4 resultados para High technology industries - Management

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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From the institutional point of view, the legal system of IPR (intellectual property right, hereafter, IPR) is one of incentive institutions of innovation and it plays very important role in the development of economy. According to the law, the owner of the IPR enjoy a kind of exclusive right to use his IP(intellectual property, hereafter, IP), in other words, he enjoys a kind of legal monopoly position in the market. How to well protect the IPR and at the same time to regulate the abuse of IPR is very interested topic in this knowledge-orientated market and it is the basic research question in this dissertation. In this paper, by way of comparing study and by way of law and economic analyses, and based on the Austrian Economics School’s theories, the writer claims that there is no any contradiction between the IPR and competition law. However, in this new economy (high-technology industries), there is really probability of the owner of IPR to abuse his dominant position. And with the characteristics of the new economy, such as, the high rates of innovation, “instant scalability”, network externality and lock-in effects, the IPR “will vest the dominant undertakings with the power not just to monopolize the market but to shift such power from one market to another, to create strong barriers to enter and, in so doing, granting the perpetuation of such dominance for quite a long time.”1 Therefore, in order to keep the order of market, to vitalize the competition and innovation, and to benefit the customer, in EU and US, it is common ways to apply the competition law to regulate the IPR abuse. In Austrian Economic School perspective, especially the Schumpeterian theories, the innovation/competition/monopoly and entrepreneurship are inter-correlated, therefore, we should apply the dynamic antitrust model based on the AES theories to analysis the relationship between the IPR and competition law. China is still a developing country with relative not so high ability of innovation. Therefore, at present, to protect the IPR and to make good use of the incentive mechanism of IPR legal system is the first important task for Chinese government to do. However, according to the investigation reports,2 based on their IPR advantage and capital advantage, some multinational companies really obtained the dominant or monopoly market position in some aspects of some industries, and there are some IPR abuses conducted by such multinational companies. And then, the Chinese government should be paying close attention to regulate any IPR abuse. However, how to effectively regulate the IPR abuse by way of competition law in Chinese situation, from the law and economic theories’ perspective, from the legislation perspective, and from the judicial practice perspective, there is a long way for China to go!

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This dissertation comprises three essays on the topic of industrial organization. The first essay considers how different intellectual property systems can affect the incentives to invest in R&D when innovation is cumulative. I introduce a distinction between plain and sophisticated technological knowledge, which plays a crucial role in determining how different appropriability rules affect the incentives to innovate. I argue that the positive effect of weak intellectual property regimes on the sharing of intermediate technological knowledge vanishes when technological knowledge is sophisticated, as is likely to be the case in many high tech industries. The second essay analyzes a two-sided market for news where advertisers may pay a media outlet to conceal negative information on the quality of their own product (paying positive to avoid negative) and/or to disclose negative information on the quality of their competitors products (paying positive to go negative). It is shown that whether advertisers have negative consequences on the accuracy of media reports or not, ultimately depends on the extent of correlation among advertisers products. The third essay considers the role of social learning in the diffusion of a new technology. A population of agents can choose between two risky technologies: an old one for which they know the expected outcome, and a new one for which they have only a prior. Different environments are confronted. In the benchmark case agents are isolated and can perform costly experiments to infer the quality of the new technology. In the other cases agents are settled in a network and can observe the outcomes of neighbors. We observe that in expectations the quality of the new technology may be overestimated when there is a network spread of information.

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Electronic applications are nowadays converging under the umbrella of the cloud computing vision. The future ecosystem of information and communication technology is going to integrate clouds of portable clients and embedded devices exchanging information, through the internet layer, with processing clusters of servers, data-centers and high performance computing systems. Even thus the whole society is waiting to embrace this revolution, there is a backside of the story. Portable devices require battery to work far from the power plugs and their storage capacity does not scale as the increasing power requirement does. At the other end processing clusters, such as data-centers and server farms, are build upon the integration of thousands multiprocessors. For each of them during the last decade the technology scaling has produced a dramatic increase in power density with significant spatial and temporal variability. This leads to power and temperature hot-spots, which may cause non-uniform ageing and accelerated chip failure. Nonetheless all the heat removed from the silicon translates in high cooling costs. Moreover trend in ICT carbon footprint shows that run-time power consumption of the all spectrum of devices accounts for a significant slice of entire world carbon emissions. This thesis work embrace the full ICT ecosystem and dynamic power consumption concerns by describing a set of new and promising system levels resource management techniques to reduce the power consumption and related issues for two corner cases: Mobile Devices and High Performance Computing.

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My PhD project was focused on Atlantic bluefin tuna, Thunnus thynnus, a fishery resource overexploited in the last decades. For a better management of stocks, it was necessary to improve scientific knowledge of this species and to develop novel tools to avoid collapse of this important commercial resource. To do this, we used new high throughput sequencing technologies, as Next Generation Sequencing (NGS), and markers linked to expressed genes, as SNPs (Single Nucleotide Polymorphisms). In this work we applied a combined approach: transcriptomic resources were used to build cDNA libreries from mRNA isolated by muscle, and genomic resources allowed to create a reference backbone for this species lacking of reference genome. All cDNA reads, obtained from mRNA, were mapped against this genome and, employing several bioinformatics tools and different restricted parameters, we achieved a set of contigs to detect SNPs. Once a final panel of 384 SNPs was developed, following the selection criteria, it was genotyped in 960 individuals of Atlantic bluefin tuna, including all size/age classes, from larvae to adults, collected from the entire range of the species. The analysis of obtained data was aimed to evaluate the genetic diversity and the population structure of Thunnus thynnus. We detect a low but significant signal of genetic differentiation among spawning samples, that can suggest the presence of three genetically separate reproduction areas. The adult samples resulted instead genetically undifferentiated between them and from the spawning populations, indicating a presence of panmictic population of adult bluefin tuna in the Mediterranean Sea, without different meta populations.