A critical problem that beleaguers governments in the promotion of green development is determining which approach to employ in establishing an efficient green subsidy scheme. In this study, we scrutinise the effects of three government subsidy schemes: a green non-subsidy (GNS), a green product subsidy (GPS), and a green innovation subsidy (GIS). Taking social welfare into consideration, the optimal green subsidy scheme of governments in different settings is investigated. Interestingly, we find that a green subsidy is not always a good choice for the government. When the cost of green innovation is particularly low, or when both the cost of green innovation and the variable production cost of green product are high, if the environmental improvement effectiveness yielded by green innovation is insignificant, the GNS is the best. Otherwise, both the GPS and the GIS achieve greater levels of social welfare. In addition, counter to intuition, the GPS outperforms the GIS when the cost of green innovation is sufficiently high and green innovation reduces the variable production cost of green product significantly, even if the GIS can directly help to lighten the green innovation cost load. However, from the perspective of maximising subsidy efficiency, the GIS is always better than the GPS.

Adding an online channel by cooperating with an online intermediary not only allows a brick-and-mortar (B&M) retailer to reach a larger potential market, but it also allows the B&M retailer to collect online consumer reviews (OCRs) from the online intermediary. OCRs can provide additional information for consumers to mitigate their uncertainty about product valuation. In this article, we develop a game-theoretic model to investigate how OCRs affect the B&M retailer's channel strategy and business model choice. Consumers may be self-evaluating or reviews-referenced, depending on whether they use OCRs to update their product valuation. We show that negative OCRs will deter the B&M retailer from adding an online channel by cooperating with the intermediary. Counterintuitively, the B&M retailer can still benefit from cooperating with the intermediary if the information disclosed by OCRs is only slightly negative. We also show that the B&M retailer's optimal strategy varies with the commission rate, the increase in market size achieved by cooperating with the intermediary, the proportion of reviews-referenced (self-evaluating) consumers, and the information disclosed by OCRs. Interestingly, when the commission rate is not too high and the increase in market size achieved by cooperating with the intermediary is moderate, more review-referenced customers and more positive information disclosed by OCRs will shift the B&M retailer's optimal business model from the agency model to the reselling model, then back to the agency model. This article reveals the importance of OCRs, and provides physical stores with valuable knowledge of their online expansion strategies and business model choices under various sets of market conditions.