challenges and responses to business school legitimacy: an economics...
Post on 16-Jul-2020
2 Views
Preview:
TRANSCRIPT
Challenges and Responses to Business School Legitimacy: An Economics Perspective
Lynne Pepall and Dan Richards Department of Economics
Tufts University
lynne.pepall@tufts.edu dan.richards@tufts.edu
Abstract
Business school legitimacy has been increasingly questioned over the last decade. This challenge has at least two dimensions. One concerns the relevancy and legitimacy of business school research. The other concerns the relevancy and legitimacy of business school professional training. We develop a vertically differentiated model of the business school market that permits separate consideration of these challenges. While either challenge cuts into the bottom line of both elite and second-tier business schools, they can nonetheless lead to an expansion in business school enrollments. More generally, the model permits identification of which kinds of schools are likely to be most affected by which type of legitimacy challenge. Keywords: legitimacy, vertical differentiation, peer effects We thank Andrew Pettigrew, Donald Lessard, Morris McInnes, Bhaskar Chakravorty and participants at the 2015 EFMD Conference on the Legitimacy and Impact of Business Schools and Universities (Oxford) for helpful comments.
Challenges and Responses to Business School Legitimacy: An Economics Perspective
1. Introduction
What is the role of business schools today? What gives these schools “legitimacy” as
educational institutions? What value do they bring that makes their training worthy of its
considerable cost to their students? Such questions have been raised with an escalated
vociferousness in recent years. Scholars such as Pfeffer and Fong (2002), Bennis and
O’Toole (2005), Starkey and Tempest (2008), Podolny (2009), and Thomas and Wilson
[(2011) and (2012)], among others have energetically questioned the research and
teaching agendas and, indeed, the basic business model of business schools. In these
critiques, business school faculty are typically accused of either researching the wrong
things or teaching the wrong things or both.
This charge implicitly recognizes that the “legitimacy” question has more than one
dimension. As Thomas and Wilson (2011, 2012) among others have observed, business
schools may acquire legitimacy as an academic enterprise that produces knowledge via
recognized scholarship. They may also gain legitimacy as highly skilled educators in
which faculty teaching is professionally focused and emphasizes skills and techniques
directly linked and valued in business applications.
There may be some irony in proposing an economic model to address issues of
business school legitimacy given that a number of those questioning that legitimacy, e.g.,
Bennis and O’Toole (2005) and Starkey and Tempest (2008) claim that an economics-
and-finance driven research agenda together with viewing students as “consumers” is in
fact a large part of the “legitimacy” problem. We believe however that to have a thorough
1
discussion of the “business” of business schools, an understanding of the market place in
which that “business” is conducted is extremely helpful if not absolutely necessary.
While any economic model has its limitations, working through the logic of such a
model also has many benefits. First, it forces us to recognize critical features of the
business school environment such as the differentiation among programs as well as
among the students that they serve. This is important because it means that challenge to
business school legitimacy will not have the same impact on all schools. Second, an
economic model allows one to consider explicitly that educational legitimacy is measured
in more than one dimension as well as to understand how those dimensions are
interrelated. Finally, and critically, a formal model allows us to investigate the strategic
response of business schools to legitimacy challenges. Working through those responses
in the strategic environment of the business school market—even in our simple model—
can lead to surprising results. For example we show that the strategic response of
business schools can, in some case, result in MBA programs actually enrolling more
students at precisely that moment that their legitimacy comes into doubt.
We describe our economic model of business school competition intuitively here, and
present the formal model in a brief appendix. The next section outlines the model’s basic
features while Section 3 describes the equilibrium or market outcome these features
imply. The impact of different challenges to legitimacy and the consequent strategic
responses are discussed in Section 4. Some brief concluding remarks follow in Section 5.
2. A Model of Business School Competition and the Quest for Legitimacy
2.1 A School Needs Students But Not all Students are the Same
There is considerable debate about whether business schools are academic institutions
2
producing new knowledge, or instead, are business organizations seeking to maximize
profit. One fact is common to either view however, namely, that each business school must
attract students willing to pay the tuition fee that the school has set. No institution can call
itself a school that does not enroll students. Few institutions can survive unless students
contribute to the cost of their education.
Yet while students are a necessary constituency for any business school, not all
students are the same. Some students are well prepared to succeed in a degree program
because of their innate talent, prior training, motivation or a combination of these and
other factors. Others are less able and hence less likely to reap the full benefits that a
school’s degree program offers. We recognize this feature in our model by assuming a
uniform distribution of students, differentiated in terms of their abilities to benefit from a
school’s degree program. We index this skill level by the parameter θ. At the top of the
distribution, the very best students (θ = 1) have a probability equal to 1 to benefit from
everything the school has to offer by way of an educational experience. At the bottom (θ =
0), are those students who really can get very little—essentially nothing—from a school’s
business degree program. All others lie between these two extremes.0F
1
2.2 Some Measure of Ranking Matters—to Schools as well as to Students
Generally speaking, those who get more out of a product are willing to pay more for it.
Moreover, such differentiation among consumers’ values will typically lead to a
differentiation in the products offered in the market place , [Shaked and Sutton (1982)].
The reasoning is straightforward. Take the business school market. If two schools offer
1Interestingly, simulations of our model calibrated to roughly coincide with market outcomes yield an average θ value across all management students of about 0.63. This implies that about 37 percent of the educational value schools offer is not realized by students. This is tantalizingly reminiscent of the finding cited by Alvesson (2015) that 40 percent of US students do not improve intellectually during their education.
3
the identical management training, any difference in price will sway all students to prefer
the cheaper program leaving the higher-priced school out in the cold. This will then
induce that school to cut its tuition price below its rival but now, for exactly the same
reason, its rival will be the outsider. Now the rival will cut tuition and so on. In short,
when two schools or any two firms compete in a market with identical products, price
competition is greatly intensified. To avoid this outcome, firms or schools in this case
have a strong incentive to soften the competition and segment the market by offering
different products—different kinds or different qualities of degree programs.
For simplicity, we use a duopoly model and so have two business schools offering two
different degree programs. One school offers a higher quality of program than its rival. We
denote the quality of a school’s degree program by the parameter vi, i = 1,2 and assume
that v1 > v2. We refer to the former, higher quality program as the elite school and to the
latter as its less-selective rival. The less selective school corresponds to what Bennis and
O’Toole (2005) among others call the “second tier”. The difference in quality of degree
programs is perceived or known to potential students.
What a student gains from the school’s degree will depend on the program quality as
well as on the skills and talents that the student brings to the program. Matching student
type to school we denote by θvi the benefit that a student of skill level θ will obtain from
attending a business program with quality vi. Thus, any given student (any given θ) will
gain more from attending a higher-quality school—a school with a higher v.
Of course, it is difficult to give an absolute quantifiable measure of v to any school. For
our purposes however, all that is needed is a relative measure so that students are able to
rank one school above the other. Whether this ranking is provided by the Financial Times,
4
US News, or some other source is less critical than the fact that some such ranking exists, at
least in the eyes of potential students. A relative comparison of degree quality is all that our
model requires. Note though that focusing on a ranking or relative measure has the further
advantage of allowing us to consider the quality of the less-selective school v2 relative to
that of the elite school v1, by normalizing the latter to 1. In other words, v2 = 0.8 would
imply that second tier schools offer a management program that is 80 percent as good as
that of an elite institution.
All students gain more from attending an elite school rather than a second-tier one.
However, the best or high θ students gain more from attending the elite program than do
less talented students. Thus, if the elite school charges a higher tuition, it will attract
those who can best afford that expense, namely, the highly-skilled (high θ) students who
get the most from its offerings.
2.3 Peer Effects are Real, Especially for “Elite” Schools
It has been increasingly recognized in the education literature that the ability of a
student’s peers (the θ’s in our model) is an important determinant of the student’s own
success. Since the pioneering work of Hoxby and Weingarth (2005), it has also been
increasingly recognized that this impact is especially strong for high-ability students. Lavy,
Paserman, and Schlosser (2007) find that high ability students in Israeli schools benefit
from the presence of other high-ability students but that this effect does not translate to
less capable students. More recently, Imberman, Kugler, and Sacerdote (2009) use the
natural experiment provided of student transfers induced by Hurricane Katrina to show
that high-achieving students are the ones that benefit the most significantly from the
arrival of other high-achieving students.
5
We incorporate peer effects at the elite institution and assume that their value or
importance of peer effects in the value of the degree declines as that school expands
enrollment to include less talented students. This gives the elite school a strong reason to
be selective in admissions. The importance of peer effects to the elite school mitigates the
incentive of the elite school to cut tuition and “steal” students from its lower quality rival.
Enrolling these students –who are less prepared or able to benefit from the elite school’s
curriculum—decreases the value of peer effects and therefore lowers the overall value of
the elite school’s degree program.1F
2
2.4 Scholarship and Transforming Student Lives Yield their Own Reward
Competition in the business school marketplace leads to differentiation among
programs. This is of course not unique to management education. Law schools,
seminaries, and undergraduate institutions differ notably in the academic package they
provide. An important point, emphasized by Hoxby (2014), is that elite educational
institutions are distinctive because they not only teach and transmit knowledge but they
are as well leaders in research and producing new knowledge. While scholarship has had
growing importance at all management schools, the dichotomy between research-
intensive and teaching-intensive schools still remains. Even as late as 2008, the AASCB
Report on Research Impact noted that less than half of the business schools surveyed
valued research as much as teaching, and so business school programs are differentiated
in terms of the research intensity of their faculty.
2In the canonical vertical differentiation models of Mussa and Rosen (1978) and Gabsewicz and Thisse (1979) if marginal cost is constant and independent of quality, the firm with the highest-quality product also has the largest market share. The peer effects mechanism can reverse that result. [See also, Shaked and Sutton (1982).]
6
To be sure, the value of business school research is itself part of the legitimacy
question. Yet there is good evidence that faculty scholarship can transform students’
educational experiences for the better. Research-active faculty are able to generate value by
transferring to students new knowledge or findings directly acquired from their own research or
from the latest developments in the field that may only be known and understood by such
faculty. In addition, faculty engaged in research can engage their students in the research
process, adding a research dimension to their educational experience. That engagement can
give students a “competitive edge” [Morgeson and Nahrgang (2008)]. Studies such as
O’Brien et al (2008, 2010) and Rindova et al (2005) are just some of those finding that
business faculty scholarship has a positive impact on subsequent MBA salaries.
Financial rewards to the research agenda of business schools may come through
various avenues. First, the scholarship may generate outside funds via grants and other
awards. Few achievements better establish a school’s scholarly standing than research that
wins competitive funding from prestigious peer-reviewed organizations such as the US
National Science Foundation. Second, and perhaps of more importance for management
programs is the fact that financial support from private foundations and companies serves
as a testament to the relevance and “cutting edge” quality of a school’s scholarship.2F
3 Third,
the research-based educational experience offered can transform student experiences and
lead to future alumni donations. This is consistent with empirical evidence in Becker et al
(2003) that students value faculty research when making their enrollment decisions and
3We are not saying that all research that receives funding passes the double hurdle of rigor and relevancy first emphasized (among other hurdles) by Pettigrew (1997, 2001). We are simply saying that research that meets these standards can generate funding. We are also saying that student involvement in such research activity can itself be valuable as an educational experience that, when looked back upon, can prompt donations.
7
that higher quality students value research more than less talented students.3F
4
Alumni donations can, in fact, be viewed as part of a “trust” game in which research-
active faculty first provide an exceptional experience beyond basic education and later
receive a “payment” by way of a donation—after alums have realized the value of that
training. That is, the education-first donation-later game can be viewed as a quality
assurance mechanism in which alumni only make the later donation if the educational
experience is validated by their experience after graduation. Indeed, John Byrne, editor of
the Poets & Quants website devoted to business school topics, has written that alumni
donations are perhaps the single most “telling number to judge the strength of a school’s
alumni network” as well as student satisfaction with their education. (Byrne, 2011).
Scholarly achievement is one dimension of the quest for academic legitimacy, earning a
business school an equal place in the academy with more established scholarly disciplines.
While many schools may seek this validation, we believe it is a particularly distinguishing
feature of elite schools for two reasons. First, the pressure on the business school to match
the scholarly prestige of faculty in other disciplines—Arts, Sciences, Law, Engineering, and
Medicine—is likely strongest at institutions such as Harvard, Oxford, Yale, and Chicago.
Second, both the ability to translate cutting edge research into students’ classroom
experiences and to engage students in the research experience depends on the quality of
the students themselves and this is greatest at the elite institutions.4F
5
To put it another way, because better students get more from their educational
4As Becker et al (2003) note this sets up a positive feedback loop. Elite schools attract the best students who are best able to support research-active faculty. In turn, this research generates the grant and donation income that enables elite schools to continue to attract the best students (and faculty). 5Our model incorporates the quality (θ value) of the students as one of the inputs into the research process. By this means and also via the peer effects term, the model envisions students as education producers as well as consumers.
8
program and therefore go on to better jobs, and because higher-quality students are better
research participants, it is likely that the value of both alumni donations and research
grants will be positively associated with the overall quality (the average θ) of a school’s
student body. When these factors are combined with the pressure for scholarship at the
best universities, it makes sense that the quest for scholarly legitimacy is most pronounced
at the elite business schools. In fact we observe the elite school, such as Harvard, Oxford,
Tuck and Yale not only enroll the top students, but also lead the way in terms of both
alumni donations and research rankings. [Byrne (2011) and Financial Times (2015)].
The donation and grant revenue at the elite business school then influence competition
in the business school market in two, mutually reinforcing ways. First, it provides another
compelling reason for elite schools to enroll the top quality (high θ) students in addition to
the “peer effects” factor mentioned previously. Second, by providing an additional source
of income, it makes elite schools less directly reliant on tuition income. Together, both
these factors soften price or tuition competition in the business school market. Elite
schools do not seek to expand aggressively their enrollments by cutting tuition because this
would ultimately lead to admitting less qualified students, which in turn would lower the
quality of its alumni network and reduce the school’s scholarly reputation.
3. Putting It All Together: Equilibrium in the Business School Market
The basic features characterizing the market for business school degrees underpin how
business schools compete for students. In our model, we investigate this competition in a
simple duopoly model in which there is one elite institution competing with one less
selective one. The elite school earns revenue from tuition and alumni or external
donations, whereas the non-selective school only earns tuition revenue. On the cost side,
9
the majority of each school’s costs are basically fixed (tenured faculty and facilities).
Admittedly, the elite school is likely to have greater overall fixed costs (more expensive
faculty and facilities). Yet each school plausibly has the same variable cost of admitting one
more student. This is assumed to be constant and for simplicity set equal to zero.
Each school chooses its tuition rate (t1 for the elite school and t2 for its less selective
rival) to maximize revenue in order to cover its fixed costs. We then solve for a Nash
equilibrium in tuition prices. We examine the features of a market equilibrium as well as
explore how that equilibrium changes with changes in the environment including, most
especially, threats to business school “legitimacy.”5F
6
Three key parameters determine the nature of the outcome. These are: 1) the relative
educational value v2 of the less-selective school; 2) the intensity of peer effects at the elite
institution; and 3) the strength of the connection between student quality and
grants/donations at the elite school. For roughly 90 percent of the feasible values for
these parameters, the outcome is a selective equilibrium. By this we mean that the elite
school enrolls fewer students6F
7, charges a higher tuition, and provides educational training
that provides a gross or pre-tuition value (considering peer effects) for any students it
enrolls that exceeds what that student could obtain at the second-tier school.7F
8 Of course,
6This behavioral assumption seems consistent with the assumption of many critics, e.g., Pfeffer and Fong, (2002), Starkey and Tempest (2008), and Pfeffer (2015) that management programs are viewed as “cash cow” by universities. It is not to say that business schools should act as revenue maximizers. In principle, we can model schools as having a richer set of objectives as implied by a Balanced Scorecard approach [see Thomas (2007)]. However, as Ferlie et al (2008) recognize, even business schools with broad public interest objectives will need to meet the funding challenge of somehow generating sufficient funding to cover costs 7 While this may be a sensible result, it is worth noting that in the economics literature on vertical differentiation, a standard result of models in which rivals have the same marginal cost as here, is that the elite or high-quality firm wins the lion’s share of the market. It is the peer effects and outside donation and grant income factors that reverse that result here. 8 According to US News, the top 10 highest tuition Business Schools are: Stanford, Harvard, Wharton, Chicago, MIT, Northwestern, Berkeley, Columbia, Dartmouth and Virginia.
10
in all such equilibria the top quality (high θ students) attend the elite institution. In short,
the selective equilibrium in our model captures the broad dimensions of what we observe
in the actual marketplace. Additional insights follow immediately.
First, as noted above, outside income by way of alumni donations and grants works to
soften tuition competition between the elite and its less-selective rival. In other words,
better grantsmanship or just greater giving by elite alumni to their former school leads to
higher tuition prices overall, a result also found in Peña (2010) for a related but somewhat
different reason.8 F
9 Greater access to alternative grant and donation income gives the elite
school a greater incentive to maintain the quality of its research environment, creating
“peer effects” or an educational experience that its students feel is transformative and that
could not be achieved without the institution. In turn, this makes the elite school less
willing to pursue additional tuition revenue by cutting its tuition fee to attract more but
less capable students. Yet the higher the elite school sets its tuition t1 the higher the tuition
t2 the less selective rival sets as well.9F
10
Second, any increase in the value of peer effects will make it more important for the
elite institution to focus on enrolling only very high-quality students. This has a similar
impact. It reduces the intensity of tuition competition between the two schools. If the
value of having a high average-quality (high θ) student body rises, the elite school will
raise its tuition even higher to insure that only those students with a high expected
benefit from obtaining a degree will be willing to pay the higher tuition. Yet once again,
9In Peña’s model, the donated (or possibly grant) funds are spent on any items—classrooms, IT, meal services, recreational facilities, etc.—that raise the value of the educational product to students and thereby makes them willing to pay more. 10 Tuition prices t1 and t2 are strategic complements meaning that the best response or reaction curves of each school slope upward. Thus, school 1’s best response to a rise in t2 is to raise t1, and likewise for school 2’s best response or reaction to a rise in t1..
11
when the elite school raises its tuition, its less selective rival will do the same as price
competition in the market has been softened.
Finally, it is important to note there is a segment of potential business school students
who choose not to enroll at either institution. These are students with less ability i.e., the
lower θ students. It is not the case that such students would not benefit from
management training. It is instead that in this market, they would not benefit sufficiently
to justify paying the tuition that either the elite or less-selective school is charging.
4. Challenges to Business School Legitimacy
We can use our model to work out the implications of two distinct challenges to
academic legitimacy in the business school market. We first consider what happens when
the research mission comes into question. We then consider what happens when the
value of the basic skills training offered by both the elite and the less-selective school fall
relative to some other business training alternative, e.g., in-house business training or
perhaps new alternative competency-based management programs.
4.1 Doubts About the Legitimacy of Business School Scholarly Status
When the elite school’s claim to legitimacy as a producer of rigorous and relevant new
ideas falls, its ability to convince external organizations to fund its research mission and to
persuade students that their education is professionally transformative falls as well. This
loss of grant and donation income then has consequences for the competition for students
and tuition revenue between the elite school and its less-selective rival. In particular, it
induces the elite school to pursue tuition revenue more aggressively by cutting its price.
The reaction of the less-selective rival is to cut its tuition as well. In general, the less-
selective schools’ reduction will be smaller but the strategic complementarity of tuition
12
fees means that both fall. For example, a ten percent decline in grant and donation funding
typically leads to a five percent decline in the elite tuition and a three percent decline in the
less-selective tuition. Both schools expand enrollment, but the elite school expands slightly
more so that its share of the enrolled student population rises a bit.
The most interesting result though is that, with both tuition prices falling, more
potential students are induced to incur the expense of a business school education. The
expansion in percentage of the student population enrolled is on the order of three
percent. This is not to say that the loss of research legitimacy does not hurt. Both schools
see a revenue decline of say six (less-selective) to eight (elite) percent.10F
11 Yet the general
expansion in enrollment across all schools is perhaps even more important. It means that
business school enrollment expands even as the business school claim or value as a
legitimate scholarly enterprise declines.
4.2 A Fall in the Relative Value of Business School Training
In our initial market equilibrium, there is no alternative to the two types of business
schools. This is a simplification but a useful one in that it captures a setting in which, at
least in the eyes of potential students, a business school has a legitimacy that say in-house
corporate and other programs lack. In practice, that legitimacy may come from being part
of an actual university. This gives the school the same organization—faculty,
administrators, classes, grading, and diploma ceremony—as the larger university of which
it is part. In turn, this tends to validate the business school as a true educational enterprise.
Further, as a state or non-profit institution, the business school has some built in “quality
assurance” owing to the need to protect the reputation of the entire academic enterprise.
11If the schools were just breaking-even before the decline, this would clearly require retrenchment in the long-run. Our impression however, is that most business schools currently earn a surplus.
13
Relative to say a for-profit institution, it will be less likely to “rip off” consumers by
providing worthless training that leads to few if any job opportunities.
However, saying that there is no management-training alternative to the standard
business schools is not the same as saying that no such alternatives exist at all. In fact, in-
house management training programs have been around for some time. Other
alternatives, such as private, for-profit schools are also available. What our initial model
implicitly assumes then is not that these other programs do not exist but that the training
they provide has no marketable value relative to that of the MBA degree. The alternative
yields no credentialed diploma or certificate that can credibly signal a graduate’s learning,
skills, and value to potential employers. This kind of training is not a competitive
alternative for potential business school students.
Yet the situation can change, and we consider an innovation that catalyzes such a
change. In particular, we examine the impact of a decline in the value of the traditional
university-affiliated business degree relative to that of some alternative business training.
Working in relative value terms means that we can introduce this change either by
lowering the intrinsic value (the v’s) of our two initial schools or, by raising the value of a
third alternative above its implicitly assumed value of zero. We choose the latter
approach, as it is analytically a easier to work with.
Specifically, we introduce a third business training program that offers a certificate with
intrinsic value v3 > 0 such that a student with skill level θ receives a benefit of attending
this new type of training equal to θv3. The certificate does not have the same status as the
diplomas of either of the established schools; that is, v1 = 1 > v2 > v3. Ignoring tuition, any
student will gain more from attending either the elite or even the less-selective business
14
school than s/he will from attending this new alternative.
However, what motivates a student to attend any program is the net benefit—the
benefit less the tuition fee. When v3 was initially set equal to zero, this third alternative was
not viable because it could never provide a positive net benefit even if it charged zero
tuition. Once the credential has positive value (or once the relative values of the traditional
schools falls), the third alternative is able to market its program at a low but positive price.
The alternative program can begin to compete for students with the more established
institutional rivals.
The immediate impact of this decline in the legitimacy and value of the standard
business school training is quite surprising because it depends critically on the pricing
strategy of the non-management school alternative. If we assume that the alternative
institution prices optimally to maximize revenue, it will charge a tuition price higher than
marginal cost (which like the elite and the nonselective schools is assumed to be zero)
and this sets in motion a complicated set of reactions. To understand these, it helps to
recognize that in the initial market outcome v3 = t3 = 0 and so, the non-business school
tuition t3 = 0 was in fact equal to marginal cost. Now relative values have changed and
value v3 > 0 leading to a tuition t3 > 0, i.e. greater than marginal cost.
Because the business training alternative sets a tuition price t3 that is now higher
relative to its marginal cost than it was previously, it further softens the pressure on price
relative to cost for the two initial institutions, and both raise their tuition fees a bit
further. Because of both peer effects and its research mission, the elite school tuition rise
allows it to cut back on enrollments and raise student quality, thereby increasing its grant
and donation income slightly. Again, this induces a similarly small tuition increase by the
15
less-selective school. The effects are not large relatively speaking—on the order of two to
five percent. Moreover, while the overall revenue of the elite school is relatively
unchanged by the arrival of the non-business school alternative (it loses some tuition but
gains some donation and grants), the revenue of the less-selective school that competes
more directly with the new alternative falls by nearly ten percent. Its enrollments shrink
by nearly 20 percent. So, this new competition does hurt. That pain though is
concentrated at the second-tier level.
However, the foregoing scenario may not be what those who fear a loss in the
legitimacy of traditional management schools have in mind. Critics such as Mintzberg
(2004), Pfeffer and Fong (2002), Starkey and Tempest (2008), Podolny (2009), and Thomas and
Wilson (2011) appear, in part at least, to fear a more general collapse in the perceived relative
usefulness of such training. One way to capture such a more general collapse is to imagine
instead that the third alternative, valued at v3 > 0, is provided competitively—by lots of firms
doing in-house training or many for-profit schools. If so, that competition will drive the price of
the valued alternative back to marginal cost (= 0). If this happens then the outcome will likely be
very large for both schools but the impact will still reflect an important differential between elite
and non-selective schools.
The immediate neighbor—so to speak—of the new training alternative is the less-selective
management program that now faces severe price competition. As a result, it must cut its tuition
quite dramatically. The elite business school will now feel this new price competition from its
less-selective rival and respond with a tuition price cut, as well. However, it is inhibited from
responding aggressively because again, it is reluctant to lower the average quality of its student
body owing to peer effects and research funding. This reluctance to cut price means that the
16
tuition gap between the elite school and its second-tier rival widens, leading more students to
abandon the former and switch to the latter. The elite program is left with a small but highly
talented cohort while the enrollment in the less-selective program actually expands. Overall, the
elite business program loses more students but as this raises its average student quality and thus
the educational value that it offers, its revenue loss is relatively small. By contrast, the less-
selective program’s steeper price reduction allows it to keep its enrollments fairly close to their
original level. It loses students to the new rival but gains some from the elite school. The steep
tuition price cut though necessary to achieve this means that its revenue falls. In the typical case,
it falls by close to 20 percent.
It is in this context that we can perhaps understand a further strategic response to this
loss of legitimacy as providers of professional training at traditional business schools,
namely, the move to online education. Education delivered at a distance via the medium of
the Internet may not have the same value or legitimacy in the eyes of potential students as
the standard brick-and-mortar programs. Yet it may be seen as at least equivalent to or
better than alternative, non-business school training if offered at the right price.
To be sure, once either the elite or less-selective standard schools start offering online
degrees, they begin to compete with their brick-and-mortar selves as well. Yet the only
option may be to lose many of these students either to alternative, non-MBA business
training or to one’s traditional rival who is cutting prices to compete with these non-school
alternatives. In short, the recent growth of online MBA programs, including those at highly
ranked schools such as Illinois-Champaign Urbana, may be seen as a strategic response to
the loss of legitimacy or relative value of traditional business education. This response may
also expand the overall number of MBA students once online programs are included.
17
5. Summary and Concluding Remarks
Questions regarding the legitimacy of the business school business have been raised for
some time but have taken on increased intensity and urgency in recent years. Such
challenges have at least two dimensions. One is the legitimacy of the business school as a
scholarly enterprise producing as well as disseminating knowledge on an equal footing
with the research mission of other academic institutions such as STEM programs, laws
schools, and medical schools. A second concern queries the value of the basic business
school training. Independent of any new knowledge that business faculty may produce, is
the existing knowledge that they transfer to students in MBA programs truly worthwhile?
We have approached these issues in an economics framework. Specifically, we have
built a formal model that captures the important dimensions of the business school
market. These include: 1) product differentiation among schools; 2) differences among
students in their ability to realize the benefits that a business school education offers; 3)
peer effects in learning; and 4) the potential for grant and donation income to augment
tuition revenue significantly at top institutions. For the most part, we work with a simple
duopoly model with one elite and one second-tier school. However, we later consider the
entry of a third alternative to an MBA program.
Our model suggests that the impact of challenges to business school legitimacy
depends, inter alia, on whether the challenge is focused on business school research or,
instead, on the transmission of professional management skills and competencies. In the
former case, the loss of legitimacy affects mainly the elite schools where large
investments in research activity have been made. Yet, in this case it is noteworthy that
the market response is for both schools to cut tuition and thereby expand business school
18
enrollments overall. In the second case, there is a fall in the perceived relative value of
the MBA professional training. Business school enrollments can shrink overall but it is the
second-tier programs that are now at risk in terms of revenue shortages.
This second challenge to legitimacy also raises the possibility that the longer-run
strategic response of business schools may include an expansion of online education
offered at a greatly reduced tuition price. In the absence of a challenge to their
pedagogical legitimacy, offering less expensive, online education would not be a wise
strategic choice as it largely steals students from existing brick-and-mortar programs.
However, when the value net of tuition cost for traditional programs falls relative to that
of non-business school alternatives, the strategic calculus changes. The online education
option can soften the blow because while potential students may not value the online
experience that highly, they will still find it attractive at a sufficiently low tuition rate, and
it is better to collect that revenue than to lose these students altogether.
Our model is a simplified version of the business school market and alternative
models may yield different insights. We certainly do not claim that our model is the
fundamental truth. We do claim however that the practice of modeling the economic
forces underlying business school competition is itself a valid and important exercise. It
permits one to identify the different challenges to legitimacy as well as to investigate the
strategic responses that these induce. Business schools and indeed law and other
professional schools may well be facing a legitimacy challenge. Precisely what kind of
challenge though and which schools are most threatened can only be understood by
establishing an analytical framework that permits explicit consideration of these issues.
19
6. References
Alvesson, Mats (2015). “Logics of Higher Education: Qualification, Customer-Satisfaction, or
Looking Good.” Presented at EFMD Conference on “The Legitimacy and Impact of
Business Schools and Universities.” Oxford, UK, 3-4, June.
Becker, E., C. M. Lindsay, C.M., and G. Grizzle, G. (2003). “The Derived Demand For Faculty
Research.” Managerial and Decision Economics, 24(8), 549.
Bennis, W. and J. O’Toole. (2005). “How Business Schools Lost their Way.” Harvard Business
Review, 83 (May) 96-104.
Byrne, J. (2011). “The Best B-School Alumni Networks in the U.S.” Poets & Quants.
http://poetsandquants.com/2011/05/30/best-b-school-alumni-networks/
Ferlie, E., G. McGivern and A. De Moraes. 2010. “Developing a Public Interest School of
Management.” British Journal of Management ,21: S60-S70.
Gabsewicz and Thisse (1979). “Price Competition, Quality, and Income Disparities.” Journal
of Economic Theory, 20 (June) 340-59.
Grilo, I, O. Shy, and J-F. Thisse (200). “Price Competition When Consumer Behavior Is
Characterized By Conformity Or Vanity.” Journal of Public Economics 80, (September), 385-
408.
Hoxby, C. and G. Weingarth (2005). “Taking Race Out of the Equation: School Reassignment
and the Structure of Peer Effects.” Mimeograph.
Imberman, S., A. Kugler, and B. Sacerdote (2009). “Katrina’s Children: Evidence on the
Structure of Peer Effects from Hurricane Evacuees.” American Economic Review, 102
(August), 2048-82.
Lavy, V., M. D. Paserman, and A. Schlosser (2007). “Inside the Black Box of Ability Peer
Effects: Evidence from Variation in the Proportion of Low Achievers in the Classroom.”
The Economic Journal, 122 (March), 208-37.
20
Mintzberg, H. (2004). Managers not MBAs: A Hard Look At The Soft Practice Of Managing
And Management Development. San Francisco: Berrett Koehler
Morgeson, F. and J. D. Nahrgang (2008). “Same As It Ever Was: Recognizing Stability In The
Business Week Rankings.” Academy of Management Learning & Education, 7: 26-41.
Mussa and Rosen (1978). “Monopoly and Product Quality.” Journal of Economic Theory, 18
(September), 301-17.
O’Brien, J.P., P. Drnevich, and T. Crook (2008). Does Business School Research Add
Economic Value For Students? Proceedings of the Academy of Management, Anaheim, CA.
_______, _______, _______, and C. Armstrong (2010). “Does Business School Research Add
Value for Students? Academy of Management Learning & Education, 9 (December), 638-51.
Peña, P., 2010. “Pricing in the Not-for-Profit Sector: Can Wealth Growth at American Colleges
Explain Chronic Tuition Increases? Journal of Human Capital, 4(3), 242-73.
Pettigrew, A. M. (1997a). ‘The Double Hurdles for Management Research’. In: T. Clarke (ed.),
Advancement in Organizational Behaviour: Essays in Honour of D. S. Pugh, Dartmouth
Press, London, 277-96. Pettigrew, A. (2001). “Management Research After Modernism.” British Journal of
Management, 12: 61–70.
Pfeffer, J. (2015). “Business School Legitimacy: How the Naked Emperor Perseveres.”
Presented at EFMD Conference on “The Legitimacy and Impact of Business Schools
and Universities.” Oxford, UK, 3-4, June.
Pfeffer, J. and C. Fong (2002). “The End of Business Schools? Less Success than Meets the
Eye.” Academy of Management Learning and Education, 1 (September), 78-95.
Podolny, J. M. (2009). “The Buck Stops (and Starts) at Business School” Harvard Business
Review, 87 (June), 62-70.
21
Rindova, V. P., Williamson, I. O., Petkova, A. P., & Sever, J. M. 2005. Being good or being
known: An empirical examination of the dimensions, antecedents, and consequences of
organizational reputation. Academy of Management Journal, 48(6): 1033-1049.
Shaked, A. and J. Sutton. (1982). “Price Competition Through Product Differentiation.”
Review of Economic Studies, 49 (January), 3-13.
Starkey, K. and S. Tempest (2008). “ A Clear Sense of Purpose? The Evolving Role of the
Business School.” Journal of Management Development , 27 (July), 379-90.
_________, and A. Pettigrew. (2015). “The Legitimacy and Impact of Business Schools.”
Academy of Management Learning and Education, Special Issue, forthcoming.
Thomas, Howard (2007). “Business School Strategy and Metrics for Success.” Journal of
Management Development. 26 (January), 33-42.
_________ and A. Wilson (2011). “Physics Envy,” British Journal of Management, 22
(September), 443-56.
________, and _______ (2012) "The Legitimacy of the Business of Business Schools: What's
the Future?", Journal of Management Development, 31 (July), 368 - 76
7. Appendix: A Formal Model of the Business School Market
We consider a simple duopoly model with vertically differentiated business programs.
There is a mass of N students, each indexed by the parameter θ i indicating student i's
ability to reap the benefits of a particular institution’s business program. θi is assumed to
be uniformly distributed between 0 and 1. For further simplicity, N is normalized to unity
so that market demands at each school are equivalent to the percentage of students
served.
The two business degree programs are vertically differentiated. The elite school offers
an educational product of intrinsic value v1. It’s less selective rival offers a lower ranked
22
product of intrinsic value v2 with v1 > v2 > 0. We normalize and set v1 = 1, so that v2
measures the intrinsic value of the less-selective school relative to that of its elite rival.
The expected utility of a student i attending the elite institution and incurring tuition cost t1
net of any scholarship funding is:
𝑈𝑈𝑖𝑖 = 𝜃𝜃𝑖𝑖𝑉𝑉1 − 𝛼𝛼𝑋𝑋�1− 𝑡𝑡1 (A1)
Here 𝑋𝑋�1 is the expected number of credentials or degrees conferred at the elite institution. The
greater is 𝑋𝑋�1, the less selective the elite school is and the lower is its average student quality.
This in turn, lowers the value of the education each student receives because of “peer effects”
and the parameter α is a measure of the importance of these effects.
There are no peer effects at the non-selective institution. Hence, a student’s expected
utility of attending the less selective business program at tuition cost t2 is:
𝑈𝑈𝑖𝑖 = 𝜃𝜃𝑖𝑖𝑉𝑉2− 𝑡𝑡2 (A2)
These utility functions imply the existence two marginal students for any set of tuition
prices t1 and t2. The first marginal student denoted by is such that the student is indifferent
between attending the elite school and its less selective rival. The second marginal student
denoted by is such that the student is indifferent between attending the less selective rival
and not attending a business school at all. These marginal θ values are defined by the
following three conditions:
(A3)
23
Given the assumptions of a uniform distribution of θ and N = 1 the demand functions facing the
high quality and low quality institutions are given by:
𝑋𝑋1(𝑡𝑡1, 𝑡𝑡2) = [1 − 𝜃𝜃�1(𝑡𝑡1, 𝑡𝑡2)] (A4) 𝑋𝑋2(𝑡𝑡1, 𝑡𝑡2) = [𝜃𝜃�1(𝑡𝑡1, 𝑡𝑡2) − 𝜃𝜃�2(𝑡𝑡2)]
We assume that students have rational expectations about the enrollment of institutions, which
as in Grilo, Shy and Thisse (2001), is equivalent to assuming that the institutions announce and
commit to their net tuition charges, 𝑡𝑡1 and 𝑡𝑡2 before students enroll.
We treat the total costs at each school as essentially fixed (capital facilities and
tenured faculty) and denote these as F1 and F2. Each school earns tuition revenue equal to
its tuition fee times the number of students, either X1(t1, t2) or X2(t1,t2) it enrolls. In
addition, the elite school earns research grant and alumni donation income that depends
positively on the overall skill level of its students, , which increases monotonically
with the last or marginal student admitted to the elite school. For simplicity, we assume
= , where D is a positive parameter. Consistent with our earlier normalizations, we
restrict the parameters α and D to satisfy: 0 < α < 1; and 0 < D < 1.
Each school seeks maximizes revenue net of costs or solves:
Elite School: max𝑡𝑡1 𝑡𝑡1�1 − 𝜃𝜃�1(𝑡𝑡1, 𝑡𝑡2)� + 𝜃𝜃�1(𝑡𝑡1, 𝑡𝑡2)𝐷𝐷 − 𝐹𝐹1 (A5)
Less Selective School: max𝑡𝑡2 𝑡𝑡2�𝜃𝜃�1(𝑡𝑡1, 𝑡𝑡2) − 𝜃𝜃�2(𝑡𝑡1, 𝑡𝑡2)� − 𝐹𝐹2 (A6)
Equations (A.5) and (A.6) imply the following best response functions:
𝑡𝑡1∗ =(1 + 𝐷𝐷 − 𝑣𝑣2 + 𝑡𝑡2)
2
(A7)
𝑡𝑡2∗ =(𝛼𝛼 + 𝑡𝑡1)𝑣𝑣22(1 + 𝛼𝛼)
24
Simultaneous solution of equations (A.7) yields the Nash equilibrium in tuition prices. We
restrict ourselves to selective outcomes defined as those equilibria in which relative to its less-
selective rival: 1) the elite school serves fewer (but a positive number of) students; 2) provides
greater perceived educational value; and 3) charges a higher tuition.11F
12 For this purpose, it is
useful to define three critical values of v2, the relative intrinsic value of the less-selective
school’s program.
For any relative quality of the less-selective school, 0 < v2 < 1, it is straightforward to show
that the less-selective school has a positive market share. However, if v2 is too high—if the less-
selective school’s business program is perceived to be close in quality to the elite institution’s—
the latter is unable to attract any students. In order to have a positive enrollment for the elite
program, there is an upward limit on v2. This limit is given by: =
2(1+𝛼𝛼)(1−𝐷𝐷)2−𝐷𝐷+𝛼𝛼
. Note that for any case in which this critical > 1, implying that
this constraint is always satisfied for all values of the parametersα,D in this range.
In addition the relative quality of the less-selective business program cannot be too large
otherwise those attending the elite school may not get added value.. In other words, we must
have for the marginal student at the elite institution: . We denote the critical
value of v2 satisfying this constraint as: .
12Those familiar with the canonical papers in vertical integration, Mussa and Rosen (1978), Gabszewicz, and Thisse (1979); and Shaked and Sutton (1982), will recognize that this result is distinctly different from that of these pioneering papers in which the highest quality firm also wins the largest market share. The difference here is due to the incorporation of peer effects and the non-tuition or grant and donation income for the elite school. In our framework, this corresponds to 𝛼𝛼 = 𝐷𝐷 = 0.
25
D
Finally, while v2 < is required to ensure that the elite school has positive enrollment a
further restriction on v2 is needed to ensure that the elite school enrolls fewer students than its
less-selective rival. This restriction is: 1 > v2 > ..
The regions of the parameter space 𝛼𝛼,𝐷𝐷 in Figure A1 below help identify the conditions for a
selective equilibrium. The downward-sloping red curve that delineates Region A indicates the
values for which = 0. For all values of α and D to the right and above this line, Hence,
the requirement that v2 be sufficiently large to ensure that the elite business program serves fewer
students is automatically satisfied for all α,D combinations outside of Region A.
Figure A1
The upward-sloping (left-to-right) curve separating Regions B and C reflects those
combinations such that = 1, defined by . Below and to the right of this curve,
> 1. Since v2 cannot exceed 1, this means that for all α, D combinations in Region B,
the condition that the elite institution has positive market share is satisfied. Conveniently,
however, it turns out that above this curve where , the requirement that v2 < is
α
A B
C
26
C
B AA
0.0 0.2 0.4 0.6 0.8 1.00.0
0.2
0.4
0.6
0.8
1.0
automatically met as well. Moreover, it is straightforward to show that whenever the elite
business program enrolls fewer students who each perceive that it offers higher educational value,
then it follows that in equilibrium t1 > t2.
The equilibrium in either Region B or Region C is always selective. In the former, the elite
school has a positive but smaller market share while The binding constraint on v ensures that it
offers higher educational value. In Region C, by contrast, the elite school is the elite school
offers a greater educational value and enrolls a smaller market share. The binding constraint on v
is to ensure that given these α,D combinations it enrolls a positive number of students.
The initial equilibrium implicitly assumes that there is no real alternative with positive
intrinsic value relative to that of either the elite or less-selective school. Hence, to the extent that
doubts in legitimacy reflect a fall in the relative value of business school programs, we can
capture the impact of such a challenge by introducing a third alternative that, while its intrinsic
value v3 is still less than that of either school, is now positive.
With the emergence of a third alternative with intrinsic value v3 > 0, the assumption that
each institution tries to maximize revenue given its fixed costs results in the tuition best
response functions below.
Elite (v1 = 1):
Less-Selective (0 < v3 < v2 < 1): (A8)
Non-Business School Alternative (0 < v3 < v2 < 1):
It is easy to see that equations (A8) resolve to the two-school case (A4) when v3 = t3 = 0.
The implied Nash equilibrium in tuition fees is:
27
(A9)
Enrollments and other equilibrium features then follow from equations (A9).
28
top related