Thesis (M. Com. (Economics)) -- University of Limpopo, 2017 / The study intends to investigate the determinants of employment in the platinum mining industry in South Africa. Employment levels decreased dramatically in the platinum mining industry in South Africa. This is due to decrease in export demand for platinum, high operating cost, labour unrest, low levels of production and other determinants of employment. The specific objective of the study is to determine the nexus between employment, output, domestic demand and export demand. Annual time series data covering the period between 1992-2013 was used. The study employed the Vector Error Correction Model approach. Johansen Cointegration test results confirmed the existence of a long run relationship amongst variables under investigation. Export demand and output are found to be positively related with employment. The speed of adjustment to equilibrium is -0.283202. Impulse response functions and variance decomposition are also generated to explain the response to shock amongst variables. The results of the study vindicate that the platinum mining industry should implement policies and strategies to increase output which will lead to higher levels of employment as well as economic growth. In addition, government should also create a conducive environment to enable the industry to expand and the industry should also intensify its export drive, these findings are envisaged to contribute significantly to the existing but limited literature on the subject under investigation. / National Research Foundation

The general aim of this research is to investigate approaches to: •improve small area market demand (i.e. SAMD) prediction accuracy for the purchase of automobiles at the level of each Census Collection District (i.e. CCD); and •enhance understanding of meso-level marketing phenomena (i.e. geographically aggregated phenomena) relating to SAMD. Given the importance of SAMD prediction, and the limitations posed by current methods, four research questions are addressed: •What are the key challenges in meso-level SAMD prediction? •What variables affect SAMD prediction? •What techniques can be used to improve SAMD prediction? •What is the value of integrating these techniques to improve SAMD prediction? To answer these questions, possible solutions from two broad areas are examined: spatial analysis and data mining. The research is divided into two main studies. In the first study, a seven-step modelling process is developed for SAMD prediction. Several sets of models are analysed to examine the modelling techniques’ effectiveness in improving the accuracy of SAMD prediction. The second study involves two cases to: 1) explore the integration of these techniques and their advantages in SAMD prediction; and 2) gain insights into spatial marketing issues. The case study of Peugeot in the Sydney metropolitan area shows that urbanisation and geo-marketing factors can have a more important role in SAMD prediction than socio-demographic factors. Furthermore, results show that modelling spatial effects is the most important aspect of this prediction exercise. The value of the integration of techniques is in compensating for the weaknesses of conventional techniques, and in providing complementary and supplementary information for meso-level marketing analyses. Substantively, significant spatial variation and continuous patterns are found with the influence of key studied variables. The substantive implications of these findings have a bearing on both academic and managerial understanding. Also, the innovative methods (e.g. the SAMD modelling process and the model cube based technique comparison) developed from this research make significant contributions to marketing research methodology.

<p>A study has been conducted to assess the possibilities to introduce dead cattle organs as the raw material for biogas generation at the rural household level in Bangladesh. At the same time, the present energy situation in Bangladesh is highlighted. The actors in the energy sector have been identified. The energy policy of Bangladesh is not transparent and there seems to be no energy strategy for the country. Possibilities of other renewable sources of energy are also discussed. Biomass fuels comprise the main source of energy for the rural people and the major share of energy use is consumed after cooking and household lightning. Enormous amount of labor is spent in gathering and collecting of fuel wood and agricultural residues that reduces productivity among women and young children. Besides, biogas is generated from agricultural residues and animal excreta in Bangladesh. Tremendous pressure on rural forests for fuel wood is increasing and environmental degradation is occurring. Agricultural lands are losing vital nutrients as people are using crop residues and animal excreta for energy. Under present condition, the possibilities of adopting biogas technology and dead cattle organs as the raw materials to generate biogas is analyzed in terms of availability of the raw material. Sustainable development using biogas is also considered. And lastly, some recommendation is suggested, based on the current energy situation of Bangladesh.</p>

A study has been conducted to assess the possibilities to introduce dead cattle organs as the raw material for biogas generation at the rural household level in Bangladesh. At the same time, the present energy situation in Bangladesh is highlighted. The actors in the energy sector have been identified. The energy policy of Bangladesh is not transparent and there seems to be no energy strategy for the country. Possibilities of other renewable sources of energy are also discussed. Biomass fuels comprise the main source of energy for the rural people and the major share of energy use is consumed after cooking and household lightning. Enormous amount of labor is spent in gathering and collecting of fuel wood and agricultural residues that reduces productivity among women and young children. Besides, biogas is generated from agricultural residues and animal excreta in Bangladesh. Tremendous pressure on rural forests for fuel wood is increasing and environmental degradation is occurring. Agricultural lands are losing vital nutrients as people are using crop residues and animal excreta for energy. Under present condition, the possibilities of adopting biogas technology and dead cattle organs as the raw materials to generate biogas is analyzed in terms of availability of the raw material. Sustainable development using biogas is also considered. And lastly, some recommendation is suggested, based on the current energy situation of Bangladesh.

This dissertation aims to contribute to the field of economics of competition policy by analyzing the demand structure and the market power in the Turkish beverage industry and in the cola market in particular. First, a demand system for the beverage products has been estimated by using a multi-stage linearized Almost Ideal Demand System (AIDS). Using the own-price elasticity of cola in a SSNIP test (Small but Significant Non-Transitory Increase in Price), it is shown that cola market consists of a distinct relevant product market. Then, the demand elasticities of cola products at brand and package level have been estimated by the simple and nested logit models. Finally, the estimated demand elasticities of cola products have been used in measuring the degree of market power and predicting the effects of a hypothetical merger between Pepsi and Cola Turca by using a merger simulation technique. The results show that all cola suppliers have large price-cost margins for most of their products. Prices of the merging parties increase in average by 15 - 21% after the merger. The merger also causes the market price to increase by 16- 22% and consumer surplus to decrease by nearly 5% in average. Finally, depending on these results, the thesis recommends a stricter merger control criterion than dominance criterion for competition policy in Turkey.

The potential of carbon emission regulations applied to an individual building will encourage building owners to purchase utility-provided green power or to employ onsite renewable energy generation. As both cases are based on intermittent renewable energy sources, demand side control is a fundamental precondition for maximizing the effectiveness of using renewable energy sources. Such control leads to a reduction in peak demand and/or in energy demand variability, therefore, such reduction in the demand profile eventually enhances the efficiency of an erratic supply of renewable energy. The combined operation of active thermal energy storage and passive building thermal mass has shown substantial improvement in demand-side control performance when compared to current state-of-the-art demand-side control measures. Specifically, "model-based" optimal control for this operation has the potential to significantly increase performance and bring economic advantages. However, due to the uncertainty in certain operating conditions in the field its control effectiveness could be diminished and/or seriously damaged, which results in poor performance. This dissertation pursues improvements of current demand-side controls under uncertainty by proposing a robust supervisory demand-side control strategy that is designed to be immune from uncertainty and perform consistently under uncertain conditions. Uniqueness and superiority of the proposed robust demand-side controls are found as below: a. It is developed based on fundamental studies about uncertainty and a systematic approach to uncertainty analysis. b. It reduces variability of performance under varied conditions, and thus avoids the worst case scenario. c. It is reactive in cases of critical "discrepancies" observed caused by the unpredictable uncertainty that typically scenario uncertainty imposes, and thus it increases control efficiency. This is obtainable by means of i) multi-source composition of weather forecasts including both historical archive and online sources and ii) adaptive Multiple model-based controls (MMC) to mitigate detrimental impacts of varying scenario uncertainties. The proposed robust demand-side control strategy verifies its outstanding demand-side control performance in varied and non-indigenous conditions compared to the existing control strategies including deterministic optimal controls. This result reemphasizes importance of the demand-side control for a building in the global carbon economy. It also demonstrates a capability of risk management of the proposed robust demand-side controls in highly uncertain situations, which eventually attains the maximum benefit in both theoretical and practical perspectives.

This dissertation presents innovative demand management techniques for service systems with limited resources. The first study analyzes demand management policies of animal shelters with limited Kennel space as a set of interacting stochastic queueing systems. In practice, there are two main policies being used, which we call "Kill" and "No-Kill" policies. In a "Kill" system, animals may be euthanized if a shelter is full. Many shelters have moved to a "No-Kill" policy, where they avoid killing for space and adopt other approaches to reduce supply and demand mismatch. Our goal is to provide insights on how No-Kill policies, such as coordination, adoption and neutering campaigns, help reduce the animals' killing rate so that the shelter management can choose the way to effectively solve their problems. In the second part, we consider a topic of demand management for the Sports and Entertainment (S&E) industry, called "Scaling the house", i.e., how to divide seats into zones for different prices to maximize revenue across the venue. From the data obtained from several performance venues in the U.S., we find ticket demand is impacted by locations of seats as well as by price. We characterize closed-form solutions for the optimal two-dimensional zoning decision (with row and column cuts) and the one-dimensional decision (with row cuts), and explore when each model should be applied. The third study considers pricing as a tool to manage demand for the S&E tickets. We develop dynamic pricing with demand learning models where demand is also affected by time left until the show dates. Since the show's popularity is usually uncertain to the seller, we propose a method to learn the overall popularity via Bayesian updates. We perform computational experiments to understand properties of the model solutions and identify when demand learning is most beneficial.

M. Tech. Civil Engineering / South Africa is categorized as a water stressed country and it is forecasted to experience physical water scarcity by the year 2025 with a yearly water availability of less than 1000m3 per capita. Continuous pollution of the available water resources from the sources, and the high population growth and its attributes will increase pressure on the available resources and probably resulting in increased conflicts over allocations and more stress resulting in water scarcity. The overall aim of the study was to develop tools and strategies for Water Demand Management in Mabopane, Garankuwa and Winterveldt, which are the areas supplied by Sandspruit Works Association.

published_or_final_version / Public Administration / Master / Master of Social Sciences

The ability for domestic consumers to provide demand response to dynamic electricity pricing will become increasingly valuable for integrating the high penetrations of renewables that are expected to be connected to electricity networks in the future. The aim of this thesis is to investigate whether domestic consumers will be willing and able to provide demand response in such low-carbon futures. A broad approach is presented in this thesis, with research contributions on subjects including data privacy, behavioural economics, and battery modelling. The principle argument of the thesis is that studying the behaviour of consumers with grid-connected photovoltaic ('PV') systems can provide insight into how consumers might respond to dynamic pricing in future low-carbon power systems, as both experience irregular electricity prices that are correlated with intermittent renewable generation. Through a combination of statistical and qualitative methods, this thesis investigates the demand response behaviour of consumers with PV systems in the UK. The results demonstrate that these consumers exhibit demand response behaviour by increasing demand during the day and decreasing demand during the evening. Furthermore, this effect is more pronounced on days with higher irradiance. The results are novel in three ways. First, they provide quantified evidence that suggests that domestic consumers with PV systems engage in demand response behaviour. Second, they provide evidence of domestic consumers responding to irregular electricity prices that are correlated with intermittent renewable generation, thereby addressing the aim of this thesis, and supporting the assumption that consumers can be expected to respond to dynamic pricing in future markets with high penetrations of renewables. Third, they provide evidence of domestic consumers responding to dynamic pricing that is similar to real-time pricing, while prior evidence of this is rare and confined to the USA.