Research Papers
Research Papers
Symbolic Rewards with Dynamic Scorecard: A Non-Monetary Mechanism to Improve Volunteer Engagement (with S. Lim). 2026
Abstract: Volunteers are central to nonprofit operations, yet their participation is often intermittent. Many nonprofits organize short campaigns to focus volunteer effort, but sustaining that effort throughout a campaign remains challenging. When monetary incentives are infeasible or risk undermining prosocial motivation, symbolic recognition offers an alternative. However, how should recognition reflect contributions over time to sustain volunteer effort? We address this design question through a Symbolic Rewards with Dynamic Scorecard (SRDS) mechanism that assigns recognition tiers based on individual and group contributions while discounting older contributions.
The nonprofit platform jointly determines the tier thresholds, the relative weights of individual and group contributions, and the score-depreciation rate. We model platform–volunteer interaction as a finite-horizon stochastic Stackelberg differential game incorporating post-campaign warm glow from final standing. Under a deterministic Gaussian mean-path approximation, we characterize candidate symmetric equilibrium paths that satisfy the Pontryagin conditions. With floored linear terminal recognition, we establish the existence of best responses and characterize effort patterns. Holding other factors constant, a low marginal value of final standing can yield unimodal effort, whereas a sufficiently high value can induce rising effort near the deadline. We derive a closed-form upper bound on adjacent tier spacing that maintains the marginal status-payoff gradient above a prescribed benchmark between thresholds.
We calibrate the model using one year of operational data from a regional U.S. food-rescue platform. Across two- to eight-week campaigns, optimized SRDS generates 25\%–64\% more effort than the observed status-quo baseline. Relative to symbolic rewards with no score decay and re-optimized thresholds, SRDS generates 7.8\%–15.4\% more effort across seven campaign durations.
Optimal Pricing Design for Capacity-Constrained Electric Freight Charging Stations (with R. Aksu and M. Yavuz). 2026. [pdf]
Abstract: Electrifying long-haul trucking requires megawatt-class charging stations whose grid connections limit the number of high-power charging slots they can offer, so operators must ration access among freight carriers whose delay sensitivities are privately known. We study a monopolistic charging station operator serving a unit mass of carriers along a multi-stop freight corridor: each carrier either reserves a charging slot in advance or arrives as a walk-in and faces a stochastic waiting time. Building on the mechanism-design framework, we characterize the profit-maximizing mechanism in closed form and show that it has a threshold structure that varies with corridor length: on moderately long-haul corridors, carriers sort into three service tiers – full-corridor reservations, final-leg-only reservations, and walk-in access. On extended long-haul corridors, the walk-in tier drops out and the structure collapses to two service tiers, with every carrier securing a guaranteed final-leg reservation. The optimal mechanism admits two implementations familiar in practice: (i) a posted-price menu of contracts and (ii) a uniform energy price paired with reservation surcharges. To illustrate the value of the optimal mechanism, we calibrate the model using United States trucking-industry data and observe that the optimal mechanism raises operator profit by about 18% on average relative to a uniform pricing and rationing benchmark, with the largest gains on long, capacity-constrained corridors. We further show that our core findings are robust across two settings: the tiered structure persists when a social planner maximizes welfare subject to the operator’s break-even constraint, and when carriers book in advance – before a trip’s urgency is known – yet retain the right to walk in en route, advance booking commitments confer no additional screening power and the static menu remains optimal. Our analysis rationalizes the hybrid anchor-plus-public corridor designs that Terawatt and Milence are deploying on major freight routes in the United States and Europe.
Structural Estimation of B2B Demand in Local Food Distribution: Demand Insights and Incentive Design to Improve Farmer Sourcing (with S. Lim and M. Mahmoudi ). 2025.
Abstract: Local food distributors function as essential intermediaries between small and medium farms and institutional and retail buyers such as schools, restaurants, and grocery chains. Yet these distributors face high failure risk due to inconsistent farm supply and rising operating costs, threatening the viability of local food systems. We study this operational challenge in collaboration with Tamarack Holdings (TH), a Michigan-based agri-food distributor. Using detailed transaction data and a Multiple Discrete-Continuous Extreme Value (MDCEV) demand model specification, we analyze business purchasing behavior along two dimensions of customer orders: the number of SKUs selected from the distributor’s assortment and the quantity purchased per SKU.
The demand estimates yield two key insights. First, instead of observing the traditional frequency–quantity trade-off often documented in business-to-consumer settings, business-to-business (B2B) buyers exhibit low satiation for staple products, purchasing frequent items in large volumes. Second, purchasing behavior is highly heterogeneous across buyer segments, limiting a one-size-fits-all sourcing policy.
We embed the estimated demand structure into a principal–agent contract design framework to address inconsistent supply by incentivizing farmers’ capacity expansion. We demonstrate the utility of this structural integration: contracts designed under standard Multinomial Logit (MNL) and Fractional MNL benchmarks generate average profit losses of 86.42% and 75.44%, respectively, relative to the MDCEV-based design. These losses primarily arise from the benchmarks’ inability to account for the volume-driven nature of B2B orders. Lastly, relative to the status quo of no incentives, the optimal contract increases average distributor profit by 25.65%, improves fill rates by 8.12%, and reduces stockout probability by 11.88%.
Non-Profit Support in Education: Resource Allocation and Students’ Lifetime Outcomes with Harish Guda, Milind Dawande, and Ganesh Janakiraman, Major Revision at Manufacturing and Service Operations Management. 2024. [SSRN]
Problem Definition: One of the seventeen United Nations Sustainable Development Goals aims for inclusive and equitable quality education, with lifelong benefits, for all. Our work in this paper focuses on the operations of non-profit organizations (NPOs) that broaden access to high-quality education for underprivileged students. Specifically, we analyze the resource-allocation strategy of an NPO that adopts a two-stage structure in allocating resources to its beneficiaries, e.g., free pre-secondary education (first stage) for all underprivileged students in a target population, followed by sponsorships for post-secondary education (second stage) at leading institutions to those students who demonstrate commendable performance in the first stage. The lifetime outcomes of the beneficiaries depend on their own effort and the quality of the resources that the NPO provides.
Methodology/Results: We adopt a principal multi-agent framework with moral hazard and heterogenous agents in the absence of monetary transfers. We establish the strategic role of an NPO's resource-allocation strategy on the effort beneficiaries invest and their lifetime outcomes. In particular, despite the supportive nature of the resources to both the beneficiaries and the NPO, we show why scarcity of these resources benefits the NPO.
Managerial Implications: Our findings have important implications for the design of such support policies of NPOs. We demonstrate the conditions under which the NPO must withhold resources from the beneficiaries to improve their lifetime outcomes. We also demonstrate the role of exogenous admission criteria on the NPO's resource allocation strategy. Finally, when faced with multiple beneficiary subgroups, we identify how the NPO should earmark resources for each beneficiary subgroup. We compare the optimal allocation strategy vis-a-vis a fair allocation strategy to quantify the price of fairness of the optimal solution.
Optimal Cardinal Contests, with Milind Dawande and Ganesh Janakiraman, Production and Operations Management. Forthcoming. [PDF] .
Abstract: We study the design of crowdsourcing contests in settings where the outputs of the contestants are quantifiable - e.g., a data-science challenge. This setting is in contrast to those where the output is only qualitative and cannot be objectively quantified - e.g. when the contest's goal is to design a logo. The literature on crowdsourcing contests focuses largely on ordinal contests, where the designer ranks the contestants' outputs, and awards are based on relative ranks. Such contests are ideally suited for the latter setting, where output is qualitative. For our setting (quantitative output), it is possible to design cardinal contests, where awards could be based on the actual outputs and not on their ranking alone - thus, the family of cardinal contests includes the family of ordinal contests. We study the problem of designing an optimal cardinal contest. We use mechanism design theory to derive an optimal cardinal mechanism and provide a convenient implementation - a decreasing reward-meter mechanism - of the optimal contest. We establish the practicality of our mechanism by showing that it is "Obviously Strategy-Proof", a recently introduced formal notion of simplicity in the literature. We also numerically examine the benefit of the optimal cardinal contest over the most popular ordinal contest - namely, the Winner-Takes-All (WTA) contest. Our numerical analysis suggests that, for the contest designer, the average improvement provided by the optimal cardinal mechanism over the WTA contest is about 23%. For a given number of contestants, the benefit of the optimal cardinal mechanism is especially appreciable for projects where the ratio of the designer's utility to agents' cost-of-effort falls within a wide practical range. For projects where this ratio is very high, the expected profit of the best WTA mechanism is reasonably close to that of the optimal cardinal mechanism.
Abstract: Most research examining the response of supply chains to environmental regulations assumes that all parties are subject to the same regulations. However, it is uncommon for buyers and vendors to be located in the same place and subject to the same environmental regulations. This paper investigates the inventory and production decisions of a buyer and a vendor in a supply chain with multiple buyers and a single vendor that produces multiple products under various environmental regulations. Our analysis demonstrates that the multiple buyers and multiple products scenario can be simplified to the single buyer and single product case under certain conditions. We find that a cap-and-trade regulation applied to the buyer may increase or decrease the economic order quantity in traditional supply chains, but it consistently reduces the economic order quantity in vendor-managed inventories (VMI). Our results indicate that while the cap-and-trade regulation reduces the carbon emissions of the buyer in both VMI and traditional supply chains, it may increase the carbon emissions of the vendor. Additionally, we discover that carbon cap regulation, although less commonly used than cap-and-trade regulation, may further decrease the carbon emissions of both the buyer and vendor beyond the effects of a green buyer or green vendor. Moreover, we provide recommendations for actions that the buyer or vendor can take to offset the impact of changes in parameters on economic order or production quantities.