The improvement of water quality in the streams of the Glenelg Hopkins catchment is a priority of the Glenelg Hopkins regional strategy. A major source of water pollution in the region is linked to agricultural activities as high nutrient levels from runoff have the potential to increase the incidence of blue-green algae in the waterways. Land use change, reduced rainfall, more frequent extreme rainfall events and higher temperatures associated with climate change are likely to exacerbate this trend. Water testing data of the Total Phosphorus (TP) levels in the Hopkins River and at other sites within the Hopkins Catchment indicate increasing incidence of TP above the Environment Protection Authority's target levels for extended periods of each year. Earlier research indicated that phosphorus in runoff increases when pasture fertility increases and that fertiliser management practices should be considered as an element of preventative action for reducing nutrient pollution. During our research, a survey was undertaken in the Hopkins River catchment, to determine the current management of phosphorus (P) fertilisers on grazing and mixed enterprise farms, the attitude of farmers to natural resource management and their understanding of nutrient pollution. The survey also gathered information on the way farmers made fertiliser management decisions. If cooperation relating to phosphorus fertiliser application could be facilitated between groups of farmers, it may be possible to reduce nutrient runoff into the Hopkins waterways. Cooperative game theory has successfully been used worldwide in the resolution of environmental problems where there is an economic impact to the decision making process. In this project, the amount of phosphorus applied per hectare was used in a cooperative game theory model assessing the potential for cooperative action on phosphorus management by groups of farmers, based on the trade off between the economic cost of pollution to the region waterways and the economic production benefits to the individual. The outcome of this work was individual optimal strategies for fertiliser application, allowing individual farmers to reduce their impact of agricultural production on the health of the catchment. Involving the farmer groups, while undertaking the project, raised awareness amongst the farming population of the regional nutrient pollution caused by runoff from agricultural land, and enlisted their assistance towards adopting a cooperative approach to the problem. In addition, the results have been mapped using a Geographical Information System (GIS) for visual presentation and to demonstrate the use of this process in natural resource management with the farmer groups.

This thesis looks into the economics of crowdsourcing using game theoretic modeling. The art of aggregating information and expertise from a diverse population has been in practice since a long time. The Internet and the revolution in communication and computational technologies have made this task easier and given birth to a new era of online resource aggregation, which is now popularly referred to as crowdsourcing. Two important features of this aggregation technique are: (a) crowdsourcing is always human driven, hence the participants are rational and intelligent, and they have a payoff function that they aim to maximize, and (b) the participants are connected over a social network which helps to reach out to a large set of individuals. To understand the behavior and the outcome of such a strategic crowd, we need to understand the economics of a crowdsourcing network. In this thesis, we have considered the following three major facets of the strategic crowdsourcing problem. (i) Elicitation of the true qualities of the crowd workers: As the crowd is often unstructured and unknown to the designer, it is important to ensure if the crowdsourced job is indeed performed at the highest quality, and this requires elicitation of the true qualities which are typically the participants' private information. (ii) Resource critical task execution ensuring the authenticity of both the information and the identity of the participants: Due to the diverse geographical, cultural, socio-economic reasons, crowdsourcing entails certain manipulations that are unusual in the classical theory. The design has to be robust enough to handle fake identities or incorrect information provided by the crowd while performing crowdsourcing contests. (iii) Improving the productive output of the crowdsourcing network: As the designer's goal is to maximize a certain measurable output of the crowdsourcing system, an interesting question is how one can design the incentive scheme and/or the network so that the system performs at an optimal level taking into account the strategic nature of the individuals. In the thesis, we design novel mechanisms to solve the problems above using game theoretic modeling. Our investigation helps in understanding certain limits of achievability, and provides design protocols in order to make crowdsourcing more reliable, effective, and productive.

Direct response advertising in the financial services industry in South Africa has become one of the most important tactics companies utilise to build and maintain market share. Ensuring that these advertising campaigns yield optimal return on investment numbers is the responsibility of marketing departments and their partners in the marketing and sales processes, such as the creative and media agencies, the distribution force, as well as the client service area that supports the client value proposition. The marketing executive therefore is accountable for the planning, budgeting and execution of direct response campaigns, which need to deliver sufficient results to support the company’s overall business objectives. The challenge all marketers face is the lack of a proven structured and scientific methodology to facilitate this planning, budgeting and execution process. It has always been a general view in the marketing fraternity that it is extremely difficult if not impossible to combine creative output measures, which are subjective in nature, with cost, sales and profit measures, which are objective in nature. This study aims to create a structured approach to marketing strategising and planning, by creating a marketing metrics model that enables the marketing practitioner to budget according to output needed to achieve the overarching business objectives of sales, cost management and profit. This marketing metrics model therefore unpacks the business drivers in detail, but through a marketing effort lense, to link the various factors underlying successful marketing output, to the bigger business objectives. This is done by incorporating both objective (verifiable data, such as cost per sale) and subjective variables (qualitative factors, such as creative quality) into a single model, which enables the marketing practitioner to identify areas of underperformance, which can then be managed, tweaked or discontinued in order to optimise marketing return on investment. Although many marketing metrics models and variables exist, there is a gap in the combination of objective and subjective factors in a single model, such as the proposed model, which will give the marketer a single tool to plan, analyse and manage the output in relation to pre-determined performance benchmarks. / Business Management / DCOM (Business Management)

Direct response advertising in the financial services industry in South Africa has become one of the most important tactics companies utilise to build and maintain market share. Ensuring that these advertising campaigns yield optimal return on investment numbers is the responsibility of marketing departments and their partners in the marketing and sales processes, such as the creative and media agencies, the distribution force, as well as the client service area that supports the client value proposition. The marketing executive therefore is accountable for the planning, budgeting and execution of direct response campaigns, which need to deliver sufficient results to support the company’s overall business objectives. The challenge all marketers face is the lack of a proven structured and scientific methodology to facilitate this planning, budgeting and execution process. It has always been a general view in the marketing fraternity that it is extremely difficult if not impossible to combine creative output measures, which are subjective in nature, with cost, sales and profit measures, which are objective in nature. This study aims to create a structured approach to marketing strategising and planning, by creating a marketing metrics model that enables the marketing practitioner to budget according to output needed to achieve the overarching business objectives of sales, cost management and profit. This marketing metrics model therefore unpacks the business drivers in detail, but through a marketing effort lense, to link the various factors underlying successful marketing output, to the bigger business objectives. This is done by incorporating both objective (verifiable data, such as cost per sale) and subjective variables (qualitative factors, such as creative quality) into a single model, which enables the marketing practitioner to identify areas of underperformance, which can then be managed, tweaked or discontinued in order to optimise marketing return on investment. Although many marketing metrics models and variables exist, there is a gap in the combination of objective and subjective factors in a single model, such as the proposed model, which will give the marketer a single tool to plan, analyse and manage the output in relation to pre-determined performance benchmarks. / Business Management / DCOM (Business Management)