The effects of big-data-driven information service sales on cooperation modes in a supply chain

With the rapid development of technology, big data-driven information services are gradually becoming an important tool for firms on e-commerce platforms. Firms can achieve more accurate demand forecasting and optimize the decision-making process through information. This paper examines how big-data-driven information services affect supply chain decisions by constructing Stackelberg models involving a platform and a manufacturer under two cooperation modes: reselling and agency. The platform determines the skill level of data analytics and provides two information services with different data amount, whereas the manufacturer decides which one to purchase. These choices jointly affect the forecasting accuracy for demand. Through comparison analyses, we find that information services exhibit a significant leverage effect, which confirms the value of information. However, it is unexpected that information services are not always effective in counteracting demand uncertainty, which is related to the investment cost of data analytics skill level. Additionally, the efficiency of information services also differs under two modes. With high investment cost, information services are efficient in reselling mode but inefficient in agency mode. Finally, we reveal that the manufacturer favours reselling mode when the information service fee is low and investment cost is moderate. Otherwise, he selects agency mode. The platform prefers agency mode only when the information service fee is high and investment cost is low. Both parties can achieve win-win situations under certain conditions. These findings clarify the value of information services under different cooperation modes, providing a key reference for cooperation between the platform and manufacturer.