DOCTORAL ISSUESROBERT T. SUMICHRAST, Feature Editor, Pamplin College of Business,Virginia Polytechnic Institute and State University Improving Ph.D. Education through Planning and Incentivesby Richard J. Lutz, The Graduate School, University of Florida
In recent years, a number of
environmental forces have caused Ph.D. programs in business
schools to downsize enrollments in the face of declining demand,
enhance pedagogical training, explore cross-functional
integration to pursue topics such as Total Quality Management,
and increase the representation of cultural minorities.
Incentivization. The second featureŝincentivizationŝis an
approach that has served us well at the University of Florida.
Essentially, each academic unit begins with a ``base'' budget
that allows it to maintain only a minimum-size (``critical
mass'') Ph.D. program. Securing additional resources that permit
program
expansion is contingent on the unit's performance vis-a-vis
agreed-upon performance criteria. In the paragraphs to follow, I
will describe our incentive-based planning system for Ph.D.
education. This model has proved extremely useful and, by
presenting it, I hope that other schools may be able to adapt it
to their own needs.
Objective. The current objective of the Ph.D. program is
to improve overall program quality, as measured primarily by the
quality of the initial positions accepted by Ph.D. graduates. The
measurement standards are both absolute and relative, that is, in
comparison with the placement records of designated peer
institutions. Placement quality is ranked as follows:
Strategically, there are two broad mechanisms by which output
(i.e., placement) quality can be enhanced: input quality (i.e.,
student qualifications) and throughput quality (i.e., curriculum
and other aspects of doctoral training).
Input strategy. Historically, admissions decisions have
been based largely on an assessment of the student's raw
intellectual ability, as measured by GMAT/GRE scores (especially
the
quantitative score), undergraduate grades, and, in some
instances, letters of recommendation. Typically, some indication
of the ``fit'' between the student's interests and program
emphasis is also sought.
In general, the admission decision attempts to forecast the
probability of professional success. Typically, the major concern
has been the ability of the student to conduct publishable
research. Criteria related to probable teaching ability,
knowledge of and experience in business, and, in general, the
prospects for excellent placement upon graduation, have entered
into the
admission decision less systematically. These latter criteria are
now being given more consideration at the admission stage. An MBA
degree and/or significant managerial experience, though not a
requirement, is becoming a more valuable indicator of eventual
placement quality. Careful consideration is also being given to
the ``mix'' of domestic and foreign students in the program, as
well as the representation of women and minorities. Our primary
``customers,'' that is, those universities hiring our graduates,
operate in an environment of increasing political (and central
administration) pressure to have culturally diverse faculties. At
the same time, business schools are under increasing scrutiny by,
and are increasingly reliant on, the external business community.
For businesses to support business schools, they need to be
convinced that students (undergraduate and MBA) learn about
business from knowledgeable faculty, and that faculty are
conducting meaningful research on substantive problems of
immediate or potential interest to the business community. The
foregoing implies greater emphasis on attracting as students
mature
individuals with both significant experience and genuine interest
in the world of business. This in no way suggests movement away
from scholarly potential as the overriding criterion for
admission; it does suggest, however, a somewhat broader construal
of scholarly research and an adjustment in certain tradeoffs that
are made (e.g., a 30-year-old MBA with a 620 GMAT versus an
undergraduate math major with a 700 GMAT).
Throughput strategy. It is safe to say that the
dominantŝperhaps, soleŝemphasis of the University of Florida
Ph.D. program has been on research training. Though many students
taught at some point in the program, there was little formal
training involved and, in many cases, no direct faculty
supervision or mentoring. That situation is changing.
Although classroom teaching experience is not a formal program
requirement (because some students opt for non-teaching careers),
it is the norm rather than the exception; all students are
strongly encouraged to teach as an essential part of their
education. More systematic training, supervision, and feedback
have been
instituted. The emphasis of the program has shifted from a
near-exclusive focus on research to the concept of a ``complete
faculty professional'' who is strong not only in research but
also in teaching, and is sensitive to the other aspects (e.g.,
university service) of faculty life.
Feedback/benchmarking. In support of this College-level
philosophy for Ph.D. education, each of our six academic units
(accounting, economics, finance, decision and information
sciences, management, and marketing) produced a plan at the unit
level. A fundamental aspect of the unit-level plan was the
identification of peer institutions to be used for comparative
assessment of
performance.
The following universities are in the College peer set, and were
listed as peers by at least 4 of the 6 academic units: Illinois,
Indiana, Iowa, Michigan, Ohio State, North Carolina, and Texas.
These schools form the ``core'' peer group for the Ph.D. program; however,
each academic unit obtains placement data from an additional three or
four schools that comprise peer institutions at the departmental level.
Exhibit 1 shows the nature of the information
collected from the peer institutions. Collection of the data are the joint
responsibility of the College Director of Graduate Studies and the Graduate
Coordinator in each academic unit. The single most important piece of
information is placement of graduates annually. Obviously, this information
is inclusive and not just their top graduates.
The other data collected help to establish the degree to which
programs are comparable in terms of size and support.
Finally, it is useful to obtain other sorts of data, not so much
for comparative evaluation, but rather as a source of ideas about
new approaches and philosophies, e.g., program brochures, student
manuals, curricula, teaching training programs, etc.
In general, internal performance measures are used to supplement the key placement
and student research productivity criteria. When the College began reforming
the Ph.D. program, improved placement performance was not anticipated
immediately. Nevertheless, a number of intermediate indicators were used
to track progress toward the ultimate goals. The measures shown in Exhibit
2 are classified into three groups: output, throughput, and input.
Within the latter two groups, the measures are further broken down into
process and outcome measures.
Academic units are responsible for compiling this information on
all graduates and maintaining a database.
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