Tag: MIT

Please visit the MIT System Dynamics Seminars page for more information.

You are invited to attend the System Dynamics Seminar on Friday, October 7^th from 12:30-2:00pm EDT in the Jay W. Forrester conference room, E62-450, or via Zoom: https://mit.zoom.us/j/97141505370 (Password: SDFall2022). Our guest speaker will be Kyle Hyndman (University of Texas at Dallas) presenting A Replication Study of Operations Management Experiments in Management Science (see abstract and brief bio below, announcement attached). Lunch will be provided to those attending in person.

If you would also like to schedule a 30-minute 1:1 meeting with Kyle Hyndman, please fill out the following Doodle poll by COB Wednesday and I will confirm times with a calendar invite: https://doodle.com/meeting/participate/id/eE9E20me.

Abstract 

Over the past two decades, researchers in operations management have increasingly leveraged laboratory experiments to identify key behavioral insights. These experiments inform behavioral theories of operations management, impacting domains including inventory, supply chain management, queuing, forecasting, and sourcing. Yet, until now, the replicability of most behavioral insights from these laboratory experiments has been untested. We remedy this with the first large-scale replication study in operations management. With the input of the wider operations management community, we identify ten prominent experimental operations management papers published in Management Science, which span a variety of domains, to be the focus of our replication effort. For each paper, we conduct a high-powered replication study of the main results across multiple locations using original materials. In addition, our study tests replicability in multiple modalities (in-person and online) due to laboratory closures during the COVID-19 pandemic. Our replication study contributes new knowledge about the robustness of several key behavioral theories in operations management and contributes more broadly to efforts in the operations management field to improve research transparency and reliability.

 Kyle Hyndman is a Professor of Managerial Economics at the University of Texas at Dallas. He studies problems related to (i) strategic learning, (ii) coordinating behavior, and (iii) bargaining and coalition formation using both theory and experiments to provide insights on these problems. He works on problems of interest to both economists and operations managers and his research has been published in leading journals in both economics and operations management. Most recently, he has co-edited the book “Bargaining: Current Research and Future Directions”, with the aim of providing scholars an up-to-date snapshot of the literature on bargaining theory, experiments and empirics as well as promising new directions for the field.

Please visit the MIT System Dynamics Seminars page for more information.

You are invited to attend the System Dynamics Seminar being held this Friday from 12:00-1:30 pm ET in the Jay W. Forrester conference room, E62-450, or via Zoom:: https://mit.zoom.us/j/97116456932 (password: SDFall2022).

Our guest speaker will be James Paine (MIT Sloan) presenting Simpler is (Sometimes) Better: A Comparison of Cost Reducing Agent Architectures in a Simulated Behaviorally-Driven Multi-Echelon Supply Chain Lunch will be provided to those attending in person.

If you would also like to schedule a 30-minute 1:1 meeting with Brent Moritz, please fill out this Doodle poll https://doodle.com/meeting/participate/id/b2vWmxAb by COB Wednesday and I will confirm times with a calendar invite.

Please check here for the latest updates on MIT’s COVID policies: https://now.mit.edu/policies/

Abstract

Supply chains partially consist of, and almost exclusively exist for, people. Behavioral Operations Management has endeavored to identify how the behavioral responses of these people, decision makers in supply chains, differ from the fully rational and to identify policies incorporating on these differences. The complexity of such policies, and the underlying assumptions of rationality, can vary widely. This work utilizes a model of a multi-echelon supply chain, captured by the classic Beer Game inventory management simulation, to compare the features of policies that can reduce costs from bullwhip when placed in such a system while still allowing other entities to behave in a behaviorally. This work contributes to existing supply chain management literature by applying a dueling-DQN structure and Model-Predictive learning structure to this multi-echelon supply chain system in a manner that can be leveraged for other research. However, this is secondary to the main observation of this work that relatively simple ordering policies, including static base-stock rules, in these behaviorally-driven systems can have large cost-reducing effects only marginally behind more complex methods. Additionally, for model-predictive learning agents, even myopic approaches with limited information about the overall system and greedy objectives can be cost reducing globally. This has direct managerial implications by showing how a decision maker embedded in a supply chain with other behavioral actors does not need to be perfectly rational and can be locally focused while achieving global benefits.

James Paine is a fifth-year doctoral candidate at the Sloan School of Management at MIT, studying System Dynamics and its applications to product and service delivery systems. Prior to coming to the System Dynamics group, James gained experience in the nuclear, reverse logistics, and consumer apparel industries, as both an engineer and product lifecycle-focused marketer. Currently, James focuses on behavioral operations management questions, including human-algorithm interactions, supply chain research and analytics, and dynamic modeling of product and service delivery systems. More information about James and his research can be found at https://jpaine.info/.

Please visit the MIT System Dynamics Seminars page for more information.

You are invited to attend the System Dynamics Seminar being held this Friday from 12:00-1:30pm ET in the Jay W. Forrester conference room, E62-450, or via Zoom: https://mit.zoom.us/j/96947695163 (Password: SDFall2002).

Our guest speaker will be Brent Moritz (Penn State University) presenting Unraveling Behavioral Ordering: Relative Costs and the Bullwhip Effect (see abstract and brief bio below). Lunch will be provided to those attending in person.

If you would also like to schedule a 30-minute 1:1 meeting with Brent Moritz, please fill out this Doodle poll https://doodle.com/meeting/participate/id/b2vWmxAb by COB Wednesday and I will confirm times with a calendar invite.

Please check here for the latest updates on MIT’s COVID policies: https://now.mit.edu/policies/

Abstract

Behavioral ordering results in poorer supply chain performance. However, how might one separate and evaluate the behavioral causes of increased orders from the effect of increased orders elsewhere in the supply chain?  In this paper, we investigate several related questions: (i) What is the impact of behavioral ordering in a multi-echelon supply chain? Although prior literature has shown that behavioral ordering is detrimental to performance, we show how much worse it is than rational ordering. (ii) How does behavioral ordering in one echelon impact the costs elsewhere in the supply chain? Answering this question is not straightforward, as it requires separating the impact of a rational response to incoming orders (such as increasing safety stock) from additional behavioral ordering. (iii) Does the cognitive reflection level of each decision maker impact costs in heterogeneous supply chains? (iv) What is the impact of having more than one behavioral decision maker in a supply chain? We provide evidence to show the impact of adding additional behavioral decision-makers to a supply chain. We also investigated if human behavior is consistent with a policy of dynamic updating of inventory, such as changing the amount of safety stock in response to changes in incoming demand.

We use data from a laboratory experiment, estimate behavioral parameters, and use a simulation to evaluate the cost impact of bullwhip behavior on the supply chain and by echelon. Unsurprisingly, behavioral ordering anywhere in the supply chain increases cost. However, these costs are not shared equally: Behavioral ordering by a retailer results in a larger relative cost increase elsewhere in the supply chain. In contrast, behavioral ordering by a wholesaler or distributor tends to increase the cost within that echelon. Individual decision-makers with high cognitive reflection tend to have lower costs for their supply chain, and these individuals also have lower costs for their individual echelons. We also provide initial evidence regarding the cost of multiple human decision makers in a supply chain. Adding additional behavioral decision makers increases cost, though the cost increases show a diminishing return to scale.

Brent Moritz is an Associate Professor of Supply Chain Management at the Smeal College of Business at Pennsylvania State University. He is a faculty affiliate of the Laboratory for Economics, Management and Auctions (LEMA) and is Co‐Director of Research for the Center for Supply Chain Research (CSCR) at Penn State. He earned his PhD (Operations and Management Science) at the Carlson School of Management at the University of Minnesota. He also holds a BS in Mechanical Engineering from Valparaiso University and an MBA from the Weatherhead School of Management at Case Western Reserve University. Prior to obtaining his PhD, he held positions in manufacturing operations and supply chain management at BorgWarner, Eaton and Parker Hannifin. This included international experience working in Mexico, England and Germany.

Dr. Moritz has research interests including supply chain management, behavioral operations, risk management and cognitive decision processes. His research is focused on decision‐making in contexts such as inventory, forecasting and supplier selection. His research has been published in Management Science, Journal of Operations Management, Decision Sciences Journal, Manufacturing and Service Operations Management, and Production and Operations Management. For further information: https://directory.smeal.psu.edu/bbm3

Please visit the MIT System Dynamics Seminars page for more information.

You are invited to attend the System Dynamics Seminar being held this Friday, February 25^th from 1:00-2:30 pm ET in the Jay W. Forrester conference room, E62-450, or via Zoom: https://mit.zoom.us/j/94333057556 (Password: SDSpr22). Our guest speaker will be Robert Axtell (George Mason University) presenting Dynamics of American Firms: Data and a Family of Models (see abstract and brief bio below). A reminder will be sent out closer to the date.

Please check here for the latest updates on MIT’s indoor eating and drinking policies: https://now.mit.edu/policies/events/

Abstract: Using data on the population of all American firms having employees over the last 40 years, several dozen gross empirical regularities, uncovered with statistical and machine learning techniques, will be described. These have to do with firm sizes, ages, growth rates, productivities, financial attributes, inter-firm networks, and spatial locations and involve 100s of millions of workers and 10s of millions of firms. A family of models based on a team production specification will be shown to be capable of reproducing many of these patterns. The equilibria and stability of the model are characterized. Computational challenges associated with rending this model at full-scale with the U.S. economy—in any period, 120 million worker agents self-organized into 6 million emergent firms—will be discussed. This talk is based on a forthcoming book.

Rob Axtell is Professor of Computational Social Science at George Mason University, Co-Director of the Computational Public Policy Lab at the Schar School of Policy and Government at Mason, and an affiliate of the Department of Economics there. His research focuses on the application of computational modeling and simulation techniques to economics and finance. He is External Faculty Fellow at the Santa Fe Institute and Visiting Researcher at Google. He is currently on sabbatical at MIT Sloan.

Professor Axtell is the author, with Joshua Epstein, of Growing Artificial Societies: Social Science from the Bottom Up (MIT Press). His research has appeared in Science, Nature, Proceedings of the National Academy of Sciences, as well as in leading field-specific journals such as The American Economic Review, and has been reprised in newspapers (e.g., Wall St. Journal, Los Angeles Times, Washington Post) and science magazines (e.g., Scientific American, Technology Review, Wired). For the past decade he has been using micro-data on individuals to build large-scale models of the Financial Crisis of 2008-9 (with JD Farmer, Oxford, and J Geanakoplos, Yale), the dynamics of business firms (with O Guerrero, Turing Institute), and natural resource exploitation, e.g., fisheries (with UC Santa Barbara, Oxford, and the Ocean Conservancy). The research on companies is described at length in a forthcoming book, Dynamics of Firms from the Bottom Up Data, Theories, and Models, due out later this year, which uses U.S. micro-data on firm sizes, ages, growth rates, networks, and locations to create a model at 1:1 scale with the American economy.