Omega 30 (2002) 451–478www.elsevier.com/locate/dsw

A critical review of end-user information system satisfactionresearch and a new research framework

Norman Aua;b;∗, Eric W.T. Ngaib, T.C. Edwin Chengb

aDepartment of Hotel and Tourism Management, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong KongbDepartment of Management, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong

Received 11 June 2001; accepted 21 August 2002

Abstract

This paper presents a critical review of research in end-user information system satisfaction (EUISS). An extensive literaturesearch is conducted from which over 50 EUISS related papers are identi4ed. It is found that the past research is dominated bythe expectation discon4rmation approach. To provide more insights into the psychological processing of the information systemperformance construct and its impact upon EUISS, we propose an integrated conceptual model based on the equity and needstheories. The implications of the proposed model for EUISS are discussed, and suggestions are made for testing the model.? 2002 Elsevier Science Ltd. All rights reserved.

Keywords: Cost–bene4t analysis; Information systems; Measurement; Satisfaction

1. Introduction

Assessing the e8ectiveness or success of information sys-tems (IS) within organisations has long been identi4ed asone of the most critical issues of IS management [1]. Yet, theprevalent IS assessment mechanisms are generally viewedas inadequate for evaluating the “soft” bene4ts such as im-proved decision making or added >exibility from using ISin today’s organisations [2,3]. Among myriad forms of as-sessment of IS e8ectiveness/success, “end-user IS satisfac-tion” (EUISS) is one of the most widely used measures [4].A large amount of research has been done in the past on themeasurement of end-user IS satisfaction [3,5–7]. However,it is commonly found that an IS with sound objective tech-nical performance may still result in varied levels of usersatisfaction. Goodhue [8] comments that the assumption bymany researchers that “better” information systems perfor-mance automatically leads to higher user satisfaction hasnot been consistently demonstrated in previous studies. In

∗ Corresponding author. Department of Hotel and Tourism Man-agement, The Hong Kong Polytechnic University, Hung Hom,Kowloon, Hong Kong. Fax: +852-23629362.

E-mail address: hmnorman@polyu.edu.hk (N. Au).

other words, high ratings on IS attributes do not necessarilyresult in a high level of user satisfaction. Hence, modelsdeveloped in the past may not have captured the real reasonsfor such di8erences, nor explained the underlying reasonsfor end-user satisfaction or dissatisfaction. Consequently,these con>icting results provide very little practical valuefor organisations to evaluate whether a particular aspect ofIS needs to be improved or not.

To date, many attempts have been made to capture theoverall post hoc evaluation by end users of the use of IS,along with the antecedent factors that form satisfaction bymainly using the expectancy discon4rmation theory [9,10].However, the theory fails to explain the situation in whichhigher than expected performance still results in dissatisfac-tion. This may be because end users are unable to voice theiractual expectations due to organisational barriers or becauseof erosion of user expectations after using the informationsystems over a period of time. More importantly, end usersmay not even have any expectations prior to the use of IS,in particular when users are unsure of what IS can o8er.

Identifying the determinants of EUISS is not the objectiveof this review. Many previous researchers such as Baileyand Pearson [5] have generated comprehensive lists of fac-tors that a8ect EUISS, which have been tested and shown

0305-0483/02/$ - see front matter ? 2002 Elsevier Science Ltd. All rights reserved.PII: S0305 -0483(02)00054 -3

452 N. Au et al. / Omega 30 (2002) 451–478

to be valid [3]. Instead, we aim to identify gaps in existingresearch in EUISS and propose a broader conceptual frame-work to better understand EUISS by closing these gaps.

This paper 4rst describes the main approaches to IS suc-cess measurement commonly used by organisations. It is fol-lowed by an overview of EUISS measurement in assessingIS success. The strengths and weaknesses of current EUISSmeasurements are critically evaluated. Finally, a new re-search framework grounded in the equity and needs theoriesis proposed for EUISS measurement.

2. Approaches to IS success measurement

A large number of system success measures exist be-cause IS can be viewed in di8erent ways. Broadly, IS canbe viewed from two perspectives, namely an organisationalviewpoint and a socio-technical viewpoint [11]. The prin-cipal focus of the organisational perspective is on the qual-ity of the interface and the information provided by an ISto aid the workers in accomplishing their tasks. One of themain criticisms of this approach is that it ignores the hu-man element. The socio-technical viewpoint, on the otherhand, focuses on individual needs and assumes that the in-dividual employee seeks monetary and other rewards. Fur-thermore, Delone and McLean [4] identify six dimensionsof IS success, namely system quality, information quality,information use, user satisfaction, individual impact and or-ganisational impact. These dimensions incorporate both or-ganisational and socio-technical perspectives of an IS. Theyare embedded in many common current approaches to eval-uating IS e8ectiveness, which di8er only in terms of the di-mensions chosen for measurement. For example, the systemusage approach is similar to the measurement of the infor-mation use dimension, while many studies of cost–bene4tanalysis, as well as of user satisfaction measures, incorpo-rate the measuring dimensions of system quality, informa-tion quality, and individual and organisational impacts.

2.1. Cost–bene2t analysis

Ideally, the determination of IS e8ectiveness should useobjective measurements such as cost–bene4t analysis [12].The net value of the information system to the organisation,therefore, equals the di8erence between the actual bene4tsin terms of improved organisational e8ectiveness, and thecost of IS development. Early research into IS assessmentfocuses mostly on the quantitative “hard” bene4ts, such asthe amount of cost saving and the level of technical sound-ness of the system, as an indication of its successfulness[13,14]. Typical observable measures include system re-sponse times, software time measures, reliability measures,throughput rate and the number of errors occurring withinthe process.

This approach, however, has been subjected to a greatdeal of criticism. First, it is diNcult to show causality, i.e.,

to prove that a particular bene4t is directly or solely due tothe new information system. Second, the costs and bene4tsof IS are largely qualitative or intangible in nature, and thusare diNcult to measure in terms of monetary value or time[15,16]. Even if objective data can be identi4ed, they aregenerally not recorded and thus not available. Saarinen [17]further argues that the use of quantitative and 4nancial 4g-ures are often based on an expert’s judgement, which doesnot make them more objective than less quantitative criteria.Nevertheless, Ditsa and MacGregor [18] suggest that perfor-mance and 4nancial factors tend to supersede organisationalor psychological factors when computer-based technologyis being considered.

2.2. System usage

System usage has been suggested as another measure ofIS success and is relatively easier to put into operation. Thisapproach re>ects the degree of con4dence users have in thee8ectiveness of their information systems. Some researchstudies measure actual use by recording the amount of userconnect time [19], the number of computer functions utilised[20], or the number of client records processed [21]. Onthe other hand, there are studies that measure perceived useinstead of actual use [22]. Some critics, however, argue thatthe use of IS, either actual or perceived, is only relevant whenit is voluntary [6,23]. This is because ine8ective systemsmay be used extensively as a mandatory requirement of themanagement, or for political reasons.

2.3. End-user satisfaction measurement

In view of the subjectivity of IS success or e8ectiveness,Cyert and March [24] are the 4rst to propose the conceptof user satisfaction (US) as a surrogate of system success.Myers [25] later proposes that IS success may be achievedwhen an information system is perceived to be successful bystakeholders and other observers, and is therefore best mea-sured in terms of end-user satisfaction (EUS) [16]. This isprobably the most widely used measure of IS success. Notonly does satisfaction have a high degree of face validitydue to reliable instruments having been developed by pastresearchers, but also most other measures are either concep-tually weak or empirically diNcult to validate [4,26]. Usersatisfaction is a critical construct not just because it is of-ten used as a surrogate of management information systems(MIS) e8ectiveness [3,27], but also because it is related toother important variables in systems analysis and design.

A number of studies [11,28,29] suggest that most systemsfail to meet the objectives and aspirations held for them, notbecause they are not technically sound, but because psycho-logical and organisational issues are not well addressed dur-ing the development, implementation and use of the system.Hence, from the socio-technical viewpoint, an informationsystem is viewed in a broader spectrum composed of thepeople and the work process that they must perform with a

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technology. The impact on end users is one important di-mension that should be included in any measurement of ISsuccess. Similarly, Melone [27] notes that in market-driven4rms, the realisation of bene4ts from an IS depends uponthe way the user chooses to respond to the system. Whetherthe user is satis4ed with the IS is critical in determiningwhether it is e8ective or not.

In reality a “good” information system that is perceivedby its users as a “poor” system is indeed a poor system [6].People’s unwillingness to use available systems and consid-erable alienation or dissatisfaction of end-users often turnstechnically successful systems into failures [30]. Therefore,it is generally assumed that satis4ed users will perform betterthan users with poor or neutral attitudes towards the system[5]. Research done by Gatian [31] also discovers that thereis a strong relationship between satis4ed users and betterdecision-making performance and eNciency among users.

User satisfaction is particularly critical to the success ofservices. The service sector has become increasingly domi-nant in developed economies where IS are in wide use forproductivity and competitiveness gains. It is therefore worthnoting that the correlation between satis4ed users, i.e., em-ployees, and work performance is particularly prominent inthe service industry. Often service employees are the ser-vice, and in most cases, the front-line employees are referredto as boundary spanners who provide a link between theexternal customer (or environment) and internal operationsof the organisation [32]. Service employees are the typicalend users of information systems, hence satis4ed employeesmake for satis4ed customers through better service quality.This in turn results in repeat business and increased prof-itability of the organisation.

3. An overview of end-user information systemsatisfaction

3.1. De2nition of end-user information system satisfaction

Oliver [33] de4nes satisfaction as the consumer’s ful4l-ment response. It is the customer’s judgement that a productor service feature, or the product or service itself, provides(or is providing) a pleasurable level of consumption-relatedful4lment, including levels of under- or over-ful4lment. Ful-4lment can only be judged with reference to a standard thatforms the basis for comparison. In other words, a ful4l-ment or satisfaction judgement involves a minimum of twostimuli—an outcome/performance and a comparison refer-ent. In the consumer behaviour literature, Howard and Sheth[34] de4ne satisfaction as the buyer’s cognitive state of be-ing adequately or inadequately rewarded for the sacri4cesthey have undergone.

As for IS end users, Doll and Torkzadeh [3] and Chinand Lee [7] have similar de4nitions whereby end-user sat-isfaction is de4ned as the a8ective attitude towards a spe-ci4c computer application by someone who interacts with

the application directly. In this paper, EUISS is de4ned asthe IS end-user’s overall a8ective and cognitive evaluationof the pleasurable level of consumption-related ful4lmentexperienced with the IS. IS end users refer to non-technicalpersonnel who use or interact with the system directly, asopposed to technical personnel who design the IS.

3.2. Factors/dimensions a5ecting IS user satisfaction

For more than two decades, EUS research has occupieda central role in behavioural research in IS [27]. The majorstudies of factors a8ecting EUISS to date are summarised inAppendix A. The most frequently used instrument for EUSis developed by Bailey and Pearson [5], who identify a listof 39 factors that contribute to EUS with IS. The instrumentis re-evaluated and re4ned by Ives et al. [6], and later againby Baroudi and Orlikowski [35], which result in a short-ened (comprising 13 items) measurement, which can bebroadly grouped into three main dimensions: “InformationQuality”, “EDP Sta8 and Services” and “User Knowledgeor Involvement”. Typical measures of “Information Qual-ity” include accuracy, relevance, completeness, currency,timeliness, format, security, documentation and reliability.Measures of “EDP Sta8 and Services” mainly comprise sta8attitude, relationships, level of support, training, ease of ac-cess and communication. Finally, measures of “Knowledgeor Involvement” mainly include user training, user under-standing and participation.

In fact, user knowledge directly or indirectly related vari-ables have been frequently mentioned in many studies ashaving an impact on EUS. A recent review by Mahmood etal. [36] analysing the empirical results of 45 EUS studiesand 4nd positive support for the in>uences of user experi-ence, user skills and ease of use on EUS to varying degrees.

The user involvement/participation factor is identi4ed inseveral other studies as a8ecting EUS [30,34,35,38–43]. Onthe other hand, Doll and Torkzadeh [3] identify 4ve factorsfor measuring EUS: content, accuracy, format, ease of useand timeliness. Most of these factors are mainly related to“Information Quality” mentioned above. Other dimensionssuch as “Top Management Support”, “Organization Sup-port” or user support structures of any kind are also sug-gested as in>uencing IS user satisfaction [10,36,44–48].

In addition, two other IS dimensions, namely “SystemQuality” and “Interface Quality”, are categorised by otherresearchers from the IS attributes lists [49]. Most measuresin the former dimension are engineering-oriented technicalperformance such as speed, features, robustness and upgrade>exibility. The latter category refers to the interaction be-tween the end user and the computer system, which consistsof hardware devices, software and other telecommunicationsfacilities.

While the above IS dimensions/factors are typical indica-tors of IS performance that it is believed will a8ect EUS, itis not uncommon that a given IS performance/environmentyields varied or even con>icting levels of satisfaction for

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any particular factor by di8erent end users. Levels of perfor-mance exist only as external stimuli to the end user, yet howthe end user interprets the stimuli that subsequently resultin satisfaction/dissatisfaction is not well understood. Sethiand King [43] suggest that user information processing lead-ing to attitude formation may not always be attribute-based.The commonly used measures therefore fail to reveal thepsychological intricacies and the underlying reasons of whyend users are satis4ed or dissatis4ed with an IS. More im-portantly, in terms of evaluative purposes, if the results arefound to con>ict with one another, they o8er very little prac-tical insights for an organisation to determine whether theproblems are attributed to a particular aspect of an IS.

3.3. Other models

A number of researchers have developed alternative mod-els to explain EUISS. Sethi and King [43] disagree that therelationship between EUS and various IS attributes is a lin-ear one, as suggested in most previous studies. Based onthe catastrophe theory, a “cusp” model is proposed, and it isfound that there is a non-linear relationship between a user’soverall evaluation of user information satisfaction (UIS) anddi8erent IS-related attributes. UIS is also cusp-distributedwith two control variables—extent of use and IS factorscores. Their study suggests that when the level of involve-ment with IS is small, i.e., extent of use is small, individ-uals tend to be neutral towards UIS. At higher levels of ISuse, users will then undertake extensive attribute evaluation,and small changes in IS attributes can result in catastrophicchanges in global UIS scores.

Instead of identifying factors a8ecting UIS, a recent studyby Kim et al. [50] focuses on the relationship between ISutilisation and user satisfaction. There is much controversyand inconsistency between these two constructs. Based onthe information processing view, a task contingent modelto clarify their relationship is suggested. Results show thatthere is a direct relationship between task uncertainty andutilisation, and a moderating e8ect of task uncertainty onthe relationship between utilisation and user satisfaction.

Woodroof and Kasper [51] propose a model of UIS thatintegrates three organisational behaviour theories of moti-vation, namely the equity, expectancy and needs theoriesto explain the user satisfaction and user dissatisfaction con-structs. The model suggests that process satisfaction and out-come satisfaction can have a disproportionate impact uponuser responses to an IS. For an IS to be considered suc-cessful, it must be designed to enhance the user’s processand outcome satisfaction or to reduce the user’s process andoutcome dissatisfaction.

3.4. Theoretical and methodological issues

EUISS is an important theoretical construct because of itspotential to discover both upstream and downstream linksin a causal chain [52]. Upstream activities refer to studies

on factors that cause EUISS, where EUISS is treated as adependent variable. Downstream activities refer to studieson behaviours a8ected by EUISS. To date, the majority ofstudies have focused on the upstream chain (e.g. [3,5,53]).Studies on the downstream chain have been relatively lim-ited. Examples of such studies include Gatian [31], Good-hue [8,54,55] and Winter et al. [56]. One reason for sucha phenomenon is that the downstream research domain isnot as yet well developed [52]. It is diNcult to specify theperformance-related behaviours that link user satisfactionwithout being application speci4c. System usage, for ex-ample, has obvious limitations when use is mandatory, asmentioned earlier. In addition, a number of empirical stud-ies yield a relatively low correlation between attitude andbehaviour [27,54]. This is because other variables such ashabit and social norms may dominate an individual’s be-haviour within an organisation.

For upstream research studies, Galletta and Lederer [57]question the reliability of the commonly used short formmeasure of UIS developed by Ives et al. [6]. However, themethod used by Galletta and Lederer [57] in their study iscriticised by Hawk and Raju [58] for not being grounded inclassical reliability theory. Hawk and Raju o8er reassurancethat the UIS instrument has adequate test–retest reliability.Similarly, test–retest reliability assessments of the earlierend-user computing satisfaction instrument are performedby Doll and Torkzadeh [3] and found to be stable and reliable[9,59].

Yet the upstream research studies are not without prob-lems. Despite the extensive studies done in the past twodecades, very little e8ort has been made on the conceptualand theoretical development of the UIS construct. Woodroof[51] points out that this problem is found in several popularinstruments used to measure UIS. User evaluation measuresare criticised for lacking in strong theoretical underpinnings[8,27,60], and empirical evidence of their eNcacy is mixedand contradictory [60–62]. In other words, a high user eval-uation of an IS’s attributes and services may not necessarilyresult in a high level of user satisfaction.

One reason for such inconsistent relationships is that manyprevious instruments do not account for user di8erences instandards and reference points when measuring UIS. Thismakes comparison of satisfaction scores very diNcult. Theapplication of the discrepancy model is common in the rel-evant 4eld of consumer behaviour for understanding con-sumer satisfaction [63]. In the discrepancy approach, actualperformance is compared to some performance standard andsatisfaction is measured as the di8erence between the ac-tual and the standard. Individual di8erences in the standardsbeing used for comparison are taken into consideration.Mathieson [64] suggests that user evaluation is based on acomparison of normative beliefs (expected IS attributes) anddescriptive beliefs (actual IS attributes experienced). Thisis sometimes referred to as expectation discon4rmation.

Nevertheless, satisfaction is more than a simple con4rma-tion of expected outcomes. The performance of a particular

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IS attribute may be higher than the end user’s expectationbut may not result in a satis4ed user if this attribute is notwhat the user really needs. Similarly, a technically sound ISmay still be perceived as a “poor” IS even if it has manyadvanced speci4cations that make very little additional pos-itive impact on the end users. This could well be the case inthe service industry where a reliable IS is what is needed insome areas. Sometimes an IS can provide certain featureswhich satisfy the end users’ needs, yet they may still bedissatis4ed if they feel the amount of “input” or “sacri4ce”required to have their needs ful4lled is not justi4ed. Yet the“input” elements incurred by particular end users are rarelyconsidered in previous studies. Additionally, end users mayhave ill-de4ned expectations, or even none at all, if they areunfamiliar with the IS. The overly rational expectancy-valuestructure may rarely occur in everyday life. Forcing a userto state an opinion, i.e., expectation, about a system whenthey have none could in>uence the relationships with othermodel components. This implies that some additional com-parison referent is required in the model as a reliable pre-dictor of EUISS.

As noted earlier, satisfaction comprises an a8ective atti-tude towards an object. Attitudes may contain little or noinformation about the attributes of the attitude object, i.e.,various IS attributes. Therefore measuring a user’s attitudebased on system attributes may o8er a limited, if not en-tirely distorted, picture [65]. Attitudes may not just be re-lated to an object but also a function of personality vari-ables and the role and tasks a person must perform in agiven situation [27,66]. Melone [27] also criticises the manyUIS studies that fail to recognise that attitudes of end userschange over time, and suggests using a longitudinal designthat tracks user attitudes and behaviours. While this couldbe useful, it is diNcult to conduct in practice when technol-ogy is changing so rapidly, and where a high labour turnoveris commonly found in some industries such as the serviceindustry.

Another limitation of many previous studies is that thereis little agreement on what is meant by the construct UISor its measurement. As UIS cannot be directly observed, at-tributes such as system accuracy, system timeliness, volumeof output, information accuracy and relevance, presentationformat and service quality are used to operationalise the UISconstruct [5,27]. However, many of these instruments donot explore the underlying reasons for satisfaction or dis-satisfaction with certain attributes of an IS by an end-user.Mathieson [64] suggests that information gathered by many4rms may be biased. Some users criticise an IS when theytry to use it for tasks that it is not designed to support. Indi-vidual end users may have di8erent responses to an e8ectiveIS because of the extent to which an IS ful4ls di8erent cat-egories of individual needs. Certain end users may feel dis-satis4ed with an IS because it imposes a threat to their jobsecurity or increases their workload. Others may feel satis-4ed with the same IS because it allows them to gain morepower and control over other people.

Similarly, Markus and Keil [28] discover that users donot use a technically sound system because they are notmotivated to do what the system enables them to do, andthat using the system makes it harder for them to do whatthey are motivated to do. This is due to the fact that thesystem is wrongly placed in an organisation and the usershave little or no power to demand the necessary factors thatwould have enabled them to use the system.

Finally, the original and modi4ed Pearson–Bailey usersatisfaction measurement scales are comprehensive in as-sessing users’ feelings on a variety of computer attributes.However, since the scales are developed and validated forUIS of mainframe computer systems, its applicability to PCsas commonly used by most organisations in present daysremains in doubt.

In view of these observations, we see a need for morereliable measures [57] and for a more theoretical view ofthe UIS construct [27]. We therefore propose a new modelof EUISS that aims to 4ll the observed gaps and de4cien-cies of existing models. It is important to note that ourproposed model evaluates current application rather thanpredicts behaviour. The model helps in learning how to de-velop better applications and in realising various social andeconomic “inputs” and “bene4ts” of IS investment for endusers.

4. A new research framework for EUISS

An integrated conceptual model of EUISS is proposedand shown in Fig. 1. In view of the failure of the previ-ous approaches to account for the varied levels of satisfac-tion with regard to the same level of IS performance, wepropose to incorporate three additional processing compo-nents in the model. These elements attempt to uncover thepsychological processing of end users in transforming ISperformance as an input stimulus into di8erent levels ofsatisfaction/dissatisfaction, i.e., output.

4.1. IS performance

Based upon the prior research 4ndings mentioned above,the major dimensions of IS performance relevant to andhaving a signi4cant impact on EUS consist of “InformationQuality”, “System Quality” and “System Support Services”.On the other hand, certain sectors in the service industrysuch as hotels and airlines feature a “piece-meal” approachto IS use that is characterised by having many independentinformation systems used in various individual departments[67,68]. Very often, determining whether the output fromthe IS is useful to the end users depends on how it is in-tegrated with other relevant IS in the organisation [69,70].Hence, an additional attribute, namely “System Integration”,is added to the list of “System Quality” dimension. Withreference to previous validated instruments [3,6,26], the “In-formation Quality” construct is measured by nine indicators,

456 N. Au et al. / Omega 30 (2002) 451–478

Equitable Self-development Fulfilment

IS Performance Expectation

ISPerformance

End User ISSatisfaction

Equitable Work Performance Fulfilment

Equitable Relatedness Fulfilment

IS Performance Expectation

Disconfirmation

Fig. 1. Proposed model of end-user information system satisfaction.

namely accuracy, availability, reliability, updatedness, rel-evance, timeliness, completeness, presentation format andaccessibility. Six indicators, namely response time, reliabil-ity, functionality, >exibility, user friendliness and ease ofintegration, are used to measure the “System Quality” con-struct. Finally the “System Support Service” construct willbe measured by another six indicators, namely promptness,reliability, responsiveness, technical competence, attitude ofsystem support people, ability of keeping accurate recordsand provision of training course.

Some studies of satisfaction 4nd a relationship betweenproduct performance and satisfaction, as represented by thelink L1 in the model [49,71]. This can be viewed as an af-fective evaluation of IS performance. Yet it has been arguedthat an examination of the direct e8ect of performance onsatisfaction says very little about the psychological mecha-nism of an individual user in transforming performance intosatisfaction. It is believed that the e8ect of performance onoverall satisfaction is, to a large extent, mediated by thecomparison referents shown in the model.

4.2. Expectation and expectation discon2rmation

4.2.1. Theory of expectation discon2rmationPrevious studies [72–74] in the consumer behaviour liter-

ature make an attempt to explain the cause of satisfaction byfocusing upon the antecedents of satisfaction, i.e., the sat-isfaction formation process, with the use of the expectationdiscon4rmation theory. As noted earlier, satisfaction judge-ment involves product performance as well as a compari-son referent. In the discon4rmation of expectations model,expectations are included as the criterion by which perfor-mance is compared.

The discon4rmation of expectations theory suggests thatconsumer satisfaction is determined by the size and direc-tion of the consumer’s discrepancy between expectationsand perceived product performance [49,74]. This is repre-sented by the links L2, L3 and L4 in the proposed modelin Fig. 1. On the basis of this theory, if the obtained per-formance is less than expected (negatively discon4rmed),consumers will be dissatis4ed. On the other hand, if expec-tations are met (zero discon4rmed) or performance exceedsexpectations (positively discon4rmed), consumers will besatis4ed. Expectation of IS end users therefore is believedby some IS researchers to have an impact on overall satis-faction levels, as represented by the link L5 [47,49,75].

4.2.2. Alternative views on discon2rmation expectancytheory

Although the “discon4rmed expectations” construct hasbeen widely accepted as one of the key determinants of con-sumer satisfaction [74,76], past studies on the e8ects of un-4lled expectations on consumer satisfaction have had mixedresults [71]. Expectations used in the discon4rmation of ex-pectations research are generally predictive ones. This hasbeen criticised as being logically inconsistent [72]. For ex-ample, a user predicts that an application system will per-form poorly and 4nds it performs as expected. Intuitively,one would anticipate that the user would be dissatis4ed withthe poor system, which is contrary to what the discon4rma-tion model predicts. A number of researchers have exam-ined the types of hierarchical expectations that consumersbring to product experiences [72,77]. Suh et al. [49] suggestthat EUISS be better determined by the degree of discrep-ancy between end-user “desired performance expectation”and actual IS performance.

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Another problem with the discon4rmation of expectationsmodel as also noted by Suh et al. [49] is that the modeldoes not di8erentiate between the two di8erent states ofcon4rmations—low expectations with low performance andhigh expectations with high performance. Hence, the incor-poration of actual IS performance and discon4rmation in theproposed model is likely to reveal more about satisfactionthan including discon4rmation alone.

These mixed 4ndings and controversial views sug-gest that the e8ects of expectation, discon4rmation andeven product performance on EUISS are likely to bemore complex than those simply predicted by the orig-inal expectation-discon4rmation model. In our proposedmodel, “predictive expectation” is used instead of “desiredexpectation”. This is because the “desired expectation” isthe standard of how an “ideal” IS should perform in theuser’s mind. Whereas “predictive expectation”, as stated byYau [78], is dealing with beliefs in the likelihood of theperformance level of the “existing” product, i.e., the IS. Inpractice it is much easier to manipulate the predictive typeof expectation of an IS currently used in an organisationthan to manipulate the desired expectation of an IS whichmay not even actually exist.

External in>uences such as promotional claims, wordof mouth and product cues can provide information thatcreates or a8ects expectations in the end user’s mind[79,80]. Internally, the end user’s past and current experi-ences with an IS also play an important role in expectationformation [10,31,47,79]. In addition, there is a positiverelationship between cultural values and product expecta-tion in some consumer behavioural research studies [78].These external and internal factors that in>uence a user’sexpectation are beyond the scope of this study, and henceare excluded from the model.

4.3. Equitable ful2lment

To eliminate the limitations of using expectationalone as a surrogate for EUISS, we propose three othercomparison referents—“Equitable Work PerformanceFul4lment”, “Equitable Self-development Ful4lment”and “Equitable Relatedness Ful4lment”, based on the eq-uity theory and needs theory, in measuring IS performancefor the prediction of overall satisfaction. This may of-fer additional information or insights beyond expectancydiscon4rmation. It also provides a more solid theoreticalfoundation for the EUISS construct that is lacking in mostprevious studies [81].

4.3.1. Equity theoryAccording to the equity theory developed by Adams [82],

equity is the result of an individual’s evaluation of theirinputs and rewards relationships, by making comparisonsinternally and/or externally to other reference groups. Al-though most versions of the theory stress that comparisonsare made between a person themselves and others in terms

of their input/outcome relationships, Pritchard [83] andOliver [84] state that the equity theory, in its most pristineform, simply suggests that an individual will feel dissatis-4ed if their own inputs are greater than outcomes/bene4ts,regardless of the input–outcome ratios of anyone else. If adiscrepancy is perceived between inputs and bene4ts, theindividual becomes distressed or dissatis4ed and is moti-vated to reduce this discrepancy. No social comparison isnecessary.

Equity or “fairness” has been noted in some consumerbehaviour research as a determinant of transaction and prod-uct satisfaction [33]. In the context of IS, Woodroof andKasper [51] suggest that equity could well be focused on thefairness of the “process”. A user’s perception of the inputs(costs) required and the outcomes (bene4ts) obtained fromusing one system is compared with the inputs required andthe rewards (bene4ts) obtained from using other means (e.g.manual or other systems). Traditionally, inputs are mea-sured in terms of hours of e8ort and outputs are measuredin terms of dollars of pay. The contemporary equity theoryhas emerged to involve multiple inputs and outcomes. Thesigni4cance of adding the equity construct to the measure-ment of EUISS is that it takes into consideration not onlywhat bene4ts an IS can deliver but also what “inputs” or“costs” are required from an end user to achieve those bene-4ts/outcomes. In other words, the fact that an end user is dis-satis4ed may simply because the bene4ts they obtain froman IS are not fair or worthy of the large amount of inputrequired from them. In an IS environment, similar conceptscan be found in the studies by Goodhue [8] and Joshi [85].Goodhue [8] suggests that users will give high evaluationbased not only on the inherent characteristics of a system,but also on the extent to which that system meets their taskneeds and their individual abilities. Similarly, Mahmood etal. [36] also state that IS end users are likely to have posi-tive attitudes and adopt an IS application based on perceivedbene4ts against how easy it is to achieve those bene4ts. Thisimplies that having the task needs ful4lled requires the in-put of the user’s ability and/or other resources. Likewise,Joshi [86] discovers that perceived equity in the allocationof management information systems resources is likely toin>uence overall UIS.

The salient feature of the proposed model is that both theinputs and outcomes of IS end users cover a much broaderrange than that suggested by Goodhue [8] and Joshi [86]. Infact, other variables which are known to a8ect EUISS suchas user experience, user skills, ease of use, user involve-ment and perceived usefulness are represented by variousinputs or bene4ts that are embedded in the various equitableneeds ful4lment constructs. Many of the negative impactswith the use of information systems as identi4ed in the lit-erature are likely to be the “inputs” or “costs” incurred byan individual end user. These “inputs” comprise what a userinvests or “sacri4ces” in using the information system in thehope of getting desirable outcomes/bene4ts from the IS. The“inputs” to an individual may include cognitive/intellectual

458 N. Au et al. / Omega 30 (2002) 451–478

e8ort, or physical e8ort and time (e.g. in learning to use anIS or taken to get partly involved in the development of anIS) as identi4ed in the studies of Woodroof and Kasper [51]and Goodhue [8]. Hence, it is likely that the higher the skillsand experiences an IS end user has, the less e8ort would berequired from him to extract the most bene4ts from an IS.Other possible inputs or negative impact with the use of anIS may consist of extra work load, work stress, reduction ofsocial contact, as well as diminishing recognition of non-ITexperiences and traditional skills, which have also been wellrecognised in the literature [87,88]. Unlike other consumerproducts, IS end users rarely need to purchase the system fortheir use, so 4nancial costs are normally not considered as an“input”. As stated earlier, IS end users refer to non-technicalpersons interacting with the system directly, and so seniormanagement sta8 are likely to be among them. Therefore,top management support is excluded in this model. On theother hand, the bene4ts or outcomes are in terms of the levelof various categories of needs ful4lment resulting from theuse of an IS, as to be discussed in the sequel.

The bene4ts derived from an IS may not guarantee usersatisfaction if the inputs required to acquire the bene4ts arecomparatively high. A negative “equitable ful4lment” indi-cates that if the perceived outcomes/bene4ts generated aresmaller than the inputs required (for example, if a user 4ndsthat generating a particular report is not justi4ed by the ef-fort required), then the user will be dissatis4ed [51]. Onthe other hand, positive “equitable ful4lment” indicates thatwhen perceived outcomes/bene4ts are greater than the in-puts required, it is likely that the user will be satis4ed, basedon the assumption that individuals often try to maximisetheir returns with minimum e8ort. Oliver [79] states that aperson is more willing to accept this sort of inequitable sit-uation. In reality it is the possessing of the input–outcomeratio by an individual that, as predicted by the equity the-ory, partly explains the varied levels of user satisfactionwith an IS. Although Huseman et al. [89] develop an equitysensitivity construct that classi4es individuals according totheir sensitivity to equity, it is not the main purpose of thisstudy and therefore will not be included in the proposedmodel.

Goodman [90] di8erentiates between three classes ofreferents, namely “Others”, “Self-standard” and “Systemreferents” that an individual user may choose for input–outcome ratio comparison. “Others” are users who maybe involved in a similar exchange, such as colleagues inthe same department using the same IS. “Self-standards”are unique to the individual, such as comparing theircurrent input–rewards ratio with that of an earlier job.“System referents” are implicit or explicit contractualexpectations between an employee and an employer.For example, a manager may claim that an IS is veryuser friendly and this may become the basis for evalu-ating the input requirements by end users. However, asmost of the “inputs” and “outcomes” identi4ed aboveare intrinsic and subjective to an individual, it would be

very diNcult to know and directly compare the input–outcome ratios of others. Hence, the processing of theinput–outcome ratio in this model will not involve compar-ison with other similar groups of individuals as found inmany previous studies on the equity construct.

The links L6, L7 and L8 connecting “IS PerformanceExpectation” and “Equitable Ful4lment” of various kinds, asshown in Fig. 1, imply that di8erent levels of IS performanceexpectation are likely to a8ect the input–outcome ratio of anIS end user. It is logical to assume that when users have ahigh expectation of the performance of an IS, they will alsobelieve they can get a higher “output” from an IS. Similarly,the higher the performance level of an IS, the higher thelevel of bene4ts is likely to be achieved (links L9, L10 andL11), which in turn a8ects the overall EUISS (links L12,L13 and L14).

4.3.2. Needs theoryA number of previous studies have included the con-

cept of “meeting user’s needs” as part of the measure ofan overall user satisfaction construct [5,55]. Indeed, thereis no question that satisfaction is the result of needs ful4l-ment of some kind, as de4ned earlier. The needs theory isprimarily based on the work of Maslow [91], Alderfer [92],Herzberg [93] and McClelland [94]. Maslow hypothesisesthat within every human being there exists a hierarchy of4ve needs: “Physiological”, “Safety”, “Social”, “Esteem”,and “Self-actualisation”. As each of these needs becomessubstantially satis4ed, the next higher-order need becomesdominant. Despite its popularity, little empirical evidencehas been found to substantiate that a satis4ed need activatesmovement to a new, higher need level [95].

Alderfer [92] condenses Maslow’s categories into “Ex-istence”, “Relatedness” and “Growth” needs, and refers tothis as the ERG theory. Existence needs correspond closelyto Maslow’s physiological and safety needs, which are at abasic level. Similarly, relatedness needs include all sociallyoriented needs, Maslow’s social needs and part of the esteemneeds. Finally, growth needs are related to the developmentof human potential and are similar to self-actualisation andpart of the internally based self-esteem needs in Maslow’stheory. However, Alderfer does not believe that one level ofneed must be satis4ed before the next level of need wouldemerge, as proposed by Maslow. In fact the nature of anyclear-cut hierarchical ordering has not yet been demonstrated[96]. The ERG theory suggests that all sets of needs are ac-tive in all human beings, and they are not in any hierarchicalorder of importance.

Unlike Maslow and Alderfer, Herzberg views satisfac-tion and dissatisfaction as two di8erent constructs in histwo-factor theory. He believes extrinsic needs, referred toas “hygiene” factors, will only lead to no dissatisfying con-sequences when ful4lled. Only when intrinsic needs, re-ferred to as “motivators”, are ful4lled will job satisfactionbe achieved.

N. Au et al. / Omega 30 (2002) 451–478 459

Finally, McClelland’s [94] theory of needs focuses onthree categories of needs, viz “Achievement”, “Power”, and“ANliation”. The theory suggests that individuals may havevaried levels of the above needs. This variation motivatesthem to pursue one goal instead of another.

While disagreements exist in the above theories on thenumber of levels and the categorisation of needs, what canbe observed is that di8erent needs do exist among humanbeings, and that these a8ect their values, behaviour, and,in turn, satisfaction. In other words, the ful4lment of cer-tain needs for some individuals may result in satisfaction,while under-ful4lment of other needs may not necessarilybring about dissatisfaction. Hence, in addition to the input–outcome ratio, the emphasis an individual puts on di8erentneeds categories is also critical to predicting satisfaction.

Under the IS environment, it is proposed that IS will ful-4l three categories of needs, namely “Work PerformanceFul4lment”, “Self-development Ful4lment”, and “Related-ness Ful4lment”. Work performance ful4lment refers to theneeds or bene4ts that are derived from the use of an ISin improving work performance. These are the basic andfundamental needs that an IS is expected to ful4l. Typi-cal examples include improving work eNciency, functionale8ectiveness and service quality. Self-development ful4l-ment will be focused on the needs of individual self-growthand self-advancement that are brought along by an IS suchas job promotion, work challenges and job security. Fi-nally, relatedness ful4lment includes all socially orientedneeds that require interactions with other human beings. Ex-amples of such needs or bene4ts obtained from an IS in-clude recognition and status, social relations, and power andcontrol.

One important feature of the ERG theory is the “frustra-tion regression hypothesis”, according to which the failureof a person to satisfy a particular category of needs can resultin an increase in the importance of another person’s otherneeds. Based on this assumption, the linkages L15, L16 andL17 between the three di8erent categories of equitable ful-4lment as depicted in Fig. 1 suggest that under-ful4lment orunfavourable input–outcome ratio of one category of ful4l-ment causes an end user to pursue an alternative ful4lment.The value placed on the bene4ts or outcome of the alterna-tive ful4lment therefore is likely to be higher.

4.4. End user IS satisfaction

The output of the a8ective and cognitive comparison eval-uation will be the overall EUISS construct. Based on theexpectancy discon4rmation theory, equity theory and needstheory, EUISS is proposed as a function of IS performance,IS performance expectation, IS performance expectation dis-con4rmation, equitable work performance ful4lment, equi-table self-development ful4lment and equitable relatednessful4lment. The consequences of EUISS are crucial to or-ganisations as it is likely to a8ect the work performance aswell as the level of service quality delivered by employees,

as in the case of service industry, which in turn will havean impact on repeat business.

4.5. Model validation

We have planned to test the proposed conceptual modelusing empirical data in the service industry and report the4ndings in future publications. As stated earlier, ensuringsatis4ed IS end users, i.e., employees, is particularly impor-tant to service organisations simply because employees arepart of the inputs for the service delivered. Hence, empiricaldata will be collected from the service industry as a refer-ence to explore the causal relationships between the con-structs by using Linear Structure Relationships techniques.It is believed that the resulting instrument can better concep-tualise and more accurately measure the EUISS constructthat is more 4rmly grounded in theory.

5. Conclusions

The need for reliable and valid instruments to assessthe performance of IS is becoming crucial as organisationsincrease their reliance on IT to help them compete moree8ectively and eNciently. Errors in evaluation can cause ex-pensive mistakes in terms of subsequent modi4cation. Moreimportantly, it impacts on the individual user’s quality ofwork life, the functioning of the IS department and the over-all voluntary usage of the IS within the organisation.

EUS alone is not suNcient to adequately capture the fullmeaning of e8ectiveness, since it does not fully link atti-tudes to behaviour. However, it is a more convenient mea-sure than other performance-related measures. There is alsoan implicit assumption that EUS with an IS results in somepositive change in user behaviour, leading to increased e8ec-tiveness. Research that has been done on EUISS is extensiveand diverse. The root of the problem is a lack of a theoret-ical/conceptual foundation to explain the EUISS construct.Earlier approaches to measuring EUISS assume a direct pos-itive linear relationship between the receipt of a desired out-come and the level of satisfaction. Other approaches havebuilt on, expanded and re4ned the measurements of EUISS.Yet, these approaches fail to explain the varied levels ofsatisfaction with regard to the same IS performance.

Based on the equity theory and needs theory, threeadditional comparison referents named “equitable workperformance ful4lment”, “equitable self-development” and“equitable relatedness ful4lment” are suggested for themeasurement of EUISS. Through the identi4cation of theinput–outcome ratio and di8erent categories of needs ful-4lment, useful insights can be obtained for managers intoevaluating current and future IS capabilities and IS policy.Managers can then implement more e8ective user support-ive programs to increase the ability of users. In addition,procedures for users to exploit the advantages of IS can beredesigned so that their actual users’ needs and expectationscan better be ful4lled.

460 N. Au et al. / Omega 30 (2002) 451–478

Tab

le1

Sum

mar

yon

maj

orlit

erat

ure

onen

d-us

erin

form

atio

nsy

stem

ssa

tisfa

ctio

n

Yea

rSt

udy

Sam

ple

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ple

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ende

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nden

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riab

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Sour

ceof

Find

ings

sour

cesi

ze(n

)va

riab

le(D

V)

(IV

s)in

stru

men

t

1981

Ala

vian

dH

ende

rson

[97]

Gra

duat

est

uden

tsat

the

Ohi

oSt

ate

Uni

vers

ityin

the

US

45U

ser

satis

fact

ion

with

deci

sion

supp

ortsy

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Use

rde

cisi

onst

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and

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impl

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prod

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ane8

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the

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satis

fact

ion

variab

le

1981

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ser

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(OLPM

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bank

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sw

hose

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impl

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istic

1983

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ley

and

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son

[5]

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N. Au et al. / Omega 30 (2002) 451–478 46119

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.[9

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462 N. Au et al. / Omega 30 (2002) 451–478Tab

le1

(continued

)

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emus

age

Use

rin

volv

emen

tUser

satisfaction

:B

aile

yan

dPe

arso

n(1

983)

User

involvement

andsystem

usage:

self-d

evel

oped

Use

rin

volv

emen

tin

the

deve

lopm

entof

ISw

illen

hanc

ebo

thsy

stem

usag

ean

dus

ersa

tisfa

ctio

nw

ithth

esy

stem

Use

rsa

tisfa

ctio

nw

ithth

esy

stem

will

lead

togr

eate

rsy

stem

usag

e

1986

Rus

hine

kan

dR

ushi

nek

[102

]

Subs

crib

ers

ofC

om-

pute

rwor

ldm

agaz

ine,

iden

ti4ed

and

4448

Ove

rall

satis

fact

ion

Res

pons

etim

e,nu

mbe

rof

syst

ems,

cost

e8ec

tiven

ess

ofpr

oduc

tivity

aids

,m

ainf

ram

espe

rcen

tage

,pe

riph

eral

sco

mpa

tibili

ty,pr

ogra

ms

com

patib

ility

,sy

stem

cost

,sy

stem

life,

num

ber

ofus

ers,

user

expe

ctat

ion,

eNci

ency

and

e8ec

tiven

ess

ofda

taba

sela

ngua

ge,pr

ompt

ness

ofeq

uipm

entde

liver

y,m

icro

s

Self

deve

lope

d60

%of

the

variat

ion

inov

eral

lsa

tisfa

ctio

nis

expl

aine

dby

thes

ein

depe

nden

tva

riab

les.

The

top

thre

em

ostpr

omin

ent

indu

cer

ofus

ersa

tisfa

ctio

n

N. Au et al. / Omega 30 (2002) 451–478 463qu

ali4

edby

apa

nel

ofex

perts

perc

enta

ge,eN

cien

cyof

pow

er/e

nerg

y,pr

ompt

ness

ofso

ftw

are

deliv

ery

are

good

resp

onse

time,

num

ber

ofsy

stem

user

san

dus

ers

inan

inst

alla

tion

and

mee

ting

usin

gex

pect

atio

ns

1987

Ray

mon

d[4

8]Fi

nanc

ial

man

ager

sof

smal

l4r

ms

464

Use

rsa

tisfa

ctio

nFa

ctor

s(2

0sc

ales

)ex

trac

ted

from

Pear

son

and

Bai

ley

(198

3)an

dIv

eset

al.(1

983)

:ou

tput

qual

ity,

user

–sys

tem

rela

tions

hip,

supp

ortfa

ctor

and

ED

Pst

a8

With

refe

renc

eto

Pear

son

and

Bai

ley

(198

3)an

dIv

eset

al.

(198

3)

Inst

rum

entis

valid

and

relia

ble

tobe

appl

ied

insm

all

orga

nisa

tions

.Su

ppor

tfa

ctor

isfo

und

tobe

mos

tcr

itica

lin

a8ec

ting

user

satis

fact

ion

insm

allor

gani

satio

ns

1988

Bar

oudi

and

Orlik

owsk

i[3

5]

IS end-

user

from

bank

ing,

insu

ranc

e,re

taili

ngan

dm

anu-

fact

urin

gin

dust

ries

358

EU

SIn

form

atio

npr

oduc

t;ED

Pst

a8an

dse

rvic

esan

dkn

owle

dge

and

invo

lvem

ent

With

refe

renc

eto

Ives

etal

.(1

983)

The

UIS

mea

sure

deve

lope

dby

Ives

etal

.(1

983)

appe

ars

tobe

are

ason

ably

valid

and

relia

ble

mea

sure

1988

Dol

lan

dTor

kzad

eh[3

]End

user

sin

44se

lect

ed4r

ms

from

variou

sse

ctor

s

618

End

-use

rco

mpu

ting

satis

fact

ion

(EU

S)

Con

tent

,ac

cura

cy,fo

rmat

,ea

seof

use,

timel

ines

sW

ithre

fere

nce

toB

aile

yan

dPe

arso

n(1

983)

,D

ebon

set

al.

(197

8),

Neu

man

and

Sege

v(1

980)

,N

olan

and

Sew

ard

(197

4),

Swan

son

(197

4),

Gal

lagh

er(1

974)

and

valid

ated

All

5fa

ctor

sw

ere

posi

tivel

yco

rrel

ated

toen

d-us

erco

mpu

ting

satis

fact

ion

1988

Mon

taze

mi

[103

]End

user

sin

83sm

all4

rms

Phas

e1—

164

End

-use

rsa

tisfa

ctio

nw

ithco

mpu

ter-

base

din

form

atio

n

35fa

ctor

sus

edin

Bai

ley

and

Pear

son

(198

3)in

stru

men

tW

ithre

fere

nce

toB

aile

yan

dPe

arso

n(1

983)

End

-use

rsa

tisfa

ctio

nis

posi

tivel

yco

rrel

ated

with

:(1

)th

enu

mbe

rof

anal

ysts

pres

entin

the

4rm

464 N. Au et al. / Omega 30 (2002) 451–478Tab

le1

(continued

)

Yea

rSt

udy

Sam

ple

Sam

ple

Dep

ende

ntIn

depe

nden

tva

riab

les

Sour

ceof

Find

ings

sour

cesi

ze(n

)va

riab

le(D

V)

(IV

s)in

stru

men

t

inte

rvie

wPh

ase

2—qu

estio

nnai

re

syst

em(C

BIS

)(2

)fo

rmal

info

rmat

ion

requ

irem

ents

anal

ysis

(3)

end-

user

partic

ipat

ion

insy

stem

desi

gn(4

)en

d-us

erlit

erac

y(5

)de

cent

ralis

edor

gani

satio

n

No

corr

elat

ion

exis

tsbe

twee

nle

ngth

ofC

BIS

use

and

user

satis

fact

ion

1988

Ber

gero

nan

dB

erub

e[4

4]End

user

sin

31or

-ga

nisa

tions

indi

8ere

ntse

ctor

s

212

Use

rsa

tisfa

ctio

nPr

esen

ceof

user

supp

ortst

ruct

ure

(ste

erin

gco

mm

ittee

,in

form

atio

nce

nter

and

supp

ortgr

oup)

,fr

eque

ncy

for

cons

ultin

gw

ithsu

ppor

tst

ruct

ures

,es

tabl

ishm

entof

mic

roco

mpu

ter

plan

and

esta

blis

hmen

tof

polic

ies

User

satisfaction

:w

ithre

fere

nce

toB

aile

yan

dPe

arso

n(1

983)

and

Ives

etal

.(1

983)

IVs:

self-d

evel

oped

End

user

sw

ere

mor

esa

tis4e

dw

ithth

eir

mic

ro-c

ompu

ting

activ

ities

whe

n:(1

)or

gani

satio

nal

mic

ro-c

ompu

ting

plan

was

inco

rpor

ated

inth

eIS

mas

ter

plan

(2)

ther

ew

asan

info

rmat

ion

cent

erto

supp

orten

d-us

erac

tivity

(3)

user

sha

dac

cess

toa

hot-lin

eto

solv

eth

eir

mic

ro-c

ompu

ting

prob

lem

s

1989

And

erso

n[1

04]

Non

-sup

er-

viso

ryw

orke

rsof

ahi

ghte

chno

logy

4rm

inth

eU

S

90U

ser

satis

fact

ion

with

CB

ISUsersatisfactionmeasure

:ac

cura

cy;re

liabi

lity;

timel

ines

san

dre

leva

ncy

Factor:

ease

ofle

arni

ng;jo

bsa

tisfa

ctio

n;de

cisi

ontim

eus

ing

CB

ISan

dm

anua

lw

ork

requ

ired

inus

ing

CB

IS

Use

rsa

tisfa

ctio

n:w

ithre

fere

nce

toB

aile

yan

dPe

arso

n(1

983)

IVs:

self-

deve

lope

dan

dw

ithre

fere

nce

toH

ackm

anan

dO

ldha

m(1

976)

,Loc

ke(1

976)

,an

dB

aile

yan

dPe

arso

n(1

983)

The

char

acte

rof

job

(job

satis

fact

ion;

job

grow

thop

portun

ities

,m

otiv

atin

gpo

tent

ialof

the

job)

have

very

little

impa

cton

user

satis

fact

ion

and

usag

eof

CB

IS.It

was

foun

dth

ated

ucat

ion

and

trai

ning

inth

esy

stem

(eas

eof

lear

ning

)an

dop

portun

ities

for

enha

nced

wor

kpr

oduc

tivity

are

impo

rtan

t(m

anua

lw

ork

and

deci

sion

time)

N. Au et al. / Omega 30 (2002) 451–478 46519

89D

ollan

dTor

kzad

eh[3

0]

End

user

sin

variou

sin

dust

ries

atdi

8ere

ntle

vel

618

EU

SEUSmeasure

:co

nten

t,ac

cura

cy,fo

rmat

,ea

seof

use,

timel

ines

s

Factor:

end

user

invo

lvem

ent(p

erce

ived

)

Contextualfactor

:de

sire

din

volv

emen

t

With

refe

renc

eto

Dol

lan

dTor

kzad

eh(1

988)

Am

ong

user

sin

the

equi

librium

orm

oder

ate

depr

ivat

ion

stat

e(d

esired

invo

lvem

ent=

perc

eive

din

volv

emen

t),pe

rcei

ved

invo

lvem

entha

sa

posi

tive

and

sign

i4ca

ntco

rrel

atio

nw

ithen

d-us

ersa

tisfa

ctio

n..

Use

rsin

ahi

ghde

priv

atio

nst

ate

(des

ired¿

perc

eive

d)w

ould

have

ane

gativ

eco

rrel

atio

nbe

twee

npe

rcei

ved

invo

lvem

entan

dsa

tisfa

ctio

n.A

mon

gsa

tura

ted

user

s(p

erce

ived¿

desi

red)

,pe

rcei

ved

invo

lvem

entha

da

nega

tive

butno

n-si

gni4

cant

corr

elat

ion

with

satis

fact

ion

1989

Gal

letta

and

Led

erer

[57]

Man

ager

san

dex

ecut

ives

ofva

riou

sor

gani

sa-

tions

.27

inco

ntro

lgr

oup,

38in

“fai

l-ur

e”ex

-pe

rim

enta

lgr

oup

and

27in

“suc

-ce

sses

”ex

-pe

rim

enta

lgr

oup

92U

ISMeasureofUIS

:th

e13

-ite

msc

ale

deve

lope

dby

Ives

etal

.(1

983)

and

4ad

ditio

nalsu

mm

ary

item

sIv

eset

al.

(198

3)The

sum

mar

yite

ms

beha

ved

mor

ere

liabl

yth

anth

e13

-ite

mde

taile

dqu

estio

nsfo

ral

lgr

oups

.The

reis

still

ane

edfo

rre

liabl

em

easu

res

ofU

IS.The

sum

min

gof

deta

iled,

inde

pend

entite

ms

toob

tain

agl

obal

mea

sure

ofus

ersa

tisfa

ctio

nco

uld

bein

valid

1989

Nat

h[4

2]End

user

sin

12la

rge

orga

nisa

-tio

nsin

the

US

98EU

SMeasureofEUS:in

form

atio

ntim

elin

ess;

info

rmat

ion

accu

racy

;vo

lum

eof

outp

ut;pa

rtic

ipat

ion

insy

stem

deve

lopm

ent;

ease

ofup

grad

ing;

plan

ning

for

futu

resy

stem

appl

icat

ion;

syst

em’s

resp

onsi

vene

ssto

chan

ging

user

need

s;at

titud

eof

man

ager

sto

war

dsus

ing

com

pute

rs;to

pm

anag

emen

tin

volv

emen

t;ap

plic

atio

nof

mod

ern

data

base

tech

nolo

gy;

orie

ntat

ion

ofus

ertrai

ning

tow

ard

high

erjo

b

Self-d

evel

oped

The

freq

uenc

yof

use

and

time

spen

ton

usin

gC

BIS

are

posi

tivel

yco

rrel

ated

with

end-

user

satis

fact

ion.

For

uppe

rle

velm

anag

ers,

high

erfr

eque

ncy

ofus

ele

adto

high

ersa

tisfa

ctio

n.Fo

rlo

wer

leve

lm

anag

ers,

long

ertim

e

466 N. Au et al. / Omega 30 (2002) 451–478Tab

le1

(continued

)

Yea

rSt

udy

Sam

ple

Sam

ple

Dep

ende

ntIn

depe

nden

tva

riab

les

Sour

ceof

Find

ings

sour

cesi

ze(n

)va

riab

le(D

V)

(IV

s)in

stru

men

t

desc

ript

ion;

suita

bilit

yof

com

pute

rtrai

ning

for

user

need

s

Factor:

freq

uenc

yof

use

and

time

spen

t

spen

ton

usin

gco

mpu

ters

lead

tohi

gher

satis

fact

ion

1990

Josh

i[8

6]End

user

sof

cent

ral-

ized

ISin

med

ium

-siz

een

gine

er-

ing

and

chem

ical

orga

nisa

-tio

ns,a

gove

rn-

men

tag

ency

and

am

ajor

univ

ersi

ty

226

Ove

rall

UIS

Newvariable

:equ

ityin

the

allo

catio

nof

MIS

reso

urce

s

Othervariables:

qual

ityof

info

rmat

ion

prod

uct,

user

know

ledg

ean

din

volv

emen

tle

vel,

ED

Pst

a8an

dse

rvic

es

Equ

ity:

self-d

evel

oped

Oth

erva

riab

les:

with

refe

renc

eto

Ols

onan

dIv

es(1

981)

,Iv

eset

al.(1

983)

All

fact

ors

are

posi

tivel

yco

rrel

ated

with

UIS

1990

Naz

em[1

05]

End

user

ofsm

all

busi

ness

(¡10

0pe

rson

nel)

4rm

sw

hich

use

com

pute

r-iz

edge

n-er

alle

dger

inth

eU

S

102

Use

rsa

tisfa

ctio

nof

acco

untin

gso

ftw

are

Measureofsoftwaresatisfaction

:av

aila

bilit

yof

softw

are

supp

ortse

rvic

e;av

aila

bilit

yof

softw

are

trai

ning

serv

ice;

secu

rity

;>e

xibi

lity

toex

pand

;ea

seof

use;

accu

racy

ofou

tput

;re

liabi

lity

Factor:

sour

ceof

softw

are

(sel

f-de

velo

ped;

o8-the

-she

lf;cu

stom

prog

ram

;ot

hers

)

Self-d

evel

oped

Sign

i4ca

ntdi

8ere

nces

wer

efo

und

betw

een

sour

ceof

softw

are

and

the

follo

win

gfa

ctor

sna

mel

yso

ftw

are

supp

ort,

trai

ning

,>e

xibi

lity

and

secu

rity

.N

osi

gni4

cant

rela

tions

hips

wer

efo

und

with

resp

ectto

the

rem

aini

ng3

fact

ors

(eas

eof

use,

accu

racy

and

relia

bilit

y)

1990

Tan

and

Lo

[106

]O

Nce

auto

mat

ion

user

sin

acad

emic

inst

itutio

nin Si

ngap

ore

68End

-use

rsa

tisfa

ctio

nfo

roN

ceau

tom

atio

nsy

stem

33fa

ctor

sse

lect

edfr

omPe

arso

nan

dB

aile

y(1

983)

inst

rum

ent

Mod

i4ed

from

Pear

son

and

Bai

ley

(198

3)

All

fact

ors

are

sign

i4ca

ntin

a8ec

ting

EU

Sfo

roN

ceau

tom

atio

nsy

stem

N. Au et al. / Omega 30 (2002) 451–478 46719

90Ig

baria

and

Nac

hman

[107

]

End

user

sfr

om6

larg

eco

mpa

nies

inU

S.Typ

esof

inst

itutio

nsin

clud

eba

nkin

g,hi

gher

educ

atio

n,fo

odpr

o-du

ctio

n,hi

ghte

chno

logy

and

man

u-fa

ctur

ing

108

End

-use

rsa

tisfa

ctio

n(a

ttitu

deto

war

dIS

sta8

and

serv

ices

,in

form

atio

npr

oduc

t,kn

owle

dge

and

invo

lvem

ent)

Lea

ders

hip

styl

eof

ISm

anag

er,ha

rdw

are/

softw

are

acce

ssib

ility

and

avai

labi

lity,

com

pute

rba

ckgr

ound

ofus

ers,

user

attit

udes

tow

ards

end-

user

com

putin

gan

dsy

stem

utili

satio

n

EUS:w

ithre

fere

nce

toB

arou

dian

dO

rlik

owsk

i(1

983)

,Ive

set

al.(1

983)

and

Bar

oudi

and

Orlik

owsk

i(1

988)

Leadership

style:

Bas

s(1

981)

Hardware

andsoftware

accessibility

and

availability:

Ben

son

(198

3),

Riv

ard

and

Hu8

(198

8)

Computer

anxiety:

Rau

b(1

981)

Attitudes

towardsend

user

:G

oodh

ue(1

986)

System

utilization

:Sr

iniv

asan

(198

5)

Sign

i4ca

ntpo

sitiv

ere

latio

nshi

psbe

twee

nus

ersa

tisfa

ctio

nan

dle

ader

ship

styl

eof

ISm

anag

er,

hard

war

e/so

ftw

are

acce

ssib

ility

and

avai

labi

lity,

com

pute

rba

ckgr

ound

ofus

ers,

user

attit

udes

tow

ards

end-

user

com

putin

gan

dsy

stem

utili

zatio

n

No

sign

i4ca

ntre

latio

nshi

psw

ere

foun

dbe

twee

nus

ersa

tisfa

ctio

nan

dge

nder

,ed

ucat

ion,

and

orga

nisa

tiona

lle

vel

1991

Liet

al.[1

08]

IS man

ager

sin

ava

riet

yof

indu

stries

109

Use

rsa

tisfa

ctio

nw

ithIS

39fa

ctor

sad

opte

din

Pear

son’

s(1

983)

inst

rum

ent

With

refe

renc

eto

Bai

ley

and

Pear

son

(198

3)an

dIv

eset

al.

(198

3)

The

inst

rum

entw

asfo

und

tobe

relia

ble

and

cons

iste

nt.

Wei

ghtin

gth

eIS

Ssc

ore

with

thei

rco

rres

pond

ing

impo

rtan

cera

tings

isun

nece

ssar

y.IS

man

ager

sse

emto

beco

ncer

ned

with

ISeN

cien

cybu

tIS

user

sse

emno

t

468 N. Au et al. / Omega 30 (2002) 451–478Tab

le1

(continued

)

Yea

rSt

udy

Sam

ple

Sam

ple

Dep

ende

ntIn

depe

nden

tva

riab

les

Sour

ceof

Find

ings

sour

cesi

ze(n

)va

riab

le(D

V)

(IV

s)in

stru

men

t

1992

Cho

and

Ken

dall

[109

]End

user

sin

info

r-m

atio

nce

ntre

s

180

Use

rsa

tisfa

ctio

nan

dus

erpe

rfor

man

ce

Coe

rciv

ean

dno

n-co

erci

veus

eof

pow

erSe

lf-d

evel

oped

Non

-coe

rciv

eso

urce

ofpo

wer

ispo

sitiv

ely

corr

elat

edto

end-

user

satis

fact

ion

and

perf

orm

ance

.C

oerc

ive

sour

ceof

pow

eris

nega

tivel

yco

rrel

ated

toen

d-us

ersa

tisfa

ctio

nan

dpe

rfor

man

ce

1992

Yav

erba

uman

dN

osek

[110

]

MB

Ast

uden

tsen

rolle

din

anin

tro-

duct

ory

MIS

cour

seat

Tem

ple

Uni

vers

ityin

US

73End

-use

rsa

tisfa

ctio

n(a

ttitu

deto

war

dIS

sta8

and

serv

ices

,in

form

atio

npr

oduc

t,kn

owle

dge

and

invo

lvem

ent)

ISed

ucat

ion

and

trai

ning

With

refe

renc

eto

Bar

oudi

and

Orlik

owsk

i(1

988)

Edu

catio

nan

dtrai

ning

will

lead

toch

ange

sin

user

satis

fact

ion,

attit

ude

tow

ard

ISst

a8an

dse

rvic

es,

info

rmat

ion

prod

uct,

know

ledg

ean

din

volv

emen

t.The

rela

tions

hips

can

beei

ther

posi

tive

orne

gativ

e

1992

Josh

i[1

11]

End

user

sfr

omva

riou

sor

-ga

nisa

tions

incl

udin

gch

emic

alm

anuf

ac-

turing

4rm

s,go

v-er

nmen

tag

enci

es,

com

mu-

nity

col-

lege

and

univ

ersi

ty

324

UIS

Traditionalfactors:

qual

ityof

info

rmat

ion

prod

uct,

know

ledg

ean

din

volv

emen

t,at

titud

esto

war

dsED

Pst

a8

Newfactors:

Equ

ityin

the

allo

catio

nof

MIS

reso

urce

s,ro

leco

n>ic

tan

dro

leam

bigu

ity

Traditional

factors:

with

refe

renc

eto

Ives

etal

.(1

983)

and

Oso

nan

dIv

es(1

981)

Equityfactor

:Jo

shi(1

989)

Rol

eam

bigu

ityan

dro

leco

n>ic

t:R

izzo

(197

0)

All

fact

ors

are

sign

i4ca

ntly

corr

elat

edw

ithU

IS.Equ

ityha

sth

ehi

ghes

tco

rrel

atio

nw

ithU

IS

1992

Glo

rfel

dan

dC

rona

n[1

12]

PCan

dm

ainf

ram

eap

plic

atio

nus

ers

39in

1988

and

67in

1990

UIS

ofPC

and

mai

nfra

me:

info

rmat

ion

prod

uct,

user

know

ledg

e,ED

Pst

a8

End

-use

rco

mpu

ting

(EU

C)

man

agem

entst

rate

gyW

ithre

fere

nce

toIv

eset

al.

(198

3)an

dD

ollan

dTor

kzad

eh(1

988)

EU

Cm

anag

emen

tst

rate

gyha

sno

sign

i4ca

nce

ina8

ectin

gus

ersa

tisfa

ctio

nin

PCan

dm

ainf

ram

eco

mpu

ter

N. Au et al. / Omega 30 (2002) 451–478 46919

93B

enar

dan

dSa

tir[3

9]A

ctua

lan

dpo

tent

ial

exec

utiv

ein

form

a-tio

nsy

s-te

mus

ers

(CEO

)in

variou

sC

anad

ian

orga

nisa

-tio

ns

74U

ser

satis

fact

ion

with

EIS

Usersatisfactionmeasure

:pr

ovid

ere

leva

ntin

form

atio

n;im

prov

ein

form

atio

nqu

ality

;im

prov

eco

ordi

natio

nbe

twee

nm

anag

ers;

allo

wfo

rqu

icke

rde

cisi

onm

akin

g,in

form

atio

nac

cess

ibili

ty,e

ase

ofus

e

Factors

:EIS

initi

ated

byus

ers;

seni

orm

anag

emen

tin

volv

emen

tin

EIS

impl

emen

tatio

n;us

ing

cons

ulta

nts

toas

sist

inEIS

sele

ctio

n/im

plem

enta

tion;

apr

otot

ype

desi

gnap

proa

chan

dav

aila

bilit

yof

variou

sEIS

func

tions

Self-

deve

lope

dC

ontrad

ictto

mos

tpr

evio

usre

sear

ch4n

ding

s,th

ere

are

nosi

gni4

cant

rela

tions

hips

betw

een

user

satis

fact

ion

and

the

4rst

4fa

ctor

s.The

reis

sign

i4ca

ntre

latio

nshi

pbe

twee

nus

ersa

tisfa

ctio

nan

dth

eav

aila

bilit

yof

14EIS

func

tions

1993

Law

renc

ean

dLow

[47]

End

user

of2

ISin

ala

rge

Aus

tral

ian

gove

rn-

men

tco

r-po

ratio

ns

96fo

rsy

stem

“A”

and

59fo

rsy

stem

“B”

Use

rin

form

atio

nsa

tisfa

ctio

nof

ISw

ithin

user

-led

deve

lopm

ent

Use

rpe

rcep

tion

ofre

pres

enta

tion,

user

perc

eptio

nof

man

agem

entsu

ppor

t,pr

evio

usex

pect

atio

ns,cu

rren

tex

pect

atio

ns,pr

evio

usex

perien

cew

ithco

mpu

ters

With

refe

renc

eto

Bai

ley

and

Pear

son

(198

3)

Ast

rong

posi

tive

corr

elat

ion

betw

een

user

perc

eptio

nof

repr

esen

tatio

nan

dU

IS.A

sign

i4ca

ntco

rrel

atio

nbe

twee

nto

pm

anag

emen

tsu

ppor

tan

dU

IS

1993

Am

oako

-G

yam

pah

and

Whi

te[3

7]

End

user

s(m

anag

eran

dop

erat

or-

user

s)in

one

orga

n-is

atio

nin

US

52U

ser

satis

fact

ion

ofIS

Use

rin

volv

emen

tW

ithre

fere

nce

toB

aron

asan

dLou

is(1

988)

Stro

ngpo

sitiv

eco

rrel

atio

nbe

twee

npe

rcei

ved

user

invo

lvem

entan

dus

ersa

tisfa

ctio

n

1994

Hen

ryan

dSt

one

[10]

End

user

sof

aco

mpu

ter-

base

dm

edic

alin

form

a-tio

nsy

stem

ina

hosp

ital

inU

S

524

End

-use

rsa

tisfa

ctio

nM

anag

emen

tsu

ppor

t,ea

seof

syst

emus

e,pr

evio

usco

mpu

ter

expe

rien

ce,co

mpu

ter

self-e

Nca

cyan

dou

tcom

eex

pect

ancy

With

refe

renc

eto

Tor

kzad

ehan

dD

oll’s

(199

1)

Com

pute

rse

lf-e

Nca

cyha

sth

ela

rges

tpo

sitiv

eim

pact

onEU

S,fo

llow

edby

man

agem

entsu

ppor

tfo

rth

esy

stem

,ea

seof

syst

emus

e,ou

tcom

eex

pect

ancy

and

last

lypr

evio

usco

mpu

ter

expe

rien

ce

1994

Ket

tinge

ran

dLee

[113

]U

nder

grad

uate

342

Use

rsa

tisfa

ctio

nw

ithth

ein

form

atio

n

Serv

ice

qual

ityw

ithSE

RV

QU

AL

scal

e:ta

ngib

les;

relia

bilit

y;re

spon

sive

ness

;as

sura

nce

and

empa

thy

With

refe

renc

eto

Bar

oudi

and

Orlik

owsk

i

The

“rel

iabi

lity”

and

“em

path

y”di

men

sion

sof

ISse

rvic

equ

ality

in

470 N. Au et al. / Omega 30 (2002) 451–478Tab

le1

(continued

)

Yea

rSt

udy

Sam

ple

Sam

ple

Dep

ende

ntIn

depe

nden

tva

riab

les

Sour

ceof

Find

ings

sour

cesi

ze(n

)va

riab

le(D

V)

(IV

s)in

stru

men

t

and

grad

uate

stud

ents

inse

rver

alM

ISan

dm

anag

e-m

ent

scie

nces

cour

ses

that

used

the

colle

ge’s

ISse

rvic

es

serv

ices

func

tion

(198

8),

Gal

letta

and

Led

erer

(198

9)an

dPa

rasu

ram

anet

al.(1

988)

SER

VQ

UA

Lm

aybe

need

edto

supp

lem

entth

ese

rvic

edi

men

sion

ofus

ersa

tisfa

ctio

nof

info

rmat

ion

serv

ice

func

tion

mea

sure

1994

McK

een

etal

.[9

4]IS

end

user

san

dpr

ojec

tle

ader

sor

proj

ect

man

ager

s

151

Use

rsa

tisfa

ctio

nU

ser

partic

ipat

ion

4contingencyfactors:

task

com

plex

ity,sy

stem

com

plex

ity,us

erin

>uen

ce,us

er-d

evel

oper

com

mun

icat

ion

With

refe

renc

eto

Ives

etal

.(1

983)

and

Bar

oudi

and

Orlik

owsk

i(1

988)

Use

rpa

rtic

ipat

ion

has

adi

rect

rela

tions

hip

with

user

satis

fact

ion.

The

stre

ngth

ofits

rela

tions

hip

depe

nds

onth

ele

velof

task

com

plex

ityan

dsy

stem

com

plex

ity.The

high

erth

eta

skan

dsy

stem

com

plex

ity,th

est

rong

erth

ere

latio

nshi

pbe

twee

nus

ersa

tisfa

ctio

nan

dus

erpa

rtic

ipat

ion

and

vice

vers

a.U

ser

in>u

ence

and

user

–de

velo

per

com

mun

icat

ion

wer

epo

sitiv

ely

rela

ted

tous

ersa

tisfa

ctio

nre

gard

less

ofth

ele

velof

partic

ipat

ion

1994

Suh

etal

.[4

9]End

user

sin

Kor

ean

busi

ness

4rm

s

150

Use

rsa

tisfa

ctio

n,pe

rcei

ved

usef

ulne

ss,de

gree

ofIS

use

Dis

con4

rmed

expe

ctat

ions

:de

sire

dIS

perf

orm

ance

and

actu

alIS

perf

orm

ance

ISperformanceindicators

:ac

cura

cy,sp

eci4

city

,su

Nci

ency

,re

cenc

y,pr

esen

tatio

nfo

rmat

,ea

seof

use,

acce

ssib

ility

and

>exi

bilit

y

With

refe

renc

eto

Dol

lan

dTor

kzad

eh(1

988)

Ove

rall

user

satis

fact

ion

and

perc

eive

dus

eful

ness

wer

esi

gni4

cant

lyin

>uen

ced

byth

edi

scre

panc

ybe

twee

nen

d-us

erde

sire

san

dac

tual

perf

orm

ance

1995

Dol

leta

l.[2

6]IS

end

user

s22

4U

ISED

Pst

a8an

dse

rvic

es,in

form

atio

npr

oduc

tan

dkn

owle

dge

and

invo

lvem

ent

With

refe

renc

eto

Ives

etal

.(1

983)

Thr

ough

the

use

ofco

n4r-

mat

ory

fact

oran

alys

is,th

efa

ctor

sw

ere

both

valid

and

relia

ble

asa

mea

sure

ofU

IS

N. Au et al. / Omega 30 (2002) 451–478 47119

95K

ekre

etal

.[1

14]

Softw

are

user

2500

+C

usto

mer

satis

fact

ion

for

softw

are

prod

ucts

Cap

abili

ty;us

abili

ty;pe

rfor

man

ce,re

liabi

lity;

inst

alla

bilit

y;m

aint

aina

bilit

yan

ddo

cum

enta

tion

Self-d

evel

oped

Cap

abili

tyan

dus

abili

tyar

ecr

itica

ldr

iver

sof

over

all

cust

omer

satis

fact

ion

1995

Vla

hos

and

Ferr

att[1

15]

Man

ager

sof m

iddl

e-to

-lar

gesi

zeco

rpo-

ratio

nsin

Gre

ece

55Sa

tisfa

ctio

nof

com

pute

rba

sed

info

rmat

ion

syst

em(C

BIS

)

Am

ount

ofus

ean

dpe

rcei

ved

valu

eof

CB

ISSe

lf-d

evel

oped

Satis

fact

ion

was

posi

tivel

yco

rrel

ated

toth

epe

rcei

ved

valu

eof

CB

ISin

supp

ortin

gm

anag

emen

tde

cisi

on-m

akin

g.The

amou

ntof

use

was

notne

cess

arily

rela

ted

toth

epe

rcei

ved

valu

eno

rsa

tisfa

ctio

nof

CB

IS

1996

Dol

lan

dX

ia[1

16]

ISen

dus

ers

359

UIS

Con

tent

,ac

cura

cy,fo

rmat

,ea

seof

use

and

timel

ines

sW

ithre

fere

nce

toD

ollan

dTor

kzad

eh(1

988)

(are

plic

atio

nto

Dol

let

al.

(199

4))

Thr

ough

the

use

ofco

n4rm

ator

yfa

ctor

anal

ysis

with

di8e

rent

sam

plin

gm

etho

d,al

lfa

ctor

sw

ere

both

valid

and

relia

ble

asa

mea

sure

ofU

IS

1996

Ete

zadi

-Am

oli

and

Farh

oom

and

[45]

ISen

dus

erin

variou

sor

-ga

nisa

tions

341

End

-use

rco

mpu

ting

satis

fact

ion

and

user

perf

orm

ance

Doc

umen

tatio

n;ea

seof

use;

func

tiona

lity

ofsy

stem

;qu

ality

ofou

tput

;su

ppor

tan

dse

curity

Bas

edon

prev

ious

rese

arch

but

did

not

indi

cate

whi

chon

e

All

six

fact

ors

are

valid

and

relia

ble

indi

cato

rof

user

satis

fact

ion.

Asi

gni4

cant

variat

ion

inus

erpe

rfor

man

ceca

nbe

expl

aine

dby

the

six

corr

elat

edfa

ctor

sun

derlyi

ngEU

CS

1996

Lee

and

Pow

[117

]End

user

sof

clin

ical

hosp

ital

info

rma-

tion

syst

emin

Hon

gK

ong

and

end

user

sin

the

4nan

cese

ctor

66fr

omho

spita

lan

d51

from

4-na

ncia

lse

ctor

Use

rsa

tisfa

ctio

nIn

form

atio

nac

cess

beha

viou

ran

dex

pect

atio

nof

qual

ityW

ithre

fere

nce

toSw

anso

n’s

user

repo

rtev

alua

tion

ques

tionn

aire

(Sw

anso

n,19

87)

Stro

ngpo

sitiv

eco

rrel

atio

nbe

twee

nus

ersa

tisfa

ctio

nan

din

form

atio

nac

cess

beha

viou

ran

dex

pect

atio

nof

qual

ity

472 N. Au et al. / Omega 30 (2002) 451–478Tab

le1

(continued

)

Yea

rSt

udy

Sam

ple

Sam

ple

Dep

ende

ntIn

depe

nden

tva

riab

les

Sour

ceof

Find

ings

sour

cesi

ze(n

)va

riab

le(D

V)

(IV

s)in

stru

men

t

1996

Sim

onet

al.

[118

]M

embe

rsof

activ

edu

tyU

SN

aval

Con

stru

c-tio

nB

atta

lion

200

End

user

satis

fact

ion,

com

preh

ensi

onan

dsk

illtran

sfer

Info

rmat

ion

syst

emtrai

ning

met

hods

and

cogn

itive

abili

tyW

ithre

fere

nce

toD

ollan

dTor

kzad

eh(1

988)

(for

EU

Spa

rt)

Tra

inee

sin

trai

ning

trea

tmen

tsin

clud

ing

hand

s-on

com

pute

rtrai

ning

(beh

avio

urm

odel

ing

and

expl

orat

ion)

had

high

erle

vel

ofus

ersa

tisfa

ctio

nth

antrai

nees

inco

nven

tiona

lle

ctur

etrai

ning

1997

Ang

and

Soh

[119

]IS

end

user

sin

3la

rge

com

pani

es

133

Use

rin

form

atio

nsa

tisfa

ctio

nan

djo

bsa

tisfa

ctio

n

Demographicvariables:

sex;

age;

educ

atio

nalle

vel;

year

sin

pres

entjo

b;ye

ars

inth

eco

mpa

ny;

orga

nisa

tiona

lpo

sitio

n

Computerbackground

:fr

eque

ncy

ofus

e;us

ertrai

ning

;co

mpu

ter

liter

acy

With

refe

renc

eto

Yav

erba

um(1

988)

No

sign

i4ca

ntre

latio

nshi

psbe

twee

nco

mpu

ter

back

grou

ndan

dU

ISor

job

satis

fact

ion.

Age

was

sign

i4ca

ntly

rela

ted

toU

ISan

djo

bsa

tisfa

ctio

n.O

rgan

isat

iona

lpo

sitio

nw

asno

tsi

gni4

cant

lyre

late

dto

UIS

.Edu

catio

nalle

velw

asne

gativ

ely

corr

elat

edto

UIS

and

num

ber

ofye

ars

inco

mpa

nyw

aspo

sitiv

ely

corr

elat

edw

ithU

IS.Jo

nsa

tisfa

ctio

nan

dU

ISw

ere

high

lypo

sitiv

ely

corr

elat

ed

1997

Dow

ning

[120

]End

user

sof te

leph

one

inte

ract

ive

voic

ere

spon

sesy

stem

inU

S

543

EU

SEUSmeasure

:co

nten

t;ac

cura

cy;fo

rmat

;ea

seof

use;

timel

ines

s

Additionaldimension

:ag

eof

end-

user

With

refe

renc

eto

Dol

lan

dTor

kzad

eh(1

988)

Old

erus

ers

are

assa

tis4e

dw

ithth

eIS

asyo

unge

rus

ers

and

the

actu

alus

age

issi

mila

rac

ross

age

grou

ps

1997

Mej

ias

etal

.[1

21]

End

user

s(U

San

dM

exic

an)

ofgr

oup

supp

ort

syst

ems

(GSS

)

230

US

sam

ple

and

239

Mex

i-ca

nsa

mpl

e

Use

rsa

tisfa

ctio

nw

ithgr

oup’

sde

cisi

on

Mex

ican

grou

psex

pres

sed

mor

ede

cisi

onsa

tisfa

ctio

nth

anU

SG

SSgr

oup

N. Au et al. / Omega 30 (2002) 451–478 47319

97R

yker

etal

.[7

5]IS

end

user

sin

2he

alth

care

orga

nisa

-tio

nsin

US

252

Use

rsa

tisfa

ctio

nw

ithIS

Dimension

:in

form

atio

npr

oduc

ts;pr

ovid

erst

a8an

dse

rvic

es;

know

ledg

ean

din

volv

emen

t

UserexpectationsofIS

:Ext

erna

lso

urce

s(w

ord-

of-m

outh

from

frie

nds

outs

ide

wor

k,TV

com

mer

cial

s,V

endo

rpe

rson

nel,

Aca

dem

icsc

hool

san

djo

urna

ls)

Pastexperience

:In

tern

also

urce

s:(w

ord-

of-m

outh

from

co-w

orke

rs,IS

sta8

com

mun

icat

ions

)

Expectation

:w

ithre

fere

nce

toZei

tham

let

al.(1

993)

and

Pitt

etal

.(1

995)

UIS

dimension

:w

ithre

fere

nce

toIv

eset

al.

(198

3)

Use

rsw

hose

prim

ary

in>u

ence

was

exte

rnal

toth

eor

gani

satio

nha

dsi

gni4

cant

lyus

ersa

tisfa

ctio

nth

anus

ers

who

sepr

imar

yin

>uen

cew

asin

tern

alto

the

orga

nisa

tion

1998

Gel

derm

an[1

22]

Dut

chm

anag

ers,

info

rma-

tion

man

-ag

ers

and

cont

rolle

rs

212

ISpe

rfor

man

ceU

ser

satis

fact

ion

and

usag

eW

ithre

fere

nce

toD

ollan

dTor

kzad

eh(1

988)

Use

rsa

tisfa

ctio

nis

sign

i4ca

ntly

rela

ted

tope

rfor

man

ce.The

rela

tion

betw

een

usag

ean

dpe

rfor

man

ceis

nots

igni

4can

t

1998

Seth

ian

dK

ing

[40]

Facu

ltym

embe

rsat

aU

Sac

adem

icin

stitu

tion

55U

ser

info

rmat

ion

satis

fact

ion

MeasureofUIS

:us

eof

(PC

;co

mpu

ter

lab;

mai

nfra

mes

;pr

inte

rs;ne

twor

k);re

latio

nshi

pw

ithco

mpu

ter

supp

ortst

a8(C

SS);

tech

nica

lsk

illof

CSS

;at

titud

eof

CSS

;re

spon

sive

ness

ofC

SS;ac

cess

toC

SS;e8

ectiv

enes

sof

CSS

;pa

rtic

ipat

ion

inde

cisi

on-m

akin

gab

outco

mpu

ter

reso

urce

s;de

gree

ofco

ntro

lov

erco

mpu

ter

reso

urce

s;trai

ning

prog

ram

sav

aila

bilit

y;st

eps

that

the

adm

inis

trat

ion

have

take

nto

impr

ove

com

putin

gfa

cilit

ies

and

reso

urce

spr

ovid

edfo

rco

mpu

ting

activ

ities

Factor:

exte

ntof

use

Self-d

evel

oped

usin

ga

cusp

cata

stro

phe

mod

el

The

reis

ano

n-lin

ear

rela

tions

hip

betw

een

aus

er’s

over

allev

alua

tion

ofU

ISan

dan

inde

xcr

eate

dby

aver

agin

gth

eus

ersa

tisfa

ctio

nre

spon

ses

todi

8ere

ntIS

-rel

ated

attrib

utes

.Ext

entof

use

isa

cont

rol

fact

ora8

ectin

gth

eno

n-lin

ear

rela

tions

hip.

UIS

iscu

sp-d

istrib

uted

with

2co

ntro

lva

riab

les

nam

ely

exte

ntof

use

and

ISfa

ctor

scor

es

1999

Dow

ing

[123

]End

user

sof te

leph

one

inte

ract

ive

voic

ere

spon

sesy

stem

inU

S

543

EU

SMeasureofEUS:sy

stem

usag

eW

ithre

fere

nce

toD

ollan

dTor

kzad

eh(1

988)

for

EU

San

dse

lf-d

evel

oped

for

usag

ebe

havi

our

Syst

emus

age

inte

rms

oftim

ean

dsp

ace

isa

valid

alte

rnat

ive

mea

sure

ofEU

S

474 N. Au et al. / Omega 30 (2002) 451–478Tab

le1

(continued

)

Yea

rSt

udy

Sam

ple

Sam

ple

Dep

ende

ntIn

depe

nden

tva

riab

les

Sour

ceof

Find

ings

sour

cesi

ze(n

)va

riab

le(D

V)

(IV

s)in

stru

men

t

1999

Kha

lilan

dElk

ordy

[40]

Bra

nch

man

ager

san

dm

anag

eria

lre

pres

enta

-tiv

esof

22ba

nks

inEgy

pt

120

Use

rsa

tisfa

ctio

nan

dsy

stem

usag

eUsersatisfactionmeasures:

rela

tions

hip

with

ISst

a8;

syst

em>e

xibi

lity;

qual

ityof

syst

ems

outp

ut;

unde

rsta

ndin

gof

syst

ems;

invo

lvem

entin

syst

ems

deve

lopm

ent

Systemusage:

usag

eof

syst

emou

tput

;im

portan

ceof

man

ualre

ports;

impo

rtan

ceof

prin

ted

repo

rts;

impo

rtan

ceof

on-lin

ein

form

atio

n

User

satisfaction

:m

odi4

esfr

omB

aile

yan

dPe

arso

n(1

983)

and

Ives

etal

.(1

983)

Satis

fact

ion

with

syst

emou

tput

cont

ribu

tem

ostto

the

over

allus

ersa

tisfa

ctio

nU

ser

satis

fact

ion

isfo

und

toha

vesi

gni4

cant

posi

tive

rela

tions

hips

tous

age

ofsy

stem

outp

ut,im

portan

ceof

prin

ted

repo

rts

and

impo

rtan

ceof

on-lin

ein

form

atio

nbu

tha

vene

gativ

ere

latio

nshi

pto

the

impo

rtan

ceof

man

ualre

ports

1999

Palv

iaan

dPa

lvia

[124

]End

user

ofa

smal

lbu

sine

ssco

mpa

nies

(med

ium

empl

oyee

is4)

inth

eU

S

100

ITsa

tisfa

ctio

nUsersatisfactionmeasure

:so

ftw

are

adeq

uacy

;so

ftw

are

mai

nten

ance

;in

form

atio

nco

nten

t;in

form

atio

nac

cura

cy;in

form

atio

nfo

rmat

;ea

seof

use;

timel

ines

s;se

curity

and

inte

grity

;re

prod

uctiv

ity;

docu

men

tatio

n;ve

ndor

supp

ort;

trai

ning

and

educ

atio

n

Factor:

(1)

Bus

ines

sre

late

d(typ

eof

busi

ness

;si

ze;

pro4

tabi

lity

and

loca

tion)

(2)

Ow

ner

char

acte

rist

ics

(gen

der;

age;

race

;ed

ucat

ion

and

com

putin

gsk

ills)

Bas

edon

Palv

ia(1

996)

Sign

i4ca

ntre

latio

nshi

psw

ere

only

foun

dbe

twee

nge

nder

and

age

ofow

ner

and

ITsa

tisfa

ctio

n.Fe

mal

esex

hibi

ta

high

erle

velof

satis

fact

ion

and

youn

ger

owne

rsha

vegr

eate

rsa

tisfa

ctio

nth

anol

der

ones

N. Au et al. / Omega 30 (2002) 451–478 475

Acknowledgements

We are grateful to the constructive comments of twoanonymous referees on an earlier version of this paper. The4rst author is supported in part by The Hong Kong Poly-technic University under a sta8 development grant.

Appendix A.

A summary of major studies of factors a8ecting Ecliss todate is given in Table 1.

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