Optimal timing of big data application in a two-period decision model with new product sales

Abstract

We study a firm's strategy in adopting big data technology to motivate consumer demand over two periods. In the first period, the firm designs a product to sell to the market and determines whether to apply big data to attract more consumers. In the second period, the firm designs a new product and determines whether to sell the old product and the new product simultaneously, where big data can also be applied in this period to stimulate more demands. We formulate this problem into four models considering whether the firm adopts big data in the first period and/or the second period, and whether the firm only sells the new product or sells both the old and new products in the second period. We find that the firm prefers to apply big data over both periods when the cost is low, only over the second period when the cost is median and will not apply big data when the cost is high. Interestingly, only applying big data over the first period also may bring the most profits with heterogeneous big data coefficients. Furthermore, applying big data in the second period is the better choice for the social welfare.