The impact of order fulfillment on consumer experience: text mining consumer reviews from Amazon US

Yulia Vakulenko, Diogo Figueirinhas, Daniel Hellström, Henrik Pålsson
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Abstract

Purpose

This research analyzes online consumer reviews and ratings to assess e-retail order fulfillment performance. The study aims to (1) identify consumer journey touchpoints in the order fulfillment process and (2) determine their relative importance for the consumer experience.

Design/methodology/approach

Text mining and analytics were employed to examine over 100 m online purchase orders, along with associated consumer reviews and ratings from Amazon US. Using natural language processing techniques, the corpus of reviews was structured to pinpoint touchpoints related to order fulfillment. Reviews were then classified according to their stance (either positive or negative) toward these touchpoints. Finally, the classes were correlated with consumer rating, measured by the number of stars, to determine the relative importance of each touchpoint.

Findings

The study reveals 12 touchpoints within the order fulfillment process, which are split into three groups: delivery, packaging and returns. These touchpoints significantly influence star ratings: positive experiences elevate them, while negative ones reduce them. The findings provide a quantifiable measure of these effects, articulated in terms of star ratings, which directly reflect the influence of experiences on consumer evaluations.

Research limitations/implications

The dataset utilized in this study is from the US market, which limits the generalizability of the findings to other markets. Moreover, the novel methodology used to map and quantify customer journey touchpoints requires further refinement.

Practical implications

In e-retail and logistics, comprehending touchpoints in the order fulfillment process is pivotal. This understanding helps improve consumer interactions and enhance satisfaction. Such insights not only drive higher conversion rates but also guide informed managerial decisions, particularly in service development.

Originality/value

Drawing upon consumer-generated data, this research identifies a cohesive set of touchpoints within the order fulfillment process and quantitatively evaluates their influence on consumer experience using star ratings as a metric.

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订单执行对消费者体验的影响:美国亚马逊消费者评论文本挖掘
目的本研究分析了消费者的在线评论和评分,以评估电子零售订单的履行情况。本研究旨在:(1)识别订单履行过程中的消费者旅程接触点;(2)确定这些接触点对消费者体验的相对重要性。设计/方法/途径采用文本挖掘和分析方法,对亚马逊美国网站上超过 1 亿份在线购买订单以及相关的消费者评论和评分进行了研究。利用自然语言处理技术,对评论语料库进行了结构化处理,以确定与订单履行相关的接触点。然后,根据评论对这些接触点的态度(积极或消极)对评论进行分类。研究结果这项研究揭示了订单履行过程中的 12 个接触点,分为三组:送货、包装和退货。这些接触点对星级评价有重大影响:积极的体验会提升星级评价,而消极的体验则会降低星级评价。研究限制/影响本研究使用的数据集来自美国市场,这限制了研究结果在其他市场的推广。此外,用于绘制和量化顾客旅程接触点的新方法还需要进一步完善。实际意义在电子零售和物流业,理解订单履行过程中的接触点至关重要。这种理解有助于改善与消费者的互动并提高满意度。原创性/价值这项研究利用消费者生成的数据,在订单执行过程中确定了一系列具有凝聚力的接触点,并以星级作为衡量标准,定量评估了这些接触点对消费者体验的影响。
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来源期刊
CiteScore
11.20
自引率
10.40%
发文量
34
期刊介绍: IJPDLM seeks strategically focused, theoretically grounded, empirical and conceptual, quantitative and qualitative, rigorous and relevant, original research studies in logistics, physical distribution and supply chain management operations and associated strategic issues. Quantitatively oriented mathematical and modelling research papers are not suitable for IJPDLM. Desired topics include, but are not limited to: Customer service strategy Omni-channel and multi-channel distribution innovations Order processing and inventory management Implementation of supply chain processes Information and communication technology Sourcing and procurement Risk management and security Personnel recruitment and training Sustainability and environmental Collaboration and integration Global supply chain management and network complexity Information and knowledge management Legal, financial and public policy Retailing, channels and business-to-business management Organizational and human resource development Logistics and SCM education.
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