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MEASURING USER SATISFACTION AND PERCEIVED USEFULNESS IN THE ERP
CONTEXT
===============================================================

By Pliskin, Nava
Publication: The Journal of Computer Information Systems
Date: Friday, April 1 2005
HEADNOTE

ABSTRACT

Initially, Enterprise Resource Planning (ERP) systems held the promise
of easily integrating all processes within and around the
organization. Many reported ERP failures have led us to conduct,
within the context

of ERP implementation, an empirical examination of two success
indicators: user satisfaction and perceived usefulness. The results
reveal high levels of user satisfaction and perceived usefulness, both
in nominal values and in comparison to other systems. They also show a
strong correlation between perceived usefulness and user satisfaction,
suggesting that perceived usefulness is one of the factors affecting
user satisfaction with ERP systems. On the other hand, hypotheses
testing revealed no supporting evidence for possible relationships
between user satisfaction or perceived usefulness and organizational
characteristics such as the department to which the respondent
belonged or user characteristics such as organizational level,
education, age, computing experience, and gender.

Keywords: Enterprise Resource Planning (ERP), user satisfaction,
perceived usefulness.

INTRODUCTION

The role of information systems (IS) has increased in importance over
recent decades to the point where it now represents about half of all
capital investment on a global basis (40). In addition, growing
numbers of strategic IS that shape or critically support
organizational processes have also been reported (40). In 1969,
Blumenthal (7) proposed an integrated architecture for organizational
IS and to this day, enterprise application integration is considered
an important issue. Enterprise Resource Planning (ERP) systems,
defined as "configurable information systems packages that integrate
information and information-based processes within and across
functional areas in an organization" (33), promise seamless
integration of financial, accounting, supply chain management, human
resources, and customer information (44, 71)

Reports about successful and failed ERP implementations (9) have led
us to propose a system development methodology for an ERP system (2)
and to conduct an empirical examination of two success indicators
within the context of ERP implementation (see next section): user
satisfaction and perceived usefulness. As described in the third and
fourth sections, our study tests the relationships between user
satisfaction, perceived usefulness, and a set of personal and
organizational characteristics, making use of an empirical survey
conducted in Canada. Implications from the results, for practice and
research, are presented in conclusion.

LITERATURE REVIEW

Both practitioners and researchers recognize the need to evaluate IS
success (40, 57). Measurement of IS success first appeared on the
research agenda in the early 1970s (32, 39, 45, 48, 63, 75) Zmud (73),
whose research was based on Ginzberg's (19) study, identified eight
dimensions affecting IS. Vertinsky et al. (70) found performance to be
most highly correlated with self-predicted use. Building on Vertinsky
et al. (70), Robey (54) suggested that IS success must be measured
through perceived measures rather than through direct measures.

The effort to identify the factors affecting IS success continued
apace throughout the 1980s and 1990s (e.g., 14, 34, 35, 36, 46, 65,
66). DeLone and McLean (11) introduced a model of IS success with six
major dimensions: system quality, information quality, use, user
satisfaction, individual impact, and organizational impact. Many
researchers, including Seddon (58), Melone (43), Torkzadeh and Doll
(69), Swanson (67), Bonner (8), Drury and Farhoomand (13), and
Ballentine et al. (4), referred to the DeLone and McLean model.
Research on IS success focusing on specifics such as executive systems
(52), expert systems (72), and planning systems (50), provided
refinement for the DeLone and McLean model. Most of these studies
included user satisfaction and perceived usefulness among factors
comprising IS success, relating them to other variables.

User Satisfaction

Over the years, the principal approach has been to regard user
satisfaction (6, 21) and system usage (45, 54, 61, 69) as surrogates
for each other and for IS success (43, 75) The gain in popularity of
user satisfaction as a measure of IS success (11, 28, 35, 48, 56) may
be attributed to the absence of a comprehensive agreed-upon instrument
and the intuitive connection to IS success (41) since, intuitively, if
users are dissatisfied with an IS, it is difficult to consider it a
success (3, 5, 12, 28, 53, 55, 68) reviewed the results of 45
user-satisfaction studies carried out between 1982 and 2000 and found
that the most frequently used scale for the measurement of user
satisfaction is the Bailey and Pearson (3) instrument. Ives et al.
(28) attempted to improve the Bailey and Pearson and introduced a
short form for situations where time is a major consideration and
their work was the basis for (5, 16, 38, 53, 68) However common and
prevalent, the reliability of usersatisfaction measures has been
repeatedly questioned (16, 18, 20, 31). In this study, we apply the
Doll and Torkzadeh (12) instrument, which has been packaged into a
structured questionnaire that presents twelve items, using a 5-point
Likert scale, ranging from "1" (almost never) to "5" (almost always).
Past research demonstrated instrument validity (41, 62).

Perceived Usefulness

Perceived usefulness has also been considered by many to be an
important measure of IS acceptance (10, 25, 29, 58. Larcker and Lessig
(34) studied perceived usefulness as a surrogate for IS success. Davis
(10), within the context of his Technology Acceptance Model (TAM),
found a significant positive correlation between perceived usefulness
and the predicted future use of the technology. His research was
replicated by others (1, 11, 23, 24, 25, 58, 60). Similarly to Igbaria
et al. (25), Seddon (58) included perceived usefulness in an adapted
version of the DeLone and McLean (11) model of IS success, concluding
that perceived usefulness affects user satisfaction and is affected by
system quality, information quality, and benefits to individuals,
organizations and society. In this study, we apply Franz and Robey's
(15) 12-item instrument.

User Characteristics

Department: Several studies have found significant differences between
different user groups in terms of user satisfaction (59, 74) and in
terms of perceived usefulness (24).

Position in Organizational Hierarchy: Some studies show no correlation
between organizational level and user satisfaction (23, 24). Another
study reports satisfied low-level employees as opposed to very
unsatisfied managers (30). Gallagher (17) suggested that perceived
usefulness may differ across users at different organizational levels.

Formal Education Level: Users with more formal education tend to use
computers more and greater user satisfaction. Igbaria's (23) and
Jackson et. al.'s (29) studies found higher perceived usefulness among
users with more formal education.

Age: Older users will express less IS satisfaction (47). According to
Igbaria's (23) and Jackson et. al.'s (29) studies, older users
perceive systems as more useful.

Computer Experience: More years of computer experience lead to greater
use of computers and to greater user satisfaction (47). Igbaria's (23)
and Jackson et. al.'s (29) studies found that users with better
computer skills perceive systems as more useful.

Gender: Gender differences in terms of computing attitudes, computer
use and computing practices have been widely studied (23, 47) and for
the most part found differences between men and women with regard to
user satisfaction and perceived usefulness.

RESEARCH MODEL AND HYPOTHESES

This study examines, in the ERP context, the relations between user
satisfaction and perceived usefulness (23, 25, 39, 49, 58, 76) as well
as six user characteristics: functional department to which the user
belongs, position in the organizational hierarchy, formal education
level, age, computer experience, and gender. The 13 hypotheses tested
are depicted in Figure 1.

METHODLOGY

The research is based on an empirical survey conducted at a plant
producing recreational vehicles in Canada. The ERP system (by SAP) at
the plant had been the main IS since its implementation and its use by
employees was, therefore, not voluntary. This particular site was
selected mainly because the ERP system had been introduced to the
users long enough prior to the study for them to have established
opinions by the time they were surveyed. The time span was, however,
short enough for the respondents to be still able to compare the ERP
system to the IS used prior to the ERP implementation. No less
important, the personal acquaintance of one of the authors with senior
management and the fact that implementations in other parts of the
firm were still forthcoming, ensured much needed topmanagement
interest in, and support for, the study.

Data were collected by means of a three-part questionnaire. The first
part consisted of questions on user characteristics including
position, department, age, level of education, level of computer
experience, and gender. The second part tested user satisfaction with
the system using Doll and Torkzadeh's (12) short-form questionnaire.
The third part tested perceived usefulness of the system using Franz
and Robey's (23) instrument. A letter from the organization's CIO,
urged the addressee to respond preceded the questionnaire, and a
privacy statement assured respondents that the survey was completely
anonymous and that the information provided would be used for
statistical analysis only.

The sample population consisted of 200 ERP users, belonging to
different departments, holding different levels within the
organization, and having different levels of computer experience and
education. In order to achieve a high return rate, a senior IT manager
was in charge of sending out the questionnaires and collecting them.
Of the 200 users surveyed, 184 (92%) returned questionnaires, of which
172 (86%) were valid.

RESULTS

Of the 172 respondents returning valid questionnaires, 70 (40.7%)
belonged to the Logistics Department. The remaining respondents
belonged to Production - 41(23.8%), Finance - 31 (18.0%), R&D - 19
(11.0%), Sales - 10 (5.8%), and anther department (not used) - 1
(0.6%). Organizational level was determined by the "position"
parameter in the questionnaire: 43 (25.0%) of the respondents were
classified as belonging to the high groups and 129 (72.7%) to the low
group. Education was classified into three levels: 124 (72.1%) did not
hold a university degree, 47 (27.3%) held university degrees, and 1
(0.6%) was N/A (not used). Four age groups emerged in the sample: 35
(20.3%) were in the 20-30 group, 61 (35.5%) were in the 30-40 group,
54 (31.4%) were in the group, 40-50, and 22 (12.8%) were over 50 years
old. All respondents had some computing experience, with 12 (7.0%)
having 1 to 3 years, 25 (14.5%) 3-5 years, and 135 (78.5%) over five
years of computing experience. Gender distribution was 114 (66.3%)
males and 58 (33.7%) females.

User Satisfaction

Table 1 contains descriptive statistics for the 12 user satisfaction
items in the questionnaire, using Doll and Torkzadeh's (12) short
form. Doll and Torkzadeh's (12) instrument consisted of five factors:
content (4 questions), accuracy (2 questions), format (2 questions),
ease of use (2 questions), and timeliness (2 questions). For this
study, exploratory factor analysis was conducted and factors were
extracted, testing limits of two to six factors and using principal
component analysis with the varimax rotation and the Kaiser
normalization. Most of the above-mentioned factors were not found
significantly outstanding nor did logical partition of the results
into meaningful factors emerge in any of the runs. Only ease of use,
also predicted by Doll and Torkzadeh (12), emerged as an outstanding
factor in all runs resulting in three or more factors. Natural (no
limit on the number of factors) factorization resulted in two factors
only, again with no meaningful value.

IMAGE ILLUSTRATION 1

FIGURE 1

Research Model and Hypotheses

The confirmatory factor analysis conducted is depicted in Figure 2,
and the standardized regression weights, inter-factor correlations,
and standard fit measures of the model are shown in Table 2, 3, and 4,
respectively. The high values in Tables 2 and 4 indicate that the
results fit the expected construct of Doll and Torkzadeh's 5-factor
model. However, the high correlation values in Table 3 suggest that a
model of one or three factors could be accepted here as well. This
finding validates the Doll and Torkzadeh (12) instrument for use on
ERP systems.

H1: NPar Kruskal-Wallis analysis showed no significant difference
between respondents belonging to different departments (p<0.05),
except for Item 3 of the 12. user satisfaction items: "Does the ERP
system provide up-to-date information?" (p = 0.037). One-way ANOVA
analysis showed no significant differences (p < 0.05) in user
satisfaction between users belonging to different departments, except
for Item 3, which was close to being significantly separable (p =
0.053). Thus, contrary to the findings of Sengupta and Zviran (59) and
Zviran (74), the results show no difference in user satisfaction
between users belonging to different departments.

IMAGE TABLE 2

TABLE 1

Averages and Standard Deviations for User Satisfaction

FIGURE 2

Confirmatory Factor Analysis Model

H2: NPar Mann-Whitney and T-Test analysis to examine for differences
according to organizational level showed no significant differences (p
< 0.05) in user satisfaction between low-level and high-level
employees. This finding supports previous results (22, 24).

H3: NPar Mann-Whitney analysis showed no significant differences in
user satisfaction (p < 0.05) between users of different education
levels except for Item 5 "Is the ERP system user friendly?" (p =
0.030) and Item 8 "Does the ERP system provide reports that seem to be
just about exactly what you need?" (p = 0.035). T-Test analysis showed
no significant difference in user satisfaction (p < 0.05) between
users of different education levels except for Item 8 (p = 0.028) and
for Item 5, which was close to being significantly separable (p =
0.051) here as well. Thus, contrary to prior research by Palvia and
Palvia (47), education seems to make no significant difference in
terms of user satisfaction.

H4: NPar Kruskal-Wallis and one-way ANOVA analyses showed no
significant differences (p < 0.05) in user satisfaction between users
of different ages. Tukey post hoc analysis found no definitive order
of user satisfaction levels between the users of different ages.
Contrary to prior research (47), no differences in user satisfaction
were found between users of different ages.

H5: NPar Mann-Whitney analysis showed no significant differences (p <
0.05) between users with different computing experience, except for
Item 4 out of the 12 user satisfaction items: "Does the information
content meet your needs" (p = 0.007). T-Test analysis showed no
significant difference (p < 0.05), except for Item 4 (p = 0.009).
Contrary to prior research (47), no differences in user satisfaction
were found between users with different levels of computing
experience.

H6: NPar Mann-Whitney and T-Test analysis to examine for differences
according to gender showed no significant differences (p < 0.05) in
user satisfaction between men and women, contrary to prior research
(47).

Perceived Usefulness

Table 5 contains descriptive statistics for the Franz and Robey's (15)
instrument.

IMAGE TABLE 3

TABLE 2

Standardized Regression Weights

TABLE 3

Correlations Between Factors

TABLE 4

Fit Measures

TABLE 5

Averages and Standard Deviations for Perceived Usefulness

As Franz and Robey did not report any factor analysis in their
instrument validation process, no confirmatory factor analysis was
conducted. No logical partition into meaningful factors was found in
any of the exploratory factor analysis runs conducted, testing the
limits of two to six factors and using principal component analysis
with the varimax rotation and the Kaiser normalization. Natural (no
limit on the number of factors) factorization resulted in four
factors, again with no meaningful values.

H7: NPar Kruskal-Wallis analysis showed no significant difference (p <
0.05) between users belonging to different departments, except for
Item 5 of the 12 perceived usefulness items: "To what extent do you
actually use the reports or output that are provided to you by the ERP
system?" (p = 0.029). Oneway ANOVA analysis showed significant
differences (p < 0.05) between users belonging to different
departments on five of the 12 items: Item 1 "To what extent do you
actually use the ERP system compared to your original expectations?"
(p = 0.002), Item 2 "To what extent could you get along without the
use of the ERP system?" (p = 0.001), Item 5 "To what extent do you
actually use the reports or output that are provided to you by the ERP
system?" (p = 0.007), Item 6 "To what extent do data that you receive
from the ERP system require correction?" (p = 0.015), and Item 9 "To
what extent do you understand what the ERP system does in assisting
you with your job?" (p = 0.013). Even though Tukey post hoc analysis
of these results revealed no definitive order of perceived usefulness
levels between the users belonging to different departments, two
observations are noteworthy. First, the Finance department scored
highest on five of the 12 items and was one of the two highest on 10
of the 12 items. Second, the Production department had the lowest
score on six of the 12 items. Contrary to Henry (22), no differences
in perceived usefulness were found between users belonging to
different departments.

H8: NPar Mann-Whitney analysis showed no significant difference (p <
0.05) between low-level and high-level employees, except for Item 4
out of the 12 perceived usefulness items: "To what extent did you get
along better on your job before the ERP system was implemented?" (p =
0.037). T-Test analysis also showed no significant difference (p <
0.05) between low-level and high-level employees, except for the same
Item 4 (p = 0.034). Thus, supporting Galetta and Lederer (17),
organizational level makes no difference in terms of perceived
usefulness.

H9: NPar Mann-Whitney analysis showed no significant difference (p <
0.05) between users of different education levels, except for Item 1
out of the 12 perceived usefulness items (p = 0.033). T-Test analysis
also showed no significant difference (p < 0.05) between users of
different education levels, except for Item 1 (p = 0.033). Thus, no
difference in perceived usefulness between users with different levels
of education, contrary to prior research (23).

H10: NPar Kruskal-Wallis and one-way ANOVA analyses showed no
significant differences (p < 0.05) in perceived usefulness between
users of different ages. Tukey post hoc analysis found no definitive
order of perceived usefulness levels between the users of different
ages. Contrary to prior research (23), age made no difference in
perceived usefulness.

H11: NPar Mann-Whitney analysis showed no significant difference (p <
0.05) between users of different computing experience except for Item
8 out of the 12 perceived usefulness items: "To what extent does the
ERP system provide reports to you that seem to be just about exactly
what you need?" (p = 0.002). T-Test analysis also showed no
significant difference (p < 0.05) between users of different computing
experience, except for Item 8: (p = 0.006). Contrary to prior research
(23, 29), different computing experience makes no difference in terms
of perceived usefulness.

H12: NPar Mann-Whitney analysis showed a significant difference (p <
0.05) between men and women on four out of the 12 perceived usefulness
items: Item 1 (p = 0.000), Item 3 "To what extent does the ERP system
assist you in performing your job better?" (p = 0.010), Item 7 "To
what extent does the ERP system overload you with more data than it
seems you can possibly use?" (p = 0.016), and Item 10 "To what extent
is the ERP system troublesome for you, or difficult to operate, or to
interact with, in order for you to get information to accomplish your
job?" (p = 0.007). T-Test analysis of the results also showed a
significant difference (p < 0.05) on the same four items: 1 (p =
0.000), 3 (p = 0.010), 7 (p = 0.019), and 10 (p = 0.017) with women
scoring higher. Thus, contrary to prior research (23), gender made no
significant difference in perceived usefulness.

Perceived Usefulness versus User Satisfaction

Table 6 shows the Pearson correlations between perceived usefulness
and user satisfaction in the ERP context. Each question in the
perceived usefulness questionnaire was correlated with the total mean
of user satisfaction. Also, the total mean of perceived usefulness was
correlated with the total mean of user satisfaction. As evident from
Table 6, for 11 of the 12 questions and for the total mean, perceived
usefulness is highly correlated (sigma < 0.01) with user satisfaction.

IMAGE TABLE 4

TABLE 6

Correlations of Perceived Usefulness with the Mean User Satisfaction

Figure 3 provides a graphical representation of the results listed in
Table 6, showing perceived usefulness and user satisfaction to be
directly related in the ERP context. The milder effects of subgroup
division on user satisfaction may suggest that perceived usefulness is
a more primary measure than user satisfaction.

H13: The strong correlation between perceived usefulness and user
satisfaction, along with the stronger separation among subgroups in
the measurement of perceived usefulness suggest, as do other studies
(23, 25, 39, 58), that in the ERP context perceived usefulness
directly affects user satisfaction.

SUMMARY AND CONCLUSIONS

This study used two survey instruments developed in prior research-to
measure user satisfaction and perceived usefulness in the ERP context,
providing validation for the Doll and Torkzadeh (12) instrument. The
strong positive correlation between perceived usefulness and user
satisfaction demonstrated in this study suggests that perceived
usefulness is one of the factors affecting user satisfaction with an
ERP system, corroborating the strong relationship between perceived
usefulness and user satisfaction that has been well documented in the
non-ERP context.

Neither user satisfaction nor perceived usefulness seemed associated
with the user characteristics investigated in this study, namely:
department, organizational level, age, computing experience,
education, and gender. The effects of ERP consolidation and
standardization may explain why department does not seem to make a
difference since users of a single standard system are more likely to
be equally satisfied than the users of many dissimilar systems. The
strong management support at the survey site may explain why
organizational level does not seem to make a difference since
low-level employees and managers are likely to react similarly to an
ERP system when top management is supportive. The effects of ERP
consolidation, especially interface standardization may explain why
education, age, computer experience, and gender do not seem to make a
difference since standard ERP systems are geared toward all user types
in terms of education, age, computer experience, and gender. Even
though respondents reported relatively high levels of computing
experience, it is reasonable to assume that a system with a standard
and easy to use interface requires less computing experience to
operate.

IMAGE GRAPH 5

FIGURE 3

Pearson Correlations of Perceived Usefulness with User Satisfaction

The results of the current study are significantly different from the
results of other studies on non-ERP systems (12, 26, 41, 51, 55) and
suggest that user satisfaction levels measured here are significantly
higher than those reported by others. These differences may suggest
that ERP systems, being large and complex compared to most other ISs,
especially when additional modules are added (37), must be studied
separately to provide practical insights.

The main weakness of this paper is that the external validity of this
survey is very limited because data was collected by distributing all
questionnaires to the employees in the same company, at a single site,
using one vendor's ERP system (49, 64). Thus, without representing the
diversity of culture and structure, the generalizability of the study
is a major concern. For example, the results reported in this paper
might be strongly influenced by specific situation of the survey site
such as strong management support and thus might not be generalizable.
Data collection in only one organization is especially problematic
when results are significantly different from the results of other
studies. Extra empirical studies at multiple sites, using ERP systems
from the same and other vendors, are needed in future work for
achieving higher levels of generality and external validity.

The other limitations illustrated are less crucial but also have
implication for future research. First, not enough organizational
information (e.g., relative changes in work processes required by
different departments) or project information (e.g., implementation
duration) was gathered. Since such information could have been helpful
in the analysis of the results and may have produced more interesting
conclusions, it is recommended that future studies collect such
organizational information. second, this study considers only two of
the factors affecting IS success: user satisfaction and perceived
usefulness. A better understanding of ERP success will be achieved by
studying in the future other factors affecting success, including user
involvement, top management support, and user attitudes. Third, the
study is limited by its focus on a successful ERP implementation, with
its inherently high levels of user satisfaction and perceived
usefulness, and the exclusion of less successful implementations. A
better understanding of the factors affecting ERP success, user
satisfaction and perceived usefulness could be attained if, in further
research, unsuccessful ERP systems are studied as well. Fourth, in the
absence of a "standard" instrument for the measurement of perceived
usefulness (such as the one used in this study for the measurement of
user satisfaction), comparison to similar studies was not possible but
might become possible in the future after more progress is made toward
a perceived-usefulness instrument.

With this paper's contribution as a starting point, i.e., the
relationships between user satisfaction, perceived usefulness, and a
set of personal and organizational characteristics found in one plant,
future research can thus focus on validating the Doll and Torkzadeh
user satisfaction instrument (12) and Franz and Robey perceived
usefulness instrument (15), using methodology that analyzes in
additional ways more data from various organizations which use a
variety of ERP systems. Such studies can provide more general and
valid findings regarding ERP system success, user satisfaction, and
perceived usefulness. Another suggestion for future study concerns
inclusion of other documented factors affecting IS success, such as
user involvement, top management support and user attitudes, to
provide a better understanding of the factors affecting ERP success.

Because it is difficult to generalize the results of this study, the
practical implications mentioned next must be considered with caution.
One practical implication of this study arises from finding ERP
systems to behave differently from other IS types with respect to
demographics. Another practical implication arises from finding a
nominally high level of user satisfaction with ERP systems. ERP
practitioners can use these practical implications to improve ERP
design and implementation processes, to implement better ERP systems,
and to achieve higher ERP success rates and more user satisfaction.

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AUTHORAFFILIATION

MOSHE ZVIRAN

Tel Aviv University

Tel Aviv, Israel

NAVA PLISKIN

Ben-Gurion University of the Negev

Beer-Sheva 84105, Israel

RON LEVIN

Tel Aviv University

Tel Aviv, Israel

 

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