Theses and Dissertations (Economics)
http://hdl.handle.net/2263/31861
2024-03-29T11:05:59ZRunning events in a crisis context : a sport consumer marketing perspective
http://hdl.handle.net/2263/94363
Running events in a crisis context : a sport consumer marketing perspective
In this thesis, Running events in a crisis context: a sport consumer marketing perspective, the candidate investigated emotional and behavioural aspects of sport event participation, specifically running events, prior to and during phases related to the unique COVID-19 crisis. The study was conducted in three parts, with the first two applying a novel netnography among an online community of marathon runners, utilising both inductive and deductive qualitative research methods. In the third part, a quantitative CHAID segmentation approach was employed. The first part focused on self-expressiveness and showed that event participants derive a deeper sense of happiness (or eudaimonia) from marathon event participation. This results in positive marketing outcomes, particularly positive authentic electronic word-of-mouth communication. The second part showed that brand love is enduring during a crisis, and the third part showed the potential for virtual running events across different segments. The study provides theoretical, practical and methodological contributions within the field of sport marketing and consumer behaviour.
Thesis ((PhD) Marketing Management)--University of Pretoria, 2023.
2023-06-30T00:00:00ZUncertainty related to infectious diseases and forecastability of the volatility of financial assets
http://hdl.handle.net/2263/91596
Uncertainty related to infectious diseases and forecastability of the volatility of financial assets
In the context of the great turmoil in the financial markets caused by the COVID-19 outbreak, we examine the predictability of the US Treasury securities (Chapter 2), international stocks (Chapter 3), foreign exchange rates and Bitcoin (Chapter 4) and agricultural commodity futures (Chapter 5) given daily infectious diseases-related uncertainties (EMVID) using the heterogonous autoregressive volatility (HAV-RV) model. On stationary intraday data computed from a 5-minute interval, we conduct a recursive out-of-sample forecast. Through the RMSFE metric, our results provide evidence that these financial assets remain attractive to investors within the pandemic episode, with Bitcoin obtaining significantly high forecast gains among all the other assets in the medium and long forecast horizons. The US Treasury securities remain risk-free and the worldwide recognition of gold as a “safe haven” asset is emphasised. Among the agricultural traded commodities, cocoa and oats futures had significant forecast gains. The international stocks in Pakistan and Singapore appeared to be the most volatile. It is also evident that an econometrician can acquire the highest forecast gain in the Swiss Franc futures in the foreign exchange market.
In Chapter 6, we use annual data on real gold returns and the probability of fatality due to contagious diseases over the period 1258 to 2020, we detect nonlinearity and regime changes in the relationship between the two variables of concern. We rely on a quantile regression model to show that real gold returns can hedge against the risks associated with such rare disasters (COVID-19), primarily when the market is in its bullish state, with it being negatively impacted in its bearish state.
By assessing the role of contagious diseases on these financial assets’ returns we find strong evidence that contagious diseases play an important role in forecasting their RV. Understandably, our results have important portfolio implications for investors, speculators and portfolio managers during periods of high levels of uncertainty associated with infectious diseases.
Thesis (PhD (Economics))--University of Pretoria, 2022.
2022-01-01T00:00:00ZA proposed framework for supply chain analytics using customer data
http://hdl.handle.net/2263/90061
A proposed framework for supply chain analytics using customer data
The COVID-19 pandemic and recent geopolitical events have called for a need to re-evaluate methodologies for Supply Chain Risk management. Significant investment in supply chain technology has resulted in data being generated throughout the value chain. Customer data, specifically, is of interest in order to establish customer-centricity and an enhanced customer journey. However, the transformation of this data to insight is not obvious for some organisations. Forecasting models are typically used to inform decision-making, mitigate risks and enlighten policymakers. This thesis aims to address this challenge by proposing a set of capabilities that will enhance the integration of the supply chain network to its customer data. Given this context, two methodologies were used to address the research problem; (i) multinational petrochemicals company was considered for our case study and a web-based survey was distributed among key stakeholders at their head offices in South Africa. A structured equation model (SEM) was constructed to empirically test the proposed relationships among the constructs, specifically: People, Process and Technology capabilities; (ii) The macro-economic factors that drive customer demand also considered. Increasing crude oil prices have increased logistics costs and have incited the deglobalization of supply chain operations. A novel petroleum forecasting model is also proposed, particularly focusing on the forecasting on South Africa’s petrol and diesel consumptions. The model uses indices for Brent crude oil price (ZAR), Gross Domestic Product (GDP), Rand to Dollar exchange rate, Consumer Confidence Index (CCI) and Business Confidence Index (BCI) data as input data. Overall, this study suggests that in order to effectively serve their customers, organisations need to establish a culture of customer centricity that is underpinned by appropriate supply chain analytics techniques. The predictive model further highlights the need to establish the relationship between the organisation’s supply chain and micro and macro-economic drivers.
Thesis (PhD (Business Management))--University of Pretoria, 2022.
2022-01-01T00:00:00ZThe self-fulfilling prophecy of uncertainty : a study on the impact of uncertainty and contagion on economic outcomes and policy
http://hdl.handle.net/2263/89866
The self-fulfilling prophecy of uncertainty : a study on the impact of uncertainty and contagion on economic outcomes and policy
Economic globalisation has ushered in the integration of world financial markets, and the degree of interconnectedness has never been greater. In the face of a resurgence in global risks from trade, geopolitical tensions and global health risks, such as the outbreak of COVID-19, there has been an increasing focus on the impact of uncertainty on economic outcomes. Overall, uncertainty has been found to have significant negative impact on economies with the potential to compound recession and hinder economic recovery. The principal objective of this study is to address the impact of uncertainty and contagion on economic outcomes and policy in the South African context through a broad focus on the key markets – including the stock market, the currency market and the goods market – with particular focus on non-linear modelling and asymmetric effects, where the sign and size of a shock or uncertainty within markets have different impacts.
In order to meet this objective, this study first investigates the interdependence and volatility transmissions and contagion between the stock and currency markets through a bivariate Exponential Generalised Autoregressive Conditional Heteroscedasticity (EGARCH) framework. This approach is used to allow for asymmetric effects of the shocks, allowing both the size and the sign of the shock to have different impacts. The impact of COVID-19 on the transmission mechanism is also explored. The outcomes from this analysis provide strong evidence in support of the “stock-orientated” approach, where significant price and volatility spillovers propagate from the stock market into the foreign exchange market, whilst evidence of the “flow-orientated” approach is seen in the second moment, and significant shock and asymmetric spillovers from the exchange to the stock market are found. The results support the asymmetric and long-range persistence volatility spillover effect and show strong evidence of contagion between stock and foreign exchange markets. These spillovers became more pronounced during the COVID-19 pandemic, confirming heightened contagion in these markets during periods of crisis.
Secondly, attention turns to the goods market. The inflation-inflation uncertainty nexus is investigated through GARCH and GARCH-in-mean (GARCH-M) models to establish whether inflation uncertainty is a self-fulfilling prophecy, i.e., does higher inflation uncertainty leads to higher inflation and vice versa? The empirical outcomes from this study suggest the existence of a bidirectional relationship between inflation and inflation uncertainty, with stronger evidence in support of the Friedman-Ball hypothesis which states that heightened levels of inflation induce higher uncertainty about future inflation and weaker evidence in favour of the Cukierman-Meltzer hypothesis that proposes a reverse causation. The study also finds that inflation targeting has contributed significantly to reducing the level of inflation and inflation uncertainty. The Rossi-Wang (2019) time-varying Granger causality testing, which is robust in the presence of instabilities, further provides interesting insight into the relationship notably that both the Friedman-Ball and Cukierman-Meltzer hypotheses break down during the inflation targeting period, which further hints towards the efficacy of inflation targeting as monetary policy framework.
Finally, the thesis determines how high and low states of uncertainty in the three key domestic markets – the stock market, currency market and goods market – and uncertainty in the global market impact the effectiveness of monetary policy in South Africa. High and low uncertainty states in the markets are examined by employing sign-restriction and the Self-Exciting Interacted VAR (SEIVAR) analysis. This framework is particularly appealing in that it allows for estimating the economy’s response conditional on uncertainty states in the different markets. Impulse response analysis reveals that monetary policy is less effective in high uncertainty states in the different markets. Overall, the study attempts to inform policy in the face of uncertainty.
Thesis (PhD (Economics))--University of Pretoria, 2022.
2022-04-01T00:00:00Z