Potentials of Sub-Saharan Africa in the Global Market for International Tourism

Abstract

This paper examines the future prospects of Sub-Saharan African region in the international market for tourism. This was achieved by analyzing past trends of international tourism arrivals and receipts in the region, and projecting these trends to the year 2010 using an amalgamation of four different time-series projection models after being evaluated by the MAPE. Results are given as confidence limits in three different scenarios. They show that arrivals of international tourists to Sub-Saharan Africa would increase from 17.9 millions in 2000 (end of observed period) to 28.9 million and 44.9 million tourists by the year 2010. The figures for receipts would go from $7.0b in 2000 to $11.0b and $15.3b by the year 2010. Receipts per capita (i.e., per tourist) would however decline at an annual rate of between 20.48% and 20.91% during the projection period. Socioeconomic impacts of these findings are given, and their implications for international marketing strategies and government public policies in Sub-Saharan Africa are discussed.

Prospects for Latin America and Caribbean Region in the Global Market for International Tourism: A Projection to the Year 2020

“…Li et al (2005) reviewed a total of 84 post-1990 studies of international tourism demand modeling and forecasting, but of these less than 9 forecasted for developing countries, and only 1 of these 9 was a country in the Latin America and Caribbean region! In order to fill this gap, and following after Oyewole (2006) on similar work for Sub-Saharan Africa, the present article makes a projection of international tourism for Latin America and Caribbean region up to the year 2020. Some countries in Latin America and Caribbean region-like Mexico-are establishing tourism development programs with long range plans up to the year 2025 (WTO, 2001).…”

“…In a review of 7 works on tourism projections, univariate time series method was found by Witt et al (2003) to be the most accurate method 4 out of the 7 studies. Several researchers (e.g., Coshall, 2006;Kulendran & Witt, 2001;Martin & Witt, 1989;Oyewole, 2006) have preferred the time series models because of their versatility under different conditions. They are held to be time and cost-effective while generating forecasts that are equally, or sometimes even more accurate compared with the behavioral models (Choy, 1984;Martin & Witt).…”