This study investigates an e-commerce platform's incentive to voluntarily disclose demand information to an upstream manufacturer. In contrast to previous studies that emphasize the platform's mandatory (or ex-ante) information disclosure, this study examines voluntary (or ex-post) information disclosure, which allows the platform to selectively decide whether to perform information disclosure based on the level of forecast demand. The typical online selling channels in which the platform or the manufacturer (or both) play the role of seller are identified as reselling, marketplace, and hybrid cases. In each transaction case, the interactions between the platform's information disclosure strategy, the level of forecast demand, the platform's forecasting capability, the degree of demand uncertainty, and channel substitutability are analyzed. We find that information on good market demand should be withheld in the reselling case, information indicating a slightly below-average market condition should be withheld in the marketplace case, and information on good or poor demand should be withheld in the hybrid case. The platform is more likely to perform information disclosure as the forecasting capability or the degree of demand uncertainty increases. Moreover, both the platform and the manufacturer can benefit from a well-formulated voluntary information disclosure strategy. Our findings show e-commerce platforms how to better exploit demand forecast information in a voluntary disclosure setting and provide an explanation for practices such as their focus on improving their forecasting capability and market potential. •This paper studies a platform's voluntary information disclosure to a manufacturer.•Three types of transaction scenarios (reselling, agency, hybrid) are considered.•The platform is more likely to disclose information if the forecasting capability or demand uncertainty is high.•A higher demand forecasting ability or demand uncertainty level may promote the platform to be more inclined to disclose information.