The Business Strategy Game: A Performance Review of the New Online Edition Developments in Business Simulation and Experiential Learning, Volume 33, 2006 THE BUSINESS STRATEGY GAME: A PERFORMANCE REVIEW OF THE NEW ONLINE EDITION Alan L. Patz University of Southern California alanpatz@mac.com H2: During a BSG exercise, leading teams will increase their lead throughout the competition. ABSTRACT Several previous studies have shown consistent performance results in total enterprise simulations. That is, teams that lead at the end of the exercise tend to have led from the beginning, and their lead grows as the decision series continues. The same pattern is observed in the new online version of the Business Strategy Game, but growing performance leads, although present, are not as pronounced. METHOD A BSG TE simulation was conducted in 6 sections of an undergraduate, capstone strategic management course over a period of 3 semesters. Each section formed an independent industry, and a total of 275 students participated. All students were seniors majoring in the various fields of business administration. After one class session devoted to the clarification of simulation rules, evaluation procedures, and decision- making mechanics, a two-year practice decision sequence was completed. Questions pertaining to the results of each session were answered and the evaluation procedure was restated. That is, students were reminded that the cumulative scores at the end of the simulation were the figures of merit. They were reminded also of the relevant TE simulation manual pages before both practice decisions and all subsequent real decisions. INTRODUCTION Past studies (Patz, 1999, 2000, 2001) have shown consistently that total enterprise (TE) simulations have a predictable performance pattern. That is, teams that lead at the end of the exercise have led from the beginning and their lead grows as the decision series continues. This is the case for MICROMATIC (Scott & Strickland, 1985), the Multinational Management Game (Edge, Keys & Remus, 1985), CORPORATION (Smith & Golden, 1989), and the Business Strategy Game (Thompson & Stappenbeck, 1997). The importance placed on ending cumulative scores rather than current period results emphasizes long- rather than short-term strategies. Moreover, attention was directed to three specific conditions. First, the actual ending period of the simulation would remain unknown. (Each period is a year in the BUSINESS STRATEGY GAME, and the length of the semester allowed for a maximum of ten periods of play.) Second, all teams were expected to end their management tenure with a going concern, not a firm stripped of long term potential in order to gain short-term ranking enhancements. Third, 20% of the semester grade for the course depended on ending cumulative score rankings. Similarly, using the Business Strategy Game (Thompson & Stappenbeck, 1999, 2001, 2002), most teams that are advised to attend to specific strategic variables do not do so (Patz, 2002, 2003, 2004, 2005). Research findings indicate that the learning of and attention to strategy ratings led to superior and large performance differences between winning, first place teams, and last place teams. This study focuses on the new online Business Strategy Game (Thompson & Stappenbeck, 2005) in order to determine whether or not these consistent results continue. There are specific instructions on what is important in the competition. So, does the convenience of online participation change performance patterns? Decisions were due at specific times, processed by the simulation model, and the results were available to participating teams immediately. This allowed seven days before the next set of decisions, required on a weekly basis for six consecutive decisions. HYPOTHESES Based upon the results summarized in the preceding paragraphs, the hypotheses for this study are obvious for the online Business Strategy Game (BSG): SIMULATION SCORING In all trials of this simulation, five scoring dimensions are important: earnings per share (EPS) return on equity (ROE), credit rating, image rating, and stock price. These H1: During a BSG exercise, leading teams at the end of the exercise will have led throughout the competition. 58 mailto:alanpatz@mac.com Developments in Business Simulation and Experiential Learning, Volume 33, 2006 The second one is the best in industry standard. In this case each team is compared with the industry leader on the same five scoring dimensions. With a weight of 20% on each dimension, the cumulative ratings of each team depends upon the leading firm in the industry. For example, if the cumulative EPS of the leading team is 10%, and the second place team’s is 8%, then the second place team’s score on that dimension is (8/10)(20) or 16. scores, however, are used in two different ways. (Refer to the user’s manual for the precise scoring procedures.) The first one is investor confidence. It depends upon how each team meets five goals of the board board of directors: 1. Grow earnings per share at least 7% annually through Year 15 and at least 5% annually thereafter. Finally, 50% of each the investor confidence and best in industry standard scores determined each team’s yearly and cumulative scores—beginning with year 11 after a ten-year history. 2. Maintain a return on average equity investment (ROE) of 15% or more annually. 3. Maintain a B+ or higher credit rating. 4. Achieve an image rating of 70 or higher. 5. Achieve stock price gains averaging about 7% annually through year 15 ad about 5% annually thereafter. Table 1 High-Medium-Low Main Effects Interaction Effects Industry F p F p 1 10.29 .008 .179 .997 2 15.85 .003 3.171 .005 3 13.63 .003 3.151 .005 4 27.93 .001 6.225 <.0001 5 6.86 .051 2.618 .025 6 72.55 <.0001 2.257 .042 Individual Industry Analyses of Variance Figure 1 - Industry 1 0 20 40 60 80 100 120 11 12 13 14 15 16 Year High Medium Low 59 Developments in Business Simulation and Experiential Learning, Volume 33, 2006 Figure 2 - Industry 2 0 20 40 60 80 100 120 11 12 13 14 15 16 Year High Medium Low 60 Figure 3 -Industry 3 10 Firms - 49 Participants 0 20 40 60 80 100 120 11 12 13 14 15 16 Year High Medium Low Developments in Business Simulation and Experiential Learning, Volume 33, 2006 Figure 4 - Industry 4 0 20 40 60 80 100 120 11 12 13 14 15 16 Year High Medium Low Figure 5 - Industry 5 0 20 40 60 80 100 120 11 12 13 14 15 16 Year High Medium Low 61 Developments in Business Simulation and Experiential Learning, Volume 33, 2006 Per (section through individu both hy except I Th and inc Th are sign period and low Ho overall (F = 1.7 2 and F As GAME strategy differen last pla matter. Figure 6 - Industry 6 0 20 40 60 80 100 120 11 12 13 14 15 16 Year High Medium Low RESULTS formance results for each of the six industries s) and all six combined are shown in Figures 1 7 and Tables 1 and 2. The statistics for each of the al six industries summarized in Table 1 indicate that potheses H1 and H2 are confirmed for each industry ndustry 1. at is, all leading teams at the end of the exercise led reased their lead throughout the competition. e main effects—high, medium, and low finishes— ificant as well as the interaction effects over the six competition. Differences between high, medium, finishes increased. wever, when combining all six industries for an analysis of variance, the interaction effect disappears , p = .1062) These results are summarized in Table igure 7. DISCUSSION already noted, previous BUSINESS STRATEGY studies indicated that the learning of and attention to ratings led to superior and large performance ces between winning, first place teams, and losing, ce ones. Other variables, such as price did not The ones that did—and formed the basis of an eight-point strategy rating system—were broad or focused product line, quality, service, brand image, low cost, market share leadership, superior value, and global or focused coverage. The new online version of this simulation has eleven competitive factors that drive market share. They are: 1. Wholesale selling price for branded footwear 2. S/Q or Styling/Quality rating 3. Product line breadth 4. Advertising expenditures 5. Mail-in rebates 6. Appeal of celebrity endorsements 7. Number of weeks it takes to deliver orders to retailers 8. Support offered to retailers in merchandising and promoting the company’s brand 9. Number of independent retail outlets carrying the company’s brand 10. Effectiveness of the company’s online sales effort on its Web site 11. Customer loyalty There are several facets to each one of these factors, and the two practice decisions are essential for obtaining participant familiarity with their complexity. Nevertheless, even with this added complexity, Table 2 and Figure 7 exhibit a different result from the ones obtained in the previous studies. All teams appear to learn, just at different rates. 62 Developments in Business Simulation and Experiential Learning, Volume 33, 2006 Source SS Between Ss 31017 Hi-Med-Lo 22088 Ss w Groups 8929 Within Ss 5134 Groups 975 Hi-Med-Lo x Groups 753 Groups x Ss w Groups 3405 Analysis of Varianc Figure 55 Firm 0 20 40 60 80 100 120 11 12 Two findings supporting this conclusion summarized in Table 2. The first one, already noted, is lack of an interaction effect. The differences between hi medium, and low performing teams remained constant o the six-period competition. The second is that even wit the high, medium, and low performing groups, the differ teams within each one learned at different rates (F = 4.3, .0017). In short, this suggests at least two areas for fut research. The first is concerned with how TE simulat complexity and learning interact. Secondly, what sort of simulation models will allow administrators to ad complexity during a competition? For example, incre complexity as the competing teams begin to demonstr comparable skills. Table 2 df MS F p 17 2 11044 18.6 <.0001 15 595 90 5 195 4.3 .0017 10 75 1.7 .1062 75 45 e for All Industries Combined 7 - All Industries s - 275 Participants 13 14 15 16 Year High Medium Low REFERENCES are the gh, ver hin ent p = Edge, Keys & Remus (1985) The Multinational Management Game. Plano, TX: Business Publications. Patz (1999) “Overall Dominance in Total Enterprise Simulation Performance.” Developments in Business Simulation and Experiential Learning, Volume Twenty-Six, 115-116. ure ion TE just ase ate Patz (2000) “One More Time: Overall Dominance in Total Enterprise Simulation. Developments in Business Simulation and Experiential Learning, Volume Twenty-Seven, 254-258. Patz (2001) “Total Enterprise Simulation Winners and Losers.” Developments in Business Simulation and Experiential Learning, Volume Twenty-Eight, 192-195. 63 Developments in Business Simulation and Experiential Learning, Volume 33, 2006 64 Patz (2002) “Strategy Learning in a Total Enterprise Simulation.” Developments in Business Simulation and Experiential Learning, Volume Twenty-Nine, 143-148. Patz (2003) “Revisiting Strategy Learning in a Total Enterprise Simulation.” Developments in Business Simulation and Experiential Learning, Volume Thirty, 213-219. Patz (2004) “Some Strategists Don’t Learn or Can’t Learn.” Developments in Business Simulation and Experiential Learning, Volume Thirty-One, 160-165. Patz (2005) “When Prophecy Fails: A Small Sample Preliminary Study.” Developments in Business Simulation and Experiential Learning, Volume Thirty- Two, 240-244. Scott & Strickland (1985) MICROMATIC. Palo Alto, CA: Houghton-Mifflin. Smith & Golden (1989) CORPORATION. Englewood Cliffs, NJ: Prentice-Hall. Thompson & Stappenbeck (1999) The Business Strategy Game. (6th ed.) New York: McGraw-Hill Irwin. Thompson & Stappenbeck (2001) The Business Strategy Game. (7th ed.) New York: McGraw-Hill Irwin. Thompson & Stappenbeck (2002) The Business Strategy Game. (8th ed.) New York: McGraw-Hill Irwin. Thompson & Stappenbeck (2005) The Business Strategy Game. (Online 8th ed.) New York: McGraw-Hill Irwin. Table of Contents Volume 33, 2006 Learning Assurance Using Business Simulations Applications To Executive Management Education Team Teaching In An Integrated Business Course Using Critical Problem Based Learning Factors In An Integrated Undergraduate Business Curriculum: A Business Course Success Personality Type And Strategic Planning Business Games As Strategic Management Laboratories The Relationship Between Students' Success On A Simulation Exercise And Their Perception Of Its Effectiveness As A PBL Problem Forecasting Accuracy And Learning: The Key To Measuring Simulation Performance The Business Strategy Game: A Performance Review Of The New Online Edition Using The Socratic Method And Bloom's Taxonomy Of The Cognitive Domain To Enhance Online Discussion, Critical Thinking, And Student Learning Using Negotiation Exercises To Promote Critical Thinking Skills Effective Leadership Experiences For Management Majors In A Futures Class The Role Of Learning Versus Performance Orientations When Reacting To Negative Outcomes In Simulation Games Is Pay Inversion Ethical? A Three-Part Exercise Simulations And Experiential Exercises - Do They Result In Learning? Have We Figured It Out Yet? Examining Program Management In Business Simulations: Student And Faculty Views Validating Business Simulations: Do Simulations Exhibit Natural Market Structures? Characterizing Business Games Used In Distance Education Utilizing Games In A Graduate Level Instructional Game Course Employment Interview Preparation: Assessing The Writing-To-Learn Approach Simulations - Bridging From Thwarted Innovation To Disruptive Technology Creating An Authentic Cultural Lens Using Case Dialogue Learning By Fire: Reflections Of A First Time Online Instructor An International Internship With A Service-Learning Focus Learner Participation In The Online Learning Experience: Help Or Hindrance? Any Given Sunday: Intervention In Pursuit Of Simulation Team Parity Beginning With The End: Creating An Experiential Exercise From Assessment Criteria Simulating Life Cycles: Life Span As The Measure Of Performance In Business Gaming Simulations It's Puzzling: Communications, Competition, And Cooperation Balanced Scorecard Implementation For Strategy Management: Variation Of Manager Opinion In Real And Simulated Companies Cases And Business Games: The Perfect Match! Three-Attribute Interrelationships For Industry-Level Demand Equations Using A Web-Based Module To Teach Information Literacy Decision Support System For Demand Forecasting In Business Games The Invalidity Of Profit=F(Market Share) PIMS Validation Of Marketing Games Online Market Test Laboratory With The MINSIM* Program The Gas Mileage Game - A Policy Simulation Delivered Cost And Differentiation Applied To Threshold 3rd Ed. The Effect Of Team-Leadership Modes On Team Performance: A Preliminary Study The Design And Use Of A Macroeconomics Simulation Using Maple Software: A Pilot Study The Instructor's Toolbox: A Meaning-Centered Framework For The Social Construction Of Experiential Learning Incorporating Strategic Product-Mix Decisions Into Simulation Games: Modeling The 'Profitable-Product Death Spiral' Group Composition And Groupthink In A Business Game A Direct Approach To Teaching Business Ethics A Decision Support System For Planning Sales, Production, And Plant Addition With Manager: A Computer Simulation Polish - American Entrepreneurial Business Cooperation Workshop Utilizing The Income/Outcome Simulation Student Leader Training Exercise Student Preference To Mode Of Learning In Hong Kong Experiential Learning For Technology-Based And Management Programme In Hong Kong: A China Study Tour A Price Game With Product Differentiation In The Classroom Discrete Event Modeling In A New Transportation Simulation Supply-Side Modeling In A Total Enterprise Simulation The Quality Game Towards A Massive Multiplayer Online Business Simulation Making The Connection: Improving Virtual Team Performance Through Behavioral Assessment Profiling And Behavioral Cues Individual Learning Producing A Learning Organization: 'Playing Dice With Polar Bears' Narratology and Ludology: Competing Paradigms or Complementary Theories in Simulation Framework For Evaluating Internet Research Using Children's Games To Illustrate Strategy Concepts: Is Less Better?