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Journal of Education for Business

ISSN: 0883-2323 (Print) (Online) Journal homepage: http://www.tandfonline.com/loi/vjeb20

Validating the Management Education by
Internet Readiness (MEBIR) Scale With Samples of
American, Chinese, and Mexican Students
John A. Parnell & Shawn Carraher
To cite this article: John A. Parnell & Shawn Carraher (2005) Validating the Management
Education by Internet Readiness (MEBIR) Scale With Samples of American, Chinese, and
Mexican Students, Journal of Education for Business, 81:1, 47-54, DOI: 10.3200/JOEB.81.1.47-54
To link to this article: http://dx.doi.org/10.3200/JOEB.81.1.47-54

Published online: 07 Aug 2010.

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Validating the Management Education
by Internet Readiness (MEBIR) Scale
With Samples of American, Chinese,
and Mexican Students
JOHN A. PARNELL
UNIVERSITY OF NORTH CAROLINA AT PEMBROKE
PEMBROKE, NORTH CAROLINA

ABSTRACT. In this study, the

authors validated a scale that measures
Management Education by Internet
Readiness (MEBIR) using American,
Chinese, and Mexican students. The
authors analyzed scale properties as
well as prospects for Internet-delivered
management education programs in
China and Mexico. Findings supported
the integrity of the original scale and
its distinction from one’s self-management ability. The MEBIR scale represents a good first step toward a standardized assessment and identification
of those most likely to benefit from
Internet-mediated education and training efforts.

A

number of corporate experts
believe that, within several years,
the majority of all corporate training
will be delivered online (Herther,
1997). In addition, the number of business schools offering programs over

the Internet continues to expand
(Arbaugh, 2000; Kwartler, 1998).
However, online delivery of undergraduate and graduate business courses
remains a relatively recent phenomenon, with a small, but growing literature base of knowledge (Briones, 1999;
Clauson, 1999; Ellram & Easton, 1999;
Taylor, 1996). This is true in the global
business arena, although the use of
online instruction is growing rapidly
(Smith & Duus, 2001). Nonetheless,
there still exists no coherent theory of
Internet
management
education
(Simonson, Schlosser, & Hanson,
1999) because most conceptual work
has been either macrotheoretical
(White, Rea, McHaney, & Sanchez,
1998) or atheoretical (Hiltz & Wellman, 1997).
Traditional universities have been
focused primarily on training faculty

to develop courses, although relatively
little interest has been shown in ascertaining student readiness for these
courses (Robertson & Stanforth,
1999). In a previous study (2003), we
proposed the Management Education
by Internet Readiness (MEBIR) scale
to measure a learner’s propensity for
successfully completing a management education experience delivered

SHAWN CARRAHER
CAMERON UNIVERSITY
LAWTON, OKLAHOMA

through the Web. Initial empirical
results were promising, but further validation of the scale was required.
Meanwhile, Internet delivery in the
international arena appears to be growing exponentially, but remains in its
nascent stage of development. In other
words, demand for the Internet is so
great that many providers are entering

the market early and with limited
resources. As a result, they have experienced difficulties along the way. The
use of the Internet to address the
tremendous international demand for
management education may be an
attractive means of meeting the international challenge. Following this logic, in
the present study, we assessed scale
properties among American, Chinese,
and Mexican samples. We also analyzed
the data for prescriptive purposes.
Online Delivery of Management
Education and the Management
Education by Internet Readiness
(MEBIR) Scale
A variety of factors have led to the
recent trend toward Internet-based management education (Klor de Alva, 2000;
MacFarland, 1998). Internet access in the
United States has expanded geometrically while advances in course platforms
and computing capacity have created
opportunities for the efficient delivery of

sophisticated content via the Web (Alavi,
Yoo, & Vogel, 1997; Holland, 1996; Parnell & Carraher, 2003). Competition
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from nonacademic sources (e.g., corporate universities) has intensified (Dunn,
2000; Kedia & Harveston, 1998; Moore,
1997; Rahm & Reed, 1997; Shrivastava,
1999). Many learners are reporting high
satisfaction with the online delivery of
management education (Bailey & Cotlar,
1994; Brandon & Hollingshead, 1999;
Ellram & Easton, 1999; Greco, 1999;
Kerker, 2001; Parnell, 2000; Sweeney &
Oram, 1992).
In some respects, the attractiveness of
the Internet as a delivery tool is enrollment driven. Enrollments in traditional

Master’s in Business Administration
(MBA) programs have not experienced
consistent growth throughout the past
decade (MacLellan & Dobson, 1997).
The Internet has facilitated the delivery
of content in a more convenient manner,
resulting in a potential increase in
online MBA offerings (Greco, 1999).
Indeed, student satisfaction data suggest
that the implementation of distance programs is easier to effectuate at the graduate level than at the undergraduate
level (Clow, 1999).
There is considerable anecdotal evidence to support the notion that online
delivery has the potential to be at least
as effective as traditional face-to-face
delivery due to a number of advantages
inherent in the delivery method (Meisel
& Marx, 1999). These advantages
include flexibility and convenience
(Nelson, 1997; Oblinger & Kidwell,
2000), increased access for isolated

learners (Nelson, 1997; Ross & Klug,
1999), the Internet’s plethora of business and academic resources (Bigelow,
1999; Freitas, Myers, & Avtgis, 1998;
Quick & Lieb, 2000; Strauss, 1996),
and potential for improved delivery efficiency (Roberts, 1998).
There are a number of avenues for
criticism of online instruction (Parnell
& Carraher, 2003). Critics charge that
much is lost when instructors and
learners are not face-to-face and able
to ask questions freely and discuss
issues (Smith & Dillon, 1999) and that
testing over the Internet is cumbersome and creates numerous opportunities for academic dishonesty. They also
argue that the actual long run costs
associated with distance education can
be tremendous (Parnell, 2000), especially for a technology whose educa48

Journal of Education for Business

tional value is not yet fully understood

(Grossman, 1999).
The Management Education by
Internet Readiness (MEBIR) Scale
The advantages and disadvantages
of Internet-mediated management education notwithstanding, individual
learner characteristics represent a critical factor in the success of such programs (Hara, 1998). The MEBIR scale
(see Appendix) was developed on the
philosophy that individual characteristics—not just technology, faculty ability, and content—should be assessed
before launching an Internet-delivered
management education program.
The first dimension of the scale,
technological
mastery
(TECH),
reflects the learner’s familiarity with
and mastery of the medium by which
online management content is delivered, which is the Internet (El-Tigi,
2000; Hara, 1998; Mioduser, Nachmias, Lahav, & Oren, 2000; Parasuraman, 2000; Rennes & Collis, 1998).
The second dimension, flexibility of
course delivery (FLEX), reflects the

degree to which the learner perceives
that Internet-delivered coursework is
more flexible and convenient (Ellis,
2000; Galer, 1999; Mioduser et al.;
Rich, Pitman, & Gosper, 2000;
Tysome, 2001). The final dimension,
anticipated quality of course (QUAL),
reflects the degree to which the learner
perceives Internet courses would be of
high quality (Blake, 2000; Dellana,
Collins, & West, 2000; Kolb, 2000;
Parasuraman & Grewal, 2000).
The Internet in China and Mexico
The Internet in China
According to one survey, there are
approximately 10 million personal
computers with access to the Internet
and a total of 26.5 million Internet
users in China (“China,” 2005). The
number of Internet users in China has

nearly doubled every 6 months for the
past 2 years (Zhao, 2002). However,
reliable usage data are not presently
available (Ashling, 2005).
Most Chinese Internet activity has
been for e-mail and informational pur-

poses. Although three fourths of Chinese online users report spending time
at e-commerce Web sites, most have
never made an online purchase.
Indeed, using the Internet as a purchase tool runs counter to traditional
Chinese shopping habits. Although
their Internet experience is limited,
Chinese cyberbuyers reported an interest in and willingness to expand the
online purchase activity in the coming
months (Wee & Ramachandra, 2000).
However, most analysts believe that
online buying will become mainstream
within the next few years, and expect
the strong growth in Internet usage to
continue (“China”).
The Chinese government is a strong
supporter of Internet usage. Most government agencies have Web pages,
although they primarily provide information and are not used to conduct business. State-owned China Telecom has
reduced its Internet access fees considerably since 1997 (Hachigian, 2001).
The Chinese government is sensitive
to the use of the Internet as an effective
medium of state opposition (Yang,
2001). Net executives in China seek to
adhere to local customs, a practice that
many critics interpret as voluntary censorship. For example, the Web site for
Yahoo in China posts news on world
events only from government-owned
newspapers. A number of international
news sites are often blocked at centralized routers that control Internet traffic
in and out of China, resulting in hit-andmiss access for savvy surfers who read
English (Yee, 2001).
Internet advertising is a relatively
new phenomenon in China. In 2000, the
Chinese government issued its first
licenses to local Internet companies,
effectively establishing a market-entry
criterion for Internet companies that
wish to display advertisements on their
sites. Internet advertising in China was
expected to reach $250 million by 2004
(Madden, 2000). China Southern Airlines boasts one of the most successful
sales-producing Web sites in China,
with sales topping $50 million annually
(China Southern Airlines, 2000).
The adoption rate of the Internet as a
purchasing tool in China lags behind
other parts of Asia, such as Hong Kong
and Singapore. The typical Chinese

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cyberbuyer is less than 30 years old,
earns less than $2,400 per year, makes
online purchases of less than $100, and is
mostly likely to be a male management
or technical professional with higher educational levels (“China,” 2005; Wee &
Ramachandra, 2000).
The Internet in Mexico
Internet usage in Mexico remains
concentrated in the hands of a few
(Gower, 2001b). Recently, however,
free Internet access has been touted as a
means of bridging the digital divide in
Mexico. Nonetheless, estimates suggest
that only about 5% of the Internet connections in Mexico are made through
free-access providers, compared to
about 50% in Europe (Gower, 2001a).
Poor reliability and the lack of technical
support have been identified as major
problems associated with the effort.
Internet advertising was expected to
grow more rapidly in Latin America than
any other major online region between
2001 and 2005 (Mack, 2001). A number
of key Mexican firms, including Grupo
Bimbo, Grupo Posadas, and Telmexare,
are fast developing their Internet infrastructures (“Top 10,” 2001). Financial
institutions in Mexico have been slow to
adapt to the Web, but this appears to be
changing (Thurston, 2000).
In sum, the rapidly emerging
economies of China and Mexico present
opportunities for providers of Internet
management education. However, Internet adoption in the two countries lags
behind the United States. There are substantial differences between China and
Mexico in terms of Internet usage patterns, cultural influences, and governmental regulations.

provide age and undergraduate grade
point average (GPA) information.
We assessed reliability and validity to
ensure the integrity of the MEBIR scale.
For the American sample (see Table 1),
coefficient alpha (Cronbach, 1951) reliability estimates for the subscales were
.588 for the TECH scale, .812 for the
FLEX scale, and .569 for the QUAL
scale, and we found each to be unidimensional based on the results of limited information factor analysis (Sethi &
Carraher, 1993), a confirmatory factor
analytic method for the estimation of
unidimensionality. Hence, the scale has
a moderate level of internal consistency,
an important indication of reliability
(Kuratko, Montagno, & Hornsby, 1990;
Peter, 1979).
For the Chinese sample (see Table 2),
Cronbach’s alpha reliability estimates
for the subscales were .573 for the
TECH scale, .534 for the FLEX scale,
and .508 for the QUAL scale. For the
Mexican sample (see Table 3), Cronbach’s alpha reliability estimates for the
subscales were .511 for the TECH scale,
.558 for the FLEX scale, and .675 for
the QUAL scale.
We assessed convergent and discriminant validity in three ways, first by correlation matrix (Bagozzi, 1981; Buck-

ley, Carraher, & Cote, 1992; Carraher,
Buckley, & Cote, 2000; Carraher &
Whitley, 1998). The matrix developed
represents mean correlations among
items from each scale separately and
mean correlations between items from
different scales. Intracorrelations within
the MEBIR scale (items within the same
subscales) were moderately high and
consistent (.323 among TECH items,
.394 among FLEX items, and .288
among QUAL items), suggesting convergent validity (Campbell & Fiske,
1959). The intercorrelations within the
MEBIR scale (items within different
subscales) were substantially lower and
consistent (.052), suggesting discriminant validity (Campbell & Fiske;
Churchill, 1979).
Second, the convergence of the items
on the factors demonstrated convergent
validity of the scale. The “clean” loading of each item on only one factor suggested discriminant validity.
Finally, we assessed convergent and
discriminant validity through the use
of variance extracted and shared variance statistics (Fornell & Larcker,
1981). Variance extracted is the
amount of the joint variance captured
by the construct and not by measurement error. Fornell and Larcker recom-

TABLE 1. Rotated Factor Solution for the Management Education by
Internet Readiness (MEBIR) Scale, U.S. Sample

Item

Subscale
loading

Flexibility

Technology

Quality

.726
.810
.700

.169
–.002
.105

.115
.274
–.008

.354
.139
–.009

.146
.209
–.002

.648
.624
.268

Technology (α = .588)
TECH1
TECH2
TECH3

.730
.779
.728

.201
–.117
.308
Flexibility (α = .812)

Validation of the Management
Education by Internet Readiness
(MEBIR) Scale
We administered the MEBIR scale to
145 American, 139 Chinese, and 113
Mexican management students. The
sample included Chinese students in
mainland China and those studying in
the United States. We also asked
respondents to complete a previously
validated three-item self-management
scale (Parnell & Carraher, 2003) and to

FLEX1
FLEX2
FLEX3

.853
.863
.841

.865
.836
.815
Quality (α = .569)

QUAL1
QUAL2
QUAL3

.724
.708
.776

.346
.551
–.007

Note. Technology refers to the Technological Mastery dimension of the MEBIR, Flexibility refers
to the Flexibility of Course Delivery dimension, and Quality refers to the Anticipated Quality of
Course dimension.

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TABLE 2. Rotated Factor Solution for the Management Education by
Internet Readiness (MEBIR) Scale, Chinese Sample
Subscale
loading

Item

Flexibility

Technology

Quality

.194
.870
.677

–.761
–.281
–.325

–.169
–.375
–.008

–.525
.630
.212

–.130
–.178
–.222

.347
.617
.742

Technology (α = .573)
TECH1
TECH2
TECH3

.623
.810
.765

.009
.137
.001
Flexibility (α = .534)

FLEX1
FLEX2
FLEX3

.608
.753
.805

.556
.388
.797
Quality (α = .508)

QUAL1
QUAL2
QUAL3

.727
.768
.634

–.699
–.412
–.001

Note. Technology refers to the Technological Mastery dimension of the MEBIR, Flexibility refers
to the Flexibility of Course Delivery dimension, and Quality refers to the Anticipated Quality of
Course dimension.

mended .50 as a benchmark for the
establishment of convergent validity.
Variance extracted was .534 for the
TECH subscale, .610 for the FLEX
subscale, and .528 for the QUAL subscale, suggesting some degree of convergence on the factors.
Shared variance is the squared correlation between two constructs and should
be significantly less than the extracted
variances for either of the constructs.
Shared variance between the subscales
averaged .039, suggesting discriminant
validity (Fornell & Larcker, 1981).
In sum, results of the analysis supported the integrity of the scale. Further,
there was also evidence to suggest that
the scale can be applied to samples outside of the United States, specifically
those in Mexico and China.
Findings and Implications for
Management Education
Given the support for the MEBIR
scale, it is worthwhile to examine relationships among the various subscales.
It is also interesting to consider prospective relationships between each subscale
and the age and grade point averages
(GPA) of the respondents. As such, factor scores (regression method) were cal50

Journal of Education for Business

culated for each subscale, as well as for
the three-item self-management scale
(Parnell & Carraher, 2003).
Self-management ability was positively correlated with each of the three
MEBIR subscales (see Table 4). This is
not surprising, and supports the importance of an ability to organize effectively, manage one’s time, and maintain selfdiscipline (Hara, 1998; Meisel & Marx,
1999). Hence, one’s self-management
ability can facilitate Internet-mediated
education because it enables learners to
adjust to the increased independence
associated with online training.
It is interesting that older students
tended to score higher on the self-management (SELF) scale, but they were
less likely to perceive Internet-mediated instruction to be of high quality.
Not having been raised with the technology, many older students may
remain convinced of the superiority of
face-to-face instruction even when
they possess adequate self-management skills.
Undergraduate GPA was not associated with any of the MEBIR subscales,
although respondents with higher
GPAs were also likely to report higher
self-management abilities. This finding is worth noting because it high-

lights the fact that neither GPA nor
self-management ability necessarily
heightens one’s readiness to use the
Internet as a learning tool.
Three implications for management
education are worthy of brief discussion. First, international management
education delivered through the Internet presents an exceptional long-term
opportunity for graduate institutions,
as future students will likely possess
greater comfort with technology than
current ones (Bayram, 1999; March,
2000; Quilter & Chester, 2001). In
addition, older learners tend to place
higher value on the flexibility associated with Internet delivery and to perceive their own self-management abilities to be higher (Parnell, 2000;
Schwarzer, Mueller, & Greenglass,
1999). Hence, given the return of older
students to higher education at an
increasing rate, the value of a university offering its graduate business courses online should continue to increase
as well. This could present a challenge,
however, given the fact that older students may not perceive the quality of
Internet-mediated instruction to be as
high as that of traditional face-to-face
instruction, as was the case with the
present sample.
Second, face-to-face interactions
provide a personal touch not easily
secured in an online environment.
Practitioners developing programs for
international delivery should consider
that at least some personal contact
might be warranted (Hara, 1998). The
scale developed in this article measures readiness for Internet coursework, but makes no claims concerning
its effectiveness. We would suggest
that this scale be validated on other
samples and also linked to other outcomes of interest to management educators, such as retention rates, learning, use of new skills on the job, and
value added to the student and potential employers.
Third, management education in
China and, to a lesser extent, in Mexico,
typically consists of hard, technically oriented management curricula delivered
via lecture. A high degree of student participation during lectures is not common
(Wo & Pounder, 2000), making the student acceptance of Internet education

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TABLE 3. Rotated Factor Solution for the Management Education by
Internet Readiness (MEBIR) Scale, Mexican Sample

Item

Subscale
loading

Flexibility

Technology

Quality

.866
.823
.508

.326
–.211
.238

.001
–.461
–.004

.943
.360
.209

.005
–.008
.198

.742
.190
.127

Technology (α = .675)
TECH1
TECH2
TECH3

.910
.696
.722

–.128
.241
–.593
Flexibility (α = .511)

FLEX1
FLEX2
FLEX3

.500
.844
.778

.009
.518
.768
Quality (α = .558)

QUAL1
QUAL2
QUAL3

.722
.809
.677

.446
.858
.611

Note. Technology refers to the Technological Mastery dimension of the MEBIR, Flexibility refers
to the Flexibility of Course Delivery dimension, and Quality refers to the Anticipated Quality of
Course dimension.

TABLE 4. Correlation Matrix for Management Education by Internet
Readiness (MEBIR) Scale, Self-Management Scale (SELF), Age, and
Grade Point Average (GPA)
Item

TECH

FLEX

QUAL

SELF

AGE

GPA

TECH
FLEX
QUAL
SELF
AGE
GPA

1.000

–.015
1.000

–.044
.328*
1.000

.118*
.232*
.193*
1.000

–.047
–.057
–.155*
.104*
1.000

–.013*
.071
.068
.195*
–.015
1.000

Note. TECH = Technological Mastery; FLEX = Flexibility of Course Delivery; QUAL = Anticipated Quality of Course.
*p = .05.

potentially higher in China and Mexico
than in the United States. Hence, the relationship between self-management ability and one’s readiness of Internet-mediated education may not be as critical
outside of the United States.
Future Directions
The present study lends support to the
application of the MEBIR scale outside
of the United States. A number of key
questions remain, however, resulting in
several important avenues for future

research. First, the application of Western scales to non-Western samples
remains a difficult process (Peng, Lu,
Shenkar, & Wang, 2001), and the present study was no exception. When
scales are not translated to account for
language and cultural differences for
generalization’s sake, scale reliabilities
generally suffer as a result. However,
when scales are translated or modified
to address cultural differences, then
direct comparisons between distinct
cultural groups are tenuous at best.
Some researchers have crafted and

implemented different measures for
work values in China and in the United
States, arguing that Western measures
may not be appropriate within the Chinese culture (Cyr & Frost, 1991; Jamal,
1999, Siu, 2003; Xie, 1996). Solving
this dilemma is not easy, however.
Future research should embrace multiple approaches to develop a comprehensive understanding of the phenomena.
Second, Western models and instruments typically do not measure the constraints in which Chinese employers
function (Adler, Campbell, & Laurent,
1989). As a result, Chinese applications
of Western survey instruments, such as
the scales used in the present study,
have their limitations. Alternatively,
researchers may choose to develop
instruments from indigenous Chinese
values (e.g., Fahr, Podsakoff, & Cheng,
1987; Fahr, Tsui, Xin, & Cheng, 1998)
to maximize measurement precision.
Unfortunately, doing so is expensive
and typically produces results that are
incomparable with Western literature
(Peng et al., 2001). Additional research
that integrates both approaches in
hypothesis testing may lend more robust
and reliable conclusions.
Third, individual characteristics of
the learner, although critical, represent
only one factor that can influence the
success or failure of Internet-mediated
management education (Lo Choi Yuet
Ngor, 2001; Parnell & Carraher, 2003;
Quilter & Chester, 2001). This is especially true when the content has an
international flavor and learners are dispersed across borders. Additional
research should examine the relationships between MEBIR and other critical
success factors, such as faculty training,
faculty and learner technological access
and support, cultural differences that
may exist, and specific course content
(Dobrin, 1999; Hitch & Hirsch, 2001).
Delivery of courses via the Web also
necessitates that faculty members “buy
in” to a nontraditional model of education, whereby the faculty member
becomes the facilitator instead of the
teacher (Harden & Crosby, 2000).
Fourth, business schools must learn to
target learners with the combination of
individual characteristics most appropriate for their program offerings (Cox,
2000; Egerton, 2001). These characterisSeptember/October 2005

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tics include MEBIR, but may also
include myriad personality factors and
other factors, such as learning styles, coping methods, tolerance for ambiguity,
polychronicity, need for achievement,
cognitive complexity, intelligence, and
motivation to learn. The development of
a comprehensive model depicting dimensions critical to success in various graduate programs is needed rather than the
use of a piecemeal approach to matching
applicants with programs.
The final future direction concerns
outcomes assessment. If the quality of
Internet-mediated programs is to be easily and effectively measured, it will be
necessary to develop concise, operational models for comparing outcomes
from Internet-delivered and traditional
programs. Traditional assessment models assume face-to-face interaction
between instruction and learner. As
such, alternative models are necessary
to account for differences inherent in
Internet-mediated instruction, and traditional models may need to be modified
to account for different factors in the
two instructional styles. This instrument
provides a good first step toward the
standardized assessment process and
the identification of those ready to learn
through Internet education.
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APPENDIX
The Management Education by Internet Readiness (MEBIR) Scale
TECHNOLOGICAL MASTERY
TECH1 I generally have no problems downloading files and software via the Internet.
TECH2 I consider my computer ability to be better than average.
TECH3 I get frustrated easily with technology. (R)
FLEXIBILITY OF COURSE DELIVERY
FLEX1 Taking an Internet course would allow me to arrange my work schedule more
effectively.
FLEX2 Taking an Internet course could allow me to finish my degree more quickly.
FLEX3 Taking an Internet course could allow me to take a class I would otherwise not
be able to take.
(appendix continues)

September/October 2005

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(appendix continued)

ANTICIPATED QUALITY OF COURSE
QUAL1 I would probably learn more from my fellow students in an Internet course
than I would in a face-to-face course.
QUAL2 I would probably not learn as much in an Internet course as I would in a
face-to-face course. (R)
QUAL3 I learn more effectively when I interact with people in a face-to-face
setting. (R)
Note. (R) indicates items that were reverse-coded.

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