08832323.2013.763755
Journal of Education for Business
ISSN: 0883-2323 (Print) 1940-3356 (Online) Journal homepage: http://www.tandfonline.com/loi/vjeb20
Management Science in U.S. AACSB InternationalAccredited Core Undergraduate Business School
Curricula
Susan W. Palocsay & Ina S. Markham
To cite this article: Susan W. Palocsay & Ina S. Markham (2014) Management Science in U.S.
AACSB International-Accredited Core Undergraduate Business School Curricula, Journal of
Education for Business, 89:2, 110-117, DOI: 10.1080/08832323.2013.763755
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Date: 11 January 2016, At: 20:32
JOURNAL OF EDUCATION FOR BUSINESS, 89: 110–117, 2014
C Taylor & Francis Group, LLC
Copyright
ISSN: 0883-2323 print / 1940-3356 online
DOI: 10.1080/08832323.2013.763755
Management Science in U.S. AACSB
International-Accredited Core Undergraduate
Business School Curricula
Susan W. Palocsay and Ina S. Markham
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James Madison University, Harrisonburg, Virginia, USA
In 2003, accreditation standards were revised to require coverage of management science
(MS) after previously removing it in 1991. Meanwhile, increasing awareness of the value
of business analytics stimulated a renewed interest in MS. To examine its present status in
undergraduate core business curricula, the authors conducted two studies to review quantitative
course requirements at top-ranked schools and to survey MS course content. The results indicate
limited visibility of MS as a discipline and significant variation in MS topic coverage across
institutions. These findings raise serious concerns about the ability of business schools to
produce future graduates with the skills needed to support industry adoption of advanced
analytics.
Keywords: business analytics, business core curricula, management science, quantitative
analysis
The decline of the management science (MS) course in business school programs has received considerable attention in
the MS community over the past two decades. After thriving as a requirement for Association to Advance Collegiate
Schools of Business (AACSB) accreditation until 1991, it
was suddenly removed from the standards in a revision aimed
at allowing more diversity in business school missions with
added flexibility in core curricula content. Criticism of its
emphasis on teaching mathematical techniques and lack of
relevance to management education were cited as primary
reasons for the traditional MS course being eliminated from
business programs at many institutions (Grossman, 2001;
Powell, 1998).
In an attempt to stave off its extinction, MS educators
began to shift away from teaching the detailed steps of algorithms toward spreadsheet-based quantitative analysis in
the mid-1990s (Powell, 2001; Ragsdale, 2001). This turned
out to be a natural transition because spreadsheet software
had already been widely adopted throughout the business
world for its data manipulation, graphing, and computational
Correspondence should be addressed to Susan W. Palocsay, James Madison University, Department of Computer Information Systems & Business
Analytics, MSC 0202, 800 S. Main Street, Harrisonburg, VA 22807, USA.
E-mail: palocssw@jmu.edu
capabilities. Thus, the changeover to a spreadsheet platform
immediately made MS more practical and relevant for business students. It also allowed for an increased emphasis on
modeling, problem solving, and quantitative reasoning skills
that are important for organizational decision-making (Powell, 1995). Other reform efforts included improved pedagogical methods and more usage of cases and real-world examples
of successful operations research (OR)/MS applications.
Then, in April 2003, the AACSB approved a new set of
standards for accreditation of business programs (AACSB International, 2011). While there were still no specific course
requirements, statistical data analysis and MS were added
to the requisite list of management-specific knowledge and
skills areas. The addition of this specification in the AACSB
standards, largely due to an Institute of Operations Research
and the Management Sciences (INFORMS)-supported petition effort (Horner, 2003), was anticipated to provide MS
with a second opportunity to demonstrate its value to management education and consequently strengthen MS content
in the business core (Grossman, 2003; Sodhi & Tang, 2008).
At the same time, advancements in information technology were driving explosive growth in the field of business analytics as companies sought ways to manage and understand
business performance using enterprise and e-commerce data
(Kohavi, Rothleder, & Simoudis, 2002). Subsequent media
and vendor reports on management by the numbers increased
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MANAGEMENT SCIENCE IN BUSINESS SCHOOL CURRICULA
awareness of the contribution of analytics to improved
business strategy and better financial results (Ante, 2009;
Baker, 2008; IBM Software Group, 2009; Thurm, 2007).
This attention gave a further boost to MS for its role as the
provider of advanced techniques used for predictive and prescriptive analytics (Lustig, Dietrich, Johnson, & Dziekan,
2010).
In this article, we provide an update on the current status of
MS in U.S. business programs with a focus on undergraduate
education, which has received less attention in the literature
than master of business administration (MBA) education. We
undertook this study for two reasons. First, it was necessary to
respond to a recent curriculum review at our institution where
a task force recommended removal of the MS course from
the business core—after it had survived the 1991 changes in
AACSB standards. Secondly, conversations with colleagues
at other schools and lack of pertinent literature revealed a
need for formal inquiry into the state of undergraduate MS
with regard to both changes in accreditation standards and
the emerging analytics field.
We first reviewed quantitative requirements in the business core at the top 50 schools as ranked in 2011 by
Bloomberg Businessweek (Gloeckler, 2011).1 Then we identified a subset of institutions from 452 AACSB-accredited
undergraduate programs with a clearly recognizable OR/MS
course in the core curriculum and surveyed business school
faculty at those schools to gain an overview of their course
content. We present survey findings in the context of the
historical evolution of MS teaching in business programs,
chronicled by an extensive bibliography. Finally, we discuss
implications for the future role of MS in the context of the
developing business trend toward increased use of analytics.
BACKGROUND
Prior to 1991, the structure of business programs had essentially become uniform to ensure compliance with standards
from the AACSB, the most prestigious business school accreditor. But criticisms of this curriculum, with its analytical
orientation and strong disciplinary focus, were already being
raised by the early 1980s. The emerging consensus was that
better preparation of business students demanded a broader,
more relevant education, which also encompassed interpersonal skills, political and regulatory factors, and a global
perspective (Windsor & Tuggle, 1982). Despite these warnings, the MS profession was unprepared for the fallout when
AACSB eliminated what was referred to as the common body
of knowledge that had mandated course work in disciplines,
including quantitative methods.
This abrupt change in accreditation philosophy gave business schools flexibility to design curricula appropriate for
their individual missions and constituents (Miles, Hazeldine, & Munilla, 2004). Curriculum requirements were limited to four areas of foundation knowledge (accounting,
111
behavioral science, economics, and mathematics–statistics)
and four core areas that did not directly correspond to the
pre-1991 common body of knowledge (Grossman, 2003). In
response to the ensuing decline of MS in business programs,
leaders in the discipline authored numerous reports and articles addressing various aspects of MS education for business
students. From a historical perspective, this body of literature
encompassed a range of important pedagogical topics over
the next decade:
• Analyzing reasons for the diminishing status of MS (e.g.,
Grossman, 2001; Jordan et al., 1996; Powell, 1998),
• Endorsing adoption of spreadsheet tools (e.g., Grossman,
1999; Powell, 1997; Ragsdale, 2001; Savage, 1997; Winston, 1996),
• Recommending emphases on end-user modeling (e.g.,
Leon, Przasnyski, & Seal, 1996; Powell, 1995, 2001),
• Suggesting more integration with functional business areas (e.g., Carraway & Clyman, 1997; Jordan et al., 1996),
and
• Advocating case teaching and other instructional methods
(Bodily, 1996; Lasdon & Liebman, 1998; Liebman, 1994;
Mukherjee, 2001).
Most of these works concentrated primarily on educational issues at the MBA level. However, many of the
points made in them also applied to undergraduate business
instruction. Chandrashekar and Kleinsorge (1997) conducted
a survey of undergraduate programs at 24 AACSB-accredited
business schools to examine quantitative core curriculum requirements for benchmarking purposes. They reviewed both
statistics and MS teaching practices and reported that all
of the schools mandated at least one statistics course but
only 25% included MS in the business core. Some programs
(17%) required MS for particular majors and others offered
it as an elective (12%). However, approximately half (46%)
provided no MS at the undergraduate level and none of these
schools indicated any interest in reinstating a formal MS
requirement.
In 2002, Ammar and Wright assessed MS relative to operations management (OM) in undergraduate business curricula at 163 masters-granting institutions. They found that OM
was required in the majority (84%) but MS was a mandatory
course at a mere 18% of them, while 13% required neither
OM nor MS. After classifying schools into three tiers, their
data showed that 23% of the top-tiered institutions had no
MS or OM requirements.
In contrast, a 2003 review reported that a much higher percentage (40.7%) of 342 AACSB-accredited business schools
offered at least one course with MS content at the undergraduate level (Albritton, McMullen, & Gardiner, 2003). These
results were based on a methodology which characterized
offerings as MS when the course titles included the terms
operations research or management science. Courses labeled
as quantitative analysis or methods (QA/QM) were counted
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S. W. PALOCSAY AND I. S. MARKHAM
separately and assumed to cover a combination of MS and
statistics if there was not a distinct statistics course. It was
unclear whether or not these courses were core requirements
for all business majors. Using this approach, the detailed
breakdown of schools in the study showed that 35.1% had
at least one OR/MS course, 5.6% had both statistics and
QA/QM courses, 14.3% had only QA/QM, 9.6% had only
statistics, and 35.4% did not have a course with either title
specification (MS or QA/QM).
Another major revision of AACSB accreditation standards
in 2003 introduced a standard for curricula management
that emphasizes systematic evaluation and continuous improvement while still not requiring a specific list of courses
(Gundersen et al., 2011). However, it did mandate that 14
content topics be present, of which three are relevant to MS:
general knowledge and abilities in the “use of information
technology” and “analytical skills” and management-specific
skills in “statistical data analysis and management science as
they support decision-making processes throughout an organization” (AACSB International, 2011, p. 70).
MS can be broadly defined as the application of advanced
analytical principles and methods from mathematics, engineering, and science to improve organizational ability to
address managerial problems and issues (INFORMS, 2012).
The new AACSB standards were welcomed in the MS community as support of the view that business graduates need
quantitative, decision-oriented analytical tools and concepts
for long-term success in their careers. This view was further reinforced by an increasing focus on data analysis technologies (Kohavi et al., 2002). As a result, MS was widely
expected to undergo a renaissance in business schools.
QUANTITATIVE REQUIREMENTS AT
TOP-RANKED U.S. BUSINESS SCHOOLS
The primary objective of this research was to assess the
present state of MS and establish a baseline for comparison of
quantitative core requirements, including calculus, statistics
and OM as well as MS, using top-ranked AACSB-accredited
undergraduate business programs in the United States. A
broad perspective was desirable because undergraduates, unlike MBA students, are subject to both general and business
educational requirements. A study by Lee and Lee (2009)
found that more rigorous mathematical content in curricula
was associated with higher undergraduate starting salaries.
Also, many business school faculty and administrators view
these subjects as a collective group providing mathematical
and problem-solving skills.
The 2011 rankings as listed in Bloomberg Businessweek
are available online in a special report published in March
(Gloeckler, 2011). The rankings are based on five major
components: academic quality (30%), student survey (30%),
recruiter survey (20%), starting salaries (10%), and graduates sent to top MBA programs (10%). A detailed descrip-
TABLE 1
Distribution of MS Courses
Highest degree
Masters
Doctorate
Total
No MS course
MS course
72.22%
71.88%
72.00%
27.78%
28.13%
28.00%
Note. MS = management science.
tion of the methodology for calculation of these component
scores is described in Lavelle (2011). The academic quality
measure equally weights average SAT scores, student-tofaculty ratios, average class sizes, percentage of students
with internships, and hours spent on schoolwork.
Geographically, the top 50 schools in 2011 were distributed among 22 states with almost a third located in
Massachusetts, Pennsylvania, and New York. Thirty of these
schools were private institutions. Average full-time undergraduate student enrollment was 1,815 with a 17.5 average
student-faculty ratio. A doctorate is the highest degree offered in business at 32 of the schools with the remaining 18
offering master’s degrees. AACSB profile data (provided by
44 of the schools) indicate that an average of 386.14 (total
of 16,990) master’s degrees were granted versus 564.4 (total of 24,832) undergraduate business degrees in 2009–2010.
Only 15 schools reported graduating more master’s than undergraduate students, underscoring the significance of undergraduate business education.
We reviewed each school’s web site to determine quantitative core curriculum requirements and, because all programs
require at least one calculus course, we focused attention on
statistics, OM, and MS. Each course was classified as being
primarily one of these three subject areas based on course
title and catalog description with two additional categories
created for hybrid courses (statistics/MS and MS/OM). To be
labeled as an MS course, evidence of multiple MS topics areas was required with an emphasis on optimization, decision
analysis, and simulation. We did not consider MS courses
that were required only in specified business majors (e.g.,
finance) or available as electives. Using this methodology,
we found an MS course in 14 schools (28%), a statistics/MS
hybrid course in 6 schools (12%), and one MS/OM hybrid
course (2%). The distribution of the 14 MS courses among
schools offering doctorates was similar to that of master’s
degree-granting schools as shown in Table 1.
Next we grouped the 50 schools based on their quantitative profile: statistics only, statistics and OM, statistics and
MS, and all three courses required. Results are presented in
Figure 1. The dominant profile was a combination of statistics and OM. Of the 29 business programs with this profile,
10 required two statistics courses in addition to OM. A requirement for a three-course sequence of statistics, MS, and
OM was the second most common profile. Among these 14
programs, there was one MS/OM hybrid course and three
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MANAGEMENT SCIENCE IN BUSINESS SCHOOL CURRICULA
FIGURE 1 Quantitative profiles of top-ranked business schools (color
figure available online).
statistics/MS hybrids; two of these three hybrid courses were
required in addition to a separate MS course. Overall, 48%
of the top 50-ranked programs required at least three quantitative courses.
The diversity of quantitative requirements at these highly
ranked schools reinforces the flexibility allowed in application of AACSB standards. All of them, however, require one
or more statistics courses. Statistics has long been considered
essential for business curricula, most likely due to its close association with economics (Becker, 1987; Tabatabai & Gamble, 1997). It is also frequently used to satisfy mathematics
requirements for general education and may be taught outside
the business school. Most of the statistics course descriptions
included traditional introductory topics: descriptive statistics,
probability concepts and distributions, confidence interval
estimation, hypothesis testing, correlation, and simple linear
regression. Analysis of variance, multiple regression, time
series forecasting, quality control, and decision analysis also
appeared but less frequently. Some course descriptions indicated an emphasis on business decision-making applications
and use of computer software.
A majority (86%) of the top-ranked schools also require
OM in the core undergraduate curriculum, acknowledging
its significance as a primary functional area of business
(Raiszadeh & Ettkin, 1989). However, OM course titles and
descriptions were less homogeneous than those for statistics and reflected changes in the field over time (Hays,
Bouzdine-Chameeva, Goldstein, Hill, & Scavarda, 2007).
Many of the OM courses showed the continuing influence
of industrial engineering and OR with coverage of mathematical models for aggregate planning, facility location, production distribution, and inventory management (Lovejoy,
1998). Topics overlapping with both statistics and MS also included forecasting, quality control, and project management.
But approximately a third of OM courses indicated distinct
movement away from being technique-oriented with more
113
attention on supply chain management, process improvement, service management (Aksin & DeHoratius, 2010a,
2010b), globalization, applications of information technology, and integration with other business disciplines (Pal &
Busing, 2008).
A qualitative evaluation of course information for MS
revealed considerably less structure than statistics and more
variation than OM. For example, course titles included Quantitative Analysis, Analytic Decision Modeling Using Spreadsheets, and Mathematics for Management Science. Decision making in a business context was a theme throughout
MS course descriptions. About 75% referred to quantitative
models or modeling and approximately half specified use of
spreadsheets. Linear programming and optimization were the
most frequently occurring topics when coverage was listed.
Overall, MS was less visible than either statistics or OM:
“management science” appeared in only about a quarter of
MS course titles.
SURVEY OF CONTENT IN MS COURSES
The diversity of MS courses in the top-ranked business
schools prompted us to seek more data from the population of AACSB-accredited undergraduate programs in the
United States. We briefly examined curricula at 452 institutions and located 68 required MS courses as the basis for a
survey. Note that this was not an in-depth assessment due
to the size of the dataset and may underrepresent the presence of MS. We selected one contact (faculty member or
administrator) for each department or school responsible for
the MS courses and distributed a short web-based survey.
Twenty-four complete responses (35%) were received.
Coverage of modeling topics in MS courses varied across
respondent institutions (Figure 2). Albrightton et al. (2003)
and Gallagher (1991) previously reported linear programming (LP) as the most frequently occurring topic in MBA
courses as did Gunawardane (1991) for undergraduate programs. LP continued to dominate in our study and was the
only topic taught in all of the courses. Decision analysis
FIGURE 2
Coverage of MS topics (color figure available online).
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114
S. W. PALOCSAY AND I. S. MARKHAM
FIGURE 3
online).
Coverage of LP modeling applications (color figure available
was second, also matching rankings in Gunawardane and
Gallagher However, our results showed a general shift toward more project management, including Program Evaluation and Review Technique/Critical Path Method, than simulation, queuing, and inventory modeling. Unlike previous
studies, we listed breakeven analysis as a possible topic and
found that it was covered in 67% of respondent courses.
Overlap with statistics occurred with a little more than half
of the MS courses incorporating regression and time series
forecasting.
Anticipating the prevalence of LP, we asked respondents
about treatment of applications of LP modeling using standard textbook nomenclature (Figure 3). Traditional product
mix, blending, and network models were in the top tier. Production and inventory planning across multiple time periods
also had strong visibility. Financial applications and data envelopment analysis, a recent addition for MS textbooks, were
significantly less popular.
When questioned about the use of computer software,
a majority (87%) of the respondents indicated that use of
Excel spreadsheets was required. For the remainder, the
primary software being used was QM for Windows (ver. 3.2,
Prentice Hall, Inc., Upper Saddle River, NJ). For spreadsheet
users, emphasis was on built-in Excel tools, particularly
Solver (Figure 4). Use of commercial add-ins for decision
analysis and simulation was also correlated with frequency
of topic coverage. There were a total of 10 different
textbooks used with only two of them being adopted at six
or more schools: An Introduction to Management Science
(13th ed.; Anderson, Sweeney, Williams, Camm, & Martin,
2011) and Quantitative Analysis for Management (10th ed.;
Render, Stair, & Hanna, 2009).
DISCUSSION AND LIMITATIONS
Our findings indicate that top-ranked business schools generally require substantial course work with a strong quantitative
emphasis. However, the role of MS in developing quantita-
FIGURE 4
online).
Usage of Excel tools and add-ins (color figure available
tive skills in business students varies considerably among
these programs. When compared to earlier studies, we did
not discover any concrete evidence that the 2003 reinstatement of MS in AACSB standards and/or the embracing of
analytics by industry have generated a resurgence of MS in
undergraduate business curricula. We acknowledge that it is
possible (but difficult to determine) that these may have influenced some schools to retain MS courses and/or content
in their programs.
Our survey on undergraduate MS course content showed
that linear optimization and decision analysis continue to
maintain a solid presence but otherwise there is significant
variety in topic coverage. Historically discussion about which
topics should be included in an introductory MS course
has centered around MBA curricula. Borsting, Cook, King,
Rardin, and Tuggle (1988) proposed two MBA course designs which included linear programming, simulation (of
waiting lines), and either inventory theory or decision theory plus forecasting. In a response to this proposal, Samson
(1988) suggested minimum and maximum percentages for
a broader list of course topics, making an argument in favor of more breadth than depth in coverage. He gave linear
programming and decision theory ranges of 20% to 50% and
dynamic programming and simulation ranges of 10% to 30%.
All other topics were assigned minimums of 0% indicating
that they were optional.
Gallagher (1991) surveyed executive MBA programs and
found six areas that were cited by a majority of respondents
(in order): linear programming, decision analysis, inventory,
simulation, project management, and queuing theory. He also
found a strong tendency to include inventory theory and
project management in the MS course when OM was not required. In a survey of 150 undergraduate business programs,
Gunawardane (1991) reported that the four topics most frequently taught were (in order) linear programming, decision
theory, simulation, and queuing theory. As spreadsheets became the primary teaching technology, Winston (1996) as
well as Carraway and Clyman (1997) described MBA courses
with modules on mathematical programming, decision
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MANAGEMENT SCIENCE IN BUSINESS SCHOOL CURRICULA
theory, and Monte Carlo simulation. Other approaches to
MS course design have been based on surveys comparing
topics taught in MBA programs to importance of techniques
as used by practitioners in industry (e.g., Chen, 1981; Lane,
Mansour, & Harpell, 1993). More recently, Albritton and
McMullen (2006) proposed using forecasting topics to integrate statistics and MS and Noonan (2007) advocated a
hybrid course that presents data analysis and statistics in
support of decision making via traditional MS techniques.
The extensive literature on MS education, dating back to
the 1950s, indicates that there has never been a clear consensus on MS curricula or required MS course topics (e.g.,
Burford & Williams, 1972). In addition, reviews of the proposed MBA courses in Borsting et al. (1988) criticized the assumption of prerequisite knowledge of probability and statistics and skills in mathematical reasoning. At that time, there
was an expectation that the MS course would be part of a
triad consisting of statistics, MS, and OM due to the highly
structured nature of AACSB standards. We saw evidence that,
while some (28%) of the top-ranked undergraduate programs
still follow the original sequence, a majority have integrated
MS into their OM courses while maintaining a separate statistics requirement. This indicates that MS is likely still seen
as essentially a pre- or corequisite for OM and may not be
getting recognition for its applicability across the other functional areas of business.
IMPLICATIONS FOR THE FUTURE
Our review of MS course status provides strong evidence
that the identity problems associated with MS as a profession (Sodhi & Tang, 2008) continue to affect its stance in
undergraduate business curricula. In those programs where
MS is highly visible, it is generally recognized for providing
students with a strong foundation in Excel-based modeling.
Upstream teaching faculty, particularly in the finance and
accounting disciplines, has come to rely on prior training
of spreadsheet-modeling skills. These programs are in the
best position to take advantage of the current buzz around
business analytics as a means for corporations to develop
competitive gains.
The most frequently cited definition of analytics, due to
Davenport and Harris (2007), is “the extensive use of data,
statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions
and actions” (p. 7). They went on to identify four categories
of business analysts based on roles and job responsibilities:
champions, professionals, semiprofessional, and amateurs. A
report from the McKinsey Global Institute (Manyika et al.,
2011) cited a shortage of people with skills for analyzing and
decision making with big data as a major obstacle for organizational innovation, productivity, and growth. And lack of
knowledge of how to use analytics to improve business performance was identified as one of the top two challenges in a
115
survey of executive managers by the MIT Sloan Management
Review and the IBM Institute for Business Value (Lavalle,
Hopkins, Lesser, Shocklley, & Kruschwitz, 2010).
INFORMS, with strong support from its members (Liberatore & Luo, 2011), has recently taken several steps aimed
at becoming the primary source of analytical professionals who create advanced models and algorithms: publication of the Analytics magazine, chartering of an analytics
section, renaming the practice conference, and development
of a certification for analytics professionals. However, this
group of analysts is predicted to represent only 5–10% of a
company’s analytic talent. In contrast, analytical amateurs,
described as knowledgeable consumers of analytics, are expected to comprise 70–80% of an organization’s analytical
workforce. Another 15–20% of analysts are projected to be
semi-professionals (Harris, Craig, & Egan, 2010).
Business schools have an opportunity to address the need
for these analytical semi-professionals and amateurs: employees who will be responsible for collecting and organizing data, comprehending analytical solutions, incorporating analytical results in specific business domains such as
marketing, finance, and operations, and generating insights
for enhanced organizational decision-making (Liberatore &
Luo, 2010). OR/MS Today (List, 2012) recently reported that
there was a 75% increase in the number of online ads for
jobs requiring data analysis skills between 2010 and 2012,
with management and market research analysts representing two of the three occupations most frequently needing
these skills. Discussion of the future position of MS in undergraduate business school curricula should consider how
to capitalize on this opportunity and create a leadership role
for MS in producing graduates proficient in the skills needed
to support industry adoption of analytics.
NOTE
1. Our college of business has consistently held a position
in the top 5% of undergraduate business schools ranked
by Bloomberg Businessweek.
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ISSN: 0883-2323 (Print) 1940-3356 (Online) Journal homepage: http://www.tandfonline.com/loi/vjeb20
Management Science in U.S. AACSB InternationalAccredited Core Undergraduate Business School
Curricula
Susan W. Palocsay & Ina S. Markham
To cite this article: Susan W. Palocsay & Ina S. Markham (2014) Management Science in U.S.
AACSB International-Accredited Core Undergraduate Business School Curricula, Journal of
Education for Business, 89:2, 110-117, DOI: 10.1080/08832323.2013.763755
To link to this article: http://dx.doi.org/10.1080/08832323.2013.763755
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Date: 11 January 2016, At: 20:32
JOURNAL OF EDUCATION FOR BUSINESS, 89: 110–117, 2014
C Taylor & Francis Group, LLC
Copyright
ISSN: 0883-2323 print / 1940-3356 online
DOI: 10.1080/08832323.2013.763755
Management Science in U.S. AACSB
International-Accredited Core Undergraduate
Business School Curricula
Susan W. Palocsay and Ina S. Markham
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James Madison University, Harrisonburg, Virginia, USA
In 2003, accreditation standards were revised to require coverage of management science
(MS) after previously removing it in 1991. Meanwhile, increasing awareness of the value
of business analytics stimulated a renewed interest in MS. To examine its present status in
undergraduate core business curricula, the authors conducted two studies to review quantitative
course requirements at top-ranked schools and to survey MS course content. The results indicate
limited visibility of MS as a discipline and significant variation in MS topic coverage across
institutions. These findings raise serious concerns about the ability of business schools to
produce future graduates with the skills needed to support industry adoption of advanced
analytics.
Keywords: business analytics, business core curricula, management science, quantitative
analysis
The decline of the management science (MS) course in business school programs has received considerable attention in
the MS community over the past two decades. After thriving as a requirement for Association to Advance Collegiate
Schools of Business (AACSB) accreditation until 1991, it
was suddenly removed from the standards in a revision aimed
at allowing more diversity in business school missions with
added flexibility in core curricula content. Criticism of its
emphasis on teaching mathematical techniques and lack of
relevance to management education were cited as primary
reasons for the traditional MS course being eliminated from
business programs at many institutions (Grossman, 2001;
Powell, 1998).
In an attempt to stave off its extinction, MS educators
began to shift away from teaching the detailed steps of algorithms toward spreadsheet-based quantitative analysis in
the mid-1990s (Powell, 2001; Ragsdale, 2001). This turned
out to be a natural transition because spreadsheet software
had already been widely adopted throughout the business
world for its data manipulation, graphing, and computational
Correspondence should be addressed to Susan W. Palocsay, James Madison University, Department of Computer Information Systems & Business
Analytics, MSC 0202, 800 S. Main Street, Harrisonburg, VA 22807, USA.
E-mail: palocssw@jmu.edu
capabilities. Thus, the changeover to a spreadsheet platform
immediately made MS more practical and relevant for business students. It also allowed for an increased emphasis on
modeling, problem solving, and quantitative reasoning skills
that are important for organizational decision-making (Powell, 1995). Other reform efforts included improved pedagogical methods and more usage of cases and real-world examples
of successful operations research (OR)/MS applications.
Then, in April 2003, the AACSB approved a new set of
standards for accreditation of business programs (AACSB International, 2011). While there were still no specific course
requirements, statistical data analysis and MS were added
to the requisite list of management-specific knowledge and
skills areas. The addition of this specification in the AACSB
standards, largely due to an Institute of Operations Research
and the Management Sciences (INFORMS)-supported petition effort (Horner, 2003), was anticipated to provide MS
with a second opportunity to demonstrate its value to management education and consequently strengthen MS content
in the business core (Grossman, 2003; Sodhi & Tang, 2008).
At the same time, advancements in information technology were driving explosive growth in the field of business analytics as companies sought ways to manage and understand
business performance using enterprise and e-commerce data
(Kohavi, Rothleder, & Simoudis, 2002). Subsequent media
and vendor reports on management by the numbers increased
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MANAGEMENT SCIENCE IN BUSINESS SCHOOL CURRICULA
awareness of the contribution of analytics to improved
business strategy and better financial results (Ante, 2009;
Baker, 2008; IBM Software Group, 2009; Thurm, 2007).
This attention gave a further boost to MS for its role as the
provider of advanced techniques used for predictive and prescriptive analytics (Lustig, Dietrich, Johnson, & Dziekan,
2010).
In this article, we provide an update on the current status of
MS in U.S. business programs with a focus on undergraduate
education, which has received less attention in the literature
than master of business administration (MBA) education. We
undertook this study for two reasons. First, it was necessary to
respond to a recent curriculum review at our institution where
a task force recommended removal of the MS course from
the business core—after it had survived the 1991 changes in
AACSB standards. Secondly, conversations with colleagues
at other schools and lack of pertinent literature revealed a
need for formal inquiry into the state of undergraduate MS
with regard to both changes in accreditation standards and
the emerging analytics field.
We first reviewed quantitative requirements in the business core at the top 50 schools as ranked in 2011 by
Bloomberg Businessweek (Gloeckler, 2011).1 Then we identified a subset of institutions from 452 AACSB-accredited
undergraduate programs with a clearly recognizable OR/MS
course in the core curriculum and surveyed business school
faculty at those schools to gain an overview of their course
content. We present survey findings in the context of the
historical evolution of MS teaching in business programs,
chronicled by an extensive bibliography. Finally, we discuss
implications for the future role of MS in the context of the
developing business trend toward increased use of analytics.
BACKGROUND
Prior to 1991, the structure of business programs had essentially become uniform to ensure compliance with standards
from the AACSB, the most prestigious business school accreditor. But criticisms of this curriculum, with its analytical
orientation and strong disciplinary focus, were already being
raised by the early 1980s. The emerging consensus was that
better preparation of business students demanded a broader,
more relevant education, which also encompassed interpersonal skills, political and regulatory factors, and a global
perspective (Windsor & Tuggle, 1982). Despite these warnings, the MS profession was unprepared for the fallout when
AACSB eliminated what was referred to as the common body
of knowledge that had mandated course work in disciplines,
including quantitative methods.
This abrupt change in accreditation philosophy gave business schools flexibility to design curricula appropriate for
their individual missions and constituents (Miles, Hazeldine, & Munilla, 2004). Curriculum requirements were limited to four areas of foundation knowledge (accounting,
111
behavioral science, economics, and mathematics–statistics)
and four core areas that did not directly correspond to the
pre-1991 common body of knowledge (Grossman, 2003). In
response to the ensuing decline of MS in business programs,
leaders in the discipline authored numerous reports and articles addressing various aspects of MS education for business
students. From a historical perspective, this body of literature
encompassed a range of important pedagogical topics over
the next decade:
• Analyzing reasons for the diminishing status of MS (e.g.,
Grossman, 2001; Jordan et al., 1996; Powell, 1998),
• Endorsing adoption of spreadsheet tools (e.g., Grossman,
1999; Powell, 1997; Ragsdale, 2001; Savage, 1997; Winston, 1996),
• Recommending emphases on end-user modeling (e.g.,
Leon, Przasnyski, & Seal, 1996; Powell, 1995, 2001),
• Suggesting more integration with functional business areas (e.g., Carraway & Clyman, 1997; Jordan et al., 1996),
and
• Advocating case teaching and other instructional methods
(Bodily, 1996; Lasdon & Liebman, 1998; Liebman, 1994;
Mukherjee, 2001).
Most of these works concentrated primarily on educational issues at the MBA level. However, many of the
points made in them also applied to undergraduate business
instruction. Chandrashekar and Kleinsorge (1997) conducted
a survey of undergraduate programs at 24 AACSB-accredited
business schools to examine quantitative core curriculum requirements for benchmarking purposes. They reviewed both
statistics and MS teaching practices and reported that all
of the schools mandated at least one statistics course but
only 25% included MS in the business core. Some programs
(17%) required MS for particular majors and others offered
it as an elective (12%). However, approximately half (46%)
provided no MS at the undergraduate level and none of these
schools indicated any interest in reinstating a formal MS
requirement.
In 2002, Ammar and Wright assessed MS relative to operations management (OM) in undergraduate business curricula at 163 masters-granting institutions. They found that OM
was required in the majority (84%) but MS was a mandatory
course at a mere 18% of them, while 13% required neither
OM nor MS. After classifying schools into three tiers, their
data showed that 23% of the top-tiered institutions had no
MS or OM requirements.
In contrast, a 2003 review reported that a much higher percentage (40.7%) of 342 AACSB-accredited business schools
offered at least one course with MS content at the undergraduate level (Albritton, McMullen, & Gardiner, 2003). These
results were based on a methodology which characterized
offerings as MS when the course titles included the terms
operations research or management science. Courses labeled
as quantitative analysis or methods (QA/QM) were counted
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S. W. PALOCSAY AND I. S. MARKHAM
separately and assumed to cover a combination of MS and
statistics if there was not a distinct statistics course. It was
unclear whether or not these courses were core requirements
for all business majors. Using this approach, the detailed
breakdown of schools in the study showed that 35.1% had
at least one OR/MS course, 5.6% had both statistics and
QA/QM courses, 14.3% had only QA/QM, 9.6% had only
statistics, and 35.4% did not have a course with either title
specification (MS or QA/QM).
Another major revision of AACSB accreditation standards
in 2003 introduced a standard for curricula management
that emphasizes systematic evaluation and continuous improvement while still not requiring a specific list of courses
(Gundersen et al., 2011). However, it did mandate that 14
content topics be present, of which three are relevant to MS:
general knowledge and abilities in the “use of information
technology” and “analytical skills” and management-specific
skills in “statistical data analysis and management science as
they support decision-making processes throughout an organization” (AACSB International, 2011, p. 70).
MS can be broadly defined as the application of advanced
analytical principles and methods from mathematics, engineering, and science to improve organizational ability to
address managerial problems and issues (INFORMS, 2012).
The new AACSB standards were welcomed in the MS community as support of the view that business graduates need
quantitative, decision-oriented analytical tools and concepts
for long-term success in their careers. This view was further reinforced by an increasing focus on data analysis technologies (Kohavi et al., 2002). As a result, MS was widely
expected to undergo a renaissance in business schools.
QUANTITATIVE REQUIREMENTS AT
TOP-RANKED U.S. BUSINESS SCHOOLS
The primary objective of this research was to assess the
present state of MS and establish a baseline for comparison of
quantitative core requirements, including calculus, statistics
and OM as well as MS, using top-ranked AACSB-accredited
undergraduate business programs in the United States. A
broad perspective was desirable because undergraduates, unlike MBA students, are subject to both general and business
educational requirements. A study by Lee and Lee (2009)
found that more rigorous mathematical content in curricula
was associated with higher undergraduate starting salaries.
Also, many business school faculty and administrators view
these subjects as a collective group providing mathematical
and problem-solving skills.
The 2011 rankings as listed in Bloomberg Businessweek
are available online in a special report published in March
(Gloeckler, 2011). The rankings are based on five major
components: academic quality (30%), student survey (30%),
recruiter survey (20%), starting salaries (10%), and graduates sent to top MBA programs (10%). A detailed descrip-
TABLE 1
Distribution of MS Courses
Highest degree
Masters
Doctorate
Total
No MS course
MS course
72.22%
71.88%
72.00%
27.78%
28.13%
28.00%
Note. MS = management science.
tion of the methodology for calculation of these component
scores is described in Lavelle (2011). The academic quality
measure equally weights average SAT scores, student-tofaculty ratios, average class sizes, percentage of students
with internships, and hours spent on schoolwork.
Geographically, the top 50 schools in 2011 were distributed among 22 states with almost a third located in
Massachusetts, Pennsylvania, and New York. Thirty of these
schools were private institutions. Average full-time undergraduate student enrollment was 1,815 with a 17.5 average
student-faculty ratio. A doctorate is the highest degree offered in business at 32 of the schools with the remaining 18
offering master’s degrees. AACSB profile data (provided by
44 of the schools) indicate that an average of 386.14 (total
of 16,990) master’s degrees were granted versus 564.4 (total of 24,832) undergraduate business degrees in 2009–2010.
Only 15 schools reported graduating more master’s than undergraduate students, underscoring the significance of undergraduate business education.
We reviewed each school’s web site to determine quantitative core curriculum requirements and, because all programs
require at least one calculus course, we focused attention on
statistics, OM, and MS. Each course was classified as being
primarily one of these three subject areas based on course
title and catalog description with two additional categories
created for hybrid courses (statistics/MS and MS/OM). To be
labeled as an MS course, evidence of multiple MS topics areas was required with an emphasis on optimization, decision
analysis, and simulation. We did not consider MS courses
that were required only in specified business majors (e.g.,
finance) or available as electives. Using this methodology,
we found an MS course in 14 schools (28%), a statistics/MS
hybrid course in 6 schools (12%), and one MS/OM hybrid
course (2%). The distribution of the 14 MS courses among
schools offering doctorates was similar to that of master’s
degree-granting schools as shown in Table 1.
Next we grouped the 50 schools based on their quantitative profile: statistics only, statistics and OM, statistics and
MS, and all three courses required. Results are presented in
Figure 1. The dominant profile was a combination of statistics and OM. Of the 29 business programs with this profile,
10 required two statistics courses in addition to OM. A requirement for a three-course sequence of statistics, MS, and
OM was the second most common profile. Among these 14
programs, there was one MS/OM hybrid course and three
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MANAGEMENT SCIENCE IN BUSINESS SCHOOL CURRICULA
FIGURE 1 Quantitative profiles of top-ranked business schools (color
figure available online).
statistics/MS hybrids; two of these three hybrid courses were
required in addition to a separate MS course. Overall, 48%
of the top 50-ranked programs required at least three quantitative courses.
The diversity of quantitative requirements at these highly
ranked schools reinforces the flexibility allowed in application of AACSB standards. All of them, however, require one
or more statistics courses. Statistics has long been considered
essential for business curricula, most likely due to its close association with economics (Becker, 1987; Tabatabai & Gamble, 1997). It is also frequently used to satisfy mathematics
requirements for general education and may be taught outside
the business school. Most of the statistics course descriptions
included traditional introductory topics: descriptive statistics,
probability concepts and distributions, confidence interval
estimation, hypothesis testing, correlation, and simple linear
regression. Analysis of variance, multiple regression, time
series forecasting, quality control, and decision analysis also
appeared but less frequently. Some course descriptions indicated an emphasis on business decision-making applications
and use of computer software.
A majority (86%) of the top-ranked schools also require
OM in the core undergraduate curriculum, acknowledging
its significance as a primary functional area of business
(Raiszadeh & Ettkin, 1989). However, OM course titles and
descriptions were less homogeneous than those for statistics and reflected changes in the field over time (Hays,
Bouzdine-Chameeva, Goldstein, Hill, & Scavarda, 2007).
Many of the OM courses showed the continuing influence
of industrial engineering and OR with coverage of mathematical models for aggregate planning, facility location, production distribution, and inventory management (Lovejoy,
1998). Topics overlapping with both statistics and MS also included forecasting, quality control, and project management.
But approximately a third of OM courses indicated distinct
movement away from being technique-oriented with more
113
attention on supply chain management, process improvement, service management (Aksin & DeHoratius, 2010a,
2010b), globalization, applications of information technology, and integration with other business disciplines (Pal &
Busing, 2008).
A qualitative evaluation of course information for MS
revealed considerably less structure than statistics and more
variation than OM. For example, course titles included Quantitative Analysis, Analytic Decision Modeling Using Spreadsheets, and Mathematics for Management Science. Decision making in a business context was a theme throughout
MS course descriptions. About 75% referred to quantitative
models or modeling and approximately half specified use of
spreadsheets. Linear programming and optimization were the
most frequently occurring topics when coverage was listed.
Overall, MS was less visible than either statistics or OM:
“management science” appeared in only about a quarter of
MS course titles.
SURVEY OF CONTENT IN MS COURSES
The diversity of MS courses in the top-ranked business
schools prompted us to seek more data from the population of AACSB-accredited undergraduate programs in the
United States. We briefly examined curricula at 452 institutions and located 68 required MS courses as the basis for a
survey. Note that this was not an in-depth assessment due
to the size of the dataset and may underrepresent the presence of MS. We selected one contact (faculty member or
administrator) for each department or school responsible for
the MS courses and distributed a short web-based survey.
Twenty-four complete responses (35%) were received.
Coverage of modeling topics in MS courses varied across
respondent institutions (Figure 2). Albrightton et al. (2003)
and Gallagher (1991) previously reported linear programming (LP) as the most frequently occurring topic in MBA
courses as did Gunawardane (1991) for undergraduate programs. LP continued to dominate in our study and was the
only topic taught in all of the courses. Decision analysis
FIGURE 2
Coverage of MS topics (color figure available online).
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114
S. W. PALOCSAY AND I. S. MARKHAM
FIGURE 3
online).
Coverage of LP modeling applications (color figure available
was second, also matching rankings in Gunawardane and
Gallagher However, our results showed a general shift toward more project management, including Program Evaluation and Review Technique/Critical Path Method, than simulation, queuing, and inventory modeling. Unlike previous
studies, we listed breakeven analysis as a possible topic and
found that it was covered in 67% of respondent courses.
Overlap with statistics occurred with a little more than half
of the MS courses incorporating regression and time series
forecasting.
Anticipating the prevalence of LP, we asked respondents
about treatment of applications of LP modeling using standard textbook nomenclature (Figure 3). Traditional product
mix, blending, and network models were in the top tier. Production and inventory planning across multiple time periods
also had strong visibility. Financial applications and data envelopment analysis, a recent addition for MS textbooks, were
significantly less popular.
When questioned about the use of computer software,
a majority (87%) of the respondents indicated that use of
Excel spreadsheets was required. For the remainder, the
primary software being used was QM for Windows (ver. 3.2,
Prentice Hall, Inc., Upper Saddle River, NJ). For spreadsheet
users, emphasis was on built-in Excel tools, particularly
Solver (Figure 4). Use of commercial add-ins for decision
analysis and simulation was also correlated with frequency
of topic coverage. There were a total of 10 different
textbooks used with only two of them being adopted at six
or more schools: An Introduction to Management Science
(13th ed.; Anderson, Sweeney, Williams, Camm, & Martin,
2011) and Quantitative Analysis for Management (10th ed.;
Render, Stair, & Hanna, 2009).
DISCUSSION AND LIMITATIONS
Our findings indicate that top-ranked business schools generally require substantial course work with a strong quantitative
emphasis. However, the role of MS in developing quantita-
FIGURE 4
online).
Usage of Excel tools and add-ins (color figure available
tive skills in business students varies considerably among
these programs. When compared to earlier studies, we did
not discover any concrete evidence that the 2003 reinstatement of MS in AACSB standards and/or the embracing of
analytics by industry have generated a resurgence of MS in
undergraduate business curricula. We acknowledge that it is
possible (but difficult to determine) that these may have influenced some schools to retain MS courses and/or content
in their programs.
Our survey on undergraduate MS course content showed
that linear optimization and decision analysis continue to
maintain a solid presence but otherwise there is significant
variety in topic coverage. Historically discussion about which
topics should be included in an introductory MS course
has centered around MBA curricula. Borsting, Cook, King,
Rardin, and Tuggle (1988) proposed two MBA course designs which included linear programming, simulation (of
waiting lines), and either inventory theory or decision theory plus forecasting. In a response to this proposal, Samson
(1988) suggested minimum and maximum percentages for
a broader list of course topics, making an argument in favor of more breadth than depth in coverage. He gave linear
programming and decision theory ranges of 20% to 50% and
dynamic programming and simulation ranges of 10% to 30%.
All other topics were assigned minimums of 0% indicating
that they were optional.
Gallagher (1991) surveyed executive MBA programs and
found six areas that were cited by a majority of respondents
(in order): linear programming, decision analysis, inventory,
simulation, project management, and queuing theory. He also
found a strong tendency to include inventory theory and
project management in the MS course when OM was not required. In a survey of 150 undergraduate business programs,
Gunawardane (1991) reported that the four topics most frequently taught were (in order) linear programming, decision
theory, simulation, and queuing theory. As spreadsheets became the primary teaching technology, Winston (1996) as
well as Carraway and Clyman (1997) described MBA courses
with modules on mathematical programming, decision
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MANAGEMENT SCIENCE IN BUSINESS SCHOOL CURRICULA
theory, and Monte Carlo simulation. Other approaches to
MS course design have been based on surveys comparing
topics taught in MBA programs to importance of techniques
as used by practitioners in industry (e.g., Chen, 1981; Lane,
Mansour, & Harpell, 1993). More recently, Albritton and
McMullen (2006) proposed using forecasting topics to integrate statistics and MS and Noonan (2007) advocated a
hybrid course that presents data analysis and statistics in
support of decision making via traditional MS techniques.
The extensive literature on MS education, dating back to
the 1950s, indicates that there has never been a clear consensus on MS curricula or required MS course topics (e.g.,
Burford & Williams, 1972). In addition, reviews of the proposed MBA courses in Borsting et al. (1988) criticized the assumption of prerequisite knowledge of probability and statistics and skills in mathematical reasoning. At that time, there
was an expectation that the MS course would be part of a
triad consisting of statistics, MS, and OM due to the highly
structured nature of AACSB standards. We saw evidence that,
while some (28%) of the top-ranked undergraduate programs
still follow the original sequence, a majority have integrated
MS into their OM courses while maintaining a separate statistics requirement. This indicates that MS is likely still seen
as essentially a pre- or corequisite for OM and may not be
getting recognition for its applicability across the other functional areas of business.
IMPLICATIONS FOR THE FUTURE
Our review of MS course status provides strong evidence
that the identity problems associated with MS as a profession (Sodhi & Tang, 2008) continue to affect its stance in
undergraduate business curricula. In those programs where
MS is highly visible, it is generally recognized for providing
students with a strong foundation in Excel-based modeling.
Upstream teaching faculty, particularly in the finance and
accounting disciplines, has come to rely on prior training
of spreadsheet-modeling skills. These programs are in the
best position to take advantage of the current buzz around
business analytics as a means for corporations to develop
competitive gains.
The most frequently cited definition of analytics, due to
Davenport and Harris (2007), is “the extensive use of data,
statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions
and actions” (p. 7). They went on to identify four categories
of business analysts based on roles and job responsibilities:
champions, professionals, semiprofessional, and amateurs. A
report from the McKinsey Global Institute (Manyika et al.,
2011) cited a shortage of people with skills for analyzing and
decision making with big data as a major obstacle for organizational innovation, productivity, and growth. And lack of
knowledge of how to use analytics to improve business performance was identified as one of the top two challenges in a
115
survey of executive managers by the MIT Sloan Management
Review and the IBM Institute for Business Value (Lavalle,
Hopkins, Lesser, Shocklley, & Kruschwitz, 2010).
INFORMS, with strong support from its members (Liberatore & Luo, 2011), has recently taken several steps aimed
at becoming the primary source of analytical professionals who create advanced models and algorithms: publication of the Analytics magazine, chartering of an analytics
section, renaming the practice conference, and development
of a certification for analytics professionals. However, this
group of analysts is predicted to represent only 5–10% of a
company’s analytic talent. In contrast, analytical amateurs,
described as knowledgeable consumers of analytics, are expected to comprise 70–80% of an organization’s analytical
workforce. Another 15–20% of analysts are projected to be
semi-professionals (Harris, Craig, & Egan, 2010).
Business schools have an opportunity to address the need
for these analytical semi-professionals and amateurs: employees who will be responsible for collecting and organizing data, comprehending analytical solutions, incorporating analytical results in specific business domains such as
marketing, finance, and operations, and generating insights
for enhanced organizational decision-making (Liberatore &
Luo, 2010). OR/MS Today (List, 2012) recently reported that
there was a 75% increase in the number of online ads for
jobs requiring data analysis skills between 2010 and 2012,
with management and market research analysts representing two of the three occupations most frequently needing
these skills. Discussion of the future position of MS in undergraduate business school curricula should consider how
to capitalize on this opportunity and create a leadership role
for MS in producing graduates proficient in the skills needed
to support industry adoption of analytics.
NOTE
1. Our college of business has consistently held a position
in the top 5% of undergraduate business schools ranked
by Bloomberg Businessweek.
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