FORECASTING MARKET SHARE USING A FLEXIBLE LOGISTIC MODEL

There is a strong competition from low-priced imported catfish fillets resulting in a declining market share for domestic farm-raised catfish fillets. To match the competition, catfish processors are embarking on pricing policy measures that are volume-oriented instead of profit- or image-oriented. This could be an effective short-run pricing policy measure for optimal long-run sustainability and profitability of the industry. Volume pricing strategies are aimed at meeting target sales volumes or market shares. This paper explores and compares the performance of the standard logit, the inverse power transformation (IPT) logit and the logarithmic version of the inverse power transformation logit models in terms of generating forecasts for market share of U.S. farm-raised catfish fillets. The results suggest a better performance of the log-IPT in every aspect compared to the linear standard logit and the IPT logit models.