The Public-Private Partnership (P3 or PPP) model has been proposed as an alternative delivery system to address funding shortage problems associated with large-scale projects. Appropriately allocating and managing risks among project participants is critically important for a P3 project's success. This thesis focuses on one of the tools to manage revenue risk, the revenue guarantee, where a guarantor compensates a concessionaire with a predetermined amount of revenue in the event of a revenue shortfall. It is a form of real option—specifically a put option if a premium is paid for the downside protection or a collar option if potential upside revenue is traded for the protection. Previous research has explored the purpose and valuation of revenue guarantee options. This study focuses on the feasibility of utilizing a guarantee in US P3 highway projects through preparatory study and field investigation. In the preparatory phase, the work examines existing revenue risk management methods and how revenue guarantee options supplement them while also proposing an implementation framework. Additionally, it discusses a new option type,a collar option, including its concept, benefits, applicability, and valuation. In the field investigation phase, the preparatory work is synthesized into interview protocols that are used to seek market perspectives on revenue risks and revenue guarantee feasibility. Twenty people representing government officials, concessionaires, financial advisors and lending institutions were interviewed. The interview results indicated that a revenue guarantee shows promise as a viable tool, and the government should be willing to provide one. The decision to utilize a revenue guarantee depends on funding method selection, a public agency's institutional capacity, and the effectiveness of alternative risk mitigation approaches. Suggestions for implementation, such as applicable projects and a guarantee triggering criterion, are also provided. / Ph. D.

In recent decades, revenue diversification has become a prevalent practice in state and local government finance. The trend of revenue diversification, according to the portfolio theory, has far-reaching implication for public financial management as it may change revenue stability, which has been an important policy objective for state and local government administrators. This study explores how revenue diversification affects revenue stability from both empirical and theoretical perspectives. Drawing on portfolio theory and regional science literature, this study develops a theoretical framework to explain how the effect of revenue diversification on revenue volatility of sub-national governments varies in terms of its economic base instability. To empirically test the theoretical framework, an econometric model that explores a series of factors that could affect revenue stability is estimated using socioeconomic and fiscal data of 156 Georgia county governments and 47 state governments during the years 1986-2004. The findings indicate that revenue diversification affects revenue stability conditional on the instability of a jurisdiction’s economic base. The county level analysis suggests revenue diversification significantly increases the revenue instability of a county that has a stable economic base and the revenue stabilizing effect of diversification is enhanced as an economic base becomes more unstable. However, the state level analysis shows that revenue diversification significantly reduces revenue volatility for a state that has a stable economic base and the revenue stabilizing effect of diversification decreases when an economic base gets more unstable. An important policy implication of the dissertation is that the degree of revenue diversification should be gauged by the condition of its corresponding economic base in order to achieve the goal of revenue stability.

The purpose of this study was to determine the effects of interactions with IRS employees on tax practitioners' attitudes toward the IRS. The mission of the IRS is to inspire the highest degree of public confidence as it collects the proper amount of tax revenues at the least cost to the public. The IRS believes it must project a favorable image to tax practitioners in order to foster a high level of support for its mission. Prior surveys of tax practitioners found that practitioners have generally unfavorable attitudes toward the IRS and its employees. This study examined whether the unfavorable attitudes result from interactions with IRS employees, and provides empirical evidence of the effects of interactions with IRS employees on tax practitioners' attitudes toward the IRS.

Abstract The purpose of this study is to investigate how big data solutions in the Swedish healthcare system can generate a revenue. As technology continues to evolve, the use of big data is beginning to transform processes in many different industries, making them more efficient and effective. The opportunities presented by big data have been researched to a large extent in commercial fields, however, research in the use of big data in healthcare is scarce and this is particularly true in the case of Sweden. Furthermore, there is a lack in research that explores the interface between big data, healthcare and revenue models. The interface between these three fields of research is important as innovation and the integration of big data in healthcare could be affected by the ability of companies to generate a revenue from developing such innovations or solutions. Thus, this thesis aims to fill this gap in research and contribute to the limited body of knowledge that exists on this topic. The study conducted in this thesis was done via qualitative methods, in which a literature search was done and interviews were conducted with individuals who hold managerial positions at Region Västerbotten. The purpose of conducting these interviews was to establish a better understanding of the Swedish healthcare system and how its structure has influenced the use, or lack thereof, of big data in the healthcare delivery process, as well as, how this structure enables the generation of revenue through big data solutions. The data collected was analysed using the grounded theory approach which includes the coding and thematising of the empirical data in order to identify the key areas of discussion. The findings revealed that the current state of the Swedish healthcare system does not present an environment in which big data solutions that have been developed for the system can thrive and generate a revenue. However, if action is taken to make some changes to the current state of the system, then revenue generation may be possible in the future. The findings from the data also identified key barriers that need to be overcome in order to increase the integration of big data into the healthcare system. These barriers included the (i) lack of big data knowledge and expertise, (ii) data protection regulations, (iii) national budget allocation and the (iv) lack of structured data. Through collaborative work between actors in both the public and private sectors, these barriers can be overcome and Sweden could be on its way to transforming its healthcare system with the use of big data solutions, thus, improving the quality of care provided to its citizens. Key words: big data, healthcare, Swedish healthcare system, AI, revenue models, data-driven revenue models

Thesis (MBA.) -- University of Limpopo, 2007 / The Department of Health and Social Development in Limpopo endeavors to efficiently and effectively manage revenue collection. The study analyzed the revenue collection for the Capricorn district hospitals from 2001 to 2006 by identifying problems and possible solutions related to revenue collection. A quantitative analysis of data has been obtained from in- depth structured interviews and revenue records. An analytic retrospective study design was used. All revenue records from 2001/2002 to 2006/2007, financial managers, revenue clerks, and clients /patients who came to request credit from each hospital constituted the population of the study. The findings were that in 2001/2002 none of the hospitals were able to attain the revenue targets. In 2005/2006 revenue targets were increased by almost double the amount however all hospitals were able to attain the revenue targets as prescribed. It implies that the hospitals were able to collect more revenue than in the previous financial year. It has been noted that the appointment of CEOs has brought a tremendous change in revenue collection. It has been identified that revenue is the life blood for a country or institution. The institutions need commitment of all stakeholders to collect revenue.

Robust Airline Fleet Assignment Barry C. Smith 140 Pages Directed by Dr. Ellis L. Johnson Fleet assignment models are used by many airlines to assign aircraft to flights in a schedule to maximize profit. Major airlines report that the use of fleet assignment models increases annual profits by more than $100 million. The results of fleet assignment models affect subsequent planning, marketing and operational processes within the airline. Anticipating these processes and developing solutions favorable to them can further increase the benefits of fleet assignment models. We propose to produce fleet assignment solutions that increase planning flexibility and reduce cost by imposing station purity, limiting the number of fleet types allowed to serve each airport in the schedule. We demonstrate that imposing station purity on the fleet assignment model can limit aircraft dispersion in the network and make solutions more robust relative to crew planning, maintenance planning and operations. Because station purity can significantly degrade computational efficiency, we develop a solution approach, Station Decomposition, which takes advantage of airline network structure. Station Decomposition uses a column generation approach to solving the fleet assignment problem; we further improve the performance of Station Decomposition by developing a primal-dual method that increases the solution quality and model efficiency. Station Decomposition solutions can be highly fractional; we develop a fix and price heuristic to efficiently find integer solutions to the fleet assignment problem. Airline profitability can be increased if fleet assignment models anticipate the effects of marketing processes such as revenue management. We develop an approach, ODFAM, which incorporates airline revenue management effects into the fleet assignment model. We develop an approach to incorporate station purity and ODFAM using a combination of column and cut generation. This approach can increase airline profit up to $27 million per year.

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This study investigates the revenue performance of choice-based revenue management (RM) systems in various business environments. Previous research conducted using simulated data suggests that incremental revenue gains of up to 15% are to be expected when choice-based RM techniques are employed. In addition, despite the novelty of these techniques, the implementation of choice-based RM systems is considered to be feasible at large global corporations. The revenue potential and the ease of execution associated with the choice-based methods are examined in the context of a large hotel chain. Customer-centric data which includes transaction and time of booking availability information is collected for five hotel properties located in the continental US. The customer preference for hotel products and their attributes is determined using discrete choice and other ad hoc models of demand. Optimization techniques that account for the customer purchasing behavior are employed to compute the capacity control policies the hotel operator should follow to maximize its revenues. Results indicate that collecting customer-centric data from today s RM systems is a time-consuming task. In the environment in which the study hotels operate, the choice-based RM systems report incremental revenue gains that are dependent on how the purchasing behavior models are formulated. In capacity constrained regimes that are the focus of RM, revenue gains of up to 2% are typically noted. In controlled environments in which the customer purchasing behavior can be better asserted, the incremental revenue gains range between 1% and 14%. These findings suggest that the execution of the choice-based RM, while feasible, needs to be preceded by the implementation of efficient and, most likely, expensive data collection procedures. The incremental revenue gains, consistent with those reported in the literature, indicate that RM users can substantially benefit from the use of the choice-based RM.

Thesis (M.S.)--University of Texas at El Paso, 2008. / Title from title screen. Vita. CD-ROM. Includes bibliographical references. Also available online.

Thesis (M.B.A.)--University of Hong Kong, 1997. / Includes bibliographical references.