Modelling multinational telecommunications demand with limited data

Forecasting the diffusion of innovations in the telecommunications sector is a constantly recurring problem for national providers. The problem is characterised by short data series making the estimation of model parameters unreliable. However, the same innovation will be diffusing simultaneously in other national markets, although with a different start date. The use of these cross-sectional data in constructing innovation diffusion models is investigated here. Four models for pooling the cross-sectional data are described and two diffusion models are discussed although only one, the Gompertz model, is used throughout. Three innovation data sets are used in the evaluation of the models: digital cellular telephones, ISDN connections and fax connections. The pooled diffusion forecasts proved to be more accurate in several comparisons relative to a naïve benchmark and to individual forecasts when available.