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The objectives of the M&SOM Practice-Based Research Competition are to motivate, help develop, reward and highlight high-quality OM research papers with significant practical relevance, and to publish these papers in the M&SOM Journal. This paper competition is distinguished by the following features: (i) its focus on practical impact; (ii) papers considered are not yet published; (iii) involvement of high-level practitioners to evaluate papers; (iv) presentations at the MSOM conference by contestants;
(v) organization primarily by the M&SOM journal as opposed to the MSOM Society.
This competition seeks to reward unpublished OM research papers with a high potential or realized impact on practice. Work not implemented yet may be considered, as long as potential benefits to practice can be ascertained with a high level of confidence. More generally, validity (i.e., the extent to which the results presented do or would apply in practice) is a key evaluation criteria.
Entries must be submitted through ScholarOne Manuscripts by September 16, 2026 (please select “Practice-Based Research Competition” for the manuscript type) and include:
The main evaluation criteria include the following:
Papers having a substantial overlap with another paper that is already published, accepted or currently under review with another journal are not eligible. Suitable papers already under review with the M&SOM journal may be considered at any stage of the competition (see Process section below), provided any missing required material is provided by the authors and consent is given by the paper authors, the Department Editor currently overseeing the review and the Competition Chair.
The competition is supported by an Academic Competition Committee effectively organized as a department of the journal: it is composed of M&SOM journal Editorial Board members and chaired by a Competition Chair appointed by the journal EIC. The Competition Chair may appoint individuals to serve as guest Associate Editors for the competition, in consultation with the journal EIC. The competition also involves a Judge Panel composed of high-profile practitioners. The competition selection stages are as follows:
To be announced.
To be announced.
Related questions should be sent to Jérémie Gallien (Competition Chairs) and Bernadett Racz (Administrative Assistant) at [email protected], and [email protected].
Flexible Data Aggregation for Prediction and Decision Making with Contextual Information: Applications in Retailing
Ying Rong; Zhenkang Peng; Chengzhang Li; Zichao Luo; Guangrui Ma; Mingyong Zhao
Cancer Screening Outreach Guided by Machine Learning: The Benefits of Proactive Care
Minje Park; Carri Chan; Keith Boell; Elliot Mitchell; Abdul Tariq; David Vawdrey
Contextual Stochastic Optimization for Omnichannel Multi-Courier Order Fulfillment Under Delivery Time Uncertainty
Tinghan Ye; Sikai Cheng; Amira Hijazi; Pascal Van Hentenryck
Enhancing Volunteer Retention: The Role of Experienced Volunteers
Vinit Tipnis; Christopher Chen; Fei Gao Fei
Data-Driven Pricing for Availability-Based Upgrades Under a Multiple Binary Choice Model with Copula
Ruxian Wang; Ovunc Yilmaz; Zifeng Zhao; Farbod Ekbatani; Andrew Vakhutinsky
The Non-Linear Impact of Promised Delivery Time on Online Purchasing
Shin Oblander; Kinshuk Jerath
Improving Farmers' Income on Online Agri-platforms: Evidence from the Field
Somya Singhvi; Retsef Levi; Manoj Rajan; Yanchong (Karen) Zheng
Leveraging Consensus Effect to Optimize Ranking in Online Discussion Boards
Yonatan Gur; Gad Allon; Joseph Carlstein
Pooling and Boosting for Demand Prediction in Retail: A Transfer Learning Approach
Sheng Liu; Dazhou Lei; Yongzhi Qi; Dongyang Geng; Jianshen Zhang; Hao Hu; Zuo-Jun Max Shen
Patient Sensitivity to Emergency Department Waiting Time Announcements
Eric Park; Huiyin Ouyang; Jingqi Wang; Sergei Savin; Siu Chung Leung; Timothy Rainer
Decarbonizing OCP
Vassilis Digalakis Jr.; Dimitris Bertsimas; Ryan Cory-Wright
Got (Optimal) Milk? Pooling Donations in Human Milk Banks with Machine Learning and Optimization
Timothy Chan; Rafid Mahmood; Deborah O'Connor; Debbie Stone; Sharon Unger; Rachel Wong; Ian Zhu
Redesigning Sample Transportation in Malawi Through Improved Data Sharing and Daily Route Optimization
Jónas Jónasson, Sarang Deo, Emma Gibson, Mphatso Kachule, Kara Palamountain
Ancillary Services in Targeted Advertising: from Prediction to Prescription
Georgia Perakis, Alison Borenstein, Ankit Mangal, Stefan Poninghaus, Divya Singhvi, Omar Skali Lami, Jiong Wei Lua
Improving Match Rates in Dating Markets through Assortment Optimization
Ignacio Rios, Daniela Saban, Fanyin Zheng
Demand Learning and Dynamic Pricing for Varying Assortments
Kris Ferreira, Emily Mower
Estimating Personalized Demand with Unobserved No-purchases using a Mixture Model: An Application in the Hotel Industry
Pelin Pekgun, Sanghoon Cho, Mark Ferguson, Andrew Vakhutinsky
Incentivizing Commuters to Carpool: A Large Field Experiment with Waze
Maxime Cohen, Michael-Davis Fiszer, Avia Ratzon, Roy Sasson
Data-Driven Optimization for Commodity Procurement Under Price Uncertainty
Christian Mandl, Stefan Minner
Detecting Customer Trends for Optimal Promotion Targeting
Lennart Baardman, Setareh Borjian Boroujeni, Tamar Cohen-Hillel, Kiran Panchamgam, Georgia Perakis
Disclosing Product Availability in Online Retail
Eduard Calvo, Ruomeng Cui, Laura Wagner
Pricing for Heterogeneous Products: Analytics for Ticket Reselling
Michael Alley, Max Biggs, Rim Hariss, Charles Herrmann, Michael Lingzhi Li, Georgia Perakis
Understanding the Value of Fulfillment Flexibility in an Online Retailing Environment
Levi DeValve, Yehua Wei, Di Wu, Rong Yuan
Forecasting Airport Transfer Passenger Flow Using Real-Time Data and Machine Learning
Xiaojia Guo, Yael Grushka-Cockayne, Bert De Reyck
Analysis and Improvement of Blood Collection Operations
Turgay Ayer, Can Zhang, Chenxi Zeng, Chelsea C. White III, V. Roshan Joseph
Product-Line Pricing Under Discrete Mixed Multinomial Logit Demand
Hongmin Li, Scott Webster, Nicholas Mason, Karl Kempf
Dynamic Pricing of Omnichannel Inventories
Pavithra Harsha, Shivaram Subramanian, Joline Uichanco
Forecasting New Product Life Cycle Curves: Practical Approach and Empirical Analysis
Kejia Hu, Jason Acimovic, Francisco Erize, Douglas J. Thomas, Jan A. Van Mieghem
Optimal Retail Location: Empirical Methodology and Application to Practice
Chloe Kim Glaeser, Marshall Fisher, Xuanming Su
The Hurricane Decision Simulator: A Tool for Marine Forces in New Orleans to Practice Operations Management in Advance of a Hurricane
Eva D. Regnier, Cameron A. MacKenzie