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

被引:288
|
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
  • [31] Combined Text-Mining/DEA method for measuring level of customer satisfaction from online reviews
    Park, Jaehun
    EXPERT SYSTEMS WITH APPLICATIONS, 2023, 232
  • [32] Service quality as a determinant of customer satisfaction and resulting behavioural intentions: A SEM approach towards Malaysian resort hotels
    Ali, Faizan
    TOURISM, 2015, 63 (01): : 37 - 51
  • [33] STUDY OF TOURIST SATISFACTION AT BUSAN'S TEMPLES: A QUANTITATIVE TEXT MINING APPROACH
    Lim, Varren Christian
    Handani, Narariya Dita
    INTERNATIONAL JOURNAL OF BUSINESS AND SOCIETY, 2024, 25 (03): : 930 - 946
  • [34] Analyzing Customer Experience Feedback Using Text Mining: A Linguistics-Based Approach
    Ordenes, Francisco Villarroel
    Theodoulidis, Babis
    Burton, Jamie
    Gruber, Thorsten
    Zaki, Mohamed
    JOURNAL OF SERVICE RESEARCH, 2014, 17 (03) : 278 - 295
  • [35] CUSTOMER PRODUCT EXPERIENCE ANALYSIS USING TEXT MINING: A NEURO LINGUISTIC PROGRAMMING APPROACH
    Mangaonkar, Nikhita
    Sirsat, Sudarshan
    2017 INTERNATIONAL CONFERENCE ON COMPUTING METHODOLOGIES AND COMMUNICATION (ICCMC), 2017, : 216 - 219
  • [36] Exploring antecedents impacting user satisfaction with voice assistant app: A text mining-based analysis on Alexa services
    Kumar, Anand
    Bala, Pradip Kumar
    Chakraborty, Shibashish
    Behera, Rajat Kumar
    JOURNAL OF RETAILING AND CONSUMER SERVICES, 2024, 76
  • [37] RESEARCH ON E-COMMERCE CUSTOMER SATISFACTION EVALUATION METHOD BASED ON PSO-LSTM AND TEXT MINING
    Yang, Qin
    3C EMPRESA, 2023, 12 (01): : 51 - 66
  • [38] Using the fuzzy weighted association rule mining approach to develop a customer satisfaction product form
    Kang, Xinhui
    Porter, Caroline Samantha
    Bohemia, Erik
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2020, 38 (04) : 4343 - 4357
  • [39] Understanding Antecedents That Affect Customer Evaluations of Head-Mounted Display VR Devices through Text Mining and Deep Neural Network
    Maeng, Yunho
    Lee, Choong C.
    Yun, Haejung
    JOURNAL OF THEORETICAL AND APPLIED ELECTRONIC COMMERCE RESEARCH, 2023, 18 (03): : 1238 - 1256
  • [40] Pricing-Based Demand Response for a Smart Home With Various Types of Household Appliances Considering Customer Satisfaction
    Liu, Yi
    Xia, Liye
    Yao, Guodong
    Bu, Siqi
    IEEE ACCESS, 2019, 7 : 86463 - 86472