Business Simulation and Professional Development

Week: 9 1

Topic Overview – Impediments To The Diffusion Of The New Technology

Learning Outcome:

LO.1 explain the theory and practice of businesses (COI, CID, SID)

LO.2 describe a range of current problems and changes that organizations face in being successful (COI,

CID, IC, SID).

LO.5 students will discuss good practice for organization success (COI, CID, SID).

LO.6 undertake a critical audit of skills and capabilities for a professional career and identify areas

required for improvement (COI, CID, EID).

1.Introduction

Despite the inherent advantages associated with the new technology, there are a number of impediments

that can thwart the successful promotion of these simulation products. Most of these problems are

cultural. In fact, cultural resistance has been cited as the second greatest obstacle to e-learning

(Summers, 2004). Some cultural obstacles to the new technology products are presented next.

2. Cultural Obstacles to the new technology products

2.1 The new products place more responsibility on the learner.

Learners must make time for learning and apply themselves without the benefit of a class, mandatory

homework, or other motivational pressures. Integrating learning into work might overcome this barrier,

with work pressures acting as an incentive for greater training. How and whether learners make this

cultural adjustment is essential. Many companies evaluate training through employee participation rates

and trainee opinion questionnaires. The survey from Learning & Training Innovations asked e-learning

users how they measured e-learning success( Summers, 2004). The top two answers were employee

feedback and tracking the number of employees who used the online offerings.

2.2 Self-motivated learning on demand threatens human resources departments.

It integrates learning into work, so it is not a separate event delivered and controlled by the company’s

trainers. It decentralizes training and empowers employees to determine the when, where, and pace of

learning. This empowerment is particularly important to knowledge workers because their career depends

on their continuing their educations. Knowledge workers might even seek training from outside the

company such as through programs offered by their professional associations (Summers, 2004).

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2.3 People learn differently.

Some people prefer mentored instruction while others prefer group problem-solving exercises. Still others

prefer self-paced learning. Simulation products currently do not address this diversity of learning styles

(Summers, 2004).

2.4 Delivery Costs.

Although the delivery costs are variable costs and are low, the development costs, which are fixed costs,

are high. Traditional e-learning requires an average of 220 hours of development work for each hour of

content (Brandon-Hall, 2002). In contrast, simulations delivered via e-learning require 750 to 1,300 hours

of work for each hour of simulation (Brandon-Hall, 2002). Some simulations require even more labor. The

Strategic Management Group claims to invest from 1,200 to 1,500 hours for each hour of simulation

(Aldrich, 2001).

2.5 Simulations are Risky.

Like many information products, simulations are risky because customers cannot try them without buying

them. Although demonstration copies or “product tours” partially relieve this problem, customers still face

considerable risk, and this risk can retard growth until lead users prove the new technology’s value.

Because of these questions and the benefits of seminars, some companies are hedging their bets by

providing simulation-based seminars. Once the seminar has been completed, employees are allowed to

have continuing access to the simulation and all its supplementary materials through an annual

subscription. This combination of electronic and face-to-face learning has spawned a new buzzword:

blended learning. Interestingly, Faria (1987) reported that simulation exercises were frequently used with

cases, lectures, training films, readings, and group discussions. This suggests that e-learning has

adapted to become like the methods it might replace. Other problems associated with the new technology

products deal with the technology’s delivery and its comparative efficacy:

- Does the Internet provide enough bandwidth to transport the new simulations effectively?

- Is personalized, artificial-intelligence-generated feedback as effective as live, expert feedback?

- Finally and most important, do people learn better or faster with the new simulations than with the

traditional technologies

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3. Creative destruction versus fragmentation

Will the new technology companies come to dominate or even replace the old? If so, this would be a case

of creative destruction, a concept proposed by Schumpeter (1989). Alternatively, the new technology

companies may simply increase the number and variety of suppliers and products. The outcome depends

on whether the new technology is superior and whether the new technology companies can consolidate

the industry. The new technologies and products have already been discussed, but what about

consolidation? To consider this issue, first consider why the industry is fragmented.

3.1 A fragmented industry

Porter’s (1980) strategic analysis is helpful in this case and yields the following insights into industry

structure and competition. Decreasing entry barriers. Knowledge of traditional computer-based simulation

technology is being diffused, thereby lowering a key entry barrier, which was technological expertise.

Simulation & Gaming has published numerous articles by experts on simulation design (Gold, 1992; Gold

& Pray, 1984, 1989; Mergen & Pray, 1992; Teach, 1990; Thavikulwat, 1991, 1992). System dynamics is a

course of study at many universities, and several companies provide authoring tools for system dynamics

simulations. Some computer-based training authoring tools enable users to create simple decision-tree

simulations. Finally, spreadsheet software lowers simulation development costs by providing an interface

and a programming environment. Faria (1987, 1998) provided additional evidence that the industry’s

entry barriers are decreasing due to:

-High selling costs. In the corporate market, most suppliers gain sales from consultative selling, perhaps

because estimating the return on training investments is notoriously difficult. This inhibits economies of

scale. High delivery costs. Many simulations require a seminar presentation. Seminars require expensive

facilitators, which prevents scale economies.

-Low product differentiation. Although every simulation is different, the differences are often

inconsequential. All industry simulations have somewhat different interfaces, market structures, and

parameter values; nonetheless, they all prompt learners to make the same type of marketing, finance,

and production decisions. To the learner, they are largely the same, and this creates several difficulties

for suppliers. Without a differential product advantage, a supplier has difficulty dominating the licensing

market. This is unfortunate because licensing simulations to consultants overcomes the high cost of sales

and seminars. Consultants would pay the costs of both, thereby enabling simulation suppliers to gain

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scale economies. Insufficient product differentiation also minimizes repeat sales. Suppliers cannot offer

new, improved versions of their products, a standard strategy in the software industry, because product

differentiation is not meaningful. Facing this reality, companies supplying traditional computer-based

simulations increase sales by adapting their simulations to different markets such as retailers,

wholesalers, service companies, and manufacturers (Mergen & Pray, 1992).

-Lack of resources and skills. Many of the suppliers of traditional computer-based simulations were

university professors who sold their simulations through book publishers. Other suppliers were small,

local consultants. Few suppliers sought professional management with experience in growing a

company.

-Entry barriers. The new technology raises entry barriers in several ways. Agent based technology,

artificial-intelligence-generated feedback, and high-quality graphics all increase entry barriers. Software

libraries that enable quick, inexpensive customization further raises entry barriers, as do libraries of

supplementary materials. In fact, smaller suppliers are concerned that technology is overtaking their

ability to maintain the interfaces and game features learners desire (Fritszche, Biggs, Cotter, Jensen, &

Wolfe, 1998). The need for supplementary materials also increases switching costs, especially if

customers can organize reference materials into a personal reference. For example, customers could

save search queries and search results, highlight text, and create their own hyperlinks among the various

references. In addition to raising entry barriers, high switching costs have another benefit. When

simulations and supplementary materials are priced as annual subscriptions, high switching costs provide

suppliers with a reliable revenue stream.

-Selling costs. Competition is lowering prices, but the real issue affecting price is the underlying business

model used by the new technology companies.

-Distribution costs. Removing seminars from the training method reduces a major barrier to scale

economies. Moreover, high entry barriers and product differentiation can promote licensing, thereby

shifting the distribution costs away from suppliers.

-Resources and skills. The corporate market should grow into a billion-dollar industry and much more if

its e-learning segment grows robustly. This growth is attracting professional management and venture

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capital. However, it is a double-edged sword. It is also attracting large suppliers from a variety of

industries, such as e-learning, training, and consulting.

4. New scientific research opportunities

Business simulations support research into learning and various aspects of man agement, including

decision support, strategy making, group behavior, organizational learning and change, and leadership

(Keys & Wolfe, 1990). The new simulation technologies and the next new technologies create additional

opportunities. These technologies facilitate new research techniques. Scientists can analyze decision

making with theory and measures from applied mathematics, computer science, and artificial intelligence.

These new techniques can direct simulation-based research into new fields. For example, scientists can

study decision-making heuristics (Kahneman, Slovic, & Tversky, 1982; Plous, 1993) and satisficing

(Simon, 1994, 1997). By applying the new technology to industry simulations, scientists can study how

management affects industrial organization, how competition diffuses knowledge over firms, and how

flexibility affects performance.

Week: 9 6

References

Aldrich, C. (2001, September 1). The state of simulations: Soft-skill simulations emerge as a powerful new

form of e-learning. OnlineLearning.

Brandon-Hall. (2002, March). Executive summary of E-learning simulations: Tools and services for creating

software, business, and technical skills simulations.

Gold, S. C. (1992). Modeling short-run cost and production functions in computerized business simulations.

Simulation & Gaming, 23, 417-430.

Gold, S. C., & Pray, T. F. (1984). Modeling market- and firm-level demand functions in computerized

business simulations. Simulation & Games, 15, 346-363.

Gold, S. C., & Pray, T. F. (1989). The production frontier: Modeling production in computerized business

simulations. Simulation & Games, 20, 300-318.

Faria, A. J. (1987). A survey of the use of business games in academia and business. Simulation & Games,

18, 207-224.

Faria, A. J. (1998). Business simulation games: Current usage levels—A ten year update. Simulation &

Gaming, 29, 295-308.

Fritzsche, D. J., Biggs, W. D., Cotter, R. V., Jensen, R. L., & Wolfe, J. (1998). What is the future of business

gaming? Developments in Business Simulation & Experiential Learning, 25, 263.

Kahneman, D., Slovic, P., & Tversky, A. (1982). Judgment under uncertainty: Heuristics and biases. New

York: Cambridge University Press.

Keys, J. B., & Wolfe, J. A. (1990). The role of management games and simulations in education and

research. Journal of Management, 16, 307-336.

Plous, S. (1993). The psychology of judgment and decision making. New York: McGraw-Hill.

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Porter, M. E. (1980). Competitive strategy. New York: Free Press.

Schumpeter, J. A. (1989). The theory of economic development (R. Opie, Trans.). New Brunswick, NJ:

Translation. (Original work published 1911).

Simon, H. A. (1994). The sciences of the artificial (8th ed.). Cambridge, MA: MIT Press.

Simon, H. A. (1997). Administrative behavior (4th ed.). New York: Free Press.

Summers, G. J. (2004). Today’s business simulation industry. Simulation & Gaming, 35(2), 208-241.

Thavikulwat, P. (1991). Modeling the human component in computer-based business simulations. Simulation

& Gaming, 22, 350-359.

Thavikulwat, P. (1992). Product quality in computerized business simulations. Simulation & Gaming, 23,

431-441.

Teach, R. D. (1990). Demand equations for business simulations with market segments. Simulation &

Gaming, 21, 423-442.