The museums visitors seasonal forecasting model: the UK case

P. 79–80.

Pavlova E.

In recent years, an increase in interest in museum activities has been observed, the number of museum visitors shows a stable positive trend. The research question of this paper is as follows: which months for museums have maximum and minimum attendance rates? The aim of the research is to predict the number of visitors to United Kingdom museums per month, both at the macro-level (country) and at the level of individual museums.  For forecasting purposes, seasonal multiplicative forecasting models with a linear and logarithmic trend are used. The used model makes it possible to identify the seasonal component of each month in the structure of demand for museum services.  Three indicators are used to assess the accuracy of the model: Mean Error (ME), Mean Average Percentage Error (MAPE), and Root Mean Square Error (RMSE). The obtained results allow us to use the developed model for a point forecast of the number of visitors to UK museums for the month. In addition, seasonal components of each month were identified. These indicators make it possible to identify the most active and passive months of visiting museums, and can be used to arrive at managerial decisions concerning the organization of work with museum visitors. 

Keywords: forecasting, museums, Additive models, multiplicative model

In book

Proceedings of Analytics for Management and Economics Conference AMEC 2019

St. Petersburg: [б.и.], 2019.