2008 - Marketing Educators' Association

Finally, with regard to common method variance,
“CMV” can occur when using the same survey
instrument to collect data on both exogenous and
endogenous variables. If CMV exists, a model with
fewer factors should fit a dataset as well as (or better
than) a “more complex” structural model (Podsakoff
et al., 2003). A series of Chi-square difference tests,
in which the model becomes “more complex” (i.e.,
gains an additional factor), shows that not only are
the changes significant but model fit also increases.
For example, a two-factor model generates a Chisquare
of 129.94, with 34 degrees of freedom, while
the three-factor model generates a Chi-square of
59.01, with 32 degrees of freedom. Although this
procedure does not eliminate common method
variance, is does indicate that inter-item correlations
exist for reasons other than due to method bias
(Korsegaard & Roberson, 1995). The various
measurement statistics for each item/construct are
available in Table 1.
Structural Model
The results, obtained from LISREL 8.72, indicate a
significant Chi-square (χ 2 (32) = 59.01, p< .01) but
also a well-fitting model (NFI = .93, NNFI = .95, CFI
= .97, IFI = .97). The results support H1, namely that
formal, yet flexible programming leads directly to
greater student satisfaction (γ = .44, p< .05). These
TABLE 1
C.R. α AVE
Satisfaction
I was satisfied to be a part of __.
Being part of __ was a good experience.
Being in __ was a wise choice.
.94 .94 .83
Programming .79 .78 .83
The programs were beneficial in facilitating
the meeting of new people and/or people
with whom I would not normally interact.
I was exposed to a variety of issues/ideas
that I would not normally know about or be
aware of.
The programs addressed and/or were
connected to the three questions.
I was able to better answer the three
questions as a result of these programs.
Community-building .79 .79 .57
The commons (or other defined social
spaces) enabled me to interact with others.
The living arrangements allowed me to have
positive experiences interacting with others.
I met many good friends.
I have closer connections with certain people
as a result of being in __.
All items measured on 5-point scales, where 1=completely
disagree and 5=completely agree.
62
results also support H2, namely that formal, yet flexible
programming fosters community-building (γ = .51, p<
.05). Finally, with regard to community-building
leading to greater student satisfaction for the
living/learning program, the results support H3 (β =
.38, p< .05).
Intervening Effects
Tests for the intervening effects of “knowing others in
the program” and gender were performed by
conducting multi-group analyses using LISREL 8.72.
The results show that the model differs for the
“knowing/don’t know” groups but not for the two
genders. Further, the results do not support that the
specific paths differ between groups, for either the
“knowing/don’t know” groups or the two genders.
Therefore, in this data, knowing others does not
intervene on the Programming Satisfaction path (H4
not supported). Likewise, the results do not support H5
(gender intervening on the Community-building
Satisfaction path). However, although the statistical
results do not support the hypotheses, the path
coefficients for both effects are in the appropriate
direction. For example, as hypothesized in H4, the
coefficient on the Programming Satisfaction path for
those who “know others” (.49) is greater than for those
who “don’t know others” (.36). Likewise, with regard to
H5, the coefficient on the Community-building
Satisfaction path for males (.55) is greater than for
females (.26). Perhaps future work, with an increased
sample size will lead to more robust and significant
multi-group results.
DISCUSSION
At the end of their book, Strange and Banning (2001)
discuss ways to shape both the physical and academic
landscapes, in order to more fully accommodate
student living and learning initiatives at the universitylevel.
Although students, for the most part, are able to
adapt to changes in these environments, part of the
responsibility lies with the university and its ability to
provide not only various opportunities for bridging
these two environments but also clear (though not
rigid) guidelines and programs that facilitate such
bridging of environments. Budgets and other
resources (e.g., physical space, administrative efforts)
can positively or negatively impact living/learning
programs; however, based on a cursory scan of
various institutional websites, colleges and universities
of various sizes continue to develop or maintain
living/learning programs. Thus, the timing is perhaps
most appropriate to begin looking at whether such
programs fulfill the expectations of the students who
participate.