This paper considers a hybrid-format online retailing supply chain in which a manufacturer sells products to an online retailer and an intermediary with a wholesale contract, the retailer sells them through the intermediary by paying a commission fee (i.e. agency selling format), and the intermediary resells products as an e-tailer (i.e. reselling format). We use a theoretical model to answer a key question: whether the intermediary has an incentive to share demand information with others, and if it shares, which strategy is most beneficial to each member? Four information-sharing models are established and the results show that the intermediary always has incentive to share information voluntarily, and the best strategy strongly depends on the channel competition intensity and proportional fee. In addition, the manufacturer (retailer) can obtain profit if the intermediary only shares information with him (her), and all members can achieve a Pareto improvement (i.e. win–win–win situation) when both the manufacturer and retailer are informed. We further examine the impact of platform cost to demonstrate the robustness of results. When manufacturer cooperates with the retailer, the intermediary always intends to share information, whereas it has no incentive to do so if the intermediary and retailer make a coalition.

Population aging has become a notable and enduring demographic phenomenon worldwide. Older adults’ walking behavior is determined by many factors, such as socioeconomic attributes and the built environment. Although a handful of recent studies have examined the influence of street greenery (a built environment variable readily estimated by big data) on older adults’ walking behavior, they have not focused on the spatial heterogeneity in the influence. To this end, this study extracts the socioeconomic and walking behavior data from the Travel Characteristic Survey 2011 of Hong Kong and estimates street greenery (the green view index) based on Google Street View imagery. It then develops global models (linear regression and Box–Cox transformed models) and local models (geographically weighted regression models) to scrutinize the average (global) and location-specific (local) relationships, respectively, between street greenery and older adults’ walking time. Notably, green view indices in three neighborhoods with different sizes are estimated for robustness checks. The results show that (1) street greenery has consistent and significant effects on walking time; (2) the influence of street greenery varies across space—specifically, it is greater in the suburban area; and (3) the performance of different green view indices is highly consistent.