explains that the business value AI offers is solid rather than sexy or splashy. AI will improve products and processes and make decisions better informed—important but largely invisible tasks. AI technologies won't replace human workers but augment their capabilities, with smart machines to work alongside smart people. AI can automate structured and repetitive work; provide extensive analysis of data through machine learning (“analytics on steroids”), and engage with customers and employees via chatbots and intelligent agents. Companies should experiment with these technologies and develop their own expertise. Davenport describes the major AI technologies and explains how they are being used, reports on the AI work done by large commercial enterprises like Amazon and Google, and outlines strategies and steps to becoming a cognitive corporation. This book provides an invaluable guide to the real-world future of business AI. A book in the Management on the Cutting Edge series, published in cooperation with MIT Sloan Management Review.

Download or read book Artificial Intelligence written by Harvard Business Review and published by HBR Insights. This book was released on 2019 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: Companies that don't use AI to their advantage will soon be left behind. Artificial intelligence and machine learning will drive a massive reshaping of the economy and society. What should you and your company be doing right now to ensure that your business is poised for success? These articles by AI experts and consultants will help you understand today's essential thinking on what AI is capable of now, how to adopt it in your organization, and how the technology is likely to evolve in the near future. Artificial Intelligence: The Insights You Need from Harvard Business Review will help you spearhead important conversations, get going on the right AI initiatives for your company, and capitalize on the opportunity of the machine intelligence revolution. Catch up on current topics and deepen your understanding of them with the Insights You Need series from Harvard Business Review. Featuring some of HBR's best and most recent thinking, Insights You Need titles are both a primer on today's most pressing issues and an extension of the conversation, with interesting research, interviews, case studies, and practical ideas to help you explore how a particular issue will impact your company and what it will mean for you and your business.

Download or read book Artificial Intelligence For Dummies written by John Paul Mueller and published by John Wiley & Sons. This book was released on 2018-03-16 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt: Step into the future with AI The term "Artificial Intelligence" has been around since the 1950s, but a lot has changed since then. Today, AI is referenced in the news, books, movies, and TV shows, and the exact definition is often misinterpreted. Artificial Intelligence For Dummies provides a clear introduction to AI and how it’s being used today. Inside, you’ll get a clear overview of the technology, the common misconceptions surrounding it, and a fascinating look at its applications in everything from self-driving cars and drones to its contributions in the medical field. Learn about what AI has contributed to society Explore uses for AI in computer applications Discover the limits of what AI can do Find out about the history of AI The world of AI is fascinating—and this hands-on guide makes it more accessible than ever!

Download or read book Algorithms Artificial Intelligence and Simple Rule Based Pricing written by Qiaochu Wang and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automated pricing comes in two forms - rule-based (e.g., targeting or undercutting the lowest price, etc) and artificial intelligence (AI) powered algorithms (e.g., reinforcement learning (RL) based). While rule-based pricing is the most widely used automated pricing strategy today, many retailers have increasingly adopting pricing algorithms powered by AI. Q-learning algorithm (a specific type of RL algorithm) is particularly appealing for pricing because it autonomously learns an optimal pricing policy and can adapt to any evolution in competitors' pricing strategy and market environment. It is commonly believed that the Q-learning algorithm has a significant advantage over simple rule-based pricing algorithms; therefore, in a competitive environment, most firms should adopt Q-learning based pricing algorithms if their competitors are using such algorithms. However, through extensive pricing experiments in a workhorse oligopoly model of repeated price competition, we show that a firm's best response to its competitor's Q-learning based algorithms is to use simple rule-based pricing algorithms. We find that when a Q-learning algorithm competes against a rule-based pricing algorithm, higher prices are sustained in the market in comparison to when multiple Q-learning algorithms compete against each other. The high prices are sustained because the rule-based algorithm introduces stationarity into the repeated price competition, which allows the Q-learning algorithm to more effectively search for the optimal policy benefiting both sellers. Further, the experimental phase where the Q-learning algorithm learns the optimal pricing policy is significantly shorter when it competes against a rule-based pricing algorithm in comparison to when it competes against another Q-learning algorithm. Our results are robust to alternative modeling assumptions on market structure, algorithm type, number of players, etc.

Download or read book Artificial Intelligence in Marketing written by K. Sudhir and published by Emerald Group Publishing. This book was released on 2023-03-13 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: Review of Marketing Research pushes the boundaries of marketing—broadening the marketing concept to make the world a better place. Here, leading scholars explore how marketing is currently shaping, and being shaped by, the evolution of Artificial Intelligence (AI).

Download or read book PRICE INTELLIGENCE written by Kunal Miind and published by BAKER & MCGILL. This book was released on 2021-01-05 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt: In "Pricing Intelligence: How to Use Data to Optimize Your Pricing Strategy for Business Leaders," entrepreneur and technology expert, Kunal Miind explores how businesses can use data to optimize their pricing strategies. This book covers everything from the power of price intelligence, understanding customers, and competitive pricing analysis, to dynamic pricing strategies and best practices for pricing strategy optimization. Written for business leaders looking to stay competitive, this comprehensive guide is a must-read for anyone looking to make better pricing decisions. Whether you're a small business owner or a corporate executive, this book is a must-read for anyone looking to make better pricing decisions and stay competitive in today's rapidly changing business landscape. Published by BAKER & MCGILL (https://bakermcgill.com.au)

Download or read book The Promise of Artificial Intelligence written by Brian Cantwell Smith and published by MIT Press. This book was released on 2019-10-08 with total page 179 pages. Available in PDF, EPUB and Kindle. Book excerpt: An argument that—despite dramatic advances in the field—artificial intelligence is nowhere near developing systems that are genuinely intelligent. In this provocative book, Brian Cantwell Smith argues that artificial intelligence is nowhere near developing systems that are genuinely intelligent. Second wave AI, machine learning, even visions of third-wave AI: none will lead to human-level intelligence and judgment, which have been honed over millennia. Recent advances in AI may be of epochal significance, but human intelligence is of a different order than even the most powerful calculative ability enabled by new computational capacities. Smith calls this AI ability “reckoning,” and argues that it does not lead to full human judgment—dispassionate, deliberative thought grounded in ethical commitment and responsible action. Taking judgment as the ultimate goal of intelligence, Smith examines the history of AI from its first-wave origins (“good old-fashioned AI,” or GOFAI) to such celebrated second-wave approaches as machine learning, paying particular attention to recent advances that have led to excitement, anxiety, and debate. He considers each AI technology's underlying assumptions, the conceptions of intelligence targeted at each stage, and the successes achieved so far. Smith unpacks the notion of intelligence itself—what sort humans have, and what sort AI aims at. Smith worries that, impressed by AI's reckoning prowess, we will shift our expectations of human intelligence. What we should do, he argues, is learn to use AI for the reckoning tasks at which it excels while we strengthen our commitment to judgment, ethics, and the world.

Download or read book Artificial Intelligence and Machine Learning for Business written by John Medicine and published by . This book was released on 2020-10-07 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt: Do you want to learn about Artificial Intelligence and Machine Learning and how they are revolutionizing Life, Health Care, Business and Marketing? Do you want to modernize your business and marketing strategies to be ahead from competitors by applying Artificial Intelligence to it? Artificial intelligence technology has become so common that many people do not realize that AI is already a part of their lives. Businesses use AI in many realms, including predictive analytics, product pricing, and marketing. In healthcare, artificial intelligence can be used in medical image analysis, language processing in dictation, and automated healthcare services. Because of machine learning capabilities in AI, any data that artificial intelligence is provided with can be used to learn and to make new, unexpected predictions and recommendations. In this book, the reader will understand not only how AI works, but will also learn how machine learning is revolutionizing the industry. Although artificial intelligence can be complex, AI technology does not have to be a daunting subject. Understanding artificial intelligence requires a basic understanding of how machines can be programmed to think like humans. It is no surprise that AI is revolutionizing most areas of industry. Big tech companies have been on the forefront of AI because of their large amounts of data and their brain power in the form of machine learning teams, but anyone can learn how to use artificial intelligence to accomplish a basic business goal. Artificial intelligence technology has progressed so fast that many business leaders find themselves faced with the task of integrating all this new tech into how they do business. This can be a challenge for leaders and others whose core business function is not directly related to artificial intelligence or computer science. Artificial intelligence can be simply applied to business marketing strategies, social media engagement, and a host of other business functions. You will learn: - How Machine Learning works - AI Models and Networks - AI applied to complicated Tasks - How apply AI to your Marketing - How AI is changing Business - The secret of Big Tech companies and much more! Even if you don't know anything about Artificial Intelligence and Machine Learning you can learn how they can improve your business. Click Buy Now button to get started!

Download or read book Artificial Intelligence for Business written by John Medicine and published by . This book was released on 2020-10-07 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Do you want to learn about Artificial Intelligence and Machine Learning and how they are revolutionizing Life, Health Care, Business and Marketing? Do you want to modernize your business and marketing strategies to be ahead of competitors by applying Artificial Intelligence to it? If so then keep reading. Artificial intelligence technology has become so common that many people do not realize that AI is already a part of their lives. Businesses use AI in many realms, including predictive analytics, product pricing, and marketing. In healthcare, artificial intelligence can be used in medical image analysis, language processing in dictation, and automated healthcare services. Because of machine learning capabilities in AI, any data that artificial intelligence is provided with can be used to learn and to make new, unexpected predictions and recommendations. In this book, the reader will understand not only how AI works, but will also learn how machine learning is revolutionizing the industry. Artificial intelligence technology has progressed so fast that many business leaders find themselves faced with the task of integrating all this new tech into how they do business. This can be a challenge for leaders and others whose core business function is not directly related to AI or computer science. AI can be simply applied to business marketing strategies, social media engagement, and a host of other business functions. These AI applications can be accomplished no matter what the skill level of the user is. Artificial Intelligence for Business: A Modern Business Approach will teach readers how they can benefit from the AI wave to keep themselves and their business endeavors up to date. Business data and AI are linked together so that the Business and the technology evolve together. Business leaders are faced left with the question of how to bring artificial intelligence into their business, and sometimes this is as simple as recording data measures electronically so that AI can access it and use it to make powerful recommendations. As the intelligence demonstrated by machines, AI will become more prominent and important as AI capabilities increase. From a practical standpoint, this means that businesses are faced with the reality of incorporating AI into their operations now or being left so far behind that they will be relegated to playing an endless game of catchup. In Artificial Intelligence for Business: A Modern Business Approach, readers will learn not only the business strategies they can use to keep up with artificial intelligence, but the many powerful applications that AI can have in business, from automation of business processes and machine learning, to predicting customer behavior and product pricing. You will learn: - How Machine Learning works - AI Models and Networks - AI applied to complicated Tasks - How apply AI to your Marketing - The secret of Big Tech companies - Insights into AI Systems - How to build AI strategies for your business - How to build Machine Learning Models - How to apply AI to Marketing and Social Media - 10 AI Trends for Businesses ...and more! Even if you don't know anything about Artificial Intelligence and Machine Learning, your education in AI, so that you can use it to accomplish all your business goals, begins here! Click the Buy Now button to get started!