The Economics of Peer-to-Peer Networks

Peer-to-Peer (P2P) networks have emerged as a significant social phenomenon for the distribution of information goods and may become an important alternative to traditional client-server network architectures for knowledge sharing within enterprises. This paper reviews and synthesizes the relevant computer science and economics literatures as they relate to P2P networks, and raises important questions for researchers interested in studying the behavior of these networks from the perspective of the economics of information technology. With regard to the economic characteristics of these networks, we show that while the characteristics of services provided over P2P networks are similar to public goods and club goods, they have many important differences and hence there is a need for new theoretical models as well as empirical and experimental analysis to understand P2P user behavior. We then identify several important areas for study with regard to the economics of P2P networks and review recent academic papers in each area

Essays on Applied Network Theory.

Network economics is a fast growing area of study, with a lot of potential for addressing a wide variety of socio-economic phenomena. Networks literally permeate our social and economic lives. The unemployed find jobs using the information and assistance of their friends and relatives. Consumers benefit from the research of friends and family into new products. In medicine and other technical fields, professional networks shape research patterns. In all these settings, the well-being of participants depends on social, geographic, or trading relationships. The countless ways in which network structures affect our well-being make it critical to understand: (i) how network structures impact behavior, (ii) what can be done, in the way of design by policymakers, to improve systemic outcomes. This area of study, broadly called network economics, is at the heart of my research interests. In my dissertation I focus on three specific applications of network theory. The first application concerns networks in trade, where network structure represents the organization of trade agreements between countries. The second application deals with networks in financial market, and the network is used to model the structure of interbank exposures. Lastly, for the third application, I consider networks in labor markets and migration. In this context, the network represents the structure of social relations between people. Each of these applications of network analysis is addressed by one of three chapters in the thesis.Network analysis (Planning); Social networks -- Mathematical models; Social sciences -- Network analysis; Economics, Mathematical;

Networks and Markets

Networks influence human behavior and well being, and realizing this, individuals make conscious efforts to shape their own networks. Over the past decade, economists have combined these ideas with concepts from game theory, oligopoly, general equilibrium, and information economics to develop a general framework of analysis. The ensuing research has deepened our understanding of classical questions in economics and opened up entirely new lines of enquiry

Networks

Building on the theoretical bases of nets and networks, this paper aims to systemise and typify the networks operating in social and economic life and accordingly analyse the nets and networks that can be identified in logistics. The most recent achievements of mathematics, economics and information technology as well as the globalisation set new challenges to logistics, which it can handle on the basis of the above mentioned networks only. This Paper highlights the potential forms and relations of logistics networks

Trust and Risk in Business Networks: Towards a Due Diligence for Electronic Commerce

This paper develops a due diligence for electronic transactions with new partners in business networks with complex goods such as food products to enable the use of e-commerce potentials in first time transactions. The e-commerce due diligence is a means to reduce perceived risks and uncertainties for businesses and create trust and confidence in the electronic transaction with appropriate information. The paper presents a conceptual framework for the due diligence integrating the principles of transaction decision making and the four phases of a transaction process. The operationalization of the framework assigns trust signals and control elements to the four process phases to be communicated during the process.Trust, risk, electronic commerce, first time transactions, due diligence, food networks, Agribusiness, Institutional and Behavioral Economics, Marketing,

The complex interaction between Global Production Networks, Digital Information Systems and International Knowledge Transfers

Traditionally many studies of knowledge in economics have focused on localized networks and intra-regional collaborations. However, the rising frequency by which firms collaborate within the context of global networks of production and innovation, the increasingly intricate divisions of labor involved and the extensive use of the Internet to facilitate interaction are all relatively novel trends that underline the importance of knowledge creation and flows across different locations. Focusing on this topic, the present chapter examines the complex interactions between global production networks (GPN), digital information systems (DIS) and knowledge transfers in information technology industries. It seeks to disentangle the various conduits through which different kinds of knowledge are transferred within such networks, and investigate how recent generations of DIS are affecting those knowledge transfers. The paper concludes that the dual expansion of GPN and DIS is adding new complexity to the practice of innovation: To access knowledge necessary for sustained creativity firms often have to link up with remote partners in GPN, but to be able to absorb and utilize this knowledge, they also frequently have to engage in local interactive learning processes. These local- global linkages - and the various skills necessary to operate them - are strongly interdependent, mutually reinforcing and critical for the development and maintenance of innovation-based competitiveness.

Proceedings of the Conference on Human and Economic Resources

Recent development of information technologies and telecommunications have given rise to an extraordinary increase in the data transactions in the financial markets. In large and transparent markets, with lower transactions and information costs, financial participants react more rapidly to changes in the profitability of their assets, and in their perception of the risks of the different financial instruments. In this respect, if the rapidity of reaction of financial players is the main feature of globalized markets, then only advanced information technologies, which uses data resources efficiently are capable of reflecting these complex nature of financial markets. The aim of this paper is to show how the new information technologies affect modelling of financial markets and decisions by using limited data resources within an intelligent system. By using intelligent information systems, mainly neural networks, this paper tries to show how the the limited economic data can be used for efficient economic decisions in the global financial markets. Advances in microprocessors and software technologies make it possible to enable the development of increasingly powerful systems at reasonable costs. The new technologies have created artificial systems, which imitate people’s brain for efficient analysis of economic data. According to Hertz, Krogh and Palmer (1991), artificial neural networks which have a similar structure of the brain consist of nodes passing activation signals to each other. Within the nodes, if incoming activation signals from the others are combined some of the nodes will produce an activation signal modified by a connection weight between it and the node to which it is linked. By using financial data from international foreign exchange markets, namely daily time series of EUR/USD parity, and by employing certain neural network algorithms, it has showed that new information technologies have advantages on efficient usage of limited economic data in modeling. By investigating the “artificial” works on modeling of international financial markets, this paper is tried to show how limited information in the markets can be used for efficient economic decisions. By investigating certain neural networks algorithms, the paper displays how artificial neural networks have been used for efficient economic modeling and decisions in global F/X markets. New information technologies have many advantages over statistics methods in terms of efficient data modeling. They are capable of analyzing complex patterns quickly and with a high degree of accuracy. Since, “artificial” information systems do not make any assumptions about the nature of the distribution of the data, they are not biased in their analysis. By using different neural network algorithms, the economic data can be modeled in an efficient way. Especially if the markets are non-linear and complex, the intelligent systems are more powerful on explaining the market behavior in the chaotic environments. With more advanced information technologies, in the future, it will be possible to model all the complexity of the economic life. New researches in the future need a more strong interaction between economics and computer science.neural networks,knowledge, information technology, communication technology

Patronage, Reputation and Common Agency Contracting in the Scientific Revolution: From Keeping 'Nature's Secrets' to the Institutionalization of 'Open Science'

This essay examines the economics of patronage in the production of knowledge and its influence upon the historical formation of key elements in the ethos and organizational structure of publicly funded open science. The emergence during the late sixteenth and early seventeenth centuries of the idea and practice of “open science" was a distinctive and vital organizational aspect of the Scientific Revolution. It represented a break from the previously dominant ethos of secrecy in the pursuit of Nature’s Secrets, to a new set of norms, incentives, and organizational structures that reinforced scientific researchers' commitments to rapid disclosure of new knowledge. The rise of “cooperative rivalries” in the revelation of new knowledge, is seen as a functional response to heightened asymmetric information problems posed for the Renaissance system of court-patronage of the arts and sciences; pre-existing informational asymmetries had been exacerbated by the claims of mathematicians and the increasing practical reliance upon new mathematical techniques in a variety of “contexts of application.” Reputational competition among Europe’s noble patrons motivated much of their efforts to attract to their courts the most prestigious natural philosophers, was no less crucial in the workings of that system than was the concern among their would-be clients to raise their peer-based reputational status. In late Renaissance Europe, the feudal legacy of fragmented political authority had resulted in relations between noble patrons and their savant-clients that resembled the situation modern economists describe as "common agency contracting in substitutes" -- competition among incompletely informed principals for the dedicated services of multiple agents. These conditions tended to result in more favorable contract terms (especially with regard to autonomy and financial support) for the agent-client members of the nascent scientific communities. This left the new scientists better positioned to retain larger information rents on their specialized knowledge, which in turn tended to encourage entry into the emerging disciplines. They also were thereby enabled collectively to develop a stronger degree of professional autonomy for their programs of inquiry within increasingly specialized and formal scientific academies which, during the latter seventeenth century, attracted the patronage of rival absolutist States in Western Europe.open science, new economics of science, economics of institutions, patronage, asymmetric information, principal-agent problems, common agency contracting, social networks, 'invisible colleges', scientific academies