本文精选了运营管理领域国际顶刊《Manufacturing & Service Operations Management》近期发表的论文，提供运营管理研究领域最新的学术动态。

Recharging Retail: Estimating Consumer Demand Spillovers from Electric Vehicle Charging Stations

原刊和作者：

Information Systems Research Volume 35, Issue 1

Yash Babar （University of Wisconsin–Madison）

Gordon Burtch （Boston University）

Abstract

Problem definition: We estimate the impact of electric vehicle (EV) charging stations on volumes of consumer foot traffic received by nearby retail establishments. We also explore the conditions under which any effects manifest. Methodology/results: We use a differences-in-differences design, exploiting the staggered introduction of Tesla Supercharger stations across the United States. We combine data on Supercharger installations with mobile phone–based estimates of retailer foot traffic. We explore heterogeneity in the treatment effect, in terms of EV charger characteristics, visitor characteristics, establishment type, and local physical context. We estimate that establishments experience an average 4% increase in monthly visits following the installation of a Tesla Supercharger. These effects arise primarily for retailers that offer relatively quick services (e.g., fast food) and for those located very near to the charger (within 150 meters). The effects are also more pronounced when the Supercharger is one of the first EV chargers introduced into the local area. Managerial implications: We document evidence of the positive retail demand spillovers arising from EV charging station infrastructure. We also document the conditions under which the benefits manifest. Insights for EV network operators, retailers, and policymakers are included.

Link: https://doi.org/10.1287/msom.2022.0519

Collaborative Vehicle-to-Grid Operations in Frequency Regulation Markets

原刊和作者：

Information Systems Research Volume 35, Issue 1

Ho-Yin Mak （Georgetown University）

Runyu Tang （Xi'an Jiaotong University）

Abstract

Problem definition: We study the operations of electric vehicles (EVs) providing frequency regulation services to the electric grid in vehicle-to-grid (V2G) systems. In particular, individually owned EVs collaboratively bid in the regulation market, coordinated by a platform that operates the network of charging equipment. We study how the platform determines optimal pricing incentives for drivers to plug in their EVs, accounting for heterogeneous driving schedules. Methodology/results: We model the platform’s pricing optimization problem as a bilevel program: At the upper level, the platform determines hourly rebates for EV owners to plug in their EVs and capacity bids in the regulation market; at the lower level, individual travelers optimize their travel and charging schedules in response to pricing incentives. To account for uncertainties and heterogeneity in regulation market prices and travel patterns, we adopt distributionally robust optimization techniques to formulate the problem as a mixed-integer second-order cone program. We conduct a computational study based on the California Household Travel Survey data set and actual frequency regulation prices. Our results show that the ability to offer time-varying rebates and install workplace chargers can significantly improve the V2G platform’s expected profits. Managerial implications: As EV adoption progresses past the nascent stage, V2G business models become more viable. Successful implementation of V2G provides economic incentive for switching to EVs, potentially helps sustain adoption growth, and complements the growth of renewable power by helping stabilize the grid. Our findings shed light on the design of driver incentives for V2G systems.

Link: https://doi.org/10.1287/msom.2022.0133

Aggregating Distributed Energy Resources: Efficiency and Market Power

原刊和作者：

Information Systems Research Volume 35, Issue 1

Zuguang Gao （University of California）

Khaled Alshehri （King Fahd University of Petroleum and Minerals）

John R. Birge （University of Chicago）

Abstract

Problem definition: The rapid expansion of distributed energy resources (DERs) is one of the most significant changes to electricity systems around the world. Examples of DERs include solar panels, electric storage, thermal storage, and combined heat and power plants. Because of the small supply capacities of these DERs, it is impractical for them to participate directly in the wholesale electricity market. We study in this paper the question of how to integrate these DER supplies into the electricity market, with the objective of achieving full market efficiency. Methodology/results: We study four aggregation models, where there is an aggregator who, with the knowledge of DERs’ utility functions and generations, procures electricity from DERs, and sells them in the wholesale market. In the first aggregation model, a profit-maximizing aggregator announces a differential two-part pricing policy to the DER owners. We show that this model preserves full market efficiency, that is, the social welfare achieved by this model is the same as that when DERs participate directly in the wholesale market. In the second aggregation model, the profit-seeking aggregator is forced to impose a uniform two-part pricing policy to prosumers from the same location, and we numerically show that there can be large efficiency loss. In the third (fourth) aggregation model, a uniform (semiuniform) two-part pricing policy is applied to DER owners, whereas the aggregator becomes fully regulated but is guaranteed nonnegative (positive) profit. It is shown that these models again achieve full market efficiency. Furthermore, we show that DER aggregation also leads to a reduction in the market power of conventional generators. Managerial implications: DER aggregation via profit-seeking and/or regulated aggregators has been investigated by California Independent System Operator and New York Independent System Operator, among others, and the recent Federal Energy Regulatory Commission Order No. 2222 paved the way for aggregators to bid in the wholesale market. Our four aggregation models may shed light on how DERs should be included in the wholesale electricity market.

Link: https://doi.org/10.1287/msom.2021.0539

Market Thickness in Online Food Delivery Platforms: The Impact of Food Processing Times

原刊和作者：

Information Systems Research Volume 35, Issue 1

Yanlu Zhao （Durham University）

Felix Papier （ESSEC Business School）

Chung-Piaw Teo （National University of Singapore）

Abstract

Problem definition: Online food delivery (OFD) platforms have witnessed rapid global expansion, partly driven by shifts in consumer behavior during the COVID-19 pandemic. These platforms enable customers to order food conveniently from a diverse array of restaurants through their mobile phones. A core functionality of these platforms is the algorithmic matching of drivers to food orders, which is the focus of our study as we aim to optimize this driver-order matching process. Methodology/results: We formulate real-time matching algorithms that take into account uncertain food processing times to strategically “delay” the assignment of drivers to orders. This intentional delay is designed to create a “thicker” marketplace, increasing the availability of both drivers and orders. Our algorithms use machine learning techniques to predict food processing times, and the dispatching of drivers is subsequently determined by balancing costs for idle driver waiting and for late deliveries. In scenarios with a single order in isolation, we show that the optimal policy adopts a threshold structure. Building on this insight, we propose a new k-level thickening policy with driving time limits for the general case of multiple orders. This policy postpones the assignment of drivers until a maximum of k suitable matching options are available. We evaluate our policy using a simplified model and identify several analytical properties, including the quasi-convexity of total costs in relation to market thickness, indicating the optimality of an intermediate level of market thickness. Numerical experiments with real data from Meituan show that our policy can yield a 54% reduction in total costs compared with existing policies. Managerial implications: Our study reveals that incorporating food processing times into the dispatch algorithm remarkably improves the efficacy of driver assignment. Our policy enables the platform to control two vital market parameters of real-time matching decisions: the number of drivers available to pick up and deliver an order promptly, and their proximity to the restaurant. Based on these two parameters, our algorithm matches drivers with orders in real time, offering significant managerial implications.

Link: https://doi.org/10.1287/msom.2021.0354

Toward Advancing Women’s Health in Least Developed Countries: Evaluating Contraceptive Distribution Models in Senegal

Information Systems Research Volume 35, Issue 1

Amir Karimi （The University of Texas at San Antonio）

Anant Mishra （University of Minnesota）

Karthik V. Natarajan （University of Minnesota）

Kingshuk K. Sinha （University of Minnesota）

Abstract

Problem definition: Improving access to contraceptives is one of the most effective interventions to prevent unintended pregnancies and save the lives of women in least developed countries (LDCs), where the overwhelming majority of maternal deaths occur. However, access to reproductive health commodities is often limited in LDCs because of frequent stock-outs at last-mile health facilities. In this study, we evaluate and compare the effect of two distribution models on last-mile contraceptive availability and key public health outcomes (e.g., unintended pregnancies, maternal and newborn deaths). These distribution models are (i) the commonly used pull distribution model, in which health facilities are fully responsible for managing inventory, and (ii) an alternative model known as the informed push distribution model, which delegates inventory management tasks to external logistics providers. Methodology/results: We leverage the staggered transition from pull distribution to informed push distribution in Senegal, a country that redesigned its contraceptive distribution system. We conduct empirical analyses, including a triple differences estimation, on novel field data compiled from multiple sources to evaluate the effect of the transition. We find that the transition significantly reduces contraceptive stock-outs, frontline health worker workload, unintended pregnancies, and maternal and newborn mortalities and also improves client satisfaction, especially in health facilities with less mature inventory management practices and less developed road infrastructure. A comprehensive cost–benefit analysis shows that the aforementioned benefits are achieved in a cost-efficient manner at these facilities, making them prime candidates for the transition. However, for facilities with less mature inventory management practices but more developed road infrastructure, upgrading the inventory management system is a substantially more cost-efficient alternative than transitioning to a new distribution model without compromising the benefits. Managerial implications: Given the resource constraints faced by the public health sector in LDCs, it is imperative to understand how the operational and public health benefits of the transition to the informed push model vary based on facility characteristics. Our findings offer actionable insights for resource allocation by identifying health facilities that benefit the most from the transition.

Link: https://doi.org/10.1287/msom.2021.0488