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Mohsen ELHAFSI - School of Business, University of California, Riverside
January 28
Title : Long-Term Procurement under Supply Risks: Incentives for Production Smoothing
Abstract : Production smoothing is critical for ensuring continuous supply, price stability, and customer satisfaction, yet it remains vulnerable to dynamic supply risks. This paper examines how firms can incentivize production smoothing within procurement relationships.We study a novel long-term procurement contract in a decentralized, two-echelon supply chain, where a risk-averse buyer sources from a supplier whose supply states are private and evolve dynamically. Using a constrained optimal control framework, we derive the optimal contract and develop a divide-and-conquer algorithm to compute its components. The optimal contract balances efficiency maximization, production smoothing, and information screening, and is characterized by front-loaded premiums and elevated early production quantities. Our contributions are threefold. (i) We identify an intertemporal linkage in production quantities: the buyer raises current production while reducing future quantities—a dynamic akin to a lever-fulcrum system. This linkage arises even when control does not influence state transitions, reflecting the buyer’s motive to control rent while smoothing production. (ii) We demonstrate a constructive role of risk aversion: the buyer’s preference for production smoothing mitigates efficiency losses from information asymmetry, narrowing the gap between second-best and first-best outcomes through a preference channel. (iii) We provide actionable guidance: the buyer’s pursuit of production smoothing to hedge against uncertainty can alleviate agency problems. We caution against the irrelevance theorem that treats post-contract private information as innocuous, and we show why buyers should moderate investments in supplier information capabilities while favoring long-term procurement relationships. By highlighting the interplay between production smoothing and information asymmetry, our results contribute to both procurement theory and managerial practice.
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Kai HOBERG - Kühne Logistics University
January 14
Title : Demand Implications of Reshoring : How Product Origin Shapes Perceptions, Purchase Intentions, and Willingness to Pay
Robin Kabelitz-Bock, Kai Hoberg, Guido Voigt
Abstract : Firms are increasingly re-evaluating global production locations due to supply chain disruptions, cost volatility, sustainability pressures, and geopolitical risks. While reshoring research has focused on cost and risk assessments, little is known about the demand-side implications of production location decisions. Building on country-of-origin (CoO) research, our study examines whether and why consumers value local product origins and how such preferences affect purchase intention (PI) and willingness to pay (WTP). Using a mult-method design, we conduct three complementary empirical studies with a total of 1.878 subjects. Study 1 employs a choice-based conjoint experiment to test consumer preferences across origins and products. Study 2 investigates the behavioral mechanisms linking origin, perceptions, PI, and WTP. Study 3 isolates the causal effects of quality, environmental, and social sustainability perceptions on these outcomes.
Across studies, consumers consistently favor local production and exhibit higher WTP for domestic goods, revealing measurable demand-side value.
Origin affects WTP indirectly through PI, with quality as the strongest driver, complemented by environmental and social sustainability.
The findings extend production location decision and CoO research by providing behavioral evidence of consumer-based value creation and integrating sustainability perceptions into production location decision making. For managers, the findings highlight that emphasizing credible information about production origin can justify a price premium, providing a potential lever to offset higher costs of local production and emphasizing the importance of considering both cost and demand implications of production location decisions.
Keywords: Reshoring, production location decision, country of origin, consumer behavior.
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Sytske WIJNSMA - UC Berkeley Haas
December 17
Title : Des produits plus intelligents, une durée de vie plus courte : le coût environnemental des produits embarqués
Abstract :
Les produits à forte composante logicielle sont confrontés à un défi majeur en matière de durabilité : l’obsolescence matérielle est de plus en plus due à l’évolution des logiciels plutôt qu’à la dégradation physique, générant ainsi d’importants flux de déchets électroniques. Cet article examine la réponse stratégique de la chaîne d’approvisionnement pour atténuer ce remplacement forcé du matériel grâce à deux mécanismes : le support des logiciels existants et la pérennisation du matériel. Nous modélisons des configurations de chaîne d’approvisionnement intégrées (logiciels internes) et décentralisées (logiciels tiers) afin de déterminer les conditions d’adoption de ces mesures d’atténuation et leur impact sur la production de déchets électroniques et le bien-être des consommateurs. Enfin, nous analysons l’effet de la législation sur la responsabilité élargie des producteurs (REP) et de la loi sur la résilience en matière de cybersécurité (CRA), récemment introduite.
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Yasmine BECK - Postdoc at ESSEC
November 12
Title : A Primer on Bilevel Optimization under Uncertainty and Solution Approaches for Robust Bilevel Problems.
Abstract : Bilevel optimization is a rather young but very active sub-field of mathematical optimization. The main reason is that bilevel optimization problems can serve as a powerful tool for modeling hierarchical decision-making processes, which arise in various real-world applications such as in critical infrastructure defense, transportation, or energy. However, the nested structure of bilevel problems makes them intrinsically hard to solve—even if all parameters of the problem are exactly known. Further challenges arise if problems under uncertainty are considered.
In this talk, we begin with a brief introduction to bilevel optimization under uncertainty. In particular, we highlight that the sources of uncertainty in bilevel optimization are much richer compared to classic, i.e., single-level, optimization because not only the problem data but also the (observation of the) decisions of the two players can be subject to uncertainty.
We then explore how techniques from robust optimization can be used to tackle bilevel problems under uncertainty and discuss some recent algorithmic advances for solving mixed-integer linear Gamma-robust bilevel problems. Finally, we conclude with a brief look at emerging solution approaches for another class of robust bilevel problems.
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Nandan KUMAR SINGH, FORE School of Management, New Delhi
October 21
Title : Optimal Strategies for Battery Design for Recyclability under Uncertainty and
Regulation
Abstract :
Electric Vehicle battery regulations mandate the Original Equipment Manufacturers (OEMs) to use certain proportion of rare earth metals in the design of newer batteries. This requires the OEMs to enter into collaboration with the battery recyclers. In this paper, we consider the strategic interactions between OEMs and the battery recyclers from the perspective of designing batteries for recyclability when there is uncertainty around the recycling value. We model the interaction as a Stochastic Stackelberg–Nash Equilibrium problem, where the recycler is the follower and decides on the recycling capacity, while the OEM as the leader, seeks to maximize expected profit by optimizing its investment in designing batteries suitable for recycling. We obtain the following results. First, in the absence of any regulation, we show that a contract can lead to a win-win-win outcome for the OEM, the recycler, and the environment. The total business value also increases compared to the case of no collaboration. Second, we show that under a regulation mandating minimum recycling threshold, the total business value increases even more when the battery recyclability design cost is low. Conversely, when the battery recyclability design is costly and the used battery transaction price is high, stricter regulation always decreases business value. However, when the battery recyclability design is costly and the used battery transaction price is low, total business value becomes a convex unimodal function of regulation, the impact is driven by the quantum of minimum recycling material target by the government. Finally, our analysis suggests that when the mandatory recycling level exceeds a certain threshold, it always benefits the recycler and hurts the OEM suggesting that the government could consider introducing subsidies for OEMs to support battery design for recyclability.
Keywords: Electric Vehicle Battery, Recycling, Regulation, Uncertainty, Stochastic Stackelberg Nash Equilibrium.
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Javier MARENCO - University Torcuato Di Tella, Argentina
October 1
Titre : Dynamic parking in unstructured parking lots
Abstract : We consider the following dynamic car parking problem. We have a parking lot, which we assume is divided into a grid of n × m positions. A single car can be placed in each position. We assume that each position corresponds to a rectangle with its longest side parallel to the horizontal axis, so that each car faces either the left or right side of the grid. In the classic scheme, the grid is divided into vertical "lanes," on which a car cannot be placed, such that the remaining positions allow a path to/from the parking lot entrance/exit. In this work, we consider a more general version of the problem, in which a car can park in any position of the grid, as long as there are paths from the entrance/exit to that position when the car enters and exits the parking lot. Once parked, a car cannot move from its position. A priori, this strategy allows for the allocation of a larger number of cars than the classic scheme, making better use of available resources.
We assume we have a list of reservations, each consisting of a day and time of the reservation, a day and time of the car's arrival at the parking lot, and a day and time of the car's departure from the parking lot. Given this reservation list, the offline problem consists in determining the largest number of cars (or, alternatively, the largest revenue) that can be allocated to the parking lot. The online version consists of determining, for each car in the reservation list in order of reservation date, whether the car can be accepted and, if so, in which position it should be allocated. In this work, we propose an integer linear programming model for the offline problem and several integer linear programming-based strategies for the online problem. Using historical reservation data for a parking lot in Santiago, Chile, we show that online schemes are feasible and allow for a better use of the available space.
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