The Effects of Patent Attributes and Patent Litigation on Control Rights, Alliance Formation and Technological Innovation

My dissertation consisting of three essays focuses on the role of technological innovations in value distribution within R&D alliance, and the impact of patent litigation on R&D alliance formation and technological innovation. Essays one and two are intended to extend signaling theory with transaction cost economics (TCE) and social embeddedness perspective. Essays two and three investigate the consequences of patent litigation on R&D alliance formation and technological search, respectively. Essay one investigates the empirical relationships between patent attributes and allocation of control rights, and the relationships between patent attributes and up-front payment in R&D alliance contracts. Patent attributes of focal innovations signal varying dimensions of patent quality. With a sample of R&D alliance contracts between biotechnology and pharmaceutical firms, I find that patent novelty decreases the number of control rights won by biotech firms and that self-citation reduces the amount of upfront payment paid to biotech firms. Essay two examines the effect of firms being litigious about patent enforcement on subsequent R&D alliance formation. Empirical results show that being litigious about patent enforcement increases subsequent R&D alliances and that repeat ties of litigious firms reduce the positive effect of being litigious on R&D alliance formation. Essay two extends signaling theory by highlighting the understudied role of repeat signal to unintended signal receivers. Essay three examines the effects of patent litigation on technological exploration and exploitation of litigious firms. With a sample of public firms in biotechnology and pharmaceutical industry, empirical result suggests that repeat patent litigation is disruptive to exploitative and explorative innovations. This study makes a small step in investigating the unintended consequences of profiting from innovations by repeatedly resorting to patent litigation

Exploration on the Cultivation of Comprehensive Ability of Construction Cost Students in Private Universities

In view of the serious disadvantages such as the homogenization brought by the rapid expansion of the scale of Chinese colleges and universities, college graduates can not meet the needs of talents, the comprehensive ability of engineering cost graduates is weak, through analyzing the comprehensive ability of college students and the comprehensive ability that engineering cost students should have, put forward on the basis of professional knowledge education, strengthen the practical education, reform the teaching mode, Promote the process of ideological and political education, give full play to the educational role of private colleges and universities, and train high-quality professional talents with comprehensive development

Modeling and Managing Longevity Risk: Models and Applications

With the threat of longevity risk to the insurance industry becoming increasingly apparent in recent years, insurers and reinsurers are concerned about how to better model and manage longevity risk. However, modeling and managing longevity risk is not trivial, due in part to its systematic nature and in part to the excessive amount of risk factors that constitute the risk. The theme of this thesis is modeling and managing longevity risk. In particular, this thesis focuses on four types of uncertainties among all possible risk factors. These four risk factors include 1) mortality jump risk; 2) longevity drift risk; 3) population basis risk; and 4) cohort mismatch risk. In the current literature, a number of stochastic mortality models with transitory jump effects have been proposed to capture mortality jump risk. Rather than modeling the age pattern of jump effects explicitly, most of the existing models assume that the distributions of jump effects and general mortality improvements across ages are identical. Nevertheless, this assumption does not appear to be in line with what can be observed from historical data. In this thesis, we addressed this disconnect by introducing a Lee-Carter variant that captures the age pattern of mortality jumps by a distinct collection of parameters. The model variant was then further generalized to permit the age pattern of jump effects to vary randomly. We illustrated the two proposed models with mortality data from the United States and English and Welsh populations, and further used these data to value hypothetical mortality bonds with similar specifications to the Atlas IX Capital Class B note that was launched in 2013. The features we considered were found to have a significant impact on the estimated prices. We then explored longevity drift risk, which is the uncertainty about the mortality trend itself. We tackled longevity drift risk by introducing the locally-linear CBD model in which the drifts that govern the expected mortality trend are allowed to follow a stochastic process. Compared to the original CBD model, this specification results in median forecasts that are more consistent with recent trends and more robust relative to changes in the data sample period. Furthermore, the proposed model also yields wider prediction intervals that may better reflect the possibilities of future trend changes. To mitigate the risk associated with changes in drifts, we proposed a new hedging method called the generalized state-space hedging method which demands less stringent assumptions. The proposed method allows hedgers to extract more hedge effectiveness out of a hedging instrument, and is therefore useful when there are only a few traded longevity securities in the market. To incorporate population basis risk, we further extended the proposed generalized state-space hedging method to a multi-population setting. In this extended hedging method, the hedging strategy is derived by first reformulating the assumed multi-population stochastic mortality model in a state-space representation, and then considering the sensitivities of the hedge portfolio and the liability being hedged to all relevant hidden states. Inter alia, this method allowed us to decompose the underlying longevity risk into components arising solely from the hidden states that are shared by all populations and components stemming exclusively from the hidden states that are population-specific. The latter components collectively represent an explicit measure of the population basis risk involved. Through this measure, a new metric called standardized basis risk profile was developed. This metric allowed us to assess the relative levels of population basis risk that q-forwards with different reference populations, reference ages, and times-to-maturity may lead to. The proposed methodologies were illustrated using real mortality data from various national populations. Similar to population basis risk, cohort mismatch risk is another risk that is related to population differences when conducting an index-based longevity hedge. It arises when the hedger chooses to link hedging instruments to different cohorts. Although existing index-based longevity hedging strategies mitigate the risk associated with period effects, they often overlook the risk associated with different cohorts. The negligence of cohort effects may lead to sub-optimal hedge effectiveness if the liability being hedged is a deferred pension or annuity which involves cohorts that are not covered by the data sample. We proposed a new hedging strategy that incorporates both period and cohort effects. The resulting longevity hedge is a value hedge which reduces the uncertainty surrounding the τ-year ahead value of the liability being hedged in terms variance or Value-at-Risk. We further developed a method to expedite the evaluation of a value longevity hedge. By utilizing the fact that the innovations of the stochastic processes for the period and cohort effects are not serially correlated, the proposed method avoids the need for nested simulations that are generally required when evaluating a value hedge

Environmental and economic sustainability of key sectors in China's steel industry chain: An application of the Emergy Accounting approach

Abstract Increasing urbanization day–by–day requires new housing and transportation infrastructures. As a consequence, demand for steel – a basic material for buildings construction as well as for vehicles and railroads – would also increases. This study applies Emergy Accounting (EMA) to assess the Chinas steel industry environmental performance and to identify key application sectors. Subsequently, this study calculates emergy–based indicators capable to assess the present economic performance, environmental sustainability, and land resource appropriate utilization. Building on these indicators, changes of sustainability scenarios in key application sectors are also investigated, with special focus on increased use of recycled steel. The results show that the environmental impacts of steel use in downstream sectors, specially in the Housing and Vehicles Sectors, are significantly higher. Furthermore, the downstream sectors also have a very large requirement for embodied land. Additionally, the Emergy Benefit Ratio (EBR) shows non-negligible advantages to China derived from importing raw iron from abroad at international market prices. Finally, when the recycling rate of scrap steel increases, the performance of downstream sectors improves, with the Vehicle sector showing the most significant changes. Although the benefits of steel-based economy to society are clear, multidimensional sustainability concerns and international competition for primary resources necessitate a transition towards increased recycling and innovative materials within a strictly enforced "circular economy" policy

A Method to Detect AAC Audio Forgery

Advanced Audio Coding (AAC), a standardized lossy compression scheme for digital audio, which was designed to be the successor of the MP3 format, generally achieves better sound quality than MP3 at similar bit rates. While AAC is also the default or standard audio format for many devices and AAC audio files may be presented as important digital evidences, the authentication of the audio files is highly needed but relatively missing. In this paper, we propose a scheme to expose tampered AAC audio streams that are encoded at the same encoding bit-rate. Specifically, we design a shift-recompression based method to retrieve the differential features between the re-encoded audio stream at each shifting and original audio stream, learning classifier is employed to recognize different patterns of differential features of the doctored forgery files and original (untouched) audio files. Experimental results show that our approach is very promising and effective to detect the forgery of the same encoding bit-rate on AAC audio streams. Our study also shows that shift recompression-based differential analysis is very effective for detection of the MP3 forgery at the same bit rate

A scheme for anaerobic digestion modelling and ADM1 model calibration

Anaerobic digestion (AD) is a technology that produces biogas, also known as renewable natural gas, from organic waste materials under the activity of anaerobic microorganisms. In recent years, an increasing attention on energy produced from renewable resources has led to the need and development of tools helping with improving the process performance and design of AD, such as the Anaerobic Digestion Model No.1 (ADM1). ADM1 is a process-based model that can predict the biogas yield and identify potential prohibitions in the AD process from the properties of the feedstock and inoculum. Initial values of state variables and model parameters need to be calibrated when applying ADM1 to a particular feedstock. In this study, an ADM1 model using differential algebraic equations (DAE) system, called DAE ADM1, was developed. Specifically, the influence of the initial values of AD process state variables on the calibration of model stoichiometric and kinetic parameters were investigated, by comparing them with literature data, by highlighting their high impact on the model setup