{"title":"The Impact of Sentiment Scores Extracted from Product Descriptions on Customer Purchase Intention","authors":"","doi":"10.1007/s00354-024-00242-9","DOIUrl":null,"url":null,"abstract":"<h3>Abstract</h3> <p>This study investigates whether and how the textual content of product descriptions, especially the sentiment element, influences buyers’ purchase intentions. Using year-round digital transaction data from Mercari, a leading e-Commerce platform in Japan, we examine the interplay of hard and soft information signals exchanged between sellers and buyers. The study addresses two crucial questions: (1) Do the descriptions that sellers provide on product sales pages impact the buyer’s intent to purchase? and (2) In what way does the description influence the buyer’s purchase intention? Quantitative analysis is used to understand the relationship between product descriptions, sentiment elements, and purchase intentions. The results show that sentiment factors in product descriptions can serve as high-quality “signals” that can help buyers make informed purchasing decisions and reduce information asymmetry between buyers and sellers. This research contributes to understanding decision-making in online markets, particularly the role of soft information and sentiment analysis.</p>","PeriodicalId":54726,"journal":{"name":"New Generation Computing","volume":"57 1","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2024-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"New Generation Computing","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s00354-024-00242-9","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
引用次数: 0
Abstract
This study investigates whether and how the textual content of product descriptions, especially the sentiment element, influences buyers’ purchase intentions. Using year-round digital transaction data from Mercari, a leading e-Commerce platform in Japan, we examine the interplay of hard and soft information signals exchanged between sellers and buyers. The study addresses two crucial questions: (1) Do the descriptions that sellers provide on product sales pages impact the buyer’s intent to purchase? and (2) In what way does the description influence the buyer’s purchase intention? Quantitative analysis is used to understand the relationship between product descriptions, sentiment elements, and purchase intentions. The results show that sentiment factors in product descriptions can serve as high-quality “signals” that can help buyers make informed purchasing decisions and reduce information asymmetry between buyers and sellers. This research contributes to understanding decision-making in online markets, particularly the role of soft information and sentiment analysis.
期刊介绍：
The journal is specially intended to support the development of new computational and cognitive paradigms stemming from the cross-fertilization of various research fields. These fields include, but are not limited to, programming (logic, constraint, functional, object-oriented), distributed/parallel computing, knowledge-based systems, agent-oriented systems, and cognitive aspects of human embodied knowledge. It also encourages theoretical and/or practical papers concerning all types of learning, knowledge discovery, evolutionary mechanisms, human cognition and learning, and emergent systems that can lead to key technologies enabling us to build more complex and intelligent systems. The editorial board hopes that New Generation Computing will work as a catalyst among active researchers with broad interests by ensuring a smooth publication process.
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