BUSINESS MODELS FOR ONLINE LEARNING: AN EXPLORATORY SURVEY

Karen Vignare
MSU Global Ventures

Christine Geith
MSU Global

Stephen Schiffman
Babson College and Franklin W. Olin College of Engineering

ABSTRACT

Despite the rapid growth in the adoption of online learning, there is a dearth of detailed information on effective business models, business strategies and effective practices on which to build sustainable online education programs. A survey instrument was developed as an initial attempt to define business models and business strategies for online learning. The survey results yielded some interesting data about which online learning financial models seem to have more or less "control" of which business functions. The sample was a convenience one and as such will require further filtering of data. It is also clear that more needs to be done to define business strategies and models and thus provide guidance to this growing segment of higher education.

KEYWORDS

Online Learning, Business Strategies, Business Functions, Business Models for Online Learning

I. Introduction

Despite published research on the business side of online education, there are few in-depth examples of the business strategies, business models and business success factors used in higher education degree-granting institutions for sustaining online learning. There is a lack of information to help guide business decisions, such as best practices or benchmarks, from the different perspectives of different types of higher education organizations.

The number of institutions that need this information is growing. The majority of higher education institutions in the United States are now using some form of distance education. According to the National Center for Education Statistics, 56% of two-year and four-year institutions offered distance education courses in 2000–2001 [1]. Of these, 90% offered Internet courses using asynchronous computer-based instruction. Corroborating these findings and indicating continued growth are the National Sloan Surveys of Online Learning [2, 3, 4] using data from 1000 representative higher education institutions in the United States. Evidence from 2003 shows that 81% of all institutions of higher education offered at least one fully online or blended course and 34% offered a complete online degree program. Sixty-seven percent indicated that online education is a critical long-term strategy for their institution [3].

An exploratory investigation by Schiffman [5] confirms the desire and need for business models, strategies, methods and benchmarks. Schiffman identifies business issues such as revenue distribution and generation, compensation, planning, student services, course and degree regulation, marketing, sources of capital, cost management and product development. Confirmed by Schiffman's project is the need to expand access and generate revenue through online learning.

Discussions in an online Sloan-C workshop on the Business Issues of Online Learning in Spring 2005 demonstrated a strong need for to identify and document critical information for decision-making. Workshop participants affirmed that issues such as marketing expenditures, program design strategies and faculty compensation are strongly impacted by the business context in which programs are developed and delivered. For example, an institution using online learning primarily for non-credit professional development programs has very different objectives, resource constraints, and levels of control over business factors than an institution focused on expanding access to its credit programs.

Applying successful models and strategies from other institutions requires knowledge of the similarities and differences in the organizational contexts. This paper begins the process of identifying the most common contextual variables that have an impact on business issues and using them to create categories l for identifying peer institutions.

II. Review of the Literature

Despite the rapid growth in the adoption of online learning, there is a dearth of detailed information on effective business models, business strategies and effective practices on which to build sustainable online education programs. What has been published on the business side of online education tends to focus on the costs and economic models, the growing for-profit sector, and new organizational approaches such as spin-offs and virtual university consortia. There are very few detailed, descriptive studies focused on the business models, strategies and effective practices of online education in U.S. degree-granting institutions.

Cost and economic models for distance and online education have been examined by noted experts in the field such as Bates [6]; Bishop [7]; Daniels [8]; Finkelstein, Frances, Jewett & Scholz [9]; Rumble [10, 11] and Twigg [12, 13, 14]. The for-profit sector has been described in detail by researchers such as Kelly [15] and Harley, Lawrence, Ouyang and White [16]. Virtual university consortia have been inventoried by the National Alliance of Statewide/Regional Virtual Learning Colleges and described by Johnstone [17, 18].

A few notable compilations of case studies have been published profiling different aspects of distance and online learning. Sloan-C has published a number of detailed case studies in the Sloan-C Series focusing on cost-effectiveness and other business aspects of institutions [19, 20, 21]. Carchidi [21] analyzed organizational forms of virtual delivery in postsecondary institutions and included five descriptive case studies. Daniels [8] profiled the world's mega universities. Jewett [23] and Young [24] published a series of cost-benefit case studies that included some aspects of the distance learning business models of eight different U.S. institutions. Witherspoon [25] described the purposes and practices of twenty-two early adopters of distance and online learning in the U.S. including some aspects of their business models.

Most recently, a study by Curran [26] used example case studies to describe the business strategies of U.S. and European institutions engaged in online learning. Findings identified 13 strategies for increasing access, enhancing quality and containing costs. Curran concluded that "Striking an appropriate balance between pedagogic strategies, scale of provision and resource expenditures remains an inherent challenge for the future development of e-learning" [26]. Though Curran's study is a useful identification of different overall business strategies, it does not include detailed information, such as success factors, for decision making or practitioner implementation.

This review of the literature indicates a noticeable lack of practical, published information on the business models used in higher education institutions, particularly non-profits, to run the business side of online learning. There is a need to identify and share information on what works to accelerate success and adoption of successful models.

III. Methodology

The authors created a set of questions based on research studies [5, 26]. The test questions were beta tested with a group of Directors and Deans who were recognized as running highly successful online learning departments. After the beta test a 21-item questionnaire was finalized. The final questionnaire collected demographic information on each responding university/college/organization and the respondents' views of their own business practices. The demographic data collected information about the type of college and specific information about its current online learning business. Besides the demographic questions, there was a mix of open-ended and Likert-type questions. The other question types were inclusive multiple choice questions.

IV. Findings

The findings were useful for gaining further insight into how organizations integrated business strategies into the procedures for online learning. The findings are clearly of an exploratory nature. The results of the survey with this sample seem to indicate that financial models drive many business strategies.

A. Overall Demographics

The survey was distributed via email on the Sloan-C listserv, the NUTN listserv, UCEA listserv, and the Sloan online research study. The convenience sample yielded a total of 128 responses from 110 unique institutions. Since this was an initial exploratory survey and it used a convenience sample, it is not clear whether the population is representative of the colleges who offer online learning. Several demographic factors do seem to differ somewhat from the latest annual Sloan-C survey on online learning and from other benchmark data sources.

The convenience sample which responded was more heavily skewed to those offering graduate and baccalaureate degrees than would normally be found in the US higher education market.

Table 1. Reported and Actual College Classifications
*Source: http://www.carnegiefoundation.org/Classification/CIHE2000/Tables.htm

Based on those who offer online learning as reported by the annual Sloan-C survey on online learning, the data is also skewed toward the upper degree offerings. In the 2004 Sloan survey, Associates colleges offered the most online learning, followed by masters, doctoral, specialty and finally baccalaureate [2]. The latest data showed growth in baccalaureate degrees but remains skewed to graduate and associate providers offering more online courses then other institutions [1]. The data did fall in the middle of those reporting whether they where public or private institutions as benchmarked against the Department of Education statistics and the Sloan-C survey. In the convenience sample, 70% reported being public while the Department of Education reports 60% of all institutions are public. The Sloan-C survey data shows public institutions offering 83% of all online learning. The private institutions numbers are reflected as follows: 30% in the convenience sample, 40% of all Department of Education institutions, and 17% of those offering online learning.

The following demographic information was provided by the respondents. The respondents reported having the following number of enrollments: 15% had less than 500 enrollments; 14% had between 500 to 1000 enrollments; 30% had between 1001 to 5000 enrollments, 13% had between 5001 and 10000 enrollments; 26% had over 10001 enrollments and; 3% choose not to answer. Most of the respondents offered only for credit courses and programs. Another survey question asked how many of the enrollments were from traditional students. The answers varied greatly. Forty-four percent indicated that traditional students accounted for less than 25% of the enrollments; 19% indicated traditional students accounted for between 26% to 50% of all online enrollments; 11% indicated that 50% to 75% of all enrollments came from traditional students and; and 23% indicated that more than 76% of the enrollments came from traditional students.

Over 50% indicated that their online enrollments accounted for less than 10% of the total enrollments from the institution. The majority, nearly 75% of all respondents, indicated that the total number of programs, certificates or certifications numbered less than 25. The most common types of programs were masters followed closely by bachelors, then associates and doctoral. Respondents were asked in a Likert-scaled question what their reasons were for offering online learning. The top reasons for offering online learning were enhancing the value of the university brand and contributing to extension efforts followed by returning a surplus to the university. If only the ‘very important' answers are included then contributing to extension was the top reason followed by returning a surplus to the university. Respondents indicated that contributing to speed of graduation and on-campus student retention were only of 'minor' or 'not important' reasons for offering online learning.

Respondents were also asked how online courses were designed. The majority of responses indicated that generally faculty or staff by themselves designed courses. Some institutions indicated that faculty developed courses so that others could deliver them and some answered that teams of faculty and staff developed courses so that teams could deliver them. The differentiation could be described as the first choice continues the traditional practice of individual faculty creating and delivering courses; the next two choices are closer to a master faculty developing for others to deliver; in the final choice, faculty work with staff to develop courses that others can deliver. The last model is more like the approach typical of corporate training.

All the data were cross-tabulated to look for patterns and relationships. No clear relationships emerged from grouping institutions by their demographic likenesses. On the other hand, grouping the institutions by the business model as described below provided some interesting patterns of what functions were controlled by various business models.

B. Identification of a Business Model

Using terminology that was tested with several colleagues, the researchers decided to ask survey respondents the following question:

Table 2. Types of Business Models

As can be seen three business models were most predominant in the list: (1) Independent self-funded, college, (2) department or school within the university which is self-funded or college, and (3) department or school within the university which is overhead funded. What is also clear is that many respondents felt none of the choices correctly identified the business model. Most of the respondents in the ‘other' category explained that their institutions were a mixture of the business models. Clearly, more work needs to be done on identifying the best terminology for these business models. However, the groupings did provide a way to look for patterns in what units control which business functions.

The following charts use the three predominant types of business models and break-out business functions by the focus areas of student services, business decision making, and curriculum planning. Student services functions are plotted against the three models. The direct control of student services showed the least amount of variation in the respondents' answers. It seems as though most colleges have agreed—regardless of how they initiated the business of online learning—that student services, technical support and control for quality needs to controlled by the unit offering online learning. However, it is less clear who should be responsible for retention. It is worth noting those respondents from the over-head funded unit overall felt they were almost 25% less likely to have control over this business function than respondents from other business models. The retention for non-credit is almost a misleading question, since most respondents indicated that very little of their offerings were non-credit.

Chart 1. Student Services by Model

The business decision making plotted against the model also showed more contrasts than student services. For the most part, the college or independent units which are self-funded had very similar answers except for their control of partnerships and removal of products from the market. The college overhead-funded model differed especially in regard to controls. None of the data indicates, however, that one type of unit is more successful than another. It is clear that the college overhead-funded units must work with more internal partners to make these decisions. That implies that processes must be worked out over time to address how the primary college/university will respond to these functions. It is entirely true that the lack of control over some business decisions could result in less efficient processes and be a disadvantage as well to colleges with overhead-funded business models.

Chart 2. Business Decisions by Model

In the third chart, where curriculum planning is plotted against the model type, the largest variations seem to exist amongst the models. The overhead-funded unit has very little control of faculty selection and curriculum creation. If the unit can not control or impact the creation of curriculum, it can not respond to business opportunities in online learning. There also seems to be some disconnect among the respondent answers. The college overhead-funded unit indicated it could impact the quality learning experience, yet one of the major tenets of the student learning experience is faculty. If the college overhead-funded unit can not hire faculty, then it seems that the quality learning experience could be impacted. It is possible that the college has other mechanisms in place to make sure faculty teaching online will provide a quality learning experience.

Chart 3. Curriculum Issues by Model

C. Open-text Discussion of Business Challenges

Respondents were asked what the biggest business challenges they faced were. The responses, as might be expected, varied widely. Of the 128 total responses, 100 took the time to add an open text business challenge. Coding and counting of the responses indicated some of the biggest challenges were faculty, staffing, investment, constantly changing environments, managing quality, and support for students and faculty. Many faulted faculty for slowing down how quickly the university could offer courses online. Others indicated that faculty wanted more quality control but did not understand how online learning works. The responses clearly evoked a sense that these units were not in control of the academic experience and shared many responsibilities which make delivery of a quality learning experience difficult.

Other issues reported by the respondents included paying for development and developing the right business model and marketing analysis for return on investment. Many indicated the central university did not have a process for return on investment and estimating marketability of courses or degrees. A few respondents indicated that the university had trouble with any investment in courses since they did not believe new on-campus courses required investment. The lack of appropriate marketing knowledge was also voiced as a business challenge. The challenging issues also included quality control issues like which students to admit, how to support students with what types of services (tutoring for instance) and maintaining a high level of retention. A few responses stated that it was difficult to get central administration support for growth and investing in new technologies.

D. Limitations

While some conclusions can be drawn from the survey, the data set used is limited in its scope. The survey provides much preliminary data to further investigate the complex issues involved. It will be worth refining the definitions of business models and the strategies controlled or influenced by the online learning unit. That information will allow for further hypothesis testing on whether there are required business strategies for an online learning unit to be successful.

The research will also begin to define terminology for those who manage online learning units at their own institutions. Furthermore, it is very important to continue to share this research for the benefit of the entire ALN community.

V. Discussion of Findings

As an exploratory study, the survey has added a great deal of knowledge about business model research for online learning. There appears to be some connection to the Miller and Schiffman thesis (in this issue) that colleges started their online learning operations to meet either access or quality needs of the institution. Given the starting point and the reality that most online learning colleges started from an access point then it becomes clearer as to why enhancing brand value, returning a surplus and contributing to extension are the most important reasons for offering online courses. There appears to be connection to other research discussing the difficulties and lack of guidance in establishing business rules for online learning which differ from the rest of the university offerings [7, 16, 18]. Many respondents indicated frustration with the process for establishing these business rules when they did not control many of the business functions. In other words, respondents felt like they were held responsible for costs and outcomes but they were not in control of critical functions that impact costs and outcomes.

It is clear that more needs to be investigated about the business models and strategies for online learning. The authors held an online workshop hosted by the Sloan Consortium in which many participants discussed many business issues that they had regarded as unique to their own individual institution. The compounding complexities of being in a relatively new field where rules and processes are being established plus the unique characteristics of individual institutions do seem to indicate that much more work needs to be done in this field to see if it is critical to be in control or establish a unified process for all those units involved in delivering online learning. During the seminar, nine additional case studies were shared with participants and are reprinted in this volume. The case studies include colleges that differed in their business models and shared strategies about either business planning, curriculum planning and student services.

It is clear that there is need for further guidance on how to manage business models in online learning.

VI. About the Authors

Karen Vignare currently serves as the Director of MSU Global Ventures at Michigan State University. In that role, Karen is responsible for creating online entrepreneurial approaches for extending both non-credit and credit programs at MSU. Before that, she was the Sr. Research Analyst for the Online Learning Department at the Rochester Institute of Technology. She also served in other roles at RIT in the Online Learning department. Before coming to RIT, Karen was a full-time faculty member at SUNY-Alfred State in the marketing, retail, and computer technology fields. She also served as a vice president and political economist for a Wall Street financial firm. She publishes regularly on various topics in online learning. She has an MBA from the University of Rochester 's William Simon School of Business and a BS from Frostburg State University in political science and economics. She is currently attending doctoral classes at Nova Southeastern University.

Dr. Christine Geith is director of Michigan State University's MSU Global, the university's entrepreneurial business unit that works with academic partners across the campus and worldwide to develop and market online institutes, programs and services. She is responsible for developing strategic frameworks and business models and leading all activities that impact revenue growth. This includes business development, alliances and partnerships, product development, marketing, sales and customer support. Dr. Geith's research interests include costs, benchmarks and business models for online and blended learning. Dr. Geith has over fifteen years of experience in online learning including four years as director of MSU Global Ventures. Prior to joining MSU, Dr. Geith was executive director of e-learning at Rochester Institute of Technology. Dr. Geith holds an M.B.A. from Rochester Institute of Technology and a Ph.D. from the University of Nebraska-Lincoln.

Dr. Stephen Schiffman is currently Associate Professor of Entrepreneurship at both Babson College and the F.W. Olin College of Engineering.  At Babson, Steve was dean of the undergraduate program for 8 years while a new undergraduate business curriculum was developed and launched in the fall of 1996. In 1997, the Pew Charitable Trusts recognized this effort by selecting Babson for a Pew Leadership Award for renewal of undergraduate education. Steve holds a Ph.D. in mathematics from Dartmouth College as well as an M.S. in management from Sloan School, MIT. He has taught at the University of Colorado and Colorado College, and, prior to joining Babson College, he worked at Digital Equipment Corporation.

VII. Acknowledgements

The authors wish to thank Sloan-C for its support and dissemination of this research. The authors also wish to acknowledge Rochester Institute of Technology for allowing the researchers to use its online survey tool. The researchers also wish to acknowledge George Lorenzo for his work on the case studies.

VIII. REferences

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IX. Appendix A