Tourism in the Caribbean: competitiveness, upgrading, linkages and the role of public private partnerships (PPP) and public policy

The main purpose of this paper is to explore and analyze the contributions that publicprivate partnerships and public policy have made in the development of tourism in the Caribbean as tools for enhancing competitiveness in the Caribbean tourism industry. The paper explores these contributions mainly in the context of the upgrading strategies that Caribbean countries have pursued over the past 15 years or so and using the lens of the tourism value chain and tourism cluster approach. The paper also analyzes the potential roles that public-private partnerships and public policy will continue to play in the future especially in the process of building linkages between the tourism sector and other sectors in order to increase net benefits from tourism to the Region. This paper is divided into five sections. In Section I, we define public-private partnerships (PPP) and describe the areas in tourism where PPP are most widely used, the tools used to implement PPP in tourism and the various forms of PPP. Economic arguments are then laid to motivate PPP as a determinant of tourism competitiveness using the tourism value-chain and tourism cluster approach. Specific case examples illustrating the contributions of PPP and public policy towards increasing tourism competitiveness are provided at a regional level and for specific areas in Sections II and III respectively. Section IV summarizes findings from the previous two sections and discusses ways to enhance the effectiveness of PPP and public policy in Caribbean tourism for increased competitiveness. Section V analyzes a few of the challenges that the Caribbean tourism sector is facing. The final section proposes new areas of intervention for PPP and public policy as tools for enhancing competitiveness in the Caribbean tourism sector in order to assist the region in addressing these challenges.

Tourism in the Caribbean: competitiveness, upgrading, linkages and the role of public private partnerships (PPP) and public policy

The main purpose of this paper is to explore and analyze the contributions that publicprivate partnerships and public policy have made in the development of tourism in the Caribbean as tools for enhancing competitiveness in the Caribbean tourism industry. The paper explores these contributions mainly in the context of the upgrading strategies that Caribbean countries have pursued over the past 15 years or so and using the lens of the tourism value chain and tourism cluster approach. The paper also analyzes the potential roles that public-private partnerships and public policy will continue to play in the future especially in the process of building linkages between the tourism sector and other sectors in order to increase net benefits from tourism to the Region. This paper is divided into five sections. In Section I, we define public-private partnerships (PPP) and describe the areas in tourism where PPP are most widely used, the tools used to implement PPP in tourism and the various forms of PPP. Economic arguments are then laid to motivate PPP as a determinant of tourism competitiveness using the tourism value-chain and tourism cluster approach. Specific case examples illustrating the contributions of PPP and public policy towards increasing tourism competitiveness are provided at a regional level and for specific areas in Sections II and III respectively. Section IV summarizes findings from the previous two sections and discusses ways to enhance the effectiveness of PPP and public policy in Caribbean tourism for increased competitiveness. Section V analyzes a few of the challenges that the Caribbean tourism sector is facing. The final section proposes new areas of intervention for PPP and public policy as tools for enhancing competitiveness in the Caribbean tourism sector in order to assist the region in addressing these challenges.

Caribbean tourism and agriculture: Linking to enhance development and competitiveness

This study examines current trends in tourism and agriculture in Caribbean countries and the strategy for linking them in order to facilitate their future development. The tourism industry has, in the past, developed largely apart from other sectors such as agriculture. On the other hand, agriculture has developed mainly to satisfy export markets. Domestic agriculture has had limited development and has therefore been displaced to a considerable extent by food imports. The recent promotion of agriculture tourism linkages is an attempt to enhance the local value added of the tourism industry, while at the same time promoting the development of domestic agriculture. However, it is argued that agriculture-tourism linkage per se will not facilitate the development of either tourism or agriculture. The nature of the tourism product in each country has to be understood before effective strategies could be devised for improving competitiveness. A similar approach is also necessary in respect of the agriculture sector. Increased linkage between tourism and agriculture could be enhanced through the adoption of a cluster-based strategy for improving the competitiveness of the tourism sector and for improving the livelihoods of communities and rural areas.

Weather forecasting for Eastern Amazon with OLAM model

O modelo OLAM tem como característica a vantagem de representar simultaneamente os fenômenos meteorológicos de escala global e regional através de um esquema de refinamento de grades. Durante o projeto REMAM, o modelo foi aplicado para alguns estudos de caso com objetivo de avaliar o desempenho do modelo na previsão numérica de tempo para a região leste da Amazônia. Estudos de caso foram feitos para os doze meses do ano de 2009. Os resultados do modelo para estes casos foram comparados com dados observados na região de estudo. A análise dos dados de precipitação mostrou que o modelo consegue representar a distribuição média da precipitação acumulada e os aspectos da sazonalidade da ocorrência dos eventos, mas não consegue prever individualmente a acumulação de precipitação local. No entanto, avaliação individual de alguns casos mostrou que o modelo OLAM conseguiu representar dinamicamente e prever, com alguns dias de antecedência, o desenvolvimento de fenômenos meteorológicos costeiros como as linhas de instabilidade, que são um dos mais importantes sistemas precipitantes da Amazônia.

The bias in reversing the Box-Cox transformation in time series forecasting: An empirical study based on neural networks

The Box-Cox transformation is a technique mostly utilized to turn the probabilistic distribution of a time series data into approximately normal. And this helps statistical and neural models to perform more accurate forecastings. However, it introduces a bias when the reversion of the transformation is conducted with the predicted data. The statistical methods to perform a bias-free reversion require, necessarily, the assumption of Gaussianity of the transformed data distribution, which is a rare event in real-world time series. So, the aim of this study was to provide an effective method of removing the bias when the reversion of the Box-Cox transformation is executed. Thus, the developed method is based on a focused time lagged feedforward neural network, which does not require any assumption about the transformed data distribution. Therefore, to evaluate the performance of the proposed method, numerical simulations were conducted and the Mean Absolute Percentage Error, the Theil Inequality Index and the Signal-to-Noise ratio of 20-step-ahead forecasts of 40 time series were compared, and the results obtained indicate that the proposed reversion method is valid and justifies new studies. (C) 2014 Elsevier B.V. All rights reserved.

Determining spatial resolution in spatial load forecasting using a grid-based model

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Structuring an ontology of the basic vocabulary of tourism

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Estimation of a preference map of new consumers for spatial load forecasting simulation methods using a spatial analysis of points

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The Economic Impacts of Tourism in Ouro Preto, MG, Brazil

The tourism spending like other activities has direct and secondary effects on the economy, and presents complex interaction with other activities deserving a special treatment for measuring its contribution to the global result of production and consumption. In this paper, it is used the Money Generation Model to measure the global economic impact of tourism sales in Ouro Preto, this method is not so limited by the data and it is able to produce good approximations to reality. It was not possible to adopt the WTO methodology due to data limitation. The results revealed the real importance of tourism for Ouro Preto, representing up to 10.4% of GDP in 2002, up to 21.8% of tax revenues in 2004, and approximately 11% of the region’s population in 2002 was related to tourism sales. Some actions can be outlined from these results in order to illustrate the current economic reality of the tourism in Ouro Preto. It is also possible to improve the tourist planning accomplished by the local City Hall in a coherent way with the economic results generated by the tourism.

Hospitality, Restaurant and Tourism Retreat Luncheon

Thank you for inviting me to be here with you today - it is a real treat. I am a big supporter of the Hospitality, Restaurant and Tourism Management program and have great expectations for it. In fact, I expect this program will grow and grow and grow, because I know from past experience what a program like this can do.

Analysis of NDVI time series using cross-correlation and forecasting methods for monitoring sugarcane fields in Brazil

Brazil is the largest sugarcane producer in the world and has a privileged position to attend to national and international market places. To maintain the high production of sugarcane, it is fundamental to improve the forecasting models of crop seasons through the use of alternative technologies, such as remote sensing. Thus, the main purpose of this article is to assess the results of two different statistical forecasting methods applied to an agroclimatic index (the water requirement satisfaction index; WRSI) and the sugarcane spectral response (normalized difference vegetation index; NDVI) registered on National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA-AVHRR) satellite images. We also evaluated the cross-correlation between these two indexes. According to the results obtained, there are meaningful correlations between NDVI and WRSI with time lags. Additionally, the adjusted model for NDVI presented more accurate results than the forecasting models for WRSI. Finally, the analyses indicate that NDVI is more predictable due to its seasonality and the WRSI values are more variable making it difficult to forecast.

Hybrid Water Demand Forecasting Model Associating Artificial Neural Network with Fourier Series

This paper addressed the problem of water-demand forecasting for real-time operation of water supply systems. The present study was conducted to identify the best fit model using hourly consumption data from the water supply system of Araraquara, Sa approximate to o Paulo, Brazil. Artificial neural networks (ANNs) were used in view of their enhanced capability to match or even improve on the regression model forecasts. The ANNs used were the multilayer perceptron with the back-propagation algorithm (MLP-BP), the dynamic neural network (DAN2), and two hybrid ANNs. The hybrid models used the error produced by the Fourier series forecasting as input to the MLP-BP and DAN2, called ANN-H and DAN2-H, respectively. The tested inputs for the neural network were selected literature and correlation analysis. The results from the hybrid models were promising, DAN2 performing better than the tested MLP-BP models. DAN2-H, identified as the best model, produced a mean absolute error (MAE) of 3.3 L/s and 2.8 L/s for training and test set, respectively, for the prediction of the next hour, which represented about 12% of the average consumption. The best forecasting model for the next 24 hours was again DAN2-H, which outperformed other compared models, and produced a MAE of 3.1 L/s and 3.0 L/s for training and test set respectively, which represented about 12% of average consumption. DOI: 10.1061/(ASCE)WR.1943-5452.0000177. (C) 2012 American Society of Civil Engineers.

Strategic environmental assessment in tourism planning - Extent of application and quality of documentation

Strategic environmental assessment (SEA) has been applied throughout the world in different sectors and in various ways. This paper reports on results of a PhD research on SEA applied to tourism development planning, reflecting the situation in mid-2010. First, the extent of tourism specific SEA application world-wide is established. Then, based on a review of the quality of 10 selected SEA reports, good practice, as well as challenges, trends and opportunities for tourism specific SEA are identified. Shortcomings of SEA in tourism planning are established and implications for future research are outlined. (C) 2012 Elsevier Inc. All rights reserved.