Consumer Decision Making in a Multi-Generational Choice Set Context

Most new product adoption models have focused on single-generation products. Only recently have researchers begun to focus on the importance of analyzing consumers' purchase demands in multi-generation products. This paper proposes a model that incorporates both initial and repeat purchases and allows for leap-frogging behavior for multi-generation technological products. Whereas most new product adoption models are based on aggregate market sales, the proposed model is estimated and validated on individual consumer data. Within a logistical modeling framework, the model combines a purchase incidence (buy/not buy) component and generation choice components for each time period. These model components allow for individual heterogeneity. Purchase probabilities for buyers are captured as a function of purchase history, buyer expectations of future generations, and preferences for the currently available options. The proposed model is parsimonious. It requires relatively simple data for estimation. It is empirically tested using individual-level purchase data from an illustrative pilot study in the multi-generation personal computer (PC) market. The model fits and explains individual consumers' actual purchase behaviors reasonably well. The research tries to determine the strategy dynamics and key success factors (KSFs) for excellence in performance of the so-called 'tiger' SMEs in Singapore.