Working Papers

• Do Penalties Promote Responsible Operations? Evidence from the U.S. Mining industry,
  with Anna Sáez de Tejada Cuenca
  
  • Selected for MSOM Sustainable Operations SIG conference (2025)
    
  Abstract

  Financial penalties---fines levied for violations found during site inspections---are widely used to encourage responsible operations (such as compliance with environmental and labor standards or with supplier codes of conduct). However, the effectiveness of penalties in achieving this objective remains unclear. In this paper, we empirically investigate whether higher penalties lead to more responsible operations using a large, granular dataset from the U.S. mining industry. Our identification strategy exploits a policy shock that sharply increased the penalty amounts for health and safety infractions in the mines. We find that higher penalties had, at best, a modest effect on responsible operations. While there was some decrease in violations, we find no evidence of a decrease in accidents or injuries at mines that faced higher fines. We show that this null effect is driven, at least in part, due to an unanticipated and unintended consequence of higher penalties: mining companies strategically contested the higher fines in court, that led to discounted payment amounts, delay in payment times, and higher regulatory costs. By examining the mechanisms through which higher penalties (fail to) promote responsible operations, our work offers insights that can be generalized to contexts beyond mining (e.g., global supply chains).
• Are Chief Sustainability Officers Guardians of Environmental Justice? An Empirical Evaluation,
  with Finn Petersen and Rachna Shah
  
  • Selected for MSOM Sustainable Operations SIG conference (2024)
    
  • Selected for AOM Best Paper Proceedings 2024 (top 10% of submissions)
    
  Abstract

  Environmentally hazardous manufacturing facilities are disproportionately located in underserved communities, which exposes low-income and non-white populations to significantly higher toxic releases and adverse health risks. We study whether a firm governance reform—specifically, the appointment of a Chief Sustainability Officer (CSO)—can mitigate this environmental injustice. Using data on the toxic releases of U.S. manufacturing facilities from 2000 to 2020, we find that appointing a CSO decreases toxic releases by up to 19% and that the effect is particularly pronounced for facilities in underserved communities. We show that this effect is driven, at least in part, by increased implementation of source reduction activities by the treated facilities. Our work sheds new light on how corporate governance reforms act as a control mechanism for addressing environmental injustice, an issue that has proven challenging to regulate effectively.
• The Effect of Expedited Payments on Project Delays: Evidence from QuickPay Reform,
  with Volodymyr Babich, Harish Krishnan, and Jie Ning
  
  Abstract

  Contractors are usually not paid immediately after an invoice is submitted. Payment delays affect the value of projects to contractors, which, in turn, affects their financing costs, decisions about project acceptance and sequencing, and competition among contractors. We examine how payment delays affect project completion times. We develop several theories that link payment delays to project delays and test our theories using the U.S. government's project data, taking advantage of an exogenous shock from the QuickPay reform that expedited payments to certain federal contractors. Surprisingly, our results show that faster payments led to greater project delays. Compared with the pre-QuickPay delay rate per quarter, there is a 26% increase, on average, in the delay rate for projects subject to the QuickPay reform. Both the likelihood of a project delay and the expected delay magnitude conditional on it being positive are significantly higher for the affected projects after QuickPay. We present evidence indicating that project delays can be explained by the contractor's liquidity constraints and competition among contractors. We identify other factors that moderate the effect of QuickPay. For example, the delays are not as severe if a treated project is in the portfolio with projects that do not receive faster payments or if it is at an early stage in its life. We show that the delay is not caused by contractors taking on more projects in response to the reform.

Journal Publications

• Project Networks and Reallocation Externalities,
  with Harish Krishnan and Juan Serpa
  Management Science, 2025
  Preprint: PDF
  • Selected for MSOM Supply Chain SIG conference (2022)
    
  • Selected for 1st ACM conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO'21)
  Abstract

  A project involves several participants—including clients, contractors, and subcontractors—that work concurrently on multiple projects and allocate resources among them. This interdependency creates a network of otherwise unrelated projects. We map the network of U.S. government projects involving over 150,000 participants. We show that a seemingly localized disruption, affecting only one project site, eventually causes delays across unrelated projects. This is because participants opportunistically reallocate resources into disrupted projects, at the expense of other projects, triggering a domino effect of further reallocations in the network. Thus, the costs of on-site disruptions end up being shared by multiple participants in the network, rather than being fully absorbed by the affected project. Performance-based incentives, which reward contractors for timeliness, exacerbate these externalities by encouraging self-interested resource reallocation.
• Managing Reputation Risk in Supply Chains: The Role of Risk-sharing under Limited Liability,
  with Harish Krishnan
  Management Science, 67(8): ‍4845-4862, 2021
  Preprint: PDF
  Abstract

  When a supplier fails to comply with social and environmental standards, the buyer’s reputation suffers. Reputation costs can typically be very high for the buyer whereas the supplier’s liability is often limited. Conventional procurement strategies like dual sourcing mitigate the buyer’s operational risk, but often do so at the expense of increasing its reputation risk and sourcing costs. In this paper, we propose a risk-sharing contract for managing the buyer’s reputation concerns. We find that by sharing some of the supplier’s operational loss, the buyer may (in some conditions) decrease its reputational risk but this has to be balanced against an increase in the operational risk. Risk-sharing also reduces sourcing costs because the buyer takes on some of the worst-case loss of a wealth-constrained supplier. These results suggest that risk-sharing can be superior, as a procurement strategy, to conventional approaches like dual sourcing or penalty contracts. This is true when reputation and sourcing costs are a significant concern, and operational costs are not that high. Under some conditions, the buyer may choose risk-sharing even if it increases reputation risk in order to reduce procurement costs.
• Solving Semi-open Queuing Networks with Time-varying Arrivals: An Application in Container Terminal Landside Operations,
  with Govind Kumawat, Debjit Roy, and René de Koster
  European Journal of Operational Research, 267(3): 855-876, 2018
  Abstract

  Semi-open queuing networks (SOQNs) are widely applied to measure the performance of manufacturing, logistics, communications, restaurant, and health care systems. Many of these systems observe variability in the customer arrival rate. Therefore, solution methods, which are developed for SOQNs with time-homogeneous arrival rate, are insufficient to evaluate the performance of systems which observe time-varying arrivals. This paper presents an efficient solution approach for SOQNs with time-varying arrivals. We use a Markov-modulated Poisson Process to characterize variability in the arrival rate and develop a matrix-geometric method (MGM)-based approach to solve the network. The solution method is validated through extensive numerical experiments. Further, we develop a stochastic model of the landside operations at an automated container terminal with time-varying truck arrivals and evaluate using the MGM-based approach. Results show that commonly used time-homogeneous approximation of time-varying truck arrivals is inaccurate (error is more than 15% in expected waiting time and expected number of trucks waiting outside the terminal) for performance evaluation of the landside operations. The application results are insightful in resource planning, demand leveling, and regulating the number of trucks permitted inside the terminal.
• A Cooperative Quay Crane-based Stochastic Model to Estimate Vessel Handling Time,
  with Debjit Roy and René de Koster
  Flexible Services and Manufacturing Journal, 29: 97-124, 2017
  Abstract

  Having a good estimate of a vessel’s handling time is essential for planning and scheduling container terminal resources, such as berth positions, quay cranes (QCs) and transport vehicles. However, estimating the expected vessel handling time is not straightforward , because it depends on vessel characteristics, resource allocation decisions, and uncertainties in terminal processes. To estimate the expected vessel handling time, we propose a two-level stochastic model. The higher level model consists of a continuous-time Markov chain (CTMC) that captures the effect of QC assignment and scheduling on vessel handling time . The lower level model is a multi-class closed queuing network that models the dynamic interactions among the terminal resources and provides an estimate of the transition rate input parameters to the higher level CTMC model. We estimate the expected vessel handling times for several container load and unload profiles and discuss the effect of terminal layout parameters and crane service time variabilities on vessel handling times. From numerical experiments, we find that by having QCs cooperate, the vessel handling times are reduced by up to 15 %. The vessel handling time is strongly dependent on the variation in the QC service time and on the vehicle travel path topology.
• Modeling Emergency Evacuation with Time and Resource Constraints: A Case Study from Gujarat,
  with Debjit Roy
  Socio-Economic Planning Sciences, 51: 23-33, 2015
  Abstract

  This study develops an off-site emergency response plan for a nuclear power plant in Gujarat, India subject to time constraints with resource limitations and risk of radiation exposure to victims. We formulate an optimization model to capture the effect of delay in evacuation, limited resource availability, and costs associated with resource allocation. A single chain closed queuing network model with class switching is used to model traffic congestion during evacuation. The throughput measures from the queuing network are used as inputs in the optimization model. Further, two resource allocation strategies are suggested and genetic algorithm is used for optimizing resource utilization and evacuation risk. The results indicate that pooling resources among a cluster of affected areas is most suitable for evacuation. Numerical experiments are conducted to analyze the time trade-offs and the effect of service time variability on the expected evacuation time. The proposed model can serve as an important resource planning and allocation tool for emergency evacuation.

Book Chapter

• A Two-level Stochastic Model to Estimate Vessel Throughput Time,
  with Debjit Roy and René de Koster
  Progress in Material Handling Research: 2014, Material Handling Institute, Charlotte, NC.