Multigeneration Product Diffusion in the Presence of Strategic Consumers

Frequent new product releases pose significant challenges for firms as they manage successive generations of product diffusion. We develop an analytical model to study the effect of different purchase options by strategic consumers on a firm’s profit and the firm’s strategies for the timing and pricing of its successive generations of product diffusion. We show that consumers’ strategic behavior, although adversely affecting the sales of the first-generation product, positively influences the sales of the second-generation product through an initial “seeding” effect. The influence of strategic consumers on profit and sales depends largely on the discount-to-price ratio of the first generation relative to the performance improvement in the second generation. When the relative discount is small, the seeding effect on the second-generation product dominates. When the relative discount is large, the “cannibalization” effect on the first-generation product dominates. We further demonstrate that the optimal entry timings recommended in the literature (i.e., “now,” “maturity,” or “never”) can occur under different market conditions. In general, higher performance improvement and lower salvage value would support a higher optimal price, a larger discount, and a later introduction time. In addition, the firm can benefit from patient consumers when the performance improvement is relatively small, and it can induce the complete substitution of the later generation for the earlier generation when the performance improvement is relatively large. Overall, our model provides a theoretical foundation for understanding the effect of consumer strategic behavior on product diffusion, and our results offer important insights about firms’ multigeneration product diffusion strategies. The online appendix is available at https://doi.org/10.1287/isre.2017.0720 .

• 저널Information Systems Research · 29(1) · 206–224
• 토픽Innovation Diffusion and Forecasting · Management Science and Operations Research
• DOI10.1287/isre.2017.0720
• 저자Zhiling Guo, Jianqing Chen