Despite the rich geological heritage encompassed within the Kruger National Park (KNP), the unemployment rate and poverty levels remain high for local communities abutting the northern part of the park. This study focused on the northern part of the KNP because no study has been conducted to identify and locate geoheritage sites and due to high unemployment rates and poverty levels in that area compared to the southern part of the park. The primary purpose of this research was to investigate and evaluate the potential for geotourism to contribute towards social sustainability and more effective local community development. Geotourism is an emerging research field and South Africa holds some fascinating geological heritage; however, geotourism has been under researched. Therefore, it was important to examine the potential for geotourism to effectively contribute towards local development. Considering that the national government of South Africa through the National Development Plan (NDP) and National Tourism Sector Strategy (NTSS) recognises tourism as one of the growth pillars for poverty alleviation and job creation, geotourism can contribute towards this as one of the potential solutions. Social sustainability and stakeholder framework theories linked to the concept of sustainable development allowed examination of geotourism and its potential contribution to local sustainable development in the context of this study. This study used a four phased mixed research methodology (qualitative and quantitative) to investigate the potential for geotourism development as a secondary market to supplement the current tourism market (wildlife viewing) and to examine the geotourism potentiality to assist in addressing unemployment and poverty. The first phase was a database inventory development, field ranking, evaluation and prioritisation of geoheritage sites using six indicators (geotourism value, cultural value, ecological sensitivity, accessibility, development requirements, and currently available academic literature) of 15 potential geoheritage sites. The collected field data was converted into Microsoft word and excel documents for analysis. Furthermore, excel data with geographic information and values of the six indicators of 15 geoheritage sites was imported into GIS software in order to produce evaluation and prioritisation maps. The second phase entailed semi-structured interviews (qualitative) with 16 key participants which included local community leaders (2), local residents (2), SANParks officials (4), National Department of Tourism government officials (3), local high school tourism teachers (2), Limpopo conservation agency (1) and tourism operators (2). Content analysis was used to analyse the transcripts of semi-structured interviews in order to identify the emerging themes and sub-themes to understand the perceptions of all participants towards geotourism and local social sustainability. The third phase of the research was an online survey (quantitative) of 105 valid respondents and the collected data was statistically analysed in order to understand the perceptions of respondents towards geotourism and local social sustainability. Thereafter, the findings from the first three phases of the study were analysed and interpreted together so as to draw conclusions based on divergence and convergence of findings (fourth phase). In this context, qualitative analysis and statistical analysis of results helped to draw conclusions and recommendations of the research. In conclusion, it was evident from the findings that the northern part of KNP is enriched with precious potential geoheritage sites that can be utilised for geotourism development towards achieving social sustainability, especially of local communities abutting the northern part of the park. However, geotourism has not been developed and introduced as a new tourism market segment at the KNP. The theoretical supplement from this study is that geotourism can contribute towards achieving social sustainability, especially of local communities. Fundamentally, this study shows that previous social sustainability literature lacks focus and has been limited on integrating local culture into social sustainability frameworks. As such, this case study suggests that stakeholder theory and geotourism can be used as tools in reintegrating local culture, understanding social sustainability and towards social sustainability. This study reinforces the theory of social sustainability, stakeholder and geotourism by revealing that local communities abutting the northern part of the KNP and other stakeholders could potentially benefit through socio-economic benefits (income/ employment, community well-being, cultural and shareholding benefits, tour operating, tour guiding, economic growth, supply of goods and services, accommodation and retail businesses), educational benefits (upskilling of tour guides, training of local communities and creating awareness among different stakeholders), and environmental benefits emanating from geotourism development at the KNP. It is therefore recommended that SANParks and/or government immediately introduce geotourism as a new tourism market at the northern part of the KNP. It is recommended that SANParks and/or government should ensure that local communities in the northern part of the KNP are effectively consulted and involved in the planning and decision-making process regarding development and introduction of new tourism products such as geotourism. Furthermore, SANParks and/or government should ensure that there is collaborative stakeholder engagement among all role players, local communities and tourists have access to the geoheritage sites inside the park and local communities benefit from geotourism. The findings of this study intend to assist SANParks, local community leaders, the private sector (including existing tour operators) and government departments in achieving a national database of geoheritage sites to ultimately be associated with sustainable geotourism activity led by local communities. Show less

Despite the rich geological heritage encompassed within the Kruger National Park (KNP), the unemployment rate and poverty levels remain high for local communities abutting the northern part of the park. This study focused on the northern part of the KNP because no study has been conducted to identify and locate geoheritage Show more

Extant research has established that destination branding through sport events is deemed to be a valuable resource for brand development and positioning, as well as for accessing social, economic and environmental benefits for both developed and developing nations. However, the destination branding discourse remains widely contested among academics and practitioners, as there is, as yet, no commonly accepted framework for the destination branding theory. Moreover, the theory underpinning sport event leveraging towards informed branding practices, especially in the developing destination context, is lacking. The current study conceptualises the leveraging of home-grown sport events for destination brands; extending the scope of other known sport event leveraging studies in the developing context. The research critically examines key stakeholders involved in sport and destination branding by detailing their perceptions in relation to the leveraging of home-grown sport using the South African brand as a case study. Show less

Extant research has established that destination branding through sport events is deemed to be a valuable resource for brand development and positioning, as well as for accessing social, economic and environmental benefits for both developed and developing nations. However, the destination branding discourse remains widely Show more

This study investigates monetary policy shocks and industrial production in BRICS countries. The study is presented in four separate but related essays. The first (chapter three) employs a Panel Structural Vector Autoregressive model (𝑃−𝑆𝑉𝐴𝑅) to investigate how monetary policy shocks affect industrial output in BRICS countries using monthly data for the period 1994:1 to 2013:12. A nine variable 𝑃−𝑆𝑉𝐴𝑅 with short-run restrictions among the variables is constructed for the analysis. The study finds that variations in the exchange rate have the largest impact on industrial output in the BRICS countries. It is also observed that inflation rates significantly increase industrial output, peaking after about 11 months. This suggests that monetary authorities should be cautious when formulating policies aimed at reducing the inflation rate because of the spill over effect on industrial output. Further analysis reveals that interest rates have a marginal effect on exchange rates, while money supply makes a relatively large contribution to exchange rate fluctuations. Again, it is observed that changes in money supply exert a very large impact on variations in the rate of inflation. Thus, money supply plays an important role in curbing inflation. The study also analyses variations in interest rates, money supply and inflation and recommends that monetary authorities in the BRICS countries adjust interest rates, and not money supply, in response to inflation expectations. The second essay (chapter four) models exchange rate behaviour in the BRICS countries. This study examines global shocks and variations in the BRICS countries local currency/United States dollar exchange rate using the symmetric Generalized Autoregressive Conditional Heteroscedasticity (GARCH), Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH) and Asymmetric Power Autoregressive Conditional Heteroscedasticity (APARCH) models to determine the relationship between the two. The GARCH, EGARCH and APARCH are employed under normal (Normal Gaussian) and nonnormal (Student‘s t and Generalized Error) distributions. Using monthly exchange rate data covering the period 1994:01–2013:12, the study finds that exchange rates in Brazil, Russia and India can well be modelled by the symmetric GARCH (1,1) model while in China, the three models perform well. In South Africa, the results of the three models also perform well but the EGARCH (1,1) model is found to be the best. Further analyses of the models reveal that the Student‘s t distribution produces better fit for estimating exchange rate variations and global shocks in BRICS countries compared to the Normal Gaussian and GED values under the nonnormal distributions. Overall, the study recommends that the BRICS countries should consider the impact of oil prices and global interest rates when formulating and implementing policies that impact on exchange rates. The third essay (chapter five) examines whether the five BRICS countries share similar business cycles and determines the probability of any of the countries moving from a contractionary regime to an expansionary regime. The study further examines the extent to which changes in monetary policy affect industrial output in expansions relative to contractions. Employing the Peersman and Smets (2001) Markov-Switching Model (MSM) and monthly data from 1994:01 – 2013:12, the study reveals that the five BRICS countries have similar business cycles. The results further demonstrate that the BRICS countries‘ business cycles are characterized by two distinct growth rate phases: a contractionary regime and an expansionary regime. It is observed that area-wide monetary policy has significantly large effects on industrial output in recessions as well as in booms. It is also established that there is a high probability of moving from state 1 (recession) to state 2 (expansion) and that on average, the probabilities of staying in state 2 (expansion) are high for each of the five countries. It is, therefore, recommended that the BRICS countries should sustain uniform policy consistency (monetary policy), especially as they formulate and implement economic policies to stimulate industrial output. The fourth essay (chapter six) investigates the long run and short run dynamics between industrial production and the factors affecting production in the emerging market economies of BRICS countries. Using the Chudik and Pesaran (2013) P-ARDL model and monthly data from 1994:01 – 2013:12, the study finds evidence of a cointegrating relationship between industrial production and selected variables. It is further observed that capital, labour, per capita income and exports have a positive long run impact on industrial production in the BRICS countries. However, a currency appreciation (an increase in the exchange rate) has a negative impact on industrial production. In the short run, it is found that imports, exports, exchange rates, labour, capital and per capita income significantly affect industrial production. The policy implication stemming from the analysis is that a sound economic policy is important for output production and industrialization in BRICS countries while poor policy will result in a nexus of constraintsfrom which escape may be difficult (or impossible). The industrial sector, therefore, should also be listed as a sector that can actualize the diversification process and boost economic performance in the EMEs. There should also be policy consistence in curtailing the declining trend of industrial production. Show less

This study investigates monetary policy shocks and industrial production in BRICS countries. The study is presented in four separate but related essays. The first (chapter three) employs a Panel Structural Vector Autoregressive model (𝑃−𝑆𝑉𝐴𝑅) to investigate how monetary policy shocks affect industrial output Show more

This study investigates monetary policy shocks and industrial production in BRICS countries. The study is presented in four separate but related essays. The first (chapter three) employs a Panel Structural Vector Autoregressive model (𝑃−𝑆𝑉𝐴𝑅) to investigate how monetary policy shocks affect industrial output in BRICS countries using monthly data for the period 1994:1 to 2013:12. A nine variable 𝑃−𝑆𝑉𝐴𝑅 with short-run restrictions among the variables is constructed for the analysis. The study finds that variations in the exchange rate have the largest impact on industrial output in the BRICS countries. It is also observed that inflation rates significantly increase industrial output, peaking after about 11 months. This suggests that monetary authorities should be cautious when formulating policies aimed at reducing the inflation rate because of the spill over effect on industrial output. Further analysis reveals that interest rates have a marginal effect on exchange rates, while money supply makes a relatively large contribution to exchange rate fluctuations. Again, it is observed that changes in money supply exert a very large impact on variations in the rate of inflation. Thus, money supply plays an important role in curbing inflation. The study also analyses variations in interest rates, money supply and inflation and recommends that monetary authorities in the BRICS countries adjust interest rates, and not money supply, in response to inflation expectations. The second essay (chapter four) models exchange rate behaviour in the BRICS countries. This study examines global shocks and variations in the BRICS countries local currency/United States dollar exchange rate using the symmetric Generalized Autoregressive Conditional Heteroscedasticity (GARCH), Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH) and Asymmetric Power Autoregressive Conditional Heteroscedasticity (APARCH) models to determine the relationship between the two. The GARCH, EGARCH and APARCH are employed under normal (Normal Gaussian) and nonnormal (Student‘s t and Generalized Error) distributions. Using monthly exchange rate data covering the period 1994:01–2013:12, the study finds that exchange rates in Brazil, Russia and India can well be modelled by the symmetric GARCH (1,1) model while in China, the three models perform well. In South Africa, the results of the three models also perform well but the EGARCH (1,1) model is found to be the best. Further analyses of the models reveal that the Student‘s t distribution produces better fit for estimating exchange rate variations and global shocks in BRICS countries compared to the Normal Gaussian and GED values under the nonnormal distributions. Overall, the study recommends that the BRICS countries should consider the impact of oil prices and global interest rates when formulating and implementing policies that impact on exchange rates. The third essay (chapter five) examines whether the five BRICS countries share similar business cycles and determines the probability of any of the countries moving from a contractionary regime to an expansionary regime. The study further examines the extent to which changes in monetary policy affect industrial output in expansions relative to contractions. Employing the Peersman and Smets (2001) Markov-Switching Model (MSM) and monthly data from 1994:01 – 2013:12, the study reveals that the five BRICS countries have similar business cycles. The results further demonstrate that the BRICS countries‘ business cycles are characterized by two distinct growth rate phases: a contractionary regime and an expansionary regime. It is observed that area-wide monetary policy has significantly large effects on industrial output in recessions as well as in booms. It is also established that there is a high probability of moving from state 1 (recession) to state 2 (expansion) and that on average, the probabilities of staying in state 2 (expansion) are high for each of the five countries. It is, therefore, recommended that the BRICS countries should sustain uniform policy consistency (monetary policy), especially as they formulate and implement economic policies to stimulate industrial output. The fourth essay (chapter six) investigates the long run and short run dynamics between industrial production and the factors affecting production in the emerging market economies of BRICS countries. Using the Chudik and Pesaran (2013) P-ARDL model and monthly data from 1994:01 – 2013:12, the study finds evidence of a cointegrating relationship between industrial production and selected variables. It is further observed that capital, labour, per capita income and exports have a positive long run impact on industrial production in the BRICS countries. However, a currency appreciation (an increase in the exchange rate) has a negative impact on industrial production. In the short run, it is found that imports, exports, exchange rates, labour, capital and per capita income significantly affect industrial production. The policy implication stemming from the analysis is that a sound economic policy is important for output production and industrialization in BRICS countries while poor policy will result in a nexus of constraintsfrom which escape may be difficult (or impossible). The industrial sector, therefore, should also be listed as a sector that can actualize the diversification process and boost economic performance in the EMEs. There should also be policy consistence in curtailing the declining trend of industrial production. This study investigates monetary policy shocks and industrial production in BRICS countries. The study is presented in four separate but related essays. The first (chapter three) employs a Panel Structural Vector Autoregressive model (𝑃−𝑆𝑉𝐴𝑅) to investigate how monetary policy shocks affect industrial output in BRICS countries using monthly data for the period 1994:1 to 2013:12. A nine variable 𝑃−𝑆𝑉𝐴𝑅 with short-run restrictions among the variables is constructed for the analysis. The study finds that variations in the exchange rate have the largest impact on industrial output in the BRICS countries. It is also observed that inflation rates significantly increase industrial output, peaking after about 11 months. This suggests that monetary authorities should be cautious when formulating policies aimed at reducing the inflation rate because of the spill over effect on industrial output. Further analysis reveals that interest rates have a marginal effect on exchange rates, while money supply makes a relatively large contribution to exchange rate fluctuations. Again, it is observed that changes in money supply exert a very large impact on variations in the rate of inflation. Thus, money supply plays an important role in curbing inflation. The study also analyses variations in interest rates, money supply and inflation and recommends that monetary authorities in the BRICS countries adjust interest rates, and not money supply, in response to inflation expectations. The second essay (chapter four) models exchange rate behaviour in the BRICS countries. This study examines global shocks and variations in the BRICS countries local currency/United States dollar exchange rate using the symmetric Generalized Autoregressive Conditional Heteroscedasticity (GARCH), Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH) and Asymmetric Power Autoregressive Conditional Heteroscedasticity (APARCH) models to determine the relationship between the two. The GARCH, EGARCH and APARCH are employed under normal (Normal Gaussian) and nonnormal (Student‘s t and Generalized Error) distributions. Using monthly exchange rate data covering the period 1994:01–2013:12, the study finds that exchange rates in Brazil, Russia and India can well be modelled by the symmetric GARCH (1,1) model while in China, the three models perform well. In South Africa, the results of the three models also perform well but the EGARCH (1,1) model is found to be the best. Further analyses of the models reveal that the Student‘s t distribution produces better fit for estimating exchange rate variations and global shocks in BRICS countries compared to the Normal Gaussian and GED values under the nonnormal distributions. Overall, the study recommends that the BRICS countries should consider the impact of oil prices and global interest rates when formulating and implementing policies that impact on exchange rates. The third essay (chapter five) examines whether the five BRICS countries share similar business cycles and determines the probability of any of the countries moving from a contractionary regime to an expansionary regime. The study further examines the extent to which changes in monetary policy affect industrial output in expansions relative to contractions. Employing the Peersman and Smets (2001) Markov-Switching Model (MSM) and monthly data from 1994:01 – 2013:12, the study reveals that the five BRICS countries have similar business cycles. The results further demonstrate that the BRICS countries‘ business cycles are characterized by two distinct growth rate phases: a contractionary regime and an expansionary regime. It is observed that area-wide monetary policy has significantly large effects on industrial output in recessions as well as in booms. It is also established that there is a high probability of moving from state 1 (recession) to state 2 (expansion) and that on average, the probabilities of staying in state 2 (expansion) are high for each of the five countries. It is, therefore, recommended that the BRICS countries should sustain uniform policy consistency (monetary policy), especially as they formulate and implement economic policies to stimulate industrial output. The fourth essay (chapter six) investigates the long run and short run dynamics between industrial production and the factors affecting production in the emerging market economies of BRICS countries. Using the Chudik and Pesaran (2013) P-ARDL model and monthly data from 1994:01 – 2013:12, the study finds evidence of a cointegrating relationship between industrial production and selected variables. It is further observed that capital, labour, per capita income and exports have a positive long run impact on industrial production in the BRICS countries. However, a currency appreciation (an increase in the exchange rate) has a negative impact on industrial production. In the short run, it is found that imports, exports, exchange rates, labour, capital and per capita income significantly affect industrial production. The policy implication stemming from the analysis is that a sound economic policy is important for output production and industrialization in BRICS countries while poor policy will result in a nexus of constraintsfrom which escape may be difficult (or impossible). The industrial sector, therefore, should also be listed as a sector that can actualize the diversification process and boost economic performance in the EMEs. There should also be policy consistence in curtailing the declining trend of industrial production. This study investigates monetary policy shocks and industrial production in BRICS countries. The study is presented in four separate but related essays. The first (chapter three) employs a Panel Structural Vector Autoregressive model (𝑃−𝑆𝑉𝐴𝑅) to investigate how monetary policy shocks affect industrial output in BRICS countries using monthly data for the period 1994:1 to 2013:12. A nine variable 𝑃−𝑆𝑉𝐴𝑅 with short-run restrictions among the variables is constructed for the analysis. The study finds that variations in the exchange rate have the largest impact on industrial output in the BRICS countries. It is also observed that inflation rates significantly increase industrial output, peaking after about 11 months. This suggests that monetary authorities should be cautious when formulating policies aimed at reducing the inflation rate because of the spill over effect on industrial output. Further analysis reveals that interest rates have a marginal effect on exchange rates, while money supply makes a relatively large contribution to exchange rate fluctuations. Again, it is observed that changes in money supply exert a very large impact on variations in the rate of inflation. Thus, money supply plays an important role in curbing inflation. The study also analyses variations in interest rates, money supply and inflation and recommends that monetary authorities in the BRICS countries adjust interest rates, and not money supply, in response to inflation expectations. The second essay (chapter four) models exchange rate behaviour in the BRICS countries. This study examines global shocks and variations in the BRICS countries local currency/United States dollar exchange rate using the symmetric Generalized Autoregressive Conditional Heteroscedasticity (GARCH), Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH) and Asymmetric Power Autoregressive Conditional Heteroscedasticity (APARCH) models to determine the relationship between the two. The GARCH, EGARCH and APARCH are employed under normal (Normal Gaussian) and nonnormal (Student‘s t and Generalized Error) distributions. Using monthly exchange rate data covering the period 1994:01–2013:12, the study finds that exchange rates in Brazil, Russia and India can well be modelled by the symmetric GARCH (1,1) model while in China, the three models perform well. In South Africa, the results of the three models also perform well but the EGARCH (1,1) model is found to be the best. Further analyses of the models reveal that the Student‘s t distribution produces better fit for estimating exchange rate variations and global shocks in BRICS countries compared to the Normal Gaussian and GED values under the nonnormal distributions. Overall, the study recommends that the BRICS countries should consider the impact of oil prices and global interest rates when formulating and implementing policies that impact on exchange rates. The third essay (chapter five) examines whether the five BRICS countries share similar business cycles and determines the probability of any of the countries moving from a contractionary regime to an expansionary regime. The study further examines the extent to which changes in monetary policy affect industrial output in expansions relative to contractions. Employing the Peersman and Smets (2001) Markov-Switching Model (MSM) and monthly data from 1994:01 – 2013:12, the study reveals that the five BRICS countries have similar business cycles. The results further demonstrate that the BRICS countries‘ business cycles are characterized by two distinct growth rate phases: a contractionary regime and an expansionary regime. It is observed that area-wide monetary policy has significantly large effects on industrial output in recessions as well as in booms. It is also established that there is a high probability of moving from state 1 (recession) to state 2 (expansion) and that on average, the probabilities of staying in state 2 (expansion) are high for each of the five countries. It is, therefore, recommended that the BRICS countries should sustain uniform policy consistency (monetary policy), especially as they formulate and implement economic policies to stimulate industrial output. The fourth essay (chapter six) investigates the long run and short run dynamics between industrial production and the factors affecting production in the emerging market economies of BRICS countries. Using the Chudik and Pesaran (2013) P-ARDL model and monthly data from 1994:01 – 2013:12, the study finds evidence of a cointegrating relationship between industrial production and selected variables. It is further observed that capital, labour, per capita income and exports have a positive long run impact on industrial production in the BRICS countries. However, a currency appreciation (an increase in the exchange rate) has a negative impact on industrial production. In the short run, it is found that imports, exports, exchange rates, labour, capital and per capita income significantly affect industrial production. The policy implication stemming from the analysis is that a sound economic policy is important for output production and industrialization in BRICS countries while poor policy will result in a nexus of constraintsfrom which escape may be difficult (or impossible). The industrial sector, therefore, should also be listed as a sector that can actualize the diversification process and boost economic performance in the EMEs. There should also be policy consistence in curtailing the declining trend of industrial production. Show less

This study investigates monetary policy shocks and industrial production in BRICS countries. The study is presented in four separate but related essays. The first (chapter three) employs a Panel Structural Vector Autoregressive model (𝑃−𝑆𝑉𝐴𝑅) to investigate how monetary policy shocks affect industrial output Show more