ASSOCIATIONS BETWEEN INDIVIDUAL COGNITIVE PROGRESSIVE VARIABLES AND BUSINESS GAME PERFORMANCE AND PLAY Experiential Learning Enters the Eighties, Volume 7, 1980 169 ASSOCIATIONS BETWEEN INDIVIDUAL COGNITIVE PROGRESSIVE VARIABLES AND BUSINESS GAME PERFORMANCE AND PLAY Joseph A. Wolfe, University of Tulsa ABSTRACT Business game players’ cognitive structures were studied as they related to environmental perceptions, behaviors, and performance results. An individual’s cognitive structure had a relationship on how the environment was perceived independent of its objective state. Cognitive structure was not associated with rare behavior or game performance INTRODUCTION Business gaming’s cognitive processing elements have continually interested ABSEL’s members and its conferences. Goosen [12] has traced the Association’s earliest research and publishing interests while a review of ABSEL’s most recent 1976-1979 Proceedings issues reveals that approximately 9.3% of their annual content was directly devoted to papers on learning-style models, information acquisition, organization and usage, and certain personality factors would appear to affect participant play and performance. This emphasis is appropriate as (1) experiential learning theory includes a Substantial and pivotal cognitive element [15;21], (2) current learning theory is more process-related than substantive in its approach [13]., and (3) tae typical gaming situation requires the participant to react rationally to a complex, semi-ambiguous internal/external environment. interest in an individual’s cognitive processes, however, has even more widespread importance. Contemporary organization theory states that the firm’s decision makers do not deal with the real or ‘objective” environment but instead that they react to an environment :.at has been perceptually created [22; 40; 41]. Accordingly, the decision-maker’s cognitive equipment could play a vital role in determining what is seen by the organization’s environmental scanners. It has also teen hypothesized and empirically determined that the fidelity between the firm’s enacted environment and its objective one is critical for the organization’s ultimate effectiveness and survival [23; 27; 30; 3b; 37]. Downey and Slocum [7], Downey, Hellriegel and Slocum [6], Tosi, Aldag and Storey [38], and Hunsaker [17] all suggest that much of the environmental variability “seen by the organization’s decision-makers is cognitively caused by the individual’s personal characteristics, Consequently, it is possible that Type I or Type II environmental assessment errors are being made while simultaneously frustrating the organization’s needs for rationality. LITEPATURE REVIEW Business games, simulations, and experiential exercises nave often been used as laboratory settings for the study of individual and group decision-making practices [2; 3; 4; 8; 9; 11; 18; 28; 29; 35; 39]. This paper, though, is more concerned with the degree to which a players outcomes and behaviors in a dynamic and complex business policy type game are affected by personal, cognitive-processing characteristics. It has been reasoned that more cognitively complex individuals, who simultaneously possess an ability to integrate widely dispersed information cues and stimuli, would perform better in complex and dynamic decision- making situations [8; 9; 29; 35]. Lundberg [24] and Lundberg and Richards [25] specifically treated this general proposition in a policy-making business same. Various elements making up an individual’s cognitive style were drawn from students playing Greene and Sisson’s [14] “Top Operation Management Game.” Those elements were: A. Differentiation--the ability to discern a number of dimensions within a complex situation; measured by Bieri’s Cognitive Complexity- Simplicity Test [1]; B. Discrimination--the ability to interpret differences within a dimension; measured by Pettigrew’s Category Width Scale [33]; and C. Integration--the ability to tie together diverse elements into a whole; measured by Streufert and Schroder’s Impression Formation Test [35]. Lundberg’s more cognitively complex participants referred to a greater number of game dimensions in their strategy statements while those with greater integrative abilities expressed more integrated strategies. When behavioral or profit performance measures were considered, however, the results became quite equivocal. Those high in discrimination acted no differently regarding product prices or promotion expenditures than those without high discriminatory powers. While a significant relationship (p .012) was found between discrimination and decision quality, there were no relationships between differentiation and decision quality or integration and profit performance. Although the Lundberg study controlled for team social effects by using only single-member firms, and used psychological instruments of known validity and reliability, the lack of the expected relationships could lie within the particular simulation used in the study. The Top Operating Management Game is a very simplistic simulation and therefore might have been incapable of creating the proper laboratory situation demanded by Lundbert’s research questions. The simulation allows only four decisions per round, it is non-interactive, and it is didactic for an optimal “solution” is contained in the game’s program. Using Wolfe’s [44] measures of game complexity, the Greene and Sisson game would lie at the point of greatest simplicity and would probably manifest the same negative elements attendant with simple games of this type. As recently reviewed by Keys [20, p. 28], “this is a very simple business game…The strategy options are too few and the model sophistication too simple to provide much in the way of an analytical or strategic decision-making exercise.” It appears then that a more complex business game would provide the more appropriate environment for determining; the relationships between a player’s cognitive processing capabilities and the results obtained in a business game. METHODOLOGY Experiential Learning Enters the Eighties, Volume 7, 1980 170 Business college seniors (n=49) in a business policy course played ten simulated quarters of Jensen and Cherrington’s The Business Management Laboratory [19] from initially equal starting positions. This simulation has been found to be comprehensive, functionally unbiased, and motivating [42; 41; 44]; it would lie at the complex end of Wolfe’s [44] game complexity scale. Participation in the simulation and the results obtained regarding total earnings, ROI and ROE amounted to 55% of the course’s final grade. Solo firms were employed to eliminate group decision-making effects and to insure chat individual cognitive properties would not be diluted through continual action. Seven industries of equal size were ultimately created. The following measures were drawn before the beginning of play: A. Cognitive structure-- measured by an instrument created by Zajonc [45]; the instrument produces four measures of a respondent’s orientation as applied to a specifically-cued situation. In this case, the subjects were asked to describe the qualities of a job applicant based on his personal letter of introduction. The Zajonc instrument was preferred over the Bieri and Streufert and Schroder tests as these latter tests are basically clinical in nature. Zajonc’s four measures are: 1. Differentiation-- the number of attributes given to a cognitive structure; analogous to Lundberg’s Differentiation. 2. Complexity-- the number of subdivisions used to define the attributes in a cognitive structure; analogous to Lund- berg’s Discrimination. 3. Unity-- the degree to which the components of the cognitive structure depend on each other; part of Lundberg’s Integration. 4. Organization- the extent that one part or a cluster of parts dominates the entire cognitive structur; a remaining component of Lundberg’s Integration. B. Ambiguity Tolerance-- measured by McDonald’s AT-20 [26]; this instrument determines the degree to which players might flee the initially-ambiguous and psychologically threatening gaining situation. Those with low ambiguity tolerance would be expected to engage in fixation or attempt to clarify or re-structure their environment through the purchase of additional information. C. Category Width-- measured by Pettigrew’s CW scale [33]; this test measures how broadly an individual is tuned to the environment. Wide categorizers cast large data nets to increase their chances of success while simultaneously enveloping greater amounts of irrelevant or confusing material. Narrow categorizers cast small nets to minimize errors but simultaneously limit their successes. The participants also responded to an instrument (Internal reliability rkk = 0.65 designed to elicit certain beliefs and perceptions regarding the environment’s decision-making characteristics and strategic imperatives. This Likert-type instrument produced scores on the following: A. Clarity-- the degree of ambiguity that is felt to exist in the macro- and micro-economic system. B. Causality-- the degree of mechanistic determination felt to exist in the system. C. Timespan-- the timeframe or temporality with which the respondent deals comfortably. D. Fixation-- the degree to which single problem- solving elements are chosen to the exclusion of more comprehensive and multiplicative solution elements. As shown In Table 1, the perceptions measured by the instrument were often associated with the more basic cognitive processing variables previously obtained front the subjects. Accordingly, these environmental perceptions may be considered to be projections of the individual’s own cognitive and personality makeup rather than objectively- accurate appraisals of the environment’s objective qualities. Behavioral measures were collected in the form of the (1) average number of decisions made during the first two periods of play, (2) average number of decisions made during the last two periods of play, and (3) number of special information reports purchased. Quarterly and cumulative firm re8ults in the form of dollar earnings, and rates-of-return on owner’s equity and invested capital were also collected. Although the participants played in separate industries for grading purposes, all performance results were converted to standardized z-scores in this study to make possible the merging of industry-derived financial performances. RESULTS Environmental Perceptions Those individuals high in Differentiation described an environment that lacked clarity (r=.203); they also worked with shorter timespans (r=.233). Individuals possessing strong interdependencies in their cognitive structures believed their causal linkages were more tightly coupled (r=.267); they also used longer timespans (r=.415) while simultaneously being more fixated regarding their strategic decision elements (r=.271). High ambiguity tolerance was associated with low environmental clarity (r=.211), weak causality (r=.382), and the low degree of fixation employed (r=.264). Wide category width was associated with high clarity (r=.254), tight causal linkages (r=.357), long timespans (r=.249), and low fixation (r=.284). No associations were found for TABLE 1 CORRELATIONS BETWEEN CERTAIN COGNITIVE VARIABLES AND ENVIRONMENTAL PERCEPTIONS Cognitive Variables Clarity Causality Timespan Fixation Differentiation -.203a -.160 -.233 .103 Complexity -.009 .142 .080 .143 Unity -.012 .267 a .415b .271 a Organization .022 -.088 -.083 -.117 Ambiguity Tolerance -2.11 a .382 b .155 -.264 a Category Width .254a .357 b .249 a -.284 a a Significant p< .05 b Significant p< .01 Experiential Learning Enters the Eighties, Volume 7, 1980 171 the variables Complexity or Organization. Playing Behaviors While certain relationships were found between cognitive variables and environmental perceptions, no statistically significant relationships were found to exist between those same cognitive variables and player behaviors. It would be expected that those with low ambiguity tolerances would purchase more information so as to better structure their environment to make it less threatening and more tolerable. We would also expect those high in differentiation and category width to make a larger number of initial decisions in che simulation. Table 2 presents the Pearson correlation coefficients associated with the behaviors measured in this study. TABLE 2 PEARSON CORRELATIONS BETWEEN COGNITIVE VARIABLES AND GAME BEHAVIORS Cognitive Variables Initial # Decisions Ending # Decisions Special Reports Differentiation - .048 -.134 -.117 Complexity .018 -.041 -.171 Unity .148 .018 -.020 Organization .067 -.064 -.146 Ambiguity Tolerance .198 -.140 -.140 Category width .190 -.053 .035 TABLE 3 SECOND ORDER CORRELATIONS AFTER CONTROLLING FOR COGNITIVE VARIABLES Cognitive Variables T Beginning vs. End States Number of Decisions Environment Earnings Differentiation .090 -1.34 .250a Complexity .086 -.145 .253a Unity .087 -.113 .241a Organization Ambiguity .091 -.117 .263a Tolerance .068 -.102 .247a Category Width .082 -.131 .246a asignificant p (. .05 Given that decision-making is a dynamic process which moves one from one point to another, Table 3 presents the results of a further analysis of second order correlations to discover any possible cognitively-induced moderations on the decision-making process. Hotelling’s test [16] found that the correlation coefficients obtained after partialing the data were no different than those obtained before controlling for the cognitive variables examined here. Substantive Result The data in Table 4 demonstrate that no significant relationships were found between the variables studied and the players’ financial results. Additionally, respective multiple r-squares for earnings, ROE, and ROI were only .051, .061, and .055 which leaves approximately 95% of the variance in firm output to be explained by factors other than those investigated here. DISCUSSION This study has produced evidence that certain cognitive variables affect how the environment is perceived. These perceptions appear to be independent of the environment’s objective nature. As incorrect as these perceptions are, however, these errors had no association with the differential results obtained by the game players. As found elsewhere, other variables such as scholastic achievement, high aptitude, and rational deci3ion-making practices have a large impact on performance results. These findings are basically supportive of the programmed aspect of experiential learning theory-- that is, structure leads to behavior. If the simulation is (1) rich in learning experiences, (2) comprehensive and complete, and (3) conscientiously applied, favorable learning outcomes will result. TABLE 4 PEARSON CORRELATIONS BETWEEN COGNITIVE VARIABLES AND FIRN FINANCIAL RESULTS Cognitive Variables Earnings ROE ROI Differentiation -.044 -.152 .029 Complexity -.072 -.180 -.054 Unity .056 -.004 .040 Organization -.159 -.057 -.122 Ambiguity Tolerance .093 -.100 .066 Category width• .030 -.090 .013 This study’s findings should also bring solice to those who must bear the brunt of students complaints about the particular game they have been forced to play. It appears that those statements are basically anxiety verbalizations rather than true statements regarding the game’s objective reality. Game administrators should also find comfort in the fact that players were not handicapped by the particular cognitive equipment they possessed. Another Implication of this study is that actual behaviors and/or objective results are more valid evaluative criteria in a business game than are students’ statements of intent or rationalizations of results. Students’ perceptions at the least appear to be contaminated by individualistic cognitive Structures while an unbiased simulation is indifferent to these corruptions because it coldly rewards and reacts only to a player’s decisions. While outside the immediate scope of this study, our evidence regarding the discontinuities between the perceived environment and the objective one should render questionable a typical organizational research strategy. Researchers such as Dill [5], Duncan [10], Lawrence and Lorsch [23], Negandhi and Reimann [31], Osborn and Hune [32], and Schmidt and Cummings [341 Experiential Learning Enters the Eighties, Volume 7, 1980 172 have used manager’s environmental perceptions as either correct or necessary statement of a particular decision- making situation. In reality it appears that the decision- maker’s environmental perceptions (1) are strongly influenced by personal cognitive equipment, (2) have relatively little impact on the results obtained from the decision-making process, and (3) that structural elements are very important in determining the behaviors and results obtained by managers. SUMMARY Cognitive structure was found to be related to the environment perceived by game participants. These perceptions had no effect on how they played or the results they obtained. 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Table of Contents Volume 7, 1980 Symbol Recognition and Correlation for Evaluating Decision Making in Computer Aided Business Simulations Polanal: An Experiential Approach to Decision Support The Use of Time Contracts in Formal Education Indexing Simulation Model Response for Gaming Flexibility Moving Toward A Theory of the Use of Simulation Games and Experiential Exercises Use of Simulation Administration to Achieve Pedagogical Objectives Experiential Learning on the Job - A Business Internship Program Toward the Ultimate Experiential Exercise A Learning Through Managing Program Workshop Using Experiential Materials in Industry Training Sponsored Experiential Learning - An Opportunity Problems and Pitfalls of Externally Sponsored Field Research Projects Viewed form an Experiential Learning Perspective A Modular Approach to Experiential Learning: Classroom & Consulting Using Simulation & Experiential Learning In Industrial Settings Terminations: An Experiential Review Agenda Items -- Board of Supervisors' Meeting - Town of Jori The Objective-Setting Interview in MBO: An Experiential Approach The All-Star World Series Team Exercise: an Experiential Learning Exercise Dealing with Various Organizational Behavior Issues Progress Report on global, A Rich Multinational Gaming Environment Computer Simulation: A Tool to Teach Queuing Theory New Technology for Business Games Technological Frontiers in Computer Simulations for Business Education Simulating the Product Life Cycle on Interactive Terminals On Compensatory Demand Functions in Marketing Simulations The Use of Games at Different Levels in a Single Marketing Course to Increase Game Participation Sun Airlines: A Heterogeneous Consumer demand exercise Incorporating a Group Selection Test An Organization Development Approach to Teaching Organization Behavior CBID: Cognitive, Behavioral, and Interpersonal Development - A Skill Development/Social Learning Approach to Management Development Using a Live Case Via Video Tape A Town and gown Approach Development of Student Generated Cases Using Computerized Text Editing and Database Technology Interdisciplinary Approached to Problems in Utilizing Experiential Techniques To Use or Not To Use Experiential Techniques, That's is the Question Forming Participant Teams in Simulation Gaming The Problems of Motivating Students and Clients in Live-Case Projects Problems of Teaching Leadership Skills Through Experiential Techniques Conflict Style Measurement: Antecedent to Change - A Proposal for an Experiential Exercise Demonstration Fundamentals of Simulation for Newcomers An M.B.A. Orientation Simulation for Managing Time and the Areas of One's Life SimNet Workshop: The International Simulation Network Demonstrates Three New Business Games The Use of a Simulation Model in the Planning and Evaluation of Commercial Bank Operations Probability Assessment and Performance in Business Game Simulations WageSim: A Wage and Salary Administration Simulation Grading as a Teaching and Feedback Mechanism: Modifying Student's Self-Perceptions of Performance Can Business Games Effectively Teach Business Concepts? Development of Multiple Value Orientations in Conflict Resolution Behavior: An Experiential Teaching Paradigm in Labor-Management Relations Course Designing a Competency-Based Peer Assessment Scale for the Evaluation fo Teaching in Higher Education A Method for Evaluating Information for the Equipment Replacement Decision: An Application of Monte Carlo Simulation Simulation: A Method of Appraising Communication Networks in Managerial Decision Making An Evaluation of In-Class Student Involvement Evaluation of the SBI Program from an Experiential Viewpoint: Focus on the Student Differential Predictors of Academic Performance for White and Non-White Samples The Manager's Dilemma: An Unobtrusive Measure of the managerial Sex-Role Stereotype Are Computer Simulations Sexist? The Effect of Group Size on Attitudes Toward the Simulation Associations Between Individual Cognitive Processing Variables and Business Game Performance and Play Students' Perceptions on Managerial Functions After Exposure to Either the Case Method or a Simulation What Business Students Learn from Finance Simulations Attitude Toward Experiential Exercises, The Student-Teacher Relationship, Student Psychological Types, and Performance An Example of How to Design a Research-Based and Classroom-Effective Organizational behavior Exercise Some Issues in Game Design Untested Hypotheses: An Approach to Experiential Learning Evaluation of Simulation Games: A Critical Look at Past Efforts and Future Needs Is Self-Perception Predictable? - Some Laboratory Results An Exercise in Conflict-Handling Behavior The Relationship Between Group Size and the Learning Curve Effect in a Gaming Environment Learning About Organizational Management Through Organizational Management: Closing the Gap Strategies, Managerial Approaches, and Decision Making in a General Management Simulation A Comparison and Evaluation of Similar and Dissimilar Group Scenarios Generated Using Manual Simulation Games Weaknesses of Research Methods in Experiential and Simulation Studies