Vol. 11, No. 2
Copyright ©1998, Idea Group Publishing.
A Conceptual Development of Process
and Outcome User Satisfaction
JONATHAN B. WOODROOF
Middle Tennessee State University, USA
GEORGE M. KASPER
Virginia Commonwealth University, USA
Integrating three prominent organizational behavior theories of motivation (equity, expectancy, and needs)
with concepts of information systems success, this paper develops a broad conceptual foundation from which
to view and understand user satisfaction in information systems. This integration attempts to clarify many
of the diverse dimensions of user satisfaction and examines the notions of process and outcome satisfaction
and dissatisfaction in information systems.
Much research has been done on the relationship between the success of an information system and the satisfaction of the people who use them. Yet many studies report
inconsistent or contradictory results. Despite these inconclusive findings, the relationship between user satisfaction (US)
and information systems (IS) success has great appeal.
Historically, US research has been plagued by many
problems. Directly measuring the success of an IS has been
found to be impractical and perhaps impossible (Galletta &
Lederer, 1989). Therefore, surrogates are used. The linkage
between the operationalizations of US and the IS success
construct has been tenuous at best. Methodological problems,
such as weak construct validity, have also contributed to the
lack of progress and the mixed results on US (Jarvenpaa,
Dickson, & DeSantis, 1985; Zmud, Byrd, Sampson, Lenz, &
Reardon, 1993). Perhaps the most compelling problem,
however, is the lack of conceptual development (Jarvenpaa et
al., 1985; Kim, 1989; Straub, 1989; Melone, 1990; Zmud et al.,
1993). While the US construct has often been used to evaluate
system effectiveness, there is no clearly articulated theory
relating US to IS success (Klenke, 1992; Melone, 1990;
Yaverbaum & Nosek, 1992).
The purpose of this paper is to develop a more comprehensive model of US. The proposed model of US integrates
three prominent organizational behavior theories (equity, expectancy, and needs) with the concepts of IS success. In
addition to suggesting a theoretical foundation for US, this
integration identifies the notions of process and outcome as
critical to assessing IS satisfaction and dissatisfaction. The
paper begins with a discussion of the various definitions of
user satisfaction that have been used in IS research. Next, a
model of US that synthesizes organizational behavior theories
and the concepts of IS success is proposed. By integrating the
organizational behavior theories of equity, expectancy, and
needs with the concepts of IS success, a broad, theory-based
foundation for US in IS is developed. The conclusions are then
presented and implications of the model for US research are
discussed.
Manuscript originally submitted January 26, 1997; Accepted April 11, 1997 for publication.
Spring • 1998
Information Resources Management Journal
37
The US Construct
US has been defined as a learned disposition toward the
objects of an IS (Lucas, 1973), a set of beliefs about the relative
value of an IS (Swanson, 1974), “the sum of one’s positive and
negative reactions to a set of factors” (Bailey & Pearson, 1983,
p. 531), and “the extent to which users believe the information
system available to them meets their information requirements” (Ives, Baroudi, & Olsen, 1983, p. 785). Other definitions include terms like “felt need,” “system acceptance,”
“perceived usefulness,” “MIS appreciation,” “feelings about
a system,” and “system friendliness” (Melone, 1990).
There is currently no agreement on a definition for US
and many of the current definitions of US are conceptually
inadequate. According to Melone (1990, p. 80),
This lack of agreement on the conceptual definition of
the user-satisfaction construct has lead to a situation in
which there are many operationalizations and an equal
number of conceptual definitions, for the most part
lacking theoretical foundation.
There is also no consensus on how US should be measured. A plethora of instruments has been developed and used
in past US research, and these US instruments are as diverse
as they are numerous (Lucas, 1973; Noland & Seward, 1974;
Swanson, 1974; Schultz & Slevin, 1975; Schewe, 1976;
Pearson, 1977; Bailey & Pearson, 1983; Ives, Baroudi, &
Olsen, 1983; Barki & Huff, 1985; Raymond, 1985; Raymond,
1987; Baroudi & Orlikowski, 1988; Montazemi, 1988; Tait &
Vessey, 1988; Doll & Torkzadeh, 1988; Galletta & Lederer,
1989; Tan & Lo, 1990). Moreover, the scales from which
these instruments are constructed lack theoretical basis (Shirani,
Aiken, & Reithel, 1994; Sanders & Garrity, 1995).
In summary, US research in IS is plagued by many
problems, including the lack of consensus on a conceptual
definition of the US construct, the lack of agreement on how
US should be measured, and the inconsistent and even contradictory results that have been reported over the past two
decades. The core reason for these problems and the resulting
lack of progress in this area of research seems to be that, while
much effort has been expended on the measurement of US,
there has been very little work on the construct itself. Because
of this, some IS researchers have called for a richer conceptual
foundation for the US construct (Melone, 1990).
In response to this call, Sanders and Garrity (1995)
extended the model of IS Success developed by DeLone and
McLean (1992) by identifying four dimensions of US: Task
Support Satisfaction, Quality of Worklife Satisfaction, Interface Satisfaction, and Decision Making Satisfaction. The
DeLone / McLean model, as modified by Sanders and Garrity,
is presented in Figure 1.
The four dimensions Sanders and Garrity (1995, p. 18)
identified are defined as follows:
• Task Support Satisfaction measures the fit between the job
and the computer system. Items for this scale attempt to
measure the functionality of the system in terms of how the
system helps the individual to get a job done and fulfill task
requirements.
• Quality of Worklife Satisfaction measures how a computer
system affects an individual’s quality of worklife and job
satisfaction. Items for this scale attempt to measure whether
the system supports the social needs, intellectual needs, and/
or physiological requirements of the individual in the context of job related activities.
• Interface Satisfaction measures the quality of the computer
system interface. Evaluation focuses on the characteristics
of the interface in terms of presentation, format, and efficiency. Items for this construct attempt to determine whether
Figure 1: The DeLone/McLean Model of IS Success, as modified by Sanders and Garrity (1995).
38
Spring • 1998
Information Resources Management Journal
Vol. 11, No. 2
the outputs are arranged logically, the presentation media is
acceptable, and/or the information is readily accessible.
• Decision Making Satisfaction measures how well a system
supports decision and problem solving activities. Items for
this construct attempt to determine whether the system
supports the individual in recognizing problems, structuring
problems, and/or making decisions related to the goal of
controlling some business process.1
Support Satisfaction, Quality of Worklife Satisfaction, Interface Satisfaction, and Decision Making Satisfaction is relabeled “Dimension,” because each of these dimensions could
be related to satisfaction or dissatisfaction. And finally, note
that the term “User Satisfaction” is changed to the more
generic term, “User Affective Response” (UAR), allowing for
the user’s response to be either satisfaction or dissatisfaction
(Woodroof & Kasper, 1996).
The model presented here extends the DeLone / McLean
model by including notions of IS process satisfaction and
outcome satisfaction, as well as dissatisfaction. Concerning
the notion of dissatisfaction, Woodroof and Kasper (1996)
have shown that US in IS may be a separate construct from IS
user dissatisfaction (UD), and the wording of IS satisfaction
instruments (whether positively or negatively) can significantly impact a user’s affective response. Concerning the
notions of process and outcome, a user’s satisfaction with the
process of an IS (how easy it is to learn and use) may be
significantly different from that user’s satisfaction with the
outcome of an IS (output in the form of generated documents
and reports).
Given these notions, each of the four dimensions identified by Sanders and Garrity can be considered along two
additional dimensions: satisfaction / dissatisfaction and process / outcome. The addition of these dimensions (together
with the dimensions identified by Sanders and Garrity) to the
DeLone / McLean model, results in the model in Figure 2.
Note, in Figure 2, the mappings of the process, outcome,
satisfaction, and dissatisfaction combinations onto each of the
four dimensions identified by Sanders and Garrity.
Also note that the word “Satisfaction” in the terms Task
A Theoretical Foundation for UAR
A theoretical foundation for the UAR construct can be
found in the organizational behavior literature. Landy and
Becker (1987) identify three theories of motivation that use
satisfaction as the dependent measure: equity, expectancy,
and needs. Using the common dependent measure of satisfaction to integrate these three organizational behavior theories
results in a well-founded and broad-based foundation for the
study of UAR. The theoretical foundation for the User
Interface dimension of the UAR construct in IS is presented in
Figure 3.
Figure 3 shows the User Interface dimension; however,
any dimension of UAR can be mapped into the model. As
shown in Figure 2, the Interface Dimension can be evaluated
along the dimensions of process, outcome, satisfaction, and
dissatisfaction. The attributes of an interface that research has
shown to be important are: input/output attributes like readability of characters, color schemes used, layout of fields and
text, and message feedback (Zmud et al., 1993), user friendliness attributes like response time, time required to learn, rate
of errors and ease of recovery, and retention over time
(Shneiderman, 1992), as well as information quality attributes
Figure 2: An Extension of the DeLone/McLean Model of IS Success, based on the Sanders/Garrity (1995) Modification
Spring • 1998
Information Resources Management Journal
39
Figure 3: Theory Foundation for the User Affective Response (UAR) Construct
such as content, accuracy, and timeliness (Pearson, 1977). It
must invest in the system (e.g., training requirements, effort,
is posited that some of these interface attributes may have a
time, cognitive requirements, and costs). This investment is
process orientation and some may have an outcome orientaevaluated in conjunction with the perceived returns, and a
tion; some may tap better into the notion of satisfaction, while
comparison to other users of other systems is made to deterothers may tap better into dissatisfaction.
mine relative efficiency. If the returns of the process are
These notions (process, outcome, satisfaction, and disgreater than the investment required to generate those returns,
satisfaction) are supported by equity, expectancy, and needs
the process would be considered efficient, and thus fair and
theories from the referent discipline of organizational behavsatisfying. If the process of converting investment into returns
ior. Each of these theories (and their support for these four
is not efficient, the process would be considered inefficient,
and thus unfair and dissatisfying. The efficiency of the system
notions) is discussed in detail below.
is constantly reevaluated by the user, so that the effect on UAR
Equity Theory — Process
is dynamic. Thus, equity theory emphasizes efficiency. Those
Equity (or inequity) is the result of an individual’s
users who have considerable interaction with the IS (i.e. entry
evaluation of his or her inputs and rewards in comparison to
clerks) may give added importance to the efficiency with
another’s inputs and rewards. People appraise rewards in
which the processes produce the outputs. Process facets
terms of their fairness (Locke & Latham, 1990). If a discrepwould include the ease of learning and using an application,
ancy is perceived between one’s efforts and rewards compared
recalculation speed, refresh rate, and error recovery rate.
to another’s efforts and rewards, the individual is motivated to
Expectancy Theory — Outcome
reduce this discrepancy. As Figure 3 shows, one’s perception
of fairness is also moderated by one’s cognitive development.
Expectancy theory focuses attention on outcome. Ex“People who have attained high levels of cognitive developpectancy theory posits that individuals consider alternative
ment are better able to apply equity propositions than are those
outcomes, analyze the costs and benefits of each outcome, and
who have not achieved these levels” (Landy & Becker, 1987,
choose an outcome that maximizes their utility. As shown in
p. 16). There is evidence that equity in the mind of an
Figure 3, affecting this decision are valence — the strength of
individual is continually being recalculated and reassessed
one’s preference for an outcome, and expectations — the
(Greenberg & Ornstein, 1983). It follows that UARs ebb and
likelihood that a particular outcome will occur. Likewise,
flow based on one’s equity recalculations.
valence and expectations affect UAR. If a user’s valence is
In an information systems context, equity theory focuses
high, UARs are affected depending upon how strongly the
attention on the fairness of the process. A user’s perception
outcome is expected and whether the outcome actually occurs.
of the inputs required and the results obtained using one
In an IS context, expectancy theory emphasizes the
system are compared to the inputs required and the results
effectiveness of the outcome. For most managers who rely on
obtained by others using other systems. Inputs are what a user
IS to support decisionmaking, outcomes (generated docu40
Spring • 1998
Information Resources Management Journal
Vol. 11, No. 2
ments and reports) are the very reason for the existence of an
IS. The importance of the layout and format of reports to
decision makers is well documented (Swanson, 1974;
Gallagher, 1974; Igersheim, 1976; Zmud, 1979; O’Reilly,
1982; Jenkins & Ricketts, 1985). To many users (upper
management and users who do not interact very often with the
IS), the outcome of an IS is more important than the processes
that produced the outcome.
Both the perceived efficiency of the process and the
effectiveness of the outcome have an impact on UAR, and the
effects of both equity (process) and expectancy (outcome) are
moderated by needs. Both process and outcome must be
considered in light of users’ needs.
Needs Theory
Needs theory is primarily based on the works of Maslow,
Alderfer, and Herzberg. All three agree that there are “need
levels,” although they disagree on the number of levels and the
categorization of needs. They also view satisfaction differently. Maslow introduces a satisfaction-progression dimension, Alderfer adds a dissatisfaction - regression component,
and Herzberg, in his two-factor theory, discusses satisfaction
and dissatisfaction as two different constructs (Herzberg,
Mausner, Peterson, & Capwell, 1957).
Landy and Becker (1987) stress the cognitive element in
needs theory by arguing that individuals create their own
unique needs categories. As seen in Figure 3, the creation of
these needs categories is influenced by an individual’s cognitive abilities, experience, and the situation in which he or she
works. Because individuals construct their own unique needs
categories, any evaluation of UAR must consider needs theory.
In summary, the notions of process and outcome have
roots in foundational theories of organizational behavior, and
this provides a basis from which to consider the impact of these
notions on user responses to an IS. Although theory suggests
that these notions impact user responses to an IS, process and
outcome do not necessarily have an equivalent impact. For
example, users who have considerable interaction with the IS
(i.e., entry clerks) may give added importance to the efficiency
with which the processes produce output. Also, in some group
decision support systems, the process by which the decisions
are made may take precedence over the decision itself.
Alternatively, there are situations where the outcome is
considered more important than the process. There are some
application environments where the outcome is considered so
important that a frustrating process will be tolerated. Here,
outcome dominates process in the UAR evaluation. One
example is the current state of equation editors. Most are very
tedious to use and require disproportional amounts of computer resources, yet many find the professional looking output
to be worth the frustrating process.
US and UD
In Figure 3, US and UD are shown as related but separate
constructs. That US and UD are separate constructs is also
Spring • 1998
suggested by equity, expectancy, and needs theories and
supported by both empirical and anecdotal evidence. In fact,
depending upon the theory, US or UD may be the more salient.
In terms of equity theory, the more salient of the two in an IS
context is UD. This is a result of overselling the capabilities
of a system. Wittingly or unwittingly, information systems are
often oversold and users are rarely pleasantly surprised by the
efficiency of the system that is actually delivered. In this way,
US is not increased because the system simply performs as the
designer claimed it would. Rather, users become dissatisfied
when the system fails to meet their understanding of the
designer’s claims.
In expectancy theory, US and UD depend upon the
combination of expected outcome and valence. Combining
expected or unexpected outcomes with high or low valence
produces four possibilities: 1) high valence and expected
outcomes; 2) high valence and unexpected outcomes; 3) low
valence and expected outcomes; and 4) low valence and
unexpected outcomes. These are shown in Table 1.
As Table 1 shows, only the high valence situations, affect
US and UD. Only when the user has a high desire for a
particular outcome is US or UD affected. If the user has no
preference for a particular outcome, neither US nor UD is
affected. Assuming high valence, US is obtained when the
user has low expectations of realizing the outcome, and yet the
outcome is realized. Conversely, UD occurs when a user
strongly desires an outcome, fully expects to realize the
outcome, and yet the outcome does not materialize. Consider
the following example.
Suppose a decision is to be made about an operating
system. DOS is currently in use, but a move is underway to
move to either UNIX or Windows NT. If the user has no
preference for either UNIX or Windows NT, then neither US
nor UD will be associated with the decision. On the other
hand, if the user has a strong preference for one of these
operating systems, either US or UD will be associated with the
outcome. A user who strongly wants to move to Windows NT,
but who has low expectations of this occurring, will experience some degree of US if Windows NT is chosen. Conversely, the selection of Windows NT will produce UD in
those who had a strong preference for UNIX and who fully
expected it to be chosen.
In related empirical work, Avery and Jones (1985) show
that reward and punishment are not points on a single continuum, but are two independent constructs. The factors that
Valence
(desire for
outcome)
High
High
Zero
Zero
Expectancy
(likelihood of
outcome)
High
Zero
High
Zero
Outcome
Occurred
Outcome Did
Not Occur
Zero US
High US
Zero US
Zero US
High UD
Zero UD
Zero UD
Zero UD
Table 1: Valence and Expectation Combinations
Information Resources Management Journal
41
are considered rewards are not necessarily the same factors as
those whose absence defines punishment. Likewise, the
factors that produce satisfaction are not necessarily the same
factors as those whose absence produces dissatisfaction.
Locke and Latham (1990) suggest one possible explanation for the believed nonsymmetrical relationship of satisfaction and dissatisfaction. Human beings often assume too
much credit when an outcome is successful and too little blame
when an outcome is not successful. Because success is often
attributed to one’s own efforts, when a successful outcome is
obtained, higher satisfaction results (Locke & Latham, 1990).
Conversely, when an unsuccessful outcome occurs, dissatisfaction does not necessarily occur because humans tend to
attribute unsuccessful outcomes to others, discounting the
contribution of their own shortcomings to the failure.
Expectancy theory also suggests that satisfaction and
dissatisfaction are independent constructs. For example,
Landy and Becker (1987, p. 20) write,
...when positive outcomes are involved, more is better.
The same relationship does not hold, however, when
negative outcomes are involved. The decision process
seems to be much more primitive. When negative
outcomes are involved, it does not seem to matter how
negative they are. In other words, the extent of negativity
is not related to the force to avoid that outcome — more
is not worse. The case of negative outcomes seems to be
all or none.
Likewise, needs theory points to the nonsymmetrical
relationship between satisfaction and dissatisfaction. In fact,
this is the essence of Herzberg’s two-factor theory (Herzberg,
et al., 1957). Despite its virtual dismissal as a theory of
motivation, Herzberg’s work has merit as it relates to the
constructs of satisfaction and dissatisfaction. Indeed, one of
the criticisms of Herzberg’s two-factor theory is that it focuses
on “satisfaction” rather than on the actual motivation of an
employee (Szilagyi & Wallace, 1987). In fact, Herzberg
considered satisfaction and dissatisfaction to be two different
constructs. In IS, US and UD seem to be two separate unipolar
constructs. The items or situations that contribute to US are
not necessarily the same as those that promote UD. Empirical
results support this contention (Woodroof & Kasper, 1996).
Integrating equity (process) and expectancy (outcome)
theories with US and UD results in a four category classification scheme shown in the center of Figure 3: US and UD with
a process and US and UD with an outcome. Needs are nested
within each of these four categories, and may differ with the
particular IS situation.
Implications
measuring UAR, two phenomena are apparent: 1) the outcome-oriented questions far outnumber the process-oriented
questions, and 2) the positively-framed questions far outnumber the negatively-framed questions. Without adjustment, this can produce misleading results. Consider, for
example, the “overall” satisfaction statistics provided by Doll
and Torkzadeh (1988). According to their measures, an
overall satisfaction score of 49 or more would indicate that a
user was satisfied with an application, while an overall satisfaction score of less than 49 would indicate that a user was not
satisfied with an application. However, because of the disproportionate weighting of process and outcome questions (less
than 20% of the questions are related to process), the scores are
inconclusive. For example, it is possible for a user to respond
with low satisfaction to an application’s outcome, high satisfaction with the process of an application, and yet have a low
overall US score on this instrument.
Summary and Conclusions
Research on users’ affective responses to information
systems has suffered from a lack of conceptual development.
This paper proposes such a foundation, integrating three
established organizational behavior theories. This conceptual
foundation provides a framework for studying UAR. The
framework is significant because it integrates theories of
satisfaction and categories of IS support, identifying process
and outcome satisfaction and dissatisfaction as salient to
UAR.
The contribution of this paper may be seen in three ways.
First, for information systems to be considered successful,
they must be both effective (outcome) and efficient (process).
When studying user responses to an IS, it is important to
consider the potential impact that the notions of process and
outcome have on US and UD. Second, research on the
development of future instruments should consider the mix
and weighting of process-oriented and outcome-oriented questions. Finally, the conceptual development of this paper has IS
design implications, suggesting that information systems should
be designed to enhance the user’s process and outcome satisfaction, or perhaps a more realistic goal, to reduce the user’s
process and outcome dissatisfaction.
Endnote
1
According to Sanders and Garrity (1995, p. 6-7),
“Decision making satisfaction is related to task support satisfaction, but there is a difference in terms of focus and details...
Whereas task support satisfaction applies to both managers
and non-managers, decision making satisfaction focuses on
personnel that primarily have decision making responsibilities.”
In reviewing most of the more popular instruments
42
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Information Resources Management Journal
Vol. 11, No. 2
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Jonathan B. Woodroof is an assistant professor of Accounting at Middle Tennessee State University in Murfreesboro,
Tennessee, where he teaches the accounting information systems courses. His research areas of interest include
accounting information systems, end-user computing, human-computer interaction, interface design, and the Internet.
George M. Kasper is the Chair of the Department of Information Systems and Quantitative Sciences in the College of
Business Administration at Virginia Commonwealth University in Richmond, Virginia.
Spring • 1998
Information Resources Management Journal
43
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SMEs in India
Munmun Basak and Indranil Guha (2016). Teaching Cases Collection (pp. 51-61).
www.irma-international.org/article/e-procurement-utilisation-in-the-maintenance-repair-andoverhaul-mro-supply-chain-by-smes-in-india/162790/
Establishing the Credibility of Social Web Applications
Pankaj Kamthan (2009). Encyclopedia of Information Science and Technology, Second Edition (pp. 14321437).
www.irma-international.org/chapter/establishing-credibility-social-web-applications/13764/
The Impact of Computer Self-Efficacy and System Complexity on Acceptance of Information
Technologies
Bassam Hasan and Jafar M. Ali (2009). Best Practices and Conceptual Innovations in Information
Resources Management: Utilizing Technologies to Enable Global Progressions (pp. 264-275).
www.irma-international.org/chapter/impact-computer-self-efficacy-system/5522/