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

Sustainability has become one of the key elements of development for most tourist destinations. Some cities have adopted a sustainable development strategy as a long-term solution in improving socio-economic, cultural, and environmental practices. Traditionally, destinations have used events to achieve community enrichment, protect the natural environment, and create or maintain national pride. The aim of this research was to analyse the impact of events on sustainable tourism development in Durban. The study analysed the perceptions of key stakeholders regarding the contribution of events to socio-economic growth of the city of Durban. In carrying out the research, a mixed method approach was used. A total of 400 questionnaires were administered and 25 in-depth interviews were conducted. The results show that there are economic spin offs resulting from visitor spending during major events in the City. Furthermore, the study shows that although events can be used as a tool for sustainable tourism development, the challenge is the unbalanced racial structure within the industry, poor state of the economy, and limited access to business start-up capital for SMMEs. The study concludes that events play a vital role in socio-economic growth and development of the tourism sector in Durban and recommends multi-stakeholder collaboration and partnerships to ensure sustained tourism growth. Show less

Sustainability has become one of the key elements of development for most tourist destinations. Some cities have adopted a sustainable development strategy as a long-term solution in improving socio-economic, cultural, and environmental practices. Traditionally, destinations have used events to achieve community enrichment, 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

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