The antecedents of customer satisfaction and dissatisfaction toward various types of hotels: A text mining approach

被引:289
|
作者
Xu, Xun [1 ]
Li, Yibai [2 ]
机构
[1] Calif State Univ Stanislaus, Coll Business Adm, Dept Management Operat & Mkt, One Univ Circle, Turlock, CA 95382 USA
[2] Univ Scranton, Kania Sch Management, Operat & Informat Management Dept, Scranton, PA 18510 USA
关键词
Customer satisfaction; Customer dissatisfaction; Antecedents; Hotel type; Online reviews; Text mining; LATENT SEMANTIC ANALYSIS; ONLINE PRODUCT REVIEWS; USER-GENERATED CONTENT; WORD-OF-MOUTH; BEHAVIORAL INTENTIONS; GUEST SATISFACTION; SERVICE QUALITY; BUDGET HOTELS; HOSPITALITY; MANAGEMENT;
D O I
10.1016/j.ijhm.2016.03.003
中图分类号
F [经济];
学科分类号
02 ;
摘要
Customers' online reviews play an important role in generating electronic word of mouth; these reviews serve as an online communication tool that highly influences consumers' demand for hotels. Using latent semantic analysis, which is a text mining approach, we analyze online customer reviews of hotels. We find that the determinants that create either customer satisfaction or dissatisfaction toward hotels are different and are specific to particular types of hotels, including full-service hotels, limited-service hotels, suite hotels with food and beverage, and suite hotels without food and beverage. Our study provides a clue for hoteliers to enhance customer satisfaction and alleviate customer dissatisfaction by improving service and satisfying the customers' needs for the different types of hotels the hoteliers own. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:57 / 69
页数:13
相关论文
共 50 条
  • [1] Voice of airline passenger: A text mining approach to understand customer satisfaction
    Sezgen, Eren
    Mason, Keith J.
    Mayer, Robert
    JOURNAL OF AIR TRANSPORT MANAGEMENT, 2019, 77 : 65 - 74
  • [2] FACTORS INFLUENCING CUSTOMERS' SATISFACTION AND DISSATISFACTION WITH HOTELS: A TEXT-MINING APPROACH
    Kuhzady, Salar
    Ghasemi, Vahid
    TOURISM ANALYSIS, 2019, 24 (01): : 69 - 79
  • [3] Ecological hotels' customer satisfaction through text mining of online reviews: a case of Ecuador hotels
    Moreno Brito, Yahaira Lisbeth
    Ban, Hyun-Jeong
    Kim, Hak-Seon
    JOURNAL OF HOSPITALITY AND TOURISM INSIGHTS, 2024, 7 (03) : 1532 - 1552
  • [4] Heritage hotels and customer experience: a text mining analysis of online reviews
    Chittiprolu, Vinay
    Samala, Nagaraj
    Bellamkonda, Raja Shekhar
    INTERNATIONAL JOURNAL OF CULTURE TOURISM AND HOSPITALITY RESEARCH, 2021, 15 (02) : 131 - 156
  • [5] The Determinants of IS User Satisfaction and Dissatisfaction: A Text Mining Approach
    Yu, Yixiu
    Davis, Fred D.
    AMCIS 2017 PROCEEDINGS, 2017,
  • [6] Text mining approach to explore dimensions of airline customer satisfaction using online customer reviews
    Lucini, Filipe R.
    Tonetto, Leandro M.
    Fogliatto, Flavio S.
    Anzanello, Michel J.
    JOURNAL OF AIR TRANSPORT MANAGEMENT, 2020, 83
  • [7] Leveraging sentiment analysis via text mining to improve customer satisfaction in UK banks
    Ghadiridehkordi, Amirreza
    Shao, Jia
    Boojihawon, Roshan
    Wang, Qianxi
    Li, Hui
    INTERNATIONAL JOURNAL OF BANK MARKETING, 2025, 43 (04) : 780 - 802
  • [8] Measuring SERVQUAL dimensions and their importance for customer-satisfaction using online reviews: a text mining approach
    Chatterjee, Swagato
    Ghatak, Arpita
    Nikte, Ratnadeep
    Gupta, Shivam
    Kumar, Ajay
    JOURNAL OF ENTERPRISE INFORMATION MANAGEMENT, 2023, 36 (01) : 22 - 44
  • [9] Digital Marketing Platforms and Customer Satisfaction: Identifying eWOM Using Big Data and Text Mining
    Kitsios, Fotis
    Kamariotou, Maria
    Karanikolas, Panagiotis
    Grigoroudis, Evangelos
    APPLIED SCIENCES-BASEL, 2021, 11 (17):
  • [10] Consequences of Customer Dissatisfaction in Upscale and Budget Hotels: Focusing on Dissatisfied Customers' Attitude Toward a Hotel
    Kim, Bona
    Kim, Seongseop
    Heo, Cindy Yoonjoung
    INTERNATIONAL JOURNAL OF HOSPITALITY & TOURISM ADMINISTRATION, 2019, 20 (01) : 15 - 46