¹Yuan Ze University, Chung-li, Taiwan

Correspondence: F-M Tseng, Department of International Business, Yuan Ze University, 135 Yuan Tung Rd, Chung-li, Taiwan 320, Taiwan. E-mail: fmtseng@saturn.yzu.edu.tw

Received October 2006; Accepted April 2007; Published online 11 July 2007.

Abstract

An appropriate sales forecasting method is vital to the success of a business firm. The logistic model and the Gompertz model are usually adopted to forecast the growth trends and the potential market volume of innovative products. All of these models rely on statistics to explain the relationships between dependent and independent variables, and use crisp parameters. However, fuzzy relationships are more appropriate for describing the relationships between dependent and independent variables; these relationships require less data than traditional models to generate reasonable estimates of parameters. Therefore, we have combined fuzzy regression with the logistic and Gompertz models to develop a quadratic-interval Gompertz model and a quadratic-interval logistic model, and we applied the models to three cases. Our practical application of the two models shows that they are appropriate tools that can reveal the best and worst possible sales volume outcomes.