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INFORMS Philadelphia – 2015

274

4 - Improving Food Bank Gleaning Operations: An Application in

New York State

Erkut Sonmez, Assistant Professor, Boston College, 140

Commonwealth Ave, Fulton Hall, Chestnut Hill, 02446,

United States of America,

erkut.sonmez@bc.edu,

Miguel Gomez,

Deishin Lee, Xiaoli Fan

We develop a stochastic optimization model to help food banks to improve their

gleaning operations. Gleaning refers to collecting food from what is left in the

fields after harvest, and donating the goods to food banks or pantries that service

food insecure individuals.

TA48

48-Room 105A, CC

Managing Contracts and Financial Flow in

Supply Chain

Sponsor: Manufacturing & Service Oper Mgmt/iFORM

Sponsored Session

Chair: Lingxiu Dong, Associate Professor, Washington

University in St. Louis, One Brookings Drive, St. Louis, MO, 63132,

United States of America,

dong@wustl.edu

1 - Buyer Intermediation in Supplier Finance

Tunay Tunca,

ttunca@rhsmith.umd.edu

, Weiming Zhu

We analyze the role and the efficiency of buyer intermediation in supplier

financing (BIF). We theoretically demonstrate that BIF can significantly improve

the supply chain surplus over traditional financing. Using data from a large

Chinese online retailer, we estimate model parameters, empirically verify the

theory, and predict efficiency gains.

2 - Financial Pooling in Supply Chains

S. Alex Yang, Assistant Professor, London Business School, Sussex

Place, London, United Kingdom,

sayang@london.edu

, Qu Qian,

Ming Hu

Trade credit pools liquidity between suppliers and retailers. Due to this pooling

effect, even if the supplier’s cost of capital is higher, the retailer may still demand

for trade credit. Supply chain finance increases the efficiency of this pooling

effect, and hence reduces the overall chain financing cost.

3 - Trade Credit and Supplier Competition

Jiri Chod, Boston College, Carroll School of Management,

Chestnut Hill, MA,

jiri.chod@bc.edu,

S. Alex Yang,

Evgeny Lyandres

We study the effect of competition among suppliers on their willingness to

provide trade credit. Providing trade credit to a financially constrained buyer

allows this buyer to reallocate his cash budget to purchasing from competing

suppliers. Thus, relaxing the buyer’s financial constraint may backfire at the

supplier who provides financing. This is a possible explanation of the empirical

regularity that firms selling differentiated products tend to offer more trade credit.

4 - Push, Pull, and Delayed Payment Contracts when a Manufacturer

Expands His Product Line

Xiaomeng Guo, PhD Candidate, Olin Business School,

Washington University in St. Louis, Campus Box 1156, One

Brookings Drive, St. Louis, MO, 63130, United States of America,

xiaomeng.guo@wustl.edu

, Lingxiu Dong, Danko Turcic

A manufacturer’s ability to sell a new product often depends on a retailer’s

willingness to stock the product. We construct a game-theoretic model of a supply

chain with stochastic, price-sensitive demand and consider three basic wholesale

price contracts: push, pull and delayed payment contracts. We show how a

manufacturer can influence the retailer’s incentive to carry a second product by

choosing a “correct” contract type and clarify which contract should be expected

in equilibrium.

TA49

49-Room 105B, CC

Uncertainty in Sourcing and Procurement

Sponsor: Manufacturing & Service Oper Mgmt/Supply Chain

Sponsored Session

Chair: Zohar Strinka, PhD Candidate, University of Michigan,

1205 Beal Ave., Ann Arbor, MI, 48109, United States of America,

zstrinka@umich.edu

1 - Supplier Diversification under Random Yield and Price

Dependent Demand

Guang Xiao, Olin Business School, Washington University in St.

Louis, St. Louis, United States of America,

xiaoguang@wustl.edu

,

Lingxiu Dong, Nan Yang

We consider a firm’s supply diversification problem under supply random yield

and price sensitive demand. We study two pricing schemes: responsive pricing

and ex ante pricing. We characterize the sourcing decisions under each pricing

scheme and compare them to study the strategic relation between diversification

and responsive pricing.

2 - Risk Pooling under Price and Demand Uncertainty

Refik Gullu, Professor, Bogazici University, Industrial Engineering

Dept., Bebek, Istanbul, 34342, Turkey,

refik.gullu@boun.edu.tr

,

Nesim K. Erkip

We consider purchasing and distribution decisions for a commodity whose price is

random and correlated with its demand. A model, where the purchasing decisions

of locations are pooled is proposed. We obtain the optimal purchase quantity,

time and quantity of allocation, and quantify the benefits of pooling price risk.

3 - Bunching Supply Contracts with Information Asymmetry in a

Two-echelon Supply Chain

Zahra Mobini, Erasmus University Rotterdam, Rotterdam,

Netherlands,

mobinidehkordi@ese.eur.nl,

Albert Wagelmans,

Wilco Van Den Heuvel

In a two-echelon supply chain consisting of a supplier and a retailer where the

latter has private information about his cost parameter, we analyze the design of

the supplier’s optimal menu of contracts. Instead of offering a separating menu,

the supplier offers a menu of bunching contracts where each contract is intended

to appeal to more than one retailer type. We investigate the effects of offering

such a menu on the supplier’s profit.

4 - Overstock Goods Auctions

Zohar Strinka, PhD Candidate, University of Michigan,

1205 Beal Ave., Ann Arbor, MI, 48109, United States of America,

zstrinka@umich.edu

, H. Edwin Romeijn

Manufacturers sometimes find themselves with a considerable quantity of

overstock goods. In these cases, some turn to online liquidation auctions to sell

excess inventory. We propose implementing US Treasury-style auctions in this

setting which allow bidders to specify pairs of bid price and a desired quantity at

that price. We consider bidders who are themselves retailers and face

newsvendor-type costs based on the number of units won and uncertain demand.

TA50

50-Room 106A, CC

Operations Management and Marketing Interface

Sponsor: Manufacturing & Service Operations Management

Sponsored Session

Chair: Ozge Sahin, Johns Hopkins University,

ozge.sahin@jhu.edu

Co-Chair: Yao Cui, Cornell University, 401N Sage Hall, Ithaca, United

States of America,

yao.cui@cornell.edu

1 - Econometric Models of Pairwise Externalities and Social

Attractiveness for the Music Industry

Stefano Nasini, Post-doctoral Researcher, IESE Business School,

3-7, Arnus i Gari, Barcelona, Spain,

snasini@iese.edu,

Victor Martínez-de-Albéniz

We developed an econometric model of social attractiveness that integrates time

variation of individual decisions with the structural information concerning their

spillovers. The exponential family of distributions is used to jointly deal with the

dynamic and structural aspect of such a complex statistical setting. It resulted in a

well-suited model for the analysis of artist goods. An application to a large data

set of song diffusion on the radio is presented.

2 - Inventory Management for Luxury Goods

Ruslan Momot, INSEAD, Boulevard de Constance,

Fontainebleau, 77305, France,

ruslan.momot@insead.edu,

Elena Belavina, Karan Girotra

Firms selling conspicuous goods face a trade-off: producing more allows for

extracting more revenues but compromises the product’s reputation for

exclusivity. We capture this trade-off in a dynamic model of strategic customer

and firm behavior that includes limited memory. Firms should follow stationary

cyclic strategies alternating scarcity and overproduction. The former builds a

reputation whereas the latter exploits it. The longer the customer memory,

shorter is the overproduction phase.

3 - A Newsvendor Model with Product Bundling

Qingning Cao, University of Science and Technology of China, 96

Jinzhai Rd, SM 611, Hefei, China,

caoq@ustc.edu.cn

, Jun Zhang,

Kathy Stecke, Xianjun Geng

This paper studies a firm’s optimal ordering decision of a primary product when

the firm can bundle this product with another product. The firm makes an

ordering decision before demand uncertainty resolves, and then retails this

primary product either alone or in a mixed bundle with a secondary product. Our

results suggest that as compared to a no-bundling benchmark, the firm should

overstock (understock) when the wholesale price is high (low).

TA48