The Effects of Stress and Chatbot Services Usage on Customer Intention for Purchase on E-commerce Sites

Abed Matini, Stanley Lekata, Boniface Kabaso
{"title":"The Effects of Stress and Chatbot Services Usage on Customer Intention for Purchase on E-commerce Sites","authors":"Abed Matini, Stanley Lekata, Boniface Kabaso","doi":"10.11648/j.ijdst.20241001.11","DOIUrl":null,"url":null,"abstract":"In the rapidly evolving digital marketplace, customer service has become a critical factor influencing consumer behaviour. With the advent of Artificial Intelligence (AI), particularly chatbots, customer service companies are increasingly leveraging technology to enhance user experience. This study explores the relationship between customer emotions, detected during interactions with e-commerce chatbots, and their subsequent purchase intentions. Emotion detection within Human-Computer Interaction (HCI) is a vital area of research, as specific emotions, such as joy or frustration, can significantly impact marketing effectiveness and consumer decision-making. This research aims to understand how emotional responses to chatbot interactions can predict customer's intention to purchase, thereby offering insights for businesses to optimize their AI-driven customer service strategies. The study analyzes four diverse datasets – EmotionLines, CARER, GoEmotion, and EmotionPush – to identify emotion-labelled sentences indicative of purchase intention. Our findings reveal that Neutral and Joyful emotions are predominant in influencing customers' purchase intentions, highlighting the importance of understanding these emotional states in e-commerce settings. While Neutral emotion is most influential, Joy consistently plays a significant role in positive customer engagement. This research underscores the need for e-commerce businesses to focus on emotional intelligence in chatbots, enhancing customer experience and potentially driving sales. Future research directions include examining real chatbot-customer interactions to further understand the impact of AI-driven customer service on consumer emotions and behaviours.","PeriodicalId":281025,"journal":{"name":"International Journal on Data Science and Technology","volume":"355 ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal on Data Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11648/j.ijdst.20241001.11","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

In the rapidly evolving digital marketplace, customer service has become a critical factor influencing consumer behaviour. With the advent of Artificial Intelligence (AI), particularly chatbots, customer service companies are increasingly leveraging technology to enhance user experience. This study explores the relationship between customer emotions, detected during interactions with e-commerce chatbots, and their subsequent purchase intentions. Emotion detection within Human-Computer Interaction (HCI) is a vital area of research, as specific emotions, such as joy or frustration, can significantly impact marketing effectiveness and consumer decision-making. This research aims to understand how emotional responses to chatbot interactions can predict customer's intention to purchase, thereby offering insights for businesses to optimize their AI-driven customer service strategies. The study analyzes four diverse datasets – EmotionLines, CARER, GoEmotion, and EmotionPush – to identify emotion-labelled sentences indicative of purchase intention. Our findings reveal that Neutral and Joyful emotions are predominant in influencing customers' purchase intentions, highlighting the importance of understanding these emotional states in e-commerce settings. While Neutral emotion is most influential, Joy consistently plays a significant role in positive customer engagement. This research underscores the need for e-commerce businesses to focus on emotional intelligence in chatbots, enhancing customer experience and potentially driving sales. Future research directions include examining real chatbot-customer interactions to further understand the impact of AI-driven customer service on consumer emotions and behaviours.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
压力和聊天机器人服务的使用对电子商务网站客户购买意向的影响
在快速发展的数字市场中,客户服务已成为影响消费者行为的关键因素。随着人工智能(AI),尤其是聊天机器人的出现,客户服务公司越来越多地利用技术来提升用户体验。本研究探讨了在与电子商务聊天机器人互动过程中检测到的客户情绪与其后续购买意向之间的关系。人机交互(HCI)中的情绪检测是一个重要的研究领域,因为特定的情绪(如喜悦或沮丧)会对营销效果和消费者决策产生重大影响。本研究旨在了解对聊天机器人互动的情绪反应如何预测客户的购买意向,从而为企业优化其人工智能驱动的客户服务战略提供见解。本研究分析了 EmotionLines、CARER、GoEmotion 和 EmotionPush 这四个不同的数据集,以识别表明购买意向的情绪标签句子。我们的研究结果表明,"中性 "和 "愉悦 "情绪在影响客户购买意向方面占主导地位,这凸显了在电子商务环境中了解这些情绪状态的重要性。虽然 "中性 "情绪最具影响力,但 "喜悦 "情绪始终在积极的客户参与中发挥着重要作用。这项研究强调,电子商务企业需要关注聊天机器人中的情绪智能,从而提升客户体验并促进销售。未来的研究方向包括研究聊天机器人与客户的真实互动,以进一步了解人工智能驱动的客户服务对消费者情绪和行为的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Agent Based Intelligent System for Enhanced Teamwork Performance The Effects of Stress and Chatbot Services Usage on Customer Intention for Purchase on E-commerce Sites Logistics Web Application for the Tracking of Parcels Extractive Text Summarization Using Deep Learning for Tigrigna Language Modelling the Volatility of Central Bank of Kenya Currency Exchange Rates
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1