Unfolding the Allegory Behind Market Communication and Social Error and Correction

2009 ◽  
Author(s):  
Daniel B. Klein
Keyword(s):  
Market Communication

Literature, Media and Market

2021 ◽  
Vol 9 (8) ◽  
pp. 2176-2178
Author(s):  
Dr. Jnanee Debasish Mishra
Keyword(s):  
Daily Life ◽  
Great Influence ◽  
The Other ◽  
Media Ethics ◽  
Modern Times ◽  
Market Communication ◽  
The Media ◽  
Media Market

Synopsis: Literature is the medicine for man and civilization for years. It attracts and affects the soul and mind. In modern times transformation of media makes a big difference in human approach. Though Communication is the primary aim of media, but it works like a window of conscience. In the age of globalization the media has a great influence on society. Though market is an economical concept but our daily life is bound to rely upon it. And now literature, media and market remain in an inter related manner. One affects the other two. This analysis tries to find out the inter relationship among literature, media and market. Keywords: Literature, Media, Market, Communication, Globalization, Literary Sensibility, Media ethics, Change in media approach

Fatal Attraction? Popular Modes of Inclusion in the Economic System

2002 ◽  
Vol 8 (1) ◽  
Author(s):  
Urs Stäheli
Keyword(s):  
Stock Market ◽  
Economic System ◽  
Stock Exchange ◽  
Turn Of The Century ◽  
Cultural Identities ◽  
Functional Systems ◽  
Fatal Attraction ◽  
Market Communication ◽  
Crowd Psychology ◽  
Inclusive Society

AbstractThe paper suggests a concept of the popular which understands itself as an alternative to mainstream Cultural Studies which refer to the Popular in terms of hegemonic articulations of socio-cultural identities such as gender, ethnicity, sexuality or class. In contrast, my contention is that the Popular is intrinsically linked to the universalism of functionally differentiated systems. The popular then describes how functional systems use the distinction between a universalistic semantics of inclusion and its seductive, hyper-universalistic exaggeration. At the turn of the century, it was crowd psychology (e.g. Le Bon) which provided the semantics to deal with the new forms of hyper-universalism. The paper uses this redefined notion of the popular for analyzing discourses on speculation and the stock exchange. It focuses on those semantics which implicitly problematize the process of inclusion by trying to make it more attractive. The inclusion of the speculator becomes a process of seduction, resulting in a precarious expansion of inclusion. It is discussed how such a ›massive universalism‹ is produced by stock market communication itself and how it relates to the modern ideal of a more and more inclusive society.

ALGORITHMS, MACHINE LEARNING, AND COLLUSION

2018 ◽  
Vol 14 (4) ◽  
pp. 568-607 ◽  
Author(s):  
Ulrich Schwalbe
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Experimental Economics ◽  
Competition Law ◽  
Price Setting ◽  
Legal Problems ◽  
Pricing Behavior ◽  
Computer Scientists ◽  
Market Communication ◽  
Self Learning

Abstract This paper discusses whether self-learning price-setting algorithms can coordinate their pricing behavior to achieve a collusive outcome that maximizes the joint profits of the firms using them. Although legal scholars have generally assumed that algorithmic collusion is not only possible but also exceptionally easy, computer scientists examining cooperation between algorithms as well as economists investigating collusion in experimental oligopolies have countered that coordinated, tacitly collusive behavior is not as rapid, easy, or even inevitable as often suggested. Research in experimental economics has shown that the exchange of information is vital to collusion when more than two firms operate within a given market. Communication between algorithms is also a topic in research on artificial intelligence, in which some scholars have recently indicated that algorithms can learn to communicate, albeit in somewhat limited ways. Taken together, algorithmic collusion currently seems far more difficult to achieve than legal scholars have often assumed and is thus not a particularly relevant competitive concern at present. Moreover, there are several legal problems associated with algorithmic collusion, including questions of liability, of auditing and monitoring algorithms, and of enforcing competition law.

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