Bilgilendirme: Sürüm Güncellemesi ve versiyon yükseltmesi nedeniyle, geçici süreyle zaman zaman kesintiler yaşanabilir ve veri içeriğinde değişkenlikler gözlemlenebilir. Göstereceğiniz anlayış için teşekkür ederiz.
 

A Hybrid Approach Based on Qualitative and Quantitative Techniques for Analyzing Last-Mile Parcel Delivery

No Thumbnail Available

Date

2025

Journal Title

Journal ISSN

Volume Title

Publisher

Springer India

Open Access Color

OpenAIRE Downloads

OpenAIRE Views

Research Projects

Journal Issue

Abstract

Operational excellence in last-mile delivery is becoming increasingly challenging, highlighting the need for a strategic assessment framework to improve decision-making processes. This study aims to provide a strategic assessment tool for last-mile parcel delivery processes, which are critical in terms of service levels, cost management and sustainability. The study presents a comprehensive approach to identify and prioritise feasible strategies by combining qualitative data obtained from expert opinions with Strengths, Weaknesses, Opportunities, and Threats analysis (SWOT) and Multi-Criteria Decision-Making (MCDM) methods. As a result of semi-structured interviews conducted with nine experts, 27 strategic criteria were identified and classified under SWOT dimensions. The 10 strategies developed during the interviews were evaluated by using the Intuitionistic Fuzzy Set (IFS) approach, which considers expert reliability, the Full Consistency Method (FUCOM) for weighting, and the Complex Proportional Assessment (COPRAS) technique for final ranking. There is a clear gap in the literature regarding critical criteria and strategies for last-mile delivery in developing economies. Since it is not possible to implement all strategies simultaneously due to limited resources, the strategies proposed in this study have been prioritised according to their relative importance. While expert-based evaluations in the literature typically assume that experts have equal influence, this study differs from the literature by weighting experts based on their level of experience. This approach not only addresses the gap in strategy and criterion development in the literature but also offers a more realistic and feasible approach from an implementation perspective. The findings show that all strategies are meaningful in improving last-mile performance, but their impact levels vary. "Developing public and corporate strategies for environmental sustainability" stands out as the highest priority strategy with a performance index of 100 points, while "Incorporating parcel transportation-related topics into logistics management education" is considered as the lowest priority strategy with 91.94 points. Limitations of this study arise from the niche nature of the sector and the small sample size.

Description

Omurgonulsen, Mine/0000-0001-6905-1154

Keywords

Last-Mile Parcel Delivery, Hybrid Framework, Expert Involvement, SWOT Analysis, Intuitionistic Fuzzy Set (IFS), Multi-Criteria Decision-Making (MCDM)

Turkish CoHE Thesis Center URL

Fields of Science

Citation

WoS Q

N/A

Scopus Q

Q3
OpenCitations Logo
OpenCitations Citation Count
N/A

Source

Opsearch

Volume

Issue

Start Page

End Page

PlumX Metrics
Citations

Scopus : 0

Captures

Mendeley Readers : 5

Google Scholar Logo
Google Scholar™
OpenAlex Logo
OpenAlex FWCI
0.0

Sustainable Development Goals

1

NO POVERTY
NO POVERTY Logo

3

GOOD HEALTH AND WELL-BEING
GOOD HEALTH AND WELL-BEING Logo

7

AFFORDABLE AND CLEAN ENERGY
AFFORDABLE AND CLEAN ENERGY Logo

8

DECENT WORK AND ECONOMIC GROWTH
DECENT WORK AND ECONOMIC GROWTH Logo

9

INDUSTRY, INNOVATION AND INFRASTRUCTURE
INDUSTRY, INNOVATION AND INFRASTRUCTURE Logo

10

REDUCED INEQUALITIES
REDUCED INEQUALITIES Logo

11

SUSTAINABLE CITIES AND COMMUNITIES
SUSTAINABLE CITIES AND COMMUNITIES Logo

13

CLIMATE ACTION
CLIMATE ACTION Logo

14

LIFE BELOW WATER
LIFE BELOW WATER Logo

16

PEACE, JUSTICE AND STRONG INSTITUTIONS
PEACE, JUSTICE AND STRONG INSTITUTIONS Logo

17

PARTNERSHIPS FOR THE GOALS
PARTNERSHIPS FOR THE GOALS Logo