Abstract
meet demand when it occurs. Consumer and recovery vehicle locations are variable, and the vehicle recovery service
is contracted out in the service supply chain. This research aims to identify how different variables/factors influence
backlogs during busy periods and service performance. A case study of a vehicle recovery company was undertaken
using observation and analysis of historical data to map the process. Discrete event simulation (DES) was used to
model several processes to evaluate the operational impact of changes. We find that ensuring complete and accurate
information transmission over the chain supports the TOD service by enhancing the ‘allocation’ activity of the
dispatch center staff; i.e., pairing vehicles to consumer requirements. Simple changes to how information is collected,
shared, and used in the service supply chain can significantly reduce the percentage of jobs taking more than a given
time
| Original language | English |
|---|---|
| Pages (from-to) | 121-138 |
| Number of pages | 18 |
| Journal | International Journal of Operations Research |
| Volume | 14 |
| Issue number | 3 |
| Publication status | Published - 2017 |
| Externally published | Yes |
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Transport on-demand in a service supply chain experiencing seasonal demand: Managing persistent backlogs. / Duong, Linh N.K.; Wood, Lincoln C.; Wang, Jason X.; Wang, William Y. C.
In: International Journal of Operations Research, Vol. 14, No. 3, 2017, p. 121-138.Research output: Contribution to journal › Article
TY - JOUR
T1 - Transport on-demand in a service supply chain experiencing seasonal demand:
T2 - Managing persistent backlogs
AU - Duong, Linh N.K.
AU - Wood, Lincoln C.
AU - Wang, Jason X.
AU - Wang, William Y. C.
PY - 2017
Y1 - 2017
N2 - Successful transport-on-demand (TOD) requires having sufficient capacity in the right location tomeet demand when it occurs. Consumer and recovery vehicle locations are variable, and the vehicle recovery serviceis contracted out in the service supply chain. This research aims to identify how different variables/factors influencebacklogs during busy periods and service performance. A case study of a vehicle recovery company was undertakenusing observation and analysis of historical data to map the process. Discrete event simulation (DES) was used tomodel several processes to evaluate the operational impact of changes. We find that ensuring complete and accurateinformation transmission over the chain supports the TOD service by enhancing the ‘allocation’ activity of thedispatch center staff; i.e., pairing vehicles to consumer requirements. Simple changes to how information is collected,shared, and used in the service supply chain can significantly reduce the percentage of jobs taking more than a giventime
AB - Successful transport-on-demand (TOD) requires having sufficient capacity in the right location tomeet demand when it occurs. Consumer and recovery vehicle locations are variable, and the vehicle recovery serviceis contracted out in the service supply chain. This research aims to identify how different variables/factors influencebacklogs during busy periods and service performance. A case study of a vehicle recovery company was undertakenusing observation and analysis of historical data to map the process. Discrete event simulation (DES) was used tomodel several processes to evaluate the operational impact of changes. We find that ensuring complete and accurateinformation transmission over the chain supports the TOD service by enhancing the ‘allocation’ activity of thedispatch center staff; i.e., pairing vehicles to consumer requirements. Simple changes to how information is collected,shared, and used in the service supply chain can significantly reduce the percentage of jobs taking more than a giventime
KW - transport-on-demand (TOD)
KW - vehicle recovery service provider (VRSP)
KW - backlog
KW - service supply chain
KW - information accuracy
KW - information completeness
UR - http://www.orstw.org.tw/ijor/index.html
M3 - Article
VL - 14
SP - 121
EP - 138
JO - International Journal of Operations Research
JF - International Journal of Operations Research
SN - 1813-713X
IS - 3
ER -