Incorporating a choice-based diffusion model into a bi-objective multi-generation product optimization problem under consignment stock policy

Rapid changes and evolution in technological innovation have spilled over many industries and compelled firms to release new products periodically. The advent of new products intensifies the importance of analyzing sales data trends and finding the most profitable portfolio that can no longer be ignored in production planning. The topic of diffusion processes has evoked considerable interest from academics and practitioners to forecast sales patterns of two or three competitive generations. However, there is still a lack of in-depth discussion on the effects of core determinants on customers' preferences and choices. This paper bridges the gaps in the literature by conceptualizing the interaction effects among current and new products on diffusion processes that could affect supply chain operations. Specifically, the Bass diffusion model (BDM) is modified to estimate market volume, advertisement effects, and sales data trends, then combined with a choice model to examine how consumers' propensities affect the choice probability of alternatives. The proposed choice-based diffusion model is incorporated into a supply chain problem for joint planning on a production-location-inventory problem concerning the economic and social aspects of designing multi-generation production lines. The model formulation is a bi-objective mixed-integer nonlinear problem with a computation burden. Thus an outer approximation-based algorithm is proposed to reduce computational complexity and combined with an augmented ε-constraint to generate efficient Pareto sets. The model is validated by conducting a case study in Iran and compared to other established models. The computational results demonstrate the proposed model outperforms the expert forecasts, and there are no significant differences between the total sales estimated by the proposed model and the actual sales. The manager is advised to adopt a conscious policy for adoption engagement under supply constraints. It should price the products in a way be more tightly aligned with customers’ desirability and overcome the supply constraints by increasing production or storage capacities. •A bi-objective optimization approach is applied to design and plan multi-generational products.•A novel choice-based diffusion model is proposed for demand forecasting.•The proposed non-convex model is transformed into a convex problem and solved by an outer approximation-based algorithm.•Model verification is done by conducting a case study