{"title":"负面评论是订单的终结者吗?共享住宿背景下基于方面的在线评论情感阈值分析","authors":"Bo Wang, Xin Jin, Ning Ma","doi":"10.1108/k-10-2023-2132","DOIUrl":null,"url":null,"abstract":"<h3>Purpose</h3>\n<p>Existing research has predominantly concentrated on examining the factors that impact consumer decisions through the lens of potential consumer motivations, neglecting the sentiment mechanisms that propel guest behavioral intentions. This study endeavors to systematically analyze the underlying mechanisms governing how negative reviews exert an influence on potential consumer decisions.</p><!--/ Abstract__block -->\n<h3>Design/methodology/approach</h3>\n<p>This paper constructs an “Aspect-based sentiment accumulation” index, a negative or positive affect load, reflecting the degree of consumer sentiment based on affect infusion model and aspect-based sentiment analysis. Initially, it verifies the causal relationship between aspect-based negative load and consumer decisions using ordinary least squares regression. Then, it analyzes the threshold effects of negative affect load on positive affect load and the threshold effects of positive affect load on negative affect load using a panel threshold regression model.</p><!--/ Abstract__block -->\n<h3>Findings</h3>\n<p>Aspect-based negative reviews significantly impact consumers’ decisions. Negative affect load and positive affect load exhibit threshold effects on each other, with threshold values varying according to the overall volume of reviews. As the total number of reviews increases, the impact of negative affect load diminishes. The threshold effects for positive affect load showed a predominantly U-shaped course of change. Hosts respond promptly and enthusiastically with detailed, lengthy text, which can aid in mitigating the impact of negative reviews.</p><!--/ Abstract__block -->\n<h3>Originality/value</h3>\n<p>The study extends the application of the affect infusion model and enriches the conditions for its theoretical scope. It addresses the research gap by focusing on the threshold effects of negative or positive review sentiment on decision-making in sharing accommodations.</p><!--/ Abstract__block -->","PeriodicalId":49930,"journal":{"name":"Kybernetes","volume":"30 1","pages":""},"PeriodicalIF":2.5000,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Are negative reviews the order terminators? An aspect-based sentiment threshold analysis of online reviews in the context of sharing accommodation\",\"authors\":\"Bo Wang, Xin Jin, Ning Ma\",\"doi\":\"10.1108/k-10-2023-2132\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<h3>Purpose</h3>\\n<p>Existing research has predominantly concentrated on examining the factors that impact consumer decisions through the lens of potential consumer motivations, neglecting the sentiment mechanisms that propel guest behavioral intentions. 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引用次数: 0
摘要
目的现有研究主要集中在从潜在消费动机的角度研究影响消费者决策的因素,而忽视了推动客人行为意图的情感机制。本文基于情感渗透模型和基于方面的情感分析,构建了反映消费者情感程度的 "基于方面的情感积累 "指数,即负面或正面情感负荷。首先,本文使用普通最小二乘法回归验证了基于方面的负情感负荷与消费者决策之间的因果关系。然后,利用面板阈值回归模型分析了负面情感负载对正面情感负载的阈值效应以及正面情感负载对负面情感负载的阈值效应。负面影响负荷和正面影响负荷表现出相互的阈值效应,阈值随评论总量的变化而变化。随着评论总数的增加,负面影响负荷的影响逐渐减弱。积极情感负荷的阈值效应主要呈 U 型变化。主持人及时、热情地回复详细、冗长的文字,有助于减轻负面评论的影响。它关注负面或正面评论情绪对共享住宿决策的门槛效应,从而填补了研究空白。
Are negative reviews the order terminators? An aspect-based sentiment threshold analysis of online reviews in the context of sharing accommodation
Purpose
Existing research has predominantly concentrated on examining the factors that impact consumer decisions through the lens of potential consumer motivations, neglecting the sentiment mechanisms that propel guest behavioral intentions. This study endeavors to systematically analyze the underlying mechanisms governing how negative reviews exert an influence on potential consumer decisions.
Design/methodology/approach
This paper constructs an “Aspect-based sentiment accumulation” index, a negative or positive affect load, reflecting the degree of consumer sentiment based on affect infusion model and aspect-based sentiment analysis. Initially, it verifies the causal relationship between aspect-based negative load and consumer decisions using ordinary least squares regression. Then, it analyzes the threshold effects of negative affect load on positive affect load and the threshold effects of positive affect load on negative affect load using a panel threshold regression model.
Findings
Aspect-based negative reviews significantly impact consumers’ decisions. Negative affect load and positive affect load exhibit threshold effects on each other, with threshold values varying according to the overall volume of reviews. As the total number of reviews increases, the impact of negative affect load diminishes. The threshold effects for positive affect load showed a predominantly U-shaped course of change. Hosts respond promptly and enthusiastically with detailed, lengthy text, which can aid in mitigating the impact of negative reviews.
Originality/value
The study extends the application of the affect infusion model and enriches the conditions for its theoretical scope. It addresses the research gap by focusing on the threshold effects of negative or positive review sentiment on decision-making in sharing accommodations.
期刊介绍:
Kybernetes is the official journal of the UNESCO recognized World Organisation of Systems and Cybernetics (WOSC), and The Cybernetics Society.
The journal is an important forum for the exchange of knowledge and information among all those who are interested in cybernetics and systems thinking.
It is devoted to improvement in the understanding of human, social, organizational, technological and sustainable aspects of society and their interdependencies. It encourages consideration of a range of theories, methodologies and approaches, and their transdisciplinary links. The spirit of the journal comes from Norbert Wiener''s understanding of cybernetics as "The Human Use of Human Beings." Hence, Kybernetes strives for examination and analysis, based on a systemic frame of reference, of burning issues of ecosystems, society, organizations, businesses and human behavior.