{"title":"用文本分析衡量服务质量:考虑消费者意见在社交和非社交在线平台上的重要性和表现","authors":"Lin Lu , Pei Xu , Yen-Yao Wang , Yu Wang","doi":"10.1016/j.jbusres.2023.114298","DOIUrl":null,"url":null,"abstract":"<div><p>Online word-of-mouth (WOM) has attracted considerable attention from researchers due to its abundant information on customer perceptions that drive product and service improvement. This study develops a novel weighted service quality (WSQ) metric derived from online customer opinions, leveraging the importance-performance analysis framework. Data collected from social and non-social online platforms confirms that this WSQ approach outperforms the widely used average sentiment score approach and significantly predicts the industry service quality standard, Airline Quality Rating (AQR). In addition, the WSQ metric derived from social media proves to be a more vital indicator for AQR than that derived from a non-social online platform. A significant difference in topic distributions was also identified between consumer opinions from social media and non-social online platforms. Our study makes several crucial contributions to the service quality literature on employing online WOM using sentiment analysis and topic modeling techniques.</p></div>","PeriodicalId":15123,"journal":{"name":"Journal of Business Research","volume":"169 ","pages":"Article 114298"},"PeriodicalIF":10.5000,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Measuring service quality with text analytics: Considering both importance and performance of consumer opinions on social and non-social online platforms\",\"authors\":\"Lin Lu , Pei Xu , Yen-Yao Wang , Yu Wang\",\"doi\":\"10.1016/j.jbusres.2023.114298\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Online word-of-mouth (WOM) has attracted considerable attention from researchers due to its abundant information on customer perceptions that drive product and service improvement. This study develops a novel weighted service quality (WSQ) metric derived from online customer opinions, leveraging the importance-performance analysis framework. Data collected from social and non-social online platforms confirms that this WSQ approach outperforms the widely used average sentiment score approach and significantly predicts the industry service quality standard, Airline Quality Rating (AQR). In addition, the WSQ metric derived from social media proves to be a more vital indicator for AQR than that derived from a non-social online platform. A significant difference in topic distributions was also identified between consumer opinions from social media and non-social online platforms. Our study makes several crucial contributions to the service quality literature on employing online WOM using sentiment analysis and topic modeling techniques.</p></div>\",\"PeriodicalId\":15123,\"journal\":{\"name\":\"Journal of Business Research\",\"volume\":\"169 \",\"pages\":\"Article 114298\"},\"PeriodicalIF\":10.5000,\"publicationDate\":\"2023-09-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Business Research\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0148296323006574\",\"RegionNum\":1,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Business Research","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0148296323006574","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS","Score":null,"Total":0}
Measuring service quality with text analytics: Considering both importance and performance of consumer opinions on social and non-social online platforms
Online word-of-mouth (WOM) has attracted considerable attention from researchers due to its abundant information on customer perceptions that drive product and service improvement. This study develops a novel weighted service quality (WSQ) metric derived from online customer opinions, leveraging the importance-performance analysis framework. Data collected from social and non-social online platforms confirms that this WSQ approach outperforms the widely used average sentiment score approach and significantly predicts the industry service quality standard, Airline Quality Rating (AQR). In addition, the WSQ metric derived from social media proves to be a more vital indicator for AQR than that derived from a non-social online platform. A significant difference in topic distributions was also identified between consumer opinions from social media and non-social online platforms. Our study makes several crucial contributions to the service quality literature on employing online WOM using sentiment analysis and topic modeling techniques.
期刊介绍:
The Journal of Business Research aims to publish research that is rigorous, relevant, and potentially impactful. It examines a wide variety of business decision contexts, processes, and activities, developing insights that are meaningful for theory, practice, and/or society at large. The research is intended to generate meaningful debates in academia and practice, that are thought provoking and have the potential to make a difference to conceptual thinking and/or practice. The Journal is published for a broad range of stakeholders, including scholars, researchers, executives, and policy makers. It aids the application of its research to practical situations and theoretical findings to the reality of the business world as well as to society. The Journal is abstracted and indexed in several databases, including Social Sciences Citation Index, ANBAR, Current Contents, Management Contents, Management Literature in Brief, PsycINFO, Information Service, RePEc, Academic Journal Guide, ABI/Inform, INSPEC, etc.