In the past decade, a new entrepreneurial phenomenon aimed at seeding start-up companies has emerged across the globe: the social enterprise (SE) accelerator program. These accelerators focus on scaling social entrepreneurs by accelerating their journey to the market. Different actors like business reporters, entrepreneurs, and angel investors have expressed skepticism around the viability of the accelerator model. To research this sustainability, this thesis studied the revenue models of SE accelerators. Four semi-structured interviews were conducted with experts working at SE accelerators in Stockholm. These four identified getting revenue from partnerships, government institutions, and philanthropy and donations. Consulting contracts, equity shares and fees were not used by these four but were discussed as potential revenue streams. All respondents emphasized the importance of revenue model diversification and were currently working on strategies to act on this. Diversifying the revenue models of SE accelerators will increase the sustainability of their revenue models. This might be the first step from the focus of monetary gain towards a society where business is created to do good.

This thesis covers two separate studies. The first study, chapter 2, was conducted to evaluate whether there are additional economic returns from producing strawberries in the high tunnel compared to the open-field in Southeast Virginia. We develop and compare budgets for eight strawberry cultivars grown in the two environments and sold under three marketing strategies (pre-pick wholesale, pre-pick retail, and U-pick). Almost all cultivars in the high tunnel generated negative net revenues regardless of the marketing strategy. In contrast, net revenues from open-field cultivars were always positive. In the second study, chapter 3, we used a fractional multinomial logit model to estimate the effect of crop revenues, input costs, and fuel ethanol production on the joint acreages planted to eight U.S major crops (barley, corn, cotton, peanuts, rice, sorghum, soybeans, and wheat). We found a positive and statistically significant marginal effect of the expected peanuts' revenue on its acreage share. The expected corn revenue had a negative average marginal effect on soybean acreage share, and the effect of expected wheat revenue was positive on cotton acreage share and negative on rice acreage share. / Master of Science / This thesis covers two separate research studies. The first study, chapter 2}, was conducted to evaluate whether growing strawberries in a simple, low-cost, and passive heat structure known as a "high tunnel" would yield more profit (the difference between total revenues and total costs) compared to growing them outside in an open-field in Southeast Virginia. We estimate and compare differences between total revenues and costs for eight strawberry cultivars grown in the two environments and sold under three marketing strategies. The first two marketing strategies involve growers harvesting strawberries themselves. They can then either retail them (farm stands, farmers' markets, or in a similar setting: pre-pick retail) or sell them in bulk to be retailed by others (pre-pick wholesale). A third marketing strategy involves consumers visiting a farm and picking their own strawberries (U-pick). Almost all cultivars grown in the high tunnel structure resulted in a loss (negative difference between total revenues and costs) regardless of the marketing strategy. In contrast, cultivars produced in the open-field always generated a profit (positive total revenues and costs difference). In the second study, chapter 3, we estimated the effect of crop revenues, input costs, and fuel ethanol production on acreages planted to eight U.S major crops (barley, corn, cotton, peanuts, rice, sorghum, soybeans, and wheat), and we considered the fact that acreages allocated to one crop affect other crops' acreages. We found that increasing the expected revenue of peanuts leads to an increase in its acreage share. Increasing the expected revenue of corn leads to a decrease in soybeans' acreage share. Finally, increasing the expected revenue of wheat leads to an increase in the cotton acreage share and a decrease in the rice acreage share.

This thesis examines the use of tax incentives to promote foreign direct investment (FDI) in Thailand and the issues arising out of the way in which the Thai revenue system has chosen to implement these incentives. Thailand experiences sporadic political unrest, and has been affected by regional and global economic crises. Since FDI appears to increase economic growth and help the host country to achieve sustainable development, the Thai government has a clear policy to encourage FDI. Tax incentives have become a significant weapon in the Thai government’s arsenal for encouraging this aim. This thesis presents a detailed analysis of the tax incentives and the mechanisms used for their implantation. Analysis reveals that, unfortunately, the Thai government has also chosen to deliver the administration of tax incentives in to the hands of two separate bodies ─ the Revenue Department and the Board of Investment (BOI). This strategy is problematic because it creates unnecessary difficulties and uncertainty in the administration of incentives and promotes confusion among foreign investors. The jurisdictional problems inherent in the system of the dual allocation of tax incentive powers are highlighted in the landmark Minebea case, which involved conflicting interpretations by the Revenue Department and the BOI. In addressing these jurisdictional problems, this thesis examines norm conflict resolution principles in general and the lex specialis in particular, and argues that the Investment Promotion Act of 2001 (IPA 2001), being a special law, and so overrides the more general provisions of the Revenue Code. Two solutions are suggested in order to tackle the current problem: 1) to amend the IPA 2001 to specify methods of tax calculation and clearly define problematic terms and 2) to incorporate the tax incentive provisions provided for BOI-promoted companies into the Revenue Code. This is based on the premise that all tax matters, including tax incentives provisions, should be administered only by the revenue authority, i.e. the Revenue Department.

Many top market capitalization companies are information technology (IT) firms, including Apple, Google, Microsoft, and Facebook, each of which is valued at more than $300 billion. Facebook is less than 10 years old and is one of the top 10 companies in the world in terms of market capitalization. However, technologies change rapidly; website revenue—which once grew at a brisk rate—has slowed down, while mobile technology growth is increasing and technology trends are shifting toward cloud hosting and big data analytics. IT companies that have increased their R&D spending remain leaders throughout periods of technology change. Companies such as Facebook and Google have doubled and tripled their profits, respectively over` the past decade. In this dynamic environment, analysts play a critical role in evaluating IT company financial statements and estimating company sales and earnings per share (EPS). This study examines how changes in R&D spending are related to analysts’ sales and earnings estimate revisions. An analysis of data over a 20-year period shows that analysts typically revise their sales estimates based on changes in a company’s R&D expenditures. The correlation between analyst earnings estimates and R&D expenditures, however, varies based on company size and industry within the IT sector. Analysts play a particularly important role in small companies, where the correlation between R&D and sales changes is not as high as in large companies. Analysts are thus critical to the functioning of capital markets in the IT sector.

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This thesis examines the various impacts of the new revenue recognition accounting standard on software companies. It begins by explaining why the FASB and IASB updated the existing revenue recognition standard and then compares and contrasts the legacy GAAP to the upcoming GAAP standard. It then moves into a detailed analysis of the key changes affecting the software industry, specifically: intellectual property, the elimination of vendor specific objective evidence, and the principal versus agent consideration. Additionally, it examines software as a service in comparison to the historical model of software as a product and how the new standard will impact the direction of the software industry. Finally, it concludes with a discussion of investor considerations and how the standard will impact users of the financial statements. While there is abundant knowledge of the accounting change within the accounting industry, there is less knowledge and almost no quantifiable information for the public, which based on the various changes detailed, will result in a surprising material effect on software company financial statements.

A tariff policy is two-sided and may be compared to a wall. Every export from a country is some other country's import, and every tariff imposition, while apparently a domestic law to bring in a revenue or build up home industries, is, at the same time the means of keeping out some other country's exports. Too often, we look upon only one side of the wall--our own side. We are likely to regard the tariff as a means of controlling the inflow of foreign goods or as a means of raising revenue. But to understand the tariff policy and employ it to its fullest advantage or disadvantage we must be willing and capable of looking over the wall to understand the effect of a tariff--or any other commercial policy--on the aims and aspirations of other nations.

Master Thesis: Customer Lifetime Value - Application to Banking Sector Author: Zuzana Lajksnerová Abstract This thesis deals with the calculation of the customer life value for clients of second largest Czech commercial banks - Československá obchodní banka a.s.. The aim is to estimate the revenue each individual brings to the bank within the first year, two, four since creating a profile but also during the whole time he or she remains in their customer base. The first, theoretical part contains of structured overview of the modeling approach from available literature. In the second part, we develop two different models, which are subsequently applied on client data of 2.7 million ČSOB customers. The prediction takes into account both revenues from each product and probability that customer will use this product. For estimation of the two models we use several different econometric methods, thus linear regression, bootstrap, probit and multinomial logit. The results show that demographic data such as age and gender, as well as product related variables, greatly inuence the final level of value of customer. It is also shown that higher potential earnings are associated with men, people of working age and loyal customers.

Doctor of Philosophy / Department of Agricultural Economics / Michael Langemeier / This study focused on the inclusion of risk in efficiency measures to determine its impact on traditional efficiency scores. Previous research and theory suggests efficiency scores will be lower under risk and for risk averse individuals. Risk aversion may deter use of new production technologies and production levels may not be as high as under other risk preferences. Two data sets were used in the analysis. A panel data set of 256 farms from 1993-2010 was used to address the impact of risk measured as variability in outputs and downside risk on efficiency. A separate data set of 258 farms for 2008 was used with a corresponding risk preference score to determine the impact of risk preference on efficiency. The risk preference scores in the sample ranged from 5 to 86 where a smaller value represents stronger risk aversion. Data envelopment analysis was used to construct a nonparametric efficiency frontier and calculate cost- and revenue-based economic, overall, technical, allocative, and scale efficiency measures. Five inputs: labor, crop input, fuel, livestock input, and capital; and two outputs: crops and livestock were used in the analysis. The results focused on cost- and revenue-based economic efficiency. They showed that risk did affect average efficiency scores and is necessary to include in efficiency analysis. The average cost efficiency without risk was 0.6763. It increased to 0.7200 and 0.7018 respectively when cost efficiency was adjusted to recognize variability in outputs and downside risk. The average portion of cost inefficiency explained by variability in outputs was 28.06 percent. Downside risk explained 22.66 percent of cost inefficiency. The average revenue efficiency without risk was 0.7611 and increased to 0.8372 and 0.7811 when revenue efficiency was adjusted for variability in outputs and downside risk, respectively. Variability in outputs explained 42.53 percent and downside risk explained 30.58 percent of revenue inefficiency. The average cost efficiency for the 258 farms was 0.5691 and increased to 0.6043 with the consideration of risk preference scores. The average revenue efficiency was 0.6735 and increased to 0.6987 with risk preference scores. The efficient farms varied across cost and revenue efficiency, and the risk measures used. This lends support to the use of both input-oriented (cost) and output-oriented (revenue) efficiency measures as well as the use of multiple measures of risk.

Magíster en Gestión de Operaciones / Ingeniero Civil Industrial / En el presente trabajo se considera el problema de asignación de asientos para diversas clases de clientes en una red de Aerolíneas, más conocido en inglés como Network Revenue Management. Usando la metodología de programación dinámica, se busca maximizar el beneficio esperado sujeto a restricciones de tiempo y capacidad de los aviones en la red. Uno de los problemas que enfrentan las aerolíneas al momento de vender vuelos interconectados en una red es qué precio fijar para cada clase de cliente de tal forma de no dejar potenciales compradores fuera al fijar precios altos, ni perder potenciales ingresos con precios bajos. Para gestionar la demanda a través del tiempo, las aerolíneas utilizan políticas de control de asientos como Booking Limits, Protection Levels o Bid Prices, cuya solución se obtiene de resolver problemas de optimización dinámicos o estáticos. Esta tesis aborda este problema cuando la demanda está sujeta a incertidumbre. Bajo este escenario el problema es altamente riesgoso, pues los costos de operación son elevados y el producto que se ofrece es perecible, es decir, los asientos libres no se pueden inventariar lo que genera pérdidas. Para enfrentar esto se propone resolver usando optimización aversa al riesgo más conocida como optimización robusta. El enfoque de optimización robusta es optimizar contra el peor de los casos que pudiera surgir debido a la incertidumbre en la demanda, encontrando políticas de control en la capacidad de los aviones relativamente insensibles a variaciones en la estimación de demanda. La formulación robusta intenta mitigar el impacto de los errores en la estimación de probabilidades de transición mediante la elección de una política óptima maximin, donde la minimización es sobre un conjunto de probabilidades de transición y el objetivo es escoger una política que maximice los beneficios esperados sobre este conjunto. Los experimentos que se realizaron muestran que cuando el riesgo supera cierto umbral, el modelo robusto captura de forma más eficiente el riesgo y obtiene resultados esperados mejores que los modelos tradicionales.