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Weighing of Hotel Website Dimensions and Attributes

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Weighing of Hotel Website Dimensions and Attributes aRob Law bCatherine Cheung ahmroblaw_at_polyu.edu.hk, bhmcat_at_polyu.edu.hk School of Hotel and Tourism Management – PowerPoint PPT presentation

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Title: Weighing of Hotel Website Dimensions and Attributes


1
Weighing of Hotel Website Dimensions and
Attributes
  • aRob Law
  • bCatherine Cheung
  • ahmroblaw_at_polyu.edu.hk, bhmcat_at_polyu.edu.hk
  • School of Hotel and Tourism Management
  • The Hong Kong Polytechnic University

2
Presentation Outline
  • 1. Introduction
  • 2. Methodology
  • - the survey
  • - the modeling process
  • 3. Results and Discussions
  • 4. Conclusions

3
1.1 Introduction
  • Which is the top growth driver for e-commerce?
  • Travel spending

4
1.2 Introduction
  • Online travel sales will increase from US18
    billion in 2002 to US64 billion in 2007.
  • Online hotel room bookings would grow from US5
    billion in 2001 to US14.8 billion in 2007.

5
1.3 Introduction
  • There is an increasing amount of investments on
    hotel websites.
  • The existing literature only has a limited number
    of published articles that investigated the
    performance of hotel websites.

6
1.4 Introduction
  • Many approaches of website performance
    evaluations are either lack of well-defined
    objective standard or without direct involvement
    of consumers.

These traditional techniques do not suffice to
serve benchmarking in the latest competitive
hotel business.
7
1.5 Introduction
  • This research attempts to build a multi-criteria
    decision making model that incorporates the
    opinions of hotel website users into the weights
    of hotel website dimensions and attributes, and
    focuses on the functionality component.

8
2.1 Methodology
  • The research was a component of a large-scale
    Omnibus Survey for International visitors in Hong
    Kong, which used a non-random sampling method to
    interview visitors form 7 major market regions
  • Chinese Mainland, Taiwan, Singapore,
    Malaysia, the United States, Australia, and
    Western Europe.

9
2.2 Methodology
  • The questionnaire comprised two major parts. The
    first part required respondents to assign a
    numeric percentage weight. A higher percentage
    represented that the dimension or attribute is
    more important when the respondent was
    considering making online reservations. The
    second part was to seek for demographic
    characteristics.

10
3.1 Results and Discussions
  • Most respondents were male, in the age groups of
    26-35 and 36-45, received college/university
    diploma/degree or above education, with personal
    income of US 10,000-49,999, and were mainly from
    Taiwan, the United States, and Western Europe.

11
3.2 Results and Discussions
  • Table 1 shows the Cronbachs alpha measures of
    the five dimensions. Results showed good
    reliability for all dimensions.
  • Table 1 Reliability Analysis

Dimensions Cronbachs Alpha
Reservations Information 0.8801
Facilities Information 0.8711
Surrounding Area Information 0.8666
Website Management 0.8238
Contact Information 0.7519
12
3.3 Results and Discussions
  • Table 2 lists the weights (relative importance)
    of the five dimensions
  • Table 2 Dimension Weights

Dimensions Weight (importance mean) s.t.d.
Reservations Information 22.24 5.09
Facilities Information 21.70 4.79
Contact Information 20.81 5.75
Surrounding Area Information 18.76 5.44
Website Management 16.49 5.75
13
3.4 Results and Discussions
  • Table 3 to Table 7 list attribute weights in each
    dimension.

Table 3 Attribute Weights in the Dimension of
Reservations Information
Attributes Dimension Weight (importance mean) s.t.d.
Room Rates 12.28 4.56
Check Rates and Availability 11.80 3.84
Online/Real Time Reservations 10.86 2.59
Security Payment Systems 10.33 2.90
View or Cancel Reservations 10.09 2.40
Reservation Policies 9.67 2.58
Check In and Check Out Time 9.64 2.58
Worldwide Reservations Phone Number 9.43 2.86
Payment Options 8.89 4.63
Special Request Forms 7.02 3.04
14
3.5 Results and Discussions
  • Table 4 Attribute Weights in the Dimension of
    Facilities Information

Attributes Dimension Weight (importance mean) s.t.d.
Hotel Location Maps 12.14 4.58
Hotel Features 11.91 4.63
Guest Room Facilities 11.58 4.56
Photos of Hotel Features 10.90 3.15
Hotel Descriptions 10.77 2.86
Hotel Promotions 9.20 3.47
Restaurants 8.48 2.90
Frequent Guest Program 7.68 3.54
Virtual Tours 7.58 3.19
Meeting Facilities 6.34 3.54
Employment Opportunities 3.43 3.53
15
3.6 Results and Discussions
  • Table 5 Attribute Weights in the Dimension of
    Contact Information

Attributes Dimension Weight (importance mean) s.t.d.
Telephone Number 16.80 5.09
Address 16.65 5.32
E-mail Address 15.32 4.94
Fax Number 12.22 4.90
Contact Person 11.22 4.72
Frequently Asked Questions 9.98 5.63
Feedback Form 9.27 5.55
Online Forum 8.54 4.61
16
3.7 Results and Discussions
  • Table 6 Attribute Weights in the Dimension of
    Surrounding Area Information

Attributes Dimension Weight (importance mean) s.t.d.
Transportation 22.62 8.96
Airport Information 21.32 6.32
Main Attractions of the City 20.09 5.42
General Information of the City 19.55 6.89
Public Holidays 15.15 6.67
17
3.8 Results and Discussions
  • Table 7 Attribute Weights in the Dimension of
    Website Management

Attributes Dimension Weight (importance mean) s.t.d.
Up-to-date Information on the Site 24.90 11.29
Multilingual Site 21.29 8.11
Site Map 19.44 6.55
Search Function 19.26 6.53
Links to other related businesses 15.11 7.19
18
4.1 Conclusions
  • In the context of online reservations of hotel
    rooms, the leading online travel agents like
    Expedia and Travelocity get the largest share
    from online customers.

19
4.2 Conclusions
  • Many travelers presently use the Internet to
    search and purchase travel services/products are
    discouraged with the inflexibility of many online
    travel agents, and half of the consumers who use
    online travel agents have had problems with
    website contents.

20
4.3 Conclusions
  • The findings of this research make a contribution
    for hoteliers to determine customers preference.

21
4.4 Future Research
  • To determine the rating criteria on the basis of
    hotel website users, for specific attributes.
  • To investigate the development of a future
    website measurement standard.

22
  • Thank you!
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