Networks of Collaboration in Oligopoly

In an oligopoly, prior to competing in the market, firms have an opportunity to form pair-wise collaborative links with other firms. These pair-wise links involve a commitment of resources and lead to lower costs of production of the collaborating firms. The collection of pair-wise links defines a collaboration network. We study the architecture of strategically stable networks. Our analysis reveals that in a setting where firms are ex-ante identical, strategically stable networks are often asymmetric, with some firms having a large number of links while others have few links or no links at all. We characterize such asymmetric networks; the dominant group architecture, stars, and inter-linked stars are found to be stable. In asymmetric networks, the firms with many links have lower costs of production as compared to firms with few links. Thus collaboration links can have a major influence on the functioning of the market.networks;oligopoly;market competition

On the Estimation of Nonrandom Signal Coefficients from Jittered Samples

This paper examines the problem of estimating the parameters of a bandlimited signal from samples corrupted by random jitter (timing noise) and additive iid Gaussian noise, where the signal lies in the span of a finite basis. For the presented classical estimation problem, the Cramer-Rao lower bound (CRB) is computed, and an Expectation-Maximization (EM) algorithm approximating the maximum likelihood (ML) estimator is developed. Simulations are performed to study the convergence properties of the EM algorithm and compare the performance both against the CRB and a basic linear estimator. These simulations demonstrate that by post-processing the jittered samples with the proposed EM algorithm, greater jitter can be tolerated, potentially reducing on-chip ADC power consumption substantially.Comment: 11 pages, 8 figure

Technological change in markets with network externalities

Technological Change;Externalities

Lepton number violation in Little Higgs model

In this note we examine the constraints imposed by muon anomalous magnetic moment ($(g-2)_\mu$) and $\mu^- \to e^+ e^- e^-$ on lepton number violating (LNV) couplings of the triplet Higgs in Little Higgs (LH) model.Comment: revtex4.0 file, 5 pages including 8 eps figures, version to appear in Phys. Rev.

Validating Network Value of Influencers by means of Explanations

Recently, there has been significant interest in social influence analysis. One of the central problems in this area is the problem of identifying influencers, such that by convincing these users to perform a certain action (like buying a new product), a large number of other users get influenced to follow the action. The client of such an application is a marketer who would target these influencers for marketing a given new product, say by providing free samples or discounts. It is natural that before committing resources for targeting an influencer the marketer would be interested in validating the influence (or network value) of influencers returned. This requires digging deeper into such analytical questions as: who are their followers, on what actions (or products) they are influential, etc. However, the current approaches to identifying influencers largely work as a black box in this respect. The goal of this paper is to open up the black box, address these questions and provide informative and crisp explanations for validating the network value of influencers. We formulate the problem of providing explanations (called PROXI) as a discrete optimization problem of feature selection. We show that PROXI is not only NP-hard to solve exactly, it is NP-hard to approximate within any reasonable factor. Nevertheless, we show interesting properties of the objective function and develop an intuitive greedy heuristic. We perform detailed experimental analysis on two real world datasets - Twitter and Flixster, and show that our approach is useful in generating concise and insightful explanations of the influence distribution of users and that our greedy algorithm is effective and efficient with respect to several baselines

Networks in economics: a perspective on the literature

The Oxford Handbook of the Economics of Networks represents the frontier of research into how and why networks they form, how they influence behavior, how they help govern outcomes in an interactive world, and how they shape collective ..

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

Hybrid R&D

We develop a model of R&D competition and collaborationin which individual firms carry out independent in-house researchand also undertake joint research projects with other firms. Weexamine the impact of collaboration on in-house research andexplore the circumstances under which a hybrid organization ofR&D which combines the two is optimal for firms andsociety. We find that investments in independent research and injoint research are complementary: an increase in the number ofjoint projects also increases in-house research. Firm profits arehighest under a hybrid organization if the number of firms issmall (less than 5) while they are highest with pure in-houseresearch if the number of firms is large (5 or more). However,social welfare is maximized under a hybrid organization of R&D inall cases. Our analysis also yields new results on the role ofcooperative R&D. We find that non-cooperative decision making byfirms leads to larger R&D investments and higher social welfarethan fully cooperative decision making. However, a hybrid form ofdecision making where there is bilateral cooperation in jointprojects and non-cooperative decision making in in-house researchyields the highest level of welfare in concentrated industries.

Heterogeneity and Networks

© 2018 Elsevier B.V. This chapter shows that networks can have large and differentiated effects on behavior and then argues that social and economic pressures facilitate the formation of heterogeneous networks. Thus networks can play an important role in understanding the wide diversity in human behavior and in economic outcomes