10,082 research outputs found
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
Lepton number violation in Little Higgs model
In this note we examine the constraints imposed by muon anomalous magnetic
moment () and 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
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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 ..
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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.
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