The objective of this chapter is to evaluate user satisfaction with Web portals. To achieve this goal, we scan the information systems literature for research on portals and other factors that influence satisfaction. Few studies have investigated this issue. So, in this section we review information systems literature on three separate topics that are of interest in this research: (1) Web portals, (2) user satisfaction with information systems, and (3) factors that influence user interaction with information systems. While we have discussed the importance of Web portals and user satisfaction in this study, we have to understand that this interaction does not take place in a vacuum. A number of other factors, such as user age, education, and experience can influence satisfaction with Web portals. In the third sub-section (factors that influence user interaction with information systems), we will identify other factors that are important to our study. In this sub-section we also propose our research hypotheses. We now consider each of these topics separately.
Web portals have been defined in a number of different ways. A portal is described as a Web “supersite” with a collection of links to popular Web services on the Internet. A portal is also defined as “a term, generally synonymous with gateway, for a World Wide Web site that is or proposes to be a major starting site for users when they get connected to the Web or that users tend to visit as an anchor site.”
Portals can be classified into three types based on the functions they perform: horizontal portals, vertical portals and enterprise portals. A Horizontal portal is a Web site that provides consumers with access to a number of different sites in terms of content and functionality. This portal is generally a consumer portal that can be personalized and customized by the user. Horizontal portals are also called general public portals or mega portals. My Yahoo! and My Excite are examples of horizontal portals. A Vertical portal or vortal focuses on a specific community of users (Isaacs, 1999). This portal is geared towards a narrow audience or a community with specific interests, such as, consumer goods, computers, retail, brokerage services, and banking. An enterprise portal (also called a corporate portal) provides access to proprietary internal information within a company via a company intranet and access to selected Internet sites. For example, employees can have access to their pay stubs or retirement contributions through an enterprise portal. There are other specialized portals based on technology or location that have been identified in information systems research. Examples of such portals are: WAP portals that use mobile technology, and embedded or appliance portals where the portal is embedded in an appliance such as WebTV and OnStar in vehicles.
In this research we restrict our discussion to the two major types of Web portals: horizontal portals and vertical portals. Although we find a number of papers in the information systems literature that classified Web portals, we fail to identify research that investigated use of Web portals. In the next section we review the literature on user satisfaction with information systems.
User satisfaction has received considerable attention of researchers since the 1980s as an important surrogate measure of information systems success (Aladwani and Palvia, 2002; Aladwani, 2002; Bailey and Pearson, 1983; Goodhue and Thompson, 1995). While most user satisfaction instruments were developed for transaction processing and traditional systems that were not Web-based at the time of development, some instruments have been successfully validated in an Internet-based environment. This validation is important if we assume that the Internet provides a unique environment that makes a user’s experience considerably different from that of a traditional information system. In the paragraphs that follow we provide a review of literature on user satisfaction primarily from a measurement perspective.
The user satisfaction measurement literature has been dominated by two scale development studies, one by Bailey and Pearson (1983) and the other by Doll and Torkzadeh (1988). Bailey and Pearson first identified 36 factors that could influence satisfaction from a survey of 22 studies done earlier. They put special emphasis on the dimensionality and intensity of every individual’s reaction to each of the factors identified. They used a semantic differential technique with four bipolar adjective pairs and a 7-interval scale. They explained this technique by an example, “… the meaning of “format of output” (a factor) could be measured between the pairs: good vs. bad, simple vs. complex, readable vs. unreadable, and useful vs. useless (Bailey and Pearson, 1983; Aladwani, 2002). Two additional scales were added for each factor: (1) satisfactory vs. unsatisfactory and (2) important vs. unimportant. Validity and reliability of this instrument was checked using a sample of 32 middle managers (these were managers who had previously been interviewed in the factor-identification phase).
A review of existing literature shows that applications of the Bailey and Pearson user satisfaction and the revised User Information Satisfaction scale have been limited. One of the reasons cited in other research is that the scale was a semantic differential rather than a Likert-type scale.
Doll and Torkzadeh (1988) designed and validated a 12-item instrument to measure enduser satisfaction called the End User Computing Satisfaction, or EUCS, instrument. They proposed a second order factor model of end-user computing satisfaction, which consisted of five first-order factors: content, accuracy, format, ease of use and timeliness. These factors were measured using 12 items. The second-order factor was interpreted as end-user satisfaction. In their instrument, Doll and Torkzadeh added two global measures of perceived overall satisfaction and success to serve as a criterion. Their instrument was regarded as comprehensive because they reviewed previous work on user satisfaction in their search for a comprehensive list of items. The end-user satisfaction construct was developed with a five point Likert-type scale (1 = almost never; 2 = some of the time; 3 = about half of the time; 4 = most of the time; and 5 = almost always). In their original study, Doll and Torkzadeh, validated this instrument using end user data from 44 organizations. A number of studies have confirmed the validity of this instrument (Doll and Torkzadeh, 1991; Doll et al., 1994; McHaney and Cronan, 1998; McHaney et al., 1999; Chen et al., 2000; McHaney et al., 2002).
We use Doll and Torkzadeh’s satisfaction instrument and the overall satisfaction criteria for our research. We choose this measure for our study because it is a validated instrument that has been widely used in information systems research.
Factors Influencing User Interaction
Based on our review of literature in the area of Web portals, user satisfaction and factors influencing user interaction with information system, we identify that demographic factors such as gender, age, experience and use of Web portals will influence an individual’s satisfaction with the system. This essentially means that gender, age, experience and use of Web portals are independent variables in our research model, and satisfaction with the Web portal is our single dependent variable. In the paragraphs that follow we provide evidence from the information systems literature to support our choice of variables and propose hypotheses for each combination of independent and dependent variables.
A number of factors influence user interaction with computer systems. In a study of knowledge and information workers in a university setting, Harrison and Rainer (1992) investigated the role of individual differences in skill on end-user computing. They found that factors such as male gender, lower age, more experience with computers, less anxiety towards computers, higher levels of confidence in using computers, lower math anxiety, and creative cognitive style contribute towards higher computer skills. Ford et al. (2001) in a similar study investigated individual differences in Internet searching. They looked at cognitive styles, levels of prior experience, Internet perceptions, age and gender. They found that effectiveness in Web searching is related to male gender, low cognitive complexity, and cognitive style. Males having higher computer skills can also be due to the finding that males are more likely to have relevant computer literacy and programming courses than females (Foster et al., 2003). Although men are found to have a better educational background and computer skills, Spennemann and Atkinson (2003) found that female students tend to use e-mail more than males. Simon (2001) investigated satisfaction with Web sites on a global scale. This study focused on perception and satisfaction levels of subjects from different cultural backgrounds on four Web sites. The research found differences among different culture clusters, and between males and females in certain cultures.
So far we have identified research that has investigated the role of gender on user satisfaction. We now turn our attention to the type of portal. The type of portal is important since there is a difference between horizontal and vertical portals. While horizontal portals provide personalization and customization capabilities, these mega portals do not offer a sense of community or shared common interest that is the focus of vertical portals. Therefore, we expect user satisfaction to be affected by gender of the individual and the type of portal. Moreover, if we control for type of portal, we propose that there will be a difference in satisfaction between the genders. Similarly, we can expect difference in satisfaction based on the type of portal used if we control for gender. Therefore, we propose our hypotheses as follows:
Hypothesis 1: Satisfaction with a Web portal will be affected by gender and the type of portal used.
Hypothesis 1A: Controlling for type of portal used, there will be a difference in satisfaction of males and females with the portal.
Hypothesis 1B: Controlling for gender, there will be a difference in satisfaction based on the type of portal used.
Age of the user is also an important factor in computer interaction. Couper and Rowe (1996) examined respondent reaction to a self-administered component of a computer-assisted personal interview survey. They found that respondents’ age, education and computer experience influence their decision to self-complete the computer-assisted self-interview items. As mentioned earlier, Ford et al. (2001) also investigated the role of age in the retrieval effectiveness of information from a search engine. Therefore, we state our age-related hypotheses as follows:
Hypothesis 2: Satisfaction with a Web portal will be affected by age and the type of portal used.
Hypothesis 2A: Controlling for type of portal used, there will be a difference in satisfaction of various age groups with the portal.
Hypothesis 2B: Controlling for age, there will be a difference in satisfaction based on the type of portal used.
Experience is another factor that has been studied in the area of interaction with computer systems. In a study of the relationships between user satisfaction, job satisfaction changes, user’s behavior and demographics in an Internet-oriented workplace, Simmers and Anandarajan (2001) found that individuals with more training and experience have higher levels of user satisfaction. But, they did not find differences in the user satisfaction between men and women. We state our hypotheses as follows:
Hypothesis 3: Satisfaction with a Web portal will be affected by experience and the type of portal used.
Hypothesis 3A: Controlling for type of portal used, there will be a difference in satisfaction among different experience levels.
Hypothesis 3B: Controlling for experience, there will be a difference in satisfaction based on the type of portal used.
Next we propose that the extent of use of the Internet or Web and type of portal will impact satisfaction with portals. Our justification is as follows: as individuals spend more time using the Internet or the World Wide Web, they will have an increasing need to use a portal. A portal will provide a user with the ability to organize and personalize the information they have or need from the Web. For example, a user may use the Web to access credit information on a number of their credit cards. Rather than visiting different bank sites to access credit card balance and payment information, the user may provide all login information to a portal site, and this site may aggregate balance and payment information from multiple sites and present it to the user on one page. Therefore, we feel that as a user uses the Web more, the better informed or educated the person will be, and this will affect the individual’s satisfaction with a Web portal. Therefore, we state our hypotheses as follows:
Hypothesis 4: Satisfaction with a Web portal will be affected by the extent of Web use and the type of portal.
Hypothesis 4A: Controlling for type of portal used, there will be a difference in satisfaction based on the extent of Web use.
Hypothesis 4B: Controlling for Web use, there will be a difference in satisfaction based on the type of portal.
In summary, we have identified four factors that influence user satisfaction with Web portals. We have proposed research hypotheses for each of these factors. In the next section we report on the methodology used in this study.
What is a portal anyway? http://www.acs.utah.edu/acs/news/portals.html