Abstract
The South African tourism industry is expected to develop substantially over the next fifteen years, due to anticipated high tourism market growth rates. However, tourism demand is subject to a host of uncontrollable factors, which are difficult to measure and project. Despite this fact, the tourism industry of a country, including both private sector and public sector operators, needs scientifically accepted projection bases to make investment and other strategic decisions. In this article we aim to convey the results and recommendations of an empirical study based on the Delphi research model, and to indicate the implications thereof for future national tourism strategies of South Africa. The approach, methodology and techniques used in the research are relevant to researchers internationally, and the recommendations are useful for national tourism policy and strategy formulation in any geographical context.
Highlights
Background to the researchAgainst the background of far reaching political changes in South Africa over the past three years, windows of substantial opportunity are opening for the tourism industry in the subcontinent of Africa
The application of the Delphi technique as a marketing research tool in the South African tourism industry has provided a number of significant findings and indicators of the likely future tourism scenario of the country
The major limitations of the study is that expert opinions are more reliable for aggregate forecasting of likely tourism occurrences and trends
Summary
Background to the researchAgainst the background of far reaching political changes in South Africa over the past three years, windows of substantial opportunity are opening for the tourism industry in the subcontinent of Africa. The Delphi technique offers certain limitations or disadvantages, (see e.g. Kaynak & Macauly, 1984): - So-called expert opinions are generally less satisfactory than hard facts; Responsibility is dispersed, and good and bad estimates are given equal weight; and - The method is usually more reliable for aggregate forecasting of tourism trends than for developing reliable breakdowns by specific territory, customer groups (e.g. leisure, business, special interest) or product type (sightseeing, culture, adventure, sporting events, etc.).
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