Segmentation of e-customers in terms of sustainable last-mile delivery

最后一英里(运输) 英里 业务 交付性能 营销 订单(交换) 市场细分 持续性 环境经济学 财务 经济 天文 生态学 生物 物理 过程管理
作者
Maja Kiba-Janiak,Katarzyna Cheba,Magdalena Mucowska,Leise Kelli de Oliveira
出处
期刊:Oeconomia Copernicana [Instytut Badan Gospodarczych / Institute of Economic Research]
卷期号:13 (4): 1117-1142 被引量:17
标识
DOI:10.24136/oc.2022.032
摘要

Research background: A rapidly developing e-commerce market and growing customer expectations regarding the speed and frequency of deliveries have made the last mile of the supply chain more challenging. The expectations of e-customers increase every year. They choose those companies that deliver goods faster and cheaper than others. A significant group of customers in Poland still selects home delivery. Many of them frequently return products to the retailer. These expectations and behaviour pose a challenge for the transport companies to deliver parcels to individual customers soon after the purchase, sometimes even on the same day. In addition, increasingly frequent deliveries contribute to environmental pollution, congestion, and accidents, as well as more expensive deliveries. Purpose of the article: The paper aims to identify e-customers? preferences and assess their impact on sustainable last-mile delivery (LMD) in the e-commerce market. The authors have also identified factors influencing e-customers? behaviour to make last-mile delivery more sustainable. Methods: The conjoint analysis was applied to evaluate a set of profiles defined by selected attributes in order to investigate the overall preferences for the profiles created by the respondents to the survey. Findings & value added: The segmentation of e-customers according to their preferences connected with last-mile delivery was presented. The added value of the paper is the presentation of the methodology to assess the impact of customer preferences on sustainable last-mile delivery. The obtained results may contribute to the formulation of recommendations for e-commerce and logistics companies regarding the preferences of e-customers to improve the sustainability of last-mile delivery.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
gzmejiji发布了新的文献求助10
1秒前
科研通AI6.1应助Chen采纳,获得10
1秒前
华仔应助坦率采纳,获得10
2秒前
wty发布了新的文献求助30
2秒前
nhsyb嘉完成签到,获得积分10
2秒前
3秒前
冒如怿发布了新的文献求助30
4秒前
4秒前
6秒前
千夜冰柠萌完成签到,获得积分10
7秒前
圈儿多尼完成签到,获得积分10
7秒前
Hug发布了新的文献求助10
8秒前
大个应助笑点低剑封采纳,获得10
8秒前
量子星尘发布了新的文献求助10
8秒前
李想完成签到,获得积分10
8秒前
9秒前
陈陈要毕业完成签到 ,获得积分10
9秒前
QUAV完成签到,获得积分20
9秒前
caopeili完成签到 ,获得积分10
10秒前
10秒前
苏嘉完成签到,获得积分10
11秒前
铭铭发布了新的文献求助10
11秒前
科研通AI6.1应助尉迟半芹采纳,获得10
13秒前
idannn发布了新的文献求助10
13秒前
百里酚蓝完成签到,获得积分10
14秒前
打打应助苗逍遥采纳,获得10
14秒前
14秒前
科研混子发布了新的文献求助10
15秒前
15秒前
15秒前
shouyi886完成签到,获得积分10
16秒前
李爱国应助franklin_fsz采纳,获得30
16秒前
小李发布了新的文献求助10
16秒前
阳光问安完成签到 ,获得积分10
17秒前
17秒前
桐桐应助小小莫采纳,获得10
18秒前
裔振飞完成签到,获得积分10
18秒前
李健应助tRNA采纳,获得10
19秒前
20秒前
21秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Introduction to strong mixing conditions volume 1-3 5000
Clinical Microbiology Procedures Handbook, Multi-Volume, 5th Edition 2000
从k到英国情人 1500
Ägyptische Geschichte der 21.–30. Dynastie 1100
„Semitische Wissenschaften“? 1100
Real World Research, 5th Edition 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5737956
求助须知:如何正确求助?哪些是违规求助? 5374957
关于积分的说明 15336581
捐赠科研通 4881157
什么是DOI,文献DOI怎么找? 2623366
邀请新用户注册赠送积分活动 1572101
关于科研通互助平台的介绍 1528930