Knowledge that Transforms

Problem definition: We examine the environmental implications of shifting from in-person to virtual conference formats and identify the effects of such a shift on the value conferences provide to our societies. We extend work from other fields to present a more comprehensive comparison of the environmental impact and perceived value of different conference formats for the operations management/research communities. Methodology/results: We leverage a series of COVID-19–induced natural experiments to precisely evaluate the environmental footprint and societal value difference between in-person and virtual formats via life cycle assessment and survey techniques, respectively. Specifically, we focus on Institute for Operations Research and the Management Sciences, Production and Operations Management Society, and European Operations Management Association conferences that were conducted in both formats between 2019 and 2021. The environmental assessment reveals a huge impact reduction: for climate change, on average, from 941.9 kg CO 2eq per person for in-person formats to 1.0 for virtual. The value assessment emphasizes, instead, a detrimental utility loss with the overall perceived value derived from attendance moving—on a scale from 0 to 10—on average, from 7.9 to 4.0. When investigating the drivers of conference valuation, virtual formats show some merits, such as lower perceived costs and the added value of flexibility. The preference for in-person formats is unambiguous though, justified by the large performance gap related to socialization and networking, the two most important value drivers identified by our analysis. Managerial implications: These results highlight an inherent trade-off between virtual and in-person conferences. To overcome it, we discuss four strategies as to how our societies can reduce their environmental footprints and remain true to their essential purpose: (1) reduce in-person impact, (2) improve virtual design, (3) hybrid and decentralized formats, and (4) revise conferencing model and societies’ role.

The journal is pleased to publish the abstracts of the six finalists of the 2022 Manufacturing and Service Operations Management Society’s student paper competition. The 2022 prize committee was chaired by Florin Ciocan (INSEAD), Ersin Korpeoglu (University College London), and Nikos Trichakis (Massachusetts Institute of Technology). The judges were Adam Elmachtoub, Adem Orsdemir, Agni Orfanoudaki, Alp Akcay, Alper Nakkas, Amrita Kundu, Amy Pan, Andrew Wu, Antoine DESIR, Anyan Qi, Arian Aflaki, Ashish Kabra, Auyon Siddiq, Bilal Gokpinar, Bob Batt, Bora Keskin, Can Zhang, Dan Iancu, Dan Iancu, Daniel Freund, Daniel Lin, Daniela Saban, David Drake, Dawson Kaaua, Ekaterina Astashkina, Elena Belavina, Elodie Adida, Emre Nadar, Fabian Sting, Fanyin Zheng, Fei Gao, Georgina Hall, Gizem Korpeoglu, Gonzalo Romero, Guoming Lai, Hessam Bavafa, Hummy Song, Ioannis (Yannis) Bellos, Ioannis Stamatopoulos, Iris Wang, Itir Karaesmen, Jiankun Sun, Jiankun Sun, Jiaru Bai, Jiayi Joey Yu, Jing Wu, Joel Wooten, John Silberholz, Jonathan Helm, Jose Guajardo, Karen Zheng, Ken Moon, Kenan Arifoglu, Kimon Drakopoulos, Kostas Bimpikis, Lennart Baardman, Lina Song, Luyi Gui, Luyi Yang, Miao Bai, Mika Sumida, Ming Hu, Mumin Kurtulus, Nazli Sonmez, Negin Golrezaei, Nektarios Oraiopoulos, Nil Karacaoglu, Nitin Bakshi, Nitish Jain, Nur Sunar, Olga Perdikaki, Ovunc Yilmaz, Ozan Candogan, Panos Markou, Pengyi Shi, Philip Zhang, Philipp Cornelius, Qi (George) Chen, Qiuping Yu, Ruslan Momot, Ruth Beer, S. Alex Yang, Saed Alizamir, Safak Yucel, Sanjith Gopalakrishnan, Santiago Gallino, Sarah Yini Gao, Scott Rodilitz, Sebastien Martin, Sheng Liu, Shouqiang Wang, Simone Marinesi, Sina Khorasani, So Yeon CHUN, Somya Singhvi, Soo-Haeng Cho, Soroush Saghafian, Sriram Dasu, Stefanus Jasin, Stephen Leider, Tian Chan, Tim Kraft, Tom Tan, Vasiliki Kostami, Velibor Misic, Vishal Agrawal, Xiaojia Guo, Xiaoshan Peng, Xiaoshuai Fan, Xiaoyang Long, Yangfang (Helen) Zhou, Yasemin Limon, Yehua Wei, Ying-Ju Chen, Yonatan Gur, Yuqian Xu, Zhaohui (Zoey) Jiang, Zhaowei She, and Zumbul Atan.

Problem definition: In many resource scheduling problems for services with scheduled starting and completion times (e.g., airport gate assignment), a common approach is to maintain appropriate buffer between successive services assigned to a common resource. With a large buffer, the chances of a “crossing” (i.e., a flight arriving later than the succeeding one at the gate) will be significantly reduced. This approach is often preferred over more sophisticated stochastic mixed-integer programming methods that track the arrival of all the flights to infer the number of “conflicts” (i.e., a flight arriving at a time when the assigned gate becomes unavailable). We provide a theoretical explanation, from the perspective of robust optimization for the good performance of the buffering approach in minimizing not only the number of crossings but also the number of conflicts in the operations. Methodology/results: We show that the buffering method inherently minimizes the worst-case number of “conflicts” under both robust and distributionally robust optimization models using down-monotone uncertainty sets. Interestingly, under down-monotone properties, the worst-case number of crossings is identical to the worst-case number of conflicts. Using this equivalence, we demonstrate how feature information from flight and historical delay information can be used to enhance the effectiveness of the buffering method. Managerial implications: The paper provides the first theoretical justification on the use of buffering method to control for the number of conflicts in resource assignment problem.

Problem definition: Firms seek to use the contest format to source solutions from a broader network of outside solvers. We study the application of the contest approach in multistage settings and show how and when screening of contestants between stages can produce improved contest outcomes. Methodology/results: We present an application-driven game-theoretic model to capture imperfections in screening using the true-positive rate (sensitivity) and the true-negative rate (specificity). Specifically, we consider a two-stage contest with a screening decision by the firm between the stages. Solvers face uncertainty about their probability of fit, and the final quality of the solution is dependent on the performance across both stages. We identify two mechanisms through which screening induces greater effort, namely the encouragement effect and the competitive contest effect, and characterize how screening should be tuned to the problem setting. We find that filtering out true negatives in contests with exogenous solvers’ probability of fit is optimal for solution-seeking firms. Our results indicate that in case of problems with endogenous probability of fit and less up-front complexity, coarse (imperfect) screening is beneficial in order to manage competition and stimulate greater effort, but it behooves the firm to resort to more accurate screening otherwise. We also derive nuanced results for the case when a seeker faces screening constraints and must balance screening sensitivity and specificity. Managerial implications: Our work provides firms an additional degree of freedom in terms of specific and sensitive screening to design and run contests and to better engage outside solvers. We derive actionable results and translate them into a managerial framework to help fine-tune the screening mechanism for improved contest performance.

Problem definition: Inventory commitment and monetary compensation are widely recognized as effective strategies in monopoly settings when customers are concerned about stockouts. To attract more customer traffic, a firm reveals its inventory availability information to customers before the sales season or offers monetary compensation to placate customers if the product is out of stock. This paper investigates these two strategies when retailers compete on both price and inventory availability. Methodology/results: We develop a game-theoretic framework to analyze the strategic interactions among the retailers and customers and draw the following insights. First, both inventory commitment and monetary compensation may lead to a prisoner’s dilemma. Although these strategies are preferred regardless of the competitor’s price and inventory decisions, the equilibrium profit of each retailer could be lower in the presence of inventory commitment or monetary compensation because they intensify the competition between the retailers. Second, we find that market competition may hurt social welfare compared with a centralized setting by reducing the product availability in equilibrium. The inventory commitment and monetary compensation strategies further intensify the competition between the retailers, therefore causing an even lower social welfare. Managerial implications: Our study shows that, although inventory commitment and monetary compensation improve retailers’ profit and social welfare under monopoly, these strategies should be used with caution under competition.

Problem definition: We consider the parallel machine scheduling (PMS) under job-splitting game defined by a set of manufacturers where each holds uniform parallel machines and each is committed to produce some jobs submitted to her by her clients while bearing the cost of the sum of completion times of her jobs on her machines. An efficient algorithm for this scheduling problem is well known. We consider the corresponding cooperative game, where the manufacturers are players that want to join forces. We show that collaboration is profitable. Yet, the stability of the cooperation depends on the cost allocation scheme; we focus on the core of the game. Methodology/results: We prove that the PMS game is totally balanced and its core is infinitely large, by developing a sophisticated methodology of linear complexity that finds a line segment in its symmetric core. We call this segment the basic core of the game. Managerial implications: This PMS game has the potential for various applications both in traditional industry and in distributed computing systems in the hi-tech industry. The formation of a partnership among entrepreneurs, companies, or manufacturers necessitates not only a plan for joining forces toward the achievement of the ultimate goals, but also an acceptable agreement regarding the cost allocation among the partners. Core allocations guarantee the stability of the partnership as no subset of players can gain by defecting from the grand coalition.

Problem definition: Dynamic forecasting models in auctions have fallen short on two dimensions: (i) the lack of an equilibrium model for final bids and (ii) the lack of a winner’s curse (i.e., a tendency to overpay conditional on winning the auction) adjustment to allow bidders to account for a common value component in the auction item. In this paper, we develop a methodology to accurately predict equilibrium stage bids from the initial bidding dynamics and quantify the impact of the winner’s curse. This methodology allows us to conduct policy simulations to optimize auction design parameters. Methodology/Results: Dynamic auctions typically have a stage of high exploratory activity, followed by an inactivity period, and then an equilibrium stage of last-minute bids with sharp jumps. With a Kalman filter approach, we use exploratory stage bids to predict an auction item’s valuation distribution. We feed this prediction into an equilibrium model and apply item-specific adjustments for winner’s curse, bidder heterogeneity, and inactivity period. We use the resulting equilibrium model to predict the equilibrium stage bids. Our methodology improves the forecast of equilibrium stage bids by 11.33%, on average, compared with a state-of-the-art benchmark. This improvement is even higher (18.99%) for common value auctions. We also find that (i) significantly more (respectively, fewer) bidders internalize the winner’s curse in common value (respectively, private value) auctions; (ii) bidders in common value auctions decrease their bids by 6.03% because of the winner’s curse; and (iii) the inactivity period has a lesser impact on the equilibrium stage bids in private value auctions. Managerial implications: Our proposed methodology is intended to facilitate the need in academia and practice for real-time bid predictions that encompass different levels of the common value component in auctions. Using our methodology, auction platforms can support their choice of minimum bid increment policies and decide how to allocate resources across different auctions to mitigate the adverse effects of the winner’s curse.