Knowledge that Transforms

The journal is pleased to publish the abstracts of the six finalists of the 2020 Manufacturing and Service Operations Management Society’s student paper competition. The 2020 prize committee was chaired by Vishal Agrawal (Georgetown), Feryal Erhun (University of Cambridge), and Jun Li (University of Michigan). The judges were Adem Orsdemir, Antoine Desir, Anton Ovchinnikov, Anyan Qi, Arian Aflaki, Arzum Akkas, Ashish Kabra, Bin Hu, Bob Batt, Bora Keskin, Can Zhang, Carri Chan, Chloe Kim Glaeser, Daniel Lin, Eduard Calvo, Ekaterina Astashkina, Elena Belavina, Elodie Adida, Enis Kayış, Ersin Korpeoglu, Fabian Sting, Fang Liu, Fanyin Zheng, Fei Gao, Florin Ciocan, Gah-Yi Ban, Gizem Korpeoglu, Guihua Wang, Guillaume Roels, Guoming Lai, Hessam Bavafa, Hummy Song, Ioannis (Yannis) Stamatopoulos, Ioannis Bellos, Iris Wang, Itir Karaesmen, Jiankun Sun, Jiaru Bai, Jing Wu, Joann de Zegher, Joel Wooten, John Silberholz, Jose Guajardo, Kaitlin Daniels, Karen Zheng, Ken Moon, Kenan Arifoglu, Lennart Baardman, Leon Valdes, Lesley Meng, Linwei Xin, Luyi Gui, Luyi Yang, Mary Parkinson, Mazhar Arikan, Michael Freeman, Ming Hu, Morvarid Rahmani, Mumin Kurtulus, Nan Yang, Necati Tereyagoglu, Nektarios Oraiopoulos, Nikos Trichakis, Nil Karacaoglu, Nitin Bakshi, Niyazi Taneri, Nur Sunar, Olga Perdikaki, Ovunc Yilmaz, Ozan Candogan, Ozge Sahin, Panos Markou, Pascale Crama, Pengyi Shi, Pnina Feldman, Qiuping Yu, Renyu (Philip) Zhang, Robert Bray, Ruslan Momot, Ruxian Wang, Saed Alizamir, Safak Yucel, Samantha Keppler, Santiago Gallino, Serdar Simsek, Seyed Emadi, Shiliang (John) Cui, Shouqiang Wang, Simone Marinesi, So Yeon Chun, Song-Hee Kim, Soo-Haeng Cho, Soroush Saghafian, Stefanus Jasin, Suresh Muthulingam, Suvrat Dhanorkar, Tian Chan, Tim Kraft, Tom Tan, Tugce Martagan, Velibor Misic, Weiming Zhu, Xiaoshan Peng, Xiaoyang Long, Yasemin Limon, Yehua Wei, Yiangos Papanastasiou, Ying-Ju Chen, and Zumbul Atan.

Manufacturing & Service Operations Management (M&SOM) depends on the volunteer work of many professionals who take the time to provide careful and constructive reviews of the manuscripts submitted to the journal. In fact, in 2010 M&SOM received 581 reviews from 363 individuals. Remarkably, 61% of those reviews were submitted on or before their due date, a figure that increases to 69% if you allow a one-day grace period. Due in large part to the responsiveness of our reviewers, M&SOM made 96% of its 391 manuscript decisions for 2010 regular submissions and revisions within 75 days and 100% within 90 days. While we deeply appreciate all those who served as reviewers for the journal in 2010, some individuals have distinguished themselves by reviewing several manuscripts and with each manuscript by writing a fair, critical, and constructive review in a timely fashion. In recognition of their outstanding service provided to support the journal's scholarly mission, M&SOM grants the 2010 Meritorious Service Award to….

The effective local reuse of physical cash by depository institutions (DIs) is the primary goal of the new cash recirculation policy of the Federal Reserve System (Fed) of the United States. These guidelines, implemented since July 2007, encourage the reuse of cash by (i) penalizing a DI for the practice of cross shipping, the near-simultaneous deposit of used cash to—and withdrawal of fit cash from—the Fed; and (ii) offering a custodial inventory program that enables a DI to transfer fit cash to the Fed's books, but physically hold it within the DI's secured facility. The effective management of the inventory of cash under these new guidelines is both a challenging and important issue for DIs. We introduce two new multiperiod models—designed specifically to capture the operations of a medium-size DI—that emerge from the DI's objective to minimize the total cost incurred in managing the inventory of cash over a finite planning horizon. The Basic Model (BM) captures the DI's mode of operations if it chooses not to locally reuse cash and, instead, incur the cross-shipping penalty. Using two important structural properties, we provide a polynomial-time dynamic programming algorithm for BM. The Reuse Model (RM) represents the DI's actions when it locally recirculates cash. We first prove the hardness of RM and then develop an integer programming formulation. A comprehensive test bed—based on our interaction with a leading secure-logistics provider—helps us to develop several useful insights into the relative impacts of the DI-specific parameters and the Fed's cross-shipping fee on the effective management of cash. In particular, we show that the Value of Local Reuse for a DI, measured as the percentage cost saving between the optimal solutions of BM and RM, is substantial, and we analyze the forces that influence the volume of cross shipping. We also develop a rolling-horizon procedure to adapt the optimal solutions of BM and RM for obtaining near-optimal real-time solutions in the presence of a modest amount of uncertainty. Finally, we provide a comparative analysis of a DI's decisions under the Fed's mechanism and those under a socially optimal mechanism.

We study a modified newsvendor model in which the newsvendor obtains a revenue from sales to end users as well as from an advertiser paying to obtain access to those end users. We study the optimal decisions for both a price-taking and a price-setting newsvendor when the advertiser has private information about its willingness to pay for advertisements. We find that the newsvendor's optimal policy excludes advertisers with low willingness to pay and distorts the price and quantity from its system-efficient level to screen the advertiser. Our analysis reveals the different roles that pricing and production quantity play as screening instruments. We perform a numerical analysis to investigate the value of information and the impact of the model parameters.

We conduct a field study in a U.S. health insurance firm to examine how product customization affects the firm's cost to serve customers through its call center. In our setting, the product is a complex health insurance plan. The firm incurs substantial costs in serving the customers through its call center and in adjudicating the claims using its information systems. The firm sells either standard plans or in some instances allows customer groups to customize their plans by adding and modifying certain aspects in active collaboration with the firm. Such a collaboration process is akin to the firm cocreating products with its customers. This cocreation process should increase customers' familiarity with their coverage and improve the fit with their medical needs. Better fit and familiarity in turn, reduces customers' incentives to contact the call center for clarifications regarding the firm's product coverage. In particular, we show that customers with a customized plan call 21% less frequently than customers with a standard plan. Our results account for possible self-selection of customers to customized plans. We also show no difference in the claims adjudication cost between a standard and a customized plan exists. Overall, our results suggest customized plans may be operationally cheaper to serve than standard plans. Thus, our paper provides a link between a growing business concern (customer support cost via call centers) and a prevalent business strategy (product customization via cocreation).

We consider a firm that produces multiple variants of a product. Products are assembled using a combination of common and dedicated components. We characterize the optimal assortment and derive the optimal inventory levels for the common and dedicated components under various bill-of-material configurations. We investigate the effect of commonality on product variety and compare its benefits under different demand characteristics. Commonality always leads to increased profits, but its effect on the level of product variety depends on the type of commonality. If all common components are used for the production of the entire set of products, then the optimal variety level increases relative to the system with no commonality. However, if the common components are used by a subset of the final products, then the optimal variety level may decrease with commonality. We find that the effects of commonality on profit and variety level are stronger under a demand model in which product demands are more variable and exhibit pairwise negative correlation relative to a model with independent demands.

This paper studies the optimization of the (S, T) inventory policy, where T is the replenishment interval and S is the order-up-to level. First, we demonstrate that the previously established joint convexity of the long-run average cost is false. Hence, the optimization is not straightforward. We then point out that the joint convexity concept depends on whether S and T are continuous or discrete variables, and in some situations it may not even be well defined. Nonetheless, we are able to identify several useful properties of the cost function, such as submodularity and coordinatewise convexity. Based on these properties, we develop efficient algorithms to compute the optimal policy for continuous and discrete demands.

Focusing on a seller's regret in not acting optimally, we develop a model of overbooking and fare-class allocation in the multifare, single-resource problem in revenue management. We derive optimal static overbooking levels and booking limits, in closed form, that minimize the maximum relative regret (i.e., maximize competitive ratio). We prove that the optimal booking limits are nested. Our work addresses a number of important issues. (i) We use partial information, which is critical because of the difficulty in forecasting fare-class demand. Demand and no-shows are characterized using interval uncertainty in our model. (ii) We make joint overbooking and fare-class allocation decisions. (iii) We obtain conservative but practical overbooking levels that improve the service quality without sacrificing profits. Using computational experiments, we benchmark our methods to existing ones and show that our model leads to effective, consistent, and robust decisions.