Logistics company governance in the improvement of last-mile delivery efficiency

Last-mile delivery is the final step in the process of providing logistics transportation services. Viettel Post’s last-mile delivery rate is lower than that of its direct competitors. With the goal of improving efficiency in last-mile delivery activities of logistics companies in general and Viettel Post company in particular. In this study, the author uses the logistics quality (LSQ) framework (Hartline & Ferrell, 1996) and the motivation-opportunity-ability (MOA) model framework (Maclnnis et al., 1991) as the foundation theory to clarify the influence of delivery staff’s own factors in the delivery staff’s performance and to improve last-mile delivery efficiency. The data sample was collected online from 295 delivery staff working at Viettel Post company, in the period from November 2023 to March 2024. Using quantitative research on the partial least squares structural equation modeling (PLS-SEM) linear structural model on the Statistical Package for the Social Sciences (SPSS) v. 20 and AMOS v. 20 software, the results showed that five influential factors were identified, including: 1) knowledge of employees (KNO), 2) employee skills (SKI), 3) employee income (INC), 4) job characteristics (JOB), and 5) company reputation (REP). Based on research, the study provides recommendations for Viettel Post company managers as well as for logistics companies to improve last-mile delivery efficiency.

Authors

Institutions

Publication Details

Journal
Journal of Governance and Regulation
Published
2025-01-09
DOI
https://doi.org/10.22495/jgrv14i1art7
Primary Topic
Operations Management Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Logistics company governance in the improvement of last-mile delivery efficiency

Cao Cam Linh
Journal of Governance and Regulation
Operations Management Techniques
article

Logistics company governance in the improvement of last-mile delivery efficiency

Cao Cam Linh
article en

Abstract

Last-mile delivery is the final step in the process of providing logistics transportation services. Viettel Post’s last-mile delivery rate is lower than that of its direct competitors. With the goal of improving efficiency in last-mile delivery activities of logistics companies in general and Viettel Post company in particular. In this study, the author uses the logistics quality (LSQ) framework (Hartline & Ferrell, 1996) and the motivation-opportunity-ability (MOA) model framework (Maclnnis et al., 1991) as the foundation theory to clarify the influence of delivery staff’s own factors in the delivery staff’s performance and to improve last-mile delivery efficiency. The data sample was collected online from 295 delivery staff working at Viettel Post company, in the period from November 2023 to March 2024. Using quantitative research on the partial least squares structural equation modeling (PLS-SEM) linear structural model on the Statistical Package for the Social Sciences (SPSS) v. 20 and AMOS v. 20 software, the results showed that five influential factors were identified, including: 1) knowledge of employees (KNO), 2) employee skills (SKI), 3) employee income (INC), 4) job characteristics (JOB), and 5) company reputation (REP). Based on research, the study provides recommendations for Viettel Post company managers as well as for logistics companies to improve last-mile delivery efficiency.

Journal of Governance and RegulationVol. 14(1)
National Economics University (VN)
Decent work and economic growth
Openalex Percentile: Top 100%
Operations Management Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.