In this paper, we study a restaurant’s take-out model choice and the coordination of an online take-out supply chain. To this end, we first derive the restaurant’s optimal price and/or platform’s commission rate under the restaurant’s three possible take-out models: do not provide online take-out service (NTO model), provide take-out service by joining an online take-out platform (TOF model), or provide online take-out service by itself (TOH model). We investigate the restaurant’s optimal take-out model choice. We then derive the optimal decisions of price and the take-out model under centralization, and study the online take-out supply chain coordination problem. We find that, first, the restaurant may not always benefit from providing online take-out service. It will be beneficial only if the incremental demand generated by take-out service is high. Second, under the centralized supply chain, the TOF model is always better than the TOH model. Meanwhile, when the incremental demand is high, the restaurant should choose the TOF model; otherwise, the NTO model is better. Third, we find that the restaurant’s take-out price and model choice decisions under a decentralized supply chain are both inconsistent with that under the centralized supply chain. Last, we design a sales reward contract which can achieve the price and model choice coordination as well as win-win outcomes for all supply chain members.

The pricing of ride-hailing platforms (e.g., Didi Rider and Uber) is heavily and simultaneously influenced by the cross-group network effect and congestion effect. To analyze the bilateral pricing of ride-hailing platforms under the influence of these two effects, in this paper we construct a game-theoretic model under four different scenarios and analyze the equilibrium outcomes. The results show that: (1) when both passengers and drivers are sensitive to hassle costs, if the cross-group network effect on the passenger side is higher than that on the driver side, then the platform’s pricing on both sides increases with the increase in the congestion effect, otherwise the prices on both sides of the platform decrease with the increase in the congestion effect; (2) when passengers are sensitive to hassle costs and drivers are sensitive to price, if the ratio for passengers’ and drivers’ different perceptions of price and hassle cost is greater than a certain threshold, then the platform’s pricing on the passenger side increases with the increase in the congestion effect and the platform’s pricing on the driver side decreases with the increase in the congestion effect, otherwise the platform’s pricing on the passenger side decreases with the increase in the congestion effect and the platform’s pricing on the drivers’ side increases with the increase in the congestion effect; (3) when passengers are sensitive to price and drivers are sensitive to hassle costs, if the ratio for passengers’ and drivers’ different perceptions of price and hassle costs is greater than a certain threshold, then the platform’s pricing on the passenger side decreases with the increase in the congestion effect and the platform’s pricing on the drivers’ side increases with the increase in the congestion effect, otherwise the platform’s pricing on the passenger side increases with the increase of the congestion effect and the platform’s pricing on the driver side decreases with the increase in the congestion effect; (4) when both passengers and drivers are price-sensitive, if the cross-group network effect on the passengers’ side is larger than that on the drivers’ side, then the platform should decrease its pricing on both sides with the increase in the congestion effect, otherwise, if the cross-group network effect on the passengers’ side is less than that on the drivers’ side, the platform should increase its pricing on both sides with the increase in the congestion effect; (5) the platform is able to generate the highest profit in each scenario, and the results of the profit comparison between the four scenarios depends on the cross-group network effects and the congestion effects on both the passengers’ and the drivers’ sides.

This paper studies a green manufacturer’s strategic licensing of its green technology to a brown rival under the consideration of the green manufacturer’s environmental concerns. Consumers in the market have green awareness. Adopting the green technology not only helps manufacturers to reduce carbon emissions, but also to increase market sizes. The green manufacturer can choose from three technology licensing strategies, i.e., no licensing (N), royalty licensing (R) or fixed-fee licensing (F). The equilibrium licensing strategy can be derived by comparing the respective payoff after adopting the three strategies. It is found that the green manufacturer should choose fixed-fee licensing strategy when the market size expansion effect is strong, and the competition intensity is moderate; otherwise, the green manufacturer should choose royalty licensing strategy. Furthermore, it is found that when the green manufacturer is more concerned about environmental impacts, it will be more willing to choose fixed-fee licensing strategy, rather than royalty licensing strategy. Through numerical tests, some interesting results are also found. For example, the brown manufacturer might be hurt even if the cost reduction effect of technology licensing is relatively stronger. Moreover, it is found that consumer surplus and social welfare nonmonotonically change with the substitution level. In summary, this research tries to provide some guidelines to the industry and the society on better managing green technology diffusions.

The evolution of tax exemption policies and consumer preferences for low-carbon products affect firms’ optimal pricing strategy selection in a competitive duopoly market. In our study, we build a two-period pricing model to examine the pricing strategy choices between low-carbon and traditional firms. Low-carbon firms offer consumers greater value, improving their overall experience and satisfaction. Given the evolution of government policies from tax exemption to taxation for low-carbon products, we divide the changes in carbon tax into two periods. Since each firm can choose either the uniform pricing strategy (setting the same price in both periods) or the tiered pricing strategy (setting different prices for two periods), four scenarios may occur. Conventional wisdom suggests that a firm’s pricing increases should result in a reduction in consumer demand. Interestingly, our results show that as traditional firm raises prices, consumer demand for traditional products could increase simultaneously in the second period. In such a case, the low-carbon firm selects the uniform pricing strategy and the traditional firm chooses the tiered pricing strategy. Moreover, as tax exemption policies evolve in duopoly markets, the cancellation of the tax exemption policy may intensify competition between traditional and low-carbon firms under certain conditions. Furthermore, given one firm’s pricing strategy, our results show that the other firm could adopt either a uniform pricing strategy or a tiered pricing strategy, which depends on the low-carbon advantage and tax rate.

Purpose: This paper explores how the manufacturer’s strategic choice (acquisition or investment) impacts product quality in a supply chain comprising two complementary suppliers and a common manufacturer.Design/methodology/approach: The manufacturer faces six strategic choices to improve product quality: acquiring or investing in the high-capable supplier, the low-capable supplier, or both. As the Stackelberg leader, the manufacturer determines which strategy is adopted, while suppliers are separately responsible for components’ quality and wholesale prices. The authors use game theory and calculate the model with Mathematica.Findings: The authors develop analytical models to analyze how acquisition costs, investment proportions, component importance and quality improvement coefficients influence decision-makers. The results show that the highest quality may not benefit the manufacturer. Investing in or acquiring a low-capable supplier is better than a high-capable supplier under certain conditions. If the gaps between two suppliers’ quality improvement coefficients and the importance of two components are dramatic, the manufacturer should choose an investment strategy.Originality/value: This study contributes to the complementary supply chain management by comparing two kinds of strategies-acquisition and investment, with a high-capable supplier and a low-capable supplier.