I2SDS Seminars: Fall 2010

Causes and Consequences of Understaffing in Retail Stores

Speaker: Vidya Mani, Kenan-Flagler Business School, University of North Carolina at Chapel Hill


In this paper we study the causes and consequences of understaffing in a retail store by examining the longitudinal data on store managers’ labor planning decisions and store performance from 41 stores of a large retail chain. By assuming store managers are profit maximizing agents, we impute the cost of labor used by store managers in making their labor planning decisions using a structural estimation technique. We show that store managers of this retail chain differ considerably in their imputed cost of labor and these costs are significantly higher compared to the average hourly wage rate for retail salespersons. This difference partially explains the understaffing observed in retail stores. Furthermore, we show that understaffing is predominantly present during peak hours but such understaffing is an optimal response by store managers due to scheduling constraints. We quantify the consequences of understaffing on store profitability by running counterfactual experiments. Finally, we show that understaffing is negatively associated with store performance measures like conversion rate and basket value.

Time: Friday, December 14th 11:15-12:15 pm

Location: Funger 320 (2201 G Street, NW)

Price-Quoting Strategies of a Tier-Two Supplier

Speaker: Bin Hu, University of Michigan


This paper studies the price-quoting strategies used by a tier-two supplier, whose tier-one customers compete for an OEM’s indivisible contract. At most one of the tier-two supplier’s quotes will ultimately result in downstream contracting and hence produce revenue for her. We characterize the tier-two supplier’s optimal price-quoting strategies and show that she will use one of two possible types of strategies, with her choice depending on the tier-one suppliers’ profit potentials: secure, whereby she will always have business; or risky, whereby she may not have business. Addressing potential fairness concerns, we also study price-quoting strategies in which all tier-one suppliers receive equal quotes. Finally, we show that a tier-two supplier’s optimal mechanism resembles auctioning a single quote among the tier-one suppliers. This paper can assist tier-two suppliers in their pricing decisions, and provides general insights into multi-tier supply chains’ pricing dynamics.

Time: Monday, December 13th 11:30-12:35 pm

Location: Funger 320 (2201 G Street, NW)

Managing Potentially Hazardous Substances from the Firm and NGO Perspective

Speaker: Tim Kraft, Stanford University


As public awareness of environmental hazards increases, a growing concern for corporations is the potential negative environmental impact of their products and the chemicals those products contain. When a substance within a product is identified as potentially hazardous (e.g., bisphenol-A (BPA) in baby bottles and triclosan in soaps and toothpastes), without regulations in place it is often difficult for a firm to financially justify the proactive replacement of the substance. From the perspective of non-governmental organizations (NGOs), groups such as ChemSec play an active role in removing potentially hazardous substances from commercial use by either targeting firms with negative press or by petitioning regulatory bodies to increase the likelihood of regulation. An NGO interested in influencing firms to replace a potentially hazardous substance must develop a strategy for how to best utilize its often limited resources. In this talk, I will present two papers that address these issues.

In the first part of the talk, we study the decisions of firms when a potentially hazardous substance is identified. A firm’s decisions are complicated by uncertainty in substance risk, regulations, and market sensitivity, as well as the existence of external stakeholders such as NGOs who may want the firm to develop a replacement substance. We investigate the timing and intensity of the firm’s investments to replace a substance. A two-stage dynamic program is used to model the problem. Our results indicate that large firms, in particular, must dedicate resources to monitoring and potentially planning the replacement of a substance. Although the additional management will be costly, it may prevent even larger losses such as inventory write-offs, profit losses, or liability costs. In the second part of the talk, we investigate the role NGOs play in removing a potentially hazardous substance from commercial use. We analyze the NGO’s decisions of who to target – the industry or the regulatory body – and how much effort to exert. In addition, we further investigate whether NGOs should take a pragmatic approach and partner with firms or maintain an antagonistic relationship. A game-theoretic, two-stage model is used to model the problem. Our results indicate that pressuring the regulatory body is most effective when the existing likelihood of regulation is low and the expected penalty for not being prepared for regulation is high.

Time: Wednesday, December 8th 11:15-12:20 pm

Location: Duques 651 (2201 G Street, NW)

On the Tradeoff Between Remanufacturing and Recycling

Speaker: Tharanga Rajapakshe, School of Management, The University of Texas at Dallas


For a firm, the dual goals – induced by the drive on Extended Producer Responsibility – of meeting environmental regulations and positioning itself as a socially-responsible entity, necessitate the understanding of supply- and demand-side implications as well as product design characteristics. These, in turn, result in a healthy tradeoff between feasible sustainability measures, thus making the implementation of an appropriate option critical for long-term survival. Motivated by our interactions with two Dallas-based reverse-logistics firms, we analyze the tradeoff between two well-known product- recovery approaches: recycling and remanufacturing. Our setting is that of a manufacturer who produces and markets a product with the objective of maximizing profit. A unit of the product consists of two modules – Module A and Module B – that could each be either remanufactured or recycled. Module B incurs a higher per-unit production cost and is also priced higher than Module A. Once a module is recovered via a take-back mechanism, it can be either used in a remanufactured unit or can be further disassembled and recycled to recover its raw material, which can then be used to produce (albeit with different yields) new units of either Module A or Module B. Any unused units of either the complete product, Module A, or Module B, can be disposed. Under this setting, we investigate three options: (i) recycling of Module A, (ii) remanufacturing of Module B, and (iii) recycling of Module A and remanufacturing of Module B.

We first provide a complete theoretical characterization of the regions of optimality of each option. Next, we study the impact of choosing an option in an ad-hoc manner on the manufacturer’s profit and analyze the sensitivity of this impact to changes in the supply-demand gap and the take-back fraction. Recognizing that emerging governmental regulations render the disposal cost particularly vulnerable to dis-economies of scale, we examine the impact of non-linear disposal cost on the (i) optimal amount recycled or remanufactured and (ii) choice of an optimal operational strategy. To obtain richer managerial insights, we introduce the concept of “ability of sustainability”, defined as a joint measure of the fraction of green consumers in the market, the take-back fraction, and product design characteristics such as the degree of substitutability of material, and examine its influence on the optimal option. Useful insights are developed on the sensitivity of the optimal choice to the relative profitabilities of the remanufacturing and recycling operations. Finally, based on the demand for the remanufactured product, we also analyze the cases when green consumers are flexible and when they are dedicated.

Time: Monday, December 6th 11:15-12:20 pm

Location: Duques 652 (2201 G Street, NW)

Anatomy of the Failure Rate Function: A Mathematical Dissection

Speaker: Nozer D. Singpurwalla, Professor of Statistics and of Decision Sciences, GWU


This is an expository talk. It is motivated by two recent developments. One, is a reviewer’s comments on my recent book; the other is a presentation by one of our speakers at the 75-th Annivarsary Meeting of the Department, who was flirting with the meaning of “risk”. The notion of the failure rate function is perhaps the main contribution of reliability, survival analysis, and acturial science to probability, with the exponentiation formula for survival being its main export. This formula is commonly used, its most recent client being mathematical finance. However, there are several caveats to the notion of the failure rate function, including a paradox that it spawns. These caveats make the exponentiation formula inexact and the paradox difficult to accept. In this talk, I will try to point out the caveats, introduce the notion of the product integral, and explain away the paradox via an animated example which includes some of my colleagues as characters in a mental game.

Time: Friday, December 3rd 3:00-4:00pm

Location: Duques 453 (2201 G Street, NW), followed by wine and cheese reception

A Unified Competing Risks Limited-Failure Model

Speaker: Sanjib Basu, Northern Illinois University


A competing risks framework refers to multiple risks acting on a system. This can result from multiple components or multiple failure modes and are often conceptualized as a series system. A limited-failure model postulates a fraction of the systems to be failure-free and can be formulated as a mixture model, or alternatively by a bounded cumulative intensity model. We develop models that unify the competing risks and limited-failure approaches. We describe Bayesian analysis of these models, and discuss conceptual, methodological and computational issues related to model fitting and model selection. We compare the performances of the two limited failure approaches and illustrate in application.

Location: Duques 360 (2201 G Street, NW)

Choice-Based Revenue Management

Speaker: Garrett Van Ryzin,Columbia University Graduate School of Business


Using consumer choice models as a basis for revenue management (RM) is appealing on many levels. Choice models can naturally model important buy-up and diversion phenomenon and can be applied to newer, undifferentiated low-fare structures and dynamic pricing problems. And recent research advances have now brought choice-based RM within striking distance of being truly practical. In this talk, we survey the recent research results in this area and discuss their implications for RM research and practice.

Time: Friday, October 22nd 2:30-3:30 pm

Location: Funger Hall 520 (2201 G Street, NW)

Bayesian Grouped Factor Models

Speaker: Merrill Liechty, LeBow College of Business, Drexel University


Firms that are publicly traded are classified based on their business models (i.e., how they make money) through industry classifications and based on their financial strength through debt ratings. As these classifications are based on the judgment of experts, it is an interesting question to determine the extent to which these classifications could be used to form prior distributions for correlation structures. Using a variable dimension Bayesian grouped factor model and standard classification schemes, we explore the value of these schemes with respect to model fit criteria, variance estimates of a tangency portfolio and value at risk calculations. In addition we demonstrate how this modeling framework can be used to include a firm which has just transitioned from being a privately held company to a publicly traded company with regards to asset allocation and risk assessment system.

Time: Friday, October 8th 3:30-4:30pm

Location: Duques 553 (2201 G Street, NW)

Obesity Index

Speaker: Roger M. Cooke, Resources for the Future and Delft University of Technology


Current notions of tail fatness or tail obesity rely on estimates of the density for extreme values. For example the index of regular variation requires that, after an initial segment, the distribution is approximately Pareto, and the mean excess function is approximately linear. Loss data we have studied are (a) very rich, (b) very fat tailed and (c) not remotely Pareto. This paper explores a measure of tail obesity for positive random variables which characterizes tail obesity in samples, and can be computed for familiar classes of distributions. If X1,…,X4 are independent samples of positive random variable X, define Obx(X) = P{X1 + X4> X2 + X3 | X1 > X2 > X3 > X4}, capturing the intuition, “the fatter the tail, the more the sum behaves like the max”. Properties of Obx will be described in the talk.

Time: Friday, October 1st, 2010, 3:30 pm – 4:30 pm (Followed by wine and cheese reception)

Location: Funger Hall 320 (2201 G Street, NW)

Learning Consumer Tastes through Dynamic Assortment

Speaker:Dorothee Honhon, University of Texas, Austin


How should a firm modify its product assortment over time when learning about consumer tastes? In this paper, we study assortment decisions on a horizontally differentiated product category where consumers’ tastes can be represented on a Hotelling line. We model this problem as a discrete time dynamic program; each period, the firm chooses an assortment to maximize total expected profits where the expectation is taken with respect to the firm’s subjective beliefs over consumer tastes. The consumers then choose a product from the assortment that maximizes their own utility and the firm observes sales, which provide censored information on consumer tastes, and updates beliefs using Bayes’ rule. The tradeoff is between the immediate profits from the sales and the informational gains. We show that it may be optimal for the firm to offer assortments that lead to losses in the current period in order to learn about consumer tastes. We also show that we can (partially) order assortments based on their information content and that the optimal assortment cannot be less informative than the myopically optimal assortment. This result is akin to the well-known ‘stock more’ result in newsvendor problems when the newsvendor is learning about demand through sales and lost sales are not observed. We also develop a Bayesian conjugate model that reduces the state space of the dynamic program and explore the properties of the value function and optimal policies.

Time: Wednesday, September 22nd, 2010, 11:00 am -12:15 pm

Location: Funger Hall 320 (2201 G Street, NW)