To protect soil quality for sustainable development and raise farmers' incomes, agricultural firms are increasingly developing green and efficient raw materials (GRMs) that can improve crop yields and reduce soil damage compared to TRMs. However, farmers have heterogeneity in both the trust in agricultural information and sustainable development attitudes, leading to underestimation of the value of GRMs. This paper explores the optimal subsidy policy of the government to promote GRMs considering the effect of farmer heterogeneity using a government‐firm‐farmer Stackelberg game. Our analysis reveals that the government should subsidize both farmers and the GRM firm when the GRMs' effectiveness is not high enough; otherwise, it is more effective to subsidize farmers but not the GRM firm. Such a government subsidy policy can bring a win–win–win outcome for farmers, the GRM firm, and social welfare under certain conditions. Although higher farmers' trust in agricultural information or sustainable development attitudes can increase their subjective willingness to adopt GRMs, counterintuitively, the total farmer surplus will decrease because in this situation: (1) the government will reduce the subsidy to farmers or (2) the GRM firm will increase the GRM price. In addition, compared with considering two‐dimensional heterogeneity of farmers, considering only one‐dimensional heterogeneity or no heterogeneity of farmers will cause the government subsidy to deviate from the goal of promoting GRMs, resulting in a 59.3% reduction in GRM market demand, a 17.3% decrease in the profit of GRM firm, and possibly even making the GRM firm “die out.”

We study an online platform’s demand information sharing strategy in a distribution channel where a manufacturer distributes products through both platform and seller channels.

In the future, vehicle sharing platforms for passenger transport will be unmanned, autonomous, and electric. These platforms must decide which vehicle should pick up which type of customer based on the vehicle’s battery level and customer’s travel distance. We design dynamic vehicle allocation policies for matching appropriate vehicles to customers using a Markov decision process model. To obtain the model parameters, we first model the system as a semi-open queuing network (SOQN) with multiple synchronization stations. At these stations, customers with varied battery demands are matched with semi-shared vehicles that hold sufficient remaining battery levels. If a vehicle’s battery level drops below a threshold, it is routed probabilistically to a nearby charging station for charging. We solve the analytical model of the SOQN and obtain approximate system performance measures, which are validated using simulation. With inputs from the SOQN model, the Markov decision process minimizes both customer waiting cost and lost demand and finds a good heuristic vehicle allocation policy. The experiments show that the heuristic policy is near optimal in small-scale networks and outperforms benchmark policies in large-scale realistic scenarios. An interesting finding is that reserving idle vehicles to wait for future short-distance customer arrivals can be beneficial even when long-distance customers are waiting.

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This paper studies the impact of bundled payment policy on healthcare cost, efficiency, quality, and shift of care. Using insurance claim data, we empirically offer a more nuanced understanding of the impact of bundled payment policy on hospital operations and provide new evidence from China. Our evidence suggests that transitioning from fee-for-service to bundled payment reimbursement resulted in declines in treatment costs and length of stay. Along with that decline, there was an increase in planned revisits to outpatient clinics, which indicates a shift of care from the inpatient to the outpatient setting, as well as a rise in unplanned revisits, indicating a decline in service quality. The increase in readmission rate to inpatient wards is very small and not statistically significant. In addition, we discuss the design and implementation of bundled payment. Our results imply that careful bundle design is vital to encouraging providers to implement the new program without sacrificing quality. Funding: This research is supported by the National Natural Science Foundation of China [Grants 72091215/72091210, 71921001], the Research Grants Council of the Hong Kong Special Administrative Region, China [Grant HKU 17500217], and the Fundamental Research Funds for the Central Universities [Grant 2040000018].