BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//talks.cam.ac.uk//v3//EN
BEGIN:VTIMEZONE
TZID:Europe/London
BEGIN:DAYLIGHT
TZOFFSETFROM:+0000
TZOFFSETTO:+0100
TZNAME:BST
DTSTART:19700329T010000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=-1SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0100
TZOFFSETTO:+0000
TZNAME:GMT
DTSTART:19701025T020000
RRULE:FREQ=YEARLY;BYMONTH=10;BYDAY=-1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
CATEGORIES:Operations Group Seminar Series
SUMMARY:Behavioral Drivers of Routing Decisions: Evidence 
 from Restaurant Table Assignment - Professor Bradl
 ey Staats\,  Associate Professor of Operations\, K
 enan-Flagler Business School\, University of North
  Carolina
DTSTART;TZID=Europe/London:20160316T090000
DTEND;TZID=Europe/London:20160316T103000
UID:TALK65098AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/65098
DESCRIPTION:Determining how best to route work is a key elemen
 t of service system design. Not surprisingly then\
 , many analytical models have identified various o
 ptimal routing algorithms for service operations m
 anagement. However\, in many settings\, humans mak
 e routing decisions dynamically\, either because a
 lgorithms don’t exist\, decision support tools hav
 e not been implemented\, or existing rules are not
  enforced. Understanding how individuals make deci
 sions creates the opportunity to identify both pos
 itive deviances\, as well as suboptimal decision m
 aking that can be improved. Therefore\, in this pa
 per we first theoretically identify the factors th
 at may impact decision making before empirically e
 xamining a large operational data set in a casual 
 restaurant setting to research whether and how hos
 ts deviate from their predefined round-robin rule 
 to seat customers to servers. We find that hosts a
 ssign customers earlier than what the round-robin 
 rule suggests to those servers who have low worklo
 ad\, high speed skills but low sales skills\, and 
 high familiarity with the hosts. In addition our m
 odels reveal that these seating heuristics are sub
 optimal in our setting and so we suggest an altern
 ative seating heuristic to prioritize servers havi
 ng high sales ability and estimate a potential sal
 es lift between 2% and 3% through counterfactual a
 nalyses. Our research contributes both theoretical
 ly and practically as we use empirical methods to 
 show not only how individuals make routing decisio
 ns\, but also how these decisions can be improved
LOCATION:Cambidge Judge Business School\,  Castle Teaching 
 Room
CONTACT:Crystal
END:VEVENT
END:VCALENDAR