Events

The Supply Chain and Operations Department & Juran Research Center Seminar Series showcases current research in Management and Operations Science, including topics in operations strategy, technology, quality, new product development, and supply chain management. Speakers are drawn from universities around the world.

2018 - 2019

Fall

Dennis Cook
University of Minnesota, School of Statistics

Date: Friday, September 28, 2018

Time: 10:00-11:30 a.m.

Location: CSOM 1-132

Title: Partial Least Squares Regression

Abstract: Partial least squares regression, which has been around for about four decades, is a dimension-reduction algorithm for fitting  linear regression models without requiring that the sample size be larger than the number of predictors.  It was developed primarily by the Chemometrics community where it is now ingrained as a core method, and it is apparently used throughout the applied sciences.

And yet it seems fair to conclude that PLS regression has not been embraced by some communities, even as a serviceable method that might be useful occasionally. Nor does there seem to be a common understanding as to why this rather enigmatic method should not be used, although bumptious discussions of PLS failings can be found in some applied areas.  Perhaps this is as it should be — perhaps not.

This talk is intended as a relatively informal overview on PLS regression, including historical context, personal encounters, methodology, relationship to envelopes and, near the end, a few recent asymptotic results for high-dimensional regressions.


Tim Kraft 
Massachusetts Institute of Technology

Date: Friday, October 5, 2018

Time: 10:00-11:30 a.m.

Location: CSOM 2-233

Title: Supply Chain Transparency and Social Responsibility 

Abstract: Consumers increasingly expect companies to ensure that their products are made in a socially responsible manner. However, most companies do not have extensive visibility into their supply chains. According to a recent study, 81% of the 1,700 companies surveyed lacked full visibility into the social responsibility (SR) practices of their suppliers. In this talk, I will first overview our work on how improved supply chain visibility into suppliers’ SR practices can impact companies’ interactions with both consumers and suppliers. I will then discuss a specific study (below) that examines the effect of visibility on consumers’ trust of companies’ SR disclosures.

According to a 2015 Nielsen survey, brand trust tops the list of factors that influence socially responsible purchases. At the same time, supply chain transparency has been identified as one of the most effective ways for companies to improve consumers’ trust of SR disclosures. The current literature focuses on the effect that disclosing information has on consumer trust, generally assuming that companies have complete information (i.e., full supply chain visibility) about the SR practices occurring in their supply chains (e.g., working conditions). In this study, we design an incentivized human-subject experiment to examine whether and how visibility impacts consumers’ trust in companies’ SR communications. Our results show that by investing to improve visibility into the SR practices in its supply chain, a company can increase consumer trust in its SR communications. This increased trust can in turn help the company to increase its sales when a good SR claim is made. This is particularly true among consumers with prosocial orientations; i.e., a willingness to sacrifice their own benefit to help others. 

This talk is based on joint work with Leόn Valdés (University of Pittsburgh) and Karen Zheng (MIT).

Gopesh Anand 
llinois, Gies College of Business

Date: Friday, September 28, 2018

Time: 10:00-11:30 a.m.

Location: CSOM 2-233

Title: TBD

Abstract: TBD

Ruomeng Cui
Emory University, Goizueta Business School

Date: Friday, November 16, 2018

Time: 10:00-11:30 a.m.

Location: CSOM 2-233

Title: TBD

Abstract: TBD

Basak Kalkanci
Georgia Institute of Technology, Scheller College of Business

Date: Friday, November 30, 2018

Time: 10:00-11:30 a.m.

Location: CSOM 2-233

Title: TBD

Abstract: TBD

Spring

Ariel Stern
Harvard University 

Date: Friday, April 19, 2019

Time: 10:00-11:30 a.m.

Location: TBD

Title: TBD

Abstract: TBD

Chris Tang
University of California, Los Angeles 

Date: Friday, May 17, 2019

Time: 10:00-11:30 a.m.

Location: TBD

Title: TBD

Abstract: TBD

The Supply Chain and Operations Department & Juran Research Center Seminar Series showcases current research in Management and Operations Science, including topics in operations strategy, technology, quality, new product development, and supply chain management. Speakers are drawn from universities around the world.

2017 - 2018

Fall

Susan Lu
Purdue, Krannert School of Management

Date: Friday, October 6, 2017

Time: 10:00-11:30 a.m.

Location: CSOM 1-132

Title: Do Mandatory Overtime Law Imporve Quality? Staffing Decisions and Operational Flexibility of Nursing Homes

Abstract: TBD

 

Soo-Haeng Cho
Carnegie Mellon University, Tepper School of Business

Date: Friday, October 27, 2017

Time: 10:00-11:30 a.m.

Location: CSOM 1-135

Title: The Theory of Crowdsourcing Contests

Abstract: 

     This talk will present papers that concern the theory of innovation tournaments (also called crowdsourcing contests or open innovation). In an innovation tournament, an organizer solicits innovative ideas from a number of independent agents. Agents exert efforts to develop their solutions, but their outcomes are unknown due to technical uncertainty and/or subjective evaluation criteria. We call an agent whose ex-post solution contributes to the organizer's utility a “contributor.”

     The first paper, entitled “Optimal Award Scheme in Innovation Tournaments,” examines optimal award scheme/rule in innovation tournaments. While extant literature either assumes a winner-take-all scheme a priori or shows its optimality under specific distributions for uncertainty, this paper derives necessary and sufficient conditions under which the winner-take-all scheme is optimal. These conditions are violated when agents perceive it very likely that only few agents receive high evaluation or when a tournament does not require substantial increase in agents' marginal cost of effort to develop high-quality solutions. Yet, the winner-take-all scheme is optimal in many practical situations, especially when agents have symmetric beliefs about their evaluation. In this case, the organizer should offer a larger winner prize when he is interested in obtaining a higher number of good solutions, but interestingly the organizer need not necessarily raise the winner prize when anticipating more participants to a tournament.

     The second paper, entitled “Innovation Tournaments with Multiple Contributors,” analyzes a general model of uncertainty and utility functions with multiple contributors, and shows that these factors play a crucial role in decision-making of agents and the organizer. Specifically, contrary to existing theories, increased competition to a tournament can have a positive impact on agents' incentives to exert effort when agents expect good outcomes with high likelihood, and a free-entry open tournament should be encouraged only when the problem is highly uncertain or the organizer seeks diverse solutions from many contributors. Our results are consistent with recent empirical evidence, hence helping close a gap in the extant literature between theory and practice.

 

Spring

John Birge
The University of Chicago, Booth School of Business

Date: Friday, March 30

Time: 10:00-11:30 a.m.

Location: CSOM 2-224

Title: Dynamic Learning in Strategic Pricing Games

Abstract:

In monopoly pricing situations, firms should optimally vary prices to learn demand. The variation must be sufficiently high to ensure complete learning.  In competitive situations, however, varying prices provides information to competitors and may reduce the value of learning. Such situations may arise in the pricing of new products such as pharmaceuticals. This talk will discuss how this effect can be strong enough to stop learning so that firms optimally reduce any variation in prices and choose not to learn demand. The result can be that the selling firms achieve a collaborative outcome instead of a competitive equilibrium. The result has implications for policies that restrict price changes or require disclosures. 

 

Karen Zheng
MIT, Sloan

Date: Friday, April 27

Time: 10:00-11:30 a.m.

Location: CSOM 2-213

Title: Economically Motivated Adulteration in Farming Supply Chains: Data and Models

Abstract: 

Food adulteration is a serious threat to public health. Many incidents of food adulteration are motivated by economic gains, defined as economically motivated adulteration (EMA). In this talk, I will present recent works that examine drivers of EMA risks in farming supply chains. We first present a multi-industry empirical study that demonstrates supply chain dispersion and local governance being two important risk drivers. To do so, we collect farming supply chain data, food sampling data, and socioeconomic data across five different industries (aquatic products, eggs, honey, pork, and poultry) in China. We define supply chain dispersion as the degree to which farming outputs are sourced from a dispersed network of farms -- and develop a method to quantify dispersion in farming supply chains based on field data. We also develop multi-faceted measures to objectively quantify the strength of city-level governance in China based on factual (as opposed to perception) data. Our results show that products made in a more dispersed supply chain and in regions with weaker governance are associated with higher EMA risks. Inspired by the empirical findings, we develop a set of supply network models to structurally analyze farms’ strategic adulteration behavior and the resulting EMA risks in farming supply chains. We examine both preemptive EMA, where farms engage in adulteration to reduce the likelihood of producing low-quality units, and reactive EMA, where farms adulterate low-quality units to increase the perceived quality of their outputs. We fully characterize the farms’ equilibrium adulteration behavior in both types of EMA and examine how quality uncertainty, supply chain dispersion, traceability, and testing sensitivity (in detecting adulteration) jointly impact EMA risks. We validate our models’ predictions with numerical analyses calibrated by field data. We conclude by offering tangible insights regarding how business entities and regulators can more proactively prevent and address EMA risks in farming supply chains.