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INFORMS Philadelphia – 2015

110

2 - Win-win Capacity Reservation Contracts in Co-manufacturing and

Co-distribution Alliances

Guillaume Roels, Associate Professor, UCLA, 110 Westwood

Plaza, Los Angeles, CA, 90095, United States of America,

guillaume.roels@anderson.ucla.edu,

Chris Tang

In some strategic alliances, a firm shares its manufacturing capacity with another,

and the latter shares its distribution capacity with the former. Even though such

bidirectional alliances have become common, they remain challenging to manage

due to the frequent disputes over capacity allocation when demand is uncertain.

In this talk, we investigate whether there exists a contractual mechanism that can

mitigate the extent of these disputes while improving the profits of all

participating firms.

3 - Optimal Allocation Rules with Waste Considerations

Sara Rezaee Vessal, HEC Paris, 1 Rue de la Liberation, Jouy en

Josas, 78350, France,

sara.rezaee-vessal@hec.edu,

Sam Aflaki,

Dimitrios Andritsos

We study capacity allocation of a scarce and perishable product among stock-out-

averse retailers that face stochastic demand. We focus on two commonly practiced

allocation mechanisms and—-using a dynamic model—-characterize the

conditions under which each allocation mechanism performs superior from a

waste and profit point of view.

4 - Using Transparency to Manage the Sourcing of Complex Non-

routinized Services

Jacob Chestnut, PhD Candidate, Ross School of Business,

University of Michigan, 701 Tappan Avenue, Ann Arbor, MI,

48109, United States of America,

jacobpc@umich.edu

,

Damian Beil

Complex services such as non-routine litigation are often billed on an hourly

basis, creating opportunities for the service provider (e.g., outside counsel) to

drive up costs for the buyer (e.g., in-house counsel) through the inefficient use of

time and resources (e.g., partner versus associate level work). The buyer can

manage these costs with greater front-end transparency, about the work to be

performed; however this transparency comes at a cost. We study this tradeoff.

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51-Room 106B, CC

MSOM Student Paper Competition Finalists - I

Sponsor: Manufacturing & Service Operations Management

Sponsored Session

Chair: Goker Aydin, Indiana University, 1309 East Tenth Street,

Bloomington, IN, 47405, United States of America,

ayding@indiana.edu

Co-Chair: Karan Girotra, Associate Professor, INSEAD, Boulevard de

Constance, Fontainebleau, 77300, France,

Karan.GIROTRA@insead.edu

Co-Chair: Sameer Hasija, Assistant Professor, INSEAD, 1 Ayer Rajah

Avenue, Grange Heights, Singapore, Singapore,

Sameer.Hasija@insead.edu

1 - MSOM Student Paper Competition Finalists Sessions

INFORMS 2015

The MSOM Student Paper Competition is awarded annually by

the Manufacturing & Service Operations Management Society at

the INFORMS Annual Meeting for papers judged to be the best in

the field of operations management.

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52-Room 107A, CC

Social Network Analysis

Sponsor: Service Science

Sponsored Session

Chair: Dr. Joanna F. Defranco, Assistant Professor Of Software

Engineering, The Pennsylvania State University, 30 East Swedesford

Road, Malvern, PA, United States of America,

jfd104@psu.edu

1 - Social Network Dynamics in Software Development Teams

Adrian Barb, The Pennsylvania State University,

asb16@psu.edu,

Dr. Joanna F. Defranco

We present a social network analysis of the communication of 112 developers in

seven software development teams distributed around the world. The project was

conducted between October 2005 and October 2006 and includes

communications among team members with different roles varying from architect

to integrator over six development iterations. A social network analysis was

performed to evaluate the progression of communication over this period during

a collaborative software development project.

2 - Exploring Networks of Faculty Paper Co-authorship

Regina Collins, New Jersey Institute of Technology,

regina.s.collins@njit.edu,

Nancy Steffen-fluhr

This research, funded by an NSF Advance grant, examined the hypothesis that

women STEM faculty suffer low retention rates due to their relative isolation

within the social and informational networks of their organizations. To test this, a

network based on co-authorship of scholarly papers was created and analyzed

from a social network perspective, examining network attributes including female

faculty’s centrality in these networks.

3 - Reconciling Infinite Choice and Zero Effort: Applying Data

Science to Rejuvenate the TV Experience

Venu Vasudevan, Senior Director, Arris,

Venu.Vasudevan@arris.com

TV’s long reign has been driven by its ability to be both simple and entertaining.

Yet the proliferation of web technologies has ushered a ‘viewers choice’ era -

where viewers seek more control over the TV experience (when/where/for how

long/). This talk is about the use of data science to address TV’s next challenge -

that of finding the right balance of simplicity and richness (both from viewer and

advertiser point of view).

4 - Social Discovery Builds the Social Network

Richard Friedman, Cto Meetme, MeetMe, 518 Kings Dr,

Cherry Hill, NJ, 08003, United States of America,

richfriedman@gmail.com

Social Networking is the broadest of terms representing any online service that

facilitates some form of communication between a network of friends, colleagues,

and personal contacts. Social Discovery, on the other hand, can be defined as the

creation of the social network. It is the discovery of people through content and

conversation that leads to building a network related to a topic or a purpose. We

will cover from discovery, interest, conversation, connection, network, and

platform.

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53-Room 107B, CC

Bounded Rationality, Social Preferences, and Risk

Management in Behavioral Operations

Sponsor: Behavioral Operations Management

Sponsored Session

Chair: Kay-Yut Chen, Professor, University of Texas Arlington, 701

West Street, Arlington, United States of America,

kychen@uta.edu

1 - The Behavioral Traps of Making Multiple, Simultaneous,

Newsvendor Decisions: An Experimental Study

Shan Li, Assistant Professor, Zicklin School of Business, Baruch

College, City University of New York, 55 Lexington Ave,

New York, NY 10010, United States of America,

Shan.Li@baruch.cuny.edu

, Kay-Yut Chen

We conducted an experimental study to compare behaviors of newsvendors who

manage one versus two independent stores. We find that ordering decisions are

closer to optimal quantities in one-store treatment. More interestingly, we

discover a significant correlation between order quantities of individuals only in

the two-store setting. We propose the concept of decision segmentation

reinforcement and develop a behavior model to capture multiple interacting

simultaneous decisions.

2 - Process-driven Discussion in Team-based Decision Making for

Operational Risk Management

Karen Zheng, MIT, 77 Massachusetts Avenue, Cambridge, MA,

02139, United States of America,

yanchong@mit.edu,

Retsef Levi,

Shujing Wang

We experimentally study how different group discussion processes affect the

outcome of team-based decision making in a risk management context. Members

in each team in the experiment are provided private information about the status

of the risk. The team will make the optimal decision only if all private information

is shared. We manipulate the structure of discussion among team members to

study how it affects information sharing within the team.

3 - Pay-it-forward: Theory, Experiments, and Managerial Implications

Narayanan Janakiraman, Asst Professor, University of Texas at

Arlington, 701 S. West Street, Arlington, 76019, United States of

America,

janakira@uta.edu,

Zhiyong Yang, Kay-Yut Chen

We study the pay-it-forward (PIF) phenomenon, where a person who received a

stranger’s kindness would act similarly kind to a future stranger. Using lab

experiments, we find that the recipient’s PIF likelihood depends on firms’ pricing

strategies, expectation of further PIF from the receiver, and social distances

between the giver and the receiver. We explain the findings in a behavioral

model, and develop a price optimization framework to enhance firms’ profitability

in this context.

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