Skip to main content
Mobile
  • Finance, Accounting & Economics
  • Global Business Management
  • Management, Leadership & Organisation
  • Marketing & Sales
  • Strategy
  • Technology & Operations
HS Talks HS Talks
Subjects  
Search
  • Notifications
    Notifications

    No current notifications.

  • User
    Welcome Guest
    You have Limited Access The Business & Management Collection
    Login
    Get Assistance
    Login
    Forgot your password?
    Login via your organisation
    Login via Organisation
    Get Assistance
Finance, Accounting & Economics
Global Business Management
Management, Leadership & Organisation
Marketing & Sales
Strategy
Technology & Operations
You currently don't have access to this journal. Request access now.
Practice paper

Mining online comments to understand customer satisfaction with hotel technologies: A comparison of hotels in Beijing and Washington, DC

Minyi Zheng, Shiang-Lih Chen Mccain, Jeffrey C. Lolli and Ping-Ho Ting
Applied Marketing Analytics: The Peer-Reviewed Journal, 5 (1), 69-82 (2019)
https://doi.org/10.69554/WVCW4357

Abstract

For hotel customers, satisfaction with amenities has long been a key factor in the stay experience. Using content analysis from 2,100 TripAdvisor reviews of hotels in Washington, DC, USA and Beijing, China, this study evaluates how various categories of hotel technology influence the satisfaction of hotel customers. Of the five categories of hotel technology considered (ie basic in-room, entertainment, business, comfort and mobile technologies), the study finds that entertainment technology is the most important. The results also indicate that comfort technology is considerably more important for hotel customers in Washington, DC than for hotel customers in Beijing. In addition to providing a research framework, this study provides a practical application for hotel managers to analyse guest comments to address customer complaints and enhance customer satisfaction at a location-specific level. Hotel managers can easily adopt the methodology to analyse property-specific customer data without substantial difficulty. Such data can then be used to meet customer needs and enhance customer satisfaction through the provision of technology that guests genuinely value. It can also assist managers in developing better marketing strategies for their hotels.

Keywords: online reviews; hotel technology; customer satisfaction; marketing analytics

The full article is available to subscribers to the journal.

Already a subscriber? Login or review other options.

Author's Biography

Minyi Zheng is a guest service representative at Marriott Philadelphia Airport. She has a master’s degree in hospitality and tourism from Widener University and a bachelor’s degree in business administration from Guangdong University of Technology. Her career interests include marketing and revenue management.

Shiang-Lih Chen Mccain is an assistant professor of marketing at Colorado Mesa University. Her research interests include the consumer buying decision process, service quality, customer satisfaction, customer loyalty and service recovery. She received her PhD in hotel administration from University of Nevada-Las Vegas.

Jeffrey C. Lolli is an associate professor at Widener University, where he coordinates the Tourism and Hospitality Management programme. He has a doctorate in higher education leadership from Widener University, and specialises in teaching operations management and human capital. His research interests include tourism and hospitality operations management, and customer and organisational behaviour/dynamics. He also has more than 20 years’ experience working in the hospitality industry in various operational management positions.

Ping-Ho Ting is a professor in the Department of Hospitality Management and Department of Leisure Studies and Tourism Management at National Chi Nan University. Dr Ting’s major research interests include enterprise resource planning, data mining and user behaviour on the web. His current research activities involve intelligent systems and hospitality information systems. His work has been published in numerous peer-reviewed journals worldwide

Citation

Zheng, Minyi, Chen Mccain, Shiang-Lih, Lolli, Jeffrey C. and Ting, Ping-Ho (2019, May 9). Mining online comments to understand customer satisfaction with hotel technologies: A comparison of hotels in Beijing and Washington, DC. In the Applied Marketing Analytics: The Peer-Reviewed Journal, Volume 5, Issue 1. https://doi.org/10.69554/WVCW4357.

Options

  • Download PDF
  • Share this page
    Share This Article
    Messaging
    • Outlook
    • Gmail
    • Yahoo!
    • WhatsApp
    Social
    • Facebook
    • X
    • LinkedIn
    • VKontakte
    Permalink
cover image, Applied Marketing Analytics: The Peer-Reviewed Journal
Applied Marketing Analytics: The Peer-Reviewed Journal
Volume 5 / Issue 1
© Henry Stewart
Publications LLP

The Business & Management Collection

  • ISSN: 2059-7177
  • Contact Us
  • Request Free Trial
  • Recommend to Your Librarian
  • Subscription Information
  • Match Content
  • Share This Collection
  • Embed Options
  • View Quick Start Guide
  • Accessibility

Categories

  • Finance, Accounting & Economics
  • Global Business Management
  • Management, Leadership & Organisation
  • Marketing & Sales
  • Strategy
  • Technology & Operations

Librarian Information

  • General Information
  • MARC Records
  • Discovery Services
  • Onsite & Offsite Access
  • Federated (Shibboleth) Access
  • Usage Statistics
  • Promotional Materials
  • Testimonials

About Us

  • About HSTalks
  • Editors
  • Contact Information
  • About the Journals

HSTalks Home

Follow Us On:

HS Talks
  • Site Requirements
  • Copyright & Permissions
  • Terms
  • Privacy
  • Sitemap
© Copyright Henry Stewart Talks Ltd

Personal Account Required

To use this function, you need to be signed in with a personal account.

If you already have a personal account, please login here.

Otherwise you may sign up now for a personal account.

HS Talks

Cookies and Privacy

We use cookies, and similar tools, to improve the way this site functions, to track browsing patterns and enable marketing. For more information read our cookie policy and privacy policy.

Cookie Settings

How Cookies Are Used

Cookies are of the following types:

  • Essential to make the site function.
  • Used to analyse and improve visitor experience.

For more information see our Cookie Policy.

Some types of cookies can be disabled by you but doing so may adversely affect functionality. Please see below:

(always on)

If you block these cookies or set alerts in your browser parts of the website will not work.

Cookies that provide enhanced functionality and personalisation. If not allowed functionality may be impaired.

Cookies that count and track visits and on website activity enabling us to organise the website to optimise the experience of users. They may be blocked without immediate adverse effect.