Directory UMM :Data Elmu:jurnal:I:Information and Management:Vol37.Issue4.Jun2000:

Information & Management 37 (2000) 77±86

A model of end user attitudes and intentions toward
alternative sources of support
Chittibabu Govindarajulua,*, Brian J. Reithelb, Vikram Sethic,1
b

a
Management Department, LeBow College of Business, Drexel University, Philadelphia, PA 19104, USA
Department of Management & Marketing, School of Business, The University of Mississippi, University, MS 38677, USA
c
Computer Information Systems Department, College of Business Administration, Southwest Missouri State University,
Spring®eld, MO 65804, USA

Received 8 October 1998; accepted 26 July 1999

Abstract
End-user computing has been the focus of research for over a decade. Recent studies on end-user computing support
concluded that end users are dissatis®ed with the support provided by the information center. In addition to support from an
information center, end users seek help from informal sources and local MIS staff. In this study we examine why end-users
prefer one source of support (e.g. information center) to another (e.g. local MIS staff). In order to understand end user

preferences, we study the factors that affect end user attitude toward a support source. Attitude is an important component in
determining user behavior toward using a support source. In this study, a model of end user attitudes and intentions toward the
source of support is presented. Analysis of data collected from 108 middle-level managers shows that respondents preferred
the use of local MIS staff to both information centers and informal support sources. The results appear to re¯ect an emerging
trend in EUC support and implications of these results are examined in the study. # 2000 Elsevier Science B.V. All rights
reserved.
Keywords: End-user computing support; EUC support sources; Informal support; Local MIS staff; Support services perceived to be important
by users; User attitude; User intention

1. Introduction
End-user computing (EUC) is de®ned as systems
developed by end users to support their decisionmaking [1]. The advantages of EUC have been well

*
Corresponding author.Tel.: ‡1-215-895-2142.
E-mail addresses: chitti@drexel.edu (C. Govindarajulu),
vis875f@mail.smsu.edu (V. Sethi).
1

Tel.: ‡1-417-836-5078

documented in the literature [9,15,21,28]. Likewise,
their risks have been clearly identi®ed [3,5,36]. Concurrently, it has also been consistently identi®ed as a
major concern for IS executives in both the private and
public sectors [11,31]. For example, Guimaraes and
Ramanujam [22], have noted that, as the level of PC
activity rises, the types and intensity of associated
problems increases, among others, due to data integrity and cost. Hence, the effective management of
EUC is required to minimize risks and to maximize
gains from IS investments. One element of EUC

0378-7206/00/$ ± see front matter # 2000 Elsevier Science B.V. All rights reserved.
PII: S 0 3 7 8 - 7 2 0 6 ( 9 9 ) 0 0 0 3 4 - 8

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C. Govindarajulu et al. / Information & Management 37 (2000) 77±86

management-end-user support-has been identi®ed as
key to developing better applications. For example, a

recent study [17] reported that the quality of user
developed applications is extremely low. They had
a high frequency of errors and data integrity problems.
Appropriate support can assist in reducing, if not
eliminating, such problems.
Although many organizations provide this support
through information centers (IC), users tend to be
dissatis®ed with these services. They also tend to
be more receptive to support from sources such as
local MIS staff and colleagues. Indeed, end users
prefer informal support even when formal support
is available [19]. However, it is not clear why users
select a speci®c support source. In order to answer this
question, it is important to understand users' positive
or negative attitudes toward a support source and how
these affect usage of that source. Thus, the main
objective of this study is to determine the factors that
affect users' attitudes toward alternative sources of
support and the effect of these attitudes on user
behavior.

Three support sources were considered: (1) information centers; (2) local MIS staff; and (3) friends/
colleagues. These were selected for two reasons:
1. Each support source has a different approach; ICs
represent the formal, centralized approach; local
MIS staff represent semi-formal, decentralized
approach; and friends/colleagues represent an
informal, decentralized approach; and
2. These support sources constitute the major types
of end-user support identified in the literature.

2. Sources of support for EUC and end-user
satisfaction
2.1. The information center
The traditional approach to end-user support has
been the establishment of an IC. The IC helps users
help themselves by providing mentors, trainers, and
technicians. IBM established the ®rst IC in Canada in
the mid-seventies. After its success, the concept
became popular and organizations started to adopt
this approach to provide support. Hammond [23]

provides prescriptions IC support services, staf®ng

ratios, job descriptions, control policies/procedures
and organizational design guidelines. The services
offered can be grouped into six categories : (1) hardware support; (2) software support; (3) data support;
(4) functional support; (5) training and education; and
(6) miscellaneous, such as the provision of hot-line
telephone assistance, publication of a newsletter, etc.
Chian et al. [12] and Wetherbe and Leitheiser [41],
give similar categorizations.
The information center was rated as the most
important source of support. In addition, Bergeron
and Berube [6] reported that users were more satis®ed
with the IS environment when an IC was present.
However, another study reported that there is a mismatch between services expected by users and services provided by IC [37]. Mirani and King [32], also
reported differences in the support expectations of
different types of end users. Consistent with these
®ndings, Nord and Nord [35] found that a signi®cant
percentage of end users were less-than-pleased by the
support provided by information centers. Thus, results

are ambiguous.
2.2. Local MIS staff
A more recent form of end-user support is the local
MIS staff who exclusively support end users of a
speci®c department and often report to the functional
departmental manager. A study conducted by the
American Management Association found that, of
the 250 organizations examined, most routine IC
functions, such as installing hardware and software,
were assigned to user departments [20]. In these
organizations, ICs were mainly responsible for communications technology, training, and data backup and
security. In addition, this study reported that 30 percent of large companies had MIS specialists on departmental budget lines to support users in that
department, and 10 ®rms with IC were planning to
phase them out, while three ®rms had already eliminated. Though the percentage of IC managers reporting to user departments and the percentage of user
departments having MIS staff is low (30 percent of the
large companies studied), these reported results seem
to indicate the emergence of a trend.
Local MIS staff support may not be responsible for
assisting users in application development and data
acquisition. Interviews with 10 local MIS personnel in

C. Govindarajulu et al. / Information & Management 37 (2000) 77±86

79

a southern university and three southern companies
about their responsibilities con®rmed this.
2.3. Informal support
This consists of technical help or advice from peers,
friends, and lead users (advanced users) in user development of applications. Informal support sources have
received considerable attention in the EUC literature
(e.g. [33,38]).
Brancheau et al. reported that users generally seem
to maintain an informal network for their support
needs. The study showed that only 13 percent of
the users relied exclusively on the IC. Pyburn noted
that the IC was not seen as a particularly useful source
of training and expertise and that users gained most of
their experience by learning on their own or from
discussion with peers. Munro et al. found that the lead

user was more ef®cient than the support group staff in
providing support. In a study conducted by Lee, a
large proportion of PC users (89 percent) reported that
colleagues are their main sources of information.
Bergeron and Berube, in their empirical study of
the EUC environment, reported that user satisfaction
with respect to microcomputing activities was negatively correlated to the level of consultation with the IS
group. They also pointed out that those users who seek
help from members of their own department for
microcomputing activities were more satis®ed. A
survey by Bowman et al. [8] reported that assistance
from `Another user' received an average rank of 1.96,
whereas assistance from `Computing center' received
a mean rank of 3.78 (where 1 ˆ most important, and
9 ˆ least important). These studies highlight the
importance that end users place on informal support.

Fig. 1. Theory of reasoned action ([2,18]).

vior. Sheppard et al. [39] conducted meta-analyses of

past research on TRA and concluded that the predictive utility of the model remained strong. In IS
research, TRA has been applied to IS settings by a
few researchers [4,13]. Davis developed the Technology Acceptance Model (TAM) from TRA for user
acceptance of IS. Davis et al. used TRA and TAM to
study user behavior in accepting computer technology.
Similarly, Jackson et al. [27] use TAM to present a
holistic framework and examine the various constructs
that lead to behavioral intention to use an IS.
3.1. Theory of reasoned action
According to TRA (Fig. 1), a person's behavior
intention is a function of two components, one personal in nature (attitude) and the other re¯ecting social
in¯uences (subjective norm). Attitude is the individual's positive or negative evaluation of the proposed
behavior. A subjective norm is the person's perception
of the social pressures put on him/her to perform or not
perform the behavior in question. According to the
model, attitudes are a function of behavioral beliefs.
3.2. The research model

3. Development of a model of end-user attitudes
toward support sources

Considerable research has been performed in social
psychology about a person's attitudes and how they
may affect behavior. Speci®cally, Fishbein and
Ajzen's [2,18] Theory of Reasoned Action (TRA) is
a widely accepted model that has been used in predicting and explaining behavior across a wide variety
of domains [14]. For example, it has been used in
marketing management to understand consumer beha-

Fig. 2 presents the TRA model as applied to the enduser context. There are two differences between these
models and the TRA. Since the context is end-user
support, behavioral beliefs in the original model
(TRA) have been replaced with user evaluation of
the support source. A user may evaluate a support
source on many dimensions such as the degree of
support received and proximity of support services. It
is proposed that the user may develop a positive or
negative attitude toward the source of support. Second, since this study is not longitudinal, actual beha-

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C. Govindarajulu et al. / Information & Management 37 (2000) 77±86

Fig. 2. A model of end user intentions and attitudes toward the
source of support.

viors (results of behavior intentions) cannot be measured. Hence, this construct was dropped.
3.2.1. User evaluation of the support source
In order to identify factors that may in¯uence user
attitude, a detailed review of the literature on user
information satisfaction was made. Based on this, the
important variables that in¯uence user attitude are: (a)
degree of support received on areas perceived to be
important by the users, (b) proximity of services, (c)
support staff quality, and (d) quality of EUC applications.
Degree of support received on areas perceived to be
important by the users
In a study based on a survey of 126 ICs, Rainer and
Carr [37] reported differences between their services
and the needs of the users. They compared the percentage of ICs offering a service to the percentage at
which end users requested the service. The service
assist user in locating data ranked 17th in IC managers offering it, while end users ranked it ®rst.
Similar differences in rank of more than 10 are
reported for several services offered. Mirani and King
also noted a mismatch of support requirements. This
may be one of the reasons for user dissatisfaction with
ICs.
Due to this mismatch, it is suggested that when
the level of support received is high in areas thought to
be important by end users, they hold a favorable
attitude toward the support group. A comprehensive
list of 12 support items based on Rainer and Carr's
study was produced for this factor. This list was
prepared based on end user requirements for support
and includes items such as help in application maintenance, help in data transfer, and help in designing
applications.

Proximity of services
Proximity of services is an important factor. Contacting a MIS person who is located in the same
department is easier than contacting an IC staff member located elsewhere. Bergeron et al. [7] found a
positive relationship between the proximity of services and user autonomy. Given two support sources
that are equally good, an end user will prefer the
source that is closer. Although users may not hold a
negative attitude towards a more distant support
source, close proximity may positively in¯uence attitude. Items such as Source can be accessed with ease
and Source available all the time were used to measure
this construct.
Quality of support staff
Researchers have consistently identi®ed competent
staff and good communication with users as critical
for the success of ICs [30]. In addition, relationships
with support staff [26] and the support staff's attitude
toward end users are equally crucial. Four items
representing each of the above qualities were used
to measure this construct.
Quality of EUC applications
The quality of EUC applications developed by end
users is an important dimension of IC success [16,29].
This factor is similar to the `information product' of
Ives et al. and Igbaria and Nachman [25]. Since EUC
applications are the ®nal result of EUC activities, this
factor may be a major determinant of user attitude.
The following items used by Ives et al. were adopted
to operationalize this construct: reliability, accuracy,
precision, and completeness.
3.2.2. User attitude, subjective norm, and behavior
intentions
In the end-user support context, attitude is de®ned
as the user's evaluative judgment of the support source.
The attitude may be positive or negative, depending
upon evaluation of the support source. In our model,
attitude and subjective norms are the major determinants of a user's intention to use a support source. Given
that informal support is popular among end users, subjective norms can be expected to have an effect on user
intentions. In the model, behavioral intention refers
to a user's intention to use a speci®c support source.
The items used to measure these constructs were
based on the guidelines of Fishbein and Ajzen. Some
of these are;

C. Govindarajulu et al. / Information & Management 37 (2000) 77±86

The support source is
What my friends think about me is
(Motivation±subjective norm)
My friends think I should (Normative
belief±subjective norm)
I plan to use the support source

81

Not suitable for me. . .Suitable for me (Attitude)
Important to me. . .Not important to me
Use the source. . .Not use the source
Many times. . .Occasionally (Behavior intention)

3.3. Research hypotheses
The research hypotheses are:
H1: The quality of support staff is positively
related to user attitude.
H2: The quality of EUC applications is positively
related to user attitude.
H3: Degree of support received in areas perceived
to be important by users is positively related to
user attitude.
H4: Proximity of services is positively related to
user attitude.
H5: User attitudes and subjective norms have a
positive relationship with user intentions.

4. Operationalization of the research model
A structured questionnaire was designed, and a
survey method was used for data collection. The
survey instrument had two parts: the ®rst to collect
demographic data and the second to collect data for
the factors hypothesized as having an effect on user
attitude, subjective norms, and behavior intentions.
Semantic differential scales with bi-polar evaluative
end-points were used to collect responses.
4.1. The pretest
The questionnaire was mailed to a randomly
selected group of 400 faculty and staff at a southern
US university. The sample population was divided into
three equal groups and each was asked to give
responses about a speci®c support source-their IC,
local MIS staff, or informal support. The university
setting was ideal, as these three support sources are all
present in the educational environment. A total of 57
useful responses were received (response rate 14.3
percent). After analysis, two changes were made to the
survey instrument. First, the scales were reversed. This

was found necessary since respondents prefer to give
high scores if they are in agreement with certain items.
Second, some of the construct items were reworded to
avoid ambiguity.
4.2. Final data collection
Respondents for the survey were a randomly
selected group of 1000 non-IS middle-level managers
from various industries throughout the US Middlelevel managers were selected because Benson, in prior
research, had found that over 50 percent of the enduser population are in that category. The mailing list of
addresses was purchased from a commercial mailing
list ®rm in California. Only ®rms with more than 150
employees were selected for the study. It was assumed
that such ®rms would have some form of support
source. Middle-level managers were given a choice
between responding to one of the three support
sources: IC, local MIS staff, and friends/colleagues.
The reason for this choice is that one of the support
sources might be absent in the respondent's ®rm. To
improve the response rate, one reminder was sent out
within a week of mailing the survey.

5. Data analysis
A total of 115 responses were received (11.5 percent response rate). Out of these, seven were not
usable, since the responses were incomplete, giving
a ®nal response rate of 10.8 percent. Due to incorrect
addresses, 17 mailings were returned (1.7 percent).
Excluding them, the adjusted ®nal response rate
was 11 percent. Although this response rate is low,
it is not abnormal for mail surveys [24]. Since the
sample population consisted of only middle-level
managers, there are no strong reasons to believe that
the respondents differ from the nonrespondents. Thus,
nonresponse bias was not considered as a threat in
this study.

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C. Govindarajulu et al. / Information & Management 37 (2000) 77±86

Table 1
Survey response break-up

Table 3
Respondents preference of the support source

Support source

Number of responses

Friends/colleagues
Information center
Local MIS staff
Total

25
40
43
108

5.1. Respondent information
Out of the 108 respondents, 64 percent belong to the
service industry and 26 percent to manufacturing.
Table 1 presents a breakdown of the responses for
each support source.
When asked to identify which support sources were
available, 74.4 percent of respondents noted friends/
colleagues while 72.4 percent indicated the availability of an IC. Approximately 62 percent of the respondents reported the presence of local MIS staff.
Surprisingly, 50 percent mentioned the availability
of vendor support. A small percentage (8 percent)
of the respondents reported that outside support
sources, such as MIS staff from another department
and family members were available to them (Table 2).
Respondents' preferences for support sources are
tabulated in Table 3. Of the 98 respondents who gave
their preferences, approximately 39 percent ranked
local MIS staff as their ®rst preference while 26.5
percent ranked friends/colleagues as their ®rst preference. Only 19 percent ranked their IC as their
preference.
5.2. Instrument validity and reliability
The survey instrument was tested for its strength by
measuring convergent validity and by performing
Table 2
Support sources available to respondents

Respondents'
preferences

Support sources (number of respondents)a
Information
Center

Friends/
colleagues

Local MIS
Staff

Rank 1
Rank 2
Rank 3

19
37
18

26
24
26

38
20
18

a
N ˆ 98. Since some respondents gave rankings to all other
support sources such as vendor support, the total will not be equal
to 98. Rank 1-Best, Rank 4-Worst.

reliability analysis. The convergent validity shows
the extent to which the measure correlates with alternative measures of the same construct. High inter-item
correlations within each construct were construed as
indications of convergent validity. With the exception
of one pair of items (correlation coef®cient ˆ 0.56) of
the construct, quality of support staff, all other factor
item correlations were above 0.6, with most above 0.8.
All of the correlations were found signi®cant. The
reliability of each factor was evaluated by the means
of Cronbach's alpha coef®cient. Table 4 presents the
Cronbach's alpha (reliability analysis) for the constructs of the instrument for each support source. The
alpha values lend support to the strong scale reliability
of the instrument.
5.3. Analysis of the proposed relationships
Regression analysis was performed to test the relationships between the constructs of the model. Table 5
summarizes the results of the analysis of relationships
between `user evaluation of the support source' and
user attitude. All the variables were related to attitude,
explaining 73 percent of the variance. For a complete
Table 4
Reliability of constructs of the final survey instrument

Type of support source

Percent of respondentsa

Information Center
Local MIS Staff
Friends/Colleagues
Vendors
Others

72.44
62.24
74.49
50.00
8.16

a
Total percentages will exceed 100 because of the availability
of multiple support sources to respondents.

Constructs/no. of items
Support staff characteristics/4
Quality of EUC applications/4
Proximity of services/3
Motivation/3
Normative beliefs/3
User attitude/4
Behavior intention/3

Alpha
0.88
0.96
0.89
0.85
0.88
0.98
0.90

N
108
104
108
100
93
106
100

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C. Govindarajulu et al. / Information & Management 37 (2000) 77±86
Table 5
Analysis of the relationship between user attitude and user evaluation of the support source
R2

Model
Attitude ˆ staff quality ‡ appl. quality ‡ support ‡ proximity
Staff quality
Appl. quality
Support
Proximity
a
b

Beta

VIF

SE Beta

T

0.342a
0.294b
0.079b
0.404a

2.60
2.48
2.59
2.22

0.116
0.104
0.036
0.107

2.951
2.831
2.191
3.781

a

0.730 (N ˆ 99)

p < 0.005.
p < 0.05.

analysis, the data for these variables was tested for the
presence of multicollinearity. An investigation of
collinearity showed low variation in¯ation factor
(VIF) values for these variables; this indicates that
multicollinearity was not a concern.
Hypothesis 5 states that `User attitudes and subjective norms have a positive relationship with user
intentions' (to use a speci®c support source). Table 6
summarizes the results of the regression analysis
conducted to study the relationship between user
attitudes, subjective norms, and behavior intentions.
The variables attitude and subjective norm were
both signi®cant and explained 64 percent of the
variance in user attitude. Thus, Hypothesis 5 was
not rejected. Results of hypotheses testing are shown
in Table 7.

6. Discussion of results
Although the majority of the respondents (75 percent) reported the presence of informal support
sources, approximately 62 percent of the respondents
reported the presence of local MIS staff in their
departments. In addition, respondents ranked local
staff as their ®rst preference for support. The following
factors might have led to the respondents' selection of
local MIS staff:
1. It is more convenient.
2. Since the local MIS staff supports only users of a
specific department, they can spend more time
with them and thus help more than IC staff whose
time is shared among departments.

Table 6
Analysis of the relationships between user intentions and user attitude and subjective norm for each support source
Model
Behavior intention ˆ attitude ‡ subjective norm
Attitude
Subjective norm
a
b

R2

Beta

SE Beta

T

0.392b
0.042a

0.092
0.017

4.270
2.490

b

0.545 (N ˆ 85)

p < 0.05.
p < 0.005.

Table 7
Summary of results of hypotheses testing
Hypotheses

Results of analysis

H1:
H2:
H3:
H4:
H5:

Supportedb
Supporteda
Supporteda
Supportedb
Supporteda,b

a
b

Quality of support staff is positively related to user attitude
Quality of EUC applications is positively related to user attitude
Degree of Support received in areas perceived to be important by users is positively related to user attitude
Proximity of Services is positively related to user attitude
User attitudes and subjective norms have a positive relationship with user behavior Intentions
p < 0.05.
p < 0.005.

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C. Govindarajulu et al. / Information & Management 37 (2000) 77±86

Table 8
Means of behavior intentions for the support sourcesa
Support sources
Construct

Local MIS Staff (N ˆ 39)

Information center (N ˆ 38)

Friends/colleagues (N ˆ 23)

Behavior Intention

20.87

17.84

16.48

a

All the means are significantly different from each other.

3. Local MIS staff can be expected to have a better
understanding of a department's business functions and needs. IC staff may not have a complete
understanding of the business [34].
The results seem to indicate that local MIS staff
support is gaining popularity among respondents. To
con®rm this, the means of behavior intentions across
support sources were tested (Table 8). As predicted,
the mean values of behavior intentions varied signi®cantly. Respondents tend to use local MIS staff support. Similarly, respondents intend to use the IC rather
than to seek help from friends and colleagues. The
difference is not, however, very large, though it may
be signi®cant.
Approximately 72 percent reported the presence of
ICs/help desks. This shows that ICs are still one of the
predominant forms of support. Although they are
widespread, respondents ranked local MIS staff support as their ®rst preference. This is in direct contrast
to earlier studies, which reported that the users favored
other support sources. In fact, middle-level managers
ranked friends/colleagues as their last preference in
our study.
All study hypotheses were supported. Earlier
research has identi®ed support staff characteristics
and the quality of user-developed applications as
crucial for a support source's (IC) success. Also,
proximity of services was identi®ed as important in
EUC context. Finally, degree of support received in
areas perceived to be important by end users, as we
suspected was found to be related to user attitude.
However, low beta values (0.079) suggest that this
may not be a crucial variable here, at least for managerial end users. In general, this study's ®ndings agree
with earlier research results.
Although the use of local MIS staff appears to be
gaining popularity now, the concept of distributed
end-user computing support has been consistently
mentioned in the literature (e.g. [10]). Hammond's

conditions for distributed support are notable. They
are (1) not enough usage to justify an IC; (2) a small
development staff; (3) highly diversi®ed user groups
with little overlap between their software packages;
and (4) highly specialized user functions with good
skill levels. If one or more of these conditions are not
satis®ed, the presence of local MIS staff in all departments may lead to redundant support efforts. Since
local MIS support is popular among end users, management should exercise proper controls use this
source. A study revealed that 50 percent of the information centers surveyed develop applications for users
[40]. It is important that local MIS staff should focus
on their primary function-helping users help themselves-rather than developing applications for users.
Though subjective norm has a signi®cant effect on
user attitude, the low beta value (0.042) seems to
support Davis et al.'s ®ndings, which suggested that
subjective norms have no effect on user attitude.

7. Conclusions
A signi®cant percentage of respondents reported the
presence of departmental IS staff to support user
computing needs. This may be an emerging trend in
EUC support. Respondents prefer local IS staff support and IC support (in that order) to informal sources.
This is an unexpected ®nding, since previous researchers have consistently reported users' preference for
informal support. Based on the empirical evidence, it
is concluded that support staff characteristics, quality
of end user applications, level of support received in
areas important to users and proximity of services
have a signi®cant effect on user attitude. However,
results show that level of support received by a user
has less in¯uence on user attitude than other constructs
and proximity was the construct most closely related
to user attitude. There is a positive relationship
between attitude and subjective norm with respect

C. Govindarajulu et al. / Information & Management 37 (2000) 77±86

to user behavior intentions. In the EUC support context, results suggest that attitude determines user
intentions to use a support source to a greater degree
than user subjective norm. Possibly, in the EUC context attitudes of a user toward a support source may be
more important than subjective norms.

References
[1] A.K. Aggarwal, Trends in end-user computing: A professional's perspective, Journal of End User Computing 6(3),
1994, pp. 32±33.
[2] I. Ajzen, M. Fishbein, Understanding Attitudes and Predicting
Social Behavior, Prentice Hall, New Jersey, 1980.
[3] M. Alavi, I.R. Weiss, Managing the risks associated with enduser computing, Journal of Management Information Systems
2 (3) (1985±1986), 5±20.
[4] H. Barki, J. Hartwick, Measuring user participation, user
involvement, and user attitude, MIS Quarterly 18(2), 1994,
pp. 59±82.
[5] D.H. Benson, A field study of end-user computing: Findings
and issues, MIS Quarterly 7(4), 1983, pp. 35±45.
[6] F. Bergeron, C. Berube, The management of end-user
computing environment: An empirical investigation, Information & Management 14, 1988, pp. 107±113.
[7] F. Bergeron, S. Rivard, L.D. Serre, Investigating the support
role of the information center, MIS Quarterly 14(3), 1990, pp.
247±260.
[8] B. Bowman, F.H. Grupe, D. Lund, W.D. Moore, An examination
of sources of support preferred by end-user computing
personnel, Journal of End User Computing 5(4), 1993, pp. 4±11.
[9] J.C. Brancheau, D.R. Vogel, J.C. Wetherbe, An investigation
of the information center from the user's perspective, Data
Base 17(1), 1985, pp. 4±17.
[10] H.H. Carr, Information centers: The IBM model vs. practice,
MIS Quarterly 11(3), 1987, pp. 325±338.
[11] S.L. Caudle, W.L. Gorr, K.E. Newcomer, Key information
systems management issues for the public sector, MIS
Quarterly 15(2), 1991, pp. 171±188.
[12] S. Chian, N. Vincent, J.G. Walls, A survey of the current
information center practices. Proceedings of the TwentySecond Annual Hawaii International Conference on System
Sciences, vol. IV, 1989, pp. 54±60.
[13] F.D. Davis, A technology acceptance model for empirically
testing new end-user information systems: Theory and results.
Ph.D Dissertation, Sloan School of Management, Massachusetts Institute of Technology, 1986.
[14] F.D. Davis, R.P. Bagozzi, P.R. Warshaw, User acceptance of
computer technology: A comparison of two theoretical
models, Management Science 35(8), 1989, pp. 982±1003.
[15] S.A. Davis, R.P. Bostrom, Training end users: An experimental investigation of the roles of the computer interface and
training methods, MIS Quarterly 17(1), 1993, pp. 61±85.
[16] W.J. Doll, G. Torkzadeh, The measurement of end-user

[17]

[18]

[19]

[20]
[21]
[22]
[23]
[24]

[25]

[26]

[27]

[28]
[29]

[30]

[31]

[32]

[33]

[34]

[35]

85

computing satisfaction, MIS Quarterly 12(2), 1988, pp. 259±
274.
D.T. Edberg, B.J. Bowman, User developed applications: An
empirical study of application quality and developer productivity, Journal of Management Information Systems 13(1),
1996, pp. 167±185.
M. Fishbein, I. Ajzen, Belief, Attitude, Intentions and
Behavior: An Introduction To Theory and Research, Addison-Wesley, Boston, 1975.
J.F. George, R. Kling, S. Iacono, The role of training and
support in desktop computing, Desktop Information Technology. Proceedings of the IFIP WG 8.2 Working Conference on
Desktop Information Technology and Organizational Worklife in the 1990's, P.xv‡407 (1990) pp. 237-252.
E.R. Greenberg, How far, how fast? Information Center,
1988, 20±24.
T. Guimaraes, X Gupta, Personal computing and support
services, OMEGA 15(6), 1987, pp. 467±475.
T. Guimaraes, V. Ramanujam, Sources of personal computing
problems, OMEGA 17(6), 1989, pp. 543±550.
L.W. Hammond, Management considerations for an information centre, IBM Systems Journal 21(2), 1982, pp. 131±161.
S.D. Hunt, P.L. Kiecker, L.B. Chonco, Social responsibility
and personal success: A research note, Journal of the
Academy of Marketing Science 18(3), 1990, pp. 239±244.
M. Igbaria, S.A. Nachman, Correlates of user satisfaction
with end-user computing: An exploratory study, Information
and Management 19(2), 1990, pp. 73±82.
B. Ives, M.H. Olson, J.J. Baroudi, The measurement of user
information satisfaction, Communications of the ACM
26(10), 1983, pp. 785±793.
C.M. Jackson, C. Chow, R.A. Leitch, Toward an understanding of the behavioral intention to use an information
system, Decision Sciences 28(2), 1997, pp. 357±390.
D.M.S. Lee, Usage patterns and sources of assistance for personal computer users, MIS Quarterly 10(4), 1986, pp. 313±325.
S.R. Magal, A model for evaluating information center
success, Journal of Management Information Systems 8(1),
1991, pp. 91±106.
S.R. Magal, H.H. Carr, H.J. Watson, Critical success factors
for information center managers, MIS Quarterly 12(3), 1988,
pp. 413±425.
McLean, E.R., Kappelman, L.A., The convergence of
organizational and end-user computing, Journal of Management Information Systems 9(3) (1992-93) 145-155.
R. Mirani, W.R. King, The development of a measure for enduser computing support, Decision Sciences 25(4), 1994, pp.
481±498.
M.C. Munro, S.L. Huff, G. Moore, Expansion and control of
end-user computing, Journal of Management Information
Systems 4(3), 1987, pp. 5±27.
R.R. Nelson, Educational needs as perceived by IS and enduser personnel: A survey of knowledge and skill requirements, MIS Quarterly 15(4), 1991, pp. 502±525.
G.D. Nord, J.H. Nord, Perceptions and attitudes of end users
on technology issues, Journal of System Management 45(11),
1994, pp. 12±15.

86

C. Govindarajulu et al. / Information & Management 37 (2000) 77±86

[36] P.J. Pyburn, Managing Personal Computer Use: The role of
corporate management information systems, Journal of
Management Information Systems 3(3) (1986±1987), 49±70.
[37] K. Rainer, H. Carr, Are information centers responsive to user
needs?, Information and Management 23, 1992, pp. 113±121.
[38] J.F. Rockart, L.S. Flannery, The management of end-user
computing, Communications of the ACM 26(10), 1983, pp.
776±784.
[39] B.H. Sheppard, J. Hartwick, P.R. Warshaw, The theory of
reasoned action: A meta-analysis of past research with
recommendations for modifications and future research,
Journal of Consumer Research 15, 1988, pp. 325±343.
[40] J. Walls, E. Turban, Information center management control
measures: A survey and comparison, IEEE Transactions on
Engineering Management 38(4), 1991, pp. 336±343.
[41] J.C. Wetherbe, R.L. Leitheiser, Information centers: A survey
of services, decisions, problems, successes, Journal of
Information Systems Management 2(3), 1985, pp. 3±10.
Chittibabu Govindarajulu Dr. Govindarajulu is an Assistant Professor of MIS
in the Management Department at Drexel University. Dr. Govindarajulu has
published several articles on end-user
computing support and group decision
support systems in journals such as
Information and Management, Journal
of Database Management, and Journal of
End-User Computing. His current research interests include end-user computing management, ERP and Group Decision Support Systems.
He received his Bachelors in Mechanical Engineering and MBA
from Anna University and Bharathiar University in India,
respectively. In 1996, he received his Ph.D. from the University
of Mississippi.

Brian J. Reithel Dr. Brian Reithel's
teaching and research experience in the
field of information technology spans
more than 15 years. His research interests revolve around systems development, both by information systems
professionals and end users, particularly
in the area of strategic information
systems. His teaching experience encompasses both Management Information Systems and Computer Science courses at the undergraduate,
masters, and doctoral levels. He is the author of more than 50
articles and papers that have appeared in numerous journals and
proceedings. He is actively involved in several academic and
professional organizations related to the information technology
field. Dr. Reithel currently serves on the faculty of the School of
Business Administration at The University of Mississippi as the
Area Coordinator for MIS/POM and as Associate Professor of
MIS.
Vikram Sethi Dr Vikram Sethi is an
associate professor in the information
systems area at Southwest Missouri State
University, Springfield, Missouri, USA.
His areas of interest include global
information systems development, the
training and development of information
systems personnel, socialization practices, and role adjustment of information
systems employees. His articles have
appeared in journals such as ISR, the
Journal of Management Information Systems, Omega, Journal of
Information Technology, and the Journal of High Technology
Management Research.