In the healthcare industry, quickly recalling defecting products can be instrumental in avoiding potentially harm to patients. Building on upper echelons theory and personality theory, we argue that neurotic CEOs are more vigilant when they face uncertainty, as they do when making recall decisions, leading to faster recalls. We build on a novel, machine-learning based approach to measure the personalities of 110 CEOs of U.S. healthcare firms and find broad support for our theory in analyses.

We measure the digital impact of the Indian COVID-19 lockdown using a survey coupled with browser history data (n=1,094). Gender differences are present for online leisure, production, YouTube, social media and job search – and not for online learning. Working women sacrificed online leisure while maintaining online production. The gender gap is larger among parents. Fathers self-reported significantly larger childcare time increases, yet browser data and partner reports do not support this.

We analyze prices paid in low-income and high-income areas after three hurricanes. Using a triple difference regression, we isolate the percentage change in prices paid by low-income versus high-income areas in affected versus unaffected areas. Compared to high-income areas, low-income areas experience a larger drop in promotions, higher unit percent price increases, a larger decrease in offer sets of low-priced items, and a larger increase in substitution from low-priced to high-priced items.

We study the impact of monitor leniency on supplier CSR risk. Using audit data from a global apparel brand, we find that leniency helps to reduce CSR risk. Testing interaction effects with our moderators, we find that greater leniency helps to reduce CSR risk when a facility’s compliance ability is low; when a facility has been audited a small number of times; and when a facility is located in a developing country. Our work provides insight into the relational factors that can influence supplier audits.

Manufacturers are increasingly being held responsible for sustainability violations across their whole supply chain. We examine a three-tier supply chain where a manufacturer and its direct supplier incentivize sub-supplier sustainability through auditing and supplier development. We show that the mechanisms are substitutive for the supplier but can be complementary for the manufacturer. Moreover, the manufacturer delegates the effort in case of very low or very high external pressure.

We propose a conceptual framework for supplier sustainability improvement that we refer to as CARE, based on self-assessments and consisting of Collect, Assess, React, and Enhance phases. CARE is highly scalable, making use of machine learning techniques to understand the link between the general supplier characteristics and their verified sustainability profile, predict the future sustainability levels of even unassessed suppliers, and determine the best plan for improvement.

A critical decision made by many firms is whether to adopt a responsive supply chain (prioritizing speed) or an efficient supply chain (prioritizing cost). We consider the environmental implications of this choice, and find that firms will have the greatest incentive to invest in responsiveness when it is most detrimental to the environment. We discuss the implications of this for policymakers seeking to encourage firms to use supply chains that generate the least environmental impact.

We investigate a Remanufacturing Original Equipment Manufacturer (ROEM) who can choose

to remanufacture recovered cores either to their original configuration or to current technology. The decay of consumers’ valuations of the products as time passes influences the optimality managerial decisions. Hence, we examine the traditional method of studying this effect and develop a more realistic model that offers new insights into the optimal remanufacturing choices.

This paper extends our research on “bespoke” resilience strategies, by formulating a supply chain model that enhances reported models by adding sustainability. The proposed model examines tradeoffs, constraints, and risks for the extended problem and considers implications for supply chain strategy development. One key question was whether the two concepts are mutually reinforcing or conflicting. Our analysis shows how the answer depends on the features of the supply chain environment.

Informal recycling of used lead acid batteries causes tremendous environmental damage, especially to children’s physical and mental developments in Bangladesh. The problem is further exacerbated as lead extracted from the process is used to produce low-quality batteries that require frequent replacements. We study public policy interventions that give incentives to extend battery lives and promote formal recycling under strong environment production, to reduce the circulation of informally-recycled lead.

We are designing a novel business model to extend the life of lead acid batteries used in electric three wheelers in Bangladesh. Through a randomized control trial, we are testing the impact of the business model on battery life and performance, recycling rate and lead emissions, energy consumption and CO2 emissions, and income and profit of battery users. The business model can be generalized to other durable goods and geographies where products fail fast because of market inefficiencies.

The initial landing location of a refugee has implications on their long-term success. We propose two new dynamic algorithms to match refugees to localities within a host country. The performance of the proposed methods is illustrated on real US refugee resettlement data. The first algorithm maximizes the average employment level, and is currently deployed in a pilot in Switzerland. The second algorithm balances employment with the desire for an even allocation to the localities over time.

Our study is the first to empirically study the impact of the minimum wage on firms’ scheduling practices. Using a highly granular dataset from a chain of fashion retail stores, we estimate that a $1 increase in the minimum wage, while having a negligible impact on the total labor hours used by the stores, leads to a 27.7% increase in the number of workers scheduled per week, but a 19.4% reduction in weekly hours per worker, and less consistent schedules, which substantially hurt worker welfare.

Under current legislation, multinational companies are at risk of having imports into the U.S. blocked due to alleged use of forced labor in their supply chains. Using a game theoretic model, we study the equilibrium interactions between firms, who may exert costly 'responsibility effort,' and enforcement organizations that allocate scarce resources to investigate multiple firms. We characterize policies that incentivize greater supply chain responsibility based on firm and industry parameters.

How shall gig workers be classified? Compared to the benchmark of contractors, we show that uniform classifications (employees, contractors+) suffer issues of worker’s being undercut and overjoining and will not always make vulnerable workers better off. To classify workers according to their needs, or operationally prioritizing vulnerable workers can Pareto improve over uniform classifications. Our work highlights the importance of worker-specific regulations in the on-demand economy.

Smallholder farmers find themselves at the crossroads of the global efforts to reduce worldwide poverty and hunger, as well as the urgent need to prevent deforestation and the associated environmental consequences. In this work, we study how the smallholder farmers' welfare can be improved while preventing deforestation. For this, we propose a detailed operational model of a farmer’s dynamic decisions of land-clearing and production, under liquidity constraints and random cost and yield shocks.

Many multinational buyers of agricultural commodities have made commitments to halt deforestation and improve farmer livelihoods in their supply chains. We propose group incentives conditional on forest protection requirements as a feasible mechanism for achieving this. We develop an analytical model and characterize the cases when group incentives dominate individual incentives, and use data collected from field research in Indonesia to assess the effectiveness of the approach.

Right-to-Repair regulations require producers to supply necessary information and parts for consumers to independently undertake repairs. These regulations aim to prolong product lifetimes through repairs, but they may have adverse consequences such as cloning. This may encourage producers to reconsider their business model choices between ownership and non-ownership models. We analyze the effect of RTR on business model choice, and the implications for producers, consumers, and the environment.