The sharing economy business model has recently received much attention to determine whether it is economically viable and environmentally friendly. The trade-off is between a decrease in production volume and an increase in product usage. We investigate both economic and environmental impacts of the sharing economy business model for comparison with the traditional models of pure sales and servicizing. Sharing economy can yield a win-win outcome as to profitability and environmental impact.

Our paper investigates the effectiveness of IoT-based nudging on energy savings. The results of our study highlight the value of using IoT technology to influence energy consumption behavior and reduce energy usage.

In team settings, it is critical to mitigate moral hazard, and induce reporting of any shirking. However, agents can free-ride, which exacerbates moral hazard; and deep-rooted loyalty considerations prevent peer reporting. We study peer reporting in a team of one principal and two agents. One of the agents may be loyal: doesn’t shirk and doesn’t report shirking. We show that even a small probability of such a loyal agent unravels reporting.

The flow of humanitarian aid as a response to the Russian Federation’s full-scale invasion of Ukraine was unprecedented. In this paper, we analyze the pressing issues of how to regulate the delivery of humanitarian aid to the final beneficiaries, preventing its loss and misuse due to corrupt behavior in the delivery process.

Girl Scouts' Cookie Program aims to develop girls' skills, but retaining their engagement is crucial. We analyze troop-based factors influencing engagement retention.

Small troop size, balanced sales performance, high adult-to-girl ratio, scout level heterogeneity, and troop-based booth sales positively impact retention.

NPOs can enhance engagement by focusing on team composition, relationship-building, and understanding the factors driving retention in volunteer and fundraising activities.

Managed charging (MH) programs allow utilities to centrally manage electric vehicle (EV) drivers' home charging to reduce cost, avoid new and aggravated peaks and blackouts, and ensure grid stability. In this paper, we present a program design model and a load management model for jointly designing and executing various MH programs.

Do energy price surcharges encourage energy efficiency investments without harming domestic manufacturing?

We analyze a supply chain model and find that energy price surcharges can have varying impacts on domestic sourcing. Supplemental policies like surcharge reduction and EE investment subsidies can help mitigate potential harm.

Policymakers should consider these findings when designing energy policies to promote energy efficiency while minimizing adverse effects on domestic manufacturing.

Efficiently managing inventories requires an accurate estimation of stockout costs. This estimation is complicated by challenges in determining how to compensate consumers monetarily to ensure they will maintain the same level of utility they would have obtained had stockouts not occurred. This paper presents an analysis of these compensation costs, as applied to the design of optimal stockout rates by an online retailer marketing to consumers aesthetically substandard fruits and vegetables.

In this study, we evaluate the effectiveness of AI-based systems in reducing the food waste generated in commercial kitchens. Using a multi-year field experiment in 500+ commercial kitchens, we estimate the waste reductions due to the use of (1) an automated transaction-level scaling system, and (2) an automated weighing and computer vision based waste-classification system. We also explore methods that use the waste data to identify the root causes behind the sub-optimal levels of food waste.

Relay logistics optimize long-haul shipments through a pit-stop network and separate drivers. This model benefits drivers and the environment, while reducing costs and lead times. An efficient algorithm solves the Relay Pickup-and-Delivery Problem, generating multiple arcs for optimal routing. Real-world experiments confirm its superiority over benchmarks, resulting in fewer miles traveled and win-win outcomes for sustainability.

By analyzing economic incentives, we show that reducing the number of stop signs at crossroads (e.g., from four to three) leads to a self-enforcing equilibrium with significant benefits. This simpler mechanism saves fuel gas, reduces time and infrastructure costs, lowers carbon emissions, and decreases police expenses. The new approach generates substantial economic gains compared to the traditional practice of erecting one stop sign in each direction.

Competition and market composition impact corporate adoption of green technologies. Cooperative markets with both green and non-green goods see increased green investment with reduced production costs. In competitive markets without green products, cost reductions facilitate green product introduction. Policy-making can leverage these findings for effective green production cost reductions.

We consider market and technological equilibria in Cournot competition with linear and isoelastic demand between firms heterogeneous in operational and environmental efficiency. We examine possibilities and limitations of incentivizing “green” technology choice with environmental/”carbon” taxes. The resultant equilibria and the impact of taxation qualitatively differ with demand function.

There are more than 1.1 billion people lacking electricity residing in off-grid communities, where extending national electricity grids is infeasible. These communities turn to stand-alone diesel generators for their energy needs, which creates significant economic, operational and environmental challenges. In this study, we identify the optimal capacity investment decisions from the perspective of a remote community and investigate how common policy mechanisms interact with these decisions.

Precision agriculture has been promoted by agricultural technology providers through the use of outcome-based pricing (OBP). In this paper, we examine the effects of OBP on the adoption rate of precision agriculture, and the benefits it offers to both farmers and service providers. We develop a two-period game model that incorporates providers' learning from experience. We also explore the implications of government intervention when the service provider switches to OBP from traditional pricing.

Recycled wastewater plays a pivotal role in water sustainability by closing the urban water cycle. This paper studies the wastewater recycling capacity investment decision of a water utility using a two-stage stochastic cost-minimization model under rainfall and recycling cost uncertainties. We characterize the optimal wastewater recycling capacity investment and conduct sensitivity analysis to investigate the impacts of uncertainties on the optimal expected cost and recycling capacity.

Disasters disproportionately affect low-income communities' access to groceries. We study price changes after hurricanes and find higher increases in low-income areas, along with stockouts and substitutions.

Low-income communities face greater price increases, reduced promotions, more stockouts, and increased substitution to higher-priced products.

Disaster response should address pricing, stock management, and equitable access to groceries based on community needs and substitution patterns.

Existing stormwater management fails to address climate-adaptive needs in cities experiencing intensified rainfall. This paper utilizes robust optimization to identify worst-case rainfall scenarios and their impact on flooding loss. It provides guidelines for risk mitigation, optimal infrastructure designs, and emphasizes the urgency of taking action as climate change exacerbates flooding risks.

We study whether legalizing marijuana affects the operational efficiency of manufacturing facilities. We leverage a state-level quasi-experimental setting that arises with the staggered passage of marijuana laws. We find that medical marijuana legislation (MML) adversely affects operational efficiency of facilities, the average waste increased by 5.22 % after MML. Facilities start fewer managerial and technical modifications after MML, which clarifies the degrading mechanisms.

Retailers are increasingly sponsoring take-back initiatives to facilitate the recycling and reuse of secondhand clothing. To stimulate the return of goods, providers share information about circular economy strategies and offer consumers a small incentive in exchange for used clothing items. Through three experiments involving over 3,5000 subjects, we test how consumers’ willingness to return their used garments is affected as the degree of circular economy transparency and reward level is manipulated.

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Many multinational organizations have made dual commitments to halt deforestation and improve farmers’ livelihoods in agricultural supply chains. We propose group incentives conditional on forest protection requirements as a feasible mechanism for achieving this. We develop an analytical model, prove structural results concerning the equilibrium outcomes, and calibrate the model using data we collected from field research in Indonesia, demonstrating the effectiveness of group requirements.

We analyze competition between a sustainable firm and an unsustainable knockoff. We study open-source sharing and advertising strategies.

Sharing green tech can be profitable. Anti-knockoff ads may not be profitable, while self-promotion ads improve profits. Simultaneous use of open-source and ads can be beneficial but may harm the environment.

Firms can use open-source and ads to combat knockoffs. Governments can facilitate sustainable tech sharing through regulations.

In malaria-endemic countries, we explore optimal donor budget allocation for subsidizing antimalarial drugs in the presence of counterfeits. We develop a game-theoretic model and evaluate strategies to combat counterfeits. Our findings suggest the importance of understanding market characteristics to design effective subsidies and policies for improving access to legitimate drugs.

We study how to optimally allocate a limited resource (community solar (CS) capacity) among consumers with heterogeneous income levels and private resource valuations. We identify the shortcomings of existing CS program designs, and study various alternatives. Our recommendation offers consumers income-dependent menus of subscription capacity and rate options; this significantly improves social welfare. We further illustrate its usefulness using numerical studies calibrated by real data.

US nonprofits disclose three expenses annually: program to meet their beneficiaries' needs; fundraising to raise donations; administration to build and maintain capacity. We characterize the optimal budget allocations to program, fundraising, and administration using a two-period model, which also includes the nonprofit’s capacity, return on program (the net value of program to beneficiaries) and uncertain future needs of beneficiaries. The optimal allocation depends on the nonprofit's capacity.

As consumers, policy makers and NGOs associate low environmental impact with “uniformly green” (UG) products or higher recycled/reused content, we explore two issues: (i) Should distinct green preferences be “targeted” with distinct product variants? (ii) Is profitable UG adoption environmentally superior? We show that optimal and eco-friendly UG adoption requires design/quality control and reduced production/material costs, and blindly demanding UG adoption may worsen environmental results.