Integrating customer preferences into operational decision-making for prioritizing emerging technologies in last-mile delivery

IF 6.8 3区管理学 Q1 BUSINESS

Electronic Commerce Research and Applications Pub Date : 2026-01-01 Epub Date: 2026-01-09 DOI:10.1016/j.elerap.2026.101573

Ahmet Çalık , Esra Boz , Sinan Çizmecioğlu , Erfan Babaee Tirkolaee

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引用次数: 0

Abstract

The rapid expansion of e-commerce has positioned last-mile delivery as the most critical and resource-intensive stage of modern supply chains. Firms must balance multiple and often conflicting objectives: reducing costs, minimizing environmental impacts, and meeting growing customer expectations for speed, reliability, and personalization. While previous research has focused on operational efficiency and routing optimization, limited attention has been given to frameworks that integrate customer preferences with technology-enabled decision-making. This study develops a hybrid decision support model by extending the classical Simple Weight Calculation (SIWEC) method with grey numbers (G-SIWEC), capable of handling uncertainty in subjective judgments to generate robust criterion weights. These weights are incorporated into a multi-objective optimization model, solved using the Weighted Sum Scalarization Method (WSSM), to minimize delivery costs and emissions while maximizing service quality. The model explicitly considers emerging delivery technologies, including drone, Autonomous Vehicle (AV), and bicycle (e-bike), to explore innovative, sustainable, and customer-centric delivery strategies. Findings highlight technology-specific patterns: drone and bicycle excel in lightweight, eco-friendly deliveries, AV dominates mid-range logistics, and conventional truck remains indispensable for heavy loads. By linking customer preferences to technology-driven operational decisions, this work provides practical insights for managers and policymakers seeking to design efficient, sustainable, and innovative last-mile delivery systems for e-commerce. These implications should be interpreted within the context of the numerical experiment conducted in this study.

查看原文本刊更多论文

将客户偏好整合到运营决策中，以优先考虑最后一英里交付中的新兴技术

电子商务的快速发展使最后一英里配送成为现代供应链中最关键、资源最密集的阶段。公司必须平衡多个经常相互冲突的目标：降低成本，最小化环境影响，满足客户对速度、可靠性和个性化日益增长的期望。虽然之前的研究主要集中在运营效率和路线优化上，但对将客户偏好与技术支持决策相结合的框架的关注有限。本研究通过扩展经典的灰色数简单权重计算（G-SIWEC）方法，开发了一种混合决策支持模型，能够处理主观判断中的不确定性，生成鲁棒的准则权重。这些权重被纳入到一个多目标优化模型中，使用加权和标量化方法（WSSM）求解，以最小化交付成本和排放，同时最大化服务质量。该模型明确考虑了新兴的配送技术，包括无人机、自动驾驶汽车（AV）和自行车（e-bike），以探索创新、可持续和以客户为中心的配送策略。研究结果强调了技术特定模式：无人机和自行车在轻型环保配送方面表现出色，无人驾驶汽车主导中程物流，而传统卡车在重载运输方面仍然不可或缺。通过将客户偏好与技术驱动的运营决策联系起来，这项工作为寻求为电子商务设计高效、可持续和创新的最后一英里交付系统的管理人员和政策制定者提供了实用的见解。这些含义应该在本研究中进行的数值实验的背景下解释。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Electronic Commerce Research and Applications 工程技术-计算机：跨学科应用

CiteScore

10.10

自引率

8.30%

发文量

审稿时长

63 days

期刊介绍： Electronic Commerce Research and Applications aims to create and disseminate enduring knowledge for the fast-changing e-commerce environment. A major dilemma in e-commerce research is how to achieve a balance between the currency and the life span of knowledge. Electronic Commerce Research and Applications will contribute to the establishment of a research community to create the knowledge, technology, theory, and applications for the development of electronic commerce. This is targeted at the intersection of technological potential and business aims.