William J. Wellington

A Survey of Simulation Game Users, Former-Users, and Never-Users

An e-mail survey of 14,497 business faculty members across all disciplines at American Association of Collegiate Schools of Business member schools was undertaken to determine current business simulation game usage and thoughts about business simulation games. Issues such as how games are first adopted, objectives for game use, achievement of course objectives, where game users look for information on business games, courses taught by game users, how and why games in use are changed or dropped, and why some faculty members do not use simulation games were addressed. Across 1,085 respondents to this survey, 30.6% were current business game users, 17.1% were former game users, and 52.3% were never-users of business games.

Validating business gaming: Business game conformity with PIMS findings

Business games have been in use in university classes in North American for 50 years. A concern over this time has been whether or not participation in such games is a meaningful experience. The merit of business games has been examined by looking at what is taught by games, comparing games to other teaching approaches, and assessing the external and internal validity of games. This article examines another approach to assessing business games. The performance outcomes of more than 2,000 students operating 717 simulation companies in 154 industries has been examined to determine if these outcomes conform to real-world business firm outcomes as reported in the ongoing PIMS (Profit Impact of Marketing Strategies) project. The findings from this research suggest once again that business simulation games are a valid teaching tool.

Team Cohesion, Player Attitude, and Performance Expectations in Simulation

The present study examines the relationship of team cohesion, participant attitudes, and performance expectations to actual performance results in a simulation competition. These measures were not only taken at the beginning and end of the competition but also during each decision-making period. The rigorously controlled experiment involving 389 students found a strong relationship between beginning team cohesion and performance expectations and final game performance, but little relationship between beginning participant attitudes and performance. Further, whereas participant attitudes and performance expectations changed over time in relation to game performance, team cohesion did not.

An Empirical Investigation into the Nature of the Learning Process in a Computer-Based Simulation Game

Past research investigating participant adaptability to game parameters in computer-based, business simulations has focused primarily on the nature of the decisions made (e.g., actual price set) in order to determine the validity of this experiential approach to management education. The present study moves back one step in the decision-making process and examines the cognitive nature of the decisions on which the behavioral responses were based (e.g., perceived importance of price to game success). A study of fourteen cognitive and fourteen behavioral measures obtained from 130 simulation participants who were randomly assigned to two experimentally manipulated environments in a 10-period game was undertaken. The results show that between-environment differences were obtained and that the outcome of the simulation learning process showed clear evidence of behavioral learning among the participants and some evidence of cognitive learning.

Measuring the Impact of a Marketing Simulation Game

Background. The evidence from past research suggests that business simulation games (BSGs) do offer a meaningful educational experience. One characteristic lacking across past research studies is the trait of indecisiveness. Aim. This study sought to explore whether business students would self-report a change in their perceptions of their indecisiveness after participating in a business simulation games (BSG). In addition, whether higher performance simulation decision makers would self-report being less indecisive (i.e. able to make decisions in a timely manner) than lower performance simulation decision makers. Method. Using a pre-test and post-test design with a comparison to an untreated control group, the change in 386 business students’ perceptions of their indecisiveness was assessed using a self-reporting questionnaire. Results. The findings showed a statistically significant reduction in the level of perceived indecisiveness as a result of the simulation experience. The higher performance students reported being less indecisive than lower performance students while both higher performance and lower performance students reported a reduction in perceived indecisiveness. The level of self-reported perceived indecisiveness amongst a control group of 137 business students indicated no significant change. Conclusion. If the combination of practice and positive reinforcement increases the comfort level (reduce feelings of risk and threat) of decision makers then perceived indecisiveness should decrease as a result of simulation participation, which may generalize across situations demanding decisions.

Using Roadside Billboard Posters to Increase Admission Rates to Problem Gambling Services Reflections on Failure

Based on the stimulus–response model of advertising, this study sought to increase admission rates to a local problem gambling service (PGS) in Windsor, Ontario, Canada, by adding a series of locally based 10 foot by 20 foot roadside billboard posters to PGS’s existing communications tools for a 24-week period. Using proof of performance reports, a pre–post survey of new callers to PGS, a website visit counter, and a media awareness survey, the findings showed that at least some individuals were influenced by billboard exposure, but admission rates continued to decline during the billboard campaign period. While one possible explanation for the communications failure was that the whole PGS communications campaign was below the minimal threshold for communications perception, another possible explanation is that the stimulus–response model of advertising used may not have been appropriate for such advertising that targets behavior change. Reflections on using an information-processing model instead of a stimulus–response model, and considerations of a two-step flow of communication, are provided. Recommendations are made regarding matching communications messages to stages of behavior change, use of online promotion, and strategies for future research.