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The Application of Multidimensional Scaling to an Analysis of
Schools of Advertising
by
Elizabeth Gigi Taylor
Jef I. Richards
April 1, 1995
The University of Texas
Department of Advertising
Submit all comments to Elizabeth Gigi Taylor, Advertising
Department, CMA 7.142, The University of Texas at Austin. Ph:
512-471-1101. Fax: 512-471-7018. E-Mail:
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The Application of Multidimensional Scaling to an Analysis of Schools of
Advertising
ABSTRACT
This paper presents a perceptual map of 15 advertising schools as
perceived by academics in order to understand the dynamics of the
advertising education market beyond simple ranking reports. The map shows
the perceived similarity between the schools and their relative
evaluation
of quality. The interpretation of the map reveals that schools are
grouped
into six clusters which are ordered by perception of prestige and
educational philosophy. Applications and implications for advertising
education are provided.
The Application of Multidimensional
Scaling to
an Analysis of Schools of Advertising
INTRODUCTION
The trend toward more integrated communication strategies on the part of
agencies and clients has influenced both professional practice and
advertising education. Today's marketing strategies are an integration of
advertising, public relations, direct marketing and promotion. These
changes are affecting the way advertising schools are preparing
advertising
majors. Within the last three years, many advertising programs at major
universities around the country, with commitments to both the business
community and the academic establishment, have reevaluated their course
curricula to accommodate the current integrated marketing communication
milieu (Medill 1993, University of Colorado 1993).
Given these changes in advertising education, there is a need for a clear
understanding of the structure of the advertising education market.
Little
reform can be made, if the current nature of the advertising education
market is unclear. It is within this changing face of advertising
education that the purpose of this paper was conceived.
LITERATURE REVIEW
Any credible review of advertising education literature must begin with
the prolific work of Billy Ross who has conducted extensive research
on the
objective dimensions of advertising education. Dr. Ross has used this
data to rank schools by number of students, number of graduates,
quantity
of published research, and faculty/student ratios (Ross 1965, 1991,
1964-1994). Where Shall I Go to College to Study Advertising and other
related publications by Dr. Ross offer clear summaries of objective
data
but lack an evaluation of the subjective dimensions of the schools.
In
fact, very little research has been conducted on advertising school
rankings based on subjective attributes.
Only three studies (Keenan 1991, Stout and Richards 1993, Watson 1989)
have ranked schools based on the perceptions or the subjective
evaluations
of survey respondents. In 1989, two ranking studies of the top-rated
advertising doctoral programs were published by Kittie Watson in the
Association for Communication Administration Bulletin. One survey
reported
the results of a survey administered to 300 members of the Association for
Communication Administration. The other study reported the results of a
survey administered to 297 member of the Broadcast Education
Association
(Watson 1989).
In 1991, Kevin Keenan of the University of Maryland, College of Journalism
surveyed academics regarding their school perceptions. He asked "Which
three schools other than your own do you consider the very best
undergraduate program in advertising?" Most recently in 1993, Patricia
Stout and Jef Richards, both of the University of Texas, asked
advertising
practitioners to rank the top advertising graduate programs.
Taylor and Morrison (1994) proposed a visual model of advertising
education that analyzed schools of advertising beyond ranking reports. A
theory versus practice continuum formed the horizontal line and a
journalism versus business continuum formed the vertical line. The two
scales together make a four quadrant grid representing an advertising
framework called the Advertising Education Model. Although illuminating,
their research was a theoretical piece without research data.
RESEARCH QUESTIONS
Advertising education ranking reports as summarized above, provide a list
of the "top of mind" schools in advertising education and a general
idea
how they compare to each other. While this simple ranking method may
be
the easiest way to collect and report a school's relative position in
the
market, two questions remain unanswered:
1. Beyond numerical rankings, how are schools of education positioned
relative to each other in the advertising education market?
2. Why are the schools positioned they way they are? That is, what
are the dimensions or attributes that are used to make these
evaluations?
The goal of this paper is to answer these two questions by placing the
schools on a perceptual map and analyzing the location of each school.
Like traditional school rankings, the evaluation of the schools in a
perceptual map are based on the perceptions of the survey respondents.
Unlike the ranking reports, the perceptual map offers a rich visual
representation of the nature of the overall education market.
Perceptual maps are a borrowed concept from the product positioning
literature within the marketing discipline. Perceptual maps show how a
product's image is positioned in the market relative to the
competition.
These visual diagrams are generated via multidimensional scaling
(MDS).
The idea of perceptual mapping is not new, but the application of this
concept to advertising education is original.
METHOD
A questionnaire was used to collect input data for the perceptual map
developed in this study. Survey data collected for multidimensional
scaling can be collected using several different formats. These
approaches
differ in the assumptions they employ, the perspectives taken, and input
data used. The following discussion traces the data collection
decisions
made in this paper.
Nonattribute data versus attribute data. One of the first decisions in
MDS is whether to collect attribute or nonattribute data. Attribute
data
are the specific dimensions used to evaluate schools. Nonattribute
data
was collected because school attributes used to evaluate schools are
not
known. In fact, one of the goals of this research is to identify the
attributes that define an advertising program.
Preference data versus similarity data. The second decision is whether to
ask respondents to evaluate schools in terms of similarity or preference.
Preference measures are gathered by asking respondents to rank schools by
personal preference. Similarity measures (proximity data) are
gathered by
asking respondents to rate perceived degree of similarity between
schools.
Similarity data was collected, rather than preference data, for two
reasons:
(1) Preference data would simply recreate a rank ordering of school which
has already been conducted in previous research (Keenan 1991, Stout and
Richards 1993). By contrast, no research has been done on the degree
of
similarity between schools. (2) Preference data increases the
possibility
of a response bias. A survey respondent might be partial to their school
and rank it higher on the preference list.
Evaluation Set. Ideally, all schools offering degrees in advertising
would be plotted on the map for a perfect representation of the
advertising
education market. Given the limitation of this approach, the goal was to
select the maximum number of schools that could be reasonably
evaluated in
a questionnaire. Fifteen schools, which translates into 105
individual
pairwise comparisons (15 (15-1) / 2) seemed to be the maximum number
of
combinations a respondent could reasonably evaluate.
The 15 schools used in the stimulus set were selected based on a composite
analysis of 9 different ranking reports published over the last ten years.
The goal of the selection process was to use a variety of ranking reports
to identify the 15 schools that accurately represented the advertising
education market. Seven of the rankings listed the schools by
objective
attributes such as undergraduate enrollment, graduate enrollment,
number of
faculty, and publishing records (Barry 1990, Soley 1988, Ross 1991,
Rotzoll 1984). The remaining two rankings were subjective opinion polls
listing the "best" advertising programs as perceived by academicians
and
practitioners (Keenan 1991, Stout and Richards 1993). The schools
used as
the stimulus set were the 15 schools with the most appearances on
these
rankings.
Sampled Set. The questionnaire was sent to the chair of the advertising
department, program, area, etc. from the same 15 advertising schools
included in the evaluation set. It was assumed that this person would be
the most knowledgeable about their own school relative to other
competing
schools. In addition, chairs generally have been in academia for
several
years and have acquired knowledge about other programs. Finally,
because
the respondent would have a vested interest in the results of the
survey,
they would be more likely to respond to the survey.
Questionnaire. The 105 pairwise comparisons were the first items on the
questionnaire. The respondent was not told what criteria to determine
similarity. The final section of the questionnaire asked respondents
about
their education, teaching and research backgrounds.
Procedure. The questionnaire was pretested with advertising faculty at the
researchers' university. Layout and presentation changes were made based
on the pretest evaluation. The 2-page self-administered
questionnaire,
cover letter and stamped, pre-addressed envelope were sent via US mail
on
March 15, 1994. A second mailing was sent on April 21. At the end of
the
data collection process, 13 out of the total 15 questionnaires were
returned. Out of the returned 13 questionnaires, only 11 contained usable
data. The final response rate was 73% or 11 surveys. The MDS
analysis
was conducted using the ALSCAL (Alternating Least-Squares Scaling)
multidimensional procedure within SPSS for Windows (Release 6.0).
Frequency counts and means were run on questions from the respondent
information section.
Choosing the Number of Map Dimensions. Table 1 indicates the overall
goodness-of-fit measures for both the 2 and 3 dimensional configurations
generated by the MDS program.
Table 1
Goodness-of-Fit Comparisons
Number of
Dimensions
Stress
R-square
2
.24955
.62233
3
.18882
.61750
The stress level with three dimensions (.18882) is lower than the stress
with two dimension (.24955). Since the lower the stress the better,
the
three dimension stress level is slightly better by .06. The R-square
level
with three dimensions (.62233) is higher than the R-square level with two
dimensions (.61750). Since the higher the R-square value the better,
the
three dimensional stress level is slightly better by .0048.
Considering both measures of fit, the three dimensional configuration is
slightly more accurate than the two dimensional figure. This slight
improvement in the goodness-of-fit measures is contrasted with the
considerable increased difficulty in interpreting the three dimensional
figure. In summary, the ease of interpreting the two dimensional model
outweighs the improved stress and R-squared values of the three
dimensional
model. Because the goal is to obtain an acceptable level of fit with the
smallest number of dimensions, the two dimensional figure is the
configuration presented in this paper.
RESEARCH FINDINGS
Table 2 lists the coordinates for each of the 15 schools in the evaluation
set. These coordinates were used to produce the spatial map in Figure 1.
TABLE 2
Evaluation Set Coordinates
School
School Codes
Dimension 1
Horizontal Axis
Dimension 2
Vertical Axis
Alabama
al
-.6433
1.0894
Baruch
ba
-.9409
-2.1524
Florida
fl
.7103
.9374
Georgia
ga
1.0990
.5340
Illinois
il
1.5664
.1882
Louisiana
la
-1.1529
1.2071
Michigan
mi
1.3344
-.2415
Missouri
mo
-.5558
-.8690
Nebraska
nb
-1.3137
.2695
Northwestern
nw
.7609
-1.4004
San Jose State
sj
-1.3160
-.5870
South Carolina
sc
-.9152
.8506
Syracuse
sy
-.0937
-1.1140
Tennessee
tn
.2475
.9912
Texas
tx
1.2146
.2971
FIGURE 1
Derived Configuration
Goodness-of-fit Measures. Table 3 shows the goodness-of-fit measures for
all 11 matrices and the overall, aggregate matrix. A review of the
fit
levels for each matrix shows only slight variations in levels between
observations. Overall, the stress and R-squared values for the aggregate
matrix is .24955 and .62233, respectfully. This means that
approximately
25% of the variance in the matrix can not be accounted for by the MDS
procedure or that approximately 62% of the variance in the overall matrix
can be accounted for by the MDS procedure. Although there is very
little
consistency in the research literature, Guilford suggests that an
R-squared
correlation of .60 or higher is acceptable (Guilford 1956). Using this
benchmark, the overall configuration of this research project has an
acceptable goodness-of-fit measure.
TABLE 3
Goodness-of-Fit Measures
School Matrix
Stress
R-Square
Alabama
.272
.546
Florida
.231
.670
Georgia
.231
.671
Illinois
.298
.476
Michigan
.200
.753
Nebraska
.292
.490
Northwestern
.213
.723
San Jose State
.267
.567
South Carolina
.195
.765
Tennessee
.316 *
.398
Texas
.186**
.786
Aggregate Matrix
.24955
.62233
Profile of Respondents. As expected, department chairs have extensive
teaching and research experience at a wide variety of schools. Many of
the
respondents have taught at two or more universities prior to their current
appointment. More than 90% of the sample have Ph.D.'s with degrees from 9
different schools. The majority of the doctorate degrees were in
Communication or Mass Communication. All respondents reported over 11
years experience in education. Given this extensive educational
background, the sample appears to be well versed and knowledgeable about
the advertising education market.
INTERPRETATION
Multidimensional scaling created the map, but the MDS process does not
directly identify the two dimensions of the space. The actual
interpretation of the configuration map must be done outside the MDS
procedure. As recommend by Doyle (1973), the interpretation offered in
this paper uses a certain degree of intuition and visual analysis.
Figure 2 is a visual interpretation of the same configuration presented
in Figure 1 with the following formatting exceptions: In the Figure
2, the
Interpretation Map, the original X and Y axes have been removed. In
addition, the orientation of the original configuration has been switched
for a clearer representation. The left side of the original
configuration
is now the top of the interpretation configuration.
Also, the standard MDS dimension labels (Dimension 1 and Dimension 2),
have been renamed to reflect the researchers' interpretation of the
map.
The vertical dimension is now called "Low-High Prestige" and the
horizontal
dimension is labeled "Academic-Professional." Finally, the schools which
are grouped together are circled to form clusters. FIGURE 2
Vertical Axis Interpretation (Top to Bottom)
After careful review of the configuration, the most apparent pattern is
the ordering of schools from top to bottom. Schools appear to be
positioned down the configuration in a general descending order of
prestige. The subjective "prestige" dimension was composed of these three
factors:
1) Academic publishing record
2) School ranking reports
3) Availability of graduate education
1) Academic publishing record.
Because the quantity of publications is such an accepted measure of
academic quality (Hexter 1969), a school's publishing record (Barry 1990,
Soley 1988) is the first measure to support the "prestige" dimension.
Intuition was supported by quantitative data with the discovery of the
following satisfying relationship between the relative location schools
and
their publishing records.
All of the top four schools in the configuration -- Illinois, Michigan,
Texas and Georgia -- are also the schools with the highest
productivity
record. Schools at the bottom of the perceptual map - Alabama, South
Carolina, Louisiana State and San Jose State - are not listed on
publication productivity summaries. Table 4, Publication Productivity
Summary, lists schools by amount of publication activity as reported by
Barry (1990) and Soley (1988). Clearly, there is a direct relationship
between publication record and the vertical position of each school on
the
map.
TABLE 4
Publication Productivity Summary
Barry (1990)
Soley (1988)
1. University of Georgia
1. University of Texas
2. University of Illinois
2. University of Georgia
3. University of Texas
3. Michigan State University
Michigan State University
4. Arizona State University
5. New York University
5. New York University
6. University of South Carolina
6. Baruch College
7. Arizona State University
7. University of Illinois
8. Baruch College, CUNY
8. Northwestern University
9. Southern Methodist University
9. University of Wisconsin
10. Columbia
10. University of Houston
Wharton
2) Subjective rankings.
Additional intuitively reasonable conclusions were confirmed by comparing
the positions of schools on advertising education ranking surveys
(Watson
1989, Keenan 1991, Stout and Richards 1993) and the position of
schools on
the perceptual map. All of the ranking surveys report the same
general
school clusterings found on the configuration map. Specifically,
Illinois,
Georgia, Texas, Michigan, and Florida are all ranked on previous surveys
in the top quarter of the lists and positioned in this MDS map in the
top
quarter of the perceptual space. See Table 5 - Opinion Survey
Summary.
TABLE 5
Opinion Survey Summary
Keenan (1991)
Stout and Richards (1993)
Watson (1989)
1. Illinois
1. Northwestern
1. Illinois
2. Texas
2. Texas
2. Georgia
3. Florida
3. Michigan State
3. Texas
4. Michigan State
4. Syracuse University
4. Missouri
5. Northwestern
Missouri
6. Georgia
6. Wisconsin
7. North Carolina
7. Harvard
8. South Carolina
Pennsylvania
9. Missouri
Thunderbird
Tennessee
3) Availability of graduate study.
Finally, the availability of graduate education (MA, MS, and Ph.D.) is
considered a function of prestige because the authors assume that
schools
offering graduate education will have a more diverse and better
qualified
faculty. In addition, the availability of graduate education is a
straightforward way to classify schools into groups. As Figure 2, the Map
Interpretation figure indicates, all of the schools in the evaluation
set
offer undergraduate advertising education. Some of the schools in the
set
offer graduate degrees, but even fewer schools have doctoral programs.
Northwestern University, the exception to typical advertising education in
many ways, is the only school which offers only a MS degree (Ross 1993).
Perhaps the fact that Northwestern only offers graduate advertising
education explains why the school is located higher on the prestige scale
than other schools that offer all three levels of academic degrees.
The conclusion drawn from these observations is that a school's "prestige"
image will increase if the program offers graduate education, that is,
both a Master's degree and a Doctorate degree. A review of Table 6
below
confirms that school offering all three levels of education are at the
top
of the map while schools only offering MA's or only BA's are located
towards the bottom of the map. The one exception to this observation is
Northwestern which is located in the top half of the map with only a
MA ad
vertising degree program.
TABLE 6
Advertising Schools by Degree Offerings
BA, MA, Ph.D.
BA and MA
MA only
BA only
Illinois
South Carolina
Northwestern
San Jose State
Michigan
Louisiana State
Texas
Nebraska
Georgia
Florida
Tennessee
Syracuse
Missouri
Alabama
Baruch
Horizontal Axis Interpretation (Left to Right)
The second apparent pattern in the configuration is the positioning of
schools from left to right on the horizontal axis. In general, the
schools
on the left side of the configuration appear to be schools with academic
and scholarly objectives. Schools on the right side of the map appear
to
be schools which emphasize professional preparation. In this
interpretation, the division between a scholarly research and
professional
preparation is based on the following three factors:
1) Academic publishing record
2) Academic or professional Master's program
3) Communication or business Master's program
1) Academic publishing record.
Again, the schools fall in a generally predictable pattern from left to
right based on their academic publication record. The schools with
the
highest scholarly publication record are located on the academic or
left
side of the configuration (Soley 1988, Barry 1990). It makes
intuitive
sense that schools which emphasize scholarly research have the
greatest
number of publications in academic journals. It also makes intuitive
sense
that the schools which emphasize professional preparation would have more
publications in trade or consumer publications. Because this study
focuses
on academic literature, no data was collected regarding publishing outside
the academic arena. The authors acknowledge that schools such as
Northwestern on the right or professional side of the configuration
undoubtedly have impressive publication records in trade and consumer
press.
2) Academic or professional Master's program.
In general, undergraduate advertising degree programs have a professional
orientation while Doctoral programs have a research emphasis. Some
Master's degrees are research based and require a thesis. Other Master's
degree programs are professionally oriented and require a professional
report. A few schools offer the option of a Master's degree in either
track (Ross 1991). Applying these observations to the perceptual map,
it
appears that the schools on the right side of the configuration
emphasize
professional education and schools on the left offer more scholarly or
academic graduate advertising education.
3) Communication or business Master's program.
All of the schools in the stimulus set except for Baruch College are
located in schools or colleges of journalism or communication.
Northwestern emphasizes business applications, although it is located in a
School of Journalism (Medill 1993). Baruch and Northwestern, the two
schools offering a business orientation, are located on the right,
professional side of the configuration along with Syracuse, Missouri, and
San Jose State. For this reason, advertising schools with a business
or
professional orientation are located on the right side of the
configuration, while advertising programs in schools of communication
offering more academic degrees are located on the left side of the map.
Clusters
Beyond horizontal and vertical positioning of schools, several distinct
clusters of stimuli are apparent. Below is a discussion of each of
the six
clusters.
Cluster 1: Top Tier Advertising Schools. University of Illinois,
Michigan State University, University of Texas, and University of Georgia
are clustered together at the top of the figure on the left side of
the
configuration. Given their relative position, these schools appear to
be
the most prestigious academic research schools in the evaluation set.
All
of these schools offer three levels of advertising education and have
impressive publishing records (Ross 1993; Soley 1988, Barry 1990).
Cluster 2: Second Tier Advertising Schools. University of Florida and
University of Tennessee are both located in the top half of the
configuration but below the first cluster of schools. Both schools offer
three levels of advertising education, but do not enjoy the publishing
records of the first tier schools (Ross 1993; Soley 1988, Barry 1990).
Cluster 3: Third Tier Advertising Schools. University of Alabama,
University of South Carolina, Louisiana State University, University of
Nebraska, and San Jose State University are all loosely grouped into
this
third tier of advertising schools. Out of this cluster, only
University of
Alabama offers a doctoral degree. All of the schools except San Jose
State University offers Master's level education (Ross 1993). San Jose
State is the only university on the west coast offering a Bachelor of
Science degree in Advertising (San Jose State University 1994). None of
the schools are ranked in publication productivity studies (Soley
1988,
Barry 1990).
Cluster 4: Integrated Marketing Communication Education. Northwestern
University is the only school located in the IMC (Integrated Marketing
Communication) cluster. Medill is different than the other programs
because it offers an integrated approach to advertising. The curriculum
is
grounded in business and marketing practice (Medill 1993). In the
perceptual map, Northwestern is in the upper half of the vertical prestige
scale and located on the right professional education side of the
configuration.
Cluster 5: Advertising within Professional Schools of Journalism.
University of Missouri and Syracuse University are appropriately
clustered
together. Both schools have a strong print and electronic
professional
journalism emphasis (University of Missouri 1993, Syracuse University
1994). This cluster is located on the right, professional side and in
the
lower half of the perceptual configuration. Perhaps the reason for
the
relatively low prestige rating of the two schools is that the
evaluation of
the schools was done by advertising faculty, not journalism faculty. In
addition, opinions from Missouri and Syracuse were not included in the
survey because the two schools did not return surveys.
Cluster 6: Business Advertising Education. Baruch College, CUNY was the
only business school in the sample. It is the only school accredited by
AACSB rather than ACEJMC. In addition, Baruch is the only program to
offer
an MBA, rather than a Master of Science, Master of Arts or a Master of Mas
s Communication (Ross 1991). Appropriately, Baruch is isolated in the
far
lower right hand corner of the configuration.
In summary, this spatial map suggests that the perception of advertising
programs is more complex than the simple ordinal format suggested by
ranking reports. The configuration in this thesis reveals that the
underlying structure of the advertising education market has several
schools groupings. Schools are clustered together according to their
perceived prestige. The top schools have a more research emphasis and
offer Doctorate education. Lower tier schools do not have prolific
publishing records and only offer Master's level education. Schools are
also clustered together based on their philosophical approach to
advertising education. Schools with an academic and communication emphasis
are group separately from schools with a business or professional
orientation.
APPLICATIONS
There are several practical ways in which the perceptual map can be
applied to advertising education. First, the perceptual map can be used
as
guide for prospective students and guidance counselors during the school
selection process. The map can help students, with specific
advertising
education goals, make school application decisions.
Similarly, the map can also be used by professors applying for positions
at advertising schools. A professor can use the map to anticipate
which
schools offer the best philosophy of education match and the desired
level
of research rigor. In addition, schools that feel favorably
represented in
the map, can use the configuration in promotional brochures to show where
their school is positioned relative to the rest of the advertising
market.
Further, healthy competition between advertising schools is generated by
schools eager to move into higher tiers of prestige.
Also, academic publishers, accustomed to segmenting the textbook market
can use the map to target textbook marketing efforts. In addition,
publishers can also use the map as a guide for soliciting professors as
authors. Publishers are more likely to court authors at top ranked
research schools for authorship because of the reputation of their school
affiliation.
In summary, this map of the current advertising education market has
implications for practitioners, students, faculty, employers, publishers,
and administrators. More intelligent decisions regarding advertising
programs can now be made based on this graphic representation of the
advertising education market. This paper essentially created a decision
making tool for those involved in advertising education.
LIMITATIONS
Design Limitations. Although great care was taken to select a qualified
sample that would represent the general perceptions of the advertising
education market, eleven respondents is too small. There is no doubt
that
the results of this study would be more robust if the sample size were
larger. In addition, a portion of the sample felt unqualified to
complete
the questionnaire. This apparent lack of respondent knowledge might
be not
because of the limited ability of the sample, but because some of the
advertising schools in the evaluation set are not very well known for
their
advertising programs. Also, the 105 pairwise comparisons made the
questionnaire very tedious and intimidating. For those respondents
completing the survey, fatigue probably affected some of the last pairwise
evaluations. Finally, the similarity scale too large. Respondents
were
asked to evaluate schools based on a 9-point semantic differential
scale.
During the coding process, it was apparent that the scale was too
large
because respondents were not using all of the gradations. Perhaps the
large scale added to the intimidation factor.
MDS Limitations . This MDS research project is subject to the following
inherent limitations of multidimensional scaling as suggested by
Kruskal
(1978). 1) Perhaps all respondents did not judge each school pair
based
on the same dimensions. Even if all respondents did use the same
attribute
set, all respondents probably did not attach the same degree of
importance
to a dimension. 2) The perception of a school's attribute might not
correspond to the reality of the school's attribute. 3) The dimensions
actually used by each respondent to evaluate the degrees of similarity
between schools might not be the same dimensions used to interpret the
map.
FUTURE RESEARCH AND CONCLUSION
The focus of this research project has been purposefully narrow. The goal
was to create a perceptual map of the advertising education market using
multidimensional scaling. Because the resulting configuration does
show
that differences in schools exist, there is justification for further
research. An interesting future study would be to conduct the same study
with a different sample and compare the perceptions of the different
sample
to the perceptions of advertising faculty. For example, how would schools
be positioned on a map if advertising executives or prospective students
made the pairwise evaluations? Finally, additional insights about the
advertising industry could be gained by applying multidimensional
scaling
to other advertising institutions like agencies, academic journals,
textbooks, media software, trade journals, and professional associations.
REFERENCES
Advertising Education Literature
Barry, Thomas E. (1990), "Publication Productivity in the Three Leading US.
Advertising Journals: Inaugural Issues Through 1988," Journal of
Advertising 19 (1), 52-60.
Hexter, J. H. (1969), "Publish or Perish - A Defense," Public Interest, 17
(Fall), 60-77.
Keenan, Kevin (1991), Unpublished Advertising Program Ranking Study,
University of Maryland, College of Journalism.
Ross, Billy (1965), Advertising Education: Programs in Four-Year American
Colleges and Universities, American Academy of Advertising and
American
Association of Advertising Agencies, Lubbock, TX: Texas Tech Press.
Ross, Billy (1991), The Status of Advertising Education , Lubbock, TX:
Advertising Education Publications.
Ross, Billy and Keith Johnson (1964-1993),Where Shall I Go To College to
Study Advertising , Baton Rouge, LA: Advertising Education
Publications.
Rotzoll, Kim B. and Arnold Barban (1984), "Advertising Education," in
Current Issues and Research in Advertising, James Leigh and Claude
Martin,
eds., The University of Michigan, 2,1-18.
Soley, Lawrence C. and Leonard N. Reid (1988), "Advertising Article
Productivity Updated,"
Journalism Quarterly 65 (Spring) 157-164.
Stout, Patricia and Jef I. Richards (1993), "Advertising Agency Views on
Graduate Education in Advertising," An unpublished study, University
of
Texas at Austin.
Taylor, Elizabeth Gigi and Deborah K. Morrison (1994), "Where Theory and
Practice
Intersect: A Proposed Model for Analyzing Advertising Education," in
Proceedings of t he 1994 Conference of the American Academy of
Advertising
, Karen Whitehill King, ed, American Academy of Advertising, 64-73.
Watson, Kittie W., Renee Edwards, and Larry L. Barker (1989), "A Rating of
Doctoral Programs in Selected Areas of Mass Communication:
1987-1988,"
Association for Communication Administration Bulletin, 67 (January),
20-36.
School Literature
Medill Brochure (1993), Evanston, Illinois: The Medill School of
Journalism, Northwestern University.
San Jose State University Brochure (1994), San Jose, California:
Department of Journalism and Mass Communications, College of Applied
Sciences and Arts.
Syracuse University Brochure (1994), Syracuse, New York: S.I. Newhouse
School of Public Communications, Syracuse University.
University of Colorado Brochure (1993), Boulder, Colorado: School of
Journalism, University of Colorado.
University of Missouri Brochure (1993), Columbia, Missouri: Department of
Advertising, University of Missouri.
Multidimensional Scaling Literature
Doyle, Peter (1973), "Nonmetric Multidimensional Scaling: A User's Guide,"
European Journal of Marketing, 17, 2, 82-88.
Guilford, J. P. (1956), Fundamental Statistics in Psychology and Education,
New York: McGraw Hill.
Kruskal, Joseph B. and Myron Wish (1978), Multidimensional Scaling, Beverly
Hills: Sage Publications.
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