Abstract
Successful transport-on-demand (TOD) requires having sufficient capacity in the right location to
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
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 |
