Strategic insights into last-mile delivery: modelling the industry 4.0 enabler for e-commerce industry

Purpose Excellent customer experience with doorstep delivery is one of the motivations for online purchasing and e-commerce. Optimal technology-driven last-mile delivery is the backbone of this business model. This paper aims to identify industry 4.0 (I4.0) technology-based enablers for efficient e-commerce logistics for last-mile delivery (LMD) operations. Design/methodology/approach This study adopts an empirically grounded quantitative approach for defining and analysing the I4.0 technology enablers for efficient LMD operations. It adopts interpretive structural modelling and matrice d’impacts croisés multiplication appliquée á un classement analysis to identify the dependency and relationship among the identified enablers. Findings The transformation technologies of I4.0 offer a comprehensive package to handle LMD and e-commerce business challenges. This research identified that LMD and logistics will be dominated by autonomous running vehicles, drones and robots; apart from that, in I4.0 adoption cases, the implementation of radio-frequency identification was found suitable for efficient logistics networks. In addition, digitalisation through digital twins, robots, autonomous vehicles and Internet of Things adoption was found to drive the system and is crucial for strategic action. Research limitations/implications The findings of this research help companies and the e-commerce industry to evaluate strategic technological investments in promising I4.0 for LMD. The study also helps managers to focus on initiating and integrating digital technologies and autonomous vehicles, drones and robots focused on LMD improvement. Practical implications The findings of this research help companies and the e-commerce industry to evaluate strategic technological investments in promising I4.0 for LMD. The study also helps managers to focus on initiating and integrating digital technologies and autonomous vehicles, drones and robots focused on LMD improvement. Social implications Industry 4.0 technologies enable more efficient route planning, reducing fuel consumption and lowering carbon emissions. Optimised delivery networks reduce waste and ensure more efficient use of resources by using suggested technologies. Originality/value This study presents strategic insights into LMD and I4.0 enablers for the e-commerce environment. It proposes a theoretical framework that can serve as a roadmap for implementing I4.0 technologies to address unaddressed bottlenecks in LMD operations, lowering the logistics network’s efficiency.

Authors

Institutions

Publication Details

Journal
RAUSP Management Journal
Published
2025-05-19
DOI
https://doi.org/10.1108/rausp-07-2024-0146
Citations
4
Primary Topic
Urban and Freight Transport Logistics
Type
article
Field-Weighted Citation Impact
4.03
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Strategic insights into last-mile delivery: modelling the industry 4.0 enabler for e-commerce industry

Bharti Ramtiyal, Surya Prakash, Ravindra Ojha, Vijay Prakash Sharma et al.
4 citations
RAUSP Management Journal
Urban and Freight Transport Logistics
4.03
article

Strategic insights into last-mile delivery: modelling the industry 4.0 enabler for e-commerce industry

Bharti Ramtiyal, Surya Prakash, Ravindra Ojha, Vijay Prakash Sharma, Ranbir Singh
article en
4 citations

Abstract

Purpose Excellent customer experience with doorstep delivery is one of the motivations for online purchasing and e-commerce. Optimal technology-driven last-mile delivery is the backbone of this business model. This paper aims to identify industry 4.0 (I4.0) technology-based enablers for efficient e-commerce logistics for last-mile delivery (LMD) operations. Design/methodology/approach This study adopts an empirically grounded quantitative approach for defining and analysing the I4.0 technology enablers for efficient LMD operations. It adopts interpretive structural modelling and matrice d’impacts croisés multiplication appliquée á un classement analysis to identify the dependency and relationship among the identified enablers. Findings The transformation technologies of I4.0 offer a comprehensive package to handle LMD and e-commerce business challenges. This research identified that LMD and logistics will be dominated by autonomous running vehicles, drones and robots; apart from that, in I4.0 adoption cases, the implementation of radio-frequency identification was found suitable for efficient logistics networks. In addition, digitalisation through digital twins, robots, autonomous vehicles and Internet of Things adoption was found to drive the system and is crucial for strategic action. Research limitations/implications The findings of this research help companies and the e-commerce industry to evaluate strategic technological investments in promising I4.0 for LMD. The study also helps managers to focus on initiating and integrating digital technologies and autonomous vehicles, drones and robots focused on LMD improvement. Practical implications The findings of this research help companies and the e-commerce industry to evaluate strategic technological investments in promising I4.0 for LMD. The study also helps managers to focus on initiating and integrating digital technologies and autonomous vehicles, drones and robots focused on LMD improvement. Social implications Industry 4.0 technologies enable more efficient route planning, reducing fuel consumption and lowering carbon emissions. Optimised delivery networks reduce waste and ensure more efficient use of resources by using suggested technologies. Originality/value This study presents strategic insights into LMD and I4.0 enablers for the e-commerce environment. It proposes a theoretical framework that can serve as a roadmap for implementing I4.0 technologies to address unaddressed bottlenecks in LMD operations, lowering the logistics network’s efficiency.

RAUSP Management JournalVol. 60(1)
Management Development Institute (IN), BML Munjal University (IN), KR Mangalam University (IN), Graphic Era University (IN)
Openalex Percentile: Top 7%
Urban and Freight Transport Logistics
4.03
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.