An exponential smoothing model for predicting traffic in the library and at the reference desk

Abstract

Purpose

The purpose of this study is to develop a mathematical model that can be used to forecast the number of individuals who enter the library as well as the number of patrons that seek assistance at the reference desk of the library. An accurate estimate of demand at the reference desk is valuable for effective staffing decisions.

Design/methodology/approach

An exponential smoothing model (Winter's model) was developed for forecasting. Data were gathered at the University of Tennessee at Chattanooga for an entire year. Using these data, an exponential smoothing model was formulated for forecasting the number of patrons seeking assistance. Since the data showed no trend but the presence of two seasonality factors, one for the week‐of‐the‐semester effect and one for the day‐of‐the‐week effect, the Winter's method appeared to be best suited. The Winter's method develops a formula from the data and allows the formula to be continuously fine‐tuned as new observations come in day after day.

Findings

The modified Winter's exponential smoothing model proved to be a good predictor of the number of patrons seeking assistance. In spite of large natural random variability present in the data, the actual values seem to follow the forecasts very closely.

Originality/value

It is vital to be able to forecast the number of clients at the reference desk that seek assistance per day. The modified exponential smoothing model is a valuable tool for such forecasting.

Citation

Ahmadi, M., Dileepan, P., Murgai, S.R. and Roth, W. (2008), "An exponential smoothing model for predicting traffic in the library and at the reference desk", The Bottom Line, Vol. 21 No. 2, pp. 37-48. https://doi.org/10.1108/08880450810898283