A FURTHER TEST OF THE GROUP FORMATION AND ITS IMPACTS IN A SIMULATED BUSINESS ENVIRONMENT Developments in Business Simulation & Experiential Exercises, Volume 11, 1984 6 A FURTHER TEST OF THE GROUP FORMATION AND ITS IMPACTS IN A SIMULATED BUSINESS ENVIRONMENT Ti Hsu, Rutgers University ABSTRACT This research was a replicate of the study done earlier by Hsu and Eng on group formation in simulated business environment. It was carried out with the introduction of the control groups along with charges of certain group composition variables. The findings are substantially different from the findings uncovered in that earlier study. Behavior arid attitudes displayed by the subjects of these studies are fir apart under different gaming settings creates by the two distinctive methods of group formation. The results of this study clearly suggest that caution should be exercised in the selection of method for group formation. INTRODUCTION Ever since the incorporation of a first generation IBM computer into its business game course designed for a group of business executives by the American Management Association in the mid- 50's [17], the use of computerized business simulation games as a teaching device has ste.3dily gained in popularity. The establishment of the Association for Business Simulation and Experiential Learning (ABSEL), which happens to be the sponsor of this conference, is very good example. The recognization of the use of business simulation games in Lieu of a regular business policy course for accreditation by the American Assembly of Collegiate Schools of Business (AACSB), is another example. Generally speaking, there are two way of playing game, be it business or otherwise. Games can be played by single-person teams or multiple-person teams. In the former case, administration of a game is relatively easy matter, since only individuals are involved. In the case of the latter, where team work is a key factor for a group’s success [3, 4, 10, [18] the situation is more complicated because various factors including group structure, such as homogeneity vs heterogeneity [13]; group composition, such as size [7, 8, 9, 12, 15], sex [11, 14], and r-ice [5]; and group formation, such as self-selection vs assignment [11, 19], may come into play before the actual game starts. Normally, group formation is one of the first, if not the first, factors that canes to the mind of the game administrator luring the planning stage of game few studies on group formation in a simulated gaming environment in general, and in a simulated business gaming environment in particular, have been carried out. The lack of empirical study on the subj3ct p3rhaps is a reflection of whit Sarason 16] charged that “By any large, teachers do not think in terms of how a group can be organized and utilized so that is a group it plays a rote in relation to th9 issues and problem that confront the group.. . " (p. 190) In and early study on group formation by Hsu and Eng [11] which attempted to distinguish members of self-selecting groups from members of instructor-assigned groups on the basis of interpersonal behavior, authors identified six important variables. They included lack of clear goals, change of goals if the game were replayed, equal participation willingness to confront other, apathy towards the decision-making process, and reaction to criticisms. that study suffered shortcomings. First, there was lack of the control groups used in the experiment as fir is the group formation is concerned. Moreover, students were randomly assigned to groups by the game instructor only after they failed to team up on the limit. The purpose of this study was to replicate the work carried out in that study with the introduction of the control groups as well is minor changes on certain group composition variables in the design of the experiment. HYPOTHESES OF THE STUDY Basically, all the hypotheses to be tested and stated below were developed in accordance with the findings of Hsu and Eng's work [11]: 1) Members of self-selecting groups would tend to have a more even membership participation than members of instructor- assigned groups; 2) Members of self-selecting groups would be more willing to confront with each other during the process of the decision- making than theft counterparts from instructor-assigned groups; 3) A high tendency of showing unclear goals may be the case more often with members of self-selecting groups than with members of randomly-assigned groups; 4) Members of self-appointed groups may be more likely to a change of their team’s goals if they were offered the opportunity to do so than member of r randomly assigned groups; 5) Members of instructor-assigned groups are more inclined to exhibit high degree of apathy towards th2 d decision-making process thin their counterparts from 1 f-appointed groups; 6) For those who are actively involved in the decision-making process, it is more likely to see that members of randomly- assigned groups are more receptive of negative comments made by their peers EXPERIMENTIAL DESIGN This study was composed of sixty-three business majors students who enrolled in upper course on business policy during the summer of 1993 at a large state university's evening division. since the majority of the students were working on their undergraduate degrees on a part-time basis, while holding full-time jobs during the day, it my be worth noting the various attributes of the students in class. Altogether, there were 26 male and 37 female students. Their ages ranged from 21 to 52 with a mean of 29 years old. Except for three students who never had full-time jobs, the others had at least six months to as many as 25 years of work experience. The average years of work experience were 8.3. The participants were divided into 14 companies with various group sizes ranging from three to seven. Companies one through seven were organized by the participants themselves whereas companies eight through fourteen were randomly assigned by the game instructor while also taking the following factors into consideration: major and sex. The last seven companies composed Developments in Business Simulation & Experiential Exercises, Volume 11, 1984 7 of thirty-one individuals were used as the control groups, while the first seven companies which ha thirty-two individuals were treated as the experimental groups. Whether a participant belonged to one of the experimental groups or not depended upon the last name of the participant. Those whose last names started 4th A through L went to the experimental groups and those who belonged to the control groups were those whose first letter of the last name started with M through Z. Part of the course requirements was to make 12 quarterly business decisions. All teams started from the same footing in Quarter 9 by taking it over presumably from the prior management. Before the making of the official decision for Quarter 9, each team was offered an opportunity to make a trial decision for Quarter 9, the results of which were not included in the final grade. This allowed them to get a first hand information about the game and to make common mistakes without any penalties enforced on them. The game portion of the class which was the 12 quarterly decisions, was further divided into two parts. The first part was consisted of eight decisions, namely from Quarter 9 through Quarter 16, while the second part had four quarterly decisions. They each accounted for 35% and 25% of the final grade, respectively. While both parts were included in the calculation of the final grade, the first part, that is, the first eight decisions were designed to let students try out different options and get a better feel of the game, so that they would be ready for the final four quarters, which were the basis of the written analysis report and the oral presentation. At the end of the summer session, a questionnaire was handed out to and completed anonymously by each of the students in class without any team collaborations. Information covered in the questionnaire included such things as group dynamics, group characteristics individual attributes and attitudes, etc. VARIABLES INCLUDED IN THE ANALYSIS Upon the review of the completed survey instruments, it was decided that the following 27 variables on group dynamics and students’ attitudes shown in Table 1 be included in the initial analysis. A 7-point scale, 1 to 7, from no evidence to high evidence, for variables 1 through 8 was used. Variables 9 through 24 were also measured by a scale of 1 to 7, referring to a low negative to a high Positive response. The remaining three variables are all categorical in nature. RESULTS Of the 27 variables on group dynamics and personal attitudes summarized in Tab1e 1, 21 were eliminated after a first round of ana1ysis based upon the results of crosstabulations and the correlational matrix. The remaining six variables shown in Table 2 were included in the multiple discriminant analysis as the independent variables. The dependent variable employed for the analysis was the group formation (ORG), a dichotomous variable. The discriminant analysis performed by the computer was the UCLA’ s BMPD7M subprogram on a stepwise fashion. Table 1 Group Dynamics and Attitudinal Variables 1) 2) 3) 4) 5) Existence of team hostility or conflict (CONFL) Low commitment. or lack of goals (GOAL) Apathy towards the decision-making process (APTHY) Lack of innovation (INNO) Lack of risk taking (RISK) 6) 7) 8) 9) 10) 11) 12) 13) 14) 15) 16) 17) 13) 19) 23) 21) 22) 23) 24) 25) 23) 27) Poor team communication (COMM) Lack of trust among team members (TRUST) Misunderstanding of team goals (UNDRST) Equal team mentality (TEAM) Equal participation (EVEN) Equal receptions of all opinions (LISTN) Openness of team members (OPEN) Willingness to confront (CONFR) Reaction to criticism (CRIT) Individual's satisfaction with the team (SATIS) Individual’s ability to guide and lead (LEAD) Individual’s ability to grasp the problems (GRASP) Team acceptance of self (LIKED) Frequency of mediocre decisions made by team (MDEC) Ample time for making reasonable decisions (ENFIM) Frequency of using up class time (USEM) Individual’s disagreement w/final decision(DISAGR) Agreeable with team goals (GOAL) Change of goals if the game were replayed (RPLW) Most frequently used approach in decisions (APPR) Division of labor (RESP) Emergence of dominant figure (DFIG) One of the uses of the discrimination analysis technique is to develop a linear function based upon 1 limited number of variables, so that group members may be classified. One common1y accepted approach is to employ the standard-score coefficients or weights to determine the relative contribution of each variable so the discrimination. It is evident from Table 2 that the variables with the 1argest negative coefficients are for COMM, poor team communication, (-0.95), and ENFIM, sufficient time for making reasonable decisions, (-0.70). The variables of UNDRST, misunderstanding of team goals, (0.64), LIKED, team acceptance of self, (0.61), CONFL, existence of team hostility or conflict, (0.43), and RPLAY, change of goals if the game were rep1ayed, (0.40). It should be noted, however, that only two variables, namely, UNDRST and LIKED, have high enough coefficients for both variables in the positive side, while the coefficients for both variables in the negative side are very high. Hence, it is reasonable to focus on these four variables with the highest absolute coefficients because they seem to contribute the most to the differentiation of the two types of groups. The identification of these four variables are also confirmed by the results of the stepwise procedure except one, whose standard coefficient was the lowest among these four variables. The rejection of the variable, LIKED, is perhaps because of the existence of a relatively moderate correlation between this variable and UNDRST, which is -.31. A significance test of the newly derived discriminant function based on the three variab1es was made to check whether Developments in Business Simulation & Experiential Exercises, Volume 11, 1984 8 significant differences between the two types of groups, self- selecting groups and instructor-assigned groups, could be substantiated. It was found that the test produced a chi-square value of 19.9 with 6 degrees of freedom, which as beyond any usual significance 1eve1, say, 0.05 or 0.01. Hence we may conclude that the new1y deprived discriminant function is highly significant to separating the types of groups. TABLE 2 The Discriminant Function Weights Variab1e Raw-score Weight Standard-score Weight COMM -0.74 -0.95 ENFM -0.44 -0.70 UNDRST 0.56 0.64 LIKED 0.64 0.61 CONFL 0.26 0.43 RPLAY 0.20 0.39 Eigenvalue 0.42699 Once the estimation of the discriminant function is completed, it is then used to calculate the individual score for each observation in order to classify it into a group. The classification results displayed in Table 3 show that of the 34 students in instructor-assigned groups, 25, or 74 percent, were classified correctly. The remaining 9 students, or 26 percent, were regarded as misclassification. With respect to self-selecting groups, 18 out of 27, or 67 percent, were considered correct classification. Overall, the discriminant function based upon the three variables classified 71 percent of the total individuals, i. e., 43 out of 61, into the groups where they actually belonged. TABLE 3 Results of Classification and Jackknife-validation C1assification Validation Actual Correct Incorrect Correct Incorrect Instructor- assigned 74% (25) 26% (9) 74% (25) 26% (9) Self- selecting 67% (18) 33% (9) 63% (17) 37% (10) TOTAL 71% 29% 69% 31% The overall correct classification of 71 percent however, my have been upwardly biased is suggested by Frank, Massy & Morrison [6] because the same data set was used to both estimate the discriminant function and classify group memberships. To overcome this problem, a jackknife validation procedure of the computer program was requested and performed in order to reduce this potential upward bias in the group classification. The validation result indicated that the correct classification was indeed over-predicted by two percentage points. Nevertheless, this validation result of group classification , which was 69%, is still an impressive one compared to a random classification which is 50%. DISCUSSION AND SUMMARY The results of the discriminant analysis identified three variables to be the good discriminators, two having negative coefficients and one with positive coefficients. Generally speaking, a large and positive standard weight would mean, in this case, a strong positive effect on the c1aissification of a case to the instructor-assigned group, and vice versa. Therefore, by combining the three variables with the largest absolute values in weight together, a clear picture begins to surface. That is, members of self-selecting groups tended to have better communication among group members (COMM), and were more likely to believe that there was not sufficient time to reach sound and reasonable decisions (ENFIM). By contrast, members of Instructor-assigned groups are more inclined to misunderstand their teams’ goals (UNDRST). With the findings discussed above, we may conclude that the results of the current study should reject the hypotheses stated earlier in this paper altogether, which were developed on the basis of the findings of an earlier work done by Hsu and Eng. This total rejection was caused by the fact that none of the six important variables found in that research was identified in this study and was, in fact, a big surprise to learn. Therefore, the study suggests that behavior and attitudes displayed by the participants of these studies are rather far apart under different game settings created by two distinctive methods of group formation. The implications of this study thus suggest that cautions should be exercised in the selection of a method for group formation in future game playing situation in general and business game playing situation in particular. While this study answered certain questions, it also created another one. That question is, “What was the real cause of the different attitudes and behavior exhibited in these studies?” Were they simply caused by coincidence? Or were they caused by the two distinctive methods of group formation alone? Or are they caused by the possibly combined force of different group formation methods and changes of the group composition, such is the use of different group sizes, and/or group structure, such factors as majors and sex. At any rate, this newly created question may be worth looking into in the future. REFERENCES [1] Anderson, L. R. and Blanchard, P. N., “Sex Differences in Task and social-emotional Behavior,” Basic and Applied Social Psyco1ogy, Vol. 3, 1992, pp. 109-139. [2] Aries, E. J., “Verbal and Non-verba1 Behavior in Single-sex and Mixed-sex Groups: Are Traditional Sex-role Changing?” Psychological Reports, Vol. 51, l982, pp. 127- 134. [3] Blake, R. P. and !4uton, J. S., “Reactions to Intergroup Competition Under Win-lose Conditions,” Management Science, Vol. 7, 1961, pp. 420-435. [4] Cartwright, D. and Zonder, A., Group Dynamics. (Evanston, Ill. Harper & Row, l968). [5] Davis, L., “Preference for Racial Composition of Groups, Journal of Psycho1ogy, Vol. 109, 1931, pp. 28-301. [6] Frank, R. E., Massy, J. F. and Morrison, D. G., “Bias in Multiple Discriminant analysis,” Journal of Marketing Research, Vol. 11, 19a5, pp. 250-23. [7] Greenberg, C. I., Wang, Yau-de, and Dossett, D. L. “Effect of Work Group Size and Task Size on Observer’s Job Characteristics Rating,” Baisic and Applied Social Psychology, Vol. 3, 1982, pp. 53-66. [8] Hackman, R. and Vidmar, N., “Effects of Size and Task Type on Group Performance and Member Reactions, Vol. 33, Sociometry, pp. 37-54. [9] Hare, A. P., “A Study of Interaction and Consensus in Different Sized Groups,” American Sociological Review, Vol. 17, 1952, pp. 261-267. Developments in Business Simulation & Experiential Exercises, Volume 11, 1984 9 [10] Homans G. C., Social Behaviour: its E1ementary Forms (N. Y. Harcourt Brace Javanovich, 1961). [11] Hsu, T. and Eng, D. J., “Effects of Different Organizational Arramgements on Interpersonal Behavior: A Discriminant approach,” in W. G. Briggs (editor), Northeast AIDS Proceedings, 1983, pp. 1-3. [12] Indik, B. P., “Some Effects on Organizational Size on Member Attitudes and Behavior,” Human Relations, Vol, 18, 1965, pt. 369-384. [13] LaFollete, W. ana Beloh1av, J., “The Effect of Motivational Homogeneity on Risk in Decision-Making,” Journal of Psychology, Vol. 112, 1982, 53-61. [14] Mamola, C., “Women in Mixed Groups: Some Research Findings,” Small Group Behavior, Vol. 10, 1979, pp. 431- 440. [15] Manners, Jr., G. E., “Another Look at Group Size, Group Problem Solving, and Member Consensus,” Academy of Management Journal, Vol. 18, 1975, 715-724. [16] Sarason, S., The Culture of the School and the Problem of Change (New York: Allyn an1 Bacon, 1971). [l7] Schrieber, ia. N., “The Theaory and Application of of the Management Game Approach to Teaching Business Policy,” (Academy of Management Journa1, Vol. 3, 1958, pp. 51- 57. [18] Sherif, M. Group Conflict and Co-operation: Their Social Psychology. (London: Routledge and Kegan Paul, 1967). [19] Van Zelst, R. H., “Sociometrically Selected Work Teams Increase Production,” Personnel Psychology, Autumn, 1952, pp. 175-135. Table of Contents Volume 11, 1984 Simulation Gaming as a Means of Researching Substantive Issues: Another Look A Further Test of the Group Formation and its Impacts in a Simulated Business Environment Impact of Economic Patterns on Student Performance in Computer Business Simulation Games Majority Fallacy Game with Independent Student Simulation and a Case Introducing the Marketing Channel Laboratory A Comparative Evaluation of a Marketing Game A Study of Comparative Effectiveness of Problem-Solving Technologies The Impact of Hierarchical and Egalitarian Organization Structure on Group Decision Making and Attitudes Risk-Free Decision Making The EX-STRA Export Strategy Game Computer Education for Management Students Developing a Computer Game/Job Simulation to Teach Functional Literacy Skills Experiencing Socialization First Hand: An Experiential Exercise in Organizational Socialization Networking Distributive Versus Integrative Approaches to Negotiation: Experiential learning Through a Negotiation Simulation Managerial Education and the Real World: Foudations for Designing Educational Tools Diagnosing Group Climate to Improve Supervisory Effectiveness Student background as a Factor in Simulation Outcomes: The Collective bargaining Example The Use of Pre-Plays in Management Education Experiencing the Process Debrief: A Workshop ABSEL Megatrend Roots MEGATRENDS for Business Simulation and Experiential Learning The Effects and Consequences of the Megatrends on Simulation Gaming: One View Opportunities for the Future: ABSEL's Role Experiential Learning-Based Discussion vs. Lecture Based Discussion: A Comparative Analysis in a Classroom Setting An Evaluation of the Minitab Package in Teaching Business Statistics Concepts A Path Analytic Study of the Effects of Alternative Pedagogies Developing and Using Weighted Application Blanks: An Experiential Exercise Building Airplanes Individual vs. Group Grade: An Exercise in Decision making A Marketing Plan Exercise: Development of Interteam Cooperation Using a Coordinated Experiential Approach Using Student Experience as the Basis for a Consumer Behavior Learning Exercise Student Evaluations of Instructors: What do Students Believe? A Description of the SOFTCAT Computer Assisted Teaching System Comparisons of Practitioners' and Professors' Perceptions of Business Policy Content and Learning Methods The Perceived Relationship Between Pedagogies and Attaining Course Objectives in the Business Policy Course The Use of Simulation in the Teaching of Business Policy A Research Study on Strategic Decisions in a Business Simulation Strategic Management Decision Making Researched Via Simulation Gaming Using Simulation to Investigate Factors in Competitive Bidding Combining Experiential Learning and management Assistance A Model for Teaching Management Skills Putting Experience Back into Experiential Learning: A Demonstration The Teaching and Behavioral Measurement of Managerial/Organizational Competencies: Developing Experiential Exercises and Simulations A Simulation Game Model for Conglomerates QCLAB - A Microcomputer Laboratory in Quality Control CTSS: A Commodity Trading Simulation System Problem Solving: An Exercise on Learning, Coaching, and Operant Conditioning A Demonstration of the Effects of Feedback as a Category of Reinforcement The Assessment of Feedback and Disclosure in Interpersonal Relations: An Experiential Exercise A Study to Determine Whether the Teaching of Basic Grammar Skills in Business Communication Classes Improves Students' Business Letter Writing Corporate Maladies Through the Eyes of the Memo Writer: A Seldom Used Experiential Tool Executive Bailout at Shake & Spear, Inc. The H.E./L&P Merger Intercultural Nonverbal Communications: An Experiential Exercise The Evolving Business Policies Course - Is Management Gaming the Logical Pedagogy? The Use of Decision Simulations in Management Training Programs: Current Perspectives Humanizing the Business of Medicine: The Use of Simulated Patients to Train medical Students Systematic Integration of Simulation Methods in a Graduate Management Curriculum Modeling Non-Price Factors in the Demand Functions of Computerized Business Using Spacial Relationships to Estimate Demand in Business Simulations Two Algorithms For Redistribution Of Stockouts In Computerized Business Simulations Leadership And Strategic Behavior A Comparison Of Two Business Strategy Simulations For Microcomputers Incorporating Decision Support Systems Into Management Simulation Games: A Model And Methodology Using Micro-Computers To Support The Analysis Of Complex Cases: It's As Easy As 1-2-3 Strategic Formulation Consistent With Pims: A Micro-Computer Application