Management and Policy Implications of Coastal Tourism Forecasts

Abstract

One of the fastest growing segments of the world's tourism industry is coastal tourism. As interest in coastal tourism intensifies, the increasing demand on coastal resources will require local governments and private businesses to obtain information on future tourism demand. However, management agencies often fail to incorporate forecasting results into the strategic planning process. The purpose of this article is to present comprehensive forecasting information of coastal tourism demand using various tourism-related time series variables, and provide public and private agencies with a framework for integrating coastal demand forecasts into the strategic planning process. Two different quantitative forecasting techniques were used to project future coastal tourism demand in South Carolina: Auto Regressive Integrated Moving Average (ARIMA) methods for short-term and midterm forecasts and Naive 1 method for long-term forecasts. Short-term forecast results suggest accommodation taxes in coastal counties will steadily increase over the next several years, while midterm forecasts of coastal tourism-related employment indicates a significant increase in labor force requirements. Long-term forecasts imply visitation to and demand of beaches and coastal resources will continue to intensify. In the coming years, tourism-related businesses in coastal destinations will be challenged to provide satisfactory experiences due to a small labor pool of quality workers. Failure to incorporate forecasts in the strategic planning process may result in the degradation of tourism resources, resulting in a reduction of tourist visitation. Integrating accurate forecasts into the strategic planning process are essential to improving the likelihood of sustainable development at tourism destinations.