Statistical Models for Forecasting Tourists’ Arrival in Kenya

Albert Orwa Akuno,Charles Wambugu Mwangi,Lawrence Areba Bichanga,Michael Oduor Otieno

doi:10.4236/ojs.2015.51008

Albert Orwa Akuno, Charles Wambugu Mwangi + Show 2 more

Open Access

https://doi.org/10.4236/ojs.2015.51008

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Abstract

In this paper, an attempt has been made to forecast tourists’ arrival using statistical time series modeling techniques—Double Exponential Smoothing and the Auto-Regressive Integrated Moving Average (ARIMA). It is common knowledge that forecasting is very important in making future decisions such as ordering replenishment for an inventory system or increasing the capacity of the available staff in order to meet expected future service delivery. The methodology used is given in Section 2 and the results, discussion and conclusion are given in Section 3. When the forecasts from these models were validated, Double Exponential Smoothing model performed better than the ARIMA model.

Highlights

Tourism is one of Kenya’s major foreign exchange earners
The forecast of tourists’ arrivals is important since it would enable the tourism related industries like airlines, hotels and other stakeholders to adequately prepare for any number of tourists at any future date
Once the presence of trend is detected in the data, smoothing of the time series data follows

Summary

Introduction

Tourism is one of Kenya’s major foreign exchange earners. This greatly depends on the arrival of various groups of tourists. The forecast of tourists’ arrivals is important since it would enable the tourism related industries like airlines, hotels and other stakeholders to adequately prepare for any number of tourists at any future date. An attempt has been made to forecast tourists’ arrivals using statistical time series modeling techniques—Double Exponential Smoothing and Auto-Regressive Integrated Moving Average (ARIMA). [1] used the same models to forecast milk production in India. [2] used univariate SARIMA models to forecast tourists’ demands in India. (2015) Statistical Models for Forecasting Tourists’ Arrival in Kenya. The analysis was carried out using R-language, Excel and Minitab version 16.1.1

Methods

Results

Conclusion