Modeling Pre-Launch New Product Demand Forecasting using Bass Diffusion in Creative Industry

Abstract

Micro, Small, and Medium Industries (IMKM) necessitate significant focus due to their economic contributions. In Indonesia, the creative industry, exhibits diverse and complex product innovations and variations, alongside a heightened risk of market failure. A market forecasting prediction model is essential prior to the product launch. However, this task becomes challenging when sales data is insufficient. A forecasting model applicable to the pre-launch stage of a new product is the Bass diffusion model, which relies on the optimization of model parameters. This study seeks to model the forecasting of new product demand prior to launch using the Bass diffusion model, specifically for creative industry products, and to assess the adoption pattern of these products within IMKM. The study identified a bass diffusion model applicable to the creative industry through an analysis of fifteen batik products, determining the optimal p, q, and m parameters based on the minimal error value. This study evaluates the adoption characteristics of IMKM batik products, noting similarities to the sales patterns of computer products and a product life cycle ranging from twelve to thirty-six months. This study identifies the parameter values for creative industry products, with an average p parameter of 0.0336, a q parameter of 0.3770, and a m parameter of 497.27. The long dress, as a category of women's fashion, exhibits the longest product life cycle, significant market potential, and a rapid diffusion rate, characterized by an average p parameter of 0.0198, a q parameter of 0.3739, and a m parameter of 721.