Capacity forecasting at Kenyan Airports
Planning for growth in capacity requires accurate prediction of future volume data. Airports, like other national facilities requires good knowledge of both economic and social trends that is currently undergoing in a nation and data of the past to accurately foretell the future which it aways tries to pursue. Since investment of such facilities are huge, accurate future estimates is paramount for efficient and cost effective expansion or growth strategy. Today it is well known that air transportation is basically an economic activity and is also dependent on socioeconomic factors of the country and the region it operates in as it is also a key contributor to national economy. This study is focused on estimating future air cargo capacity for airports and in particular JKIA. It demonstrated a better tool that provide accurate forecast to predict future capacity where historical data is not accurate enough for prediction and bearing in mind that this is an industry that is highly dynamic in nature. Multi-linear regression model was developed to predict future export cargo volume as the dependent variable dependent on other eight socioeconomic parameters which were deemed significant and useful in this forecast model. The available data for the selected indicators were also statistically analyzed and were observed that most are highly volatile by themselves. Some of the Limitations of the study were due to limited and inaccurate data. Many organizations do not keep data that can be useful for good forecast and those that have do not avail it. This is a challenge for especially those that are responsible for planning to collect and store proper data for good forecast. Other quantitative analysis like simulation can also be applied as support for this model whenever possible and the same result obtained herein can be used with a good probability to determine GDP forecast.
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