A study of the functionality of hotel websites in mainland China and the United States

A study of the functionality of hotel websites in mainland China and the United States

Rob Law


This paper reports on a study that applied the newly developed technique of measuring the incremental performance of websites to evaluate the websites of hotels in mainland China and the United States. On the basis of a conceptual framework that includes five dimensions of functionality, sixty hotel websites in mainland China and the U.S. were evaluated. The empirical findings indicate that the websites of the hotels in the U.S. significantly outperform their mainland China counterparts in four of the five dimensions. In addition, the overall performance score for hotel websites in mainland China is significantly lower than the corresponding number for the websites of hotels in the U.S.


The Internet has been changing the life styles of people, from methods of searching information to purchasing products and services. E-commerce, in particular, has become an essential part of Internet applications (Cox, 2003). In the United States, almost two-thirds of Internet users have made online purchases (Ipsos, 2002). In the context of the hotel industry, given the dramatic growth of the Internet, hotel guests and lodging companies can largely rely on the Internet as a major medium for the dissemination of information and for conducting online transactions (Jeong and Lambert, 2001).

Internet applications offer many advantages to the hotel industry. Morrison, Taylor, Morrison, and Morrison (1999) pointed out that web materials are available in various formats and languages, and with no geographical or time limitations. Hoteliers can therefore effectively pursue niche markets on the web and can substantiate their unique differences on their websites through the use of photographs, text, graphics, animation, testimony, awards, and other means. Hotels can also provide special offers or deals to online customers by offering information related to the needs and interests of their customers. Small hotels can compete in cyberspace by forming an unlimited number of Internet alliances on the web through reciprocal hyper links. In short, having a web presence brings benefits to hotels in the form of lower distribution costs, revenue growth, niche marketing, improved customer satisfaction and increased customer loyalty, improvements in quality, and the ability to address other critical business or customer needs (Morrison et al., 1999).

A hotel website is not only a place where a company places information about its products and services; a website also has a commercial value in terms of helping a hotel make a profit (Law and Leung, 2000). At present, many hotels have established online reservation systems so that online users can book hotel rooms directly from the Internet. Well-designed websites, with useful information provided to customers and extra benefits available to customers when using the online systems, can help increase sales volumes and improve the reputation of a hotel. If online users do not consider a hotel’s website to be useful, the resources that were invested in creating the site will be wasted. More importantly, a negative impact could result if customers are not satisfied with the hotel’s Internet services.

Although many hospitality researchers seem to realize the importance of the Internet for a hotel’s business strategy, only a limited number of studies have been conducted to examine hotel websites, especially the contents and features that hotels are implementing on their websites. This research attempts to investigate and evaluate the functionality performance of hotel websites, and to examine the contents of websites in the hotel sectors of mainland China and the United States, the regions with the fastest growth in Internet applications in the world. Specifically, the primary objective in this research is to measure the performance of selected hotel websites in mainland China and the U.S., and to compare and contrast their contents. The newly developed technique of measuring the incremental performance of websites (Chung and Law, 2003; Law and Chung, 2003) is used in this study to evaluate the websites. Following the definition of Lu and Yeung (1998), functionality relates to the extent to which a website provides sufficient information about the products/services being promoted.

Mainland China is chosen in this study because of the tremendous rate at which the Internet has grown in this region. In 1999, the population of Internet users in mainland China was about four million in a country of 1.25 billion people (Runckel and Associate, 1999). In 2001, this figure was 33.7 million–the world’s fastest growth rate (eTForcasts, 2003).

The United States is included in this study because of its leading position in Internet applications. In 2001, there were 148.9 million Internet users in the United States, representing more than half of US population (eTForcasts, 2003). The United States leads the world in Internet use, with 72% of American adults having had some online experience (Ipsos, 2002). In 2002, more than one-third of Americans used the Internet to search for information on products and services, up from 26% in 2000; and 39% of these Internet users made online purchases (CyberAtlas, 2002; eTForecasts, 2003).

Having introduced the research background, the following section reviews the related literature on Internet marketing and website analysis in the context of hospitality and tourism. The section on methodology then follows, which presents the procedures of sampling, data collection, and data analysis. After that, there is a findings and discussion section, in which the empirical results are analyzed. The last section concludes the study, and suggests future possibilities for research.


2.1 Hospitality Internet Marketing

The information-intensive nature of the hospitality industry suggests that the Internet and web technology can play an important role in the promotion and marketing of destinations (Doolin, Burgess, and Cooper, 2002). Hospitality is unique in that it only exists as information at the point of sale and cannot be sampled before the purchase decision is made. The information-based nature of the hospitality industry means that the Internet, which offers a global reach and has multimedia capabilities, is an increasingly important means of promoting and distributing hospitality and tourism services (Walle, 1996). The ease of use, interactivity, and flexibility of web-based interfaces suggest an allied and important role for Internet technology in the marketing of destinations. At present, most major hospitality websites are moving from simply broadcasting information to enabling users interact with their websites. This, in turn, allows a hospitality organization to allow customers to participate, to capture information about their preferences, and to use this information to provide personalized communications and services. The content of hotel websites is particularly important because it directly influences the perceived image of the hotel and thus creates a virtual experience for potential consumers. Eventually, the experience of a customer can be greatly enhanced (Cano and Prentice, 1998; Gretzel, Yuan, and Fesenmaier, 2000).

Using the web to make travel arrangements is the Internet’s second-largest commercial area, after the sale of computer technology (Law and Leung, 2000). It has been forecasted that U.S. online sales and reservations for leisure travel will rise from US$12.2 billion in 2000 to US$32.7 billion in 2005, representing 22% of the sales in the industry (Forrester Research, 2000). eTForecasts (2003) also predicts that, by 2010, most developed countries will have penetration scenarios similar to that of the U.S. In other words, there is a huge potential online market in hospitality and tourism.

2.2 Analysis of Previous Research Hospitality and Tourism Websites

Murphy, Forrest, Wotring, and Brymer (1996) analyzed the websites of thirty-six hotels, including twenty chain hotels and sixteen independent hotels, and identified thirty-two separate features contained in these websites. The selected hotel websites were visited to record the features offered in each website. The features were then grouped into the following four broad categories: promotion and marketing, service and information, interactivity and technology, and management. Research findings indicated that the most effective hotel websites are those that give the customers the easiest, most rewarding, access to relevant and related information.

A similar study was conducted by Weeks and Crouch (1999), which examined the content of Australian-based tourism and hospitality websites. The approach adopted in the research was based on the content analysis of Murphy et al. (1996). The researchers had modified the features of the website to thirty-three attributes and classified them into four major categories. These features were then utilized to analyze one hundred and twenty websites in six tourism and hospitality sectors. Each sector was then compared to find similarities and differences in the items included in these sites. The empirical findings showed that the accommodation sector was less likely than other sectors to inform online visitors about other accommodation or tourism sites.

Law and Leung (2000) performed a content-based analysis to examine the web-based online reservation services of thirty airlines. Their study found that four dimensions contributed to a successful airline website. These included the availability of product information, the provision of extra benefits, the fast loading speed of web pages, and the existence of additional services and facilities to Internet customers. Attributes to evaluate efficiency were used to analyze the online reservation services of the airlines. The collected data were analyzed and compared among selected airlines in different regions. The results revealed that North American websites outperformed their European and Asian counterparts.


The methodological approaches used in this study mainly followed the technique of measuring the incremental performance of websites (Law and Chung, 2003; Chung and Law, 2003) and content analysis (Morrison et al., 1999). In addition, both primary and secondary data were collected.

The purpose of this research is to evaluate the content of hotel websites in mainland China and the United States. The five dimensions proposed in Law and Chung’s (2003) study were adopted for content analysis. These dimensions comprised Facilities Information, Customer Contact Information, Reservations Information, Surrounding Area Information, and Management of Website. Table 1 shows the framework of measuring a hotel’s website. There were a total of 39 items in the questionnaire, which represented the perceptions of customers of the quality of hotel websites.

The research process was divided into three parts. The first part involved experienced users of hotel websites, who ranked the importance of the five dimensions and their associated attributes. The second part of the research computed weighted scores for all dimensions and attributes. Lastly, performance scores for all dimensions, as well as the overall scores for the hotel websites, are calculated.

3.1 Hotels Chosen for Analysis

In this research, a total of 60 hotel websites were selected for analysis: 30 hotels in Los Angeles and New York, the largest cities in the United States; and 30 hotels in Shanghai and Beijing, the largest cities in mainland China. The hotel websites were randomly selected from www.eexpedia.com, a major, fast-growing, and highly praised travel portal. Since lower-ranked hotels do not have enough resources to efficiently utilize the web, all of selected hotel websites were those that were three-star or above.

3.2 Data Collection

The first phase of data collection was carried out in Hong Kong using a questionnaire. By a convenience sampling in late-2002, the questionnaires were distributed to fifty hotel customers, who had experience in using hotel websites. Thirty-eight usable questionnaires were received. In this phase, the respondents were requested to rank their perception of the importance of all dimensions and their attributes. For instance, each respondent was asked to rank the importance of the ten attributes from 1 to 10 in the dimension of Reservations Information. Using hotel customers to rank the dimensions and attributes can actually enhance the descriptive capability of the model, as the original approach proposed by Law and Chung (2003) and Chung and Law (2003) only used hotel practitioners to evaluate the model.

The second phase of data collection was carried out in February to April 2003, between 8:00 p.m. to 10:00 p.m. (Hong Kong Time). At this stage, secondary data were collected from the Internet. Since hotel websites are updated regularly, data were collected within a short period of time in order to retrieve consistent information for fair comparison. Two researchers evaluated the selected hotel websites by assigning a value to each of the thirty-nine attributes using a five-point judgmental rating scale, by adopting the questionnaire used in the first phase. Wan’s (2002) two independent evaluation processes were applied to detect and eliminate potential bias or misinterpretation. In addition, to avoid unnecessary extra variability, the same computer hardware configuration, Internet Service Provider (ISP), and Internet Brower were used throughout the entire period of data collection.

3.3 Importance Rating

On the basis of the collected data, a mean score was calculated for each attribute. In order to reflect a weighted value of importance for further analysis, the mean of the attribute was transformed to a weighted score in the following way (equation 1):

n = Number of attributes in a dimension

[M.sub.i] = The mean score for attribute i for i = 1,2, … n

[W.sub.i] = Weighing Score of attribute i

W i = (1 + n – Mi)/[n.summation over j = 1] M j … (1)

3.4 Performance Rating

The performance of each attribute was defined as the measurement of the richness of the information in the attribute. A score of performance was used to indicate the performance of the attribute. To facilitate the elements of customer perception, the score was calculated by combining the average weighted score and the score of the attributes of the website. The score of performance was then multiplied by 20 in order to transform the score from a 5-point scale to a commonly used 100-point scale. This calculation is presented in equation 2.

[W.sub.i] = Weighing Score of attribute i

[S.sub.i] = The mean of the ith attribute score for i = 1, 2, … n

[P.sub.i] = Performance Score of attribute i

[P.sub.i] = 20 x [W.sub.i] x [S.sub.i] … (2)


AS previously stated, the respondents were asked to rank thirty-nine features of hotel websites, which were grouped into five dimensions according to their perceived importance. The results from the respondents concerning the importance ratings of the dimensions and attributes, and the average weighted scores, which were arranged in order of their importance, are summarized in Tables 2 to 7.


1. The dimensions were ranked with “1” as the most important and “5” as the least important.

2. The variable percentage is based on a proportion of 100%, and the total average weighted score for the dimensions is 100.

3. The Average Weighted Score was computed using equation 1.

4.1 Dimensions

The importance ratings of the five dimensions are shown in Table 2, which indicate that the most important attributes were “Facilities Information” and “Reservations Information” with overall mean values of 1.68 and 2.37, respectively. This finding reveals that customers are more interested in knowing information about the product when they are using hotel websites. On the contrary, the least important attributes are the “Surrounding Area Information” and “Management of Website”, which are rated with overall mean values of 3.84 and 3.97, respectively.

The importance rating and average weighted score for Facilities Information are listed in Table 3, and are arranged in order of importance. The attributes that are considered as the most important in this dimension are “Photos of Hotel Features”, “Hotel Promotions”, and “Hotel Descriptions.” The least important attributes are “Meeting Planner / MICE”, “Frequent Guest Program”, and “Employment Opportunities”.

Similarly, Table 4 shows the result of the importance ratings and average weighted scores for the attributes in Customer Contact Information. As shown in Table 4, the most important attributes are “E-mail Address” and “Telephone Number” with mean values of 1.89 and 2.58 respectively. The least important attributes are “What’s New / Press Release” with a mean value of 6.63.

The attributes of Reservations Information include features that are related to the information necessary to make online bookings of hotel rooms. The ten attributes that have been included, and their perceived importance and weighted scores, are presented in Table 5. The results show that the most important features are “Online / Real Time Reservation”, “Security Payment Systems”, and “Check Rates and Availability”. The least important attributes are “Special Request Forms” and “Reservation Policies.”

A total of five attributes are included in Surrounding Area Information. The results are shown in Table 6, which indicate that the most important features are “Main Attractions of the City” and “Airport Information”. The least important features are “General Information on the Country” and “Public Holidays.”

Lastly, the importance rating and average weighted scores for Management of Website are listed in Table 7. Those attributes that are considered the most important for Website Management are “Up-to-date information on the Site” and “Search Capability”. The least important attributes are “Site Map” and “Links to Partners.”

4.2. Analysis of the Performance of Websites in Mainland China and the United States

The overall performance scores for the selected hotel websites in mainland China and the U.S. are presented in Table 8.

As presented in Table 8, hotel websites in the U.S significantly outperform in all but one of the five dimensions, and in overall performance. The only dimension that does not show any significant difference is Surrounding Area Information. In addition, the U.S. hotel websites receive an overall average score of 53.68, whereas the corresponding number for mainland China is 44.99. In other words, the websites of hotels in mainland China still fall behind those of the U.S. in terms of functionality.


With the rapid advances in interactive technology and the growing popularity of the web, Internet shopping will be the next revolution in direct marketing. This growing popularity in online shopping directly applies to the hotel industry. Hotels have been attempting to establish their brand names and to enlarge their market segments through the Internet. Apparently, hotels in different regions have different levels of Internet application. The empirical results of this research show that the websites of hotels in the U.S. are more comprehensive than those in mainland China. In other words, online marketing values are used more effectively by hotel websites in the U.S.

This research has provided a modified framework for measuring the functionality of hotel websites. The related prior studies have predominately focused on the performance of websites in one region. One limitation of these prior studies is their inability to make a comparison between different regions. The current study attempts to measure the functionality of hotel websites in two dissimilar regions. Statistical analyses reveal significant differences between the selected hotel websites in mainland China and the U.S. in all but one dimension. It can be concluded that the websites of hotels in the U.S are ahead of their mainland China counterparts in terms of Internet applications. In other words, online marketing values are used more effectively in well-developed countries.

Studies on hotel websites are still at an early stage. Many questions have yet to be answered. One possibility for future research is to extend the work to other tourism-related sectors like car rental or air-ticket reservations services. Another area for future research is to examine hotel websites in other regions. Lastly, it would be valuable to examine other factors that affect the online shopping behavior of hotel customers. The hospitality industry requires new marketing strategies to meet ever-changing customer behavior. The Internet can certainly serve as a powerful tool by providing a good opportunity to meet the new challenges.



Number of

Dimension Description Attributes

Facilities General description of the hotel 11

Information property and information on the facili-

ties and services available to guests.

Customer Contact Attributes that improve direct communi- 8

Information cation between the hotel and guests.

Reservations Facilities and services available on 10

Information the website in relation to making


Surrounding Area Information related to the environment, 5

Information such as sightseeing, weather, and


Management of Attributes to allow customers to easily 5

Website access relevant and up-to-date informa-



Importance Average Weighted Score

Variables Rating Mean % [W.sub.i]

Facilities Information 1.68 28.80

Reservations Information 2.37 24.20

Customer Contact Information 3.13 19.13

Surrounding Area Information 3.84 14.40

Management of Website 3.97 13.53


Importance Average Weighted Score

Variables Rating (Mean) (%) [W.sub.i]

Photos of Hotel Features 2.63 14.20

Hotel Promotions 3.53 12.83

Hotel Descriptions 4.37 11.56

Hotel Facilities 4.58 11.24

Virtual Tours 4.76 10.97

Guest Room Facilities 5.18 10.33

Restaurant 5.50 9.85

Hotel Location Maps 7.21 7.26

Meeting Planner/ MICE 8.00 6.06

Frequent Guest Program 9.47 3.83

Employment Opportunities 10.71 1.95



Importance Average Weighted Score

Variables Rating (Mean) (%) ([W.sub.i])

E-mail Address 1.89 19.75

Telephone Number 2.58 17.83

Fax Number 3.44 15.44

Hotel Address 3.55 15.13

Online Forum 5.74 9.06

Frequently Asked Questions 5.89 8.64

Feedback Form 6.26 7.61

What’s New / Press Release 6.63 6.58


Average Weighted

Importance Score (%)

Variables Rating (Mean) ([W.sub.i])

Online / Real-time Reservation 2.47 15.51

Security Payment Systems 3.13 14.31

Check Rates and Availability 4.24 12.29

Payment Options 4.79 11.29

Room Rates 4.87 11.15

Check In and Check Out Time 5.11 10.71

View or Cancel Reservations 6.37 8.42

Worldwide Reservations Phone 7.34 6.65


Special Request Forms 8.16 5.16

Reservations Policies 8.66 4.25



Average Weighted

Importance Score (%)

Variables Rating (Mean) ([W.sub.i])

Main Attractions of the City 1.79 28.07

Airport Information 2.05 26.33

Transportation 2.37 24.20

General Information on the Count 4.26 11.60

Public Holidays 4.53 9.80


Average Weighted

Importance Score (%)

Variables Rating (Mean) ([W.sub.i])

Up-to-date Information on the Site 1.61 29.27

Search Capability 1.82 27.87

Multilingual Site 3.11 19.27

Site Map 4.16 12.27

Links to Partners 4.32 11.20


Mean Score


Mainland China United States

n = 30 n = 30

Facilities Information 14.14 16.83


Information 13.04 15.78

Customer Contact

Information 7.79 9.43

Surrounding Area

Information 5.40 5.84

Management of

Website 4.64 5.86


Performance 44.99 53.68

Variables F-value Sig.

Facilities Information 1.67 0.000 **


Information 1.46 0.000 **

Customer Contact

Information 2.86 0.000 **

Surrounding Area

Information 0.59 0.058

Management of

Website 1.14 0.000 **


Performance 3.38 0.000 **

** significant at a = 0.05


This project is partly supported by a research grant that is funded by the Hong Kong Polytechnic University (under contract number: G-T868)


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Dr. Rob Law and Ms. Catherine Cheung are faculty members at Hong Kong Polytechnic University’s School of Hotel & Tourism Management. Mr. Daniel Ho is affiliated with University of London.

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