THE IMPLICATIONS OF COGNITIVE PROCESSING VARIABLES AND THE COMPLEX DECISION Developments in Business Simulation & Experiential Exercises, Volume 8, 1981 266 THE IMPLICATIONS OF COGNITIVE PROCESSING VARIABLES AND THE COMPLEX DECISION Alfred G. Edge, University of Hawaii ABSTRACT This study explored quality differences in complex decisions by variations of a number of cognitive processing variables. The complex problem was generated through the use of a management game with success measured in terms of game performance. The variables and performance are explained using a multivariate regression model. INTRODUCTI ON Individuals appear to differ in the amount and types of information to which they orient in a complex decision making situation. Factors which may be responsible for these differences are the relative complexity of cognitive structure--that is, the number and kind of constructs available and habitually utilized; the type or temperament of the individual; and the degree to which uncertainty is perceived as threatening. This study is designed to explore quality differences in complex decisions by variations in cognitive structure, type, tolerance of ambiguity and grade point averages among decision makers. The complex problems are generated through the use of a management game with success measured in terms of game performance. The cognitive processing variables and game performance are explained using a multivariate regression model. METHODOLOGY Cognitive Structure Differences in cognitive structure among decision- makers has been described in terms of their relative ability to differentiate among dimensions of a complex problem and to discriminate by interpreting differences within a dimension. These abilities were measured by Bieri’s Cognitive Complexity-Simplicity Test (1) and Pettigrew’s Category Width Scale (2). A. Cognitive Complexity-Simplicity Test (C-C)-- Cognitive complexity is defined by Bieri as the capacity to construe social behavior in a multidimensional way. A more cognitively complex person is assumed to have a more differentiated system of dimensions available than does a cognitively simple person. The Cognitive Complexity-Simplicity Test (C-C) is based on the contention that an individual with more dimensions in his cognitive structure will make more distinct interpretations than an individual with fewer dimensions. B. Category Width Scale (C-W)--Category width is defined as the ability to discriminate, or to recognize differences among elements classified along the same dimensions. Pettigrew’s C-W scale measures how broadly an individual is tuned to the environment. Wide categorizers cast large data nets while narrow categorizers cast small nets. Type Indicator Dimensions of individual style or types were measured using the Myers-Briggs type indicator (3). The type indicator or “temperament sorter test provides three pairs of preferences for the individual tested: extravert vs. introvert (E-I), intuitive vs. sensitive (I-S), and feeling vs. thinking (F-T). Tolerance of Ambiguity Budner (4) define intolerance of ambiguity as the tendency to perceive ambiguous situations as sources of threat, and tolerance as the tendency to perceive them as desirable. A high ambiguity tolerance is viewed as a willingness to accept a state of affairs capable of alternate interpretations, or of alternate outcomes. Low ambiguity tolerance is shown by the desire to have everything reduced to black and white. This construct was measured by McDonald’s AT-20 (5). Grade Point Average The subjects grade point average (GPA) as four year college students were drawn and used as an additional variable. The Complex Problem Relationships between cognitive structure, tolerance of ambiguity type indicators, and GPA were examined by testing individuals faced with complex decision- making tasks. The complex tasks were generated through use of a business game. Business College seniors (n=32) in a Business Policy class at the University of Hawaii played eight simulated quarters of Edge, Keys and Remus’ The Multinational Management Game (6) from initially equal starting positions. Each subject performed one of two complex tasks. These tasks were: Task No. I - Division Manager Each participant (three per team) was required to make periodic decisions regarding product price, promotion expenditures, production schedule, etc. for a specific division (Japan, West Germany or USA). Task No. 2 - Corporate President Each participant (one per team) was required to make periodic decisions regarding the financial well being and competitive position of the multinational corporation. Because of the game Structure there were significant differences in ROI for the three countries. The CEO's ROI was the average of the team ROI. These country and CEO mean ROI’s were as follows: Japan -15.58, USA 12.23, West Germany 92.13, and CE0=29.59. Developments in Business Simulation & Experiential Exercises, Volume 8, 1981 267 RESULTS For this analysis four regression models are presented and discussed. Model 1 is the full model including all tests, CPA, and the country variable represented by three indicator variables. Since there were definite country differences, this variable was included in all later models. Three tests were not significant in the full model and were dropped from the model one at a time using a backwards regression program. Model 2 shows some significance (at least at the .10 level) for each of the variables remaining in the model. Country 3 was not significant but was one of the indicator variables so remains in the model. The Beta values indicate the change in ROI (in standard deviations) for a standard deviation increase in the predictor variable. The AT-20 test shows the strongest relationship, followed by CPA, and then C-C and F-T. Model 3 and Model 4 differ In that only one of C-U or F-T were included in the model. The correlation between the two was r=. 39, the highest simple correlation among the predictor variables. When this is done each becomes significant at the .05 level There is very little difference in explanatory powers of Models 3 and 4. The results or the test and measures that proved significant are discussed Individually hereafter. The Tolerance of Ambiguity Test (AT-20) This test is an indication of a subjects willingness to accept a state of affairs capable of alternative interpretation or of alternative outcome. Model 2 indicates by the negative regression coefficient of -3.16 that the lower a person scored on the test the higher the expected ROI would be. Specifically for every one point of increase in ambiguity tolerance ROI would drop 3.16 percent. In order to assess the relative affect of the several variables on ROI, Beta values are given. The Beta coefficient is the standardized regression coefficient and does not depend on the unit of measurement of the independent variables. Beta represents the change (in standard deviation) of ROI for a 1 standard deviation increase in the independent variable. The highest Beta of all the tests and measures was the AT-20 varying from -.2 to -.26 depending on the model used. Grade Point Average It is interesting to observe that CPA is not as strong an indicator of success as the AT-20 test as evidenced by its Beta value of .18 compared to AT-20's -.23. The CPA does provide a positive indication (coefficient of 16.86) that the higher it is, the higher the ROI score will be. Cognitive Complexity-Simplicity Test The more cognitively complex person is assumed to have a more differentiated system of dimensions than does his counterpart. This measure reflects an inverse relationship between cognitive complexity and the score obtained which explains the negative regression coefficient of -.14 given in Model 2. Therefore the more cognitively complex an individual is, the higher the expected ROI score. Developments in Business Simulation & Experiential Exercises, Volume 8, 1981 268 Type Indicator Test The “type indicator or ‘temperament sorter” test provided three pairs of preferences for the individual tested: extravert vs. introvert, Sensitive vs. intuitive, and feeling vs. thinking. The results of the first two pairs provided insignificant information. The results of the later, the feeling vs. thinking produced significant results in Model 4 with a negative regression coefficient of –5.23 which indicates that the “thinking type” is more likely to score higher on ROI than his counterpart. SUMMARY Interpreting the models it can be observed that the person most likely to score high in ROI in the management game is one who likes his decisions reduced to black and white, is cognitively complex rather than simple, is a thinking rather than feeling type person and has a relatively high GPA. These findings seem entirely consistent considering that the complex problem faced by these subjects is to a high degree quantitative rather than qualitative, rational rather than emotion and logical rather than illogical. REFERENCES (1) Bieri, J., “Cognitive Complexity-Simplicity and Predictive Behavior,” Journal of Abnormal and Social Psychology, Vol 51, No. 1, 1955, pp~ 263-268. (2) Pettigrew, T.F., “The Measurement and Correlates of Category Width as a Cognitive Variable,” Journal of Personality, Vol. 26, No. 1, 1958, pp. 532-544. (3) Briggs, Myers, LBS, Myers-Briggs Type Indicator, (Education Testing Services, Princeton). (4) Budner, S., ‘Intolerance of ambiguity as a personality variable,” Journal of Personality, 1962, 30, pp. 29-50. (5) McDonald, A.P., Jr., “Revised Scale for Ambiguity Tolerance: Reliability and Validity,” Psychological Reports, Vol 26, 1970, pp. 791-798. (6) Edge, A., Keys, B., Remus, W., The Multinational Management Came,’ (Business Publications Inc., Dallas, Texas, 1980). Table of Contents Volume 8, 1981 The Promotion: Human Sexuality in Organization The Simulation of Chaos Leadership Development in a Simulated Urban/Suburban (U/S) Environment Tomed: A Computer Game Emphasizing Social Responsibility/or/why the Pop-Top Can? Integrated Brain Activity and the Manager's Job: Utilizing the Troika Model What does R2 Have to do with a Product Management Course? An Analysis of the Effects of Jungian Problem-Solving Style Dimensions on Marketing Decisions Bargaining Behavior in Personal Selling and Buying Exchanges Extending the Simulation Product Life Cycle A Generalized Algorithm for Designing and Developing Business Simulations Operationalizing a Test of a Model of the Use of Simulation Games and Experiential Exercises Pygmalion and Perception: An Experiential Exercise Behavioral Consequences of Reward Regarding Employee Absenteeism in an Industrial Setting: An Operant Conditioning Approach The Simlab Program: The Use of Experimental Simulation and Process Analysis for the Development of Management and Organizations Designs for Research on Simulation-Games, Cases, and Other Experiential Exercises The Role of Students in The Case Method Weaknesses in Research Design Critical Variables in Research on the Educational Value of Management Games Research Questions for Cases Research on the Learning Effectiveness of Business Simulation Games - A Review of the State of the Science The Effects of Valuation Techniques on Holding Cost During Inflationary Periods: A Simulation Exercise The Operations Simulation - A Study in Game Development Applying Guided Design to the Production/Operations Management Course: A Progress Report and Evaluation Terminal Data Entry and Retrieval Systems Simulations and Microprocessors Microcomputers and Related Technology for Simulation Gaming Microcomputers - A New Technology for Innovations in Business Simulations Microprocessor Controlled Interactive Video Simulation Business Game Design: From Theory to Practice The Success of a Computerized Simulation in Microeconomic Pedagogy The Test Preview Game: Applying the Game Show Format Providing a Real World View of the Personal Function: A Simulation Finding an Effective Means of Teaching Managerial Behavioral Skills: Two Different Experiential Teaching Methods Compared A Management Development Program Based on the Experiential Learning Model Participant Type Differences in Response to Experiential Methods: An Informal Look Preparing Student Groups to Participate in Experiential Group Projects: An Organizational Development Approach An Instrument for the Assessment of Learning Dimensions: A Progress Report of the Learning Dimension Scale (LDS) An Empirical Analysis Relating the Learning Style Inventory to Memory and Logical Ability Teaching Styles in Simulation Experiential Learning Versus Traditional Teaching Styles Student Perceptions of Effective Teaching Behaviors Problems in Evaluation of Experiential Learning in Management Education Students' Perceptions of Learning by Simulation A Relative Evaluation of Experiential and Simulation Learning in Terms of Perceptions of Effected Changes in Students Overview of Computer Based Business Games in Business Policy Classes Behavioral Decision Theory and Business Policy Giving Accounting Students Writing Experience as Job Preparation Getting to First Base with MBO: An exercise for Writing and Evaluating Objectives Dimensions of Conflict in Experiential Learning Consumer Alienation and Perceived Relevance of the Business Simulation Using the Self-Reference Criterion to Simulate Culture in Internationalized Business Course Experiential Learning in a Cross Cultural Setting- The Practice of Simulation Approach to Business Education in Japanese Universities Student' Perceptions of the Use of a Computerized Simulation in Teaching Management Information Systems Using the Case Study Approach to Develop a Microcomputer Bases, Fully Integrated, Data Base Driven, Management Information System The Case Study as a Tool for Organizational Change: Applying the Steel Ax to the Designers of Management Information Systems Toward a Theory of Teaching Business Policy A Case Study in the Use of Experiential Learning (A Management Game Simulation) to Enhance Student Understanding of Strategy Evaluation and Policy Formulation Suggestions for Integration of the Business Administration Core Publishing Opportunities and Requirements for Business Simulation and Experiential Learning Materials How do we Apply Experiential Learning Intercollegiate Case Competitions for M.B.A. Students: Initiation and Implementation Teaching Business Policy and Strategy Using the Incident Process The Learning Co-Op Approach to the Core Policy Course Meeting the Managerial Skill Shortage - Is Academia Up to It? An Empirical Analysis of Experiential Learning Reinforcement International Experiential Learning: Experience is the Best Teacher Encouraging Student Participation During International Academic Programs European Summer Study Program: Can you, Should you, What Does it Take? Travel Seminars in Europe: How can I Direct One? International Experiential Learning: Student Evaluation ABSEL: Empirical Findings on the State of the Association Sensitivity of Performance Scores in Business Simulations Improving the Learning of a Business Simulation Game by Increasing the Process Content Student Participation in Deciding Performance Criteria for Grading in an OB Course: An Exercise and a Case Study Markup for Profit: A Simulated Self-Administered Experience in Retail Pricing The Investment Decision Game: An Experiential Learning Approach to Stock Market Decisions Through Gaming CHIPS: A Marketing Channels management Game External Validation: An Experimental Approach to Determining the Worth of Simulation Games Teaching Performance Appraisal Skills: An Experiential Approach In Support of Experiential learning: Results of a Follow-Up Survey The Introductory Management Course: Taking Theory Application One Step Further Decision Efficiency and Effectiveness in a Business Simulation The Implications of Cognitive Processing Variables and the Complex Decision Simulating the Simulation for Enhanced Player Rationality Simulation/Experiential Learning Audit