TY - GEN
T1 - Efficiency Analysis of Last Mile Delivery Station
AU - Rindrasari, Rahajeng
AU - Surjandari, Isti
N1 - Publisher Copyright:
© 2021 ACM.
PY - 2021/5/25
Y1 - 2021/5/25
N2 - *A large increase in e-commerce business has an impact on supporting industries, one of which is the logistics industry. The quality in logistics services needs to be improved in line with the increasing demand from the market. Improvements in service quality and performance need efforts from all parts of the business process, one of which is the last mile delivery stage, which is the delivery of goods from retail locations to customers. Delivery speed and accuracy are important factors for measuring the performance of the process in the last mile. The performance of the process can be seen by measuring the relative efficiency of the last mile station using the Data Envelopment Analysis (DEA) method which is able to evaluate the relative efficiency level of a DMU (Decision Making Unit), in this case the DMU analyzed is 137 last mile stations in the DKI Jakarta and West Java. The input variables to measure efficiency are the number of couriers, the number of parcels that must be sent, and the cost to pay employees, while the output variables are in terms of delivery speed and customer satisfaction. Of the 139 stations, there are 51 stations (37%) that are relatively efficient (above 95% efficiency), and 88 stations (63%) that are not yet efficient. Station with low efficiency needs to improve its performance based on the benchmark value of each variable in the DEA analysis.
AB - *A large increase in e-commerce business has an impact on supporting industries, one of which is the logistics industry. The quality in logistics services needs to be improved in line with the increasing demand from the market. Improvements in service quality and performance need efforts from all parts of the business process, one of which is the last mile delivery stage, which is the delivery of goods from retail locations to customers. Delivery speed and accuracy are important factors for measuring the performance of the process in the last mile. The performance of the process can be seen by measuring the relative efficiency of the last mile station using the Data Envelopment Analysis (DEA) method which is able to evaluate the relative efficiency level of a DMU (Decision Making Unit), in this case the DMU analyzed is 137 last mile stations in the DKI Jakarta and West Java. The input variables to measure efficiency are the number of couriers, the number of parcels that must be sent, and the cost to pay employees, while the output variables are in terms of delivery speed and customer satisfaction. Of the 139 stations, there are 51 stations (37%) that are relatively efficient (above 95% efficiency), and 88 stations (63%) that are not yet efficient. Station with low efficiency needs to improve its performance based on the benchmark value of each variable in the DEA analysis.
KW - Biterm topic model
KW - Email marketing
KW - User preferences
UR - http://www.scopus.com/inward/record.url?scp=85143897774&partnerID=8YFLogxK
U2 - 10.1145/3468013.3468344
DO - 10.1145/3468013.3468344
M3 - Conference contribution
AN - SCOPUS:85143897774
T3 - ACM International Conference Proceeding Series
SP - 277
EP - 280
BT - Proceedings of the 4th Asia Pacific Conference on Research in Industrial and Systems Engineering
PB - Association for Computing Machinery
T2 - 4th Asia Pacific Conference on Research in Industrial and Systems Engineering: Building Business Resilience to Face the Challenge in Pandemic Era, APCORISE 2021
Y2 - 25 May 2021
ER -