Session Detail Information
Add this session to your itinerary

Cluster :  Manufacturing & Service Operations Management/Service Operations

Session Information  : Sunday Nov 09, 16:30 - 18:00

Title:  Customer Behavior and Call Center Management
Chair: Philipp Afèche,Rotman School of Management; University of Toronto, 105 St.George Street, Toronto, Canada, Philipp.Afeche@Rotman.Utoronto.Ca

Abstract Details

Title: Service Time Sensitivity to Load: Who is to “Blame”?
 Presenting Author: Pnina Feldman,UC Berkeley, Haas School of Business, 2220 Piedmont Ave, Berkeley CA 94720, United States of America, feldman@haas.berkeley.edu
 Co-Author: Jun Li,Assistant Professor, Ross Business School, University of Michigan, 701 Tappan Street, Ann Arbor MI 48109, United States of America, junwli@umich.edu
 Galit Yom-Tov,Israel, gality@techunix.technion.ac.il
 
Abstract: The service operations literature typically assumes that firms control service times and that those are independent of the time customers spend waiting. Empirical evidence suggests otherwise. In fact, the time customers spend in line affects their expected service length. The reasons for that are many and involve agents and customers mechanisms for adaptations to load. Using call center data, we examine such correlations, and distinguish between customer and agent effects.
  
Title: Customer Learning in Call Centers
 Presenting Author: Seyed Emadi,Assistant Pofessor, Kenan-Flagler Business School, 300 Kenan Drive, Chapel Hill NC 27599, United States of America, Seyed_Emadi@kenan-flagler.unc.edu
 Co-Author: Baris Ata,Professor, Booth School of Business, 5807 South Woodlawn Avenue, Chicago IL 60637, United States of America, Baris.Ata@chicagobooth.edu
 Jay Swaminathan,Professor, Kenan-Flagler Business School, 300 Kenan Drive, Chapel Hill NC 27599, United States of America, Jay_Swaminathan@kenan-flagler.unc.edu
 
Abstract: We investigate the impact of customers' repeat contacts on their abandonment behavior. We use a Bayesian learning framework to model customers' behavior and estimate their parameters from a call center data.
  
Title: Optimal Staffing under Endogenous Arrivals with Heterogeneous Customer Time-of-Service Preferences
 Presenting Author: Yang Li,Doctoral Student, Rotman School of Management, University of Toronto, 105 St. George Street, Toronto ON M5S3E6, Canada, Yang.Li10@rotman.utoronto.ca
 Co-Author: Philipp Afèche,Rotman School of Management; University of Toronto, 105 St.George Street, Toronto, Canada, Philipp.Afeche@Rotman.Utoronto.Ca
 
Abstract: 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.
  
Title: Using Estimated Patience Levels to Optimally Schedule Customers
 Presenting Author: Ramandeep Randhawa,USC, Marshall School of Business, Los Angeles, United States of America, ramandeep.randhawa@marshall.usc.edu
 Co-Author: Achal Bassamboo,Northwestern University, 2001 Sheridan Rd., Evanston IL, United States of America, a-bassamboo@kellogg.northwestern.edu
 
Abstract: In M/M/N+G queueing systems, even though arriving customers appear identical, as they wait in the queue, an update can be formed on their willingness to wait. In this manner, as time progresses, customers become differentiated. We exploit this dimension of customer heterogeneity to construct scheduling policies that dynamically prioritize customers based on their time in the system in order to optimize any given system performance metric.