Thesis (Ph. D.)--West Virginia University, 2009. / Title from document title page. Document formatted into pages; contains vii, 122 p. : col. ill. Includes abstract. Includes bibliographical references.

Thesis (Ph. D.)--University of Western Sydney, Hawkesbury, 1995. / "March 1995, minor revision and correction December 1996." Includes bibliographical references (p. 327-346).

Thesis--Auburn University, 2005. / Abstract. Vita. Includes bibliographic references (p.89).

This thesis work describes the formulation of a Bayesian approach along with new tools to systematically reduce uncertainty in Research&Development (R&D) alternatives. During the initial stages of R&D many alternatives are considered and high uncertainty exists for all the alternatives. The ideal approach in addressing the many R&D alternatives is to find the one alternative which is stochastically dominant i.e. the alternative which is better in all possible scenarios of uncertainty. Often a stochastically dominant alternative does not exist. This leaves the R&D manager with two alternatives, either to make a selection based on user defined utility function or to gather more information in order to reduce uncertainty in the various alternatives. From the decision makers perspective the second alternative has more intrinsic value, since reduction of uncertainty will improve the confidence in the selection and further reduce the high downside risk involved with the decisions made under high uncertainty. The motivation for this work is derived from our preliminary work on the evaluation of biorefiney alternatives, which brought into limelight the key challenges and opportunities in the evaluation of R&D alternatives. The primary challenge in the evaluation of many R&D alternatives was the presence of uncertainty in the many unit operations within each and every alternative. Additionally, limited or non-existent experimental data made it infeasible to quantify the uncertainty and lead to inability to develop an even simple systematic strategy to reduce it. Moreover, even if the uncertainty could be quantified, the traditional approaches (scenario analysis or stochastic analysis), lacked the ability to evaluate the key group of uncertainty contributors. Lastly, the traditional design of experiment approaches focus towards reduction in uncertainty in the parameter estimates of the model, whereas what is required is a design of experiment approach which focuses on the decision (selection of the key alternative). In order to tackle all the above mentioned challenges a Bayesian framework along with two new tools is proposed. The Bayesian framework consists of three main steps: a. Quantification of uncertainty b. Evaluation of key uncertainty contributors c. Design of experiment strategies, focussed on decision making rather than the traditional parameter uncertainty reduction To quantify technical uncertainty using expert knowledge, existing elicitation methods in the literature (outside chemical engineering domain) are used. To illustrate the importance of quantifying technical uncertainty, a bio-refinery case study is considered. The case study is an alternative for producing ethanol as a value added product in a Kraft mill producing pulp from softwood. To produce ethanol, a hot water pre-extraction of hemi-cellulose is considered, prior to the pulping stage. Using this case study, the methodology to quantify technical uncertainty using experts' knowledge is demonstrated. To limit the cost of R&D investment for selection or rejection of an R&D alternative, it is essential to evaluate the key uncertainty contributors. Global sensitivity analysis (GSA) is a tool which can be used to evaluate the key uncertainties. But quite often global sensitivity analysis fails to differentiate between the uncertainties and assigns them equal global sensitivity index. To counter this failing of GSA, a new method conditional global sensitivity (c-GSA) is presented, which is able to differentiate between the uncertainties even when GSA fails to do so. To demonstrate the value of c-GSA many small examples are presented. The third and the last key method in the Bayesian framework is the decision oriented design of experiment. Traditional 'Design of Experiment' (DOE) approaches focus on minimization of parameter error variance. In this work, a new "decision-oriented" DOE approach is proposed that takes into account how the generated data, and subsequently, the model developed based on them will be used in decision making. By doing so, the parameter variances get distributed in a manner such that its adverse impact on the targeted decision making is minimal. Results show that the new decision-oriented DOE approach significantly outperforms the standard D-optimal design approach. The new design method should be a valuable tool when experiments are conducted for the purpose of making R&D decisions. Finally, to demonstrate the importance of the overall Bayesian framework a bio-refinery case study is considered. The case study consists of the alternative to introduce a hemi-cellulose pre-extraction stage prior to pulping in a thermo-mechanical pulp mill. Application of the Bayesian framework to address this alternative, results in significant improvement in the prediction of the true potential value of the alternative.

I study the role of licensed technologies in the R&D development process, the knowledge assimilation mechanism and the patent litigation procedure. I document that the use and adoption of licensed technologies is not a linear process and it has important strategic consequences. First, I focus on the joint effect of external and internal technologies and possible firm-level drivers of this relation. I find that, on average, internal R&D and licensing investments are neither complements nor substitutes. However, firms with higher levels of absorptive capacity, economies of scope, and past licensing experience are able to create positive synergies by combining the two types of investments. In addition, I find that the integration and the adoption of external technology may be limited by internal knowledge accumulation. Firms that experience an inward oriented knowledge accumulation process need to balance the trade-off between internal knowledge reliance and external knowledge assimilation. The negative relation between internal and external knowledge is positively mitigated by two organizational factors: absorptive capacity and the level of decentralization. Finally, assuming that companies are able to adopt external technologies, I find that licensed patents are more reliable than internal ones. In other words, external patents increase the probability of winning a patent lawsuit. Under this circumstance, firms are able to reduce patent uncertainty, limit market entry, and protect future revenue streams.

This dissertation attempts to contribute to our understanding of how firms can manage and benefit from its research and development (R&D) communities. In the first essay, we examine how established firms can leverage a broad R&D community to invent successfully during the early stage of a technological change. We find significant inventions by incumbents outside the existing dominant designs and relate their success to their willingness to search novel areas, explore scientific knowledge in the public domain, and form alliances with a balanced portfolio of partners. We find support for the hypotheses using data from the global semiconductor industry between 1989 and 2002. In the second essay, we examine a classical choice within an R&D community: cooperation or competition with other firms along a technology supply chain. We find that the answer depends not just on the transaction costs, strength of intellectual property protection rights, and asset cospecialization in the buyers' industries, but also the supplier's knowledge transfer capability and a typical buyer's productivity in developing licensed inventions. For instance, the effect of asset cospecialization on licensing is moderated by the factors that affect the buyers' productivity in developing external technology. Additionally, factors that reduce the buyers' development productivity can be mitigated by the supplier's knowledge transfer capability. We find empirical supports for these predictions using a cross-industry panel dataset of a sample of 345 U.S. small technology-based firms for the 1996-2007 period. In the third essay, I develop two game theoretical models to address how research competition from academic researchers affects firms' openness in disclosing intermediate R&D outcomes. Both models predict that such competition increases the firm's incentive to publish research findings, even though the firm would not have had such an incentive without the presence of the competition. The models also suggest several conditions under which the effect takes place. I further discuss the implications of ownership fragmentation for research materials within the scientific community and academic researchers' engagement in entrepreneurial activities. As implied by my models, these phenomena might instigate withholding of research findings by firms.

Tez (Yüksek Lisans) - Süleyman Demirel Üniversitesi, Sosyal Bilimler Enstitüsü, İşletme Anabilim Dalı, 2007. / Kaynakça var.

The objective of this thesis was to explore the nature of expenditure incurred on the internal development of software and its treatment in terms of the accounting and taxation frameworks to which it is subject. In fulfilling the primary objective the thesis had a number of subsidiary considerations. These included, firstly, a brief analysis of the approach of the software industry in South Africa to the taxation treatment of this type of software. The second consideration was a discussion and analysis of the taxation framework which differentiates between capital and revenue and the extent to which the receipts produced by internally developed software may be informative of the nature of the expenditure. The third was an analysis of the deductibility of expenditure incurred in the production of software with the fourth analysing the tests employed in the determination of whether expenditure is capital or revenue in nature. The fifth objective was to briefly analyse the accounting standards which find application in the determination of whether or not the software created can be considered a capital asset. The final subsidiary objective of the thesis was an analysis of the taxation framework applicable to software in respect of research and development incentives, as well as the position in the United States of America. Throughout the thesis the most apparent commonality is that there exists a significant level of uncertainty as to the taxation treatment of software both in South Africa and in America. The research concludes by stating that such uncertainty is prejudicial to the interests of research and development in relation to software.

This master thesis focuses on the analysis and design of accounting, tax and legal methods of research and development projects. In the first part of this thesis are mention a theoretical background of research and development projects. Another part deals with the management of research and development projects. The following part is a financial and strategic analysis and analysis of the current status of research and development projects in the community. The design part is determined by the accounting, tax and legal methodology for managing research and development projects and is designed to control process research and development project under the previous methodology and using SAP. In conclusion, the benefits of this methodology defined for the selected company.