DEGREE OF UNIFORMITY IN ACHIEVEMENT MOTIVATION LEVELS OF TEAM MEMBERS: ITS EFFECT ON TEAM PERFORMANCE IN A SIMULATION GAME New Horizons in Simulation Games and Experiential Learning, Volume 4, 1977 118 DEGREE OF UNIFORMITY IN ACHIEVEMENT MOTIVATION LEVELS OF TEAM MEMBERS: ITS EFFECT ON TEAM PERFORMANCE IN A SIMULATION GAME Richard J. Butler, Rochester Institute of Technology A. Parasuraman, University of Northern Iowa INTRODUCTION Simulation gaming is rapidly gaining entrance into the curricula of several business schools as a novel pedagogical tool. Many academicians have tried, and are trying, to research various aspects of simulation games and the dynamics of the interactions among game participants. One such aspect is “achievement motivation” which measures an individual’s psychological need to achieve success. This paper describes a study that was done to examine the nature of the relationship between the degree of similarity in the achievement motivation levels of individual members in a team and team performance in a simulation game. BACKGROUND A recent study [31 found a strong positive relationship between the average achievement motivation level in a team and the team’s performance in a simulation game. In this study achievement motivation was measured using a standard instrument developed by Hermans [2]. Game performance was measured by a combined ranking based on team ranks on 21 objective performance criteria over seven quarters of game play. Another study [4] which investigated the relationship between achievement motivation and performance focused on the individual game participant as the unit of analysis. Individual performance was measured by an average “peer evaluation” score, based on the evaluations given to the individual by team peers on six traits. This study found no relationship between individual achievement motivation (measured using the same instrument as in the previous study) and performance. Neither of the two studies mentioned above explicitly looked at the composition of each team in terms of the distribution of achievement motivation levels in each team. A team whose members have similar achievement motivation levels might experience group processes and performance which are different from those of another team whose members have varying levels of achievement motivation, even though both teams might have the same average achievement motivation level. Such differences in group composition could lead to different peer evaluation scores for individuals on different teams, even though those individuals might have similar achievement motivation levels. This could very well have contributed to the lack of relationship between achievement motivation and individual performance in the second study reported above. New Horizons in Simulation Games and Experiential Learning, Volume 4, 1977 119 PURPOSE OF THE STUDY The purpose of this study was to explore the relationship between the extent of similarity in the achievement motivation levels among members in a team and team performance. It was expected that differences, if any, in the dynamics of group behavior due to differences in the distribution of achievement motivation levels of team members would be reflected In team performance. This led to the following hypothesis: “There is a significant relationship between the variance in the achievement motivation levels of team members and the performance of teams which have approximately the same average achievement motivation levels.” METHOD The sample for the study consisted of 85 undergraduate students enrolled in a junior-level management course at Indiana University. They were divided into 16 teams (each having either 5 or 6 members) for participating in a management simulation game called INTOP [5], which was a major component of the course. The 29-item achievement motivation instrument developed by Hermans [2] was included as part of a general information questionnaire filled out by all students at the beginning of the course. Teams were formed so as to meet the following basic criteria: (a) the average team achievement motivation scores be approximately the same for all teams; and (b) the standard deviation of achievement motivation scores of members in each team be as different as possible across teams. After the team allocations were made the average team achievement motivation scores varied between 13.74 and 15.04, while the standard deviation of achievement motivation scores varied between 0.48 and 5.14 across teams, as shown in Table 1. Teams were also matched as closely as possible on grade point average, academic major, sex and work experience of team members. The game participants were not made aware of the variation in the standard deviation of achievement motivation scores across teams in order to avoid any biassing effect that the knowledge of this key factor might have on team performance, the dependent variable in the study. Team performance was measured by a combined ranking based on seven objective performance criteria over the final five quarters of game play that were included in the grading scheme for the course. A Spearman rank correlation coefficient (R1) was computed for the relationship between the standard deviation of achievement motivation scores (the lowest standard deviation was given a rank of 1 and the highest a rank of 16) and the team performance rankings. New Horizons in Simulation Games and Experiential Learning, Volume 4, 1977 120 TABLE 1 Team Number Average Achievement Motivation score Standard Deviation of Achievement Motivation Scores 1 14.74 1.14 2 14.92 3.38 3 14.70 0.77 4 14.34 5.14 5 14.99 2.31 6 14.68 2.57 7 14.97 1.54 8 15.04 1.78 9 15.00 0.89 10 13.85 1.97 11 14.20 0.84 12 14.14 1.19 13 14.08 0.48 14 14.85 4.78 15 13.74 3.49 16 13.87 1.36 The interactive nature of a simulation game like INTOP (or QUANTISIM which was used in the studies mentioned above) makes a team’s rankings dependent not only on the team’s own inputs to the game, but also on the inputs of other teams that compete with it. Thus there could be some pitfalls involved in assuming that an overall team ranking based on “objective” criteria is a true reflection of the quality of a team’s efforts and decision making (for a more detailed discussion of this aspect see [1]). In this study, however, of the seven objective performance criteria that were used, one criterion was completely free of this “interactive bias.” This criterion was a quarterly cash forecast made by each team. The accuracy of this forecast only depended on the team’s understanding of the game and its ability to use past information. New Horizons in Simulation Games and Experiential Learning, Volume 4, 1977 121 It was felt that this criterion would truly reflect, without any bias, at least some aspect of a team’s ability to perform well. Hence a second Spearman rank correlation coefficient (R2) was calculated for the relationship between the standard deviation of achievement motivation scores and team performance ranks for this criterion alone. The sets of team ranks based on which R1 and R2 were computed are displayed in Table 2. TABLE 2 Team Number Std. Dev. of AM Scores Team Rankings Based on: Overall Team Performance Cash Forecast Criterion 1 5 4 2.5* 2 12 8 9.0 3 2 7 11.0 4 16 12 2.5 5 11 6 7.0 6 12 13 14.5 7 8 14 4.0 8 9 1 1.0 9 4 11 12.5 10 10 16 14.5 11 3 5 15.0 12 6 15 8.0 13 1 3 6.0 14 15 9 10.0 15 14 2 5.0 16 7 10 12.5 *Teams that tied for a rank were given average rank. New Horizons in Simulation Games and Experiential Learning, Volume 4, 1977 122 RESULTS The correlation coefficients R1 and R2 turned out to be 0.182 and -0.196 respectively, which were not statistically significant. There seemed to be no significant relationship between the distribution of achievement motivation levels of team members and team performance. Thus there was very little support from these findings for the hypothesis stated earlier. DISCUSSION The above results seem to indicate that the differences in team composition, based on the achievement motivation levels of team members, do not contribute much to the dynamics of team behavior that may have a bearing on team performance. However, the negative sign of R2 seems to be intriguing. It offers some weak indication that teams with one or two members having high achievement motivation levels relative to other members (i.e. teams with high variance in achievement motivation levels) performed better on the “bias free” cash forecast criterion, compared to teams with more uniform achievement motivation levels. This seems plausible in the sense that the few individuals with relatively high achievement motivation levels on certain teams may have taken upon themselves the responsibility to do their best to achieve success for their teams, at least with respect to those aspects of team performance that were not confounded by the activities of competitors. This interpretation, however tentative, should encourage the development of sound procedures to accurately measure the true performance and decision making capabilities of teams (especially in an interactive game situation). Such procedures would enable researchers to conduct meaningful research to understand the relationships between various team characteristics and performance, and to throw additional light on the complexities of group behavior and performance in a simulation game. REFERENCES 1. Butler, R. J. and A. Parasuraman, “Integrating Business Game Performance with the Grading Process,” Proceedings, Midwest AIDS Conference (April 3-5, 1975), pp. 93-97. 2. Hermans, H., “A Questionnaire Measure of Achievement Motivation,” Journal of Applied Psychology, Vol. 54 (1970), pp. 353-363. 3. Rue, L., Slusher, A. and H. P. Sims, “Achievement Motivation and Performance in a Business Simulation Came,” Proceedings, 13th Annual Symposium of the National Gaming Council, Vol. 2 (1974), pp. 488-492. New Horizons in Simulation Games and Experiential Learning, Volume 4, 1977 123 4. Sims, H. P., Butler, R. J. and A. D. Szilagyi, “Personality Correlates of Business Game Performance and Satisfaction,” Proceedings, 13th Annual Symposium of the National Gaming Council, Vol. 2 (1974), pp. 493-498. 5. Thorelli, H. B. and R. L. Graves, International Operations Simulation, (New York: Free Press, 1964) Table of Contents Volume 4, 1977 Double Play for Gaming Effectiveness Adaptive Rule Changes in Computer Simulation Gaming Œ A Means of Pedagogical Reactive Interchange Monte Carlo Simulation in Personnel Management Training Teaching About the Implementation of Job Redesign Using Simulation and Group Discussions An Interactive Simulation of Private Sector Collective Bargaining Leadership Evaluation and training through Behavioral Simulations: Method, Results and Future An assessment of the Effect of Experiential, Simulation and Discussion Pedagologies Used in Laboratory Sections of an Introductory Management Course An Experiential Understanding of the Trust Dimension Using Consulting Cases to teach Business Policy An Experimental Testing of Teaching Methodologies in Marketing Interpersonal Skill Development: The Experiential Training Unit (ETU) and Transfer of Training An Analysis of the Relationship between Personality characteristics and Preferred Styles of Learning Analysis of Effective Communication Skill Development in Graduate Business and Engineering Experiential Education Changing Perceptions of Learning in a Simulated Environment Student Perceptions: Simulation and the Corporate Policy Course Degree of Uniformity in Achievement Motivation Levels of Team Member: Its Effect on Team Performance in a Simulation Game Channel Conflict, Cooperation and Control: an Experiential Learning Exercise Differences in Experiential and Non-Experiential Learners' Reactions to Conflict between Individual and Organizations Behavior The Evolution and Evaluation of a Required, Senior-Level Course in Experiential Business Applications Building Management Skills through Problem Solving A Live-Case Approach to the Business and Society Course Experiential Learning: Toward the Development of a Theoretical Base and the Identification of Variables and the Hypotheses to Guide Research The Role of the Administrator in Experiential Learning and Simulations Some Thoughts on a Theory of the Use of Games and Experiential Exercises Three Applications of the Management of Learning Grid An Analysis of ABSEL: Its Past Achievements and Future Prospects New Horizons in Simulation Research Prediction of Academic Achievement in a Simulation Mode via Personality Constructs Sex Differences in a Bargaining Simulation COM-GAME: A Commodity Trading Game for Use in an Introductory Business Statistics Course A Financial Institution Management Game with Direct Participant Interactions A Non-Computerized Marketing Planning and Strategy Game Delphi in the Classroom: A Demonstration of Forecasting Economic Activity The Potential of Programmable Calculators for Processing Small Business Simulations Can a Small Predominantly Clack University Incorporate the Computer Simulation Gaming Teaching Methodology into it Curriculum Measuring the Effect of an Experiential Exercise Experiential Learning - Analysis of a Partial Success Predicting Participants' Performance and Reactions in an Experiential Learning Setting: An Empirical Investigation A Simplified, Non-Computerized Marketing Channels Game Manufacturers and Retailers: A Negotiation Game for Beginning Management Students Petroleum Management Game A Securities Dealer Simulator SIM ECO SOC with Business Curriculum Modules: A Simulation for Business Ethics and Morals The Picnic: A Perceptual Errors Exercise Salt III; an Experiential Exercise to Highlight the Interpersonal Dynamics Involved in the Negotiation Process Experiential Exercise on Values, Attitudes and Conflict Resolution in Organizational Behavior Kick'N Go: A Product Management and Social Responsibility Dilemma The Use of Self-Assessment Work-shops in a school of Business Administration The Dilemma of Self-Perception