Research
My work spans three interconnected areas: sustainable and circular supply chains, business model innovation in complex and resource-constrained settings, and the use of AI and analytics to transform operations.
I combine mathematical modeling with field-based research, working directly with companies and social enterprises to develop solutions grounded in practice.
Current projects explore how organizations source, deploy, and orchestrate AI in their operations, and innovative business models for commercializing deep tech innovations.
Publications
The Value of Time-and Location-Commitment for Decentralized Emergency Medical Services
P. van den Berg, A. Calmon, A. Gernert, S. Lemmens, M. Rabinovich, and G. Romero
Emergency medical services (EMS) in many low- and middle-income countries utilize decentralized platforms coordinating independent ambulance providers. However, significant operational challenges arise from uncertainty in provider time availability and unpredictable idle locations. These uncertainties hinder reliable service coverage and negatively impact patient outcomes. Using data from our partner Flare in East Africa regarding their operations in Nairobi, Kenya, we investigate the relative effectiveness of enhancing provider temporal commitment (time availability) versus spatial commitment (strategic location) to improve system coverage. We employ optimization models tailored to ambulance commitment uncertainty, a detailed case study, data-driven simulations, and a game-theoretic model. Our findings quantify a stark “cost of decentralization”: the coverage provided by Flare’s 340 loosely committed ambulances could potentially be matched by fewer than 15 optimally deployed fully committed units. We find that enhancing spatial commitment typically yields substantially larger coverage gains than increasing time availability alone, and that both dimensions are strongly complementary.
Traceability Technology Adoption in Supply Chain Networks
P. Blaettchen, A. P. Calmon, and G. Hall
Modern traceability technologies promise to improve supply chain management by simplifying recalls, increasing visibility, and verifying sustainable supplier practices. Initiatives leading the implementation of traceability technologies must choose the least-costly set of firms—or seed set—to target for early adoption. Choosing this seed set is challenging because firms are part of supply chains interlinked in complex networks, yielding an inherent supply chain effect: benefits obtained from traceability are conditional on technology adoption by a subset of firms in a product’s supply chain. We prove that the problem of selecting the least-costly seed set in a supply chain network is hard to solve and even approximate within a polylogarithmic factor. Nevertheless, we provide a novel linear programming-based algorithm to identify the least-costly seed set. The algorithm is fixed-parameter tractable in the supply chain network’s treewidth, which we show to be low in real-world supply chain networks. The algorithm also enables us to derive easily computable bounds on the cost of selecting an optimal seed set. We leverage our toolbox to conduct large-scale numerical experiments that provide insights into how the supply chain network structure influences diffusion.
Business Model Innovation for Ambulance Systems in Low- and Middle-Income Countries: “Coordination and Competition”
A. Gernert, A. P. Calmon, G. Romero, and L. Van Wassenhove
Production and Operations Management, 2024, pp. 1–17 (New Business Models Special Issue)
· DOI · SSRN · Abstract ▾
Several low- and middle-income countries’ emergency transportation systems (ETSs) do not have a centralized emergency number. Instead, they have many independent ambulance providers, each with a small number of ambulances. As a result, ETSs in these contexts lack coordination and ambulances. Using a free-entry equilibrium model, we show that in such decentralized systems, the probability that any given call can be served by at least one ambulance, that is, its coverage, is at most 71.54%, regardless of the ETS’s profitability. We examine three business models that can address the ETS’s lack of coordination and ambulances: (i) a competitor-only business model, where an entrepreneur enters the ETS and acquires ambulances to compete with existing providers; (ii) a platform business model, where an entrepreneur coordinates existing providers; and (iii) an innovative platform-plus business model, where an entrepreneur combines (i) and (ii): setting-up a platform and acquiring platform-owned ambulances. We also examine a government-run platform that takes no commissions from providers. Using a game-theoretic approach, we find that it is optimal for all platform models to incentivize all providers to join. However, only the government-run platform may incentivize providers to acquire additional ambulances.
Operational Strategies for Distributing Durable Goods in the Base of the Pyramid
A. P. Calmon, D. Jue-Rajasingh, G. Romero, and J. Stenson
Novel life-improving products, such as solar lanterns and energy-efficient cookstoves address essential needs of consumers in the base of the pyramid (BoP). However, their profitable distribution is often difficult because BoP customers are risk-averse, their ability to pay (ATP) is lower than their willingness to pay, and they face uncertainty regarding these products’ value. We examine two practical strategies from distributors in the BoP: (1) improving the product’s affordability through a discount and (2) increasing awareness of the product’s value. We introduce a supply chain model for the BoP and analyze the distributor’s pricing problem with refunds as well as the distributor’s optimal budget allocation between strategies (1) and (2). We find that, in the BoP, the distributor’s profit-maximizing budget allocation often yields the lowest consumer surplus. This misalignment between profits and consumer surplus disappears if customers’ ATP is high. Moreover, the misalignment can be resolved if the distributor offers free product returns and commits to a maximum retail price.
Warranty Matching in a Consumer Electronics Closed-Loop Supply Chain
A. P. Calmon, S. C. Graves, and S. Lemmens
We examine a dynamic assignment problem faced by a large wireless service provider (WSP) that is a Fortune 100 company. This company manages two warranties: (i) a customer warranty that the WSP offers its customers and (ii) an original equipment manufacturer (OEM) warranty that OEMs offer the WSP. The WSP uses devices refurbished by the OEM as replacement devices, and hence their warranty operation is a closed-loop supply chain. Depending on the assignment the WSP uses, the customer and OEM warranties might become misaligned for customer-device pairs, potentially incurring a cost for the WSP. We identify, model, and analyze a new dynamic assignment problem that emerges in this setting called the warranty matching problem. We introduce a new class of policies, called farsighted policies, which can perform better than myopic policies. We also propose a new heuristic assignment policy, the sampling policy, which leads to a near-optimal assignment. We show that our assignment policies reduce the average uncovered time and the expected number of out-of-OEM-warranty returns by more than 75% in comparison with our industrial partner’s current assignment policy.
Revenue Management with Repeated Customer Interactions
A. P. Calmon, D. F. Ciocan, and G. Romero
Motivated by online advertising, we model and analyze a revenue management problem where a platform interacts with a set of customers over a number of periods. Unlike traditional network revenue management, which treats the interaction between platform and customers as one-shot, we consider stateful customers who can dynamically change their goodwill toward the platform depending on the quality of their past interactions. Customer goodwill further determines the amount of budget that they allocate to the platform in the future. These dynamics create a trade-off between the platform myopically maximizing short-term revenues, versus maximizing the long-term goodwill of its customers to collect higher future revenues. We identify a set of natural conditions under which myopic policies that ignore the budget dynamics are either optimal or admit parametric guarantees. We also show that, if these conditions do not hold, myopic and finite look-ahead policies can perform arbitrarily poorly in this repeated setting.
Inventory Management in a Consumer Electronics Closed-Loop Supply Chain
A. P. Calmon and S. C. Graves
The goal of this paper is to describe, model, and optimize inventory in a reverse logistics system that supports the warranty returns and replacements for a consumer electronic device. The reverse-logistics system is a closed-loop supply chain: failed devices are returned for repair and refurbishing; this inventory is then used to serve warranty claims or sold through a side-sales channel. Managing inventory in this system is challenging due to the short life-cycle of these devices and the rapidly declining value for the inventory. We examine an inventory model that captures these dynamics, characterize the structure of the optimal policy for stochastic demand, and introduce an algorithm to calculate optimal sell-down levels. We also provide a closed-form policy for the deterministic version of the problem and use this policy as a certainty-equivalent approximation to the stochastic optimal policy.
Submitted Papers and Working Papers
From Trees to Treewidth: Inventory Management in Complex Supply Chain Networks
P. Blaettchen, A. P. Calmon, G. Hall, and M. Tawarmalani
We propose an exact solution approach to the Guaranteed Service Model (GSM), one of the most widely applied models for optimizing safety stock placement in supply chain networks. Based on linear programming (LP), our approach handles any directed acyclic network and any cost function that depends on a stage’s incoming and outgoing service times. It scales polynomially in the number of nodes n in the network, and exponentially in its treewidth, which quantifies how “tree-like” a network is, and can be much smaller than n. This contrasts with existing approaches, which scale exponentially in n. The proof of exactness relies crucially on showing that the join of transportation-like polytopes remains integral, and it is more broadly applicable to other Operations Management problems. The use of linear programming makes for straightforward implementation, including when incorporating additional operational constraints. It also enables sensitivity analyses and the construction of principled bounds on the GSM’s optimal value. Finally, it allows for the use of standard LP optimization software, resulting in considerable gains in solving time.
A Random Model of Supply Chain Networks
P. Blaettchen, A. P. Calmon, and G. Hall
Supply chain problems are frequently formulated as optimization problems over graphs representing complex networks of interlinked input-output relationships. Frequently, these problems are hard, so researchers rely on analyzing stylized structures or developing heuristic solutions. Yet, a scarcity of real-world data has hindered our understanding of how these exact and heuristic solutions perform in practice and whether managerial insights carry over from these simplified settings. We address this critical gap by introducing RG4SC, a versatile random graph model for creating “test tracks” for supply chain management research. RG4SC’s simple micro-foundations and interpretable input parameters allow for systematically generating diverse and realistic network structures. We demonstrate its empirical validity and that it more adequately represents real-world supply chain networks than existing random models. We then showcase RG4SC’s utility for research through a case study on the Guaranteed Service Model, a widely used framework for safety stock optimization.
Data-Driven Failure Time Estimation in a Consumer Electronics Closed-Loop Supply Chain
A. P. Calmon, S. C. Graves, and S. Lemmens
Major Revision,
Production and Operations Management · SSRN · Abstract ▾
We examine and analyze a strategy for forecasting the demand for replacement devices in a large Wireless Service Provider (WSP) that is a Fortune 100 company. The Original Equipment Manufacturer (OEM) refurbishes returned devices that are offered as replacement devices by the WSP to its customers, and hence the device refurbishment and replacement operations are a closed-loop supply chain. We introduce a strategy for estimating failure time distributions of newly launched devices that leverages the historical data of failures from other devices. The fundamental assumption that we make is that the hazard rate distribution of the new devices can be modeled as a mixture of historical hazard rate distributions of prior devices. The proposed strategy uses the empirical hazard rates from other devices to form a basis set of hazard rate distributions. We then use a regression to identify and fit the relevant hazard rates distributions from the basis to the observed failures of the new device.
Specialize or Balance? Salesforce Allocation Across Differentially Vulnerable Retailers at the Base of the Pyramid
O. Fatunde-Iloeje, A. Calmon, J. de Zegher, and G. Romero
Second Place, 2021 POMS College of Sustainable Operations Best Student Paper Competition
Distributors reach Base of the Pyramid (BoP) consumers through sales agents who build personal relationships with retailers. Agent turnover disrupts these relationships, and informal retailers, who depend heavily on personal ties, are particularly vulnerable. How should a distributor allocate its salesforce across formal and informal retailers when vulnerability to disruptions differs between them? The salesforce management literature recommends specialization, but we show that specialization concentrates vulnerable retailers with agents who earn lower commissions and face elevated turnover risk. We develop an analytical model showing that specialization is optimal when both retailer types face proportional revenue losses after a disruption. When informal retailers are disproportionately vulnerable, however, the optimal allocation shifts toward balance, with each agent serving a mix of formal and informal retailers. Using data from Essmart, a durable goods distributor serving over 2,000 retailers in southern India (2016–2024), we estimate that informal retailers experience incremental revenue loss on the order of one-third of their pre-treatment Essmart-derived revenue, confirming that differential vulnerability is the empirically relevant case.
Data Analytics for Creative Processes: Designing the Next Delicious Product
A. P. Calmon, F. P. Calmon, R. Goodwin, and J. Zazo
Over the past decades, firms that develop new flavor and fragrance products (a $30 billion per year market) have amassed large amounts of data from their own internal creation processes. Yet, new product creation still mostly relies on human expertise and arduous experimentation. We present a data analytics framework to aid in the flavor and fragrance creation process. The framework consists of two steps. In the first step, we use data to fit a metric over products, a procedure we refer to as curation. The metric of choice is the Earth Mover’s Distance (EMD), where distances between products are quantified in terms of the pairwise similarity between ingredients. The curation process is formulated as a metric learning problem, where the cost matrix used in EMD computations is directly fit from labeled data. In the second step, we develop analytical tools to aid in the design of new products by sampling and evaluating new products within an EMD neighborhood of a seed product, a procedure we refer to as creation.
Optimal Agricultural Supply Planning Under Climate Change: The Impact of Extreme Weather Events
U. Serhatli, A. P. Calmon, and E. Yucesan
We analyze the impact of climate change on supply chains that manufacture commercial seeds used as input for the production of staple field crops such as wheat or corn. In particular, we examine how extreme weather events triggered by climate change affect the optimal contracting, production, and allocation decisions of seed manufacturers, the expected revenue of farmers who carry out the multiplication process, and the security of the food supply. Within a game-theoretic framework, we model the seed production process as a discrete-time stochastic dynamic optimization problem where the seed manufacturer solves an optimization problem with two stages: the planting stage, where the manufacturer chooses the number of contract farmers, and the allocation stage, where the manufacturer allocates the resulting production from the planting stage to different commercial markets with varying profit margins. We then examine the impact of climate change on the expected profits of the manufacturer and the farmers along with the efficacy of policy interventions in mitigating the deteriorating effects of climate change.
Pricing and Job Allocation in Online Labor Platforms
V. F. Araman, A. Calmon, and K. Fridgeirsdottir
We model, analyze, and optimize the operations of an online labor platform that matches jobs to workers. The arrival of jobs and workers to the platform is stochastic and the job processing time is random. The platform chooses the fees per job and assigns jobs to workers with the goal of (i) maximizing platform revenues, (ii) minimizing the unpredictability in workers’ profits, and (iii) minimizing any delay in processing the incoming jobs. Workers are sensitive to the revenue they make in the platform and, therefore, the worker arrival rate depends on the platform’s pricing and job allocation strategy. We introduce a policy class called Uniform Allocation (UA) and provide an analytical characterization of the platform’s behavior and performance under this policy class. Then, we design a UA policy that simultaneously optimizes objectives (i), (ii), and (iii) as the system scales.
Practitioner Publications and Book Chapters
When Supply Chains Become Autonomous
C. Long, D. Simchi-Levi, A. P. Calmon, and F. P. Calmon
Harvard Business Review, December 2025
· Article
Making Tech Work: Towards Supply Chain Traceability
P. Blaettchen, A. P. Calmon, and G. Hall
Customer Satisfaction and Profits at the Base of the Pyramid
A. P. Calmon, D. Jue-Rajasingh, G. Romero, and J. Stenson
Financial Access or Price Premiums? A Nuanced View into Improving Farmer Welfare and Reducing Child Labor in Commodity Supply Chains
A. P. Calmon, A. K. Gernert, D. A. Iancu, and L. N. Van Wassenhove
Responsible and Sustainable Operations, Springer, 2024
· DOI
Business Model Innovation for Ambulance Systems in Low- and Middle-Income Countries
A. Gernert, A. P. Calmon, G. Romero, and L. Van Wassenhove
Responsible and Sustainable Operations, Springer, 2024
· DOI
