CV - Job Market Paper  
 

Tekin, Muge

Job market candidate

Contact information

Tel. +34 93 542 1766

muge.tekin@upf.edu

 

 

 

Research interests

Operations Management, Business Analytics, Pricing and Revenue Management.

Placement officer

Filippo Ippolito
filippo.ippolito@upf.edu
 

References

Kalyan Talluri (Advisor)
kalyan.talluri@imperial.ac.uk

Suleyman Ozekici
sozekici@ku.edu.tr

Savas Dayanik
sdayanik@bilkent.edu.tr

 

Research

"Competitive Intelligence Based on Marginal Information" with K. Talluri (Job Market Paper)
Estimating a demand system and forecasting is central to revenue management and optimal pricing in many industries.  Recent research efforts have focused on estimating behavioral choice models based on transactional data, noting especially the complication of not being able to observe no-purchases in most commercial situations.  In this paper we address two important unaddressed and difficult issues in this stream of research: (1) estimating with competitor effects (2) estimating when the firm sells a single product.  The former is impossible without knowing competitors' observed demands, something that is rarely if ever available to a firm and what has stymied research into this.  Nevertheless we note that in many industries firms have access to marginal competitor information, such as the STR report in the hotel industry.  With access to such data, we show that the two problems we mentioned can in fact be solved together---marginal information can be used estimate competitor location attractiveness in a dynamic pricing scenario where each firm sells a single product.  A noteworthy complication in the real-world is that even competitors' initial capacity is uncertain because of private group sales, and we address this using IV estimation.  As far as we know no one has proposed anything to solve these problems for us to compare our results with, so we modify algorithms from two tangentially related areas, network tomography and the BLP algorithm from econometrics for comparison.  We present numerical performance on both synthetic data as well as on real hotel bookings data from two cities in the US and UK.

 

Research in Progress

“Competitive Intelligence from Public Data: Application to Facility Location” with K. Talluri.

“How Representative are Review Ratings of the Customer Behaviour?” with K. Talluri.

 

Publications

Tekin M. and Ozekici S. "Mean-Variance Newsvendor Model with Random Supply and Financial Hedging", IISE Transactions 47, 1-19, 2015.

Link:http://dx.doi.org/10.1080/0740817X.2014.981322