We consider an on-demand service platform using earning sensitive independent providers with heterogeneous reservation price (for work participation) to serve its time and price sensitive customers with heterogeneous valuation of the service. As such, both the supply and demand are "endogenously" dependent on the price the platform charges its customers and the wage the platform pays its independent providers. We present an analytical model with endogenous supply (number of participating agents) and endogenous demand (customer request rate) to study this on-demand service platform. To coordinate endogenous demand with endogenous supply, we include the steady-state waiting time performance based on a queueing model in the customer utility function to characterize the optimal price and wage rates that maximize the profit of the platform. We first analyze a base model that uses a fixed payout ratio (i.e., the ratio of wage over price), and then extend our model to allow the platform to adopt a time-based payout ratio. We find that it is optimal for the platform to charge a higher price when demand increases; however, the optimal price is not necessarily monotonic when the provider capacity or the waiting cost increases. Furthermore, the platform should offer a higher payout ratio as demand increases, capacity decreases or customers become more sensitive to waiting time.We also find that the platform should lower its payout ratio as it grows with the number of providers and customer demand increasing at about the same rate. We use a set of actual data from a large on-demand ride-hailing platform to calibrate our model parameters in numerical experiments to illustrate some of our main insights.

• The cost of incorporating bevacizumab for treatment of cervical cancer is driven by drug costs not management of bevacizumab-induced complications.• The availability of less expensive biosimilars is predicted to result in dramatic reductions in the incremental cost-effectiveness ratio. Objective. To evaluate the cost-effectiveness of bevacizumab in recurrent/persistent and metastatic cervical cancer using recently reported updated survival and toxicology data. a b s t r a c t a r t i c l e i n f oMethods. A Markov decision tree based on the Gynecologic Oncology Group 240 randomized trial was created. The 2013 MediCare Services Drug Payment Table and Physician Fee Schedule provided costs. In the 5-year model subjects transitioned through the following states: response, progression, minor complications, severe complications, and death. Patients experiencing a health utility per month according to treatment effectiveness were calculated. Because cervical cancer survival is measured in months rather than years, results were reported in both quality adjusted cervical cancer life months and years (QALmonth, QALY), adjusted from a baseline of having advanced cervical cancer during a month.Results. The estimated total cost of therapy with bevacizumab is approximately 13.2 times that for chemotherapy alone, adding $73,791 per 3.5 months (0.29 year) of life gained, resulting in an incremental cost-effectiveness ratio (ICER) of $21.083 per month of added life. The ICER increased to $5775 per month of added life and $24,597/QALmonth ($295,164/QALY) due to the smaller difference in QALmonths. With 75% bevacizumab cost reduction, the ICER is $6737/QALmonth ($80,844/QALY), which translates to $23,580 for the 3.5 month (0.29 year) gain in OS.Conclusions. Increased costs are primarily related to the cost of drug and not the management of bevacizumab-induced complications. Cost reductions in bevacizumab result in dramatic declines in the ICER, suggesting that cost reconciliation in advanced cervical cancer may be possible through the availability of biosimilars, and/or less expensive, equally efficacious anti-angiogenesis agents.

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Applications of government subsidies to speed up consumer trade‐ins of used products can be commonly observed in practice. This study investigates the design of such trade‐in subsidy programs and aims to provide implementable insights for practice. In particular, we focus on two open problems in the literature, (i) how to optimally allocate the subsidy budget among the multiple products covered by the trade‐in program, and (ii) how to most effectively utilize the assigned budget to incentivize consumer trade‐ins for each product. We develop a three‐stage Stackelberg game model that captures the essence of the interaction between the government's subsidy decision, the manufacturer's trade‐in rebate decision, and the consumer's product replacement decision. We show that a sharing subsidy scheme under which the government subsidy is proportional to the manufacturer's rebate is more effective in encouraging consumer trade‐ins than fixed‐amount subsidies. Moreover, a product with a higher environmental impact, a larger market size, a longer lifespan, or a lower value to consumers typically demands a larger subsidy budget allocation. We further use our results to derive a simple proportional budget allocation rule that can provide robust and near‐optimal performance. We illustrate our results by a case study based on the “old‐for‐new" program in China that subsidizes home appliance trade‐ins. Our results indicate that policy makers should pay attention to the correlation between government subsidies and manufacturer's rebate as well as key product and market characteristics when designing a subsidy scheme for trade‐in programs.

5516 Background: Unlike approved IV administered therapies, Medicare is under no obligation to cover prescription medicines. We sought to evaluate the cost-effectiveness of the two FDA-approved orally administered PARP inhibitors (PARPi), olaparib and rucaparib. Methods: A Markov model was created in TreeAge Pro 2015 with nodes in the chain allowing patients to transition through response, hematological complications, non-hematological complications, progression, and death. Separately, the PARP inhibitors were compared with IV administered drugs approved for recurrent ovarian cancers including platinum-based, non-platinum, and bevacizumab-based regimens. Toxicity and mean PFS rates for the different agents were obtained from registration trial data. Costs of IV chemotherapy, managing toxicities, infusions, and supportive care were estimated using 2015 Medicare data. Incremental cost-effectiveness ratios (ICER) were calculated and survival was reported in quality adjusted life months. Results: Platinum-based combinations were the most cost-effective at $1,672/PFS mo as compared to non-platinum agents ($6,688/mo), bevacizumab-containing regimens ($12,482/mo), olaparib ($13,3731/mo), and rucaparib ($14,034/mo). Considering a cost of $114,478 for olaparib and $137,068 for rucaparib prior to progression, costs associated with PARPi were 7.1 to 8.3X more than platinum combinations. To better compare the registration trial data to PARPi data, probability was adjusted to 2nd line for rucaparib, revealing it’s ICERs’ of per month of life added to be $26,997 for bevacizumab, $17,757 for non-platinum, and $79,585 for platinums. Using the adjusted-to-2nd-line probabilities for olaparib, exhibited ICERs were $16,549 for bevacizumab, $25,637 for non-platinums and $72,083 for platinums. Conclusions: The high costs of PARPi were not balanced by costs of infusion and managing toxicities of IV drugs typically associated with lower response rates and shorter PFS in the recurrent space. Balancing incremental clinical benefit with novel therapies remains problematic and could widen disparities among those with limited access to care.