Patent Protection with Cooperative R&D Option

We investigate R&D incentive under patent protection with cooperation option. Chowdhury [Economics Letters, 2005, 89(1), 120-126] claims that patent protection may decrease R&D incentive when the tournament effect (TE) is negative. However, We show that patent protection in the presence of R&D cooperation option always increases R&D incentive. In addition, to increase R&D incentive, this option strictly dominates imitation and may dominate royalty licensing under patent protection, introduced by Mukherjee [Economics Letters, 2006, 93(2), 196-201].R&D investment; Patent protection; Cooperative R&D

Patent Protection with Cooperative R&D Option

We investigate R&D incentive under patent protection with cooperation option. Chowdhury [Economics Letters, 2005, 89(1), 120-126] claims that patent protection may decrease R&D incentive when the tournament effect (TE) is negative. However, We show that patent protection in the presence of R&D cooperation option always increases R&D incentive. In addition, to increase R&D incentive, this option strictly dominates imitation and may dominate royalty licensing under patent protection, introduced by Mukherjee [Economics Letters, 2006, 93(2), 196-201].R&D investment; Patent protection; Cooperative R&D

Patent Protection with Licensing

This note gives a short proof that both fixed-fee and royalty licensing under patent protection can always create higher R&D investment.R&D investment; Patent protection; Licensing

MIXTURE MODELS FOR INTERVAL CENSORED OUTCOMES

Silent events such as the first detectable HIV infection, the onset of Type 2 diabetes and prostate cancer progression are often ascertained by diagnostic tests and/or self-reports that are scheduled periodically. In such applications, we only observe the time to the event of interest to lie between the times of last negative and the first positive tests, resulting in interval-censored observations. In addition, in some medical studies, a substantial proportion of participants may experience the events before the study, so-called prevalent cases, or participants may never experience the event, that is regarded as non-susceptible cases (or indolent cancer or long-term survivor). In this dissertation, I develop mixture models for the analysis of heterogeneous survival data subject to interval-censoring. The first chapter of this dissertation is motivated by a study of the effects of maternal and infant antiretroviral therapy on the sensitivity of DNA PCR diagnostic tests in detecting HIV infection in infants born to HIV-positive mothers. We apply a mixture model to evaluate the association of a set of predictors with an interval-censored time to first detectable DNA PCR test, while accounting for the subset of infants who test positive at birth. The mixture model is applied to data from the Pediatric AIDS Collaborative Transmission Study and the Women and Infants Transmission Study to evaluate the effects of maternal/infant antiretroviral therapy in HIV subtype B infected mother-infant pairs. In Chapter 2, we propose a parametric mixture model for interval censored time to event outcomes, while relaxing the commonly used proportional hazards assumption. The proposed model is applied to data collected in the National Health and Nutrition Examination Survey to evaluate risk factors of Type 2 diabetes. Chapter 3 is motivated by a Canary Prostate Active Surveillance Study (PASS) where the time to cancer progression (i.e., biopsy upgrade) is of primary interest. We propose a semiparametric mixture model to handle misclassification of progressed cancer at baseline and non-susceptible cases (or, indolent cancer). In addition, we account for imperfect diagnostic tests at each visit and risk factors that change over time in the proposed model. Extensive simulation studies are conducted to assess the performance of the proposed approaches with/without mixture components. The proposed approach is applied to the Canary Prostate Active Surveillance Study to evaluate the effects of factors on the risk of cancer progression and estimate the indolent fraction under a range of sensitivity rates of biopsy

Endogenous time preference: evidence from Australian households' behaviour

Recently, the focus has been increasingly on the importance of endogenous time preference and its varying degrees of marginal impatience. Two types of marginal impatience can change the representative household's endogenous discount function: increasing (Koopmans-Uzawa type)and decreasing (Becker-Mulligan type), which are induced by current consumption and the investment on future-oriented capital, respectively. By modifying the endogenous discount factor in a small-open-economy RBC model, the equilibrium levels of the turnover in future-oriented capital and current consumption are obtained in a reduced form, which overcomes the non-stationarity problem. The relation between current consumption and the turnover in future-oriented capital is consistent with the empirical evidence from Australia

The State of Social Computing Research: A Literature Review and Synthesis using the Latent Semantic Analysis Approach

Social computing is an emerging research discipline. The number of publications on social computing has increased by 120% annually in the past four years. Despite the proliferation of studies in this area there is a lack of comprehensive, unified, and systematic characterization of this phenomenon. The definition and characterization of this phenomenon in the extant literature is diverse and fragmented. In this paper we attempt to bring some clarity by synthesizing and summarizing the extant literature in this area. We use Latent Semantic Analysis (LSA), a text mining and natural language processing technique, to summarize the state of social computing research. The results show that there are 27 unique dimensions which currently characterize this concept. LSA also reveals that, the 266 articles found in the literature predominantly focus on three major research themes namely, Knowledge Discovery, Knowledge Sharing, and Content Management in the Social Computing context

Introduction to Digital Social Media in Enterprise Minitrack

N/