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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
International-Accredited 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
Published online: 17 Jan 2014.
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Copyright Taylor & Francis Group, LLC 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
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 busi-ness school programs has received considerable attention in the MS community over the past two decades. After thriv-ing 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 al-gorithms 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 Madi-son 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 busi-ness students. It also allowed for an increased emphasis on modeling, problem solving, and quantitative reasoning skills that are important for organizational decision-making (Pow-ell, 1995). Other reform efforts included improved pedagogi-cal 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 In-ternational, 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 peti-tion effort (Horner, 2003), was anticipated to provide MS with a second opportunity to demonstrate its value to man-agement education and consequently strengthen MS content in the business core (Grossman, 2003; Sodhi & Tang, 2008). At the same time, advancements in information technol-ogy were driving explosive growth in the field of business an-alytics 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
MANAGEMENT SCIENCE IN BUSINESS SCHOOL CURRICULA 111
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 pre-scriptive 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 busi-ness core at the top 50 schools as ranked in 2011 by
Bloomberg Businessweek(Gloeckler, 2011).1Then we
iden-tified 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 essen-tially become uniform to ensure compliance with standards from the AACSB, the most prestigious business school ac-creditor. 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 interper-sonal skills, political and regulatory factors, and a global perspective (Windsor & Tuggle, 1982). Despite these warn-ings, 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 busi-ness schools flexibility to design curricula appropriate for their individual missions and constituents (Miles, Hazel-dine, & Munilla, 2004). Curriculum requirements were lim-ited to four areas of foundation knowledge (accounting,
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 arti-cles 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; Win-ston, 1996),
• Recommending emphases on end-user modeling (e.g., Leon, Przasnyski, & Seal, 1996; Powell, 1995, 2001),
• Suggesting more integration with functional business ar-eas (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 educa-tional 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 re-quirements 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 oper-ations management (OM) in undergraduate business curric-ula 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 per-centage (40.7%) of 342 AACSB-accredited business schools offered at least one course with MS content at the undergrad-uate 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 researchormanagement science. Courses labeled as quantitative analysis or methods (QA/QM) were counted
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 im-provement 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 orga-nization” (AACSB International, 2011, p. 70).
MS can be broadly defined as the application of advanced analytical principles and methods from mathematics, en-gineering, and science to improve organizational ability to address managerial problems and issues (INFORMS, 2012). The new AACSB standards were welcomed in the MS com-munity 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 fur-ther reinforced by an increasing focus on data analysis tech-nologies (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, un-like 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 inBloomberg 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 gradu-ates sent to top MBA programs (10%). A detailed
descrip-TABLE 1 Distribution of MS Courses
Highest degree No MS course MS course
Masters 72.22% 27.78%
Doctorate 71.88% 28.13%
Total 72.00% 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-to-faculty ratios, average class sizes, percentage of students with internships, and hours spent on schoolwork.
Geographically, the top 50 schools in 2011 were dis-tributed among 22 states with almost a third located in Massachusetts, Pennsylvania, and New York. Thirty of these schools were private institutions. Average full-time under-graduate student enrollment was 1,815 with a 17.5 average student-faculty ratio. A doctorate is the highest degree of-fered 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 (to-tal of 24,832) undergraduate business degrees in 2009–2010. Only 15 schools reported graduating more master’s than un-dergraduate students, underscoring the significance of under-graduate business education.
We reviewed each school’s web site to determine quantita-tive 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 ar-eas 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 quantita-tive 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 statis-tics and OM. Of the 29 business programs with this profile, 10 required two statistics courses in addition to OM. A re-quirement 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
MANAGEMENT SCIENCE IN BUSINESS SCHOOL CURRICULA 113
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 quanti-tative courses.
The diversity of quantitative requirements at these highly ranked schools reinforces the flexibility allowed in applica-tion 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 as-sociation with economics (Becker, 1987; Tabatabai & Gam-ble, 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 indi-cated 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 statis-tics 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 mathe-matical models for aggregate planning, facility location, pro-duction distribution, and inventory management (Lovejoy, 1998). Topics overlapping with both statistics and MS also in-cluded forecasting, quality control, and project management. But approximately a third of OM courses indicated distinct movement away from being technique-oriented with more
attention on supply chain management, process improve-ment, service management (Aksin & DeHoratius, 2010a, 2010b), globalization, applications of information technol-ogy, 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 Quan-titative Analysis, Analytic Decision Modeling Using Spread-sheets, and Mathematics for Management Science. Deci-sion 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 popula-tion of AACSB-accredited undergraduate programs in the United States. We briefly examined curricula at 452 institu-tions 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 pres-ence 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 program-ming (LP) as the most frequently occurring topic in MBA courses as did Gunawardane (1991) for undergraduate pro-grams. 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).
FIGURE 3 Coverage of LP modeling applications (color figure available
online).
was second, also matching rankings in Gunawardane and Gallagher However, our results showed a general shift to-ward more project management, including Program Evalua-tion and Review Technique/Critical Path Method, than sim-ulation, 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 stan-dard textbook nomenclature (Figure 3). Traditional product mix, blending, and network models were in the top tier. Pro-duction and inventory planning across multiple time periods also had strong visibility. Financial applications and data en-velopment 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) andQuantitative Analysis for Management(10th ed.; Render, Stair, & Hanna, 2009).
DISCUSSION AND LIMITATIONS
Our findings indicate that top-ranked business schools gener-ally require substantial course work with a strong quantitative emphasis. However, the role of MS in developing
quantita-FIGURE 4 Usage of Excel tools and add-ins (color figure available
online).
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 reinstate-ment 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 in-fluenced 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 de-signs which included linear programming, simulation (of waiting lines), and either inventory theory or decision the-ory 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 fa-vor 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 re-quired. In a survey of 150 undergraduate business programs, Gunawardane (1991) reported that the four topics most fre-quently taught were (in order) linear programming, decision theory, simulation, and queuing theory. As spreadsheets be-came the primary teaching technology, Winston (1996) as well as Carraway and Clyman (1997) described MBA courses with modules on mathematical programming, decision
MANAGEMENT SCIENCE IN BUSINESS SCHOOL CURRICULA 115
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 in-tegrate 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 con-sensus on MS curricula or required MS course topics (e.g., Burford & Williams, 1972). In addition, reviews of the pro-posed MBA courses in Borsting et al. (1988) criticized the as-sumption of prerequisite knowledge of probability and statis-tics 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 statis-tics 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 func-tional 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 profes-sion (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 predic-tive 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 orga-nizational innovation, productivity, and growth. And lack of knowledge of how to use analytics to improve business per-formance was identified as one of the top two challenges in a
survey of executive managers by theMIT Sloan Management Reviewand the IBM Institute for Business Value (Lavalle, Hopkins, Lesser, Shocklley, & Kruschwitz, 2010).
INFORMS, with strong support from its members (Lib-eratore & Luo, 2011), has recently taken several steps aimed at becoming the primary source of analytical profession-als who create advanced models and algorithms: publica-tion 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 ex-pected 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: em-ployees who will be responsible for collecting and orga-nizing data, comprehending analytical solutions, incorporat-ing 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 represent-ing two of the three occupations most frequently needrepresent-ing these skills. Discussion of the future position of MS in un-dergraduate 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 byBloomberg Businessweek.
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