Research Seminars 2018/2019
Hamed QAHRI SAREMI - DePaul University, USA
June 13th 2019 - Learning Lab (K-Lab)
How Does Supplier Integration Influence Firm Performance? Insights from a Meta-Analytic Structural Equation Modeling Study
Abstract: Prior research shows an overall positive effect of supplier integration on firm performance, but also suggests the presence of a series of contingencies that may affect this relation. In this study, we propose a structural model of four performance mediators –– efficiency, effectiveness, product innovation, and customer service –– that shape the effects of three dimensions of supplier integration –– informational, operational, and relational integration –– on the financial and market performance of a firm. We test our structural model using a meta-analysis of 146 studies comprising 31,129 observations and a state-of-the-art two-stage meta-analytic structural equation modeling (TSSEM) technique. Our findings reveal a myriad of ways that the three dimensions of supplier integration can indirectly influence financial and market performance of a firm and the interactions between the four performance mediators that form these indirect effects. These findings shed light on the mechanisms through which supplier integration can influence firm performance, thereby provide important theoretical and practical contributions.
Hamed GHODDUSI - Stevens Institute of Technology, USA
May 29th 2019 - Learning Lab (K-Lab)
Risk Management of Commodity Processing Firms: An Equilibrium View
Abstract: We provide a stylized model of a commodity production chain with endogenously determined input and output prices. We characterize the hedging policies with a financial contract on the price of the input, and show that hedging effectiveness is bounded. Our model allows firms to include forward-looking information; e.g., regarding future volatility, to the calculation of their hedging strategy. We estimate a parametrized version of our model for the crude oil to refined products supply chain, using the simulated method of moments (SMM). Our model approximates the dynamics in the crude oil and refined products markets, and can be used to study the impact of technological change, changes in volatility, and shocks to the supply side in the crude oil, refined products, and the refinery industries on the optimal hedging strategy. Joint work with Sheridan Titman and Stathis Tompaidis.
Video link: https://www.youtube.com/watch?v=pAHuOg6G5cg
Jon LEE - University of Michighan, USA
May 27th 2019 - Learning Lab (K-Lab)
Explainable Models via Sparse Reflexive Generalized Inverses
Abstract: The Moore-Penrose (M-P) pseudoinverse of a matrix A is a standard tool for fitting least-squares models and solving other key problems. But even when A is sparse, the M-P pseudoinverse is usually dense. This can be problematic for situations in which A is huge. Focusing on the rank-deficient situation, we propose many new sparse generalized inverses, examine their properties, and give efficient and simple approximation algorithms for them. Our sacrifice in approximating is compensated for by explainability.
Video link: https://www.youtube.com/watch?v=3FalCmGh3h4
Foad MAHDAVI PANJOUH - University of Massachusetts, USA
April 29th 2019 - N231 (Club)
Detecting a Most Closeness-Central Clique in Complex Networks
Abstract: Centrality is a powerful concept for detecting influential components of a graph applicable to various areas such as analysis of social, collaboration, and biological networks. In this study, we employ one of the well-known centrality measures, closeness centrality, to detect a group of pairwise connected members (a highly connected community known as a clique) with the highest accessibility to the entire network. To measure accessibility of a clique, we use two metrics, the maximum distance and the total distance to the clique from other members of the network. Hence, we are dealing with two variants of the most central clique problem referred to as maximum-distance-closeness-central clique and total-distance-closeness-central clique problems. We study the computational complexity of these two problems, and prove that their decision versions are NP-complete. We also propose new mixed 0–1 integer programming formulations and the first combinatorial branch-and-bound algorithms to solve these problems exactly. We show that our algorithmic approaches offer at least 83-fold speed-up on over 97% of benchmark instances in comparison to existing approaches.
Video link: https://youtu.be/n8raW7VBRHA
Claudia ARCHETTI - University of Berscia, Italy
March 6th 2019 - Learning Lab (K-Lab)
The Flexible Periodic Vehicule Routing Problem
Abstract: The Flexible Periodic Vehicle Routing Problem (FPVRP) is the problem where a carrier has to establish a distribution plan to serve the customers over a planning horizon. Each customer has a total demand that must be served within the horizon and a limit on the maximum quantity that can be delivered at each visit. A fleet of homogeneous capacitated vehicles is available to perform the services and the objective is to minimize the total routing cost. The FPVRP can be seen as a generalization of the Periodic Vehicle Routing Problem (PVRP) which instead has fixed service frequencies and schedules and where the quantity delivered at each visit is fixed. Moreover, the FPVRP shares some common characteristics with the Inventory Routing Problem (IRP) where inventory levels are considered at each time period and, typically, an inventory cost is involved in the objective function. This study presents a worst-case analysis which shows the advantages of the FPVRP with respect to both PVRP and IRP. Moreover, a mathematical formulation for the problemi s proposed, together with some valid inequalities. Computational results show that adding flexibility improves meaningfully the routing costs in comparison with both PVRP and IRP.
Video link: https://www.youtube.com/watch?v=WG4y0MjRVuc
Bartholomew McCARTHY - Notthingham University Business School, United Kingdom
February 7th 2019 - Learning Lab (K-Lab)
Opportunities & Challenges for OM & OR Research in Omni-Channel Retailing
Abstract: The nature of retailing is changing. Historically, all customers were served from a network of bricks-and-mortar stores. Today’s retail customers seek to access information and make purchase decisions in whatever way, and on whatever device they wish. They also want to receive their orders whenever, wherever, and however they wish. Thus, retailers are under pressure to offer multiple retail channels and multiple fulfilment modes in order to satisfy very different customer journeys. ‘Omni-Channel’ retailing changes the nature and granularity of retail order fulfilment fundamentally. We first discuss different types of multi-channel retailing and provide a conceptual map for omni-channel order fulfilment decisions at strategic, operational, and tactical levels. We illustrate models for one of the most popular modes of Omni-Channel fulfilment - ‘Buy-online-pickup-in-store’ (BOPS) – where retailers use their store network for fulfilment and advertise an ordering window with a guarantee of when their order will be available for collection, often the same day. Omni-Channel retailing is practice-led and retailers are experimenting, trialling, and implementing different solutions and systems, not always successfully. The wide opportunities for both modelling research and empirical OM research across the omni-channel retailing landscape are discussed.
Video link: https://www.youtube.com/watch?v=tJ6od0g4WHs
Raouf BOUCEKKINE - Université de Aix-Marseille, France
December 4th 2018 - N231 (The Club)
On a Class of Stochastic Dynamic Lobbying Games: Theory and application to Petropolitics
Abstract: We study a 2-players stochastic dynamic symmetric lobbying game. Players have opposite interests; at any date, each player invests in lobbying activities to alter the legislation in her own benefit. The payoffs are quadratic and uncertainty is driven by a Wiener process. We prove that while a symmetric Markov Perfect Equilibrium (MPE) always exists, (two) asymmetric MPE only emerge when uncertainty is large enough. In the latter case case, the legislative state converges to a stationary invariant distribution. More importantly, we show that rent dissipation is superior in the asymmetric equilibrium (compared to the symmetric) provided uncertainty is high but remains moderate. If uncertainty is too high, lobbying efforts drop in both types of equilibria. But the specific uncertainty-induced mechanism being inherently more affected, rent dissipation is lower in the asymmetric equilibrium. Last but not least, we depart from the latter model by introducing stochastic resource revenues (as a second state equation) and asymmetric lobbying power depending on the level of resources. We use this enlarged model to study a stochastic version of the so-called "First Law of Petropolitics".
Pietro DE GIOVANNI - ESSEC Business School, France
November 15th 2018 - N305 (Nautile bulding)
Conformace Quality, Goodwill and Cooperative programs in a Dynamic Supply Chain
Abstract: This research explores a supply chain game with operations and marketing problems. It focuses on the detrimental effect of non-conformance quality on goodwill and how it can be mitigated by using a cooperative program. To address this question, we adopt a dynamic approach as both conformance quality and goodwill are dynamic phenomenon. We use a proactive approach to conformance quality where firms invest in appraisal and prevention to avoid selling defective items. High conformance quality rates translate into high marginal production cost, while low conformance quality rates generate lots of returns and consumers dissatisfaction. The latter will be explored by modelling the interface between conformance quality and goodwill. Several types of cooperative programs can be offered to alleviate the negative effect of conformance quality on supply chain members' profits. We investigate various forms of cooperation to make firms economically better-off and minimize the number of dissatisfied consumers.
Video link: https://www.youtube.com/watch?v=TJ_pTTORESM
Hassan BENCHEKROUN - McGill University, Canada
October 4th 2018 - Learning Lab (K-Lab)
OPEC, Shale Oil and Global Warming. On the importance of the Order of Extraction
Abstract: We show that OPEC’s market power contributes to global warming by enabling producers of relatively expensive and dirty oil to start producing before OPEC reserves are depleted. We fully characterize the equilibrium of a cartel-fringe model and use a calibration to examine the importance of this extraction sequence effect. While welfare under the cartel-fringe equilibrium can be significantly lower than under a first-best outcome, almost all of this welfare loss is due to the sequence effect. Moreover, the recent boom in shale oil reserves may reduce social welfare.
Video link: https://www.youtube.comwatchv=UCtuj4M2JMU
Georges ZACCOUR - HEC Montréal / GERAD, Canada
September 7th 2018 - N231 (The Club)
Brand Imitation: A Dynamic-Game Approach
Abstract: Brand imitation is a common practice that can take different forms, i.e., legal copying, as in the case of clones and knockoffs, or illegal, in the case of counterfeiting. We consider a scenario in which a producer enters the market with a "similar" product to the incumbent's and we assess the impact of this entry on the incumbent's strategies and outcomes. A distinctive feature of our model is that it allows for brand dilution, which means that the original brand suffers due to imitation, and for brand enhancement, when the availability of the imitation product actually promotes the original brand. We characterize and contrast the solutions for the scenario with entry and the benchmark case where no entry occurs, in a fully dynamic context and we examine the effect of a change in the date of entry on the entrant's profit. Joint work with Bertrand Crettez and Naila Hayek.
Keywords: Brand Imitation; Counterfeiting; Pricing Strategy; Advertising Strategy; Differential Games.
Video link: https://www.youtube.com/watchv=dK7rPntYp80