First Degree Price Discrimination Using Big Data PDF Download
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Author: Benjamin Reed Shiller
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Benjamin Reed Shiller
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Benjamin Reed Shiller
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Noby Thomas Cyriac
Publisher: Nomos Verlag
ISBN: 3748934718
Category : Law
Languages : en
Pages : 322
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Book Description
Der Autor untersucht interdisziplinär, inwieweit Art. 102 AEUV geeignet ist, den Wettbewerb vor dem missbräuchlichen Verhalten marktbeherrschender Plattformen zu schützen. Nach einer ersten Erörterung der Grundlagen der digitalen Wirtschaft, insbesondere Big Data und mehrseitige Plattformen, werden die relevanten Konzepte, die von EU-Kommission und EU-Gerichten in ihrer Entscheidungspraxis zur Auslegung von Art. 102 AEUV entwickelt wurden, näher beleuchtet, um ihre Eignung für das Missbrauchsverbot mit Blick auf Plattformbetreiber vor dem Hintergrund der Besonderheiten mehrseitiger Märkte zu bewerten. Auch das Vorhandensein und die Abgrenzung eines Datenmarktes werden diskutiert.
Author: Pietro Reho
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
The master thesis has the objective to describe and analyse the impact of technologies drastic improvements over firm's strategical behaviour. First-degree price discrimination has been considered for centuries as a mirage to apply in competitive markets, due to consumer's differentiated tastes and preferences over goods. On the other hand, the last decades have led to an exponential growth in machine learning performance and computer technologies. Such unexpected evolution permits firms to manipulate an increasing amount of data, and enlarge their perspectives on customer's reservation price knowledge. Here lies one of the greatest challenges of the new era: how could emerging technologies change the way firms set their price to consumers? The proposed master thesis aims to explore this uncovered topic, and present a global overview of pricing policies consumers are about to face with the Big data revolution.
Author: George Charlson
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Stefan Grundmann
Publisher: Oxford University Press
ISBN: 0192608274
Category : Law
Languages : en
Pages : 353
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Book Description
Choice is a key concept of our time. It is a foundational mechanism for every legal order in societies that are, politically, constituted as democracies and, economically, built on the market mechanism. Thus, choice can be understood as an atomic structure that grounds core societal processes. In recent years, however, the debate over the right way to theorize choice - for example, as a rational or a behavioral type of decision making - has intensified. This collection provides an in-depth discussion of the promises and perils of specific types of theories of choice. It shows how the selection of a specific theory of choice can make a difference for concrete legal questions, in particular in the regulation of the digital economy or in choosing between market, firm, or network. In its first part, the volume provides an accessible overview of the current debates about rational versus behavioral approaches to theories of choice. The remainder of the book structures the vast landscape of theories of choice along with three main types: individual, collective, and organizational decision making. As theories of choice proliferate and become ever more sophisticated, however, the process of choosing an adequate theory of choice becomes increasingly intricate. This volume addresses this selection problem for the various legal arenas in which individual, organizational, and collective decisions matter. By drawing on economic, technological, political, and legal points of view, the volume shows which theories of choice are at the disposal of the legally relevant decision-maker, and how they can be operationalized for the solution of concrete legal problems. The editors acknowledge the kind support of the Fritz Thyssen Foundation for an exploratory conference on the subject of the book.
Author: Cassidy R. Sugimoto
Publisher: MIT Press
ISBN: 0262529483
Category : Language Arts & Disciplines
Languages : en
Pages : 308
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Book Description
Perspectives on the varied challenges posed by big data for health, science, law, commerce, and politics. Big data is ubiquitous but heterogeneous. Big data can be used to tally clicks and traffic on web pages, find patterns in stock trades, track consumer preferences, identify linguistic correlations in large corpuses of texts. This book examines big data not as an undifferentiated whole but contextually, investigating the varied challenges posed by big data for health, science, law, commerce, and politics. Taken together, the chapters reveal a complex set of problems, practices, and policies. The advent of big data methodologies has challenged the theory-driven approach to scientific knowledge in favor of a data-driven one. Social media platforms and self-tracking tools change the way we see ourselves and others. The collection of data by corporations and government threatens privacy while promoting transparency. Meanwhile, politicians, policy makers, and ethicists are ill-prepared to deal with big data's ramifications. The contributors look at big data's effect on individuals as it exerts social control through monitoring, mining, and manipulation; big data and society, examining both its empowering and its constraining effects; big data and science, considering issues of data governance, provenance, reuse, and trust; and big data and organizations, discussing data responsibility, “data harm,” and decision making. Contributors Ryan Abbott, Cristina Alaimo, Kent R. Anderson, Mark Andrejevic, Diane E. Bailey, Mike Bailey, Mark Burdon, Fred H. Cate, Jorge L. Contreras, Simon DeDeo, Hamid R. Ekbia, Allison Goodwell, Jannis Kallinikos, Inna Kouper, M. Lynne Markus, Michael Mattioli, Paul Ohm, Scott Peppet, Beth Plale, Jason Portenoy, Julie Rennecker, Katie Shilton, Dan Sholler, Cassidy R. Sugimoto, Isuru Suriarachchi, Jevin D. West
Author: David Birget
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
In a context where more and more personal data is gathered by companies thanks to the rise of social networks, the internet of things, e-commerce and many other online services, it is interesting to explore how this data can be used profitably by different businesses. One potential application is to use online data to estimate the willingness to pay of consumers in order to implement personalised pricing. The goal of this thesis is threefold. First of all, I investigate to what extend price discrimination is already being used online. Secondly, I analyse the future economic potential of personalised pricing in the light of the recent progress in data collection and analytics. Thirdly, I examine the economic implications for different stakeholders resulting from a hypothetical large-scale use of personalised pricing by online shops. In this context, I also review current regulation and suggest potential improvements.
Author: Walter R. Paczkowski
Publisher: Routledge
ISBN: 1351713094
Category : Business & Economics
Languages : en
Pages : 318
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Book Description
The theme of this book is simple. The price – the number someone puts on a product to help consumers decide to buy that product – comes from data. Specifically, itcomes from statistically modeling the data. This book gives the reader the statistical modeling tools needed to get the number to put on a product. But statistical modeling is not done in a vacuum. Economic and statistical principles and theory conjointly provide the background and framework for the models. Therefore, this book emphasizes two interlocking components of modeling: economic theory and statistical principles. The economic theory component is sufficient to provide understanding of the basic principles for pricing, especially about elasticities, which measure the effects of pricing on key business metrics. Elasticity estimation is the goal of statistical modeling, so attention is paid to the concept and implications of elasticities. The statistical modeling component is advanced and detailed covering choice (conjoint, discrete choice, MaxDiff) and sales data modeling. Experimental design principles, model estimation approaches, and analysis methods are discussed and developed for choice models. Regression fundamentals have been developed for sales model specification and estimation and expanded for latent class analysis.
Author: Ben Depoorter
Publisher: Edward Elgar Publishing
ISBN: 1789903998
Category : Law
Languages : en
Pages : 1504
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Book Description
Both law and economics and intellectual property law have expanded dramatically in tandem over recent decades. This field-defining two-volume Handbook, featuring the leading legal, empirical, and law and economics scholars studying intellectual property rights, provides wide-ranging and in-depth analysis both of the economic theory underpinning intellectual property law, and the use of analytical methods to study it.
