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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.edu

1 - 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.edu

1 - 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.edu

1 - 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