Seminars

The following speakers will visit Kellogg this Fall for the 2007-08 Kellogg Operations Seminar Series. Please click on a date for more information about a particular talk.

Upcoming:
"A Model of Fair Process and Its Limits"
Talk by Ludo Van der Heyden, INSEAD
May 21st 2008
Fair process research has shown that people care not only about outcomes, but also about the process that produces these outcomes. For a decision process to be seen as fair, the people affected must have the opportunity to give input and possibly to influence the decision, and the decision process and rationale must be transparent and clear. Existing research has shown empirically that fair process enhances both employee motivation and performance in execution.

In this talk, we review the fair process literature and present a more operational definition of fair process, that is motivated both by the literature on fair process and that on decision making.  We present empirical evidence that supports this definition in hte framework of a study of innovation practices in 15 German manufacturing sites.  

We conclude with presenting an analytical model of fair process in a principal-agent (i.e., manager-employee) context, rooted in psychological preferences for autonomy and fairness. This model addresses the question as to why fair process is so often violated in practice. The associated paper breaks new ground by analytically examining the subtle trade-offs involved.
paper #1 paper#2

View past seminars

"Bounded Rationality in Newsvendor Models"
Talk by Xuanming Su, UC Berkeley
September 26th, 2007
Many theoretical models adopt a normative approach and assume that decision-makers are perfect optimizers. In contrast, this paper takes a descriptive approach and considers bounded rationality, in the sense that decision-makers are prone to errors and biases. Our decision model builds upon the quantal choice model: while the best decision need not always be made, better decisions are made more often. We apply this framework to the classic newsvendor model and characterize the ordering decisions made by a boundedly rational decision-maker. We identify systematic biases and offer insight into when over-ordering and under-ordering may occur. We also investigate the impact of these biases on several other inventory settings that have traditionally been studied using the newsvendor model as a building block, such as supply chain contracting, the bullwhip effect, and inventory pooling. We find that incorporating decision noise and optimization error yields results that are consistent with some anomalies highlighted by recent experimental findings.

"Inventory Assortment and Substitution Problems"
Talk by Yehuda Bassok, USC
October 10th, 2007
We consider general substitution problem, in which consumers can choose one of N variants. We start with a choice model that ranks the preference of each consumer. The preferences of each of the consumers are not known to the retailer and thus, he/she must assume that the demand for each variant is random. We are able to calculate the retailer’s optimal stocking policy. We show that the role of safety stock is to hedge against the uncertainty in the market size but not the uncertainty in the demand for each of the variants. We then move the describe competition between retailer. Again, we are able to characterize the equilibrium inventory levels and assortments. When competition is considered safety stock may be carried even if market size is known. But, in most practical cases if market size is known but consumer choice is random no safety stock is carried with a very high probability.

"Randomized Methods for Solving Convex Problems:  Some Theory and Some Computational Experience"
Talk by Robert M. Freund, MIT
October 17th, 2007
In contrast to conventional continuous optimization algorithms whose iterates are computed and analyzed deterministically, randomized methods rely on stochastic processes and random number/vector generation as part of the algorithm and/or its analysis. Whereas randomization in algorithms has been a part of research in discrete optimization for at least the last 20 years, randomization has played at most a minor role in algorithms for continuous convex optimization, at least until recently. This talk will focus on two recent randomization-based algorithms for convex optimization: a method by Bertsimas and Vempala based on cuts at the center of mass, and a new method by Belloni and Freund that “pre-conditions” a standard interior-point algorithm using random walks. For the latter, we report very promising computational results on medium-sized conic problems.

"Optimal Policies for the Acceptance of Living- and Cadaveric-Donor Livers"
Talk by Oguzhan Alagoz UC Berkeley
November 14th, 2007
The talk is based on the papers: "Determining the Acceptance of Cadaveric Livers Using an Implicit Model of the Waiting List" and "The Optimal Timing of Living-Donor Liver Transplantation"

Transplantation is the only viable therapy for end-stage liver diseases (ESLD) such as hepatitis B. In the United States, patients with ESLD are placed on a waiting list. When organs become available, they are offered to the patients on this waiting list. This study focuses on the decision problem faced by these patients: which offer to accept and which to refuse? A recent analysis of liver transplant data indicates that 60% of all livers offered to patients for transplantation are declined.

We formulate this problem as a discrete-time Markov decision process (MDP). We analyze three MDP models, each representing a different situation. The Living-Donor-Only Model considers the problem of optimal timing of living-donor liver transplantation, which is accomplished by removing an entire lobe of a living donor's liver and implanting it into the recipient. The Cadaveric-Donor-Only Model considers the problem of accepting/refusing a cadaveric liver offer when the patient is on the waiting list but has no available living donor. The Living-and-Cadaveric-Donor Model is the most general model, which combines the first two models, in that the patient is both listed on the waiting list and also has an available living donor. The patient can accept the cadaveric liver offer, decline the cadaveric liver offer and use the living-donor liver, or decline both and continue to wait.

We derive structural properties of all three models, including several sets of conditions that ensure the existence of intuitively structured policies such as control-limit policies. The computational experiments use clinical data, and show that the optimal policy is typically of control-limit type.

"Incentives for Retailer Forecasting: Rebates versus Returns"
Talk by Terry Taylor, UC Berkeley
November 28th 2007
Abstract: This paper studies a manufacturer that sells to a newsvendor retailer who can improve the quality of her demand information by exerting costly forecasting effort. In such a setting, contracts play two roles: providing incentives to influence the retailer's forecasting decision, and eliciting information obtained by forecasting to inform production decisions. We focus on two forms of contracts that are widely used in such settings and are mirror images of one another: a rebates contract which compensates the retailer for the units she sells to end consumers, and a returns contract which compensates the retailer for the units that are unsold. We characterize the optimal rebates contract, the optimal returns contract, and the manufacturer's preferred contractual form. We show that the retailer, manufacturer and total system may benefit from the retailer having inferior forecasting technology. (Joint work with Wenqiang Xiao.)

"An Empirical Investigation into the Tradeoffs that Impact On-Time Performance in the Airline Industry"
Talk by Kamalini Ramdas, Virginia
April 9th 2008
We investigate the tradeoff between aircraft capacity utilization and on-time performance, a key measure of airline quality. Building on prior theory and empirical work we expect that airlines that are close to their productivity or asset frontiers would face steeper tradeoffs between utilization and performance, than those that are further away.
We test this idea using a detailed 10-year airline industry data set, drawing on queuing theory to disentangle the confounding effects of variance in travel time and capacity flexibility along an aircraft's route. We find that greater aircraft utilization results in higher delays, with this effect being worse for airlines that are close to their asset frontiers in terms of already being at high levels of aircraft utilization. Also, we find that the negative effect of utilization on delays is greater for aircraft that face higher variability in travel time along their routes, and is lower for aircraft on routes with higher capacity flexibility - in terms of the ability to substitute in a different aircraft for a particular flight than the one that was originally scheduled. Additionally, we examine how load factor, a measure of how full an airline's flights are and therefore a key revenue driver, affects on-time performance. Our analysis enables us to explain differences in on-time performance across airlines as a function of key operational variables, and to provide insight on how airlines can better manage their on-time performance levels and aircraft utilization.

"Profit Loss and Loss of Efficiency due to Competition"
Talk by Georgia Perakis, MIT
April 16th 2008
We consider an oligopoly setting where more than two firms are competing on products that are gross-substitutes or complements. We study the profit loss due to competition (i.e., comparison of the total profit in the industry between centralized and decentralized settings) for Bertrand (price-setting) competition and for Cournot (quantity-setting) competition.  Our goal is to understand how the presence of competition affects the overall profit as well as the total surplus in the industry and what the key drivers of the inefficiencies that arise due to competition are.

Our research to date suggests that for gross substitutes the "market power" of each firm (in terms of how much they can each affect the total demand in the market with their decisions) play an important role. On the other hand, for complement products, the number of firms competing in the market and the number of products produced by each firm also play a role.  To achieve this we develop bounds on how bad the total profit in the industry can become due to competition. We further discuss a setting where each firm is selling several products and is faced with a variety of constraints on the prices or quantities of the products it offers. We provide general bounds that are independent of the constraints of the game and as a result apply to a large class of settings. Our results for example, apply to competitive settings where firms sell various versions of the same product line and want to make sure the prices between each version of the product does not vary by a lot.

Furthermore, we consider more general measures of efficiency such as the total surplus in the market. We further generalize our results to classes of nonlinear demand functions.
(joint work with A. Farahat and J. Kluberg)

"Inadvertent Disclosure—Information Risk and Governance in the Financial Supply Chain"
Talk by Eric Johnson, Dartmouth
April 30th 2008
Abstract: Firms face many different types of information security risk. Inadvertent disclosure of sensitive business information represents one of the largest classes of recent security breaches. We examine a specific instance of this problem – inadvertent disclosures through peer-to-peer file-sharing networks. We characterize the extent of the security risk for a group of large financial institutions using a direct analysis of leaked documents. We also characterize the threat of loss by examining search patterns in peer-to-peer networks. Our analysis demonstrates both a substantial threat and vulnerability for large financial firms. We find a statistically significant link between leakage and firm employment base.  Further, we address information governance, which is an underlying factor in inadvertent disclosure. We propose a governance structure based on controls and incentives, where employees’ self-interested behavior can result in firm-optimal use of information. Using a game-theoretic approach, we show that an incentives-based policy with escalation can control both overentitlement and underentitlement while maintaining the flexibility needed in dynamic business environments.

"A Model of Fair Process and Its Limits"
Talk by Ludo Van der Heyden, INSEAD
May 21st 2008
Fair process research has shown that people care not only about outcomes, but also about the process that produces these outcomes. For a decision process to be seen as fair, the people affected must have the opportunity to give input and possibly to influence the decision, and the decision process and rationale must be transparent and clear. Existing research has shown empirically that fair process enhances both employee motivation and performance in execution.

In this talk, we review the fair process literature and present a more operational definition of fair process, that is motivated both by the literature on fair process and that on decision making.  We present empirical evidence that supports this definition in hte framework of a study of innovation practices in 15 German manufacturing sites.  

We conclude with presenting an analytical model of fair process in a principal-agent (i.e., manager-employee) context, rooted in psychological preferences for autonomy and fairness. This model addresses the question as to why fair process is so often violated in practice. The associated paper breaks new ground by analytically examining the subtle trade-offs involved.
paper #1 paper#2

back to top