Information systems are expensive. The decision to install an information system necessitates a choice of mechanisms to determine whether an information system is needed, and once implemented, whether it is functioning properly or not. User information satisfaction (UIS) is one such evaluation mechanism. UIS is defined as the extent to which users believe the information system available to them meets their information requirements. UIS provides a meaningful "surrogate" for the critical but immeasurable result of an information system, namely, changes in organizational effectiveness (Baroudi, Ives & Olson, 1983).
According to Griffiths, Johnson & Hartley (2007), user satisfaction is multi-dimensional, subjective and elusive concepts to define, but in IS, user satisfaction generally taken to be a surrogate measure of success. According to researchers Wrigley et al. (1997), user satisfaction indicates that system’s objectives are being met, thereby allowing managers to differentiate between more or less successful systems. User satisfaction remains as an important research area in current IS research where IS researchers are continuing to examine the concept inordinately (DeLone and McLean 2003).
Previous investigations of the User Information Satisfaction construct have approached the definition of satisfaction from a narrow perspective. The focus was primarily on the attributes of the system, with scant attention paid to the attributes of the user or of the organizational context in which system usage occurs (Shirani, Aiken & Reithel,1994).
Meanwhile, User information satisfaction explains satisfaction as a consequence of the combination of user, organizational, and system characteristics. User and organizational characteristics combine to create a set of pre-implementation expectations regarding the information system. After implementation, the gap between the actual system characteristics and the expected characteristics forms the basis for confirmation/disconfirmation of the expectations. It is the type and degree of confirmation/disconfirmation that forms the basis for User Information Satisfaction.
User Information Satisfaction (UIS) has emerged as the major surrogate for the effectiveness of Management Information Systems (MIS) in organizations. Based on the literature, users consist of three categories: direct user, autonomous user, and indirect user. Direct user is someone who interfaces directly with the computer-based information systems, working with one or more systems, largely designed, implemented, and maintained by the MIS/Data Processing (DP) department or receives periodic computer reports. Autonomous user develops and uses simple systems and/or application programs he or she needs, either individually or in small groups of users. This class of users possesses some amount of computing skills and makes use of a variety of tools such as general purpose, commercial software, user-friendly operating systems, personal computers (PCs), workstations and higher level programming languages. The third category is indirect users which typically managers in the higher levels of the organizational hierarchy whose interface with the computer is mediated by staff analysts or assistants (Davis, C. J.1985)
Other than that, the term Computer user satisfaction (CUS) is abbreviated to user satisfaction. CUS (and closely related to the concepts such as System Satisfaction, User Satisfaction, Computer System Satisfaction, End User Computing Satisfaction) deals with user attitudes to computer systems in the context of their environments. So, in a broader sense, the definition can be extended to user satisfaction with any computer-based electronic appliance (Wikipedia).
In fact, end user computing satisfaction is an important theoretical construct because of its potential for helping us discover both forward and backward links in a causal chain (i.e. a network of cause and effect relationships that describe a large portion of the domain of MIS research) that are important to the MIS research community. Thus end user computing satisfaction is potentially both a dependent variable (when the domain of one’s research is upstream activities or factors that cause end user satisfaction) and an independent variable (when the domain of one’s research is downstream behaviors affected by end-user satisfaction) ( Doll & Torkazadeh,1991).
In this paper, the end user information satisfaction is examined as a dependent variable i.e. the factors that cause information satisfaction and comparison is done between past studies in the context of the Malaysian scenario and overseas.
2. PROBLEM STATEMENT
Malaysia is rapidly shifting its orientation into an information technology (IT) based environment, which emphasizes on the use of technology in providing information. The Multimedia Super Corridor (or MSC) established in 1998, manifests the Government commitment in leading the information based technology, be it in the world or in the region. It is envisaged that when IT is fully adopted by the Government, the E-Government status will be realized. As the Government moves towards an E-government, the private sector is also expected to move in tandem with the Government's aspiration.
Studies to evaluate IS success in Malaysia have been done by researchers like Hussein & Karim (2007) who have studied the impact of technological factors on information systems success in the electronic-government context and conceptual framework regarding corporate intranet effectiveness have been discussed in a study done by Masrek, Karim & Hussein, (2007) whereas researcher Foong (1999) examined the effect of end-user personal and system attributes on computer – based information systems success in Malaysian SMEs and Masrek, 2007 study measured campus portal effectiveness and the contributing factors. Hence, most studies done in Malaysia are confined in utilizing the user satisfaction scales developed in past studies to measure IS success i.e. it is studied as an independent variable (behaviors affected by end-user satisfaction).
Our review of the literature on user satisfaction shows that no study has specifically examined the factors that affect information satisfaction ( information satisfaction as a dependent variable) in the Malaysian context even though there is evidence from previous research, that user satisfaction is related to other factors such as user interface attractiveness, performance and navigational aids (Chiew & Salim; 2003) .
Furthermore, the existing user satisfaction scales in the IS field may not be appropriate for measuring information satisfaction for all the different IT applications involved in the IS field since most of the factors used to measure information satisfaction are for those in the end user computing (EUC) or transactional data processing (TDP) environment. For e.g. in a research done by Sugianto & Tojib 2006, the researchers commented that the existing user satisfaction scales in the IS field are considered inappropriate for measuring satisfaction with business-to-employee (b2e) portals for several reasons. First, embedded within the b2e portal are technologies with functionalities that are distinct from those employed within the end user computing (EUC) or transactional data processing (TDP) environment; that is, search and retrieval processes, work flow systems, on-line self-service applications, and collaboration tools. Second, it is evident from the IS literature that past studies barely touch on the patterns or processes that users employ to collaborate with each other an important function which can be facilitated by the b2e portal.
Since user satisfaction is an important component to measure IS success, further research needs to be done to validate the factors that effect information satisfaction (measure of information satisfaction) that is used based on the past literature specifically in the overall IS field in Malaysia and generally a revised model need to be developed that will encompass all the different IT applications and web – based IS.
3. LITERATURE REVIEW
Information is defined as data placed in a meaningful and useful context for an end user (O’Brien & Marakas, 2006). Satisfaction has been a core research topic of numerous studies from diverse theoretical perspectives. In the area of Information systems, most researchers have referred to the definition given by Bailey & Pearson (1983) who construed information satisfaction as an outcome resulting from the emotional response to the information/system attributes (Doll & Torkazadeh, 1991; Leclerq, 2007; Shaw, Delone & Niederman, 2002; Shirani, Aiken & Reitel, 1994; Wrigley et al., 1997).
User satisfaction is the sum of one’s feelings and attitudes toward a variety of factors related to the delivery of information products and services. A system without user satisfaction is less likely to be used and to produce beneficial results to a user community and the organization (Wu & Wang, 2006). The concept of user information satisfaction (UIS) has been one major subject of research for the last two decades in the field of management information satisfaction (Cho & Park, 2001). Understanding what factors impact user information satisfaction (UIS) and how they impact it, as well as developing accurate instruments to measure UIS, are goals of the body of UIS research (Shirani, Aiken & Reitel, 1994).
The information systems (IS) discipline is primarily concerned with the successful implementation of information technology (IT) in organizations. IS are an essential component of the solutions to many of the problems faced by organizations to cope with the current challenges (Bokhari, 2005). The success of information systems depends on interacting factors. The influence of theses factors varies among different organizations and even among different units within an organization.
Information satisfaction (Khosrowpour (1992) cite in Tafti) is not the only dimension of overall user satisfaction. One of the major characteristics of modern information systems is their user-interface features. This is a particularly important factor in end user computing and DSS environment. Because end users should have a high level of control in planning, development, and operations, the IS must accommodate the necessary flexibility and convenience in performing various end-user computing task.
Meanwhile Carey (1995) cite in Te’eni, Thommassin, Singh & Naganand, clarified that a user’s perception of the IS he/she is using in terms of various friendly features such as proper screen design, online assistance, error control, and flexibility may therefore have a considerable impact on the level of user satisfaction.
According to Wang, Tang & Tang (2001), the lack of consensus on a definition of satisfaction has created two serious problems for customer satisfaction research. First, developing context-specific items becomes difficult given the fact that the conceptual definition of customer satisfaction is not clear. Second, the lack of definitional and measurement standards of customer satisfaction limits theory development in this field, weakens the explanation power of any new theories, and confines the generalization of any empirical findings.
Past researches have suggested that end-user satisfaction is a critical issue in determining whether an organization’s computer based information system is successful (Montazemi, 1988). It has been reported that information systems satisfaction is composed of satisfaction with information systems’ output, satisfaction with information systems services and satisfaction with involvement in information development (Cho & Park, 2001).
Computer-based information systems are assuming increasingly important roles in day-to-day corporate management. Although they often represent a major corporate capital investment, their failure or disuse is costly not only in terms of infrastructural and operational expenditure, but more importantly in terms of lost competitive advantage. A good deal of effort has gone into defining a mechanism for measuring the "success" of an information system, with a particular emphasis on user satisfaction as a key component of success (Shirani et al., 1994).
There is a wealth of literature pertinent to user satisfaction and user satisfaction models. User Information Satisfaction (UIS) is a method for measuring user satisfaction of an information system. UIS examines the satisfaction of a whole organization. A good information system meets the requirements of a user, which reinforces the satisfaction. If the system is not good, then users will try to find an alternative way of completing their tasks without the use of the information system (Pikkarainen et al., 2006).
Bailey and Pearson (1983) defined user satisfaction as the sum of a user’s attitudes toward a variety of factors of management information systems and identified 39 factors as comprising the domain of user satisfaction ( top management involvement, organizational competition with the electronic data processing (EDP) unit, priorities determination, charge back method of payment for services, relationship with the EDP staff, communication with the EDP staff, technical competence of the EDP staff, attitude of the EDP staff, schedule of products and services, time required for new development, procession of change requests, vendor support, response/turnaround time, means of input/output with EDP center, convenience of access, accuracy, timeliness, precision, reliability, currency, completeness, format of output, language, volume of output, relevancy, error recovery, security of data, documentation, expectations, understanding of systems, perceived utility, confidence in the systems, feeling of participation, feeling of control, degree of training, job effects, organizational position of the EDP function, flexibility of systems and integration of systems). In this study it was also shown that the importance of any factor differs over the universe of computer users. The other contribution of this study is the translation of the satisfaction definition into a valid measurement instrument. The measure is based on the semantic differential of four adjective pairs which describe the factor. The relative importance of the factor is based on a separate fifth reaction. A variety of statistical tests were presented to show the validity and reliability of the questionnaire. Thus, it was concluded that computer user satisfaction as defined can be measured.
In a follow-up research, Ives, Olson and Baroudi,(1983) tested the Bailey and Pearson (1983) scale for its reliability and validity. Their findings suggested retaining 33 items for evaluating user information satisfaction. Furthermore, they attempted to produce a shorter version of this scale through the application of factor analysis. The results showed that the revised model consisted of three factors: EDP staff and services, information product, and knowledge and involvement. These factors are measured by 13 items.
Baroudi & Orlikowski ( 1988) examined the psychometric properties of the short form measure of user information satisfaction (UIS) proposed by Ives, Olson & Baroudi (1983) by asking users of large mainframe/mini computer transaction processing systems in 26 New York organizations to complete the questionnaire. Responses were reliability and validity tested and 12 of 13 scales loaded on the same three factors (EDP Staff and Services, Information Product and User Knowledge and Involvement) as they had in the study done by Ives, Olson & Baroudi (1983). The score was validated against two groups of satisfied and dissatisfied users. Baroudi & Orlikowski (1988) concluded that the short form questionnaire is a reliable and valid measure of UIS.
Montazemi’s 1988 study reports an empirical investigation of some of the relationships that exist between organizational characteristics and end-user satisfaction associated with computer-based informations systems (CBIS) in small businesses. Eight hypotheses were tested using data collected in two phase study of 83 small firms. The major finding show that end-user satisfaction is correlated with the number of systems analysts present within a firm, with the degree of analysis information requirements, with the level of participation and with end users’ level of computer literacy. In addition, it was found that decentralization of the decision-making process tends to create a need for more effective CBIS. As a result end user satisfaction was found to be higher in firms that were less decentralized. Furthermore there was more correlation between the end users and data processing personnel’s satisfaction with the CBIS environment.
A study developed by Igbaria, 1989, tested a path model of attitudes toward microcomputer usage, system usage and user satisfaction among microcomputer users. Results of path analysis of survey data gathered from 187 microcomputer users provided a moderate support for the proposed model. It was shown that attitudes toward microcomputer usage will enhance both system usage and user's satisfaction with the system. Further, the results confirmed the hypothesized model that user satisfaction influences system usage and system usage also has an influence on user satisfaction.
Doll & Torkzadeh (1988) specifically designed their instrument to measure end-user computing satisfaction. They conducted personal interviews with end-users in 44 non-randomly selected firms, then administered an 18-item instrument employing what appear to be 5-point Likert-type scales. Factor analysis was done and labeled their five factors: Content, Accuracy, Format, Ease of Use and Timeliness. Compared with the Short-Form UIS, Ease of Use is a new factor.
DeLone and McLean  analyzed more than 100 empirical papers containing IS effectiveness and success measures between 1981 and 1987. Of the multitude of measures they found, they identified six major factors of success – SYSTEM QUALITY and INFORMATION QUALITY singularly and jointly affect
both USE and USER SATISFACTION. Additionally, the amount of USE can affect the degree of USER SATISFACTION—positively or negatively—as well as the reverse being true. USE and USER SATISFACTION are direct antecedents of INDIVIDUAL IMPACT; and, lastly, this IMPACT on individual performance should eventually have some ORGANIZATIONAL IMPACT as shown in the Figure 1 below:-
The D&M IS Success Model (DeLone and McLean 1992) has served as a dominant framework for studying user satisfaction. There were over 300 articles in referred journals have referred to and made use of it, since it was first introduced and published in 1992 (DeLone and McLean 2003). The D&M IS Success Model suggested that information quality and system quality are two key factors determining user satisfaction. This is consistent with the end-user computing environment, where the phenomenon is characterized by both information consumption and direct user interaction. The quality of information is typically evaluated by measuring information attributes.
Shirani et al., 1994 research paper presented a revised model of user information satisfaction. That revised model proposes that user and organizational characteristics, both separately and interactively, create user expectations. The gap between the actual characteristics of a developed system and a user's expectations regarding the characteristics of the information system then determine whether the expectations are confirmed or not. This confirmation/disconfirmation forms the final basis for user satisfaction or dissatisfaction. For the practitioner, the model provides the foundation for anticipating the likely degree of UIS prior to implementation. The identification of strongly-held expectations regarding system characteristics would be a critical step toward ensuring user satisfaction. If the characteristics of the system in development are not consistent with the user's pre-implementation expectations then disconfirmation is likely to occur. Positive disconfirmation would boost UIS when the system exceeds expectations. Negative disconfirmation would diminish UIS when the system falls short of expectations. The systems developer can take action to modify one of the three elements that ultimately lead to confirmation/disconfirmation. From the model, those elements are user, organizational, and system characteristics. User characteristics could be modified via pre-implementation training or counseling. Organizational characteristics, which are slower to change, could potentially be modified with sufficient management support. Finally, system characteristics could be modified in situations where user and/or organizational characteristics are relatively fixed (thus leading to relatively fixed expectations).
Chin & Lee, 2000 defined end-user satisfaction with an information system as the overall affective evaluation an end-user has regarding his or her experience related with the information system. The term “experience” can be made more specific to focus upon different aspects related to the information system (e.g., computing, training, etc.). The researchers commented that past studies have focused primarily on the satisfaction measurement of the computing/use aspect of a system, but it may well be satisfaction with activities other than system use (e.g., training, participation or involvement in development or selection) that may also be of value in predicting subsequent behavior (e.g., utilization) or performance.
Bhattacherjee (2001) adopted the expectation confirmation theory to examine satisfaction. Among diverse theoretical frameworks, expectation confirmation theory has been receiving a great deal of attention in recent IS research. In his study, data collected from a field survey of online banking users indicate that while post acceptance usefulness perception continues to influence users’ continuance intention, user satisfaction with prior use has a relatively stronger effect on the dependent variable. User satisfaction, in turn, is determined primarily by users’ confirmation of expectation from prior use and secondarily by perceived usefulness.
Recently, the rise of electronic commerce has further motivated IS researchers’ interest in the study of satisfaction in the online environment (Devaraj, Fan & Kohli, 2002, McKinney, Yoon & Zahedi, 2002).
In McKinney’s et al. (2002) study two perspectives from the user satisfaction literature in IS and the customer satisfaction literature in marketing were synthesized to identify nine key constructs for analyzing web-customer satisfaction. Based on IS literature, the authors argued that measuring web-customer satisfaction for information quality and system quality provides insight about a customer’s overall satisfaction with a Web site.
Organizations are investing in information technology for an ever-increasing number of end-user tasks. Extracting benefits from these investments increasingly depends on supporting effective use of information technology and satisfying information technology users. Shaw, Delone & Niederman, 2002 research explores the end-user support factors that correlate with user satisfaction. This survey of 484 end-users examines 21 potential end-user computing support factors, such as system response time and user training in terms of their perceived importance to the end-user and the performance of IS staff in supporting each. Service quality, the gap between perceived importance and performance for each support factor, is computed. The relationships between these service quality gaps and user satisfaction are tested across different user groups (faculty, non-IS staff and students). Larger service quality gaps in the following support factors were correlated with lower user satisfaction in at least one of the three user groups: IS staff response time, IS staff technical competence, software upgrades, ease of access, cost effectiveness of the system, user understanding, documentation to support training, and data security/privacy. These results are compared to the support factors identified as significant in previous empirical studies. The primary conclusions from this study are software upgrade, staff response time and documentation of training materials are support areas that are likely to influence user satisfaction and different support factors impact user satisfaction or different user groups.
Leclerq, 2007, research work concerns the perceptual evaluation of the performance of information systems (IS) and more particularly, the construct of user satisfaction. Some researchers have indeed shown that the evaluation of an IS could not happen without an analysis of the feelings and perceptions of individuals who make use of it. Consequently, the concept of satisfaction has been considered as a guarantee of the performance of an IS. Also it has become necessary to ponder the drivers of user satisfaction. The analysis of models and measurement tools for satisfaction as well as the adoption of a contingency perspective has allowed the description of principal dimensions that have a direct or less direct impact on user perceptions. The case study of a large French group, carried out through an interpretative approach conducted by way of 41 semi-structured interviews, allowed the conceptualization of the problematic of perceptual evaluation of IS in a particular field study. This study confirmed the impact of certain factors (such as perceived usefulness, participation, the quality of relations with the IS Function and its resources and also the fit of IS with user needs). On the contrary, other dimensions regarded as fundamental do not receive any consideration or see their influence nuanced in the case studied (the properties of IS, the ease of use, the quality of information). Lastly, this study has allowed for the identification of the influence of certain contingency and contextual variables on user satisfaction and, above all, for the description of the importance of interactions between the IS Function and the users.
Personalized services are increasingly popular in the Internet world. A study done by Liang, Lai & Ku (2006), identifies theories related to the use of personalized content services and their effect on user satisfaction. Three major theories have been identified—information overload, uses and gratifications, and user involvement. The information overload theory implies that user satisfaction increases when the recommended content fits user interests (i.e., the recommendation accuracy increases). The uses and gratifications theory indicates that motivations for information access affect user satisfaction. The user involvement theory implies that users prefer content recommended by a process in which they have explicit involvement. In this research, a research model was proposed to integrate these theories and two experiments were conducted to examine the theoretical relationships. The findings of the study indicate that information overload and uses and gratifications are two major theories for explaining user satisfaction with personalized services. Personalized services can reduce information overload and, hence, increase user satisfaction, but their effects may be moderated by the motivation for information access. The effect is stronger for users whose motivation is in searching for a specific target. This implies that content recommendation would be more useful for knowledge management systems, where users are often looking for specific knowledge, rather than for general purpose Web sites, whose customers often come for scanning. Explicit user involvement in the personalization process may affect a user’s perception of customization, but has no significant effect on overall satisfaction.
Although user satisfaction is widely used by researchers and practitioners to evaluate information system success, important issues related to its meaning and measurement across population subgroups have not been adequately resolved. To be most useful in decision-making, researchers Doll et al., 2004 suggested that instruments like end-user computing satisfaction (EUCS) developed by DeLone and McLean’s which are designed to evaluate system success, should be robust. That is, they should enable comparisons by providing equivalent measurement across diverse samples that represent the variety of conditions or population subgroups present in organizations. According to these researchers, constructs such as user satisfaction are the language through which theoretical ideas and research findings are communicated among researchers and practitioners. A user satisfaction instrument with broad applicability increases the extent to which the results of studies can be generalized to other subgroups. Thus, it enables researchers to interpret results as informing the full body of theory. Using a sample of 1,166 responses, the EUCS instrument is tested for measurement invariance across four dimensions—respondent positions, types of application, hardware platforms, and modes of development. While the results suggest that the meaning of user satisfaction is context sensitive and differs across population subgroups, the 12 measurement items are invariant across all four dimensions. The 12-item summed scale enables researchers or practitioners to compare EUCS scores across the instruments originally intended universe of applicability.
The reliance on user satisfaction in measuring information system success is common among MIS researchers and practitioners, and several standardized instruments have been developed and tested .In general, the development of techniques for defining and measuring user satisfaction have been ad hoc and open to question (wikipedia).
User attitude toward the management information system (MIS) is measured by user information satisfaction (UIS). Poor user evaluation of the MIS function remains a problem in many organizations. Factors that may influence UIS and their relative influence or importance are examined. Wang, Tang & Tang (2001), found that current models for measuring user information satisfaction (UIS) and end-user computing satisfaction (EUCS) are perceived as inapplicable as they are targeted primarily towards either conventional data processing or the end-user computing environment. So, in their study, they has develops a comprehensive model and instrument for measuring customer information satisfaction (CIS) especially for web sites that market digital products and services.
However, in past research indexes for consumer satisfaction and indexes for user information satisfaction (UIS) have been developed separately in the fields of marketing and management information systems (Cho & Park, 2001). Because of this lack of interaction, they proposed an instrument for measuring electronic commerce consumer satisfaction in their research.
In a study conducted by researchers Sugianto & Tojib (2006), they identified 9 factors that effect user satisfaction with b2e portal – convenience of access, ease of use, timeliness, efficiency, confidentiality, security, communication, information content and layout.
In Malaysia, the review of the literature with regards to information satisfaction shows that most of the researches are confined to research measuring the success of IS. For example in the research done by Foong (1999), the researcher studied the effect of end-user personal and system attributes on computer-based information system success in Malaysia SMEs. The CBIS success was the composite measures of the dimensions pertaining to user satisfaction, systems usage and perceived systems effectiveness. User satisfaction was represented to the extent which the CBIS satisfied the end-user’s personal requirements – the system’s speed of information retrieval, ease of user, reliability, level of internal control, flexibility and types and attributes of reports generated by the system. The study done by Hussein, Karim & Selamat, 2007 investigated the influence of technological factors on up-stream model of Delone and McLean’s IS success dimensions whereby user satisfaction was investigated as one of the IS success factors. Similarly, researcher Masrek, 2007 and Masrek, Karim & Hussein, 2007 adopted Delone and Mclean’s IS success to measure campus portal effectiveness and the contributing factors and corporate intranet effectiveness respectively.
The factors that effect information satisfaction or alternatively the measurement of information satisfaction has had a long history within the IS discipline. A number of instruments were developed through a review of the existing UIS literature and then were tested in interviews, questionnaire surveys or a combination of these methods. Bailey and Pearson (1983) first attempted to develop a semantic differential scale to measure user satisfaction with general IS in a transactional data processing (TDP) environment. Thirty-nine items contributing to user satisfaction were identified based on a review of 22 studies of the computer/user interface. Ives, Olson & Baroudi (1983) study produced a shorter version and their model consisted of three factors: EDP staff and service, information product and knowledge and involvement. The best known measure of end-user computer satisfaction (EUCS) is the set of measure developed by Doll & Torkzadeh (1991) which is based on the five constructs of content, accuracy, format, ease of use and timeliness. The researchers measured information satisfaction to enable development of better applications.
Some researchers adopt the scales of information satisfaction depending on the purpose of their research (Igbaria, 1989; Leclerq,2007; McKinney’s et al., 2002; Montazemi, 1988; Pikkarainen et al., 2006; Wu & Wang, 2006 ) and some of them have developed their own scales to measure overall user satisfaction (Bhattacherjee, 2001; Cheung & Lee 2005; Chin & Lee, 2000; Cho & Park, 2001; Devaraj, Fan & Kohli, 2002; Liang, Lai & Ku, 2006; Shaw, Delone & Niederman, 2002) .
In Malaysia , the research has been confined adopting the existing scales of information satisfaction with regards to the Delone and Mclean’s model of IS success to measure IS success as seen in the studies done by Hussein, Karim & Selamat, 2007, Masrek, 2007 and Masrek, Karim & Hussein, 2007.
This paper has its limitation, since there is a wealth of literature and studies done on information satisfaction and hence because of time constraint, we may not been able to review all the research done on this area. However based on our review and analysis of the literature pertaining to information satisfaction, it is evident that user satisfaction is one of the important criterions and the most prevalent for measuring the success of information system. Most of the literature review presented scales to measure information satisfaction either in the overall IS systems, specific IT applications or web-based IS. In short, the factors that effect information satisfaction may be categorized in the following dimensions – information quality, system quality (Doll & Torkzadeh, 1988) and system design quality (Cho & Park, 2001).
Nevertheless, the review of the literature also shows further research and validation needs to be done to study the factors that effect information satisfaction and a revised model to measure information satisfaction that covers all the wide varieties of user environments in IS, specifically in Malaysia and in general respectively.