INFORMS Philadelphia – 2015
244
MD39
39-Room 100, CC
Innovative Strategies in the Interface of Operations
and Marketing
Cluster: Operations/Marketing Interface
Invited Session
Chair: Tingliang Huang, Assistant Professor, Boston College, Carroll
School of Management, 140 Commonwealth Avenue, Chestnut Hill,
MA, 02467, United States of America,
tingliang.huang@bc.edu1 - Dynamic Management of Opaque Selling with Boundedly Rational
Customers
Tingliang Huang, Assistant Professor, Boston College,
Carroll School of Management, 140 Commonwealth Avenue,
Chestnut Hill, MA, 02467, United States of America,
tingliang.huang@bc.edu,Zhe Yin
We study a practically important problem, where a firm sells an opaque product
to boundedly rational customers and has to dynamically determine its selling
strategies. We characterize the optimal selling policies depending on the market
environment.
2 - Optimal Staffing under Endogenous Arrivals with Heterogeneous
Customer Time-of-service Preferences
Yang Li, Rotman School of Management, University of Toronto,
105 St. George Street, Toronto, ON, M5S3E6, Canada,
Yang.Li10@Rotman.Utoronto.Ca, Philipp Afeche
The service operations literature usually treats arrivals as exogenous processes.
However, arrival processes may be endogenous in many settings. That is,
customers may account for system congestion in choosing their time of service.
We propose an equilibrium model that captures how rational customers with
heterogeneous preferences decide their time-of-service. We also study the optimal
staffing policies, taking into account customers’ time-of-service choices.
3 - Money-back Guarantees in a Distribution Channel: Bargaining
Power and Downstream Competition
Yufei Huang, PhD Student, University College London, Gower
Street, London, United Kingdom,
yufei.huang.10@ucl.ac.uk,Tingliang Huang, Ying-ju Chen
Although existing literature emphasizes the usefulness of Money-back
Guarantees (MBG), little is known about why retailers may adopt different MBG
choices in practice. To understand this, we examine two competing retailers’ MBG
decisions, who also simultaneously bargain for wholesale prices with a wholesaler
in a distribution channel. We show that, retailers’ asymmetric bargaining power
may lead to asymmetric MBG choices. We provide economic rationales for all
possible MBG outcomes.
4 - Effects of Channel Decentralization on Optimal Product Quality
under Uncertainty
Hongyan Shi, Assistant Professor, Nanyang Business School,
Nanyang Technological University, BLK S3-B1A-32, 50 Nanyang
Ave, Singapore, 639798, Singapore,
hyshi@ntu.edu.sg, Qin Geng,
Nicholas Petruzzi, Yan Liu
We provide insights on how a manufacturer’s optimal quality decision depends on
its channel structure when its market is defined by consumer heterogeneity and
market size uncertainty. We find that, in contrast to the quality-decreasing effect
of decentralization by consumer homogenization, market size uncertainty fuels an
opposing quality-increasing effect of decentralization. Moreover, we find that the
effect by market size uncertainty by and large prevails over that by consumer
homogenization.
MD40
40- Room 101, CC
Gender, Leadership, and Governance
Sponsor: Organization Science
Sponsored Session
Chair: Susan Perkins, Northwestern University, Evanston, IL,
s-perkins@kellogg.northwestern.edu1 - Can Female Leaders Mitigate the Negative Effects of Racial
Diversity? National Leaders and Structural Shifts
Susan Perkins, Northwestern University, Evanston, IL,
United States of America,
s-perkins@kellogg.northwestern.edu,Jaee Cho, Katherine W. Phillips, Negin R. Toosi
Using a multi-method research design we study the effects of inequality and
exclusion on productivity. We find that female leaders are expected improve
economic outcomes more than male leaders; are associated with greater tolerance
for diversity and self-expression, and have mitigating effects on diversity that
resulted in positive economic growth. The results imply that leadership in more
diverse environments is key to making positive structural shifts around inequality
and participation.
2 - Hierarchy Maintenance and Whites’ Decreased Support for
High-identity White Politicians
Sora Jun, Stanford University, Stanford, CA,
sorajun@stanford.edu,Lucia Guillory, Brian Lowery
We hypothesized and found that Whites withhold their political support for high
racial identity White candidates (Experiments 1-3) because of concerns that such
candidates will provoke minority discontent with the racial hierarchy
(Experiment 1). In Experiments 2 (hypothetical candidates) and 3 (real
politicians) this effect was eliminated when the social hierarchy was described as
stable, suggesting that this reduced support for high-identity candidates is a
hierarchy maintenance strategy.
3 - Naming Your Daughter Jack: The Effect of Gender in the
Evaluation Process
Tristan L. Botelho, Massachusetts Institute of Technology,
Cambridge, MA,
tbotelho@mit.edu, Mabel Abraham
Double standards, or the belief that women are held to unfairly higher standards,
is commonly invoked as an explanation for observed gender differences in
evaluative outcomes. Despite lab-based evidence supporting this argument, it
remains unclear whether double standards affect evaluations in organizational
and market contexts, where competitive pressures create a disincentive to
discriminate. Thus, we lack a complete understanding of when and how double
standards penalize women in the evaluation process. Drawing on broader status
theory, we identify the conditions under which this status-based source of
discrimination is most prevalent. Using data from a financial market setting,
comprised of investment professionals, we find that double-standards
disadvantaging women are most likely when evaluators are faced with higher
levels of uncertainty stemming from search costs and variation in the availability
of pertinent information. We also rule out that systematic gender differences in
the behavior, or characteristics, of these investment professionals are driving these
results.
4 - Leadership and the Single Woman Penalty: A Role Expectations
Account of Promotion Penalties toward Female Professionals
Damon Phillips, Columbia University, New York, NY,
dp2588@columbia.edu,Jennifer Merluzzi
We advance scholarship on workplace gender inequality by drawing attention to
professional single women. We contend that single non-mother status is
inconsistent with the role expectations of leadership associated with both men
(agentic) and women (communal). We test our thesis on the early careers of
business professionals using a multi-method approach. The result support a
discrimination-based penalty where the status and role of professional single
womanhood conflicts with that of leadership.
MD41
41-Room 102A, CC
High-dimensional Data Models for
Cost-effective Healthcare
Sponsor: Manufacturing & Service Oper
Mgmt/Healthcare Operations
Sponsored Session
Chair: Mohsen Bayati, Assistant Professor, Stanford Graduate School of
Business, 655 Knight Way, Stanford, CA, United States of America,
bayati@stanford.edu1 - Accurate Emergency Department Wait Time Prediction
Sara Kwasnick, Stanford Graduate School of Business,
655 Knight Way, Stanford, CA, United States of America,
kwasnick@stanford.edu,Mohsen Bayati, Erica Plambeck
We develop a new method for predicting Emergency Department wait times. The
method combines fluid model estimators and statistical learning, and is much
more accurate than existing approaches to ED wait time prediction. We validate
the method on historical and post-implementation data from four hospitals and
discuss lessons learned from the implementation.
2 - Online Decision-making with High-dimensional Covariates
Hamsa Bastani, Graduate Student, Stanford University,
Stanford, CA, United States of America,
hsridhar@stanford.edu,
Mohsen Bayati
Big data has enabled decision-makers to tailor choices at the individual-level.
However, this involves learning a model of decision rewards conditional on
individual-specific covariates, which are often high-dimensional. We present an
efficient method to solve this problem in an online setting and a corresponding
regret analysis. Unlike previous methods whose regret scales with the cube of the
covariate’s dimension, our method’s regret scales linearly with the number of
sparse features.
MD39