An Exploratory Study of the Impact of a Simulation Exercise on the Managerial and Personality Traits and the Decision Making Styles of Marketing Students Page 132 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 ABSTRACT Using a pre-test/post-test experimental design, the present study explores how the experience of participating in a marketing simulation game impacts the managerial and personality traits and decision making styles of the simula- tion players. The present study sought to determine whether the simulation experience had an impact on selected mana- gerial and personality traits of the participants and their decision-making style. The study findings, involving a usa- ble sample of 325 students, showed that the simulation ex- perience brought about a number of changes in participant managerial and personality traits and decision making styles and that in many instances, the extent of these chang- es were related to performance level. In particular, the traits of competitiveness and Big 5 extraversion were found to have potential as stable predictors of simulation game performance. INTRODUCTION Business simulation games have been in use in North America since 1957 (Watson 1981). Since that time, the use of business simulation games has grown enormously. In 1961 it was estimated that more than 100 business simu- lations were in use in the U.S. alone and had been played by over 30,000 business executives and countless students (Kibbee, Craft and Nanus, 1961). The Guide to Simula- tions/Games for Education and Training (Horn and Cleaves, 1980) published in 1980 described 228 business simulation games then in use at universities, community colleges and by business firms for management training purposes. Various surveys of AACSB member schools undertaken from 1962 through 1998 reported that business simulation game usage at these universities grew from 71.1 percent of the responding universities in 1962 to 97.5 per- cent of the responding universities in 1998 (Faria, 1998). A 2004 e-mail survey sent to 14,497 university business professors, yielding 1,085 returns, reported that 47.4 per- cent of the survey respondents had used one or more busi- ness simulation games during their teaching careers (Faria and Wellington, 2004). As simulation game usage has grown since 1957, there has also been a growing body of research on simulation game usage. This body of past research includes examina- tions of: (1) the internal validity of business simulations; (2) the external validity of business games; (3) the relative merit of simulation games versus other teaching approach- es; (4) the learning, or skills training, benefits of simulation games; and (5) correlates of simulation performance; among other research areas. When used, simulation games generally utilize signifi- cant student time and contribute in a significant fashion to each student’s final grade. Across the 514 responding busi- ness professors to the Faria and Wellington (2004) e-mail survey who use business simulation games, on average, 23.8 percent of class time and 25.1 percent of the final course grade were accounted for by the simulation exercise. If simulation games are to merit this usage level and the amount of course time devoted to them, one would hope that the simulation game would have a positive impact on the game participants. To examine this issue, an explorato- ry study was undertaken. AN EXPLORATORY STUDY OF THE IMPACT OF A SIMULATION EXERCISE ON THE MANAGERIAL AND PERSONALITY TRAITS AND THE DECISION MAKING STYLES OF MARKETING STUDENTS William Wellington University of Windsor r87@uwindsor.ca David Hutchinson University of Windsor dhutch@uwindsor.ca A. J. Faria University of Windsor ad9@uwindsor.ca Page 133 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 STUDY BACKGROUND AND PURPOSE Despite simulation gaming’s widespread use and the considerable research undertaken on this teaching ap- proach, the full impact of simulation games on student managerial/personality traits and decision making skills is still largely unknown (Faria et al., 2009). Research into the skills training or learning aspects of business simulation games dates back almost to the earliest uses of these exercises. The reported types of learning brought about by the use of business simulation games in- cludes goal setting and information processing; organiza- tional behavior and personal interaction skills; sales fore- casting; entrepreneurial skills; financial analysis; basic eco- nomic concepts; inventory management; mathematical modeling; personnel skills such as hiring, firing, training, leading and motivating; creative skills; communications skills; data analysis; and formal planning and report prepa- ration skills among others. Faria (2001) provides a history and extensive list of references covering research on learn- ing and skills training through the use of business simula- tion games. Past simulation research has also examined the rela- tionship between student performance in simulation games and a wide range of participant and team variables. Among the variables examined have been numerous personality characteristics, locus of team control, achievement motiva- tion, previous academic performance, time pressure, ethnic origin of team members, gender, team size, previous busi- ness experience, team organizational structure, method of team formation, and grade weighting (see for example An- derson and Lawton, 1992; Brenenstuhl and Badgett, 1977; Butler and Parasuraman, 1977; Chisholm, Krishnakuman and Clay, 1980: Edge and Remus, 1984; Faria, 2001; Gen- try, 1980; Glomnes, 2004; Gosenpud, 1989; Gosenpud and Miesing, 1992; Hergert and Hergert, 1990; Hornaday, 2001; Hsu, 1984; Moorhead, Brenenstuhl and Catalanello, 1980; Newgren, Stair and Kuehn, 1980; Patz, 1990; Roder- ick, 1984; Walker, 1979; Washbush, 1992; Wheatley, An- thony and Maddox, 1988; Wellington and Faria, 1996; and Wolfe, Bowen and Roberts, 1989). As the opportunity was available, it was decided to undertake a large sample study of business simulation game participants and how certain personality and manage- rial traits might change as a result of simulation game par- ticipation. A number of sources, including the Bernie Keys Library, Simulation & Gaming, the Journal of Management & Decision Making, and the Journal of Behavioral Deci- sion Making, were examined to determine what personality Table 1 Personality and Managerial Traits Selected for Present Study Page 134 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 and managerial traits have been most often studied in the context of business simulation game participation. From our review of past simulation gaming research, the person- ality and managerial traits identified in Exhibit 1 were se- lected for inclusion in our study. A trait is defined by psychologists as a habitual pattern of behavior, thought and emotion (Kassin, 2003). Based on a review of psychological and decision-making literature, the traits to be covered in this study can be described as follows: ambiguity intolerance (a tendency to perceive or interpret information as vague, incomplete, uncertain, in- consistent, contradictory and unclear); locus of control (the extent to which individuals believe that they can control events that affect them); competitiveness (the degree to which an individual strives or contends against others); decision-making style (tendency to use either an analytical or intuitive mental strategy for processing information and making a decision); openness (a decision making approach that recognizes communal management rather than central- ized authority); self confidence (being self assured in one’s personal judgment and ability); extraversion (a tendency toward being gregarious, assertive and interested in seeking out external stimulus); indecisiveness (an inability to make a decision); basis of decision-making (relative roles played by affect and cognition in decision making); attitude to- ward simulation (being positive or negative toward the sim- ulation experience); decision tool usage (the range of man- agerial aids used in the decision-making process); risk averseness (the reluctance to take action when there is an uncertain outcome); optimism (possessing hopefulness and confidence about the future or the successful outcome of a decision); gaming interest (individuals self reported level of gaming interest); agreeableness (a tendency to be pleasant and accommodating); conscientiousness (being painstaking and careful); work drive (a person’s disposition to work hard); and neuroticism (a tendency to experience negative emotional states). METHODOLOGY The subjects for the research to be reported here were 460 students who completed a Principles of Marketing course from the same instructor in two different semesters. The simulation used in the class was Merlin: A Marketing Simulation (Anderson, Beveridge, Lawton and Scott, 2004). The Merlin participants played as single member companies divided into industries of seven companies each and participated in a seven period competition. The study design was a basic pre-test/post-test quasi- experiment where students were asked to complete self- report questionnaires at the beginning and at the end of the seven simulation decision periods. The pretest measures involved two different questionnaire administrations. The first pretest questionnaire occurred before the students were assigned to simulation companies and any simulation exer- cise explanations were undertaken. This questionnaire fo- cused on general managerial and personality trait measures which were composed of a priori scales which were drawn from the literature including: ambiguity intolerance (1 to 6 point Strongly Agree – Strongly Disagree Scale from Bud- ner, 1962), competitiveness (1 to 5 point Strongly Disagree – Strongly Agree Scale from Mowen, 2000), the Big 5 con- Table 2 Pre-test and Post-test Measurement Scale Reliabilities Page 135 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 sisting of agreeableness, conscientiousness, extraversion, neuroticism and openness (1 to 5 point Strongly Disagree – Strongly Agree Scales from John, Donahue and Kentle, 1991 and John, Naumann and Soto, 2008), indecisiveness (1 to 5 point Strongly Disagree – Strongly Agree Scale from Frost and Shows, 1993), locus of control (1 to 6 point Strongly Agree – Strongly Disagree Scale from Rotter, 1966 and Ferguson, 1993), risk averseness (1 to 6 point Strongly Agree – Strongly Disagree Scale from Burton, Lichtenstein, Netemeyer and Garretson, 1998 and Burton, 2000), optimism (1 to 5 point Strongly Disagree – Strongly Agree Scale from Sheier and Carver, 1985) and work drive (1 to 5 point Strongly Disagree – Strongly Agree Scale from Lounsbury, Sundstrom, Loveland & Gibson, 2003 and Lounsbury, Gibson & Hamrick, 2004). The second pretest questionnaire was administered after participants had been assigned to simulation companies and had re- ceived a lecture on the simulation exercise and its purpose. The second pretest questionnaire contained measures of decision making styles and some additional managerial and personality traits which were presented in the context of the Merlin simulation experience. The characteristics measured included student attitude towards the Merlin simulation (1 to 7 point Strongly Agree – Strongly Disagree Scale from Wellington, Hutchinson and Faria, 2010), decision making style (1 to 7 point Strongly Agree – Strongly Disagree Scale from Mantel and Kardes, 1999), self confidence (1 to 7 point Semantic differential Scale from Urbany, Bearden, Kaicker and Smith-de Borrero, 1997), interest in gaming (1 to 7 point Strongly Agree – Strongly Disagree Scale from Wellington, Hutchinson and Faria, 2010), decision making tool usage (1 to 7 point Strongly Agree – Strongly Disagree Scale from Wellington, Hutchinson and Faria, 2010), and the basis of decision making-affect or cognition (1 to 7 point semantic differential Scale from Shiv and Fedorikhin, 1999). At the conclusion of the simulation, both sets of ques- tions from the pretest questionnaires were presented for completion simultaneously. The alpha reliabilities for the pre-test and post-test multi-item scales are reported on in Table 2. Students were told that the nature of their responses would not affect their grade in the course. Only students who returned both the pre-competition and post- competition questionnaires with complete sets of attitude data were included in the data analysis. This resulted in a final usable sample of 325 students which represents a 70.7 percent response rate. In the Merlin simulation competition, performance is measured using a ranking based on an index of company sales, earnings, return on sales and forecast accuracy. The- se indexes were weighted 5%, 85%, 5% and 5%, respec- tively, resulting in each participant/company being ranked from first place to last place within their industry (e.g., from first to seventh position). Teams were then classified as high performers if they had a ranking from first to third position while participants whose performance rankings were fourth through seventh were classified as low per- formers. An assessment of the changes in traits and the relation- ship of these changes to performance was undertaken using a repeated measures MANOVA analysis for each of the managerial and personality traits measured as well as the decision style variables. This allowed for simultaneous examination of changes over time and the interaction of these changes with simulation game performance. In addi- tion, a repeated measures MANOVA analysis is well suited to this study design because the managerial and personality trait measures were essentially ordinal in nature. FINDINGS The overall findings are reported on in Tables 3 and 4 and indicate that the simulation game participant experi- ence was associated with a number of significant changes in managerial and personality traits and decision making style variables. The following variables exhibited statisti- cally significant results in the repeated measures MANO- VA indicating changes within subjects over time during the simulation experience:  Agreeableness decreased  Conscientiousness decreased  Openness decreased  Locus of control decreased  Optimism decreased  Self Confidence increased for good performers and decreased for poor performer;  Basis of decision moved towards being more rational for top performers with no change for poor performers  Indecisiveness increased The following variables had statistically significant results in the repeated measures MANOVA indicating dif- ferences in values owing to the performance group classifi- cation (high versus low):  Conscientiousness - high performers were more con- scientious than low performers  Extraversion - high performers were more extraverted than low performers  Neuroticism - high performers were less neurotic than low performers  Competitiveness - high performers were more compet- itive than low performers  Locus of control - high performers felt more in control than low performers  Optimism - high performers were more optimistic than low performers  Self confidence - high performers had more self confi- dence than low performers  Basis of decision making - high performers report be- Page 136 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 Variable Measure High Performance Group Score Low Performance Group Score Within subjects: Sig. of Time Within subjects: Sig. of Time x Rank Between Subjects: Sig. of Rank Ambiguity intolerance Pretest 3.75 3.75 .167 .011* .199 (Low value = low tolereance) Posttest 3.78 3.65 Attitude Towards Merlin Pretest 3.64 3.65 .547 .000* .000* (Low value = negative attitude) Posttest 4.18 3.18 Basis of Decision Making Pretest 5.08 4.85 .001* .000* .000* (Low value=more emotional) Posttest 5.52 4.82 Big 5-Agreeableness Pretest 3.83 3.81 .001* .460 .997 (Low value=Less agreeable) Posttest 3.73 3.75 Big 5- Conscientiousness Pretest 3.65 3.50 .015* .604 .016* (Low value=Less conscientious) Posttest 3.59 3.42 Big 5 Extraversion Pretest 3.38 3.18 .863 .105 .048* (Low value=Less extraverted) Posttest 3.34 3.23 Big 5 Neuroticism Pretest 3.42 3.29 .107 .047* .020* (Low value=More neurotic) Posttest 3.43 3.18 Big 5 Openness Pretest 3.62 3.58 .016* .842 .564 (Low value=Less open) Posttest 3.54 3.51 Competitiveness Pretest 3.73 3.50 .198 .768 .006* (Low value=Less competitive) Posttest 3.69 3.44 Decision Making Style Pretest 4.47 4.28 .229 .002* .000* (Low value=More Intuitive) Posttest 4.58 4.02 Gaming Interest Pretest 3.41 3.38 .479 .000* .139 (Low value=Less interest) Posttest 3.60 3.13 Indecisiveness Pretest 3.39 3.28 .027* .243 .029* (Low value=More indecisive) Posttest 3.36 3.19 Locus of Control Pretest 3.41 3.18 .033* .548 .000* (Low value=Less in control) Posttest 3.35 3.08 Optimism Pretest 3.57 3.43 .010* .769 .036* (Low value=Less Optimism) Posttest 3.51 3.36 Self Confidence Pretest 4.12 4.03 .000* .000* .000* (Low value=Less Confidence) Posttest 5.10 3.89 Table 3 Pre-test Versus Post-test Repeated Measures MANOVA Comparison Of Change in Managerial and Personality Traits or Decision Styles By Performance Group: Significant Results Page 137 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 ing less emotional in their decision making than low performers  Decision making style - high performers report being more analytical and less intuitive than low performers Indecisiveness - high performers report being less in- decisive than low performers  Attitude towards the simulation experience - high per- formers report more positive attitudes than low per- formers The repeated measures MANOVA analysis also re- vealed that a number of variables changed only for high performers or low performers or in different directions for high versus low performers. These variables include:  Basis of decision making - high performers became significantly more rational in their decision-making  Neuroticism - low performers became more neurotic  Decision making style - high performers became more analytical while poor performers became more intui- tive Attitude toward the simulation - high performers became more positive while low performers became more negative  Ambiguity intolerance – increased for high performers and decreased for poor performers  Gaming interest – increased for high performers and decreased for low performers Finally, according to the repeated measures MANVOA there were also a number of variables for which the simula- tion experience did not seem to have any impact. The per- sonality traits of risk averseness and work drive did not appear to have been altered by the experience nor were they associated with the level of performance. The decision style variable of decision tools usage was also not altered by the experience or associated with the level of perfor- mance. DISCUSSION AND CONCLUSIONS The research reported here sought to explore whether the experience of playing a marketing simulation game was associated with changes in selected managerial and person- ality traits or the decision making style of the game partici- pants. If simulation participation does change managerial traits, personality traits or decision style, it is possible that simulation participation changes decision-making skill as well. If simulation participation improves decision-making ability, we have complete justification for committing sig- nificant student and class time to this teaching approach. What have we learned from the present study? First, a summary of the findings from the repeated measures MANOVA results are shown in Table 5. The summary table indicates that the variables of basis of decision mak- ing (rational or emotional) and self confidence changed over time within subjects, they changed over time within subjects in relation to performance and the difference in performance levels between subjects was significant. This means these variables have potential as predictors of game performance as they were related to performance. Consci- entiousness also has potential as a pretest performance pre- dictor as it was related to performance level between sub- jects and while this trait changed over time within subjects, it did not seem to be interacting with performance as it changed over time within subjects. This pattern of findings was also evident for the traits of indecisiveness, locus of control and optimism. As such, all of these traits might be considered worthy as potential predictors of performance in a simulation game but are also traits that are transformed Variable Measure High Performance Group Score Low Performance Group Score Within subjects: Sig. of Time Within subjects: Sig. of Time x Rank Between Subjects: Sig. of Rank Decision Tools Usage Pretest 2.86 2.78 .094 .886 .644 (Low value=Less use of tools) Posttest 2.99 2.93 Risk Averseness Pretest 3.64 3.55 .561 .561 .483 (Low value=More Risk Averse) Posttest 3.59 3.55 Work Drive Pretest 3.22 3.11 .219 .193 .074 (Low value=Less Work Drive) Posttest 3.22 3.04 Table 4 Pre-test Versus Post-test Repeated Measures MANOVA Comparison Of Change In Managerial And Personality Traits or Decision Styles By Performance Group: Non-Significant Results Page 138 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 by the experience. In contrast, the variables of gaming interest, decision style, and attitude towards the simulation experience are merely correlates of performance as they changed over the course of simulation play in a positive direction for good simulation performers and in a negative direction for poor simulation performers. The experience of playing the simu- lation affected these traits but only in relation to how the player performed. Importantly, the traits of extraversion and competitive- ness revealed themselves as having the potential to serve as stable pretest predictors of high versus low simulation game performance. This conclusion is based on the finding that these traits did not change over time within subjects but exhibited a significant relationship with performance. The variables of usage of decision tools, risk averse- ness, and work drive were unaffected by either simulation participation or simulation performance. The implications from these findings are that the simu- lation gaming experience can produce managerial trait changes in marketing students. However, not all of the changes observed in this study were necessarily for the better given that many of the traits declined for poor per- formers. Specifically, poor performing simulation partici- pants became less agreeable, less conscientious, less extra- verted, more neurotic and less open. As well, the high per- formers did not seem to gain in these traits as a result of the simulation experience. Further research is called for to con- firm or refute the findings from this study and to explain the unexpected changes in traits discovered in this research. Finally, as a number of managerial traits appear to predict the simulation game performance of marketing students, this merits further research to determine how well and use- ful they might be as general predictors of managerial per- formance. REFERENCES Anderson, P. H., D. A. Beveridge, L. 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Simulation & Traits Within Subjects Between Subjects Potential Performance Predictor Change Good Performer Poor Performer Competitiveness Greater Lower Yes Big 5 Extraversion Higher Lower Yes Big 5 Neuroticism Less More Big 5 Agreeableness Decreased Big 5 Openness Decreased Big 5 Conscientiousness Decreased Higher Lower Yes Locus of control Decreased Higher Lower Yes Indecisiveness Increased Less More Yes Optimism Decreased Higher Lower Yes Basis of decision making (Rationale) Bidirectional More ra- tionale Yes Self confidence Bidirectional Increased Decreased Yes Ambiguity intolerance Increased Decision style (Analytical / Intuitive) Analytical Intuitive Attitude toward the simulation More positive Less Positive Gaming interest Increased Decreased Decision tool usage Risk averseness Work drive Table 5 Summary Table of Conclusions from the Study of Changes in Managerial and Personality Traits, and Decision Styles Page 139 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 Gaming, 23(3), 326-340. 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Simulation & Gaming, 27(1), 23-40. Wellington, W. J., Hutchinson, D., & Faria, A. J. (2009). Marketing Simulation Game Decision Making Experi- ence and its Impact on Indecisiveness among Introduc- tory Marketing Students. Developments in Business Simulation and Experiential Learning, 36, 223. Wellington, W. J., Hutchinson, D., & Faria, A. J. (2010). The Impact of Playing a Marketing Simulation Game on Perceived Decision Making Abiity among Introduc- tory Marketing Students. Developments in Business Simulations and Experiential Learning, Volume 37, 2010, 37, 23. Wolfe, J,. Bowen, D.D. and Roberts, C.R. (1989). Team Building Effects on Company Performance. Simulation & Games, 20, 388-408. Table of Contents Volume 39, 2012 Designing the Training Challenge Follow The Leader: Are we Teaching our Students to be Thinkers or Followers? Two Free-Rider-Accepting Methods of Organizing Groups for a Business Game Additional Benefit Through Competency Models Assessing Brand Portfolio Normative Consistency & Trends With The Normative Position of Brands & Trends Package Modeling the Impact of Marketing Mix on the Diffusion of Innovation in the Generalized Bass Model of Firm Demand Play it Forward! The Design and Development of a Forward Contract Simulation Positioning the Company: Increasing Profits in Social Networks Merger of Companies in Business Game Exercise Towards a Knowledge-Based Approach for Autonomouse Trading Agent An Exploratory Study of the Impact of a Simulation Exercise on the Managerial and Personality Traits and the Decision Making Styles of Marketing Students Should the Concept of Potential Customers be the Foundation of Demand Theory in Business Simulations? Teaching Sustainability Experientially Drawing Upon Experience and Research to Improve Future Communications Improving Assessments of Student Learning Outcomes (SLO) Over Time The Effect of Affective Domain Characteristics on Behavioral or Psychomotor Outcomes Gossip? No, Not Me! An Experiential Exercise Student Advisement Using Gantt Charts: An Experiential Exercise in Management Theory Practicing Teachers as Digital Game Creators: A Study of the Design Considerations Designing and Solving Crossword Puzzles: Examining Efficacy in a Classroom Exercise Difficult Times Call for Innovative Measures: Microfinance as Experiential Learning in Higher Education Catalysts, Client Services, and Community Change: Interdisciplinary Collaboration in a Nascent Microfinance Initiative Build A Business . . . In An Hour or Less: Getting Closer to Reality into the Classroom Smart Goals: How the Application of SMART Goals can contribute to achievement of Student Learning Outcomes The Use of Data in "Live" Cases to Encourage Systems Thinking and Integrative Analysis: An Exercise Linking Human Resource Programs and Financial Outcomes in Real Organizations Experiential Education as a Process of Changing Mental Frames by Inducing Insight Learning Process and Content Integration in an Experiential Learning Guided Internship Program Good-bye Discussion Thread: Creating a Community of Inquiry in an Online Master's Program Fiction as a Constructivist Tool for Learning Process Consultation in an Online Environment: Shaping the Context, Introducing the Dialogue Can Simulations Provide a Better Experience? A Capstone Application Modeling a Modest Proposal for Increasing the Efficiency of Academic Reserarch Dissemination Experience GEO: A Massively Multiplayer Game SysTeamsGames Three Games for Management Simulation SimVenture - A Start-Up Business Simulation Stellarbucks Simulation Developing Games Using Strategy Maps and Balanced Scorecards Strategy Dynamics Models - Powerful But Simple In-Class Games Simulating Scenarios for Financial Statement Analysis A Valuation Model of the Simulated Firm Writing the Land: An Interdisciplinary Experiential Approach On the Estimation of the Probability of Meeting Financial Commitments: A Behavioraial Finance Perspective Using Business Simulations